Neural systems

…and the genetic basis of behavior), neural systems, and translational research on the causes, prevention, diagnosis and treatment of neurological and psychiatric disorders. Fellows receive USD 150,000 per year for three

…approaches together to understand how neural systems support behaviour and cognition. Research connects systems neuroscience with computational models, emphasizing explanations of brain function and exchange between empirical and theoretical researchers. The main meeting is at Fairmont The Queen Elizabeth and workshops are at Le Westin Montréal. Abstract submission is closed. Abstracts use double-blind review, with deci

Foundational biology from molecules and cells to organisms, populations, ecosystems and biomes. Named areas include biochemistry, genomics, synthetic biology, animal behavior, physiology and neural systems. Neural-systems research includes developmental, genetic, molecular and cellular organization, sensorimotor activation, synaptic and circuit plasticity, and computational approaches. The call also supports biological datasets and methods for observing, measuring, modeling and manipulating living systems. Single investigators, teams and consortia may propose; routine applications, product or

…a premier forum for computational and systems neuroscience. Attendees exchanged cutting-edge research in a single-track main meeting and in-depth specialized workshops, reflecting Cosyne’s mission to understand how neural systems function.

…to deny that algorithms are useful to systems neuroscience, and to interpret neural systems usi

Deep learning provides new data-driven tools to relate neural activity to perception and cognition, aiding scientists in developing theories of neural computation that increasingly resemble biological systems both at the level of behavior and of neural activity. But what in a deep neural network should correspond to what in a biological system? This question is addressed implicitly in the use of comparison measures that relate specific neural or behavioral dimensions via a particular functional form. However, distinct comparison methodologies can give conflicting results in recovering even a k

…used to simulate the dynamics of neural systems, but identifying parameters that explain experimental measurements is challenging. In particular, while these models are differentiable and would allow for gradient-based parameter optimization, the nonlinear dynamics inherent of neural systems often lead to many local minima and extreme sensitivity to initial conditions. To address this, we improve a recently developed probabilistic integration method that enables gradient-based parameter inference in ODEs known as ``Physics-Enha

…have resulted in new methods to embody neural systems into simulated environments to elicit dynamic goal-directed activity (Kagan et al., 2023, Biotechnology Advances.). Evidence of learning from in vitro neurons was established in a simplified game of Pong through closed-loop real-time electrophysiological recordings and patterned stimulations via a system called DishBrain (Kagan et al., 2022. Neuron.). Analysis of dynamic activity changes within these networks revealed key correlates associated with the appearance of

Artificial neural networks can be useful for studying brain functions. In cognitive neuroscience, recurrent neural networks are often used to model cognitive functions. I will first offer my opinion on what is missing in the classical use of recurrent neural networks. Then I will discuss two lines of ongoing efforts in our group to move beyond the classical recurrent neural networks by studying multi-system neural networks (the talk will focus on two-system networks). These are networks that combine modules for several neural systems, such as vision, audition, prefrontal, hippocampal systems.

…theoretical approaches to problems in systems neuroscience, in order to understand how neural systems function. The main meeting is single-track, with invited talks selected by the Executive Committee and additional talks and posters selected by the Program Committee based on submitted abstracts. The workshops feature in-depth discussion of current topics of interest in a small group setting.

Neural systems are remarkably robust against various perturbations, a phenomenon that still requires a clear explanation. Here, we graphically illustrate how neural networks can become robust. We study spiking networks that generate low-dimensional representations, and we show that the neurons’ subthreshold voltages are confined to a convex region in a lower-dimensional voltage subspace, which we call a ‘bounding box.’ Any changes in network parameters (such as number of neurons, dimensionality of inputs, firing thresholds, synaptic weights, or transmission delays) can all be understood as def

Investigations of the neural systems mediating the processing of social groups defined by race, specifically Black and White race groups in American participants, reveals significant overlap with brain mechanisms involved in emotion. This talk will provide an overview of research on the neuroscience of race and emotion, focusing on implicit race attitudes. Implicit race attitudes are expressed without conscious effort and control, and contrast with explicit, conscious attitudes. In spite of sharp decline in the expression of explicit, negative attitudes towards outgroup race members over the l

…variation associated with different neural systems and due to different selection pressures, he will be addressing intriguing questions like ‘Why are there so many neurons in the cerebellum?’, ‘Is the neocortex the ‘intelligent’ bit of the brain?’, and ‘What explains that the recognition by humans of emotional expressions is disrupted by trancranial magnetic stimulati

Theoretical and computational models of neural systems have been traditionally focused on small neural circuits, given the lack of reliable data on large-scale brain structures. The situation has started to change in recent years, with novel recording technologies and large organized efforts to describe the brain at a larger scale. In this talk, Professor Mejias from the University of Amsterdam will review his recent work on developing anatomically constrained computational models of large-scale cortical networks of monkeys, and how this approach can help to answer important questions in large