Dataset Information

Voltage imaging of waking mouse cortex reveals emergence of critical neuronal dynamics.

ABSTRACT: Complex cognitive processes require neuronal activity to be coordinated across multiple scales, ranging from local microcircuits to cortex-wide networks. However, multiscale cortical dynamics are not well understood because few experimental approaches have provided sufficient support for hypotheses involving multiscale interactions. To address these limitations, we used, in experiments involving mice, genetically encoded voltage indicator imaging, which measures cortex-wide electrical activity at high spatiotemporal resolution. Here we show that, as mice recovered from anesthesia, scale-invariant spatiotemporal patterns of neuronal activity gradually emerge. We show for the first time that this scale-invariant activity spans four orders of magnitude in awake mice. In contrast, we found that the cortical dynamics of anesthetized mice were not scale invariant. Our results bridge empirical evidence from disparate scales and support theoretical predictions that the awake cortex operates in a dynamical regime known as criticality. The criticality hypothesis predicts that small-scale cortical dynamics are governed by the same principles as those governing larger-scale dynamics. Importantly, these scale-invariant principles also optimize certain aspects of information processing. Our results suggest that during the emergence from anesthesia, criticality arises as information processing demands increase. We expect that, as measurement tools advance toward larger scales and greater resolution, the multiscale framework offered by criticality will continue to provide quantitative predictions and insight on how neurons, microcircuits, and large-scale networks are dynamically coordinated in the brain.

SUBMITTER: Scott G

PROVIDER: S-EPMC4261090 | biostudies-other | 2014 Dec

REPOSITORIES: biostudies-other

ACCESS DATA

Publications

Voltage imaging of waking mouse cortex reveals emergence of critical neuronal dynamics.

Scott Gregory G Fagerholm Erik D ED Mutoh Hiroki H Leech Robert R Sharp David J DJ Shew Woodrow L WL Knöpfel Thomas T

The Journal of neuroscience : the official journal of the Society for Neuroscience 20141201 50

Complex cognitive processes require neuronal activity to be coordinated across multiple scales, ranging from local microcircuits to cortex-wide networks. However, multiscale cortical dynamics are not well understood because few experimental approaches have provided sufficient support for hypotheses involving multiscale interactions. To address these limitations, we used, in experiments involving mice, genetically encoded voltage indicator imaging, which measures cortex-wide electrical activity a ...[more]

PMID: 25505314

Similar Datasets

Project description:Sensory information is encoded by populations of cortical neurons. Yet, it is unknown how this information is used for even simple perceptual choices such as discriminating orientation. To determine the computation underlying this perceptual choice, we took advantage of the robust visual adaptation in mouse primary visual cortex (V1). We first designed a stimulus paradigm in which we could vary the degree of neuronal adaptation measured in V1 during an orientation discrimination task. We then determined how adaptation affects task performance for mice of both sexes and tested which neuronal computations are most consistent with the behavioral results given the adapted population responses in V1. Despite increasing the reliability of the population representation of orientation among neurons, and improving the ability of a variety of optimal decoders to discriminate target from distractor orientations, adaptation increases animals' behavioral thresholds. Decoding the animals' choice from neuronal activity revealed that this unexpected effect on behavior could be explained by an overreliance of the perceptual choice circuit on target preferring neurons and a failure to appropriately discount the activity of neurons that prefer the distractor. Consistent with this all-positive computation, we find that animals' task performance is susceptible to subtle perturbations of distractor orientation and optogenetic suppression of neuronal activity in V1. This suggests that to solve this task the circuit has adopted a suboptimal and task-specific computation that discards important task-related information.SIGNIFICANCE STATEMENT A major goal in systems neuroscience is to understand how sensory signals are used to guide behavior. This requires determining what information in sensory cortical areas is used, and how it is combined, by downstream perceptual choice circuits. Here we demonstrate that when performing a go/no-go orientation discrimination task, mice suboptimally integrate signals from orientation tuned visual cortical neurons. While they appropriately positively weight target-preferring neurons, they fail to negatively weight distractor-preferring neurons. We propose that this all-positive computation may be adopted because of its simple learning rules and faster processing, and may be a common approach to perceptual decision-making when task conditions allow.

Dataset Information

Voltage imaging of waking mouse cortex reveals emergence of critical neuronal dynamics.

Publications

Voltage imaging of waking mouse cortex reveals emergence of critical neuronal dynamics.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets