Neuromatch 5 ePosters

Surround suppression is ubiquitous in visual processing and perception. Neurophysiology and modeling studies reveal a rich set of spatial context effects in the Primary Visual Cortex, whereby surrounding stimuli nonlinearly modulate (e.g., suppress) the responses of a center target stimulus. Studies suggest that the…

One of the many ocean swells in the history of computational approaches to mind and brain is the rise and fall of cognitive architectures. Although supplanted by neural networks as the dominant modelling modality, cognitive architectures possess many attributes sorely coveted by the computational modeller: large,…

Contemporary Bayesian theories of the mind highlight the role of prediction errors as a driving force in learning processes and the updating of our models of the world and of ourselves. This process is postulated to manifest both at explicit levels (e.g., subjective responses) and at implicit levels (e.g., eye…

Experimental evidence suggests that the brain is able to encode memories in the phase of ongoing low-frequency oscillations. Recently, trainable recurrent neural networks (RNNs) have emerged as promising models of how neural circuits process information. However, short-term memory maintenance in these networks has…

Brain-computer interface (BCI) applications enable innovative communication with and control of external devices for people with motor deficits by providing a bridge between brain signals and motor actions to replace and restore beneficial function. To measure neural response, Electrocorticography (ECoG) has been…

Due to the aging population and life digitalization, humanoid robots could be seen as potential community resources to accompany the elderly, support remote work, and improve individuals' mental or physical health. To enhance human-robot interaction, it is essential for robots to become more socialized via processing…

Parkinson's patients face many challenges in their daily lives due to their symptoms. Deep Brain Stimulation (DBS) is an intervention that uses electrical stimulation to help alleviate some of the extrapyramidal symptoms. However, DBS also has some notable side effects, one of which is its impact on sleep. The impact…

How does the organization of neural information processing enable humans’ sophisticated cognition? Here we decompose functional interactions between brain regions into synergistic and redundant components, revealing their distinct information-processing roles. Combining functional, structural, and diffusion-weighted…

Memory reconsolidation is the mechanism by which consolidated memories are updated in strength and/or content. Thus, memory reactivation can enhance the retention of reactivated items at long delays. An underlying hypothesis to these findings suggests that reconsolidation would be “reactivation specific”, implying…

Schizophrenia is considered to be a complex illness with multiple pathways contributing to its clinical phenotype and is argued to be a disorder of disrupted brain network organization. Structural covariance in schizophrenia indicates a system-level brain maturation disruption overlapping with patterns of disturbed…

INTRODUCTION Graph theory is a state of the art approach to assess functional connectivity (FC) disruption in neurological disorders. However, this methodology does not allow distinction between positive and negative FC correlations; negative correlations, or anticorrelations, are usually either discardes or taken as…

Behavior results from neural computations that occur at the level of populations of neurons, and understanding how a given computation produces a particular behavior requires a characterization of how distinct signals interact and evolve. For example, in motor cortex, discrete reaches are generated by a combination of…

The placebo and nocebo effects highlight the importance of expectations in modulating pain perception. Yet, we don't need an external source of information to form expectations about pain. The brain can learn to predict pain in a more fundamental way, simply by experiencing fluctuating, non-random streams of noxious…

Neurons in the cortico-basal ganglia circuit become excessively synchronised at beta frequencies (15-35 Hz) in Parkinson’s disease. However, it is unclear how this synchronised firing evolves across the network. Beta synchrony has often been assumed to emerge homogenously across the neurons within anatomical…

EEG has several applications in neuroscience, neural engineering, and diagnosis of neurological disorders. It records the electrical activity of the brain tissues resulting from the interaction of distinct neuronal populations. Various methods have been developed for the automatic classification of EEG signals. These…

In the social context, animal species depend on vocal communication throughout their life, as they are the primary source of communication, yet the neurophysiological underpinnings of the perception of intra-specific communication signals are still poorly understood. The brain processes underpinning the capacity to…

We examine how the saccade mechanism from biological vision can be used to make deep neural networks more efficient for classification and object detection problems. Our proposed approach is based on the ideas of attention-driven visual processing and saccades, miniature eye movements influenced by attention. We…

One of the important subfields of computational neuroscience is network neuroscience, which widely uses machine learning techniques, these include artificial neural networks. The latter ones owe a lot to neuroscience in the history of their development. Artificial neural networks (ANN) are often represented in the…

Hopfield networks are artificial neural networks which store memory patterns on the states of their neurons by choosing recurrent connection weights and update rules such that the energy landscape of the network forms attractors around the memories. How many stable, sufficiently-attracting memory patterns can we store…

Decisions about where to move the eyes depend on neurons in frontal eye field (FEF). Movement neurons in FEF accumulate salience evidence derived from FEF visual neurons to select the location of a saccade target among distractors. How visual neurons achieve this salience representation is unknown. We present a…

Convolutional neural networks currently provide the best models of biological vision. However, their decision behavior, including the facts that they are deterministic and use equal number of computations for easy and difficult stimuli, differs markedly from human decision-making, thus limiting their applicability as…

The role of the interface between internal and external factors which shape an agent's experience have been considered for millennia. In the 21st century, we have access to new technologies and ideas, but what are the breakthroughs we need that will afford new discoveries? Similarly, what disciplinary boundaries are…

Response inhibition, the ability to withhold actions that are no longer appropriate, is commonly studied using the stop-signal task. Participants’ performance on the task is often understood as a race between a go- and stop-process, making it tempting to fit evidence accumulation models as the go- and stop-racers.…

Neural activity in response to sensory stimuli leads to a reorganization of neuronal ensemble dynamics, which can be captured by lower-dimensional latent dynamics. Recurrent Neural Networks (RNN) have been proven successful at extracting such latent representations of neural dynamics. Here, we applied an RNN to the…