Flexible Computation in Cortical Networks

The flexible nature of information processing is a remarkable feature of cognition in the healthy brain.
Contextual information from either internal (arousal, mood, …) or external (sensory) variables can indeed greatly affect the outcome of diverse cortical processes (perception, decisions, …). However, despite extensive research, our understanding of how contextual signals modulate cortical information processing remains elusive.

In our research, we explore the mechanisms by which modulation of recurrent network dynamics can alter the computation performed by cortical assemblies. We investigate this question by combining theoretical modeling of spiking network dynamics and experimental analysis of sensory processing in the mouse visual cortex during behavior.

Interneuronal Modulation of Cortical Processing

Understanding cortical inhibition and its diverse roles remains a key challenge in neurophysiological research.
Traditionally, inhibition has been recognized for controlling the stability and rhythmicity of network dynamics, or refining the spatiotemporal properties of cortical representations.
In our current research, we explore the possibility that specific types of interneurons may play a complementary role, they could modulate the computational properties of neural networks.
We also explore how dysfunctions in these interneuronal populations may disrupt the network’s ability to switch between computational modes, thus impacting the flexibility of cortical processing and potentially contributing to various neurodevelopmental and psychiatric disorders.

InProsMod

This project was funded by an European Postdoctoral Fellowships from the Marie Skłodowska-Curie Actions of the European Union’s Research and Innovation Program.

Project Summary

Brain disorders are one of the greatest health challenges. It is estimated that around 30% of Europeans will suffer from a neurological and/or mental disorder at some point in their live. Given their immense socio-economic impact, it is therefore crucial to find new treatments for brain disorders. However, cognition in the healthy brain relies on a tremendous complexity at the cellular and circuit levels. Part of this complexity resides in the presence of diverse interneuronal circuits that enable inhibitory interactions between brain modules. One such circuit is the inhibitory network found in the most superficial layer of the cortex (Layer 1, L1) that is strongly driven by contextual information from higher order brain modules (i.e. top-down signals). In this project, I characterized the synaptic and circuit properties underlying the top-down control of cortical networks by L1 interneurons. My analysis revealed that the activity of L1 interneurons was strongly dependent on the N-methyl-D-aspartate receptor (NMDAR). Next, I found that normal sensorimotor function was dependent on L1 integration and was impaired upon deletion of the NMDAR in L1 interneurons. Those results therefore emphasized the important contribution of the cellular mechanisms (here the NDMAR) in L1 interneurons in shaping cortical processing in the healthy brain. Importantly, this study points to a new therapeutic target for NMDAR-related diseases such as schizophrenia or depression: L1 interneurons. By suggesting new therapeutic approaches, the fundamental knowledge generated in this action could therefore have crucial implications for brain disorders.