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Crossing scales: understanding collective neural activity

Organizers

Anna Levina  | University of Tübingen, Germany
Roxana Zeraati  | University of Tübingen, Germany

Abstract

Growing evidence suggests that to fully understand how the brain operates, we need to study neural activity on the population level. The collective neural activity can manifest across different scales: from local circuits within a single brain area to activity distributed across the whole brain. Recent advances in experimental techniques have enabled us to record simultaneously from a large group of neurons (e.g. neuropixel recordings or calcium imaging) or run multimodal recordings across different scales (e.g. Neural Event Triggered fMRI recordings). Thus we have an unprecedented amount of data to develop and verify theories explaining and quantifying collective neuronal activity. The current workshop aims at reviewing what we have learned so far and building bridges between different approaches.

There are many different ways to describe the collective behavior of neuronal populations and analyze the high-dimensional data. One option is to use the statistical physics point of view and study the features of snapshots of the activity. This approach can uncover complex scaling behavior and lead to more universal theories of neuronal dynamics. From a different point of view, we can use large scale computational models and the dynamical systems approach to describe circuits or even the whole-brain dynamics. Validation of such models in the date requires advanced methods to characterize activity in large scale neuronal recordings. To this end, novel dimensionality reduction techniques (e.g. finding underlying manifolds of high dimensional neural activity) can help us to understand the population code better. In this workshop, we aim at bringing together the different views on how the collective neural activity can be characterized and modeled. We invite speakers using different approaches and experimental paradigms to discuss their experimental findings, models, and data analysis tools and uncover which type of questions they can answer.

 

Schedule