Information processing through correlated and coordinated responses


David Dahmen  | Forschungszentrum Jülich, Germany
Johannes Zierenberg | Max Planck Institute for Dynamics and Self-Organization, Germany


Information processing in the brain is believed to arise from the coordinated response of neural activities in large populations across multiple areas. Such coordinated responses give rise to correlations in local circuits that reflect not only their internal state, but also the relevant information about the input to be processed. Understanding how such correlations are shaped by the interplay between network states and input properties is therefore essential to understand how sensory information is transformed across the multiple processing stages of the brain. Recent experimental and numerical studies addressed the question of how neural responses are shaped by both network states and input features. This includes work on network models that link computational performance to different
dynamical regimes that are controlled by multiple mechanisms, from overall strength, heterogeneity and spatial structure of connections, to excitation-inhibition balance, to specific low-rank connectivity structures or local synaptic motifs.

Likewise, experimental and theoretical work analyzed how neural dynamics are shaped by different features of the input, such as their spectrum or intrinsic dimensionality, identifying unique representations in neural activity. In this workshop, we bring together experts on correlated and coordinated neural dynamics with the goal to engage into a joint discussion on how inputs (re)shape collective neural responses. How does the observed neural activity differ across cortical regions? How is this affected by input? And what does this mean for information processing? We want to address these and other questions, work out possibilities to test theoretical predictions by experiments, and discuss functional implications.

Schedule (CEST)

Tuesday, Sept 13


Johannes Zierenberg | Max Planck Institute for Dynamics and Self-Organization
David Dahmen | Forschungszentrum Jülich


Carsen Stringer | Janelia Research Campus, USA
Large-scale recordings reveal the interplay between brainwide behavioral and cognitive representations


Guillermo Barrios Morales | Universidad de Granada, Spain
Scale-invariance & near-critical behavior across the mouse brain: a renormalization group approach


Alessandro Sanzeni | Columbia University, USA
Mechanisms underlying reshuffling of visual responses by optogenetic stimuli in mice and monkeys


30 min break


Roxana Zeraati | University of Tübingen, Germany
Flexible modulation of timescales during attention enabled by strong recurrent dynamics in spatial networks


Alex Cayco-Gajic | Ecole Normale Supérieure de Paris, France
Covariability in neural data tensors




End of first day

Wednesday, Sept 14


Juan Gallego | Imperial College London, UK
Nonlinear manifolds underlie neural population activity during behaviour


Chengcheng Huang | University of Pittsburgh, USA
Modulation of information flow in cortical circuits


Matthieu Gilson | INSERM-AMU, France
Learning in neuronal networks: processing high-order statistics embedded in time series for classification tasks


30 min break


Matthias Loidolt | University College London, UK
Perception and propagation of activity through the cortical hierarchy is determined by neural variability


Friedrich Schuessler | TU Berlin, Germany
Aligned and oblique dynamics in recurrent neural networks


Closing discussion