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Animal Sentience 2017.013: Kujala on Canine Emotions

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Canine emotions as seen through human social cognition

Miiamaaria V. Kujala

Department of Equine and Small Animal Medicine, University of Helsinki, Finland Department of Neuroscience and Biomedical Engineering, Aalto University, Finland

Abstract: It is not possible to demonstrate that dogs (Canis familiaris) feel emotions, but the same is true for all other species, including our own. The issue must therefore be approached indirectly, using premises similar to those used with humans. Recent methodological advances in canine research reveal what dogs experience and what they derive from the emotions perceptible in others. Dogs attend to social cues, they respond appropriately to the valence of human and dog facial expressions and vocalizations of emotion, and their limbic reward regions respond to the odor of their caretakers. They behave differently according to the emotional situation, show emotionally driven expectations, have affective disorders, and exhibit some subcomponents of empathy. The canine brain includes a relatively large prefrontal cortex, and like primates, dogs have a brain area specialized for face perception. Dogs have many degrees of emotion, but the full extent of dog emotions remains unknown. Humans are a socially minded species; we readily impute mind and emotion to others, even to vegetables or rocks. Hence the experimental results need to be analyzed carefully, so the emotional lives of dogs are accurately estimated. Keywords: Canis familiaris, domestic dog, emotion, psychology, social cognition, comparative cognition, neuroscience

Miiamaaria V. Kujala (Saarela) is a researcher in comparative cognition at the University of Helsinki, Faculty of Veterinary Medicine, Department of Equine and Small Animal Medicine, Helsinki, Finland; and Aalto University School of Science, Department of Neuroscienceand Biomedical Engineering, Espoo, Finland. A social cognitive neuroscientist, her current research interests are social cognition and emotional experience in dogs, non-invasive brain research across species, and human perception and interpretation of animals. http://orcid.org/0000-0002-1377-2187

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Call for Commentary: Animal Sentience publishes Open Peer Commentary on all accepted target articles. Target articles are peer-reviewed. Commentaries are editorially reviewed. There are submitted commentaries as well as invited commentaries. Commentaries appear as soon as they have been reviewed, revised and accepted. Target article authors may respond to their commentaries individually or in a joint response to multiple commentaries.

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1. Introduction

Dogs are our age-old domesticated companions. Darwin (1872) considered dogs as a comparative example in his work on emotional expression across species. Sharing the living environment with us, dogs have developed remarkable social skills in inter-species communication (for the original articles, see Hare et al. 1998, Soproni et al. 2001, Call et al. 2003, Miklósi et al. 2003, Kaminski et al. 2009). Thus, it is no surprise that we have inherent interest in understanding dog experience, behavior, and cognition. However, proving that someone experiences something is an impossibility because experiences are subjective (Nagel 1974). We can never know that another person experiences the same thing as us. There are always subtle differences in the underlying psychology and physiology, although the larger-scale responses may be similar within a species. How, then, can we know anything about the inner lives of other species such as our companion dogs?

In human emotion research, “emotion” and “feeling” are often separated because emotion can be targeted for objective experimental study through behavioral and neurophysiologic observations, whereas feeling is subjective: What the emotion feels like and how it is interpreted by the subject can only be inferred indirectly. We can detect the behavioral and physiological correlates of both my happiness and your happiness, but they can be felt and interpreted very differently by each of us.

In this work, the topic of canine emotions is approached using the framework of Anderson and Adolphs (2014). They argue that the capacity for emotion can exist across phylogeny, but emotions may consist of a different set of parallel behavioral, somatic, physiological, and cognitive responses in different species. We begin by considering the effect of the human viewpoint. Canine emotions are examined both behaviorally and biologically, with a brief review of the neural basis for primary emotions and the respective structures in the dog brain. The neural basis for secondary emotions is also reviewed, followed by a discussion of the current research on dogs. Long-term moods and comparative aspects are also considered. The ultimate purpose of this target article is to stimulate discussion about the nature and extent of dog emotions and the need for this new field of research, as well as to provide groundwork for the approach from various scientific disciplines.

One of the difficulties in considering emotional states in dogs is the inconsistency in terminology across studies. Avoiding anthropomorphic terms has left many canine affective phenomena without a standardized terminology. Different researchers have used different terms for the same phenomenon, or similar terms for separate phenomena. This review attempts to integrate results across studies and disciplines.

2. Human social cognition affects perception of dog emotional states

The existence of emotions in dogs and the perception of dog emotions by the human caretakers are separate issues. Everyday life presents many possibilities for humans to misinterpret the mind behind a dog’s behavior. For example, guardians may misinterpret the dog’s affective state in separation-related anxiety (see Mendl et al. 2010a). According to the three-factor theory of anthropomorphism (Epley et al. 2007), behavioral interpretations that are often valid with other humans are also easily attributed to non-human animals such as


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dogs. Thus, human, biologically tuned social perception is the starting point, as it filters our understanding of dog emotions.

People believe that animals such as dogs experience emotions (Morris et al. 2008, Morris et al. 2012, Walker et al. 2014). Humans are also quite consistent in classifying dogs’ emotional behavior in different contexts (Pongrácz et al. 2005, Tami & Gallagher 2009, Walker et al. 2010, Buckland et al. 2014, Faragó et al. 2014, Lakestani et al. 2014). Humans friendly dog behavior most easily recognize, whereas aggression and fear are more difficult to identify (Tami & Gallagher 2009, Wan et al. 2012, Mirkó et al. 2013, Lakestani et al. 2014) — especially by children (Meints et al. 2010, Lakestani et al. 2014). Prior experience of dog behaviour and training, rather than mere guardianship, enhances the interpretation of canine behaviour from the whole-body cues (Kujala et al. 2012, Wan et al. 2012).

Although emotions are visible throughout dog bodily cues, human attention is generally drawn to the faces of both humans (Johnson et al. 1991) and dogs (Quinn et al. 2009). Humans can classify a dog’s emotional valence (positivity-negativity) from the face irrespective of prior experience with dogs (Bloom & Friedman 2013, Schirmer et al. 2013). They can distinguish happiness (88% of the time) and anger/aggressiveness (70%) from a dog’s face, but discrimination of other discrete expressions is less reliable (fear: 45%, sadness: 37%, surprise: 20%, and disgust: 13%; Bloom & Friedman 2013).

Perception of others is affected by many factors in the human mind. The human social mind is equipped with a presupposition of intentionality (for reviews, Blythe et al. 1999, Scholl & Tremoulet 2000, Urquiza-Haas & Kotrschal 2015), from which anthropomorphism can arise. Attributing intentionality or other human characteristics to non-living things is strengthened by personal connection (Kiesler et al. 2006), and mental attribution is found in people’s descriptions of rocks (Kiesler & Kiesler 2005), computers (e.g., Nass et al. 1994), animations (Chaminade et al. 2007), robots (Gazzola et al. 2007, Imamura et al. 2015, Martini et al. 2016), or even vegetables (Vaes et al. 2016). Humans also project their views of themselves onto dogs much as they do with conspecifics, and their perceptions of dogs are similarly affected by stereotypes (Kwan et al. 2008). Thus, humans easily attribute mental and emotional states to companion dogs, and human interpretation of canine emotions is filtered by human psychological characteristics (Kujala et al. 2017).

Humans can also deny humanity in other humans (for reviews, Leyens et al. 2000, Haslam 2006). They consistently attribute more complex emotions to their in-group than out-group members (see Leyens et al. 2000). In a human brain imaging study, the observation of images of extreme out-group members (such as drug addicts or the homeless) failed to produce the medial prefrontal cortex activation connected with social cognition (Harris & Fiske 2006). Thus, the human mind is affected by various social factors, with the judgments sometimes representing more the judge’s own ideology than the reality. Likewise, when humans attempt to decipher canine emotions, dog guardians can underestimate their dogs’ aggressiveness (Mirkó et al. 2013).

Attributing minds to others is innate in humans, and the human brain appears remarkably flexible regarding the source of the other mind. Human empathy generalizes to other species (Ascione 1992, Paul 2000, Taylor & Signal 2005, Norring et al. 2014, Westbury Ingham et al. 2015, Kujala et al. 2017) and affects our interpretation of dog behavior (Meyer & Forkman 2014, Meyer et al. 2014). Empathy (Westbury Ingham et al. 2015) and the attribution of mental states (Harrison & Hall 2010) to non-human animals varies with their


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phylogenetic relatedness to humans. Mental attribution to both human and non-human species is connected to the temporoparietal junction associated with human theory-of-mind abilities (Cullen et al. 2014). Human brain responses to dogs can also be strikingly similar to responses to human conspecifics, whether observing dogs’ facial expressions (Spunt et al. 2016), pain (Franklin et al. 2013), or social interaction (Kujala et al. 2012). Human brains seek other minds and emotions, and dog emotional behaviour is filtered through the same machinery.

3. Neural support for the basic (primary) canine emotions

It is generally agreed that basic emotional states such as anger, happiness, and fear are evolutionarily adaptive (Ekman 1992, Izard 1992, Panksepp 1998, Plutchik 2001), and they have universal facial expression patterns in humans (Ekman & Friesen 1971). Basic emotional states are associated with neural structures within the limbic system and its connections to the neocortex in mammals (Damasio 1994; LeDoux 1996; Rolls 1999). Specific basic emotions are associated with specific chemical neurotransmitter balance in the brain (Panksepp 1998).

Figure 1. Key areas of the dog brain. (A) Some key subcortical areas shown on the axial magnetic resonance imaging slices (dog’s nose pointing upwards; top = anterior, bottom = posterior, left = left hemisphere, and right = right hemisphere) and (B) the cortical surface of the dog brain, with the sulci opened and the nomenclature overlaid below. The cortical surface is shown laterally from the left hemisphere (dog’s nose pointing left; left = anterior, right = posterior, top = dorsal, and bottom = ventral); the image has been magnified with standard digital image processing to show the gyri and sulci. Modified, under the terms of the Creative Commons Attribution License, from figures http://dx.doi.org/10.1371/journal.pone.0052140.g002 and http://dx.doi.org/10.1371/journal.pone.0052140.g003 (Datta et al. 2012).

http://dx.doi.org/10.1371/journal.pone.0052140.g002



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The domestic dog, as a member of mammalian order Carnivora and the Caninae

family, has a brain that includes all the major structures and connections supporting basic emotional functions (Jensen 2007, de Lahunta & Glass 2009, Evans & de Lahunta 2013). Dog brains include, bilaterally, the limbic system with the nucleus accumbens; the amygdala with its sensory and cortical connections; the cingulate cortex; and the sensory-motor cortices and the insula, deep within the pseudosylvian fissure (in humans, the Sylvian fissure occupies the topologically equivalent position). Dogs also have a relatively large prefrontal cortex that is not directly associated with motor functions (see Figure 1, Palazzi 2011, Datta et al. 2012, Evans & de Lahunta 2013).

The corresponding structures in humans have been studied extensively in recent decades regarding their roles in social and emotional function (for reviews, see e.g., Bush et al. 2000, Damasio et al. 2000, Adolphs 2002, Leppänen & Nelson 2009, Etkin et al. 2011, Schilbach et al. 2013). For dogs, the research is more scattered. Some dog brain function is also inferred from neurological experiments with cats (Felis catus) and the homologues between the brain anatomies of the two species. Many functions of the subcortical nuclei (e.g., the septal area or hypothalamus) and the finer neurophysiologic details, as well as visual cortical organization, are inferred from cat studies (King 1987, de Lahunta & Glass 2009, Sjaastad et al. 2010). Utilization of the methodology for studying human brain function has facilitated the study of dog brains. A recent study showed that dogs’ nucleus accumbens is activated by the odor of familiar humans, highlighting the possibilities of methodological advances in examining dog emotions (Berns et al. 2015).

Dog and human brains also have important differences. The association areas (brain areas not directly responsible for sensomotor functions) cover about 20% of the dog neocortex but 85% of the human neocortex (Evans & de Lahunta 2013). The rhinencephalon, devoted to processing olfactory signals, covers a relatively large area in dog brains (Evans & de Lahunta 2013). The existence of limbic and cortical structures in dogs is consistent with having the basic emotions, although dogs’ qualia – what it feels like to be a dog (Nagel 1974) — no doubt differ from our own.

4. Emotional reactivity and affective-behavioral disorders in dogs

Research on dog emotions has traditionally concentrated on the problems dog behavior causes for the human guardians, which is why we know more about dog fear and aggression. Dog emotionality has been studied to predict general emotional reactivity (Goddard & Beilharz 1986, Sforzini et al. 2009), aggression (Netto & Planta 1997, van den Berg et al. 2003, van der Borg et al. 2010), behavioral disorders (van der Borg et al. 1991), and differences among dog breeds (Scott & Fuller 1965) from puppies to adulthood. Dog aggressiveness is tested by presenting provocative stimuli, such as an unfamiliar barking dog (Netto & Planta 1997, van den Berg et al. 2003) or staring the dog in the eyes (Sforzini et al. 2009). Guardian questionnaires are also used (Netto & Planta 1997, Hsu & Serpell 2003, Duffy et al. 2008). Similarly, testing a dog’s fearfulness can include presenting a sudden loud noise, a novel object, a falling bag, or a gunshot (Melzack 1952, Beerda et al. 1998, King et al. 2003, Hydbring-Sandberg et al. 2004, Morrow et al. 2015).


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Both fearful and aggressive behaviors in dogs are associated with some physiological or autonomic responses. Stimuli eliciting fearful behavior in dogs increase their cortisol (Beerda et al. 1998, King et al. 2003, Hydbring-Sandberg et al. 2004, Dreschel & Granger 2005, Morrow et al. 2015) or progesterone levels (Hydbring-Sandberg et al. 2004), heart rates (King et al. 2003, Hydbring-Sandberg et al. 2004, Ogata et al. 2006), and body temperatures (Ogata et al. 2006). Aggressive behaviors are associated with reduced serotonergic function (Reisner et al. 1996).

The most common affective-behavioral clinically treated disorders in dogs are related to fearful or aggressive behavior and may be induced by separation anxiety, noise sensitivity (for review, Sherman & Mills 2008), and dominance/competitive aggression (see e.g., Beaver 1983, Wright & Nesselrote 1987, Cameron 1997, Reisner 1997, Haug 2008). Treatments for these conditions usually include behavior modification, often combined with neuropharmacological medication as in human psychiatric disorders (Overall 2000).

Taken together, aggression and fear are the most studied emotions in dogs, but research on other emotional states is scarce. An exception among the positive emotions is dog play behavior, which is well-documented (Bekoff 1974a, Bekoff 1974b, Bekoff 1995, Rooney et al. 2000, Horvath et al. 2008, Ward et al. 2008, Horowitz 2009a, Palagi et al. 2015).

5. Production and perception of facial expressions

Faces and facial expressions convey delicate and meaningful information about emotional states to conspecifics in humans (for reviews, Adolphs 2002, Calder & Young 2005, Hari & Kujala 2009, Leppänen & Nelson 2009) as well as in many non-human species (for reviews, Tate et al. 2006; Leopold & Rhodes 2010). Facial expressions of emotion in dogs were discussed by Darwin (1872); they characterized in great detail since the 1960s, noting similarities in the emotional expressions for aggression and happiness between dogs, other carnivores, and primates (Bolwig 1964, Fox 1970). A precise coding of human facial expressions based on the movement of facial muscles — a facial action coding system (FACS) — was developed in the 1970s (Ekman & Friesen 1978). The system has since been applied to many other primate species (Vick et al. 2007, Parr et al. 2010, Waller et al. 2012, Caeiro et al. 2013), horses (Equus caballus, Wathan et al. 2015), cats (http://www.catfacs.com/), and dogs (Waller et al. 2013). Deviating from the human-FACS, the non-human-FACS often includes the movement of ears.

Behavioral and brain responses during the perception of facial expressions have been studied in non-human primates and sheep for decades (see Tate et al. 2006). As a second non-primate species after sheep (Kendrick & Baldwin 1987), dogs have been shown to possess a distinguishable face-processing region in the temporal cortex, separating brain responses to faces from the responses to objects (Figure 2) (Dilks et al. 2015, Cuaya et al. 2016). The response profiles are roughly comparable with those of the human fusiform face area (Kanwisher et al. 1997), although the cortical region seems to be more variable in dogs. In humans, face processing continues from the fusiform to the inferotemporal cortex and the superior temporal sulcus, with the extraction of identity- and emotion-specific information (for review, Haxby et al. 2000).

http://www.catfacs.com/


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Figure 2. Stronger brain responses from dogs for faces versus objects. Images show the focus of brain activation during non-invasive functional magnetic resonance imaging in seven dogs for faces versus objects with contrast, overlaid on a digitally produced glass brain to reveal foci located within the sulci. (A) Lateral view from left hemisphere, (B) rostral view from front, and (C) lateral view from right hemisphere. A = anterior, P = posterior, S = superior (or dorsal), I = inferior (and ventral), L = left, and R = right. Modified, under the terms of the Creative Commons Attribution License, from figure http://dx.doi.org/10.1371/journal.pone.0149431.g005 (Cuaya et al. 2016).

While direct information on dogs’ brain processing of emotional expressions is missing, a growing body of behavioral and eye-tracking research supports the ability of dogs to distinguish negative and positive facial expressions in both humans and dogs, and to respond appropriately according to the valence of faces (Nagasawa et al. 2011, Racca et al. 2012, Müller et al. 2015, Barber et al. 2016, Somppi et al. 2016) (Figure 3).

Figure 3. Gaze fixations (circles) and scanning paths (lines between the circles) of two dogs (shown in light and dark green) for facial expressions of dogs and humans. White circles represent the targets of the first fixations; dogs tend to gaze first into the eyes of both humans and dogs. Figure from http://dx.doi.org/10.1371/journal.pone.0149431.g005 (Somppi et al. 2016), reprinted under the terms of the Creative Commons Attribution License.




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Dogs associate emotional vocalizations of both humans and dogs with the corresponding facial expressions, showing multisensory processing of emotional expressions (Albuquerque et al. 2016). Like human infants, dogs use human emotional expressions for social referencing, as a source of approach/avoid information for novel objects (Merola et al. 2012b, Merola et al. 2012a, Buttelmann & Tomasello 2013, Merola et al. 2014, Turcsán et al. 2015). Furthermore, they appear to generalize the valence information of facial expressions across human individuals (Müller et al. 2015, Somppi et al. 2016) rather than responding only to guardians’ expressions — in contrast to cats, who respond mainly to the valence of their guardians’ facial expressions (Galvan & Vonk 2016).

Human cross-cultural studies could provide some useful clues for studying emotions in dogs. The basic emotions are remarkably similar around the world (Ekman & Friesen 1971). Facial expressions and their recognition, situations provoking emotions, and the organization of emotions on the valence-arousal dimensions are consistent across cultures (Shaver et al. 1992). However, the perception of emotional intensity differs across cultures (Ekman et al. 1987), and the decoding and encoding of emotion in the cultural in-group appears more accurate (for meta-analysis, Elfenbein & Ambady 2002). Similarly to the cultural differences in humans, differences in breeds or environment may affect the expression or perception of emotion in dogs (for review, Mehrkam & Wynne 2014).

It appears unquestionable that dogs can both produce and process emotions through facial expression, but the question is to what extent? One remaining question concerns what part of recognizing human facial expressions by dogs is innate and what is learned through association and experience. Also, the research addressed mainly the positive-negative valence information of faces rather than the more diverse, discrete expressions of emotion (e.g., happiness, sadness, surprise, fear, disgust, anger: Ekman & Friesen 1971), so information on dogs’ ability to discriminate or respond to discrete expressions of emotion is lacking. Are there universal facial expressions of emotion in dogs as there are in humans (Ekman & Friesen 1971) — and if so, what are they?

6. Fundamental basis for secondary (social) emotions

Secondary emotions — generated through the interpretation of social situations and requiring some sense of another’s mind — are less likely than basic (primary) emotions to be attributed to dogs by people, but 22 to 94% of people believe that dogs do have secondary emotions such as shame or guilt (Morris et al. 2008, Morris et al. 2012). As adult humans, we effortlessly attribute secondary emotions to other people. Without knowledge of the differences among minds across species, we can just as easily attribute the emotions to non-humans, including dogs. However, dogs may be incapable of experiencing the more complex social emotions, or their experiences may be qualitatively very different from ours. The reason the dog is human’s best friend may be the apparently missing canine capacity for secondary emotions such as contempt or Schadenfreude (the joy in others’ misfortune).

The secondary emotions seem to require some sense of the self (Leary 2003). Having self-awareness complicates the emotional experience in many ways — allowing imagined experiences with no basis in reality. Leary (2003) clarifies the effect of self on emotional experience through five points: “Specifically, having a self permits people to (1) evoke emotions in themselves by imaging self-relevant events, (2) react emotionally to abstract and


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symbolic images of themselves in their own minds, (3) consciously contemplate the cause of their emotions, (4) experience emotions by thinking about how they are perceived by other people, and (5) deliberately regulate their emotional experience” (p. 775). As he also points out, animals do not need a concept of self in order to have a basic emotion. Humans often attempt to suppress self-referential emotional thought in various ways (e.g., by drinking alcohol) since such thoughts can cause increasing distress. In children, self-awareness appears to arise roughly concurrently with the ability to take another’s perspective (Lempers et al. 1977); early studies suggest similar co-occurrences in other species (Gallup & Suarez 1986). To date, the level of dogs’ self-awareness is not known — for example, they have not passed Gallup’s (1986) mirror self-recognition test, but they do spend less time inspecting their own urine markings than those of others (Bekoff 2001).

The brain regions responsible for secondary emotions include a network comprising the medial orbitofrontal cortex, the temporal pole, and the superior temporal sulcus in humans (Moll et al. 2002, Burnett & Blakemore 2009). In principle, homologues of these regions may also be present in the brains of dogs, in the temporal and frontal association areas. Homologues in cortices are difficult to verify because the brain functions of these cortical regions cannot be localized anatomically, thus functional brain imaging is needed. Nevertheless, the cortical association areas, associated with secondary emotions in humans, are larger in humans than in dogs (20% of the cortex in dogs and 85% in humans; Evans & de Lahunta 2013).

The brain areas responding to secondary emotions are also strongly connected to areas of the limbic system, and the connections alter the level of cognitive evaluation of the emotional states (Berridge 2003). The connections between the cortex and the limbic system are so different in magnitude between humans and other mammals that cortical lesions having minimal effects on other mammals may cause drastic changes in human function (Berridge 2003). For example, a cat without a cortex may still move and behave like a cat, whereas a human without a cortex, if alive, lies in a hospital bed completely unresponsive. Thus, it is possible that the re-representation of emotions that human encephalization produces with the interconnections to the limbic system may be the source of secondary emotions. In other words, as humans we have the potential to be angry, realize that we are angry, ponder the causes of our anger, notice that the anger momentarily affects our ability to work or cooperate, try to suppress our anger, think about how our anger appears to our companions and how it affects our relationships, and try to modify the source of the anger. If the cerebral-limbic interconnections are the source of this emotional re-representational ability in humans, the overall capacity of dogs for secondary emotions, with less encephalization than humans, may be dramatically different from ours.

7. Do dogs display guilt — or merely appeasement?

Guilt is an example of a secondary emotion often attributed to dogs, but according to current research, it fits the dog mind poorly. Horowitz (2009b) first recorded canine behavior and gestural cues in a situation where dogs could disobey the guardian’s command and eat a forbidden treat. By manipulating the guardian’s belief about what happened in the situation, she showed that dogs’ gestures were not different whether or not they obeyed. Instead, the gestures commonly associated with dog “guilt” — for example, avoiding eye contact, wagging


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the tail low and quickly, holding one’s ears or head down — were evident when the guardians scolded their dogs, regardless of the dog’s actual behavior in the experiment. This strongly suggested that the dogs responded to the guardian’s behavior with submissive gestures interpreted by dog guardians as “guilt,” rather than displaying remorse for a misdeed with the “guilty” gestures (Horowitz 2009b). After a dog has learned the association between a certain unwanted behavior (e.g., stealing food) and the guardian’s punishment later, they may display the submissive behavior in a similar situation even before the guardian’s scolding (Horowitz 2009b). This does not require remorse or an “understanding” of violating a norm, but a simple learned association between two successive situations. When dogs display “guilt” behavior, guardians are likely to scold their dog less, which suggests that “guilt” behavior may function as learned appeasement (Hecht et al. 2012).

In a recent work, pet dogs’ heart rates were measured during the “forbidden treat” experiment, and dogs who took the forbidden treat had a higher heart rate than dogs who did not (Torres-Pereira & Broom 2014). This suggests a learned association between eating the treat and a possible consequent scolding. To ensure that the rise in heart rate was not merely a function of sympathetic nervous system activation in the active condition (eating a forbidden treat), a similar result should be obtained with dogs eating a treat that they were allowed. Alternatively, as both positive and negative stress can increase sympathetic nervous system activation, the treat-stealing dogs may just be more excited by the treat. Nevertheless, even representation of the causality of the action plus an anticipatory response to the consequence does not require a sense of guilt.

8. Fairness or unequal treatment of conspecifics

Another example of dog affective representations closer to the secondary emotions is

inequity aversion (Figure 4). In studies of primate social cooperation, unequal treatment of individuals is related to negative responses (for review, de Waal & Suchak 2010). In humans, the feeling of inequality is characterized by a negative response to the violation of fairness (for reviews, see Fehr & Rockenbach 2004, Fehr & Camerer 2007). A degree of inequity aversion was reported in capuchin monkeys (Cebus apella, Brosnan & De Waal 2003) and chimpanzees (Pan troglodytes, Brosnan et al. 2005), and a few studies have investigated the phenomenon in dogs (Range et al. 2009, Horowitz 2012, Range et al. 2012, Brucks et al. 2016). In a situation where a conspecific partner was rewarded for a task and canine subjects were not, they refused to perform the task or hesitated longer (Range et al. 2009, Brucks et al. 2016).


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Figure 4. Testing dog inequity aversion; both dogs are asked to give the paw in turn. Figure from http://dx.doi.org/10.1371/journal.pone.0153799.g001 (Brucks et al. 2016), reprinted under the terms of the Creative Commons Attribution License.

The phenomenon does not qualify as a simple extinction of a learned behavior because the canine subjects refused to obey earlier after witnessing a partner receive a reward for obeying, compared to being alone (Range et al. 2009, Range et al. 2012, Brucks et al. 2016). They also tended to refuse earlier in the unequal situation than in the situation where neither dog received rewards (Range et al. 2009, Range et al. 2012). Dogs also shared their food and interacted less with partners after unequal situations, showing that the negative experience of unequal treatment, or not being rewarded for one’s efforts, diminishes subsequent cooperation and tolerance of company (Brucks et al. 2016).

Humans and some other primates can resist unequal treatment (i.e., refuse to cooperate) either when they gain less than the partner or when they gain more (Brosnan et al. 2010, Blake & McAuliffe 2011). In contrast, dogs do not resist the inequity when they are more rewarded than their companions (Horowitz 2012).

Taken together, dogs are sensitive to conspecific company in the inequity aversion test. They refuse earlier to perform the task in situations when they receive fewer rewards than their partner, compared to when they are alone, but unlike some primates, they do not resist gaining more than the partner. Although dogs behave differently toward the companion and experimenter after unequal and equal conditions (Brucks et al. 2016), this could also reflect the negative overall mood created by not being rewarded. The data to date suggest that dogs have the capacity for inequity aversion, but future work is needed with more conditions such as varying food quantities and the direction of the inequality, learning through a social model, expectation violation, negative situations affecting subsequent behavior, and individual factors such as personality or breed.



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9. Resource competition as a precursor of jealousy?

Another case of possible secondary emotions in dogs is jealousy. Dog guardians report behaviors related to jealousy as often as behaviors related to the basic emotion of anger (Morris et al. 2008). However, this also illustrates anthropomorphic misunderstandings: Couples may report that “On the rare occasion that we have a cuddle he’ll start barking and whining.” But hugging is not in dogs’ natural behavior repertoire, so people cuddling can appear to dogs as a threat between pack members, to which they react by whining or trying to separate the “fighting pack members.” In humans, jealousy usually concerns romantic relationships and extends to imaginary situations of a rival threatening a significant relationship (Leary 2003). A precursor of jealousy in dogs may exist in a situation of defending a previously gained resource such as a human companion.

In a recent behavioral study where dog guardians ignored their dogs and attended to realistic toy dogs or other objects, the dogs exhibited significantly more behaviors such as going between the guardian and the target of their attention, or pushing/touching the guardian or the target, when the target was a realistic toy dog rather than an object (Harris & Prouvost 2014). Similarly, human infants showed more negative responses when a mother’s attention was directed towards a life-like doll than an object like a book (Hart et al. 1998, Hart & Carrington 2002).

Although the current data are consistent with the possibility of situation-based resource defense being a precursor of jealousy, the evidence for envy or jealousy in dogs is inconclusive and more rigorous research is required. Unfortunately, the behaviors associated with dog jealousy can also appear in dogs as replacement behaviors, when the dog is confused as to how to react.

10. Divisions of empathy

The neuroscientific study of human empathy exploded in the beginning of the 2000s (see Singer et al. 2004, Jackson et al. 2005, Gazzola et al. 2006, Saarela et al. 2007), revealing that the emotional aspect of empathy is processed in the limbic system, insula, and anterior cingulate cortex. Similar patterns may be also possible in the canine brain. Although simple forms of non-human empathy had been studied in previous decades (Church 1959, Rice & Gainer 1962, Masserman et al. 1964, Watanabe & Ono 1986), interest in animal and human empathy grew with the study of non-human primates (for reviews, Preston & de Waal 2002, de Waal & Ferrari 2010), and also extended to non-primates, including rats (Rattus norvegicus, Ben-Ami Bartal et al. 2011).

In humans, empathy has three components: emotional empathy, cognitive empathy, and the separation of the self from the other (see Decety & Jackson 2004). Emotional empathy can be further divided into emotional contagion/self-distress and empathic concern: emotional contagion originates from automatically triggered responses to others’ emotions, and empathic concern includes expressing a worry about others’ wellbeing (Davis 1980). Emotional contagion is important for compassion, but at high levels it may lead to anxiety and passivity or aggression and antisociality rather than helping behavior (Roberts & Strayer 1996). Cognitive empathy involves a theory-of-mind-like meta-representation of another’s emotional state. To highlight the difference between emotional and cognitive empathy, the


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latter can be fully preserved in humans diagnosed with psychopathic tendencies, whereas this population shows much less emotional contagion and empathic concern (Blair 2005), possibly due to altered limbic function (Birbaumer et al. 2005).

11. From emotional contagion to prosocial behavior in dogs

Although long recognized by some (see e.g., Bekoff 2007), the capability of dogs to empathize has been receiving more scientific attention recently. Anecdotal reports of dogs apparently consoling conspecifics or humans are abundant, but the topic has been thoroughly examined only in a few experiments.

Most research on dogs’ empathy-related behavior toward conspecifics concerns behavior that resembles consolation, that is, reconciliation or post-conflict affiliation. In cooperative species, aggression toward conspecifics may be costly for the whole group. An important mechanism for managing the effects of aggression is post-conflict affiliative behavior between the former opponents (reconciliation), sometimes through mediation by a third party (de Waal & van Roosmalen 1979). Both reconciliation behavior and third-party post-conflict affiliation are present in group-living dogs and wolves in heightened greeting; sitting or lying down together; and sniffing, playing, or licking the victim of aggression (Cools et al. 2007, Palagi & Cordoni 2009, Cordoni & Palagi 2015). Emotional contagion across dogs was recently studied by playing familiar and unfamiliar conspecific whines to dogs and examining their behavior during the playback and reunion with the familiar dogs (Quervel-Chaumette et al. 2016). When exposed to dog whines (recorded when the dog was left alone), the canine subjects were more alert and exhibited more stress-related behaviors compared with exposure to acoustically matched control sounds (Quervel-Chaumette et al. 2016). Additionally, exposure to familiar dog whines triggered more comfort-offering behaviors toward the partner dogs in reunion, resembling post-conflict affiliative behavior observed in natural groups (Cools et al. 2007, Palagi & Cordoni 2009, Cordoni & Palagi 2015). Post-conflict affiliation highlights the possibility of emotional contagion or empathic concern in dogs, although its mechanisms are unknown.

Across-species affiliative interaction between a dog and their caretaker (e.g., guardian petting the dog) can cause hormonal and physiological synchronization, lowering cortisol levels and increasing oxytocin and dopamine levels in both species (Odendaal & Meintjes 2003, Miller et al. 2009, Nagasawa et al. 2009, Handlin et al. 2011, Nagasawa et al. 2015). This across-species emotional synchronization suggests a possible physiological mechanism for the emotional contagion both in humans and dogs. In a similar example related to the stress response, cortisol levels in both humans and dogs increased significantly after listening to a crying human infant compared with a babbling infant or white noise (Yong & Ruffman 2014).

Dogs may also act prosocially, pulling a rope that delivers a partner dog a reward even when the puller dogs themselves are not rewarded, but only if the recipient dog is familiar (Quervel-Chaumette et al. 2015). Similar helping behavior from dogs to humans was previously found (for review, Bräuer 2015). These results show the possibility of dogs’ altruistic behavior. More studies on the extent of this kind of behavior. Overall, the studies show emotional contagion from humans across species to dogs, as well as from dogs to their conspecifics, although the underlying mechanisms of contagion are currently not clear.


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12. Yawning contagiousness in dogs: Empathy or social relaxation?

Contagious yawning is not used as a measure of empathy in human psychology, since well-validated questionnaires (e.g., Mehrabian & Epstein 1972, Davis 1980, Lawrence et al. 2004, Dadds et al. 2008) can be combined with either behavioral studies (especially in children, see e.g., Eisenberg & Miller 1987, Eisenberg & Fabes 1990, Roberts & Strayer 1996, Eisenberg et al. 1999) or brain imaging studies (for reviews, Decety & Jackson 2004, Bernhardt & Singer 2012) to show a correspondence between self-reported reactivity and behavioral or physiological changes. Early studies reported diminished contagiousness of yawning in children with Autism Spectrum Disorders (ASD) (Senju et al. 2007, Giganti & Esposito Ziello 2009, Helt et al. 2010), which prompted speculation regarding the possible relation of contagious yawning to empathy. Newer studies have reported the capacity for contagious yawning in children with ASD (Senju et al. 2009, Usui et al. 2013) and the independence of yawning contagiousness from empathy (Bartholomew & Cirulli 2014). However, since the inaugural study showing yawn contagion across species from humans to dogs (Joly-Mascheroni et al. 2008), a range of studies has explored the possible connection of contagious yawning and empathy in canines (O'Hara & Reeve 2011, Silva et al. 2012, Madsen & Persson 2013, Romero et al. 2013, Silva et al. 2013, Buttner & Strasser 2014, Romero et al. 2014).

Yawning is a somewhat problematic measure in dogs because the canine yawn serves as a tension-releasing stress response (see e.g., Beerda et al. 1998). Nevertheless, many studies found a higher frequency of canine yawning after observing or hearing a human yawn (Joly-Mascheroni et al. 2008, Silva et al. 2012, Madsen & Persson 2013, Romero et al. 2013). Some studies also reported stronger yawn contagiousness in dogs after perceiving a familiar rather than non-familiar person yawning (Silva et al. 2012, Romero et al. 2013). This effect of social connectedness was also demonstrated within wolves (Romero et al. 2014).

In humans, the tendency to yawn after witnessing another person’s yawn is negatively correlated with amygdala activation (Schürmann et al. 2005). Thus, higher amygdala activation, which may occur naturally in unknown company as vigilance for a threat (e.g., Whalen 1998, Hart et al. 2000), acts against yawning contagion. If a similar connection existed in canids, familiarity would increase contagious yawning merely as a function of the individual’s level of social relaxedness. The yawn contagiousness in dogs, however, adds to the possibility of interspecific emotional synchronization and contagion in relaxation (Odendaal & Meintjes 2003, Miller et al. 2009, Nagasawa et al. 2009, Handlin et al. 2011, Nagasawa et al. 2015).

Altogether, the studies of empathy show that at least emotional contagion is possible in dogs. Studies on canine post-conflict affiliative behavior and prosociality also suggest some empathic concern. A recent study on canine prosocial tendencies (Quervel-Chaumette et al. 2015) also reported situation-dependent perspective-taking. The extent of empathic capacity in dogs is unknown, however (for discussion, see also Silva & de Sousa 2011). There are probably limits to the cognitive component of empathy in dogs: They lack meta-representational and self-representational skills because their brains have less encephalization and connectivity than humans. However, coupled with the rudimentary theory of mind hypothesized by Horowitz (2011), empathic responding may not be an all-or-none function but an ability that occurs to various degrees across social species.


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13. Long-term moods: A “cognitive judgment bias” test

The effects of rearing environment on emotional response in animals were noted in the 1950s by psychologists such as Hebb (1955). Raising dogs in a restricted environment affected their subsequent emotional responses (Melzack 1954). Fifty years later, the work was extended into the field of animal welfare, and the effect of the environment on the positive or negative affective states in animals was studied using an emotional judgment bias test (Harding et al. 2004). The effect is called “cognitive judgment bias” or “cognitive bias” in the animal sciences (Mendl et al. 2010a, Rygula et al. 2015), although human psychology has a multitude of different cognitive biases (see e.g., Tversky & Kahneman 1974, Haselton et al. 2005). This expectation-related “cognitive bias” is also based on studies of humans in which the phenomenon is widely known as affective congruence (e.g., Bower 1991, Fazio 2010): anxious or depressed people tend to interpret ambiguous stimuli negatively (Eysenck et al. 1991, Wright & Bower 1992, MacLeod & Byrne 1996, Gotlib & Krasnoperova 1998). Non-human animals may also be biased in their expectations after negative or positive experiences (Mendl et al. 2010b).

The basic test is simple: animals are first trained that one stimulus (e.g., a black card) signals a positive event (reward, e.g., food), and another (a white card) signals a negative event (a punishment). After such training, they are presented with ambiguous, intermediate signals (e.g., a grey card), and their reactions (e.g., time of approaching the stimulus) to the ambiguous signals are recorded. In dogs, a food bowl is placed in one corner of a room and an empty bowl in another corner (Mendl et al. 2010a). When dogs learn to discriminate the two locations, a bowl is placed between them. In the test trials, approach time to the ambiguous locations is measured: a quick approach indicates anticipation of food, an “optimistic” judgment, and a slow approach indicates a “pessimistic” judgment (Mendl et al. 2010a).

Dogs with higher separation-related anxiety approach the ambiguous bowl locations more slowly, showing a negative cognitive bias (Mendl et al. 2010a). Anxiolytic medication with the human anti-depressant fluoxetine combined with behavioral modification diminishes the bias (Karagiannis et al. 2015). However, leaving dogs alone for a brief time does not generate negative expectations (Müller et al. 2012), suggesting that it is a prolonged emotional state that induces negative bias in dogs (Mendl et al. 2010a). Likewise, briefly searching for treats prior to testing was not enough to induce positive bias in dogs (Burman et al. 2011), whereas administering oxytocin prior to testing caused positive bias (Kis et al. 2015).

To date, it seems that the cognitive bias test measures long-term tendencies, expectations, and moods rather than sudden emotions. Inducing the positive or negative expectations experimentally has proven tricky, leaving room for further investigation.


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14. Emotional and social data across species: Emotional evolution?

Although direct data on dog emotions are currently quite rare, there are more studies on dog skills in interspecific cooperative-communicative social tasks. In these tasks, parallel experiments in dogs and other canids, carnivores, and non-human primates have been extremely informative. Regarding evolutionary changes in emotion leading to changes in social cognition, Hare (2007) has suggested that “dogs’ specialized social-problem-solving skills may have first appeared after systems mediating fear and aggression were altered” (p. 62). In the long-term studies on experimental domestication of foxes, selective breeding for low levels of fear and aggression toward humans were associated with changes in foxes’ limbic systems (Trut 2001), and as a side-effect, their social cognitive abilities (Hare et al. 2005). This Emotional Reactivity Hypothesis (Hare & Tomasello 2005) was recently tested with dogs and wolves by Range, Ritter, and Viranyi (2015). In a cooperative situation, wolves were not more aggressive towards conspecifics than dogs. Thus, the modified Canine Cooperation Hypothesis is that dog-human cooperation might have originated from wolf-wolf tolerance and cooperation (Range & Viranyi 2014, Range et al. 2015).

The suggestion that there is interplay between emotional and social skills in dogs is intriguing, and merits a closer examination of the brain circuitries involved.

15. Methodological advances and future directions

Human and nonhuman emotions have a long history of being studied using different methods (Berridge 2003). Therefore, using comparable methods in humans and dogs should provide valuable new insights (for example, Racca et al. 2012, Andics et al. 2014, Törnqvist et al. 2015, Yong & Ruffman 2016). Methodological advances include non-invasive brain imaging usually used with humans, such as functional magnetic resonance imaging (Berns et al. 2012, Andics et al. 2014, Jia et al. 2014, Berns et al. 2015, Dilks et al. 2015, Cuaya et al. 2016) and surface-electroencephalography (Howell et al. 2012, Kujala et al. 2013, Törnqvist et al. 2013, Kis et al. 2014). These can now be used with dogs together with positive operant-conditional training. Thermographic imaging also appears promising for detecting emotionally-stimulated changes in body surface temperature (Travain et al. 2015, Riemer et al. 2016, Travain et al. 2016). All these new techniques require careful experimentation to avoid the possible confounds reported for human research (importantly, see Bennett et al. 2009, Kriegeskorte et al. 2009, Poldrack & Mumford 2009, Vul et al. 2009).

Numerous topics, such as theory of mind in dogs, and possible emotional lateralization or gender effects, deserved more discussion. Many personal and environmental factors underlie individual differences in human emotional processes (e.g., Tomarken et al. 1992, Canli et al. 2002, de Rosnay & Harris 2002, Gross & John 2003), and similar variation also occurs in dogs (see e.g., Gosling et al. 2003, Fratkin et al. 2013, Cook et al. 2014). Dominance relations may affect canine emotions through cerebral neurochemical concentrations (for review, Chichinadze et al. 2014). Skull shape in dogs can also affect brain formation and hence cognition and emotion (McGreevy et al. 2004, Helton 2009, Roberts et al. 2010, McGreevy et al. 2013). There is also no reason dogs could not have unique emotional states that humans do not have, for example, states related to their olfactory world and the function of the piriform cortex. These topics will certainly receive more attention in the future. We need


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more studies of the emotional world of dogs along with sensible caution in interpreting and generalizing the results. Acknowledgments This work was enabled by the Brain Research collaboration between the Aalto University and University of Helsinki (BRAHE initiative); Emil Aaltonen Foundation Personal Grant (#160121); and Tekes grant #7244/31/2016. In addition to the editors and reviewers, I wish to thank my colleagues from various fields in the human and animal sciences for their comments on an earlier draft of the article: Otto Lappi, Sanni Somppi, Helena Telkänranta, Riitta Hari, Jari Hietanen, Jukka Leppänen, Outi Vainio, and Katriina Tiira.

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Animal Sentience 2017.010: Woodruff on Fish Feel

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[Editorial note: Animal Sentience and does not publish primary research reports of findings from

experiments that hurt animals. In the context of open peer commentary, however, including criticism of findings from such experiments, secondary references to findings already published elsewhere are unavoidable.]

Consciousness in teleosts: There is something it feels like to be a fish

Michael L. Woodruff

Departments of Biomedical Sciences and Psychology, East Tennessee State University

Abstract: Ray-finned fish are often excluded from the group of non-human animals

considered to have phenomenal consciousness. This is generally done on the grounds that the fish pallium lacks a sufficiently expansive gross parcellation, as well as even minimally sufficient neuronal organization, intrinsic connectivity, and reciprocal extrinsic connections with the thalamus to support the subjective experience of qualia. It is also argued that fish do not exhibit the level of behavioral flexibility indicative of consciousness. A review of neuroanatomical, neurophysiological and behavioral studies is presented which leads to the conclusion that fish do have neurobiological correlates and behavioral flexibility of sufficient complexity to support the hypothesis that they are capable of phenomenal consciousness.

Keywords: comparative consciousness, phenomenal consciousness, fish, pallium,

comparative anatomy, comparative behavior

Michael L. Woodruff is Professor Emeritus of Biomedical

Sciences and of Psychology at East Tennessee State University. Author of more than 120 professional publications, his research interests include cognitive neuroscience and the philosophy of mind.

https://michaelwoodruff.academia.edu/



mailto:[email protected]

https://michaelwoodruff.academia.edu/




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1. INTRODUCTION

Two connected theses will be defended in this paper. The first thesis is that ray-finned fishes of the teleost subclass (Actinopterygii; hereafter referred to simply as fishes)1 are sentient. The second thesis is that the pallium contributes to sentience in these species. Allen and Trestman (2016) equate phenomenal consciousness and sentience. I will adapt their use of the term and define sentience2 as at least the minimal capacity to have subjective experience of the qualities associated with external and internal sensations, as well as affective and motivational states. The consequence of this capacity is that there is something that it “feels like” to be the individual, human or animal, that has subjective experience (Nagel 1974).

I argue that there is something it feels like to be a fish. Others disagree, and usually ground their disagreement on two general arguments. The first argument is that fishes lack the neuroanatomical substrates necessary for consciousness. This argument assumes that a layered neocortex, or a structure homologous to it, with a number of anatomically distinct divisions and reciprocal anatomical connections among them, is required for even minimal sentience. Furthermore, massive reciprocal connections between the neocortex and the thalamus are needed. Because the fish pallium is not homologous to the mammalian neocortex, and its reciprocal connections with the thalamus are sparse, fishes lack the required neuroanatomical substrates for sentience (Cabanac et al. 2009; D. Edelman et al. 2005; Key 2015, 2016a; Rose 2002, 2007; Rose et al. 2012; Seth et al. 2005). The second argument follows naturally from the first. It is that fishes do not exhibit behaviors that require sentience. On this view, all of the behaviors observed in fishes, regardless of how complex they appear to be, are explicable by reference to simple sensory–motor reflexes, species-typical behaviors, or procedural/implicit learning and memory. I contend that both of these arguments fail.

In this target article I will present research supporting the hypothesis that the fish brain is neuroanatomically complex enough to support sentience. I will also present evidence that the pallium of the fish has neurophysiological activity similar to correlates of sentience in mammals. Finally, I will provide selected examples of behaviors generally thought to require sentience in humans.

2. SENTIENCE IN FISHES: THE OPTIC TECTUM

Several theories propose that sentience emerged in animals when the hindbrain, midbrain and diencephalic nuclei first evolved (e.g., Damasio 2010; Feinberg and Mallatt 2013, 2016; Merker 2007; Panksepp 2005). These theories differ in neuroanatomical detail and in the physiological and behavioral processes they emphasize. They will not be reviewed here (see Feinberg and Mallatt 2016, chapter 7, for a discussion). However, they have the following in common: (i) proposing that at least minimal sentience is possible without a neocortex, and (ii) attributing a role in the generation of sentience to the optic tectum.

1 Cartilaginous fishes, such as sharks and rays, from the class chondrichtyans are not included in this discussion. 2 What I am calling sentience is, in general, the same process that Feinberg and Mallatt (2016) call sensory consciousness and that G. Edelman (1989) refers to as primary consciousness.


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Figure 1. The drawings in this figure are provided as aids in visualizing the physical

relationships among the major divisions of the fish brain discussed in the text. They

are generalized representations and may therefore deviate in detail from the specific

descriptions given in the cited references. (A) Schematic of a longitudinal (sagittal)

section of the fish brain. The drawing represents a parasagittal section from the

location of the dashed line in (B). That is, it comes from a location slightly away from

the midline of the brain. Abbreviations: Cb – cerebellum; Ha – habenula; Hy –

hypothalamus; OB – olfactory bulb; OT – optic tectum; Th – thalamus; P – pituitary;

PgC – preglomerular complex. (B) A schematic cross section from the dorsal through

the ventral surface of one hemisphere of the fish telencephalon. The section is drawn

to represent the approximate anterior-posterior level of the brain demarcated by the

vertical line in (A). It shows the locations of the pallial divisions given by Nieuwenhuys

and Meek (1990). Abbreviations (all beginning with D refer to divisions of the

pallium): DD – dorsodorsal; DMd – dorsomedial dorsalis; DLv – dorsomedial ventralis;


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DLd – dorsolateral dorsalis; DC – dorsalis centralis; DP – dorsalis posterior; VT –

ventral (subpallial) telencephalon; DMv – dorsomedial ventralis.

The fish optic tectum (Figure 1A) is more involved in sensorimotor integration in

fishes than its homolog, the superior colliculus, is in mammals. All sensory modalities present in any given teleost species, with the exception of olfaction, are represented in the tectum. However, visual input is especially strong and the tectum is generally viewed as the primary visual center in fishes (Feinberg and Mallatt 2013, 2016; Li 2016; Meek 1983). As such, the tectum is crucial for the transformation of visual input into directed, adaptive global motor output. This transformation begins with the creation of an accurate point-by-point representation of visual space on the retina. Feinberg and Mallatt (2016) refer to this representation as sensory isomorphism. Retinal input to the tectum generates an isomorphic neural representation of visual space. Feinberg and Mallatt take it as axiomatic “that mental images are a part of primary, sensory consciousness and, therefore, contribute to “something it is like to be.) The neural representation of the world in the tectum is experienced subjectively as mental images. On my view, this is an important insight into what it means for a neural system to participate in the generation of sentience.

2.1 Tectal Neuroanatomy

But what evidence is there that the optic tectum is a crucial part of such a neural system? Others, in particular Feinberg and Mallatt (2013, 2016) and Merker (2007), have provided extensive reviews of this evidence. I will not replicate these reviews, but will provide a brief account of data indicating that the optic tectum, and its extrinsic and intrinsic connections, meet the requirements to be an anatomical substrate of sentience in fishes. I will discuss only the visual modality, but the basic organizational pattern also applies to the other sensory modalities represented in the tectum.

One requirement is that the visual world be accurately represented in the tectum. Isomorphic retinal input mediated by the excitatory neurotransmitter glutamate terminates primarily in the uppermost of the six neuronal layers of the tectum on the opposite side of the brain. Both anatomical and electrophysiological studies indicate that the pattern of termination reflects the accurate point-by-point visual representation of the world created on the retina (Nevin et al. 2010; Meek 1983; Venegas and Ito, 1983). Another requirement is modulation of the primary sensory pathways by intrinsic excitatory and inhibitory interneurons. Primary sensory input to the tectum can be amplified by positive feedforward and feedback circuits created by excitatory glutaminergic interneurons. Intrinsic inhibitory circuits created by interneurons that use γ-aminobutyric acid (GABA) as a transmitter provide for temporal stabilization and spatial sharpening of activity within the excitatory circuits (Kardamakisa et al. 2015; Nevin et al. 2010). One function of these inhibitory circuits may be to improve discriminability of objects in the fish’s visual field. Ablation of these neurons selectively impairs prey capture in zebrafish (Del Bene et al. 2010), possibly because the prey is perceived as larger than it is and because predator avoidance rather than prey approach behavior is selected (Barker and Baier 2015).


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The tectum also receives input from mesencephalic and hindbrain nuclei, as well as the diencephalic and telencephalic regions, including the pallium. As will be discussed below, this input allows memory and emotion to influence tectal output to brainstem structures that regulate motor programs. The output of the tectum arises from neurons located in its deeper layers. This output terminates in the telencephalic, diencephalic, and brainstem sites that provide input to the tectum, and, most importantly, in premotor brainstem nuclei that directly control behavior. These nuclei send input back to the tectum, thereby providing rapid feedback to refine future output (Kinoshita et al. 2006; Meek 1983; Nevin et al. 2010; Sato et al. 2007).

In sum, the extrinsic reciprocal neuronal connections and the intrinsic neuroanatomy of the teleost tectum are complex enough to support the reentrant computational processes proposed to underlie sentience in mammals (Crick and Koch 2003; G. Edelman 1989; G. Edelman et al. 2011; Seth et al. 2005). In mammals, neural and behavioral markers of such computational processes are associated with the neocortex and its connections to the thalamus. If the conclusion reached above is correct, then it should be possible to find similar markers associated with the tectum of fishes. Here I will provide a specific example.

2.2 Selective Attention and Tectal Neurophysiology

Feinberg and Mallat (2016) include “mechanisms for selective attention to stimuli” as one of their criteria for sensory consciousness, the process that I am calling sentience. Selective attention may be a legitimate criterion for the presence of sentience, but researchers in this area do not agree as to how this may be. Sentience and selective attention are generally not considered to be the same process, and evidence indicates that either can be present without the other (Baars 1997; van Boxtel et al. 2010; Howe et al. 2009; Tononi and Koch 2015). However, it seems undeniable that the two are related. I suggest that some form of sentient pre-attentional awareness of the world exists as long as an adequate level of arousal and general, nonspecific awareness of the environment are present. However, in the absence of selective attention, the contents of sentience required to produce specific actions necessary for survival, such as finding food or avoiding a predator, are absent. On this view, then, selective attention varies the force and focus of sentience. The implication is that, if sentience did not exist, then the processes of selective attention would have no work to do. Therefore, they would not exist. But it is indisputable that they do. Thus, agreeing with Feinberg and Mallatt, I argue that selective attention is a legitimate criterion for the presence of sentience.

A principal function of selective attention in the visual modality is to guide visual search for salient environmental items, whether these items are places of safety, a predator or food. In primates, visual search for salient environmental targets is conducted in either a parallel or serial mode (Itti and Koch 2001). The parallel mode guides attentional processes when the target object is distinct from surrounding distractor objects. Reaction time for detecting the target is very short in the parallel mode and is not lengthened by increasing the number of distractor objects. In this mode, the target is said to “pop-out” from the background distractors. Attentional processes are guided by the serial mode when the distractor items are similar to the target item. Increasing the number of distractors increases reaction time and no pop-out occurs. In primates, neocortical areas are associated with these search modes and consequent action selection (Bichot and Schall 2002; Li 2016).


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Ben-Tov et al. (2015) have demonstrated both parallel and serial visual search modes in the archer fish and have found neural correlates of these processes in the optic tectum. Archer fish are able to prey on insects by hitting them with water forced from their specialized mouths. The insect is the salient object and the fish executes a visual search to locate it. Ben-Tov et al. used small rectangular bars as targets and established that the reaction time for archer fish to shoot a bar moving either faster than, or in the opposite direction from, distractor bars did not change as the number of distractors increased from 4 to 8. That is, the fish demonstrated the pop-out effect characteristic of the parallel mode of visual search. When the size of the bar was salient, reaction times for target selection increased as the number of distractors increased, indicating that the serial mode was being used.

Ben-Tov et al. identified neural correlates of pop-out in the tectum of archer fish. Discharge rates of tectal neurons correlated with characteristics of the selected target. “Speed-contrast” neurons fired at higher than baseline rates only when the speed of the target was salient while “direction-contrast” neurons fired at higher rates only when the target direction was salient. They also found “both-contrast “neurons that increased their discharge rates under either saliency condition.

Ben-Tov et al. also conducted an experiment in which the target was defined by a combination of speed and direction. Compared to selection rates for a single target feature, a target differentiated by both features was significantly more likely the be selected. When neurophysiological responses were investigated, Ben-Tov et al. found that some of the neurons that increased their firing rate to a single target increased the rate significantly more in the presence of the additive target.

In sum, archer fishes use the same attentional modes used by primates to construct a neural map of salient stimuli from a pre-attentional isomorphic neural map of the visual world. Both the isomorphic and salient neural structures are located in the tectum. The maps are dynamic and include neuronal circuits capable of associating two distinct characteristics of a visual stimulus (speed and direction of movement) to effectively drive a behavioral response. This capability may be interpreted as representing a simple form of sensory binding.

2.3 Summary

Several criteria have been suggested for a brain structure to qualify as a substrate of

sentience (e.g., Crick and Koch 1990; 2003; G. Edelman 1989; Feinberg and Mallatt 2016; Seth et al. 2005). Each of these is a criterion for sentience, not sentience itself. One criterion is complexity of neural architecture and connectivity. The tectum meets this criterion. Two other criteria are isomorphic representation of sensory input and segregation of the sensory modalities. Isomorphic sensory maps are produced in the tectum. Additionally, the neural representation of each sensory modality is segregated from the others within the tectum. Another criterion is the presence of neural mechanisms for selective attention. The tectum has these mechanisms. The ability to merge, or bind, sensory input into a coherent image which can be used to direct motor output is also included. The additive effects of two distinct characteristics of a visual stimulus suggest that the tectum has this capacity. From this analysis, it is reasonable to hypothesize that the tectum is at least a part of the physical substrate of sentience in fishes.


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Critics of this hypothesis are likely to insist that sentience requires structures that are homologous to the mammalian neocortex and thalamus and to maintain that the tectum and its interconnections failed to meet this requirement (e.g., Key 2015, 2016a, b; Rose 2002, 2007; Rose et al. 2012). It is also likely that critics would explain the ability of archer fish to discriminate between targets and distractors as some combination of reflex behavior and implicit discrimination learning. I admit there is room for such an argument. However, an explanation of the results of an experiment by Schuster et al. (2006) requires more than invoking implicit discrimination learning.

Although moving targets are salient for archer fish, the ability to hit one reliably takes practice. Schuster et al (2006) trained archer fish to reliably hit a target 60 cm above the water traveling at 60 mm/s. As with the experiment by Ben-Tov et al. (2015), these results can be explained in behavioristic terms. However, the results of the second part of the experiment by Schuster et al. does not admit of such a simple explanation. They found that a second group of fishes, who only observed another fish hitting a moving target, were able to hit the target with a high rate of accuracy on their first opportunity to do so. It is difficult to explain this observation without reference to the ability of the observers to form and store in memory a mental image of other fish successfully executing the task. This is an example of declarative memory, which requires conscious awareness (Cohen et al. 1997; Eichenbaum and Cohen 2014; Squire et al. 2015), and is, therefore, a marker for the presence of sentience.

The proposal that declarative memory is necessary for the ability of archer fish to learn from observation leads to my second thesis that the pallium is a necessary component of the neural substrate for sentience in fishes. In this I diverge somewhat from the theory proposed by Feinberg and Mallatt (2016). Those authors do include a role in memory processing for the pallium in their model but they do not grant the pallium any place in the generation of mental images. Rather, the pallium simply modulates motor commands issued by the tectum (Feinberg and Mallatt 2016, Kindle edition, location 2580). I argue below that the pallium has a more central role in the formation of mental images — and, hence, in sentience in fishes — than simple modulation of tectal processing.

3. SENTIENCE IN FISHES: PALLIAL ANATOMY

3.1 Overview of Sensory-Specific Connections

The teleost pallium receives a variety of modality-specific sensory inputs (Giassi et al. 2012b; Ito and Yamamoto 2009; Northcutt 2006; Yamamoto and Ito 2008). As in mammals, all sensory modalities in fishes, other than olfaction, reach the pallium through a subpallial relay. Unlike mammals, the primary sensory relay is not the thalamus. The thalamus does contribute input to the teleost pallium (Echteler and Saidel 1981; Ito et al. 1986), but the diencephalic preglomerular complex (PgC; Figure 1B) — a component of what Mueller (2012) named the “wider thalamus” — is the principal source of its monosynaptic sensory input (Demski 2013; Giassi et al. 2012b; Mueller 2012; Northcutt 2006; Yamamoto and Ito 2008). The PgC receives topographically organized input from the tectum (Giassi et al. 2012a; Northcutt 2006) and its output to the pallium maintains modality segregation. Recognizing this, Ito and Yamamoto (2009) concluded that: “Ascending pathways mediated by the preglomerular complex enumerated above exhibit a considerable degree of modality-specific organization similarly to mammalian thalamocortical pathways” (p. 117). For example, visual


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input terminates most heavily in the dorsal lateral pallium (DLd/DLv in Figure 1). Indeed, the DLd has been proposed as the visual pallium for many teleosts (Demski 2013; Saidel et al. 2001). Cell clusters in different parts of the DM receive auditory, gustatory, and lateral line input (Demski 2013; Northcutt 2006; Prechtl et al. 2008). In some species, the DD receives some sensory input, but its major connections are with the other pallial divisions.

The DC receives comparatively little subpallial input but has reciprocal connections with other pallial divisions and is the major source of pallial output to the tectum, the PgC, and numerous other subpallial sensory-motor structures (Echteler and Saidel 1981; Giassi et al. 2011; Giassi et al. 2012b, c; Ito et al. 1986; Murakami et al. 1983). Therefore, the large neurons in the DC can affect motor programs or modulate sensory input to other pallial divisions through its connections to the diencephalic and midbrain motor and sensory processing sites.

3.2 Non-Specific, Modulatory Pallial Inputs

In addition to the qualities associated with sensory input from the environment, sentience includes subjective feelings associated with motivational and affective states such as hunger, thirst and fear. These states are supported not by sensory-specific input from subcortical structures, but by subcortical input that terminates throughout the cortex (Purvis et al. 2011). In mammals, these systems are associated with the cholinergic, dopaminergic, GABAergic, serotonergic, and noradrenergic neurotransmitter systems. The same neurotransmitter systems are found in fishes (Echteler and Saidel 1981; Giassi et al. 2012b, c; Giraldez-Perez et al. 2013; Mueller and Guo 2009; Murakami et al. 1983; Schweitzer et al. 2012). The presence of dopaminergic and serotonergic input suggests that motivational and affectual systems found in mammals also exist in fishes. These neurotransmitters are involved in guiding approach and avoidance behaviors (e.g., Dayan 2012). Feinberg and Mallatt (2016) rightly include the feeling states associated with these behaviors in what they call sensory consciousness and what I am calling sentience. The existence of these neurotransmitter systems in fishes provides additional support for sentience in teleosts.

Additionally, cholinergic, noradrenergic and serotonergic afferents to the cortex affect memory, attentional processes, and states of consciousness (e.g., awake or asleep, dream sleep or non-dream sleep) in mammals (Richerson et al. 2012). The presence of widespread input containing these neurotransmitters from subpallial structures, particularly the midbrain and hypothalamus, to the pallium suggests the existence of common modulatory mechanisms for these functions in fishes and mammals.

3.3 Excitatory and Inhibitory Connections of the Pallial Divisions

Research from Leonard Maler’s laboratory at the University of Ottawa (Elliot et al.,

2017; Giassi et al. 2012 a, b, c; Trinh et al. 2015) exploring the pallium of two species of weakly electric knifefish has confirmed the gross pattern of intrapallial connections observed in other teleost species (Echteler and Saidel 1981; Ito and Yamamoto, 2009; Northcutt, 2006), and has added important details. Excitatory neurons are required for positive feedforward and feedback control of local circuits. Inhibitory neurons are necessary for temporal stabilization and spatial sharpening of activity within these circuits.


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Using immunocytochemical markers and localized injections of neurotracers, Giassi et al. (2012b, c) described the circuitry created by excitatory glutaminergic neurons. The DL has reciprocal excitatory connections to the DD, thus permitting feedforward/feedback excitation between the DL and DD. The DC receives excitatory glutaminergic input from the DL. Similar to what has been found in other species, the knifefish DC is the principal source of excitatory pallial output to diencephalic, midbrain and hindbrain targets, each of which returns excitatory input to the DL. These three regions of the fish pallium therefor have circuits that can support reentrant processing, one of the proposed requirements for a neurobiological substrate of sentience (e.g., Crick and Koch 2003; G. Edelman 1989; G. Edelman et al. 2011).

Mueller and Guo (2009) observed presumptive inhibitory GABAergic neurons in the DL, DD, DM and DC in zebrafish. Giassi et al. (2012a, c) confirmed this observation in knifefish. Giassi et al. (2012c) also observed rich intrinsic GABAergic plexuses and numerous GABAergic terminals, particularly in the DL. The source of some of this GABAergic innervation is the telencephalic subpallium (Elliot et al. 2017; Giassi et al. 2012c; VT in Figure 1B) which, in turn, receives excitatory glutaminergic input from the DM (Gaissi et al. 2012b, c). Whether the source is intrinsic or extrinsic, GABAergic terminals within the DL, DM and DD modulate the activity of excitatory glutaminergic neurons (R. Vargas et al. 2012).

3.4 Pallial Layers and Cryptic Columns in the DL

Giassi et al. (2012c) investigated the extrinsic connections of the DL and the other

pallial divisions of the knifefish. In order to study the intrinsic connections of the DL, Trinh et al. (2015) incubated slices of the pallia from knifefish in nutritive media. They located the DL in the slice and used a microscope to guide injections of axonal tracers into discrete parts of it. Analysis of the resulting data indicated that the trajectory of the intrinsic axons arising from some of the large neurons within the DL separate it into 60-µm-thick lamina along its horizontal axis. Axons from other large neurons have projections extending 100 to 150 µm. These projections delineate columns along the vertical axis. Each column connects reciprocally to adjacent columns creating local recurrent networks throughout the DL. Thus, the DL of the knifefish pallium exhibits both a layered and a columnar organization.

Such a neuronal organization is characteristic of the mammalian cortex, but Trinh et al. (2015) emphasize that the columns observed in knifefish are not structurally discrete in the same way as columns in regions of the mammalian neocortex, such as the somatosensory cortex. Rather, they resemble the overlapping cryptic ocular dominance columns found in the visual cortex (e.g., Kaskan et al. 2007). Cryptic columnar organization allows small changes in input to one column to cause a slight shift in neuronal activity in overlapping columns, thereby allowing spatiotemporal integration of sensory input and binding.

3.5 Fish Pallial Anatomy: Summary

The research reviewed above indicates that the fish pallium has reciprocal connections with subcortical structures that provide it with both specific sensory and non-specific modulatory input. The specific sensory input to the pallium arises primarily from the PgC and is analogous to the reentrant network between the thalamus and cortex in mammals which has been proposed to correlate with conscious experience of environmental stimuli.


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The non-specific input comes from ventral telencephalic, diencephalic and brainstem nuclei, and contains neurotransmitters associated with affective and motivational states in mammals. My conclusion is that the teleost pallium has the neuroanatomical complexity necessary to contribute to sentience. In the next section, I will give evidence that the pallium also exhibits neurophysiological markers of sentience.

4. SENTIENCE IN FISHES: PALLIAL NEUROPHYSIOLOGY

4.1 Pallial Rhythmic Electrical Activity

There are few relevant neurophysiological experiments, and they were not specifically

designed to evaluate the pallium for correlates of sentience. However, their results suggest the fish pallium exhibits generalized electrophysiological responses correlated with several criteria of sentience in mammals. For example, recordings of the electroencephalograms from the skulls of Atlantic salmon (E. Lambooji et al., 2010), African catfish (E. Lambooji et al. 2006) and the turbot (B. Lambooji et al. 2015) demonstrated that the pallium of the fish generates electrical activity in the delta (0.5–4 Hz), theta (4-8 Hz), alpha (8–14 Hz), beta (14–30 Hz) and gamma (30 Hz and higher) bandwidths. The same spectrum of EEG frequencies is generated by the mammalian cortex and correlates with levels of arousal and, at the gamma frequency, with attentional processes and possibly with sensory binding. (Baars

et al. 2013; Crick and Koch 1990; 2003; Edelman 2003; Orpwood 2013; Tononi and Edelman 1998). In addition to generalized electrophysiological responses similar to those found in the mammalian cortex, the teleost pallium shows modality-specific, sense-evoked responses (Prechtl et al. 2008; Elliot and Maier 2015).

4.2 Sensory-Evoked Activity

Prechtl et al. (1998) recorded evoked action potentials from the pallial neurons of

weakly electric elephant nose fish in response to auditory, visual, mechanical (water movement), lateral line and electrical field stimulation. The electrical field stimulation was not noxious, but intended to mimic stimulation produced by the fish itself, or by conspecifics. In accord with the anatomical data described above, responses to visual stimuli were observed predominantly in the lateral pallium. Responses to electrical stimuli also occurred more laterally in the pallium, but were clustered toward its posterior (toward the tail) pole. Mechanical-stimuli-evoked responses mostly from neurons located ventromedial to the area where responses to electrical stimuli predominated and auditory-evoked responses were predominantly found in the anterior medial pallium. It is interesting that Prechtl et al. also observed that the sensory stimuli used in their study produced field potentials that oscillated in bandwidths from 15 to 55 Hz. The higher end of these bandwidths corresponds to the gamma frequency proposed, as noted previously, to be the neurobiological signature of attentional processes and sensory binding.


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I indicated above that the primary interconnectivity of the DD is with other pallial divisions. Using electric brown ghost knifefish, Elliot and Maler (2015) made extracellular and patch-clamp recordings from DD neurons in response to electrosensory or acoustic stimulation. Extracellular recording revealed that DD neurons exhibited sustained discharge to electrosensory stimulation. It is interesting that the onset latency for DD neurons to respond to electrosensory stimulation was substantially longer than that found for medial pallial neurons to respond in the study by Prechtl et al. (1998). This finding is compatible with the anatomical data that indicate the DD does not receive significant direct sensory input, but adds further processing to sensory input to the DL and DM. Patch-clamp recordings indicated that the membrane potential for DD neurons went from the persistent “down” state of approximately -70 mV to an “up” state of approximately -45 mV in response to electrosensory stimulation. The shift to a smaller negative membrane voltage indicates an increase in neuronal excitability, and these responses correlated with the frequency of extracellular spiking. Acoustic stimulation produced similar effects. In interpreting these results, Elliot and Maler (2015) hypothesized that “Up states are induced by complex and variable pallial network activity that intervenes between sensory input and DD cells” (p. 2075). The results of this experiment suggest that the DD may be involved in longer-term cognitive processing of input to other pallial divisions and can be taken as support for the proposal that the DD serves as an association region, thereby expanding the regional complexity of the pallium.

4.3 Fish Pallial Neurophysiology: Summary

Neurophysiological studies show that neurons in the fish pallium generate the same

spectrum of EEG frequencies and waveforms observed in mammals. Pallial neurons also respond to sensory stimulation with specific evoked responses that show some segregation by sensory modality. Sensory stimulation also evokes EEG activity in the gamma bandwidth, a presumed correlate of attentional processes and sensory binding. Additionally, electrophysiological data support the hypothesis, generated from anatomical data, that a part of the pallium, the DD, possibly serves an associative function. These electrophysiological data are consistent with the hypothesis that the fish pallium contributes to the production of sentience in fishes.

5. THE PALLIUM AND BEHAVIORAL MARKERS OF SENTIENCE The purpose of this section is to discuss experiments that link behavior of fishes to

both the pallium and sentience. I will not discuss the substantial body of behavioral research that is supportive of my thesis that fishes are sentient because most of it was not designed to evaluate the role of the pallium in behavior. Additionally, much of it has been reviewed in recent publications (Allen 2013; Balcombe 2016; Braithwaite 2010; Brown 2014, 2016; Brown et al. 2011; Sneddon 2015).

Two general categories of behavior have dominated the published literature concerned with the behavioral functions of the fish pallium. The reason for this dominance stems from the anatomical, developmental, and molecular research that points to the medial pallium (DM – DMd and DMv in Figure 1B) of fishes as a homolog to the mammalian amygdala, and to the lateral pallium (DL – DLd/DLv) as a homolog to the mammalian


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hippocampus (Ganz et al. 2015; Harvey-Girard et al. 2012; Nieuwenhuys and Meek 1990; Northcutt 2006). These homologies led to the hypothesis that lesions of the DM or DL would have the same behavioral effects as lesions of the amygdala or hippocampus in mammals. Research generated primarily by researchers at the Universidad de Sevilla has largely supported this hypothesis (Portovella et al 2004a, b; Vargas et al. 2006; 2012).

5.1 Avoidance Behavior and the Pallium

As indicated earlier, I follow Allen and Trestman (2016) and define sentience broadly

as the ability to have any subjective experience. This definition differs from that of Feinberg and Mallatt (2016) who regard sentience as the affective component of sensory consciousness. Despite this definitional disagreement, I agree with their requirement that “for an animal to be ‘sentient’ it must be capable of experiencing an affective state” (Feinberg and Mallatt 2016, Kindle location 3055).

Lesions of the DM impair learned behaviors motivated by aversive stimuli in the same way that destruction of the amygdala does in mammals (Davis 1992). For example, Portavella et al. (2004a, b) assessed the effects of either DM or DL lesions on the ability of goldfish to learn a shuttle-box avoidance task. A shuttle box has two compartments. The fish had to learn to swim from one box to the other in response to presentation of a colored light (the conditioned stimulus, CS) in order to avoid electrical shock (the unconditioned stimulus, US). Portavella et al. found that DM lesions had no effect on escape from electrical shock, but significantly impaired learning of the avoidance response to the CS. DL lesions had no effect.

These results support the hypotheses that integrity of the DM is necessary for successful performance of a learned, aversively-motivated behavior and that it is a homolog of the amygdala. However, whether sentience is required to explain the acquisition of shuttle-box avoidance can be questioned. The answer to this question depends on interpretation of the two-process theory usually used to explain shuttle-box avoidance learning (Mowrer 1960). The first process is classical conditioning. The CS produces a conditioned emotional response after repeated association with the innate aversive emotional response produced by the US. The second process is operant conditioning. On one interpretation, the innate and conditioned emotional responses are equated to experience of fear. Reinforcement occurs when the avoidance response reduces fear (Mowrer 1960). Several publications describing a variety of other procedures to assess avoidance behavior in intact members of several species of fish support this view (e.g., Braithwaite 2010; Braithwaite and Boulcott 2007). If fear is considered to be a consciously experienced state, then the ability of fishes to learn shuttle-box avoidance supports the hypothesis that they are sentient. Under this interpretation, the DM is part of a distributed neural system that generates the feeling of fear. Subpallial structures comprise the core of this system, and, in conjunction with the DM, participate in elaboration of the negative affectual component of sentience in fishes.

5.2 Declarative Memory and the Pallium

Declarative memory in humans and other mammals is associated with availability for conscious recollection and provides flexible guidance to behavior in different contexts. Behaviors that require relational learning among stimuli distributed either over time or in space are considered to be exemplars of declarative memory. Transitive inference (TI)


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provides an excellent example (Cohen et al. 1997; Eichenbaum and Cohen 2014). TI is the ability to infer a relationship between items that have not been previously directly compared. First observing that A<B, B<C, and C<D, and then deducing that A<D is an example of TI. In humans TI requires conscious awareness of the relationships (Smith and Squire 2005). Thus, the presence of TI in a non-human species can be taken as an indication that the species is sentient.

Grosenick et al. (2007) demonstrated that male cichlid fish (Astatotiliapia burtoni) exhibit TI in an observational learning situation. Male A. burtoni inevitably fight for territory. A bystander male (BM) was placed in the center of an arena surrounded by five small compartments (A through E) with transparent walls. Each compartment housed a combatant fish (CF). CF B was introduced into CF A’s compartment, then CF C into CF B’s, and so on. Each invader lost the ensuing fight. For example, CF A beat CF B and CF D beat CF E. CF A and CF E were then placed in separate transparent chambers and the time the BM spent near each fish was recorded. This was repeated for CF B and CF D. Although CF A had not fought with CF E, nor CF B with CF D, the BMs consistently spent more time in the vicinity of the losers (B and E) than they did in the vicinity of winners. This is a clear indication of TI and supports the hypothesis that fish are sentient.

Destruction of the hippocampus significantly impairs behaviors associated with declarative memory (Eichenbaum and Cohen 2014; Squire et al. 2015) including TI (Smith and Squire 2005). Because the DL of fishes is considered to be the homolog of the hippocampus, lesions of the DL should disrupt behaviors associated with declarative memory in fishes. The effects of DL lesions on TI in fishes have not been demonstrated, although it is a testable hypothesis that DL lesions would impair TI in archer fishes. However, other behaviors requiring relational learning have been identified in fishes (Gerlai 2017), and the effect of DL lesions on some of these has been demonstrated.

Declarative memory is distinguished from procedural or implicit memory which is unconscious and is characterized by inflexible stimulus response associations. Classical conditioning is regarded as a characteristic example of procedural memory. It is dependent upon the integrity of the cerebellum regardless of the temporal relationship between the CS and the US (Christian and Thompson 2003). The hippocampus is not required for procedural memory, including classical conditioning, except under a specific experimental design known as “trace” conditioning. In the trace procedure, the US is turned on at some time after the CS been turned off. Thus, the term “trace” refers to the assumption that there must be some trace of the CS remaining to relate it to the US across the temporal gap between the offset of the CS and the onset of the US. This procedure differs from the “delay” procedure in which the US comes on while the CS is still present. Hippocampal destruction in humans and other mammals has no effect on conditioning in the delay procedure (Christian and Thompson 2003). Nor does destruction of the DL in the goldfish impair classical conditioning when the delay procedure is used (Gómez et al. 2016; Rodríguez-Expósito et al. 2017).

However, hippocampal destruction does impair acquisition of classical conditioning when the trace procedure is employed in both mammals (Weiss et al. 2015) and goldfish (Gómez et al. 2016; Rodríguez-Expósito 2017). These results do not mean that the cerebellum is not important in trace conditioning, as cerebellar destruction impairs trace conditioning in both mammals and fish. They are, however, interpreted to indicate that the hippocampus (or DL in fishes) functions in concert with the cerebellum in trace conditioning to enable


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declarative memory — and thus conscious awareness — to form a conscious image from memory to relate the CS and US across the temporal gap.

The same effect has been reported for shuttle-box avoidance learning by Portavella et al. (2004a). As described above, while DM lesions impaired shuttle-box avoidance learning, DL lesions had no effect when the delay procedure was used. However, when a trace procedure in which there was a five-second delay between the offset of the CS in the onset of the US was used, both DM and DL lesions impaired shuttle-box avoidance learning. These results are compatible with research in humans indicating that trace conditioning involves conscious awareness (Clark and Squire 1998) and hence give some support to the hypothesis that fish are sentient.

In addition to TI, Eichenbaum (2000) considers allocentric spatial learning to be a clear indication of the presence of declarative memory in animals. Allocentric spatial learning refers to the ability of a person or animal to encode and organize the memory system for spatial information based on the physical relationships of objects as part of a distant scene independent of the subject’s position relative to those objects. A large number of teleost species demonstrate allocentric spatial learning (e.g., Brown 2014; Durán et al. 2010; Creson et al. 2003; White and Brown 2015). The mammalian hippocampus is associated with allocentric spatial processing (Nadel 1991). The following evidence indicates that the DL is associated with spatial learning in fish.

Hippocampal neurons in rats show place-related increases in the firing rate, and hippocampal lesions impair allocentric spatial learning in rats (Nadel 1991). DL neurons in freely swimming goldfish and cichlid fish show place-related increases in the firing rate (Canfield and Mizumori 2004), and Uceda et al. (2015) observed spatial-learning-related increases in metabolic activity in the goldfish ventral DLv. Furthermore, a series of experiments from the Seville group indicate that lesions of the entire DL (e.g., Durán et al. 2010; J. Vargas et al. 2006), or just to the DLv (Bingman et al. 2017), impair allocentric spatial learning in goldfish. DM lesions, on the other hand, have no effect on allocentric spatial learning (Durán et al. 2010; J. Vargas et al. 2006).

5.3 The Pallium and Behavior: Summary

In this section I have described the results of experiments which indicate a double dissociation between the behavioral effects of DM and DL lesions. DL lesions impair behavior only when the task demands that a relationship among stimuli be maintained across time or in space. I argue that this implicates the DL in declarative memory which by general consensus implies conscious awareness. DM lesions, on the other hand, impair behaviors generally associated with procedural memory which does not require conscious awareness. However, even here, the DM may be involved in the affective component of sentience if the two-process theory of shuttle-box learning is interpreted to involve a subjective sense of fear. Particularly for the DM, the function of these pallial structures in the modulation of behavior is part of a network that includes core subpallial structures. However, I argue that the DL plays an important role in the generation of mental images, and thereby sentience, when declarative memory is required for successful execution of motor programs that are organized in brainstem structures.


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6. CONCLUSION

In this target article, I have argued that fish are sentient. As indicated above, this argument has been cogently made by others based on the complexity of brainstem circuitry (e.g., Feinberg and Mallatt 2013, 2016; Merker 2007), and the flexibility and complexity of the behavior of fishes (e.g., Balcombe 2016; Braithwaite 2010; Brown 2014; Brown et al. 2011). I have also argued that the intrinsic neuroanatomical organization and extrinsic connections of the pallium, particularly with the PgC and the tectum, are complex enough to be at least weakly analogous to the circuitry of the cortex and thalamus assumed by some to underlie sentience in mammals. Neurophysiological and behavioral data further support the hypothesis that fish have the capacity for sentience.

Based on the evidence reviewed in this paper, I suggest that the pallium is an important part of the hierarchical network proposed by Feinberg and Mallatt (2016) to underlie sentience in fishes. The tectum is at the core of this network. The tectum receives segregated sensory input and has the local and global reentrant neural circuitry needed to amplify and process this input. Segregation of the sensory modalities is maintained through the PgC to the pallium. The pallium also receives input from subpallial structures involved in placing a positive or negative valence on this input. These inputs are then integrated by various divisions of the pallium. Particularly in the case of the DL and declarative memory, the result of this integration is the formation of mental images that permit relational interactions among stimuli and flexible regulation of behaviors organized in the brainstem.

In her book Animal Minds, Andrews (2015) makes the point that, “Members of the human species have human minds, and if members of other species have minds, they will have species-specific minds of their own” (p. 4). It is safe to say the same about those processes of the mind of fishes I call sentience. Fish sentience differs from human sentience, and what it feels like is as unknowable to us as what it feels like to be a bat. However, just as Nagel (1974) found it reasonable for there to be something it feels like to be a bat, I think that it is reasonable to adduce from the existing evidence that there is something it feels like to be a fish.

Acknowledgements I thank Dr. Hugh Lafollette and Dr. Ana Giassi for helping me obtain copies of several of the publications

referenced in this paper and for their valuable comments on its draft versions. I also acknowledge the helpful

comments from the reviewers of the initial submission.

References






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UQÀM/ISC Cognitive Science Summer School June 26 - July 6 2018, Montreal, Canada

The Other Minds Problem: Animal Sentience and Cognition

Overview. Since Descartes, philosophers know there is no way to know for sure what — or whether — others feel

(not even if they tell you). Science, however, is not about certainty but about probability and evidence. The 7.5 billion

individual members of the human species can tell us what they are feeling. But there are 9 million other species on the

planet (20 quintillion individuals), from elephants to jellyfish, with which humans share biological and cognitive

ancestry, but not one other species can speak: Which of them can feel — and what do they feel? Their human

spokespersons — the comparative psychologists, ethologists, evolutionists, and cognitive neurobiologists who are the

world’s leading experts in “mind-reading" other species -- will provide a sweeping panorama of what it feels like to

be an elephant, ape, whale, cow, pig, dog, bat, chicken, fish, lizard, lobster, snail: This growing body of facts about

nonhuman sentience has profound implications not only for our understanding of human cognition, but for our

treatment of other sentient species.

Gregory Berns: Decoding the Dog's Mind with Awake Neuroimaging

Gordon Burghardt: Probing the Umwelt of Reptiles

Jon Sakata: Audience Effects on Communication Signals

PANEL 1: Reptiles, Birds and Mammals

WORKSHOP 1: Kristin Andrews: The "Other" Problems: Mind, Behavior, and Agency9

Sarah Brosnan: How Do Primates Feel About Their Social Partners?

Alexander Ophir: The Cognitive Ecology of Monogamy

Michael Hendricks: Integrating Action and Perception in a Small Nervous System

PANEL 2: Primates, Voles and Worms

WORKSHOP 2: Jonathan Birch: Animal Sentience and the Precautionary Principle

Malcolm MacIver: How Sentience Changed After Fish Invaded Land 385 Million Years Ago

Sarah Woolley: Neural Mechanisms of Preference in Female Songbird

Simon Reader: Animal Social Learning: Implications for Understanding Others

PANEL 3: Sea to Land to Air

WORKSHOP 3: Steven M. Wise: Nonhuman Personhood

Tomoko Ohyama: Action Selection in a Small Brain (Drosophila Maggot)

Mike Ryan: "Crazy Love": Nonlinearity and Irrationality in Mate Choice

Louis Lefebvre: Animal Innovation: From Ecology to Neurotransmitters

PANEL 4: Maggots, Frogs and Birds: Flexibility Evolving

SPECIAL EVENT: Mario Cyr: Polar Bears

Colin Chapman: Why Do We Want to Think People Are Different?

Vladimir Pradosudov: Chickadee Spatial Cognition

Jonathan Balcombe: The Sentient World of Fishes

PANEL 5: Like-Mindedness and Unlike-Mindedness

WORKSHOP 5 (part 1): Gary Comstock: A Cow's Concept of Her Future

WORKSHOP 5 (part 2): Jean-Jacques Kona-Boun: Physical and Mental Risks to Cattle and Horses in Rodeos

Joshua Plotnik: Thoughtful Trunks: Application of Elephant Cognition for Elephant Conservation

Lori Marino: Who Are Dolphins?

PANEL 6: Mammals All, Great and Small

Larry Young: The Neurobiology of Social Bonding, Empathy and Social Loss in Monogamous Voles

WORKSHOP 6: Lori Marino: The Inconvenient Truth About Thinking Chickens

Andrew Adamatzky: Slime Mould: Cognition Through Computation

Frantisek Baluska & Stefano Mancuso: What a Plant Knows and Perceives

Arthur Reber: A Novel Theory of the Origin of Mind: Conversations With a Caterpillar and a Bacterium

PANEL 7: Microbes, Molds and Plants

WORKSHOP 7: Suzanne Held & Michael Mendl: Pig Cognition and Why It Matters

James Simmons: What Is It Like To Be A Bat?

Debbie Kelly: Spatial Cognition in Food-Storing

Steve Phelps: Social Cognition Across Species

PANEL 8: Social Space

WORKSHOP 8: To be announced

Lars Chittka: The Mind of the Bee

Reuven Dukas: Insect Emotions: Mechanisms and Evolutionary Biology

Adam Shriver: Do Human Lesion Studies Tell Us the Cortex is Required for Pain Experiences?

PANEL 9: The Invertebrate Mind

WORKSHOP 9: Delcianna Winders: Nonhuman Animals in Sport and Entertainment

Carel ten Cate: Avian Capacity for Categorization and Abstraction

Jennifer Mather: Do Squid Have a Sense of Self?

Steve Chang: Neurobiology of Monkeys Thinking About Other Monkeys

PANEL 10: Others in Mind

WORKSHOP 10: The Legal Status of Sentient Nonhuman Species

https://sites.grenadine.uqam.ca/sites/isc/en/summer18

https://sites.grenadine.uqam.ca/sites/isc/en/summer18/schedule/34/Gregory+Berns%3A+Decoding+the+dog%27s+mind+with+awake+neuroimaging

https://sites.grenadine.uqam.ca/sites/isc/en/summer18/schedule/34/Gregory+Berns%3A+Decoding+the+dog%27s+mind+with+awake+neuroimaging

https://sites.grenadine.uqam.ca/sites/isc/en/summer18/schedule/13/Gordon+Burghardt%3A+Probing+the+Umwelt+of+Reptiles

https://sites.grenadine.uqam.ca/sites/isc/en/summer18/schedule/13/Gordon+Burghardt%3A+Probing+the+Umwelt+of+Reptiles

https://sites.grenadine.uqam.ca/sites/isc/en/summer18/schedule/56/Jon+Sakata%3A+Audience+effects+on+communication+signals

https://sites.grenadine.uqam.ca/sites/isc/en/summer18/schedule/56/Jon+Sakata%3A+Audience+effects+on+communication+signals

https://sites.grenadine.uqam.ca/sites/isc/en/summer18/schedule/60/PANEL%3A++Reptiles%2C+Birds+and+Mammals

https://sites.grenadine.uqam.ca/sites/isc/en/summer18/schedule/40/WORKSHOP%3A+Kristin+Andrews-+The+%22Other%22+Problems%3A+Mind%2C+Behavior%2C+and+Agency_

https://sites.grenadine.uqam.ca/sites/isc/en/summer18/schedule/40/WORKSHOP%3A+Kristin+Andrews-+The+%22Other%22+Problems%3A+Mind%2C+Behavior%2C+and+Agency_

https://sites.grenadine.uqam.ca/sites/isc/en/summer18/schedule/14/Sarah+Brosnan%3A+How+do+primates+feel+about+their+social+partners%3F

https://sites.grenadine.uqam.ca/sites/isc/en/summer18/schedule/14/Sarah+Brosnan%3A+How+do+primates+feel+about+their+social+partners%3F

https://sites.grenadine.uqam.ca/sites/isc/en/summer18/schedule/18/Alexander+Ophir%3A+The+cognitive+ecology+of+monogamy

https://sites.grenadine.uqam.ca/sites/isc/en/summer18/schedule/18/Alexander+Ophir%3A+The+cognitive+ecology+of+monogamy

https://sites.grenadine.uqam.ca/sites/isc/en/summer18/schedule/48/Michael+Hendricks%3A+Integrating+action+and+perception+in+a+small+nervous+system

https://sites.grenadine.uqam.ca/sites/isc/en/summer18/schedule/48/Michael+Hendricks%3A+Integrating+action+and+perception+in+a+small+nervous+system

https://sites.grenadine.uqam.ca/sites/isc/en/summer18/schedule/61/PANEL%3A+Primates%2C+Voles+and+Worms

https://sites.grenadine.uqam.ca/sites/isc/en/summer18/schedule/15/WORKSHOP%3A+Jonathan+Birch%3A+Animal+Sentience+and+the+Precautionary+Principle

https://sites.grenadine.uqam.ca/sites/isc/en/summer18/schedule/15/WORKSHOP%3A+Jonathan+Birch%3A+Animal+Sentience+and+the+Precautionary+Principle

https://sites.grenadine.uqam.ca/sites/isc/en/summer18/schedule/22/Malcolm+MacIver%3A+How+sentience+changed+after+fish+invaded+land+385+million+years+ago

https://sites.grenadine.uqam.ca/sites/isc/en/summer18/schedule/22/Malcolm+MacIver%3A+How+sentience+changed+after+fish+invaded+land+385+million+years+ago

https://sites.grenadine.uqam.ca/sites/isc/en/summer18/schedule/63/Sarah+Woolley%3A+Neural+mechanisms+of+preference+in+female+songbird

https://sites.grenadine.uqam.ca/sites/isc/en/summer18/schedule/63/Sarah+Woolley%3A+Neural+mechanisms+of+preference+in+female+songbird

https://sites.grenadine.uqam.ca/sites/isc/en/summer18/schedule/23/Simon+Reader%3A+Animal+social+learning%3A+Implications+for+understanding+others

https://sites.grenadine.uqam.ca/sites/isc/en/summer18/schedule/23/Simon+Reader%3A+Animal+social+learning%3A+Implications+for+understanding+others

https://sites.grenadine.uqam.ca/sites/isc/en/summer18/schedule/62/PANEL%3A+Sea+to+Land+to+Air

https://sites.grenadine.uqam.ca/sites/isc/en/summer18/schedule/37/WORKSHOP%3A+Steven+M_+Wise%2C+JD%3A++Nonhuman+personhood

https://sites.grenadine.uqam.ca/sites/isc/en/summer18/schedule/37/WORKSHOP%3A+Steven+M_+Wise%2C+JD%3A++Nonhuman+personhood

https://sites.grenadine.uqam.ca/sites/isc/en/summer18/schedule/9/Tomoko+Ohyama%3A+Action+selection+in+a+small+brain+%28Drosophila+maggot%29

https://sites.grenadine.uqam.ca/sites/isc/en/summer18/schedule/9/Tomoko+Ohyama%3A+Action+selection+in+a+small+brain+%28Drosophila+maggot%29

https://sites.grenadine.uqam.ca/sites/isc/en/summer18/schedule/25/Mike+Ryan%3A+%22Crazy+love%22+-+nonlinearity+and+irrationality+in+mate+choice

https://sites.grenadine.uqam.ca/sites/isc/en/summer18/schedule/25/Mike+Ryan%3A+%22Crazy+love%22+-+nonlinearity+and+irrationality+in+mate+choice

https://sites.grenadine.uqam.ca/sites/isc/en/summer18/schedule/51/Louis+Lefebvre%3A+Animal+innovation%3A+from+ecology+to+neurotransmitters

https://sites.grenadine.uqam.ca/sites/isc/en/summer18/schedule/51/Louis+Lefebvre%3A+Animal+innovation%3A+from+ecology+to+neurotransmitters

https://sites.grenadine.uqam.ca/sites/isc/en/summer18/schedule/64/PANEL%3A++Maggots%2C+Frogs+and+Birds%3A+Flexibility+Evolving

https://sites.grenadine.uqam.ca/sites/isc/en/summer18/schedule/64/PANEL%3A++Maggots%2C+Frogs+and+Birds%3A+Flexibility+Evolving

https://sites.grenadine.uqam.ca/sites/isc/en/summer18/schedule/59/SPECIAL+EVENT%3A+Mario+Cyr%3A+Polar+Bears

https://sites.grenadine.uqam.ca/sites/isc/en/summer18/schedule/57/Colin+Chapman%3A+Why+Do+We+Want+to+Think+People+Are+Different%3F

https://sites.grenadine.uqam.ca/sites/isc/en/summer18/schedule/57/Colin+Chapman%3A+Why+Do+We+Want+to+Think+People+Are+Different%3F

https://sites.grenadine.uqam.ca/sites/isc/en/summer18/schedule/46/Vladimir+Pradosudov%3A+Chickadee+spatial+cognition

https://sites.grenadine.uqam.ca/sites/isc/en/summer18/schedule/46/Vladimir+Pradosudov%3A+Chickadee+spatial+cognition

https://sites.grenadine.uqam.ca/sites/isc/en/summer18/schedule/24/Jonathan+Balcombe%3A+The+sentient+world+of+fishes

https://sites.grenadine.uqam.ca/sites/isc/en/summer18/schedule/24/Jonathan+Balcombe%3A+The+sentient+world+of+fishes

https://sites.grenadine.uqam.ca/sites/isc/en/summer18/schedule/65/PANEL%3A+Similarities+and+Differences

https://sites.grenadine.uqam.ca/sites/isc/en/summer18/schedule/65/PANEL%3A+Similarities+and+Differences

https://sites.grenadine.uqam.ca/sites/isc/en/summer18/schedule/38/WORKSHOP+%28part+1%29%3A+Gary+Comstock%3A+A+Cow%27s+Concept+of+Her+Future

https://sites.grenadine.uqam.ca/sites/isc/en/summer18/schedule/38/WORKSHOP+%28part+1%29%3A+Gary+Comstock%3A+A+Cow%27s+Concept+of+Her+Future

https://sites.grenadine.uqam.ca/sites/isc/en/summer18/schedule/84/WORKSHOP+%28part+2%29+Jean-Jacques+Kona-Boun%3A+Physical+and+Mental+Risks+to+Cattle+and+Horses+in+Rodeos

https://sites.grenadine.uqam.ca/sites/isc/en/summer18/schedule/84/WORKSHOP+%28part+2%29+Jean-Jacques+Kona-Boun%3A+Physical+and+Mental+Risks+to+Cattle+and+Horses+in+Rodeos

https://sites.grenadine.uqam.ca/sites/isc/en/summer18/schedule/11/Joshua+Plotnik_+Thoughtful+trunks%3A+Application+of+elephant+cognition+for+elephant+conservation

https://sites.grenadine.uqam.ca/sites/isc/en/summer18/schedule/11/Joshua+Plotnik_+Thoughtful+trunks%3A+Application+of+elephant+cognition+for+elephant+conservation

https://sites.grenadine.uqam.ca/sites/isc/en/summer18/schedule/43/Lori+Marino%3A+Who+cetaceans+are

https://sites.grenadine.uqam.ca/sites/isc/en/summer18/schedule/66/PANEL%3A+Mammals+All%2C+Great+and+Small

https://sites.grenadine.uqam.ca/sites/isc/en/summer18/schedule/20/Larry+Young%3A+The+neurobiology+of+social+bonding%2C+empathy+and+social+loss+in+monogamous+voles

https://sites.grenadine.uqam.ca/sites/isc/en/summer18/schedule/20/Larry+Young%3A+The+neurobiology+of+social+bonding%2C+empathy+and+social+loss+in+monogamous+voles

https://sites.grenadine.uqam.ca/sites/isc/en/summer18/schedule/44/WORKSHOP%3A+Lori+Marino%3A+The+Inconvenient+Truth+About+Thinking+Chickens

https://sites.grenadine.uqam.ca/sites/isc/en/summer18/schedule/44/WORKSHOP%3A+Lori+Marino%3A+The+Inconvenient+Truth+About+Thinking+Chickens

https://sites.grenadine.uqam.ca/sites/isc/en/summer18/schedule/27/Andrew+Adamatzky%3A+Slime+mould%3A+cognition+through+computation

https://sites.grenadine.uqam.ca/sites/isc/en/summer18/schedule/27/Andrew+Adamatzky%3A+Slime+mould%3A+cognition+through+computation

https://sites.grenadine.uqam.ca/sites/isc/en/summer18/schedule/28/Frantisek+Baluska+%28pres_%29+and+Stefano+Mancuso%3A+What+a+Plant+Knows+and+Perceives

https://sites.grenadine.uqam.ca/sites/isc/en/summer18/schedule/28/Frantisek+Baluska+%28pres_%29+and+Stefano+Mancuso%3A+What+a+Plant+Knows+and+Perceives

https://sites.grenadine.uqam.ca/sites/isc/en/summer18/schedule/29/Arthur+Reber%3A+A+novel+theory+of+the+origin+of+mind%3A+Conversations+with+a+caterpillar+and+a+bacterium

https://sites.grenadine.uqam.ca/sites/isc/en/summer18/schedule/29/Arthur+Reber%3A+A+novel+theory+of+the+origin+of+mind%3A+Conversations+with+a+caterpillar+and+a+bacterium

https://sites.grenadine.uqam.ca/sites/isc/en/summer18/schedule/67/PANEL%3A+Microbes%2C+Molds+and+Plants

https://sites.grenadine.uqam.ca/sites/isc/en/summer18/schedule/41/WORKSHOP%3A+Suzanne+Held++and+Michael+Mendl+%3A+Pig+Cognition+and+Why+It+Matters

https://sites.grenadine.uqam.ca/sites/isc/en/summer18/schedule/55/James+Simmons%3A+What+is+it+like+to+be+a+bat%3F

https://sites.grenadine.uqam.ca/sites/isc/en/summer18/schedule/47/Debbie+Kelly%3A+Spatial+cognition+in+Food-Storing

https://sites.grenadine.uqam.ca/sites/isc/en/summer18/schedule/17/Steve+Phelps%3A+Social+Cognition+across+species

https://sites.grenadine.uqam.ca/sites/isc/en/summer18/schedule/68/PANEL

https://sites.grenadine.uqam.ca/sites/isc/en/summer18/schedule/82/WORKSHOP%3A+To+be+announced

https://sites.grenadine.uqam.ca/sites/isc/en/summer18/schedule/50/Lars+Chittka%3A+The+Mind+of+the+Bee

https://sites.grenadine.uqam.ca/sites/isc/en/summer18/schedule/49/Reuven+Dukas%3A+Insect+emotions%3A+mechanisms+and+evolutionary+biology

https://sites.grenadine.uqam.ca/sites/isc/en/summer18/schedule/49/Reuven+Dukas%3A+Insect+emotions%3A+mechanisms+and+evolutionary+biology

https://sites.grenadine.uqam.ca/sites/isc/en/summer18/schedule/89/Adam+Shriver%3A+What+Do+Human+Lesion+Studies+Tell+Us+About+the+Claim+that+the+Cortex+is+Required+for+Pain+Experiences%3F

https://sites.grenadine.uqam.ca/sites/isc/en/summer18/schedule/89/Adam+Shriver%3A+What+Do+Human+Lesion+Studies+Tell+Us+About+the+Claim+that+the+Cortex+is+Required+for+Pain+Experiences%3F


https://sites.grenadine.uqam.ca/sites/isc/en/summer18/schedule/72/WORKSHOP%3A+Delcianna+Winders%3A+Nonhuman+animals+in+sport+and+entertainment

https://sites.grenadine.uqam.ca/sites/isc/en/summer18/schedule/72/WORKSHOP%3A+Delcianna+Winders%3A+Nonhuman+animals+in+sport+and+entertainment

https://sites.grenadine.uqam.ca/sites/isc/en/summer18/schedule/45/Carel+ten+Cate%3A+Avian+capacity+for+categorization+and+abstraction

https://sites.grenadine.uqam.ca/sites/isc/en/summer18/schedule/45/Carel+ten+Cate%3A+Avian+capacity+for+categorization+and+abstraction

https://sites.grenadine.uqam.ca/sites/isc/en/summer18/schedule/52/Jennifer+Mather%3A+Do+squid+have+a+sense+of+self%3F

https://sites.grenadine.uqam.ca/sites/isc/en/summer18/schedule/36/Steve+Chang%3A+Neurobiology+of+Monkeys+Thinking+About+Other+Monkeys

https://sites.grenadine.uqam.ca/sites/isc/en/summer18/schedule/36/Steve+Chang%3A+Neurobiology+of+Monkeys+Thinking+About+Other+Monkeys


https://sites.grenadine.uqam.ca/sites/isc/en/summer18/schedule/30/WORKSHOP%3A+Animal+Sentience%3A+The+Legal+Status+of+Nonhuman+Species

https://sites.grenadine.uqam.ca/sites/isc/en/summer18/schedule/30/WORKSHOP%3A+Animal+Sentience%3A+The+Legal+Status+of+Nonhuman+Species