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Isolated correlates of somatosensory perception in the posterior mouse cortex

Michael Sokoletsky,David Ungarish,Ilan Lampl · COSYNE 2022

To uncover the neural mechanisms of stimulus perception, experimenters commonly use tasks in which subjects are repeatedly presented with a weak stimulus and instructed to report, via movement, if they perceived the stimulus. The difference in neural activity between reported stimulus (hit) and unreported stimulus (miss) trials is then seen as potentially perception-related. However, recent studies found that activity related to the report spreads throughout the brain, calling into question to what extent such tasks may be conflating activity that is perception-related with activity that is re

Thu, Mar 17, 2022

ePoster · Behavioral Neuroscience

Anatomically-aligned neural processing of the IBL task

Shuqi Wang, Liam Paninski · Bernstein Conference 2024

Understanding how tasks are processed across the entire brain is a central yet complex question in neuroscience. Recently, the release of brainwide electrophysiological recordings in a standardized behavior task offers an unprecedented opportunity to approach this question. In this paper, we characterize the signal activity of all the cortical regions systematically, and correlate the resulting functional properties with their corresponding anatomical positions. Taking advantage of the proposed brainwide reduced-rank regression encoding model that is unified and well-performing, we measured tw

ePoster · Computational Neuroscience

Normal brain function results from directed causal interactions between brain regions. However, the large-scale spatial and temporal structure of these interactions remains unclear. Lagged correlations between the activity of different brain regions may reflect their directed causal interactions. Thus, we combined magnetoencephalography (MEG) and machine learning approaches to characterize and disentangle the structure of lagged correlations in the human brain. We computed lagged correlations between all pairs of cortical regions and frequencies of neural activity. We employed curvature-regul

ePoster · Neuroscience

Elucidating the state-dependence of cortical involvement in decision-making

Zeinab Mohammadi, David W. Tank, Carlos Brody, Jonathan Pillow, Lucas Pinto, Joshua Glaser · COSYNE 2025

When making decisions, animals can employ many strategies, from relying on environmental stimuli to relying on internal biases. The roles of cortical regions in shaping these decision-making strategies remain unclear, often because we lack direct access to these internal variables. Here, we investigated how optogenetic inactivation of 29 motor, sensory, or association cortical regions affects decision-making strategies in 20 mice performing a virtual T-maze task in which they were rewarded for choosing the side with more visual cues. To determine mice’s underlying strategies on any trial, we f

ePoster · Neuroscience

Bayesian inference of cortico-cortical effective connectivity in networks of neural mass models

Matthieu Gilson, Cyprien Dautrevaux, Olivier David, Meysam Hashemi · FENS Forum 2024

The characterization of brain activity has become a cornerstone of neuroscience to study cognition and neuropathologies. Here we focus on models of neural masses that aim to fit neurophysiological signals like EEG and MEG, in particular by optimizing interactions between brain regions, following previous work on the dynamic causal model (DCM) . We compare several modern Bayesian inference schemes for model inversion on simulated data . We benchmark the identifiability of local parameters governing the interplay between several neuronal populations in each region, as well as global parameters t

ePoster · Neuroscience

Normal brain function results from directed causal interactions between brain regions. However, the large-scale spatial and temporal structure of these interactions remains unclear. Lagged correlations between the activity of different brain regions may reflect their directed causal interactions. Thus, we combined magnetoencephalography (MEG) and machine learning approaches to characterize and disentangle the structure of lagged correlations in the human brain.We computed lagged correlations between all pairs of cortical regions and frequencies of neural activity. We employed variational autoe

ePoster · Neuroscience

Neural underpinnings of conflict between memory and sensory-driven experiences

Manish Prajapat, Nirupam Das, Vaishnavi Vijayasankar, Balaji Jayaprakash · FENS Forum 2024

Declarative memories, comprising explicit knowledge of facts and experiences, are known to be dependent on the hippocampus. This study posited the CA1 subfield of the hippocampus as a pivotal neural locus for retrieving past experiences. We hypothesized that if the behaviour associated with these memories is not congruent with the current sensory information, it creates an internal conflict, potentially leading to a mixed-reality perception that suppresses the solely sensory or memory-driven behaviours. Employing the tet-tag system and optogenetics in transgenic mice, we activated memory ensem

ePoster · Neuroscience