Neural computation as a tool to differentiate perceptual from emotional processes: The case of anger superiority effect

Research findings in social and cognitive psychology imply that it is easier to detect angry faces than happy faces in a crowd of neutral faces [Hansen, C. H., & Hansen, R. D. (1988). Finding the face in the crowd – An anger superiority effect. Journal of Personality and Social Psychology, 54(6), 917–924]. This phenomenon has been held to have evolved over phylogenetic development because it was adaptive to quickly and accurately detect a potential threat in the environment. However, across recent studies, a controversy has emerged about the underlying perceptual versus emotional factors responsible for this so-called anger superiority effect [Juth, P., Lundqvist, D., Karlsson, A., & Ohman, A. (2005). Looking for foes and friends: Perceptual and emotional factors when finding a face in the crowd. Emotion, 5(4), 379–395; Purcell, D. G., Stewart, A. L., & Skov, R. B. (1996). It takes a confounded face to pop out of a crowd. Perception, 25(9), 1091–1108]. To tease apart emotional and perceptual processes, we used neural network analyzes of human faces in two different simulations. Results show that a perceptual bias is probably acting against faster and more accurate identification of anger faces compared to happy faces at a purely perceptual level. We suggest that a parsimonious hypothesis related to the simple perceptual properties of the stimuli might explain these behavioral results without reference to evolutionary processes. We discuss the importance of statistical or connectionist analysis for empirical studies that seek to isolate perceptual from emotional factors, but also learned vs. innate factors in the processing of facial expression of emotion.     

Thorndike's Legacy: Learning, Selection, And The Law Of Effect

This introduction to a symposium on the centennial of Edward L. Thorndike's 1898 monograph on animal intelligence briefly considers the origins of his law of effect and the influence of Darwin's selectionism. It also provides the background for an unfinished book review by William W. Cumming of a biography of Thorndike. The review places in historical context Thorndike's position both on psychology as a science of behavior and on the vocabulary of that science.     

Enhanced proliferation of progenitor cells following long-term potentiation induction in the rat dentate gyrus

The dentate gyrus (DG) is among the few areas in the mammalian brain where production of new neurons continues in the adulthood. Although its functional significance is not completely understood, several lines of evidence suggest the role of DG neurogenesis in learning and memory. Considering that long-term potentiation (LTP) is a prime candidate for the process underlying hippocampal learning and memory, these results raise the possibility that LTP and neurogenesis are closely related. Here, we investigated whether or not LTP induction in the afferent pathway triggers enhanced proliferation of progenitor cells in the DG. LTP was induced by tetanic stimulation in perforant path-DG synapses in one hemisphere, and the number of newly generated progenitor (BrdU-labeled) cells in the DG was quantified. Compared with the control hemisphere (stimulated with low-frequency pulses), the LTP-induced hemisphere contained a significantly higher number of newly generated progenitor cells in the dorsal as well as ventral DG. When CPP, an NMDA receptor antagonist, was administered, tetanic stimulation neither induced LTP nor enhanced progenitor cell proliferation, indicating that NMDA receptor activation, rather than tetanic stimulation per se, is responsible for enhanced progenitor proliferation in the control animal. Our results show that tetanic stimulation of perforant path sufficient to induce LTP increases progenitor proliferation in adult DG in an NMDA receptor-dependent manner.     

Unsupervised discovery of nonlinear structure using contrastive backpropagation

We describe a way of modeling high-dimensional data vectors by using an unsupervised, nonlinear, multilayer neural network in which the activity of each neuron-like unit makes an additive contribution to a global energy score that indicates how surprised the network is by the data vector. The connection weights that determine how the activity of each unit depends on the activities in earlier layers are learned by minimizing the energy assigned to data vectors that are actually observed and maximizing the energy assigned to "confabulations" that are generated by perturbing an observed data vector in a direction that decreases its energy under the current model.     

Effect of neurofeedback on hemispheric word recognition

We applied SMR/theta neurofeedback (NF) training at central sites of 20 Israeli children aged 10-12 years, half boys and half girls. Half of the subjects received C3 training and the other half C4 training, consisting of 20 half-hour sessions. We assessed the effects of training on lateralized lexical decision in Hebrew. The lateralized lexical decision test reveals an independent contribution of each hemisphere to word recognition (Barnea, Mooshagian, & Zaidel, 2003). Training increased accuracy and sensitivity. It increased left hemisphere (LH) specialization under some conditions but it did not affect interhemispheric transfer. Training did affect psycholinguistic processing in the two hemispheres, differentially at C3 and C4. Training also increased hemispheric independence. There were surprising sex differences in the effects of training. In boys, C4 training improved LH accuracy, whereas in girls C3 training improved LH accuracy. The results suggest that the lateralized NF protocol activates asymmetric hemispheric control circuits which modify distant hemispheric networks and are organized differently in boys and girls.     

Using an AI creativity system to explore how aesthetic experiences are processed along the brain’s perceptual neural pathways

With the increased sophistication of AI techniques, the application of these systems has been expanding to ever newer fields. Increasingly, these systems are being used in modeling of human aesthetics and creativity, e.g. how humans create artworks and design products. Our lab has developed one such AI creativity deep learning system that can be used to create artworks in the form of images and videos. In this paper, we describe this system and its use in studying the human visual system and the formation of aesthetic experiences. Specifically, we show how time-based AI created media can be used to explore the nature of the dual-pathway neuro-architecture of the human visual system and how this relates to higher cognitive judgments such as aesthetic experiences that rely on these divergent information streams. We propose a theoretical framework for how the movement within percepts such as video clips, causes the engagement of reflexive attention and a subsequent focus on visual information that are primarily processed via the dorsal stream, thereby modulating aesthetic experiences that rely on information relayed via the ventral stream. We outline our recent study in support of our proposed framework, which serves as the first study that investigates the relationship between the two visual streams and aesthetic experiences.     

The temporal dynamics of visual object priming

Priming reflects an important means of learning that is mediated by implicit memory. Importantly, priming occurs for previously viewed objects (item-specific priming) and their category relatives (category-wide priming). Two distinct neural mechanisms are known to mediate priming, including the sharpening of a neural object representation and the retrieval of stimulus–response mappings. Here, we investigated whether the relationship between these neural mechanisms could help explain why item-specific priming generates faster responses than category-wide priming. Participants studied pictures of everyday objects, and then performed a difficult picture identification task while we recorded event-related potentials (ERP). The identification task gradually revealed random line segments of previously viewed items (Studied), category exemplars of previously viewed items (Exemplar), and items that were not previously viewed (Unstudied). Studied items were identified sooner than Unstudied items, showing evidence of item-specific priming, and importantly Exemplar items were also identified sooner than Unstudied items, showing evidence of category-wide priming. Early activity showed sustained neural suppression of parietal activity for both types of priming. However, these neural suppression effects may have stemmed from distinct processes because while category-wide neural suppression was correlated with priming behavior, item-specific neural suppression was not. Late activity, examined with response-locked ERPs, showed additional processes related to item-specific priming including neural suppression in occipital areas and parietal activity that was correlated with behavior. Together, we conclude that item-specific and category-wide priming are mediated by separate, parallel neural mechanisms in the context of the current paradigm. Temporal differences in behavior are determined by the timecourses of these distinct processes.     

Neuronal correlates of decisions to speak and act: Spontaneous emergence and dynamic topographies in a computational model of frontal and temporal areas

The neural mechanisms underlying the spontaneous, stimulus-independent emergence of intentions and decisions to act are poorly understood. Using a neurobiologically realistic model of frontal and temporal areas of the brain, we simulated the learning of perception–action circuits for speech and hand-related actions and subsequently observed their spontaneous behaviour. Noise-driven accumulation of reverberant activity in these circuits leads to their spontaneous ignition and partial-to-full activation, which we interpret, respectively, as model correlates of action intention emergence and action decision-and-execution. Importantly, activity emerged first in higher-association prefrontal and temporal cortices, subsequently spreading to secondary and finally primary sensorimotor model-areas, hence reproducing the dynamics of cortical correlates of voluntary action revealed by readiness-potential and verb-generation experiments. This model for the first time explains the cortical origins and topography of endogenous action decisions, and the natural emergence of functional specialisation in the cortex, as mechanistic consequences of neurobiological principles, anatomical structure and sensorimotor experience.