We have previously shown that several brain areas are activated both during sequence learning at wake and during subsequent rapid-eye-movements (REM) sleep (Nat. Neurosci. 3 (2000) 831– 836), suggesting that REM sleep participates in the reprocessing of recent memory traces in humans. However, the nature of the reprocessed information remains open. Here, we show that regional cerebral reactivation during posttraining REM sleep is not merely related to the acquisition of basic visuomotor skills during prior practice (...) of the serial reaction time task, but rather to the implicit acquisition of the probabilistic rules that defined stimulus sequences. Moreover, functional connections between the reactivated cuneus and the striatum—the latter being critical for implicit sequence learning—are reinforced during REM sleep after practice on a probabilistic rather than on a random sequence of stimuli. Our results therefore support the hypothesis that REM sleep is deeply involved in the reprocessing and optimization of the high-order information contained in the material to be learned. In addition, we show that the level of acquisition of probabilistic rules attained prior to sleep is correlated to the increase in regional cerebral blood flow during subsequent REM sleep. This suggests that posttraining cerebral reactivation is modulated by the strength of the memory traces developed during the learning episode. Our data provide the first experimental evidence for a link between behavioral performance and cerebral reactivation during REM sleep. © 2003 Elsevier Inc. All rights reserved. (shrink)

Self-relevance has been demonstrated to impair instrumental learning. Compared to unfamiliar symbols associated with a friend, analogous stimuli linked with the self are learned more slowly. What is not yet understood, however, is whether this effect extends beyond arbitrary stimuli to material with intrinsically meaningful properties. Take, for example, stimulus valence an established moderator of self-bias. Does the desirability of to-be-learned material influence self-learning? Here, in conjunction with computational modelling (i.e. Reinforcement Learning Drift Diffusion Model (...) analysis), a probabilistic selection task was used to establish if and how stimulus valence (i.e. desirable/undesirable posters) impacts the acquisition of knowledge relating to object-ownership (i.e. owned-by-self vs. owned-by-friend). Several interesting results were observed. First, undesirable posters were learned more rapidly for self compared to friend, an effect that was reversed for desirable posters. Second, learning rates were accompanied by associated differences in reward sensitivity toward desirable and undesirable choice selections as a function of ownership. Third, decisional caution was greater for self-relevant (vs. friend relevant) responses. Collectively, these findings inform understanding of self-function and how valence and stimulus relevance mutually influence probabilistic learning. (shrink)

From an early age, exposure to a spoken language has allowed us to implicitly capture the structure underlying the succession of speech sounds in that language and to segment it into meaningful units. Statistical learning, the ability to pick up patterns in the sensory environment without intention or reinforcement, is thus assumed to play a central role in the acquisition of the rule-governed aspects of language, including the discovery of word boundaries in the continuous acoustic stream. Although extensive (...) evidence has been gathered from artificial languages experiments showing that children and adults are able to track the regularities embedded in the auditory input, as the probability of one syllable to follow another syllable in the speech stream, the developmental trajectory of this ability remains controversial. In this work, we have collected Event-Related Potentials while 5-year-old children and young adults were exposed to a speech stream made of the repetition of eight three-syllable nonsense words presenting different levels of predictability to mimic closely what occurs in natural languages and to get new insights into the changes that the mechanisms underlying auditory statistical learning might undergo through the development. The participants performed the aSL task first under implicit and, subsequently, under explicit conditions to further analyze if children take advantage of previous knowledge of the to-be-learned regularities to enhance SL, as observed with the adult participants. These findings would also contribute to extend our knowledge of the mechanisms available to assist SL at each developmental stage. Although behavioral signs of learning, even under explicit conditions, were only observed for the adult participants, ERP data showed evidence of online segmentation in the brain in both groups, as indexed by modulations in the N100 and N400 components. A detailed analysis of the neural data suggests, however, that adults and children rely on different mechanisms to assist the extraction of word-like units from the continuous speech stream, hence supporting the view that SL with auditory linguistic materials changes through development. (shrink)

This paper serves three specific goals. First, it reports the development of an Indian Asian face set, to serve as a free resource for psychological research. Second, it examines whether the use of pre-tested U.S.-specific norms for stimulus selection or weighting may introduce experimental confounds in studies involving non-U.S. face stimuli and/or non-U.S. participants. Specifically, it examines whether subjective impressions of the face stimuli are culturally dependent, and the extent to which these impressions reflect social stereotypes and ingroup favoritism. (...) Third, the paper investigates whether differences in face familiarity impact accuracy in identifying face ethnicity. To this end, face images drawn from volunteers in India as well as a subset of Caucasian face images from the Chicago Face Database were presented to Indian and U.S. participants, and rated on a range of measures, such as perceived attractiveness, warmth, and social status. Results show significant differences in the overall valence of ratings of ingroup and outgroup faces. In addition, the impression ratings show minor differentiation along two basic stereotype dimensions, competence and trustworthiness, but not warmth. We also find participants to show significantly greater accuracy in correctly identifying the ethnicity of ingroup faces, relative to outgroup faces. This effect is found to be mediated by ingroup-outgroup differences in perceived group typicality of the target faces. Implications for research on intergroup relations in a cross-cultural context are discussed. (shrink)

The present commentary emphasizes that the acquisition of fear always involves complex changes in several quasi-independent response systems. Stimulus-specific electrodermal response differentiation as well as the bias to overestimate the belongingness of certain stimulus pairs mainly indicates cognitive processes of selective orienting and attention. Emotion, however, also involves the activation of subcortical motivational circuits. Why certain stimuli acquire rapid access to these basic motivational systems is not explained by the expectancy bias model.

It is often thought that traditional recidivism prediction tools used in criminal sentencing, though biased in many ways, can straightforwardly avoid one particularly pernicious type of bias: direct racial discrimination. They can avoid this by excluding race from the list of variables employed to predict recidivism. A similar approach could be taken to the design of newer, machine learning-based (ML) tools for predicting recidivism: information about race could be withheld from the ML tool during its training phase, (...) ensuring that the resulting predictive model does not use race as an explicit predictor. However, if race is correlated with measured recidivism in the training data, the ML tool may ‘learn’ a perfect proxy for race. If such a proxy is found, the exclusion of race would do nothing to weaken the correlation between risk (mis)classifications and race. Is this a problem? We argue that, on some explanations of the wrongness of discrimination, it is. On these explanations, the use of an ML tool that perfectly proxies race would (likely) be more wrong than the use of a traditional tool that imperfectly proxies race. Indeed, on some views, use of a perfect proxy for race is plausibly as wrong as explicit racial profiling. We end by drawing out four implications of our arguments. (shrink)

If the cortex is an associative memory, strongly connected cell assemblies will form when neurons in different cortical areas are frequently active at the same time. The cortical distributions of these assemblies must be a consequence of where in the cortex correlated neuronal activity occurred during learning. An assembly can be considered a functional unit exhibiting activity states such as full activation (“ignition”) after appropriate sensory stimulation (possibly related to perception) and continuous reverberation of excitation within the assembly (...) (a putative memory process). This has implications for cortical topographies and activity dynamics of cell assemblies forming during language acquisition, in particular for those representing words. Cortical topographies of assemblies should be related to aspects of the meaning of the words they represent, and physiological signs of cell assembly ignition should be followed by possible indicators of reverberation. The following postulates are discussed in detail: (1) assemblies representing phonological word forms are strongly lateralized and distributed over perisylvian cortices; (2) assemblies representing highly abstract words such as grammatical function words are also strongly lateralized and restricted to these perisylvian regions; (3) assemblies representing concrete content words include additional neurons in both hemispheres; (4) assemblies representing words referring to visual stimuli include neurons in visual cortices; and (5) assemblies representing words referring to actions include neurons in motor cortices. Two main sources of evidence are used to evaluate these proposals: (a) imaging studies focusing on localizing word processing in the brain, based on stimulus-triggered event-related potentials (ERPs), positron emission tomography (PET), and functional magnetic resonance imaging (fMRI), and (b) studies of the temporal dynamics of fast activity changes in the brain, as revealed by high-frequency responses recorded in the electroencephalogram (EEG) and magnetoencephalogram (MEG). These data provide evidence for processing differences between words and matched meaningless pseudowords, and between word classes, such as concrete content and abstract function words, and words evoking visual or motor associations. There is evidence for early word class-specific spreading of neuronal activity and for equally specific high-frequency responses occurring later. These results support a neurobiological model of language in the Hebbian tradition. Competing large-scale neuronal theories of language are discussed in light of the data summarized. Neurobiological perspectives on the problem of serial order of words in syntactic strings are considered in closing. Key Words: associative learning; cell assembly; cognition; cortex; ERP; EEG; fMRI; language; lexicon; MEG; PET; word category. (shrink)

Art perception offers action affordances for the self-generated movement of the eyes, the mind, and the emotions; thus some scenes are ’easy to look at', and evoke different kinds of moods depending on what kind of affordances they present for the eyes, the brain, and the action schemas that further the dynamical self-organizing patterns of activity toward which the organism tends, as reflected in its ongoing emotional life. Art can do this only because perception is active rather than passive, and (...) begins with efferent activity in emotional brain areas (e.g. hypothalamus, amygdala, hippocampus and anterior cingulate) which then motivates afferent processing (parietal imaging activity which finally, after a 1/3-second motivational/selective process is complete, resonates with occipital patterns, resulting in perceptual consciousness). The limbic system ’categories’ that motivate the ’looking-for’ of selective attention are categories of utility, to be understood in terms of emotional affordances and whole-organism affective meanings. Art plays with this looking-for, using it to make us engage in different afforded actions that relate to different limbic (emotional) categories. The drawings of children and of the artistically untutored reveal this structure when we fail to ’draw what we see’, drawing instead what we conceptualize that we ought to be seeing. Art teaches us to get beyond this almost complete dominance of habitual categories, and to see things more freshly -- both in the perceptual and in the emotive sphere. Rather than reinforcing our preconceptions, it forces us to see how they affect our view of reality. -/- Because neither perceptions nor emotional responses are really passive ’responses’ at all, art does not cause us to feel a certain way. Instead, we ’use’ art for the purpose of symbolizing our emotions. Our most important feelings are not directly ’about’ the perceptual objects that trigger them. The object in conscious attention during the feeling of an emotion is normally not the intentional object of the emotion, i.e., it is not the object in relation to which our actions could serve the purpose of the emotion. Emotions are not even triggered by simple ’stimuli’, but rather by the meaning for us of a stimulus in a total context determined by ongoing and dynamical organismic purposes. Emotions arise from the total life process, which is a dynamical system -- not as an isolated chemical event or a causal result of a simple stimulus. For this reason, emotions call not just for satiation or pleasure, but for explication; this is why art is different from entertainment or pretty decoration. Visual art affords not only a meaningful, self-directed dance of the eyes, but also a meaningful dance of this emotional explicating process. (shrink)

Reinforcement learning approaches to cognitive modeling represent task acquisition as learning to choose the sequence of steps that accomplishes the task while maximizing a reward. However, an apparently unrecognized problem for modelers is choosing when, what, and how much to reward; that is, when (the moment: end of trial, subtask, or some other interval of task performance), what (the objective function: e.g., performance time or performance accuracy), and how much (the magnitude: with binary, categorical, or continuous values). (...) In this article, we explore the problem space of these three parameters in the context of a task whose completion entails some combination of 36 state–action pairs, where all intermediate states (i.e., after the initial state and prior to the end state) represent progressive but partial completion of the task. Different choices produce profoundly different learning paths and outcomes, with the strongest effect for moment. Unfortunately, there is little discussion in the literature of the effect of such choices. This absence is disappointing, as the choice of when, what, and how much needs to be made by a modeler for every learning model. (shrink)

Several authors have characterized a striking phenomenon of perceptual learning in visual discrimination tasks. This learning process is selective for the stimulus characteristics and location in the visual field. Since the human visual system exploits symmetry for object recognition we were interested in exploring how it learns to use preattentive symmetry cues for discriminating simple, meaningless, forms. In this study, similar to previous studies of perceptual learning, we asked whether the effects of practice acquired (...) in the discrimination of pairs of shape with a specific orientation of the symmetry axis would transfer to the discrimination of shapes with different orientation of symmetry axis, or to shapes presented in different areas of the visual field. We found that there was no learning transfer between forms with very different axes of symmetry (90° apart). Interestingly, however, we found a transfer of learning effect to horizontally oriented symmetry axis from a condition with an axis of symmetry differing by 45°. Also it appears that some subjects took a longer time to learn than the typical fast learning paradigm would predict. Data showed that when observers practice discrimination of meaningless symmetric forms, consistent improvement in the performance occurs. This improvement is lasting over days, and it tends to be specific for the area of the visual field trained. We will discuss results from some of the observers whose learning was not fast, but who actually improved with more practice and with large time intervals (1 day) between training sessions. (shrink)