Thirst regulates motivated behavior through modulation of brainwide neural population dynamics

Abstract

Neuron activity across the brain How is it that groups of neurons dispersed through the brain interact to generate complex behaviors? Three papers in this issue present brain-scale studies of neuronal activity and dynamics (see the Perspective by Huk and Hart). Allen et al. found that in thirsty mice, there is widespread neural activity related to stimuli that elicit licking and drinking. Individual neurons encoded task-specific responses, but every brain area contained neurons with different types of response. Optogenetic stimulation of thirst-sensing neurons in one area of the brain reinstated drinking and neuronal activity across the brain that previously signaled thirst. Gründemann et al. investigated the activity of mouse basal amygdala neurons in relation to behavior during different tasks. Two ensembles of neurons showed orthogonal activity during exploratory and nonexploratory behaviors, possibly reflecting different levels of anxiety experienced in these areas. Stringer et al. analyzed spontaneous neuronal firing, finding that neurons in the primary visual cortex encoded both visual information and motor activity related to facial movements. The variability of neuronal responses to visual stimuli in the primary visual area is mainly related to arousal and reflects the encoding of latent behavioral states. Science , this issue p. eaav3932 , p. eaav8736 , p. eaav7893 ; see also p. 236

Accurate Localization of Linear Probe Electrode Arrays across Multiple Brains

“…Interpretation of neural activity in terms of neural circuits relies on accurate localization of individual electrodes and thereby the recorded neurons. Several workflows have been described ( Allen et al, 2019 ; Steinmetz et al, 2019 ; Siegle et al, 2021 ), but groundtruth experiments assessing the accuracy of electrode localization are lacking. We took advantage of ChR2-EYFP expression in focused axonal projections.…”

“…This need is especially acute for recently developed Neuropixels probes. The probes are commercially available and have been rapidly adopted by many laboratories ( Evans et al, 2018 ; Krupic et al, 2018 ; Allen et al, 2019 ; Bennett et al, 2019 ; Gardner et al, 2019 ; Kostadinov et al, 2019 ; Musall et al, 2019 ; Steinmetz et al, 2019 ; Trautmann et al, 2019 ; Böhm and Lee, 2020 ; Luo et al, 2020 ; Sauerbrei et al, 2020 ; Siegle et al, 2021 ). Neuropixels probes ( Jun et al, 2017 ; Steinmetz et al, 2021 ) provide recordings across 960 recording electrodes distributed over 9.6 mm shanks.…”

“…Neuropixels probes ( Jun et al, 2017 ; Steinmetz et al, 2021 ) provide recordings across 960 recording electrodes distributed over 9.6 mm shanks. Because of their long shanks, Neuropixels recordings naturally span multiple brain areas ( Jun et al, 2017 ; Allen et al, 2019 ; Steinmetz et al, 2019 ; Siegle et al, 2021 ). Neuropixels probes lack the electronic elements to pass the large currents that are required to produce electrolytic lesions.…”

“…Localizing electrodes on linear probes has been achieved by labeling silicon probes with fluorescent dye and post hoc analysis of the recorded tissue using histologic methods ( DiCarlo et al, 1996 ; Jensen and Berg, 2016 ; Guo et al, 2017 ; Salatino et al, 2017 ), aided by identifying known electrophysiological features of specific anatomic locations ( Jun et al, 2017 ; Allen et al, 2019 ; Steinmetz et al, 2019 ; Siegle et al, 2021 ). Our methods are building on this approach and assess the accuracy of such workflows using groundtruth experiments.…”

Topology of synaptic connectivity constrains neuronal stimulus representation, predicting two complementary coding strategies

“…These results were obtained in a highly detailed model, albeit one of only an individual microcircuit acting alone. The nature of biological neural manifolds is likely determined as well by long-range connections and dynamic interactions between different brain regions, meaning a purely local view is limited [ 34 , 35 ]. Yet, our results provide predictions on the general principles that may be employed to encode information in lower-dimensional neural manifolds.…”