ePoster

State-dependent population activity, dimensionality and communication in the visual cortex

Aitor Morales-Gregorio, Anno Kurth, Junji Ito, Alexander Kleinjohann, Frédéric Barthélemy, Thomas Brochier, Sonja Grün, Sacha van Albada
Bernstein Conference 2024(2024)
Goethe University, Frankfurt, Germany

Conference

Bernstein Conference 2024

Goethe University, Frankfurt, Germany

Resources

Authors & Affiliations

Aitor Morales-Gregorio, Anno Kurth, Junji Ito, Alexander Kleinjohann, Frédéric Barthélemy, Thomas Brochier, Sonja Grün, Sacha van Albada

Abstract

Brain activity depends on ongoing behavioural and arousal states, such as attention, eye closure, or sleep. These states display measurable differences in population activity [1], dimensionality [2], noise correlations [3], and autocorrelation timescales [4]. State-dependent changes in the primary visual cortex (V1) are potentially induced by cortico-cortical signals, such as those from V4 to V1, known to mediate visual attention in macaques [5]. However, relationships between such top-down signals and the aforementioned state-dependent changes have not been demonstrated directly. To investigate state-dependent dynamics, we studied the activity in V1 of macaque (N=3, Macaca mulatta), recorded using Utah arrays [6]. We found two distinct neural manifolds, strongly correlated with eyes-open and eyes-closed states, even though the macaques were sitting in a dark room. The neural dynamics during eyes-open periods had a significantly higher dimensionality, primarily due to lower noise correlations. We hypothesized that the mechanism mediating these state-dependent changes could be top-down communication. We estimated the strength and direction of cortico-cortical communication from LFP coherence and Granger causality, and found that top-down signals from V4 to V1 are significantly stronger during the eyes-open periods. Spectral analysis revealed reduced alpha power during the eyes-open condition, aligning with alpha blocking in EEG studies. Finally, we constructed a spiking neuron model demonstrating that top-down signals could generate multiple neural manifolds. These manifolds do not reflect modulations in the mean firing rate of the network, but changes in the rates of individual neurons, leading to distinct population activity. Taken together, our in vivo and in silico analysis suggests that top-down signals can actively modulate the neural manifolds of neural networks. In the case of macaque V1, we postulate that top-down modulation from V4 induces these state-dependent changes in V1 to prepare the visual cortex for fast and efficient visual responses, resulting in a visual stand-by state when the eyes are open.

Unique ID: bernstein-24/state-dependent-population-activity-335d1756