Biomathematics / Computational Biology Colloquium

Task-evoked activity quenches neural correlations and variability across cortical areas

Speaker: Takuya Ito, Center for Molecular and Behavioral Neuroscience, Rutgers University

Location: Warren Weaver Hall 1314

Date: Tuesday, February 4, 2020, 12:30 p.m.


Many large-scale functional connectivity studies have emphasized the importance of communication through increased inter-region correlations during task states. In contrast, spiking electrophysiology studies have demonstrated that task states primarily reduce correlations among pairs of neurons, likely enhancing their information coding by suppressing shared spontaneous activity. In this talk, I will adjudicate between these conflicting perspectives and assess whether brain regions during task states tend to increase or decrease their correlations. I will present empirical evidence demonstrating that variability and correlations primarily decrease during task states across a variety of cortical regions in two highly distinct data sets: non-human primate spiking data and human functional magnetic resonance imaging data. Moreover, this observed variability and correlation reduction was accompanied by an overall increase in dimensionality (reflecting less information redundancy) during task states, suggesting that decreased correlations increased information coding capacity. Finally, using dynamical systems modeling and analysis (with spiking and neural mass computational models), I will show that task-evoked activity increases the stability around a stable attractor, thereby quenching neural variability and correlations. Together, these results provide an integrative mechanistic account that encompasses measures of large-scale neural activity, variability, and correlations during spontaneous and task-evoked states in neural systems.