Computational Neuroscience

Avalanche analysis from multi-electrode ensemble recordings in cat, monkey and human cerebral cortex during wakefulness and sleep

by Nima Dehghani

Integrated Support for Neuroscience Research: from Study Design to Publication

by Shayan Shahand

S. Shahand, M.W.A. Caan, A.H.C. van Kampen, S.D. Olabarriaga. In Proceedings of HealthGrid 2012 (HealthGrid Applications and Technologies Meet Science Gateways for Life Sciences).

Computational neuroscience is a new field of research in which neurodegenerative diseases are studied with the aid of... more Computational neuroscience is a new field of research in which neurodegenerative diseases are studied with the aid of new imaging techniques and computation facilities. Researchers with different expertise collaborate in these studies. A study requires scalable computational and storage capacity and information management facilities to succeed. Many virtual laboratories are proposed and developed to facilitate these studies, however most of them cover only the parts related to the computational data processing. In this paper we describe and analyse the phases of the computational neuroscience studies including the actors, the tasks they perform, and the characteristics of each phase. Based on these we identify the required properties and functionalities of a virtual laboratory that supports the actors and their tasks throughout the complete study.

Ph.D Thesis : Neural dynamics of synchronous imitative interaction

by Guillaume Dumas

Supervisors: Jacqueline Nadel & Jacques Martinerie (formerly Line Garnero)
Defended the 3rd of October 2011

Since 2002, a new neuroimaging technique called hyperscanning allows to record several participants simultaneously and... more Since 2002, a new neuroimaging technique called hyperscanning allows to record several participants simultaneously and thus to study social interaction in a reciprocal and spontaneous social context. Meanwhile, neurodynamics and sensorimotor theories suggested to understand social interaction in a more holistic approach by considering the two interacting individuals as a single system, and giving equal importance to behavior and brain activity.

This thesis presents the study of pairs of participants recorded simultaneously during spontaneous imitation of the movement of their hands, by a dual-video combined with a hyperscanning-EEG setup. A fine grained video analysis identified the episodes of interactional synchrony and imitation, thus allowing the neurodynamic characterization of various aspects of the interaction, both at the inter- and intra-individual. The first study showed that episodes of interactional synchrony were accompanied by the emergence of inter-brain phase synchronizations in several frequency bands. The second study showed a neural differentiation between self- and other-attribution of action primacy, and found a signature of the co-ownership of the action in both partners during the spontaneous imitation. The third study validated the experimental measurements with biophysical simulations of pairs of human brains. It also showed the effects of anatomical connectivity on intra-individual neural dynamics and the facilitation of the inter-individual sensorimotor coupling.

Anatomical Connectivity Influences both Intra- and Inter-Brain Synchronizations

by Guillaume Dumas

Dumas G, Chavez M, Nadel J, Martinerie J (2012) PLoS ONE 7(5): e36414. doi:10.1371/journal.pone.0036414

Recent development in diffusion spectrum brain imaging combined to functional simulation has the potential to further... more Recent development in diffusion spectrum brain imaging combined to functional simulation has the potential to further our understanding of how structure and dynamics are intertwined in the human brain. At the intra-individual scale, neurocomputational models have already started to uncover how the human connectome constrains the coordination of brain activity across distributed brain regions. In parallel, at the inter-individual scale, nascent social neuroscience provides a new dynamical vista of the coupling between two embodied cognitive agents. Using EEG hyperscanning to record simultaneously the brain activities of subjects during their ongoing interaction, we have previously demonstrated that behavioral synchrony correlates with the emergence of inter-brain synchronization. However, the functional meaning of such synchronization remains to be specified. Here, we use a biophysical model to quantify to what extent inter-brain synchronizations are related to the anatomical and functional similarity of the two brains in interaction. Pairs of interacting brains were numerically simulated and compared to real data. Results show a potential dynamical property of the human connectome to facilitate inter-individual synchronizations and thus may partly account for our propensity to generate dynamical couplings with others.

Cooperative Behavior of Artificial Neural Agents Based on Evolutionary Architectures

by Piero Savastano

Functional and laminar dissociations between muscarinic and nicotinic cholinergic neuromodulation in the tree shrew primary visual cortex

by Gregor Rainer

Acetylcholine is an important neuromodulator involved in cognitive function. The impact of cholinergic neuromodulation... more Acetylcholine is an important neuromodulator involved in cognitive function. The impact of cholinergic neuromodulation on
computations within the cortical microcircuit is not well understood. Here we investigate the effects of layer-specific cholinergic drug application in the tree shrew primary visual cortex during visual stimulation with drifting grating stimuli of varying contrast and orientation. We describe differences between muscarinic and nicotinic cholinergic effects in terms of both the layer of cortex and the attribute of visual representation. Nicotinic receptor activation enhanced the contrast response in the granular input layer of the cortex, while tending to reduce neural selectivity for orientation across all cortical layers. Muscarinic activation modestly enhanced the contrast response across cortical layers, and tended to improve orientation tuning. This resulted in highest orientation selectivity in the supra- and infragranular layers, where orientation selectivity was already greatest in the absence of pharmacological stimulation. Our results indicate that laminar position plays a crucial part in functional consequences of cholinergic stimulation, consistent with the differential distribution of cholinergic receptors. Nicotinic receptors function to enhance sensory representations arriving in the cortex, whereas muscarinic receptors act to boost the cortical computation of orientation tuning. Our findings suggest
close homology between cholinergic mechanisms in tree shrew and primate visual cortices.

Optimizing the quantity/quality trade-off in connectome inference

by Joshua Vogelstein

Predicting Human Interactive Learning by Regret-Driven Neural Networks

by Davide Marchiori

Co-authored with Massimo Warglien

Much of human learning in a social context has an interactive nature: What an individual learns is affected by what... more Much of human learning in a social context has an interactive nature: What an individual learns is affected by what other individuals are learning at the same time. Games represent a widely accepted paradigm for representing interactive decision-making. We explored the potential value of neural networks for modeling and predicting human interactive learning in repeated games. We found that even very simple learning networks, driven by regret-based feedback, accurately predict observed human behavior in different experiments on 21 games with unique equilibria in mixed strategies. Introducing regret in the feedback dramatically improved the performance of the neural network. We show that regret-based models provide better predictions of learning than established economic models.

Neural Network Models of Learning and Categorization in Multigame Experiments

by Davide Marchiori

Co-authored with Massimo Warglien

Previous research has shown that regret-driven neural networks predict behavior in repeated completely mixed games... more Previous research has shown that regret-driven neural networks predict behavior in repeated completely mixed games remarkably well, substantially equating the performance of the most accurate established models of learning. This result prompts the question of what is the added value of modeling learning through neural networks. We submit that this modeling approach allows for models that are able to distinguish among and respond differently to different payoff structures. Moreover, the process of categorization of a game is implicitly carried out by these models, thus without the need of any external explicit theory of similarity between games. To validate our claims, we designed and ran two multigame experiments in which subjects faced, in random sequence, different instances of two completely mixed 2x2 games. Then, we tested on our experimental data two regret-driven neural network models, and compared their performance with that of other established models of learning and Nash equilibrium.

CRITIQUE OF MIND 2: THE COMPUTATIONAL RELEVANCE OF ‘MIND’.

by stanley wilkin

This article is a continuation of Critique of Mind/Intentionality, looking at the illusory nature of discrete characteristics. I suggest the historical development of mind and consciousness, dealt with fully in The Myth of Mind and Consciousness.

The myth of mind asnd consciousness is briefly considered with references to 'You', 'I' and the illusory state of... more The myth of mind asnd consciousness is briefly considered with references to 'You', 'I' and the illusory state of individual concepts of mind.

Decodifica di segnali neurali naturali attraverso una rete neurale artificiale/ Decoding natural neural signals by means of an Artificial Neural Network

by Rita Pizzi

The link includes presentation of the research activity and a full paper

Abbiamo costruito un ibrido costituito da una rete di cellule neurali umane che comanda un robot in grado di muoversi... more Abbiamo costruito un ibrido costituito da una rete di cellule neurali umane che comanda un robot in grado di muoversi in base ai comandi da noi impartiti.

Rapid reshaping of human motor generalization

by Jordan Taylor

Trial-by-trial motor adaptation: a window into elemental neural computation

by Jordan Taylor

Human motor control and learning of novel dynamic forces and the influence of attentional control

by Jordan Taylor

Experience-Dependent Adaptation of the Spatial Generalization of Human Motor Adaptation

by Jordan Taylor

Advances in Computational Motor Control Vol. 3 (2004)

Feedback-dependent generalization of visuomotor adaptation

by Jordan Taylor

Advances in Computational Motor Control Vol. 10 (2011)

Why The Brain Separates Face Recognition From Object Recognition (2011)

by Joel Leibo

Experimental validation of a hybrid computational model for selective stimulation using transverse intrafascicular multichannel electrodes

by Marco Capogrosso

FIRST NAME EQUALLY CONTRIBUTED SR AND MC

Modeling the face-to-face effect: Sensory population dynamics and active vision can contribute to perception of social context

by Nick Wilkinson

Int. Conf. on Development and Learning 2011

We introduce a novel dynamical model for visual attention based on stimulus induced population dynamics in an... more We introduce a novel dynamical model for visual attention based on stimulus induced population dynamics in an oscillatory medium, and apply this model to active perception of social content in still images. Making use of images from the newly emerging face-to-face paradigm in social developmental psychology, we show that this model generates patterns of eye movements that exhibit increased frequency of gaze shifts between actors in the social condition, as do infants at 16 months of age. The number of gaze shifts can inform useful levels of classification for the social content in the images, demonstrating a potential role for the dynamics of active perception in social cognition. This adaptive performance does not require any long term changes in structure or information storage. Our results further suggest a potential functional role in selective attention for the spiral wave activity recently observed in primary visual neo-cortex.

Incidental exposure to no-smoking signs primes craving for cigarettes

by Brian Earp

Earp, B. D., Dill, B., Harris, J., Ackerman, J., and Bargh, J. (2011). Incidental exposure to no-smoking signs primes craving for cigarettes: An ironic effect of unconscious semantic processing? Yale Review of Undergraduate Research in Psychology, Vol 2, No 1, 12-23.

The present study tests whether incidental exposure to no-smoking signs may ironically boost craving for cigarettes in... more The present study tests whether incidental exposure to no-smoking signs may ironically boost craving for cigarettes in smokers. Smokers viewed photographs in which no-smoking signs were either incon- spicuously embedded (prime) or edited out (control). Participants then used a joystick to make quick approach vs. avoid motions while viewing smoking-related and neutral stimuli on a computer screen (Chen & Bargh, 1999). We hypothesized that primed smokers, but not controls, would show an automatic reach bias toward the smoking-related stimuli. The data supported our prediction. Possible mechanisms for the effect are discussed, as well as implications for public health policy, negation-based social campaigns in general, and our understanding of the unconscious processing of semantic information.