that the major of them is the subjective novelty in the recall situation — i.e.mismatch between animal's expectation and the actual afferentation it receivesfrom the environment.

I would like now to synthesize these two generalizations in the followinghypothesis. There exists only a single physiological process of gene-expression dependent plastic response in the nerve cells. However, it isactivated in the central nervous system both during memory acquisition andunder certain conditions of memory recall. In both cases it is controlled bysystems level process of novelty detection, which is mismatch between theenvironment and existing memory of a subject.

One of main predictions from this hypothesis is that the same process ofprotein synthesis dependent memory reorganization and reconsolidationthat was found during memory recall occurs also during each episode of newlearning. Our current research is aimed at testing this new prediction.

doi:10.1016/j.ijpsycho.2008.05.005

Keynote 4:

Linking brain, mind, and behavior

Scott MakeigUniversity of California San Diego, La Jolla, California, USA

The basis for the science of psychophysiology is the belief that the overallstructure and detailed nature of our behavior and experience are tightlylinked to and supported by the physiological structure and activity of ourbody and brain. The concept that coordinated observations of physiology,experience, and behavior can be used to model the linkage between thesethree domains is at least as old as the nineteenth century investigations ofHelmholtz into kinesiology, vision, and musical experience.

The first actual observations of human brain activity associated with(bottom–up) sensation and its (top–down) interpretation employed electro-encephalography or EEG. EEG was thus the first brain imaging modality,though its early explorers and, in fact, most EEG researchers today still do notapproach their data from this point of view. Yet, modern high-density EEGrecordings capture nothing more or less than a moving image or movie ofcortical field dynamics, projected onto the scalp surface by volume conductionand further mixed with various non-brain signals or ‘artifacts’ (depending onthe interest of the researcher). The continuing computer revolution nowallows us to record this moving image from up to 256 or more sites with aresolution of a million or more bits per second, giving us an unprecedentedopportunity to study how brain, experience, and behavior are linked.

However, the main obstacle to progress in this direction is the lack ofattention to concurrent recording of behavior, which in many EEG and otherbrain imaging experiments is limited to noting the moments of infrequentsmall finger presses on a response ‘microswitch.’ It is clear, however, that ourrate of progress in understanding how human brain activity, experience, andbehavior are linked must be slow — if our recordings of brain and behavioraldata streams continue to have a information mismatch approaching a millionto one! Here, the obvious remedy to this problem is, first, to conduct brainimaging experiments that record more of our behavior that human brainshave evolved to organize and whose main function is to control.

Nearly all of the current brain imaging modalities use very heavy, rigidlysupported sensors (fMRI, PET, MEG, etc.). Thus, to produce useable dataparticipants in brain imaging experiments must keep their head rigidly fixedin place near the sensors during recordings. EEG electrodes, on the otherhand, can be quite light, and in the near future may become nearly weightlessand wireless, thus allowing subjects in EEG brain imaging experiments thefreedom to make natural head and body movements. Yet traditional EEGexperiments have not taken advantage of this freedom. Why not?

First, passive electrodes pass low-level signals back to the signal amplifiers,through electrode cables whose every movement may introduce large,uncontrolled artifacts into the data. This problem may be addressed by usingactive electrode chips and wireless telemetry. Second, until recently adequatemethods and software for separating brain source signals from scalp muscleactivities, and eye movements, cardiac artifacts, and other non-brain signalswere not available. Here, amarked advance in the last decade or so has been theintroduction of information-based signal processing methods, in particularindependent component analysis (ICA), that in favorable circumstances canlearn spatial filters that separate EEG brain imaging data into functionally

distinct signal sources, both brain andnon-brain,without startingwith a specificmodel of how or where each source contributes to the recorded signals.

However, the difficulty of extracting clean EEG brain signals from therecorded data is not the only obstacle to better understanding how brainactivity, experience, and behavior are interlinked. Another powerful metho-dological obstacle is the traditional reliance on reducing the recorded EEGdata to averaged responses to classes of events that investigators assume inadvance are associated with stereotyped patterns of brain activity. Life,however, does not allow the brain to wait for results of response averaging toorganize motivated behavioral responses to the continued stream of novelchallenges we face moment by moment! Nor have human brains evolved toevoke only a limited number of stereotyped responses to these challenges!Considering a recorded, ever-varying EEG ‘scalp movie’ to be composed of alimited repertoire of stereotyped stimulus responses, as computed byresponse averaging, plus non-brain artifacts and ongoing but whollyirrelevant EEG ‘noise’ — is itself a powerful obstacle to achieving betterunderstanding of how our brains respond to the challenge of the moment!

A more promising conception of a more adequate EEG-based psycho-physiology begins with simultaneous recording of (1) high-density EEGscalp movies, (2) detailed behavioral records, including eye and bodymovements, and (3) other psychophysiological measures, as motivatedparticipants deal with a stream of varying challenges in 3-D environments.After adequate data preprocessing to extract relevant data dimensions, newinformation-based and machine learning methods, applied to the extracteddata, may reveal much more about how our continually varying EEG brainactivity is linked to our behavior and experience. I will present some firstresults in this direction.

doi:10.1016/j.ijpsycho.2008.05.006

Keynote 5:

What makes humans humane

Karl PribramStanford University, Psychiatry and Behavioral Sciences, Stanford CA; RadfordUniversity, Brain Research Center, Radford, Virginia, USA

Abstract: Scientific and popular lore have promulgated a connectionbetween emotion and the limbic forebrain. However, there are a variety ofstructures that are considered limbic, and disagreement as to what is meantby “emotion”. This essay traces the initial studies upon which the connectionbetween emotion and the limbic forebrain was based and how subsequentexperimental evidence led to confusion bothwith regard to brain systems andto the behaviors examined. In the process of sorting out the bases of theconfusion, the following rough outlines are sketched: 1) Motivation andemotion need to be distinguished. 2) Motivation and emotion are processedby the basal ganglia; motivation by the striatum and related structures,emotion by limbic basal ganglia: the amygdala and related structures. 3) Thestriatum processes activation of readiness, both behavioral and perceptual;the amygdala processes arousal, an intensive dimension that varies frominterest to panic. 4) Activation of readiness deals with “what to do?” Arousaldeals with novelty, with “what is it?” 5) Thus, both motivation and emotionare the proactive aspects of representations, of memory: motivation, anactivation of readiness; emotion, a processing of novelty, a departure from thefamiliar. 6) The hippocampal–cingulate circuit deals with efficiently relatingemotion and motivation by establishing dispositions, attitudes. 7) Theprefrontal cortex fine-tunes motivation, emotion and attitude when choicesamong complex or ambiguous circumstances are made.

doi:10.1016/j.ijpsycho.2008.05.007

Keynote 6:

New light on brain function from the darkness of blindness

Pietro PietriniLaboratory of Clinical Biochemistry and Molecular Biology, University of PisaMedical School, Pisa, Italy

137Honorary lecture and Keynote presentations / International Journal of Psychophysiology 69 (2008) 135–138