ACTAUNIVERSITATIS

UPSALIENSISUPPSALA

2019

Digital Comprehensive Summaries of Uppsala Dissertationsfrom the Faculty of Social Sciences 174

Innate and Conditioned Fear

Investigating Responses to Threat usingPsychophysiology, Functional Magnetic ResonanceImaging, and Twin Methodology

JÖRGEN ROSÉN

ISSN 1652-9030ISBN 978-91-513-0804-3urn:nbn:se:uu:diva-395864

Dissertation presented at Uppsala University to be publicly examined in Betty Pettersson,Blåsenhus, von Kraemers Allé 1A, Uppsala, Thursday, 12 December 2019 at 10:15 for thedegree of Doctor of Philosophy. The examination will be conducted in English. Facultyexaminer: Doctor Miguel Fullana (Hospital Clinic de Barcelona, University of Barcelona).

AbstractRosén, J. 2019. Innate and Conditioned Fear. Investigating Responses to Threat usingPsychophysiology, Functional Magnetic Resonance Imaging, and Twin Methodology. DigitalComprehensive Summaries of Uppsala Dissertations from the Faculty of Social Sciences 174.67 pp. Uppsala: Acta Universitatis Upsaliensis. ISBN 978-91-513-0804-3.

Evolution has shaped systems in the human brain to respond to danger. Some of thesesystems are innate or hard-wired, while others are learned throughout the entire life span.One commonly studied type of learned threat, conditioned fear, is acquired from experiencingaversive consequences. When considering innate threat, processing imminent and social threatmay be especially relevant for understanding the neural circuitry of human fear. Imminentfear refers to experiencing proximal encounters whereas social fear refers to exposure toan unknown conspecific. Investigating whether different brain systems process innate andconditioned threat could provide us with knowledge on how defensive systems interact andinform on development and treatment of fear-related disorders. The first aim of this thesis wasto investigate whether different brain systems process innate and conditioned threat. The secondaim was to investigate if neural functions supporting imminent and social threat are heritable.In Study I, skin conductance responses (SCR) to social, imminent and conditioned threatdisplayed in immersive virtual-reality were compared. The results showed that social threatmodulated imminent threat, but neither imminent nor social threat modulated conditioned threat,indicating that distinct processes regulate imminent and social threat on one end and conditionedthreat on the other. Study II compared SCR to imminent and conditioned threat displayedeither in an immersive virtual-reality head-mounted display or a regular computer monitor. Thefindings indicated that displaying stimuli in an immersive virtual-reality head-mounted displayenhanced imminent threat responses as compared to displaying them on a regular computermonitor, suggesting a modulation of SCR by display type. Conditioned SCR was similar acrossdisplays. The conclusion of the study was that imminent threat and conditioned threat aredifferent processes as it was possible to modulate one without affecting the other. Study IIIwas a twin study comparing the genetic influence on neural responses to imminent and socialthreat using functional magnetic resonance imaging (fMRI) and SCR. The results demonstratedstrong genetic influence on responses in the lateral occipital cortex and the fusiform cortexto social threat whereas genetic influence on imminent threat was strong in early visual areasand occipito-parietal areas. In summary, innate and conditioned fear may depend on separateprocesses in the brain. Innate threat activates early visual areas, indicating a role for these areas inthreat processing. Genetic influences on fMRI responses to social and imminent threat suggeststhat separate pathways may have evolved to process these threats.

Keywords: Emotion, Imminent threat, Social threat, Twins, Face, Personal space, fMRI,Virtual reality, Amygdala.

Jörgen Rosén, Department of Psychology, Box 1225, Uppsala University, SE-75142 Uppsala,Sweden.

© Jörgen Rosén 2019

ISSN 1652-9030ISBN 978-91-513-0804-3urn:nbn:se:uu:diva-395864 (http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-395864)

Till MorTack för allt ditt stöd

List of Papers

This thesis is based on the following papers, which are referred to in the text by their Roman numerals.

I Rosén, J. Kastrati, G & Åhs, F. (2017) Social, proximal and con-

ditioned threat. Neurobiology of Learning and Memory, (142), 236–243.

II Rosén, J. Kastrati, G. Reppling, A. Bergkvist K & Åhs, F. (2019) The effect of immersive virtual reality on proximal and condi-tioned threat. Under review.

III Rosén, J. Kastrati, G. Kuja-Halkola, R. Larrson, H & Åhs, F. (2019) Genetic influence on brain function supporting imminent and social threat. Manuscript.

Reprints were made with permission from the respective publishers.

Additional scientific work not included in the thesis

1. Ahs, F. Rosén J. Kastrati, G. Fredrikson, M. Agren, T & Lundstrom, J. N. (2018). Biological preparedness and resistance to extinction of skin conductance responses conditioned to fear relevant animal pic-tures: A systematic review. Neuroscience Biobehavioral Reviews, (95), 430-437.

2. Juvrud, J. Gredebäck, G. Åhs, F. Lerin, N. Nyström, P. Kastrati, G & Rosén, J (2018). The immersive Virtual Reality Lab: Possibilities for Remote Experimental Manipulations of Autonomic Activity on a Large Scale. Frontiers in Neuroscience, (12), 305.

3. Bejerot, S. Lindgren, A. Rosén, J. Bejerot, E. Elwin, M. (2019) Teaching psychiatry to large groups in society. BMC Medical Educa-tion, (19), 148.

Contributions

The contribution of Jörgen Rosén to the studies was as follows: Study I: Designed and planned the study in collaboration with main supervi-sor. Created the stimuli and parts of the tools for data collection. Collected the data, performed the statistical analyses and wrote the main manuscript in col-laboration with main supervisor and co-authors. Study II: Designed and planned the study in collaboration with main super-visor and co-authors. Created the stimuli, supervised two master students as they collected data in collaboration with co-authors. Performed the statistical analyses and wrote the manuscript with contributions from main supervisor and co-authors. Study III: Designed and planned the study in collaboration with main super-visor and co-authors. Created the stimuli and parts of the software used for data collection in the MR scanner and collected data in collaboration with co-authors. Developed tools for data analyses, performed data analyses in collab-oration with co-authors, and wrote the manuscript with contributions from main supervisor and co-authors.

Contents

Introduction ................................................................................................... 13 Innate systems and behavior..................................................................... 13 Innate fear ................................................................................................. 14

Neural substrates of innate fear ........................................................... 15 Imminent threat .................................................................................... 17 Social threat ......................................................................................... 19

Conditioned fear ....................................................................................... 21 Neural substrates of conditioned fear .................................................. 22 Extinction of fear ................................................................................. 23

A comparison of neural mechanisms underlying innate and conditioned fear ............................................................................................................ 23

Genetic influence on innate and conditioned fear ............................... 26

Aims .............................................................................................................. 28

Methods ........................................................................................................ 29 Skin conductance response ....................................................................... 29 fMRI ......................................................................................................... 29 Twin method ............................................................................................ 30 Ethical statement ...................................................................................... 30

Summary of studies ....................................................................................... 31 Study I ...................................................................................................... 31

Background and aim ............................................................................ 31 Methods ............................................................................................... 31 Results ................................................................................................. 32 Discussion ............................................................................................ 35

Study II ..................................................................................................... 36 Background and aim ............................................................................ 36 Method ................................................................................................. 36 Results ................................................................................................. 36 Discussion ............................................................................................ 39

Study III ................................................................................................... 40 Background and aim ............................................................................ 40 Methods ............................................................................................... 40 Results ................................................................................................. 41 Discussion ............................................................................................ 43

General discussion ........................................................................................ 44 Main findings ........................................................................................... 44 Discussion ................................................................................................ 44 Limitations ............................................................................................... 47 Future directions ....................................................................................... 48 Concluding remarks ................................................................................. 50

Acknowledgements ....................................................................................... 51

References ..................................................................................................... 53

Abbreviations

ACC Anterior cingulate cortex aMCC Anterior midcingulate cortex ANS Autonomic nervous system AOS Accessory olfactory system BA Basal amygdala BLA Basolateral amygdala BNST Bed nucleus of the stria terminalis CeA Central nucleus of the amygdala CR Conditioned response CS Conditioned stimulus CS- Conditioned stimulus, non-reinforced CS+ Conditioned stimulus, reinforced dACC Dorsal anterior cingulate cortex fMRI Functional magnetic resonance imaging FPS Fear potentiated startle HR Heart rate LA Lateral amygdala LGN Lateral geniculate body MeA Medial amygdala MHDS Medial hypothalamic defensive system MOS Main olfactory system MPN Medial preoptic nucleus PAG Periaqueductal grey PMD Premammilary nucleus SC Superior colliculus SCR Skin conductance response sgACC Subgenual anterior cingulate cortex US Unconditioned stimulus

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Introduction

Evolutionary processes have shaped systems in the human brain to respond to dangers. Some of these systems are critical for our survival and become innate. A defining characteristic of innate systems is that they are present and func-tional at birth or develop early. This stands in contrast to systems that require learning, or conditioning, before eliciting defensive responses. Responses to conditioned threat have been extensively studied and are commonly consid-ered the basis for human fear research. However, knowledge concerning in-nate threat circuits in humans is limited. Investigating whether different brain systems process innate and conditioned threat could provide us with knowledge on how defensive systems interact and inform on development and treatment of fear-related disorders.

The following introduction examines findings on innate fear both in ani-mals and humans. A comparison between innate and conditioned fear is also discussed with an emphasis on translational models for human fear research.

Innate systems and behavior To survive, living organisms must develop biological systems capable of ad-aptation. Adaptation refers to the ability with which living organisms regulate internal states as a response to the environment with the purpose of maintain-ing high fitness, which in turn facilitates procreation and transfer of genetic material from one generation to the next. Hence, living organisms proficient at this task contribute to a larger variety of genetic material in the evolutionary tree of their species, making certain traits more common in the population.

Some of these biological systems are innate and must be ready before the organism faces the challenges of life. In humans, this usually corresponds with birth but may also be delayed to a later developmental stage. The human body is equipped with many different types of innate systems. One example is the immune system. It employs various defensive barriers to shield us from infections using antigens, blood chemicals and specialized cells that attack foreign matter. The innate functions of these systems (like creating antigens) are expressed the moment they become active (Alberts et al., 2002).

An important function of innate brain systems is to control instinctive be-haviors. These are similar to reflexes, but the difference is that innate systems involve more complex discriminatory processes and recruit a larger selection

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of brain regions (Blumberg, 2017). In animals, there are many types of in-stinctive behaviors intended to facilitate survival (De Franceschi, Vivattanasarn, Saleem, & Solomon, 2016; Dill, 1974; Evans, Macedonia, & Marler, 1993). Two of the most well-studied behaviors are the escape and freezing responses triggered by proximal predators (Blanchard, Blanchard, Rodgers, & Weiss, 1990; De Franceschi et al., 2016; Yilmaz & Meister, 2013). Escape and freezing behaviors are believed to have evolved in environments where predatory encounters were common (Blanchard et al., 1990) and they can also be found in humans (Schmidt, Richey, Zvolensky, & Maner, 2008). A special characteristic of most instinctive defensive behaviors is that they are typically hard-wired to a specific class of stimuli (Dill, 1974; Evans et al., 1993; Tammero & Dickinson, 2002). An example is the flight behavior ob-served in some insects as a result of looming threat (Card, 2012). Instinctive behaviors can be modulated depending on certain stimulus-properties such as threat intensity (Blanchard et al., 1990; Fanselow & Lester, 1988; McNaughton & Corr, 2004), access to food (Bellman & Krasne, 1983; Bracker et al., 2013; Ghosh et al., 2016) or prior experiences (Dill, 1974; Rodgers, Melzack, & Segal, 1963). Although there is evidence suggesting that instinctive behaviors exhibit flexibility based on learning in mice (Vale, Evans, & Branco, 2017), modulated by access to food or previously encoun-tered predators, the exact relationship between learned and instinctive behav-ior is unclear.

In sum, innate systems are important for regulating internal states and in-stinctive behaviors in living organisms. All these behaviors are critical for sur-vival and are inherited from one generation to the next. Genetically influenced behaviors can be found in most living creatures and studying them can help us identify common neural determinants.

Innate fear Fear refers to the human emotion associated with the conscious feeling of be-ing afraid. In neuroscience, fear is often used to explain the defensive response as a result of perceived harm or danger (i.e. threat). The term is also commonly used in explanations of how neural circuitry moderates defensive responses to threatening stimuli. Defensive responses to perceived danger, or threat, can result in fear, but it is not known if the emotional component associated with fear is shared across species (LeDoux, 2012). Therefore, descriptions of fear in this thesis will refer to the defensive response and not the associated emo-tion.

Innate fear can be summarized as a defensive response triggered by specific stimuli (Blanchard & Blanchard, 1989). Importantly, this defensive response can be triggered without any prior experience or learning. There are many types of innate fears including predatory fear, fear of same-species interaction

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(social threat), fear of sudden proximal encounters (imminent threat) and fear of bodily harm. Some of these innate fears are shared across species, such as predatory and imminent fear (Dill, 1974; Hirsch & Bolles, 1980; Mitchell, Chivers, McCormick, & Ferrari, 2015; Yilmaz & Meister, 2013), indicating shared ancestry for these defensive responses. Fear of same-species interac-tion is primarily found in social species (Debiec & Olsson, 2017; Toth & Neumann, 2013). A possible explanation for this is that unknown encounters of the same species could represent a potential threat, thus survival is depend-ent on the ability to distinguish between threatening and non-threatening so-cial encounters. Since fear of social threat is innate, defensive responses can be observed in human infants (Brooker et al., 2013). This is also the case for imminent threat, as infants showed defensive behavior to sudden appearances of proximal objects (Ball & Tronick, 1971).

Innate fear circuits are important for regulating defensive behavior. For in-stance, behavior such as fight or flight can be triggered by stimuli signaling threat in both humans and animals (Roelofs, 2017a). Normally, these behav-iors are motivated by external stimuli, but they can also be regulated by inter-nal physiological factors. For example, in mice the defensive response to looming stimuli is accelerated by stress hormones (Li et al., 2018) and in flies hunger can increase the frequency of risk-taking behavior (Bracker et al., 2013; Whitham & Mathis, 2000). These examples illustrate the importance of understanding internal biological systems when examining the relationship between innate threat and defensive responses. Hence, I will now review lit-erature relevant to discussing the underlying neural mechanisms governing innate fears.

Neural substrates of innate fear Almost everything we know about innate fear is based on fear models created by research on rodents. Here the most commonly studied innate fears include predatory fear, fear of same species interaction and fear of pain or suffocation. These fears are signaled to the brain via a sensory unit that can detect threat based on modalities such as olfactory (smell), auditory, vision and nociception (pain stimulation) (Silva, Gross, & Graff, 2016). In turn, neural circuitry pro-cesses these sensory modalities through an integrative threat circuit that can trigger stereotypical defensive responses. The circuitry associated with these defensive behaviors is believed to originate from areas in the amygdala and the periaqueductal grey (PAG) (Fanselow, 1994). In particular, the PAG is believed to be a key structure for moderating defensive behaviors (Silva, Gross, & Graff, 2016).

Since rodents depend on smell to navigate in their environment, olfactory systems received a lot of attention in predatory research. Here a subset of odorants been linked to innate defensive responses (Stowers & Kuo, 2015). These odors include secretion from bodily fluids such as urine, feces or saliva

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from predators like felines and snakes (Isogai et al., 2011). It has also been discovered that innate defensive behaviors can be triggered by olfactory sen-sory units capable of detecting single molecules commonly found in predator feces (Rosen, Asok, & Chakraborty, 2015). Detection of odorants is primarily handled by two systems, the main olfactory system (MOS) and the accessory olfactory system (AOS). The MOS handles a wide variety of odors and is be-lieved to be connected to the main olfactory bulb. AOS on the other hand senses pheromones and serves specialized functionality associated with social behavior (Dulac & Torello, 2003). Studies of the MOS innate circuitry shows that it is involved in signaling predators by molecular detection (Rosen et al., 2015). Other areas associated with olfactory-induced fears have also been identified and include the bed nucleus of the stria terminalis (BNST) (Fendt, Endres, & Apfelbach, 2003), the lateral septum (Endres & Fendt, 2008) and the central amygdala (Isosaka et al., 2015). It is important to note that olfactory systems can also signal danger indirectly from injured or stressed conspecif-ics. This is accomplished by alarm pheromones detected by the Gruenberg ganglion, a subunit of the main olfactory bulb (Brechbuhl, Klaey, & Broillet, 2008).

Defensive behaviors to visual threat cues have also been extensively stud-ied in rodents. Findings here suggest that defensive behavior including freez-ing and escape can be caused by looming shadows in the upper visual field (Yilmaz & Meister, 2013). These results have been obtained in laboratory set-tings using circle shadows to simulate aerial predators. Interestingly, defen-sive behaviors associated with visual threat show a greater degree of rigidity compared to behavior induced by olfactory threat, indicating that visual threats may have higher priority (Apfelbach, Blanchard, Blanchard, Hayes, & McGregor, 2005; Yilmaz & Meister, 2013). A possible explanation for this finding is that olfactory systems are specialized for detecting distant threats while visual systems also permit identification of imminent threats. Due to the relatively quick response rate for defensive behaviors associated with visual threats most of the processing is believed to take place in areas around the brain stem. One region in particular, the superior colliculus (SC), is suggested to be important for visual threat detection (Shang et al., 2015; Zhao, Liu, & Cang, 2014). This has been demonstrated in one study where it was found that the area V1 of the primary visual cortex communicates with the SC for loom-ing stimuli (Liang et al., 2015). The findings from Liang et al. (2015) demon-strate that areas in the primary visual cortex are important for driving innate defensive behavior.

Only a few studies have investigated the connection between innate defen-sive behavior and auditory cues. One study discovered that mice react with flight or freeze behavior to certain ultrasonic tones (Mongeau, Miller, Chiang, & Anderson, 2003). Here the defensive response was influenced by connec-tions between the inferior colliculus and the dorsal PAG. This finding is in line with a later study using optogenetics to study neural pathways between

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auditory cortex and areas around the brainstem (Xiong et al., 2015). In this study, it was discovered that auditory cues facilitated responses in the PAG.

Another commonly used method to study defensive responses in rodents is pain stimulation. Here the basolateral amygdala (BLA) has been identified as central for driving defensive behavior (Tovote, Fadok, & Luthi, 2015). It is important to note that pain stimulation in rodent research has been focused mainly on the creation of fear memories. As such, the innate component of nociceptive stimulation driving defensive behavior is not well understood. Although some studies found limited evidence suggesting pain information is sent from the spino-thalamic tract to neurons in the posterior intralaminar tha-lamic nucleus which in turn project to BLA (Asede, Bosch, Luthi, Ferraguti, & Ehrlich, 2015; Bienvenu et al., 2015). However, these findings have been contested by lesion studies in those areas where it was discovered that fear learning to electric foot shocks was intact (Brunzell & Kim, 2001; Herry & Johansen, 2014; Lanuza, Moncho-Bogani, & Ledoux, 2008). An alternative route for pain-instructed fear learning has been suggested by Johansen et al. (2010) where the BLA receives input from the PAG triggered by nociceptive signals projected from the spinal and trigeminal dorsal horn (Johansen, Tarpley, LeDoux, & Blair, 2010). Furthermore, it has also been demonstrated that pain can be directly detected by the central nucleus of the amygdala (CeA) by nociceptive signals from the parabrachial nucleus (Bernard & Besson, 1990).

Findings also indicate that the PAG is important for eliciting innate defen-sive responses to respiratory distress (Casanova, Contreras, Moya, Torrealba, & Iturriaga, 2013; Ricardo & Koh, 1978). This has been demonstrated in one animal study where electrical stimulation of the PAG induced panic-like be-haviors associated with asphyxiation (Schimitel et al., 2012). Because of this, the structure has received attention in translational research focused on panic disorders (Schenberg et al., 2014).

In conclusion, innate defensive responses can be triggered by signals from olfactory, visual, auditory, nociceptive and respiratory systems, indicating the possibility for shared pathways for threat detection across many different sen-sory modalities. Neural circuitry important for eliciting defensive behaviors originate in efferents from the amygdala and the PAG. Notably, the PAG is considered a key structure for eliciting innate defensive responses. I will now discuss a selected group of innate threats that have received attention in human fear research.

Imminent threat Fear of proximal encounters, or imminent threat, is a highly adaptive type of fear. The term imminent threat, or threat imminence as is often used in animal literature (Blanchard & Blanchard, 1989), refers to threatening proximal en-

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counters capable of triggering a defensive response. Theories on threat immi-nence postulate that distance to threat is a strong determinant for how an or-ganism will respond during threatening conditions (Blanchard & Blanchard, 1989; Fanselow, 1994). Indeed, behavioral adaptation in animals such as in-creased freezing can often be observed when threat is near (Blanchard, 1997; Blanchard & Blanchard, 1989). Furthermore, whereas a distant threat may elicit a more general state of attention, imminent threat focuses the attention towards the specific threatening stimuli. This suggests that defensive behav-iors are moderated by a neural circuitry capable of distance detection.

Typically, vision is used to detect imminent threat (Yilmaz & Meister, 2013), although auditory (Hersman & Anthony, 2018) and olfactory (Rosen et al., 2015) inputs can also signal nearby threat and elicit the proper defensive responses. This is accomplished by the fact that the fear circuitry responsible for eliciting defensive responses is shared across many different sensory mo-dalities (Gross & Canteras, 2012). As mentioned previously, there is evidence suggesting that areas early in the visual stream are important for eliciting de-fensive responses to visual threat (Liang et al., 2015; Shang et al., 2015). Spe-cifically, the SC appears to be important for distance detection in cats (Bergeron, Matsuo, & Guitton, 2003) and for visually-induced defensive be-haviors in mice (Ito & Feldheim, 2018). Studies also demonstrated that the SC can handle input from multiple regions in the primary visual cortex and that it is responsible for projecting to common fear circuitry such as the amygdala (Shang et al., 2015). In humans, the SC has been found to receive layer spe-cific input from the lateral geniculate nucleus (LGN) during visual stimulation (Zhang, Zhou, Wen, & He, 2015). However, there is no direct evidence linking SC to defensive responses in humans, although one study in primates showed that the amygdala can modulate defensive behaviors evoked from the SC (Forcelli et al., 2016), indicating a possibility for similar functionality in hu-mans. Taken together, these findings suggest that the SC is important for fa-cilitating defensive responses to imminent threat in rodents and to some extent in non-human primates, whereas its importance in humans still needs to be established.

Imminent threat research on humans received limited attention. In one study it was found that spatial proximity modulates fear potentiated startle, indicating a modulation of the defensive response by egocentric distance to threat (Ahs, Dunsmoor, Zielinski, & LaBar, 2015). There is also evidence suggesting that distance to threat modulates the subjective degree of dread and decreased confidence of escape (Mobbs et al., 2007). In the study by Mobbs et al. (2007) it was found that when subjects were chased through a maze by a virtual predator, fear ratings correlated with activity in the PAG. It was also demonstrated that activity in the PAG was associated with proximal encoun-ters, while distant encounters engaged neural circuitry in the ventromedial pre-frontal cortex (vmPFC). A later study also found activation in the amygdala, the BNST, insula, striatum and the PAG in response to the perceived threat

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from a proximal tarantula (Mobbs et al., 2010). A more recent study corrobo-rated these findings for imminent threat where the PAG, insula and dorsal an-terior cingulate cortex (dACC) were activated in response to location-specific threat (Suarez-Jimenez et al., 2018). In addition, activation of an adjacent structure to the ACC, the subgenual anterior cingulate cortex (sgACC), has been found to correlate positively to proximal snakes (Nili, Goldberg, Weizman, & Dudai, 2010).

Social threat Fear of same species interaction, or social threat, is a commonly studied type of fear in social species. Its general purpose is to protect from harm during social encounters. Social threat can facilitate a wide variety of defensive be-haviors that vary depending on species. For instance, rodents exhibit defensive escape behavior to aggressive conspecifics or hostility during sexual compe-tition (Motta et al., 2009). This mix of behaviors can be explained by the fact that fear circuits mediating defensive responses to social threat have been found to overlap with regions that are associated with aggression and sexual behavior. Commonly, these regions have been reported to include the medial preoptic nucleus (MPN), ventrolateral portion of the ventromedial hypothala-mus, the ventral premammillary nucleus and the dorsal premammillary nu-cleus (Kollack-Walker & Newman, 1995; Lin et al., 2011a; Motta et al., 2009; Yang et al., 2013). Note that these fear circuits are separate from the ones governing innate defensive responses to predatory fear or pain stimulation (Motta et al., 2009; Silva et al., 2013). In addition, there is also evidence sug-gesting that the PAG is activated by social threat (Motta et al., 2009).

An important brain region found to be associated with social threat in both humans and primates is the amygdala (Amaral, 2002, 2003; Ohman, 2009; Prather et al., 2001). The amygdala received a great deal of attention in human fear research (Ohman, 2005), particularly related to social phobias (Freitas-Ferrari et al., 2010), as the region is believed to be important for facilitating defensive responses to social encounters and for understanding related anxiety disorders. It is important to note that the neural mechanisms behind social fear also includes fear learning and not just innate threat responses (Debiec & Olsson, 2017). However, that is not the focus of this thesis; hence, the material presented will cover the innate component, or non-conscious processing of social threat.

A commonly used method when investigating defensive responses to social threat in humans is to use pictures of faces as it is suggested that some facial expressions can exert dominance and facilitate fear (Ohman & Mineka, 2001). In line with this, lesion studies demonstrated that amygdala damage impaired recognition of emotion in facial expressions (Adolphs, Tranel, Damasio, & Damasio, 1994; Anderson, Spencer, Fulbright, & Phelps, 2000; Young et al., 1995). Furthermore, there is evidence for amygdala activation to pictures of

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angry faces, (Mattavelli et al., 2014; Sanchez et al., 2015), suggesting innate processing of social threat.

As mentioned previously, animals can exhibit defensive behaviors to social threat. Similar behaviors have also been reported in humans in response to facial expressions (Roelofs, Hagenaars, & Stins, 2010). In the study by Roe-lofs et al. (2010) participants viewed pictures of faces with angry, happy or neutral expressions. While the participants were looking at the pictures, their body sway was recorded using a force feedback platform. It was found that angry faces (compared to neutral and happy) induced significantly less body sway, indicating freeze behavior. This has since been replicated in a more re-cent study (Noordewier, Scheepers, & Hilbert, 2019). These findings impli-cate that freezing behavior, which is typically associated with fear and is com-monly believed to facilitate perceptual and attention processes (Bradley, 2009; Bradley, Codispoti, Cuthbert, & Lang, 2001; Lang, Davis, & Ohman, 2000), may be a cross-species defensive behavior in response to social threat.

In addition, studies have identified important brain regions connected to threat and facial expressions. One area in particular, the fusiform gyrus, was found to facilitate amygdala responses to emotional faces in non-clinical sam-ples (Petrovic, Kalisch, Pessiglione, Singer, & Dolan, 2008; Pujol et al., 2009). Other areas connected to amygdala activation in response to facial presentations have also been found to include the superior temporal sulcus and the inferior temporal gyrus (Miyahara, Harada, Ruffman, Sadato, & Iidaka, 2013). An interesting finding in the study by Miyahara et al. (2013) was that the difference in perceived threat between angry and neutral faces was not reflected by the activation pattern found in the amygdala. This could be related to general attentional processes as the fusiform gyri has also been discovered to be an important region for face processing (Grill-Spector, Knouf, & Kanwisher, 2004; Grill-Spector, Weiner, Kay, & Gomez, 2017). Also, a recent study discovered that activation of the amygdala correlated with greater pre-ferred distance to angry, fearful and sad facial expressions (Vieira, Tavares, Marsh, & Mitchell, 2017). This was accompanied by activation in dorsome-dial prefrontal and orbitofrontal cortices and inferior frontal gyrus for angry and happy expressions.

In humans, there is limited evidence suggesting a link between threat im-minence and social threat (Kennedy, Glascher, Tyszka, & Adolphs, 2009). In the study by Kennedy et al. (2009) it was discovered that an individual with amygdala lesions had no sense of personal space. Contrasting this, healthy individuals showed amygdala activation when their personal space was in-truded upon. This finding indicates that the amygdala may play an important role for regulating interpersonal distance to social encounters.

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Conditioned fear In contrast to innate fear, conditioned fear is an associative form of fear learn-ing that enables living beings to make predictions based on threat cues. Thus, fear learning is important for survival and stands as a prominent example of a cross-species defensive mechanism shaped by evolutionary processes (LeDoux, 2000). In humans, conditioned fear and its underlying neurological systems received a lot of attention, as it is commonly believed that fear learn-ing influences phobias and other anxiety related disorders (Ohman & Mineka, 2001). To understand the process with which fear is acquired, I will begin by discussing a popular method used in research to create fear memories.

In classic conditioning, a previously neutral stimulus is associated with a biologically relevant unconditioned stimulus (US) that in turn activates a re-flexive unconditioned response (UR). By repeated pairings of the US and neu-tral stimulus, the organism learns to predict that the neutral stimulus is fol-lowed by a physiological response (or conditioned response, CR) and conse-quently the previously neutral stimulus becomes a conditioned stimulus (CS). This process was originally documented by Pavlov in an experiment on dogs (Pavlov, 1927). During the experiment, a sound cue was used as a neutral stimulus and food as US, resulting in a salivary response (UR). After repeated pairings, the sound cue alone produced a salivary response (CR), thus creating a connection between CS and US.

Fear conditioning operates by the same principles as other forms of classic conditioning, except that the CS is associated with threat. In rodents, a popular method to study fear conditioning is to use electric shock (US) and sound (CS). After repeated pairings, the stimuli signaling threat (sound as CS) is fol-lowed by a defensive response, such as escape or freezing (CR). This form of fear learning is commonly referred to as cued fear conditioning (Wehner & Radcliffe, 2001). In addition to cued fear learning, fear can also be associated with a context, such as a specific environment (Shoji, Takao, Hattori, & Miyakawa, 2014).

Research on conditioned fear usually employs differential conditioning. During differential fear conditioning, a neutral conditioned stimulus (CS+) is paired with an aversive unconditioned stimulus (US) so that the CS+ is asso-ciated with fear, whereas the control cue is never paired with the aversive un-conditioned stimulus (CS-) (Duits et al., 2015). This way, the CS- predicts the non-occurrence of US and becomes the safety cue.

In humans, fear conditioning commonly involves repeated pairings of vis-ual cues and electrical shocks to induce fear. In combination with these re-peated pairings, measurement of physical arousal is typically used to index the defensive response to CS. Popular methods to index fear learning include skin conductance response (SCR), fear potentiated startle (FPS) and heart rate (HR). These methods assess indices of autonomic nervous system (ANS) ac-

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tivation based on electrodermal (sweat gland secretion), reflex or cardiovas-cular (circulatory system) responses (Critchley, Elliott, Mathias, & Dolan, 2000; Davis, Falls, Campeau, & Kim, 1993; Robinson, Epstein, Beiser, & Braunwald, 1966). Activation of the ANS, in particular the sympathetic nerv-ous system, is associated with defensive behaviors to threat in animals and humans (Roelofs, 2017b). In sum, fear conditioning is a simple and effective method to study fear and anxiety related disorders and its associated memory processes (Davis et al., 1993; LeDoux, 2000).

Neural substrates of conditioned fear Acquisition of fear memories is thought to be dependent on distributed neural circuitry that includes sensory pathways and deep cortical structures such as the amygdala. In turn, the amygdala projects to neural circuitry responsible for eliciting the proper defensive responses. These pathways and the associ-ated neural circuitry governing fear memories have received extensive atten-tion in rodent research. Here the amygdala has been identified as one of the most important brain areas for facilitating associative fear memories (LeDoux, 2000). Typically, the amygdala is divided into three subregions; the lateral (LA), central (CeA) and the basal amygdala (BA), sometimes referred to as the basolateral amygdala (BLA).

The LA region is believed to be a key component in the neural circuitry serving fear conditioning. It is responsible for processing input from various sensory pathways routed through the thalamus. These pathways are thought to converge in the LA, forming the CS-US association. The LA then projects to the CeA that is considered the main output unit of the amygdala with con-nections to a wide variety of areas, including the hypothalamus, BNST and the PAG (Pape & Pare, 2010).

The connections between sensory inputs and amygdala nuclei have been studied in rats, where lesion studies demonstrated that the LA and CeA atten-uate freezing to contextual and auditory conditioned stimuli (Goosens & Maren, 2001). This functionality is further hindered by lesions located in the BA, which is believed to be important for contextual and auditory fear condi-tioning (Goosens & Maren, 2001). Although some studies demonstrated that the BA is not necessary for long-term development of contextual fear memo-ries (Fanselow & Gale, 2003; Gale et al., 2004), findings indicate that the structure is important for the formation of memories related to cued fear con-ditioning (Laurent, Marchand, & Westbrook, 2008; Vazdarjanova & McGaugh, 1998).

For contextual fear learning, there are a few more areas worth mentioning. One is the CA3 of the hippocampus, which is believed to be associated with spatial fear memory encoding (Gilbert & Brushfield, 2009) and delay (over-lapped CS and US) or trace (no overlap) conditioning (Beylin et al., 2001;

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McEchron & Disterhoft, 1999). Also important are areas in the medial pre-frontal cortex and nucleus accumbens. These regions are part of the meso-limbic dopamine projection system originating in the ventral tegmental area (Pezze & Feldon, 2004).

In humans, a limited amount of lesion studies demonstrated that the amyg-dala is important for fear learning (Bechara et al., 1995; Hamm & Weike, 2005; LaBar, LeDoux, Spencer, & Phelps, 1995). Although a recent meta-analysis investigating results from fMRI studies in humans found no evidence of amygdala activation during fear conditioning (Fullana et al., 2016). How-ever, several other areas were identified as being important for fear condition-ing. These included the thalamus, hippocampus and sub-cortical structures around the brain stem, such as the PAG. Other areas found to be activated during fear conditioning were the ACC and anterior insula (Greco & Liberzon, 2016b). It is believed that the ACC is important for expression of fear, as this area has been found to correlate with measures of physiological arousal (SCR) (Greco & Liberzon, 2016a; Shin & Liberzon, 2010).

Extinction of fear Extinction of fear can occur when the conditioned stimulus is followed by a non-reinforced exposure to CS. Extinction is not the result of forgetting the connection between CS and US, instead it is believed to be a type of inhibitory learning (Quirk & Mueller, 2008). This conclusion is based on lab studies and clinical observations that show return of fear sometime after extinction (Vervliet, Baeyens, Van den Bergh, & Hermans, 2013). A lot of research fo-cused on understanding the neural systems behind extinction and inhibitory learning as it is considered the foundation for treatment of phobias and related anxiety disorders (Lebois, Seligowski, Wolff, Hill, & Ressler, 2019). In short, extinction is a type of safety learning that competes with the memory of the original CS-US association and has practical application for clinical use. I will return to the role of extinction shortly when we contrast and compare innate and conditioned fear.

A comparison of neural mechanisms underlying innate and conditioned fear I begin with a quick recap of the characteristics of innate and conditioned fear. Innate fear is primarily facilitated by innate or hard-wired neural circuitry spe-cialized to respond to a specific class of stimuli. This is different from condi-tioned fear where the defensive response is dependent on memory and learn-ing, specifically the association between CS and US. Although innate fear is hard-wired to respond to a specific class of stimuli, certain stimulus qualities

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can modulate the defensive response. For example, rodents can change their defensive behavior depending on predatory distance or threat intensity.

A long-standing question when comparing innate and conditioned fear is if their neural pathways are separate or shared. Answering this question is vital as it could provide us with knowledge of how different fear systems interact, and in turn inform on development and treatment of fear-related disorders. However, as researchers have noted (Adolphs, 2013; Silva, Gross, et al., 2016), this is a difficult question to answer for several reasons. One is that defensive responses to innately threatening stimuli are much more flexible and diverse than responses to conditioned stimuli, in part because innate systems can respond to a wide variety of stimulus qualities, which has made the study of innate fear much more challenging. This problem is further complicated by the fact that innate responses to threat can operate through multiple sensory modalities that uses distinct neural circuitry, which is also used for condi-tioned responses. Consequently, delineating the neural circuitry for innate and conditioned fear involves isolating pathways for sensory input, memory and fear output circuitry. This is no easy task, especially when considering that many species evolved defensive systems specifically adapted to their environ-ment, thus making direct comparisons between for example rodents and hu-mans difficult. So, while there is evidence suggesting that innate and condi-tioned pathways may be separate in rodents (Gross & Canteras, 2012), more translational research is needed before we can begin to disentangle the neuro-biology of innate and conditioned fear across species.

Research in rodents identified different brain areas important for innate and conditioned fear. For example, lesion studies have shown that the LA and CeA are important for conditioned, but not innate fear. Conversely, regions in the medial amygdala (MeA) and BNST have been shown to be necessary for in-nate but not conditioned fear (Rosen, 2004). Although while this difference could be explained by separate neural circuitry, it could also be the result of sensitivity to specific predatory odors, as the MeA has been found to be an important site for the detection of olfactory stimuli (Li, Maglinao, & Takahashi, 2004). The same line of reasoning can also be applied to the LA, as the region found to process sensory information from the auditory thalamus, thus being subject to similar sensory bias (Nader, Majidishad, Amorapanth, & LeDoux, 2001).

Conditioned fear is dependent on memory and learning for eliciting defen-sive responses, specifically the CS-US association. But what about innate fear, how are memory processes affecting innate defensive responses to threat? The memory processes behind innate fear have received a lot less attention com-pared to conditioned fear. There is however some evidence in rodent research suggesting that memory functions are important for innate predatory threat in specific contexts where previous threatening stimuli has been encountered (LeDoux, 2000; Maren, 2011). The structures for innate memory encoding are believed to be situated in the hippocampus, the amygdala, cortical structures

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in the anterior cingulate and medial prefrontal regions. This has been con-firmed in lesion studies where it has been found that memory encoding can impair fear to many different threats, including innate. For example, lesions in BLA have been found to prevent fear in animals when they are exposed to predators (Martinez, Carvalho-Netto, Ribeiro-Barbosa, Baldo, & Canteras, 2011), aggressive social encounters (Jasnow & Huhman, 2001) and pain stim-ulation (Helmstetter & Bellgowan, 1994).

There is also evidence for integration of function by structures responsible for formation of memory to aversive events related to innate fear. The neural circuitry involved is believed to include the amygdala and hippocampal re-gions (Silva, Mattucci, et al., 2016). The hypothesis is that innate circuits re-sponsible for signaling threat convey information to higher order learning units where the proper integration of memory takes place. For example, in innate systems governing predatory fear it is implicated that the medial hypo-thalamic defensive system (MHDS) is important for the fear learning process (Cezario, Ribeiro-Barbosa, Baldo, & Canteras, 2008; Do Monte, Canteras, Fernandes, Assreuy, & Carobrez, 2008; Kunwar et al., 2015). This is particu-larly evident in lesion studies where it has been shown that the premammillary nucleus (PMD) and dorsal parts of the ventromedial hypothalamus impairs environmental fear to predatory threat (Do Monte et al., 2008; Kunwar et al., 2015; Silva, Mattucci, et al., 2016). Predator fear circuits routed through the PAG have also been found to be important for innate defensive responses to previously threatening contexts (Kincheski, Mota-Ortiz, Pavesi, Canteras, & Carobrez, 2012). However, pharmacological inhibition of the dorsal PAG does not appear to reduce conditioned fear to predators even though the innate fear is decreased (Silva, Mattucci, et al., 2016).

In addition, defensive responses to social threat have demonstrated that the BLA, prefrontal cortex and ventral hippocampus is important (Markham, Luckett, & Huhman, 2012; Markham, Taylor, & Huhman, 2010). Related to this, there is also some limited evidence suggesting that social threat instruct subcortical areas that project to hippocampal regions (Motta et al., 2009). These regions are in turn associated with fear learning, indicating the possi-bility of shared circuitry for social threat and memory mechanisms necessary for conditioned fear.

Pain stimulation resulting from electrical shocks can also impact memory consolidation through neural circuitry located in the amygdala, hippocampus and prefrontal cortex (Tovote et al., 2015). One recent report that investigated the interaction between innate fear stimuli and neural circuitry mediating con-ditioned fear found that specific neurons in the CeA control innate fear to predator odor and inhibits conditioned freezing to pain cues (Isosaka et al., 2015). This suggests that the CeA can serve as a priority director for innate and conditioned fear depending on stimulus input. Similar functionality is also believed to be present in the BLA, as the structure has been found to selec-tively mediate conditioned fear to neutral stimuli by employing innate fear

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circuitry in order to facilitate the proper defensive responses (Gore et al., 2015).

So, what about inhibition of innate fear? Can principles behind fear extinc-tion also be applied to innate fear? It has been suggested that panic disorders are caused by dysregulation of innate alarm systems (Klein, 1993; Klein et al., 2007). Assuming this is the case, finding ways to inhibit innate fear could provide us with new treatment methods. We know from one optogenetic study in rodents that connectivity between the ACC and the BLA is important for regulating innate fear to threatening stimuli (Jhang et al., 2018). In this study it was demonstrated that optogenetic deactivation of the ACC increased innate fear without affecting learned fear. Historically, the ACC has been found to be important for controlling defensive responses and behavior in threat situa-tions (Etkin, Egner, & Kalisch, 2011). This is also true for an adjacent struc-ture, the anterior midcingulate cortex (aMCC), which has been linked to de-fensive behavior in monkeys (Kalin, Shelton, Fox, Oakes, & Davidson, 2005) and humans (Mobbs et al., 2007). Furthermore, the ACC is believed to be involved in emotional regulation during fear conditioning (Etkin et al., 2011). Another study also demonstrated that overcoming fear of snakes was associ-ated with attenuation in the amygdala and structures in the temporal lobe, sug-gesting that innate fear can be inhibited by behavioral control (Nili et al., 2010). In rodents, there is also evidence suggesting that amygdala may be im-portant for inhibiting innate defensive behavior to predators (Choi & Kim, 2010). In this study, rats competing with a robot predator were able to procure more food if their amygdala was inactivated, indicating that risk-taking be-havior is regulated by the amygdala. Thus, while it may be theoretically pos-sible to inhibit innate fear in some cases, there is a lot more work to do before we fully understand how innate fear can be inhibited in a reliable way.

Genetic influence on innate and conditioned fear There is evidence suggesting that genes influence olfactory sensors and con-sequently innate fear to specific predatory odors in mice (Kobayakawa et al., 2007). In particular, one study using genetically modified mice identified that the Olfr1019 receptor suppresses olfactory sensory neurons, resulting in re-duced freezing to olfactory threat signals induced by fox odor (Saito et al., 2017). In addition, a recent report utilizing genetics screening and knock-out mice identified the Trpa1 as a chemosensor for predator odor induced innate defensive behaviors in mice (Wang et al., 2018), suggesting genetic contribu-tion to the function of the Trpa1 receptor. In humans, findings on genetic con-tribution to innate fear is scarcer. However, there is evidence suggesting that the polymorphic region of the serotonin transporter gene, 5-HTTLPR, can in-fluence innate fear processing to acoustic startle (Brocke et al., 2006). In line with this, a later study found that over half the variance in the overall startle response was due to additive genetic effects (Vaidyanathan, Malone, Miller,

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McGue, & Iacono, 2014), suggesting a genetic basis for defensive responses to acoustic startle.

A lot of research on genetics and fear conditioning have been conducted in rodents. Here, evidence for genetic influence on aversive Pavlovian condition-ing comes from selective breeding studies where rodents have been bred for increased responsiveness to conditioning (Ponder et al., 2007). Further, inbred mouse strains with different genetic backgrounds have been used to investi-gate the genetic and molecular foundation of defensive behaviors, including learning and memory (Parker, Sokoloff, Cheng, & Palmer, 2012; Wilson, Brodnicki, Lawrence, & Murphy, 2011). Specifically, the C57BL/6 (B6) and DBA/2 (D2) strains showed important differences in fear learning (Dellu, Contarino, Simon, Koob, & Gold, 2000; Graybeal et al., 2014; Paylor, Baskall-Baldini, Yuva, & Wehner, 1996; Schimanski & Nguyen, 2004) and have been used to identify genetic and molecular contributions to fear condi-tioning. These genes have also been linked to activation in brain regions such as the amygdala and the hypothalamus (Andre, Cordero, & Gould, 2012; Schimanski & Nguyen, 2004; Yang et al., 2008), indicating genetic influence on activity in those areas.

In humans, one twin study found that autonomic responses (SCR) to con-ditioned threat showed moderate heritability (35-45%) of conditioned SCR (Hettema, Annas, Neale, Kendler, & Fredrikson, 2003), suggesting that genes may contribute to the fear conditioning process. This finding has since been replicated in a study investigating the genetic contribution to different memory systems facilitating fear learning (Fredrikson, Annas, & Hettema, 2015). Here it was discovered that individual differences in fear conditioning were facili-tated by distinct genetic factors, separate from those modulating episodic memory. In addition, the short variant of the 5-HTTLPR polymorphism has been found to regulate fear conditioning (Garpenstrand, Annas, Ekblom, Oreland, & Fredrikson, 2001; Lonsdorf et al., 2009) and amygdala activation (Hermann et al., 2012).

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Aims

Investigating whether different brain systems process innate and conditioned threat could provide us with knowledge on how defensive systems interact and inform on development and treatment of fear-related disorders. Hence, the first aim of this thesis was to investigate whether different brain systems pro-cess innate and conditioned threat. This was examined in Study I and II. The second aim of this thesis was to investigate if neural functions supporting im-minent and social threat are heritable. To this end, the last study of the thesis examined the heritability of fMRI responses to imminent and social threat.

I The first study investigated the interplay between social, imminent

and conditioned threat.

II The second study used immersive virtual reality to investigate if im-mersion modulated the effect of imminent and conditioned threat.

III The third study, a twin study, used skin conductance and functional

magnetic resonance imaging to investigate heritability and neural ac-tivation for imminent and social threat in the human brain.

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Methods

Skin conductance response Skin conductance response (SCR) is a popular method used to index physio-logical arousal in human fear conditioning experiments. By applying elec-trodes to specific locations on the body where eccrine sweat glands are located (e.g palmar surface of the hand), a small electric pulse can be used to measure phasic shifts triggered by emotional arousal. The basic principle behind SCR is that increased sweating reduces the resistance of the skin and improves con-ductance. Thus, the skin conductance informs on the activation of the sweat glands. Since sweat secretion is controlled by the sympathetic nervous system, changes in skin conductance can be used to assess activity of this system (Sequeira, Hot, Silvert, & Delplanque, 2009). Previous reports have demon-strated that SCR can be used to investigate the connection between threat and nervous system activation (Greco & Liberzon, 2016b; Shin & Liberzon, 2010). In Study I, II and III, electrodes were placed on the palmar surface of the hand.

fMRI Functional magnetic resonance imaging (fMRI) is a common non-invasive ra-diological method to study the human body. Extending the features of regular MRI, fMRI can obtain high resolution images of tissue and measure regional blood flow. In turn, the blood flow can be used as an indicator of activity in the brain during performance related tasks. Measurement with fMRI can be used to record activity in deep subcortical structures and is therefore ideal when investigating defensive responses to threat.

When MRI is used, the participant is placed in a strong magnetic field that will align the protons in the body along the axis of the field. A radio frequency pulse is then used to align the protons in the opposite direction of the field. When the pulse is deactivated, the protons will return to their relaxed state and emit energy that can be captured by the scanner. Because tissue in the body has different magnetic signature, it is possible to reconstruct an image based on this signal. Although this image contains no direct information about neural activation. To solve this problem, fMRI can be used to measure magnetic properties of molecules in the blood stream. This is possible because fMRI

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interprets increased neural activity as a shift in the energy signature of the tissue, caused by local concentration of oxygenated blood. In turn, the shift in the magnetic field can be detected by the MR scanner and used as an index of neural activity. The signal created by this shift in the magnetic field is referred to as blood oxygen level dependent (BOLD). In fMRI during task perfor-mance, the BOLD signal is commonly compared to baseline measurements to ascertain which brain regions are activated (Heeger & Ress, 2002).

Twin method The twin method is a comparison between identical (monozygotic, MZ) twins and fraternal (dizygotic, DZ) twins to establish heritability for a certain trait of interest. The method was developed sometime between the 1900-1940 as a way to statistically analyze resemblance between family members (Mayo, 2009). The basic premise is that MZ twins are genetically identical, while DZ twins share half of their genes, similar to that of regular siblings. Assuming the twin pairs shared the same environment, the difference between two mem-bers of a pair of MZ and two members of a pair of DZ over several sets of twin pairs can be compared in order to assess the degree of genetic influence in the variation for a particular trait.

Twin analysis can be applied to quantitative data (Johnson, Turkheimer, Gottesman, & Bouchard, 2010), and many statistical methods have been de-veloped over the years to assess genetic variance. One such popular method in quantitative genetics is Falconer’s formula (Falconer, 1993). It states that broad sense heritability (h2) is determined by the correlation (rmz) for identical twins (MZ) and the correlation (rdz) for fraternal twins (DZ), estimating herit-ability between 0 and 1. The formula can also be used to calculate common or shared environment, although more sophisticated statistical methods based on structural equation modeling have been developed to solve this problem. One example is the ACE model, which includes genetic variance (A), common or shared environmental (C) and specific or non-shared environment plus error measurement (E) (Maes, 2014). This and similar models are the foundation in many popular statistical software packages for twin analysis (Feng, Zhou, Zhang, & Zhang, 2009; Sahu & Prasuna, 2016). The ACE model was used to estimate the heritability of brain function in the present thesis.

Ethical statement Ethical approval for the studies was granted by the regional Ethics Vetting Board in Uppsala. Study participants gave written informed consent before partaking in the studies and were reimbursed for their participation.

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Summary of studies

Study I Background and aim The capacity to acquire fears is important for early life survival. Certain types of fears do not require previous learning experience and are considered innate. In contrast, conditioned fears are learned by experiencing aversive conse-quences. Two types of innate fears are fear of same-species interaction (social threat) and fear of proximal encounters near the body (imminent threat). These innate fears are present early on in human development (Billington, Wilkie, Field, & Wann, 2011; Brooker et al., 2013). Conditioned fears on the other hand are developed throughout the life span. Exploring how innate and con-ditioned fears modulate each other could help us understand the development and treatment of anxiety disorders. Hence, Study I aimed to investigate the interplay between imminent, social and conditioned responses to threat.

Methods Fifty-seven healthy adult volunteers (33 females) underwent a one-day fear conditioning experiment. Seated in a lab room wearing a virtual-reality head-mounted display, half of the participants viewed stimuli consisting of 3-D vir-tual characters whereas the other half viewed virtual spheres displayed at the same locations in the virtual contexts (Figure 1). Four different types of virtual characters/objects were used during the conditioning procedure. Two of the virtual characters/objects were paired with an electric shock (CS+) and the other two were never paired with an electric shock (CS-). Two (CS+ and dis-tance matched CS-) virtual characters or objects were displayed at proximal (0.6 m) while the other two (CS+ and distance matched CS-) were displayed at distant (2.7 m) location in front of the participant in the virtual context. Fear was acquired following a habituation phase. Electric shocks served as US. Half of the CS+ trials at each location were reinforced during conditioning. Amount of trials before conditioning were 16 (4x4 stimuli/presentations), dur-ing conditioning 32 trials with (4x8 stimuli/presentations) and after condition-ing there were a total of 40 trials (4x10 stimuli/presentations). During extinc-tion, stimuli were presented again without reinforcement. SCR was used as an index of threat before, during and after conditioning.

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Results During the habituation phase, before fear conditioning, participants had greater SCR to proximal compared to distant presentation of virtual characters and objects. Proximal virtual characters elicited greater SCRs than proximal virtual objects, indicating a modulation of social threat by imminent threat. During fear conditioning SCRs were greater to presentations paired with an electric shock (CS+) compared to presentations not paired with an electric shock (CS-), indicating successful conditioning of threat. However, results showed no CS-differentiation depending on if characters or objects predicted shocks, suggesting that social modulation of fear conditioning was absent. As before conditioning, participants had higher SCR to proximal compared to distant CS during conditioning. After conditioning, participants had higher SCR to proximal than distant CS, indicating autonomic activation to imminent threat. Participants also still showed greater SCRs to the fear cue that had been paired with electric shock than to the control cue.

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Figure 1. Images depict stimuli used in Study I. One group of participants viewed four 3-D virtual characters at proximal or distant locations whereas another group was presented with four 3-D virtual spheres at the same locations. Modulation of imminent threat by social threat was tested before, during and after conditioning. During conditioning, one proximal and one distant virtual character or sphere was used as a conditioned stimulus (CS+) and was paired with an electrical shock. An-other distance matched character or sphere was used as a control stimulus (CS-) and was not reinforced during the experiment. Skin conductance response (SCR) was used as an index of fear before, during and after conditioning. From Rosén, Kastrati & Åhs (2017).

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Figure 2. Modulation of imminent and conditioned threat by social content. (A) Before conditioning, the autonomic response to imminent threat was modulated by social threat (responses to distance matched virtual characters were higher compared to responses to virtual spheres) (left panel). A similar results profile was observed after conditioning (right panel). The results for imminent threat was calculated by subtracting the average skin conductance response for all distant trial presentations from the average skin conductance response to all proximal trial presentations. (B) There was no modulation of conditioned fear by imminent threat before or after fear conditioning. Bars in graphs show ± standard error of the mean. *, P < 0.05; #, P = 0.06. CS+, conditioned stimulus, reinforced. CS-, conditioned stimulus, not reinforced. SCR, skin conductance response. From Rosén et al. (2017).

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Figure 3. Results for imminent and social threat on conditioned fear. (A) Stimulus type (virtual character and virtual sphere) did not modulate the conditioned re-sponse, suggesting that there was no modulation on conditioned fear by social threat after fear conditioning (right panel). Before fear conditioning, there was no modula-tion of conditioned fear by imminent threat as no pairing of electric shock and con-ditioned stimulus had yet occurred (left panel). (B) After fear conditioning, immi-nent threat did not modulate conditioned fear as similar levels of skin conductance responses were observed between proximal and distant stimulus presentations (right panel). Before fear conditioning, there was no modulation of conditioned fear by im-minent threat (right panel). Bars in the graphs show means ± standard error of the mean. n.s, non-significant. From Rosén et al. (2017).

Discussion The results showed that before fear conditioning, the autonomic responses to imminent threat were greater to social stimuli. Social threat therefore modu-lates the response to imminent threat. Following fear conditioning, partici-pants had increased SCR to the conditioned cue (CS+) compared to the control cue (CS-). However, conditioned fear was not modulated by social or immi-nent threat. These results suggest that the autonomic response elicited by so-cial and imminent threat operates through a shared process that is separate from that of conditioned threat. Thus, findings indicate that fear does not orig-inate from a common mechanism that is shared between innate and condi-tioned fear in the human brain.

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Study II Background and aim Innate and conditioned fear have been found to rely on different neural circuits in animals (Gross & Canteras, 2012; Yang et al., 2016). Some innate fears, such as fear of sudden proximal encounters (imminent threat), are dependent on neural circuitry early on in the visual stream. Here, increased immersion, defined as enhanced depth perception and field of view, can be used to test the difference in processing of innate and conditioned threat. If the same process regulates the response to these two types of threats, this type of manipulation should equally affect them. On the other hand, if innate and conditioned threat is processed by different neural circuits, as suggested by studies in animals, it is possible that processing of one type of threat is modulated by immersion but not the other. In fear research, head-mounted displays provide a means to reach an increased level of immersion compared to computer displays. Study II aimed to investigate if immersion could modulate SCR to imminent and conditioned threat.

Method Eighty healthy adult volunteers (46 females) underwent a one-day fear condi-tioning experiment. Participants were randomly assigned to a group viewing stimuli through a virtual-reality head-mounted display or a group viewing stimuli on a regular computer display. The participants were then further ran-domly assigned to one of two groups, one viewing stimuli in an indoor envi-ronment and the other in an outdoor environment (Figure 4), to establish whether conditioned and immersive threat responses vary over contexts. Dur-ing the experiment, participants viewed virtual characters. Four different vir-tual characters were used, two for each distance (proximal and distant). One of these two characters was paired with an electric shock (CS+) and the other was not paired with an electric shock and served as a control cue (CS-). The stimuli were presented at proximal (0.6 m) and distant distance (2.7 m) in front of the participant. Amount of trials before conditioning were 16 (4x4 stim-uli/presentations), during conditioning 32 trials with (4x8 stimuli/presenta-tions) and after conditioning there were a total of 40 trials (4x10 stim-uli/presentations). SCR to the 4 characters that served as CSs was recorded before, during and after fear conditioning.

Results The results showed that participants had higher SCR to proximal compared to distant presentations of virtual characters before fear conditioning for both display types. Importantly, SCR was higher to proximal compared to distant

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virtual characters when displayed in a virtual-reality head-mounted display than computer display. No effect of context (indoor/outdoor) or main effect of display was found. During conditioning, SCR was increased to proximal com-pared to distant stimuli presentations. An effect of display type for imminent threat was again observed as participants viewing stimuli in a virtual-reality head-mounted display showed higher SCR to imminent threat compared to participants viewing stimuli on a computer display. SCR was also greater to CS+ presentations compared to CS- presentations, indicating successful con-ditioning. However, there was no difference in SCR between CS+ and CS- as a function of immersion. The effect of distance (proximal, distant) and condi-tioning (CS+, CS-) was not modulated by context, indicating that results gen-eralized across the two environments. Following fear conditioning, increased SCR was again observed to proximal compared to distant presentations and this effect was greater in virtual-reality head-mounted display compared to computer display.

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Figure 4. Experimental setup in Study II with virtual character presentations, con-texts (indoor, outdoor) and timeline (B). (A) Participants were divided into two groups; one group viewed stimuli in a virtual-reality head-mounted display (left) and the other group viewed stimuli on a regular computer monitor (right). Four male virtual characters were presented (two depicted in A) in indoor or outdoor environ-ments that were used as conditioning contexts. From Rosén et al. (2019).

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Figure 5. Result of display type on SCR to proximal (imminent) and conditioned threat. (A) Mean difference in skin conductance responses (SCR) for proximal (im-minent) and distant virtual character presentations separated by display type (virtual-reality head-mounted display, HMD and regular computer display, 2D). Results in-dicated that virtual-reality head-mounted display facilitated SCR to proximal charac-ter presentations compared to a regular computer display. (B) Results for condi-tioned threat showed similar levels of SCR for virtual-reality head-mounted display and computer display, suggesting no modulation of conditioned fear by display type. Error bars in graphs show standard error. CS+, conditioned stimulus, reinforced; CS-, conditioned stimulus, non-reinforced (control); n.s., non-significant; ***, P < 0.001. From Rosén et al. (2019).

Discussion The results indicated that stimuli presented in a virtual-reality head-mounted display compared to a regular computer display increased SCR for imminent threat. This effect was not observed for conditioned threat. This suggests that immersive virtual reality modulates the response to imminent threat but not conditioned threat. A possible explanation for this finding is that neural cir-cuits selective for imminent threat are sensitive to variations in how stimuli are presented to the visual system whereas neural circuitry processing condi-tioned threat is not. Because it was possible to modulate the processing of one type of threat but not the other, it can be concluded that the autonomic com-ponent regulating responses to innate and conditioned threat may depend on separate processes in the human brain.

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Study III Background and aim There is evidence for genetic influence on innate defensive behaviors in ro-dents (Rosen, West, & Donley, 2006). In humans however, studies of genetic influences on innate defensive responses to different threats are lacking. One type of innate fear is the response to social threat, such as encountering an unknown member of the same species. Defensive responses to social threat can be found in most social species and are intended to protect the body from harm during same species interactions. Another type of innate fear is the de-fensive response triggered by proximal encounters near the body, or imminent threat. The defensive response to imminent threat is believed to be regulated by distance to threat and is also important for social interactions (Blanchard & Blanchard, 1989). However, knowledge regarding the interplay between social and imminent threat in the human brain is limited. Hence, Study III aimed to investigate genetic influence and interaction of brain function sup-porting social and imminent threat in the human brain using fMRI.

Methods Twins in the age range 20-60 years were recruited from the Swedish Twin Registry. The participants were screened for suitability to undergo magnetic resonance imaging, substance abuse, ongoing psychological treatment and use of medicine affecting emotion or cognitive abilities. The total sample included in the study was 294 with 71 (84 female) monozygotic and 76 (88 female) dizygotic twin pairs. The experiment was part of a larger twin study where participants underwent a 60-minute-long scanning session. During the exper-iment, participants were presented with virtual characters and cylinder-shaped objects on a 2-D computer display in the MR scanner. Cylinders were used to match the shape of the virtual characters (i.e. to keep the shape on the retina consistent between the two stimulus types). Two different virtual characters and two different cylinder-shaped objects were presented at simulated dis-tances of 0.3 m and 2.7 m (Figure 6). Participants were presented with 10 presentations of each stimulus type (character or cylinder at proximal or dis-tant location) adding up to 40 presentations in total. Total time for the experi-mental task was 10 minutes. Brain activation and autonomic responses to stim-uli presentations were measured using fMRI and SCR. Heritability was esti-mated by contrasting proximal and distant presentations and comparing social and non-social stimuli and the interaction between social and distance to threat.

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Results The results showed that presentations of proximal compared to distant stimuli (imminent threat) activated neural circuitry in areas related to early visual pro-cessing including the lateral geniculate nucleus as well as amygdala and a fronto-parietal network. In addition, imminent threat increased SCR to proxi-mal compared to distant stimuli presentations. Heritability for fMRI responses to imminent threat ranged from medium to strong (43-63%) in the primary visual cortex, the cuneus and the fusiform gyri (Figure 7A). Brain activations to social threat (virtual characters compared to cylinder-shaped objects) acti-vated areas in the inferior occipital gyri, middle temporal and occipital lobe, fusiform gyri and amygdala. Heritability for brain responses to social threat were strongest in the lateral occipital lobe and the fusiform gyri (52-54%) (Figure 7B). The results also showed stronger activation to social imminent threat than to non-social imminent threat in the superior occipital gyrus, lin-gual gyrus, middle occipital gyrus, fusiform gyrus and amygdala. Heritability ranged from 27-42% in the middle occipital gyrus and the superior occipital gyrus (Figure 7C). There was also a correlation between activated brain areas and heritability estimates (Figure 8).

Figure 6. Images used during the experiment. Two different virtual characters and cylindrical objects at proximal and distant locations were used to assess imminent and social threat. The number of presentations for stimulus type and distance was 10, with a total of 40 presentations. From Rosén et al. (2019).

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Figure 7. Heritability estimates (h2) for (A) imminent threat, (B) social threat and (C) the interaction between imminent and social threat. (A) Brain areas with strong-est heritability for imminent threat: L cuneus (63%, MNI: -6 -88 26), R calcarine gyrus V1 (53%, MNI: 14 – 80 10), R precuneus (52%, MNI: 24 -50 2), R fusiform gyrus (51%, MNI: 30 -56 -4), R lingual gyrus (49%, MNI: 16 -52 6), R superior oc-cipital gyrus (44%, MNI: 18 -86 20), L lingual gyrus (44%, MNI: -18 -82 -4), R cu-neus (42%, MNI: 16 -92 14). (B) Areas with strongest heritability estimates for so-cial threat: L inferior occipital gyrus (58%, MNI: -32 -88 -6), L fusiform gyrus (52%, MNI: -40 -80 -14), L middle occipital gyrus (52%, MNI: -28 -92 0), L infe-rior occipital gyrus (51%, MNI: -42 -74 -14), R fusiform gyrus (54%, MNI: 36 -56 -16) R inferior occipital gyrus (54%, MNI: 44 -64 -16). (C) Brain areas with the strongest heritability estimates for the interaction between imminent and social threat: L middle occipital gyrus (42%, MNI: -26 -90 2), L superior occipital gyrus (27%, MNI: -12 -96 4). Coordinates in MNI space. L = Left, R = Right. From Rosén et al. (2019).

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Figure 8. Scatterplots denoting correlations between brain activation in statistical peak voxels (T-values) and heritability (h2). Significant correlation between brain activation and heritability (r = 0.73, P < 0.05). Correlation for imminent threat (A), social threat (B) and the interaction between imminent and social threat (C), r = 0.080, r = 0.82 and r = 0.41. From Rosén et al. (2019).

Discussion Findings indicated that brain activation related to social and imminent threat was heritable, suggesting that these brain functions are under genetic influ-ence. Both imminent and social threat activated neural circuitry early in the visual stream while social threat had the highest brain activation in areas as-sociated with object and face recognition situated in the lateral occipital cortex and the fusiform cortex. Both types of threat activated the amygdala, a region commonly associated with fear in humans.

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General discussion

Main findings Study I showed that the autonomic response to imminent and social threat might operate through a shared process that is separate from conditioned threat in the human brain. Extending the findings from Study I, Study II showed that innate fears sensitive to variations in the visual stream could be modulated by immersion. Specifically, the proximal presentations facilitated the autonomic response if the stimuli were shown in an immersive virtual reality head-mounted display compared to on a computer display. Study III showed that brain activation as a response to social and imminent threat is heritable, sug-gesting genetic influence on these innate systems in the human brain. Study III also demonstrated that imminent and social threat activated circuitry com-monly associated with fear, such as the amygdala.

Discussion In Study I, it was discovered the autonomic component regulating responses to innate and conditioned threat might be processed by separate neural path-ways, in line with what has been previously shown in rodents (Gross & Canteras, 2012; Yang et al., 2016). Study I also demonstrated that threat im-minence was modulated by social threat, suggesting partially shared neural pathways for processing of these two types of innate threats. These results overlapped with findings in animals, where it has been demonstrated that in-nate defensive mechanisms share neural circuitry (Silva, Gross, et al., 2016). However, the memory encoding of these innate systems, particularly related to conditioned fear, is suggested to rely on a separate memory system, which could explain why conditioned fear was not modulated by imminent or social threat in Study I. Study I was a first step in delineating human fear circuits and its findings contributed to the discussion of whether human fear operates through a central fear state or not (Adolphs, 2013).

Study II replicated the findings from Study I with regards to the autonomic response to imminent threat. As before, proximal presentations facilitated SCR compared to distant presentations. We later replicated this effect in yet another study investigating autonomic responses to spiders and objects (Juvrud et al., 2018). Interestingly, in this study we discovered that SCR and

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pupillary measures correlated with proximal distance to stimuli. Specifically, proximal objects facilitated SCR and increased pupil dilation compared to dis-tant objects, indicating an autonomic response by two different indexes of threat to proximal stimuli. Study II suggested that depth cues are important for facilitating autonomic responses to imminent threat; similar to what has been found in primates (Maior et al., 2012; Soares, Maior, Isbell, Tomaz, & Nishijo, 2017). These results suggest that the innate circuitry controlling defensive re-sponses to imminent threat is dependent on depth perception also in humans.

An important finding in Study II was that the autonomic responses to prox-imal presentations were sensitive to increased immersion when stimuli were presented in a virtual-reality head-mounted display compared to a computer monitor. This finding corroborated that innate circuits selective to visual input can moderate autonomic responses in humans. This is in line with results ob-tained from rodent research, where it was demonstrated that the SC can mod-erate the innate defensive response to visual input (Wei et al., 2015; Yilmaz & Meister, 2013). In the study by Wei et al. (2015) it was discovered that the SC projects to the lateral posterior nucleus (LP) that in turn signal to the lateral amygdala. By blocking the amygdala output, it was demonstrated that visually evoked defensive responses could be suppressed. These findings taken to-gether with the results from Study II, suggest that similar pathways control autonomic responses to visual threats also in humans. In addition, Study II showed that a regular computer display facilitated SCR to proximal compared to distant stimuli. This finding allowed us to extend our experimental setup to environments where we could not utilize a virtual-reality head-mounted dis-play, such as in an MR-scanner.

In Study III, it was found that parts of the neural circuitry controlling brain activation to imminent and social threat were shared. This finding confirmed our initial hypothesis from Study I that innate fear circuitry operates through shared pathways, specifically related to proximal and social encounters. How-ever, some of the activated brain areas were also distinct, indicating separation of innate circuitry depending on stimulus qualities, such as if the visual input depicts a member of the same species or not. This finding suggests that innate fear circuitry is not only separate for specific sensory modalities (Gross & Canteras, 2012), but also to specific stimulus characteristics.

There is evidence suggesting that innate fear circuitry in the human brain evolved as a response to environmental challenges in our evolutionary past (Blanchard, Hynd, Minke, Minemoto, & Blanchard, 2001; Ohman & Mineka, 2001). However, one outstanding question is whether innate systems regulat-ing defensive responses to threat are influenced by heritability. To investigate this, Study III adopted a twin design where it was found that brain activation correlated with heritability estimates in the visual cortex for innate fear. One explanation for this finding is that areas in the visual cortex mature early dur-ing development, hence the expressed functionality is likely to be under strong genetic influence (Siu & Murphy, 2018). This is also consistent with findings

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demonstrating a higher degree of neural plasticity in visual areas early on in childhood compared to later stages in life (Siu, Beshara, Jones, & Murphy, 2017). Thus, the heritability found in Study III could be the result of genetic influence on stereotypical neural circuitry selective of visually induced threats.

In addition to this, Study III also demonstrated activation in a brain area associated with fear. Specifically, proximal and social stimuli presentations elicited responses in the amygdala, indicating that imminent and social threat is modulated by commonly associated fear circuitry in humans (LeDoux, 2014). Furthermore, the interaction between imminent and social threat showed activation in the amygdala, suggesting that the amygdala may be in-volved in regulating the defensive response to proximal social encounters. This finding is in line with one previous report establishing the importance of the amygdala for regulating interpersonal space in humans (Kennedy et al., 2009). In this study, it was demonstrated that proximal social encounters were associated with amygdala activation in healthy individuals, but one subject with amygdala lesions had no sense of personal space. Similar results for in-terpersonal distance have also been observed in another study where amygdala activation correlated positively with preferred longer distances to angry, fear-ful and sad facial expressions (Vieira et al., 2017). We also found that for social threat, areas commonly associated with processing of facial expressions and emotions were activated (Fusar-Poli et al., 2009; Phan, Wager, Taylor, & Liberzon, 2002), suggesting a connection between functionality serving emo-tional recognition in facial expressions and threat detection.

Research in rodents demonstrated that innate defensive behaviors to loom-ing stimuli are regulated by visual circuitry (Yilmaz & Meister, 2013). Spe-cifically, rodents exhibited freeze or flight behavior depending on visual stim-ulus properties, such as size and speed of approach. Similar escape behaviors have also been reported on in other species as a response to visual stimulus (Card, 2012; Yamamoto, Nakata, & Nakagawa, 2003). These findings suggest that some animals may have developed stereotypical innate defensive circuitry processing visually approaching threat. In humans, there is similar evidence for processing of approaching threat (Mobbs et al., 2007; Qi et al., 2018). Mobbs et al. (2007) demonstrated that imminence-driven threat increased the subjective degree of dread and decreased the confidence of escape for antici-patory pain from a virtual predator. These findings, taken together with the results from Study II and III, indicate the possibility of cross-species shared innate functionality controlling defensive responses to imminent threat.

It has been suggested that heritability of brain function can be used as a determinant for identifying specific classes of disorders (Blokland, de Zubicaray, McMahon, & Wright, 2012). This would allow technologies, such as fMRI, to investigate the source of variation in activated brain areas during performance related tasks and potentially find endophenotypes for neurologi-cal and psychiatric disorders. In Study III it was determined that the strongest

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heritability of brain activation to innate threat was located in the visual cortex and fusiform face areas. This finding suggests that these areas could be im-portant sites for investigating genetic influence on fear related disorders sen-sitive to visual input. Indeed, reports have shown that heritability account for a high degree of variability (40%) in the overall contribution to anxiety disor-ders (Hettema, Neale, & Kendler, 2001; Shimada-Sugimoto, Otowa, & Hettema, 2015) and that neuroimaging studies identified abnormal activation patterns in visual areas related to phobic stimuli (Ipser, Singh, & Stein, 2013). In line with this, one meta-study also found that activation in visual cortices related to social phobia (Gentili et al., 2016). These findings, taken together with the heritability found in Study III, indicate that genetic influence on ac-tivation in areas processing visual information may be important for under-standing the origin of certain psychiatric disorders.

Limitations Although Study I and II suggested that innate and conditioned threats are pro-cessed separately, there are a few methodological concerns that must be ad-dressed. For instance, the results were limited to measures of SCR. This means that the interpretation of the findings was restricted to one type of autonomic measure. We deliberately designed the experiment this way for practical rea-sons. However, without additional measures of autonomic activity or methods to assess neural activation, our comparison between innate and conditioned threat is limited in scope. Another potential limitation is the exclusive use of visual stimulation to trigger defensive responses. Since animal studies have shown that innate fear can be expressed through multiple sensory pathways (Gross & Canteras, 2012), it is possible that other sensory modalities, such as auditory and olfactory channels, would yield different results for innate and conditioned fear in the human brain.

In Study I and III, we used pictures of male virtual characters with neutral facial expressions and geometrical shapes to assess social threat. Study I showed that the virtual characters facilitated SCR compared to geometrical shapes. However, these results were not replicated in Study III, despite greater amygdala activation to virtual characters relative to shapes. We do not know the exact reason for the discrepancy in results, but speculate that one reason might be that stimuli were presented in immersive VR in Study I and on a flat screen in the MR-scanner in Study III. Study II showed that facilitation of SCR from threat imminence is greater in immersive VR than on a flat screen. Thus, it is possible that immersion is necessary for social modulation of threat imminence.

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Future directions To delineate the differences between innate and conditioned fear, it is neces-sary to understand the similarities and differences in neural processing of these two types of fears across species. Traditionally, much of the research on innate fear has centered on sensory input, detection of threat and output circuitry in mice (Silva, Gross, et al., 2016). This rather narrow focus on the mouse brain has left many important questions unanswered in human processing of innate threat. For example, while studies of the interaction between innate and con-ditioned fear circuits in the mouse brain exist (Isosaka et al., 2015), these find-ings may be limited to rodents and olfactory inputs. Hence, we do not know if these findings can be generalized to the human brain and other sensory mo-dalities than olfaction. This highlights the lack of a unitary experimental ap-proach that can accurately compare different sensory inputs and its neurolog-ical counterparts across species. To solve this problem, future research should establish experimental protocols that allows for comparisons of different in-nate systems between species, for example by using VR-applications.

Fear studies in humans have demonstrated that the amygdala is an im-portant site for producing defensive responses to threat (LeDoux, 2014). How-ever, some studies also found evidence for alternative fear routes. For exam-ple, one previously mentioned fMRI study (Mobbs et al., 2007) demonstrated a shift in brain activation from the ventromedial prefrontal cortex to the PAG by approaching threat from a virtual predator. This finding is also supple-mented by studies demonstrating that electrical stimulation of the PAG (Amano et al., 1982) and ventromedial hypothalamus (Wilent et al., 2010) induced feelings of panic and anxiety. Also, a lesion study showed that the amygdala is not necessary for inducing panic attacks or fear when subjects inhaled carbon dioxide, indicating a possible division of fear circuits for ex-ternal and internal triggered fear states in humans (Feinstein et al., 2013). These studies demonstrate that continued research on alternative fear sites can provide us with better understanding of the neurobiology behind fear.

Despite rigorous efforts in fMRI research to map brain areas associated with emotions (Hamann, 2012; Lindquist & Barrett, 2012; Lindquist, Wager, Kober, Bliss-Moreau, & Barrett, 2012), pinpointing the exact location of hu-man fear circuits have been difficult. A likely explanation for this is that fear and its associated defensive responses are controlled by sub-populations of neurons (Haubensak et al., 2010; Lin et al., 2011b), shared by common neural circuitry, that are indistinguishable from each other due to the limited spatial resolution of fMRI. This creates a problem when attempting to delineate dif-ferent fear circuits as many brain structures may be shared across multiple sensory modalities (Gross & Canteras, 2012) and that some of these structures project to regions outside of what could be construed as part of the central fear network (Asede et al., 2015). To complicate matters further, sites identified as

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important for fear such as the amygdala, have been found to share functional-ity across many different tasks, specifically related to negative and positive valence appraisal (Paton, Belova, Morrison, & Salzman, 2006). Consequently, mapping the fear network requires a clear definition of what constitutes parts of the network, its cellular groups and the associated functionality.

A concern when comparing fear systems in different species is that the neu-ral networks responsible for commonly defined defensive behavior (e.g. freez-ing) are regulated by species-specific anatomical structures (Blanchard et al., 2001; Graziano & Cooke, 2006; Mongeau et al., 2003). Furthermore, modu-lating factors such as individual experiences and learning are of course vastly different between for example a mouse and human. This makes direct com-parisons of defensive behavior and the neuroanatomy responsible for these behaviors difficult. Ideally, future fear research should focus on identifying common variations in defensive behaviors to provide a better understanding of how fear is expressed in different species.

Delineating fear systems could provide us with better understanding of dif-ferent types of phobia and fear related disorders. For example, it has been sug-gested that panic disorders may be caused by dysregulation of innate alarm systems (Klein, 1993; Preter & Klein, 2014). This is an interesting idea as it proposes a link between pathological innate fear circuitry and panic disorder. Furthermore, researching the connection between sensory inputs and different fear states may be important for understanding psychiatric disorders. As an example, one study found that schizophrenia may be associated with altered functionality in the occipital lobe (Tohid, Faizan, & Faizan, 2015). In line with this, it would also be interesting to investigate the connection between herita-bility and psychiatric disorders and how these disorders might influence innate fear.

Finally, the last topic that must be addressed in future studies of fear is the conscious experience of fear. This is something that has primarily received attention in humans, as we know very little about emotions in animals. For this reason, I have deliberately avoided this topic up until now. However, this is an interesting venue of research with many outstanding questions. For ex-ample, what exactly constitutes a conscious experience of fear? Can we use knowledge about emotions to control fear responses? How is the feeling of fear represented in the neural circuitry? These questions must be addressed if we are to understand the relationship between the conscious experience and fear and in doing so we may need to adopt different ways of thinking about emotions. A novel approach to address some of these problems has been put forward by Lisa Feldman Barrett. In one of her articles she outlines and pro-poses that emotions are constructed in the moment and not biologically hard-wired (Barrett, 2016). The idea is that focus should be on understanding the actual cause of the emotion and not its unique qualities. This stands in contrast to more traditional views, where emotions are regarded as discrete or distinct.

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If we are to unravel the mysteries behind emotions and fear in particular, ap-proaches like these may be critical to our efforts.

Concluding remarks The findings in this thesis indicate that innate and conditioned fear might de-pend on separate processes in the human brain, in line with what has been found in other animals. Social and imminent threat were associated with acti-vation of areas early in the visual stream, suggesting a modulation of defensive responses by these pathways. The activation of different visual areas to immi-nent and social threat converged at the level of the amygdala, which is thought to be important for the expression of fear. Importantly, activation in visual areas showed strong heritability, indicating genetic influence on threat related activity in these regions.

Research on fear systems has the potential to inform us about the function and evolutionary origin of defensive responses in different species. In humans, investigating innate and conditioned fear could provide us with better under-standing of how fear operates in the brain and inform on endophenotypes for psychiatric disorders. I foresee that future fear research should consider sev-eral aspects of fear, reaching from functional, behavioral, neurological, and evolutionary to the conscious experience.

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Acknowledgements

First and foremost, I would like to thank my mentor and friend, who also hap-pens to be my main supervisor, Professor Fredrik Åhs. The first time I met you, I thought you were a grunge singer. Fortunately for me, grunge singers can also be excellent scientist (I am still not sure if you are a singer or not). From the moment you took me under your wing and showed me the marvelous world of science, I felt safe, knowing you had an answer for almost any prob-lem (well… almost). You have proven yourself to be an excellent tutor in the arts of answering emails rapidly, scientific writing and building up alcohol tolerance (very important for science). Without you, this thesis would have never seen the light of day, and I hope we will continue to work together in the future (as long as it is not another twin study). Thank you so much for all the support and guidance you have given me over the years.

I would also like to thank my co-supervisor, Professor Tomas Furmark. I blame you and your passion for PET and magnetic cameras for my initial in-troduction to this crazy ride called academia. You are a masterful scientist and football enthusiast. Thank you for all the feedback and support you have given me.

Also, a big thank you to all former and present members of my group: Jo-hannes Björkstrand, for taking care of me when I was new and teaching me about Biopac; Andreas Frick, for being a fellow computer nerd and offering me your support during trying times; Thomas Ågren, for being a good friend and a fellow dungeon crawler; Johanna Motilla-Hoppe, for interesting and fun conversations; Olof Hjort, for being my current office mate and political ad-visor; Malin Gingnell, for possessing wonderful teaching skills; Vanda Faria, for giving me a hug when I needed it the most; Örjan Frans for always having nice things to say and finally Mats Fredriksson for your kind words and sup-port.

I would also like to extend a special thank you to my fellow collaborator and twin study survivor Granit Kastrati. Without your recruiting skills and hard work none of this would have been possible. Thank you so much for all your help, professionalism and immense dedication during our data collecting days.

A special thank you also to Sheila Achermann, my former office mate, for being one of the most intelligent and sweetest people I have ever met. Your kind words and support always meant a lot to me. I miss so you so much.

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I am also grateful to all my co-authors and colleagues that I have worked with at the Department of Psychology over the years. Thank you Gustaf Gredebäck, Joshua Juvrud and Pär Nyström for diverting my attention to the art of eye-tracking and gaming science.

Thanks also to all the PhD students and other members of the department who have made my work so much more enjoyable. In particular, I would like to thank Ronald van den Berg for giving me invaluable comments on my the-sis and instructing me in the ways of Bayesian statistics. A special thank you also to Angeli Holmstedt for being a great listener and giving me your support. Thank you also to Karin Brocki for teaching me about the value of grit and to Annika Landgren for taking care of all the administrative stuff so I did not have to. If I have forgotten anyone, do not be alarmed, it simply means I am getting old and coming down with dementia (do not worry Kim, I still remem-ber you!).

To all the research assistants and students that helped in the lab; without your hard work none of this would have been possible. Thank you Klas Berg-kvist, Aksel Reppling, Ida Hensler and Sara Hultberg. Thanks also to Kevin Vinberg for being a true science nerd and challenging me with difficult ques-tions.

I am also thankful to the staff at the Karolinska Institute MR Research Cen-ter for lending us their equipment for over a year. Thanks also to the people working at the Swedish Twin Registry for providing us with participants and the Swedish Research Council for supplying the funds.

And of course, to my friends, Patrik (Master Traveler), Per (Handsome Ex-pert) and Mathias (Storyteller), thank you for putting up with my ramblings about science, politics and computer stuff. Also, a special thanks to my child-hood friend Gunnar for being one of the kindest people I ever met, I wish you were still living in Sweden!

Finally, I would like to thank my family, my mother Ulla-Britt and stepdad Jan, for all the endless love and support I have received. To my sister Sandra, my brother-in-law Jason, and their two wonderful children Valentina and Mary, thank you so much for always brightening my day and making life so much more enjoyable. To my dad, Rolf, even though you are no longer in the world of the living, I love you so much and I know you are proud of me.

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