Cortical state fluctuations during sensory decision making

Abstract

Neocortical activity varies between states of "synchronization" and "desynchronization", with desynchronized states believed to occur specifically in regions engaged by the task. To disambiguate whether desynchronization is linked to task performance or engagement, we trained mice on tasks in which incorrect responses due to disengagement (neglect) differed from inaccurate task performance (incorrect choices). Using widefield calcium imaging to measure cortical state across many areas simultaneously, we found that desynchronization was correlated with engagement rather than accuracy. Consistent with this link between desynchronization and engagement, we found that rewards had a long-lasting desynchronizing effect. To determine whether engagement-related changes in cortical state depended on the sensory modality, we trained mice on visual and auditory task versions and found that desynchronization was similar in both and more pronounced in somatomotor than either sensory cortex. We conclude that variations in cortical state are predominately global and closely relate to variations in task engagement.

Wide-Field Calcium Imaging of Dynamic Cortical Networks During Locomotion

“…Blood flow increases with neuronal activation, and oxygenated blood absorbs light with peak absorption at ~530 nm, decreasing the duration of the increased GCaMP fluorescence (Ma et al, 2016). Therefore, additional experiments were performed to evaluate the effects of hemodynamics and other Ca 2+ independent fluorescence changes such as flavoprotein autofluorescence (Vanni and Murphy, 2014;Jacobs et al, 2018), using 4 mice (1 from the original cohort and 3 additional). We used dual-wavelength illumination to capture both Ca 2+ -dependent (470 nm, blue light) and Ca 2+ -independent (405 nm, violet light) GCaMP6f signals on consecutive frames using a Cairn OptoLED driver (Cairn OptoLED, P1110/002/000; P1105/405/LED, P1105/470/LED) (Ma et al, 2016;Allen et al, 2017;Jacobs et al, 2018;Musall et al, 2019;MacDowell and Buschman, 2020).…”

“…Therefore, additional experiments were performed to evaluate the effects of hemodynamics and other Ca 2+ independent fluorescence changes such as flavoprotein autofluorescence (Vanni and Murphy, 2014;Jacobs et al, 2018), using 4 mice (1 from the original cohort and 3 additional). We used dual-wavelength illumination to capture both Ca 2+ -dependent (470 nm, blue light) and Ca 2+ -independent (405 nm, violet light) GCaMP6f signals on consecutive frames using a Cairn OptoLED driver (Cairn OptoLED, P1110/002/000; P1105/405/LED, P1105/470/LED) (Ma et al, 2016;Allen et al, 2017;Jacobs et al, 2018;Musall et al, 2019;MacDowell and Buschman, 2020). An excitation filter (ET480/40, Chroma) was placed in front of the 470 nm LED, then both light sources were combined into the parallel light path of a Nikon AZ100M macroscope through a dichroic mirror (425 nm, Chroma T425lpxr), and then reflected off a second dichroic (505 nm, Chroma T505pxl) to the brain.…”

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

“…Measures of neural correlations and variability are widely used in neuroscience to characterize neural processes. During task states, neural variability has consistently been shown to be reduced during tasks across human functional magnetic resonance imaging (fMRI) (He, 2011(He, , 2013 , local neural populations (Churchland et al, 2010;Hennequin et al, 2018;Jacobs et al, 2018) , and both spiking (Hennequin et al, 2018;Litwin-Kumar and Doiron, 2012) and mean-field rate models (Deco and Hugues, 2012;Ponce-alvarez et al, 2015) . Despite this convergence in the neural variability literature, there are disparities in the use and interpretation of neural correlations.…”

Rigbox: an Open-Source Toolbox for Probing Neurons and Behavior

“…These have included unforced choice, multisensory choice, behavior matching, and bandit tasks, using wheels, levers, balls, and lick detectors. In addition, Rigbox has allowed us to rapidly integrate these tasks with a variety of recording techniques, including electrode recordings, 2-Photon imaging, and fiber photometry, and neural perturbations, such as scanning laser inactivation and dopaminergic stimulation (Jun et al, 2017;Jacobs et al, 2018;Lak et al, 2018;Steinmetz et al, 2018;Shimaoka et al, 2018;Zatka-Haas et al, 2018). There are pros and cons to following different programming paradigms for software developers who decide how a user will programmatically design a behavioral task.…”