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McCormick, D. A.

Publications and source records attributed to McCormick, D. A..

10 recordsLinked to original sources

Modulation of metastable ensemble dynamics explains optimal coding at moderate arousal in auditory cortex

Past work has reported inverted-U relationships between arousal and auditory task performance, but the underlying neural network mechanisms remain unclear. To make progress, we recorded auditory cortex activity from behaving mice during passive tone presentation and simultaneously monitored pupil-indexed arousal. In these experiments, neural discriminability of tones was maximized at intermediate arousal, revealing a neural correlate of the inverted-U. We explained this arousal-dependent sound processing using a spiking model with clusters. In the model, stimulus discriminability peaked as the network transitioned from a multi-attractor phase exhibiting slow switching between metastable cluster activations (low arousal) to a single-attractor phase with uniform activity (high arousal). This transition also qualitatively captured arousal-induced reductions of neural variability observed in the data. Altogether, this study elucidates computational principles to explain interactions between arousal, neural discriminability, and variability, and suggests that transitions in the dynamical regime of cortical networks could underlie nonlinear modulations of sensory processing.

neuroscience↗

Pan-cortical 2-photon mesoscopic imaging and neurobehavioral alignment in awake, behaving mice

The flow of neural activity across the neocortex during active sensory discrimination is constrained by task-specific cognitive demands, movements, and internal states. During behavior, the brain appears to sample from a broad repertoire of activation motifs. Understanding how these patterns of local and global activity are selected in relation to both spontaneous and task-dependent behavior requires in-depth study of densely sampled activity at single neuron resolution across large regions of cortex. In a significant advance toward this goal, we developed procedures to record mesoscale 2-photon Ca2+ imaging data from two novel in vivo preparations that, between them, allow simultaneous access to nearly all of the mouse dorsal and lateral neocortex. As a proof of principle, we aligned neural activity with both behavioral primitives and high-level motifs to reveal the existence of large populations of neurons that coordinated their activity across cortical areas with spontaneous changes in movement and/or arousal. The methods we detail here facilitate the identification and exploration of widespread, spatially heterogeneous neural ensembles whose activity is related to diverse aspects of behavior.

neuroscience↗

The h-current controls cortical recurrent network activity through modulation of dendrosomatic communication

A fundamental feature of the cerebral cortex is the ability to rapidly turn on and off maintained activity within ensembles of neurons through recurrent excitation balanced by inhibition. Here we demonstrate that reduction of the h-current, which is especially prominent in pyramidal cell dendrites, strongly increases the ability of local cortical networks to generate maintained recurrent activity. Reduction of the h-current resulted in hyperpolarization and increase in input resistance of both the somata and apical dendrites of layer 5 pyramidal cells, while strongly increasing the dendrosomatic transfer of low (<20 Hz) frequencies, causing an increased responsiveness to dynamic clamp-induced recurrent network-like activity injected into the dendrites and substantially increasing the duration of spontaneous Up states. We propose that modulation of the h-current may strongly control the ability of cortical networks to generate recurrent persistent activity and the formation and dissolution of neuronal ensembles.

neuroscience↗

Transitions between discrete performance states in auditory and visual tasks are predicted by arousal and uninstructed movements

During sensory-guided behavior, an animals decision-making dynamics unfold through sequences of distinct performance states, even while stimulus-reward contingencies remain static. Little is known about the factors that underlie these changes in task performance. We hypothesize that these decision-making dynamics can be predicted by externally observable measures, such as uninstructed movements and changes in arousal. Here, combining behavioral experiments in mice with computational modeling, we uncovered lawful relationships between transitions in strategic task performance states and an animals arousal and uninstructed movements. Using hidden Markov models applied to behavioral choices during sensory discrimination tasks, we found that animals fluctuate between minutes-long optimal, sub-optimal and disengaged performance states. Optimal state epochs were predicted by intermediate levels, and reduced variability, of pupil diameter, along with reduced variability in face movements and locomotion. Our results demonstrate that externally observable uninstructed behaviors can predict optimal performance states, and suggest mice regulate their arousal during optimal performance.

neuroscience↗

Cholinergic and noradrenergic axonal activity is both strongly coordinated with behavioral state and heterogeneous across the dorsal cortex

Fluctuations in brain and behavioral state are supported by broadly projecting neuromodulatory systems. In this study, we use mesoscale two-photon calcium imaging to examine spontaneous activity of cholinergic and noradrenergic axons in awake mice in order to determine the interaction between arousal/movement state transitions and neuromodulatory activity across the dorsal cortex at distances separated by up to 4 mm. We confirm that GCaMP6s activity within axonal projections of both basal forebrain cholinergic and locus coeruleus noradrenergic neurons track arousal, indexed as pupil diameter, and changes in behavioral engagement, as reflected by bouts of whisker movement and/or locomotion. The broad coordination in activity between even distant axonal segments indicates that both of these systems can communicate, in part, through a global signal, especially in relation to changes in behavioral state. In addition to this broadly coordinated activity, we also find evidence that a subpopulation of both cholinergic and noradrenergic axons may exhibit heterogeneity in activity that appears to be independent of our measures of behavioral state. By monitoring the activity of cholinergic interneurons in the cortex we found that a subpopulation of these cells also exhibit state-dependent (arousal/movement) activity. These results demonstrate that cholinergic and noradrenergic systems provide a prominent and broadly synchronized signal related to behavioral state, and therefore may contribute to state-dependent cortical activity and excitability.

neuroscience↗

Vagus nerve stimulation recruits the central cholinergic system to enhance perceptual learning

Perception can be refined by experience up to certain limits. It is unclear if perceptual limitations are absolute or could be partially overcome via enhanced neuromodulation and/or plasticity. Recent studies suggest the utility of peripheral nerve stimulation - specifically vagus nerve stimulation (VNS) - for altering neural activity and augmenting experience-dependent plasticity, although little is known about central mechanisms recruited by VNS. Here we developed an auditory discrimination task for mice implanted with a VNS electrode. VNS occurring during behavior gradually improved discrimination abilities beyond the level achieved by training alone. Using two-photon imaging, we identified changes to auditory cortical responses and activation of cortically-projecting cholinergic axons with VNS. Anatomical and optogenetic experiments indicated that VNS could enhance task performance via activation of the central cholinergic system. These results highlight the importance of cholinergic modulation for the efficacy of VNS, perhaps enabling further refinement of VNS methodology for clinical conditions.

neuroscience↗

Visual Thalamocortical Mechanisms of Waking State Dependent Activity and Alpha Oscillations

The brain exhibits distinct patterns of recurrent activity closely related to the behavioral state of the animal. The neural mechanisms that underlie state-dependent activity in the awake animal are incompletely understood. Here, we demonstrate that two types of state-dependent activity - rapid arousal/movement related signals and a 3-5 Hz alpha-like rhythm - in the primary visual cortex (V1) of mice strongly correlate with activity in the visual thalamus. Inactivation of V1 does not interrupt arousal/movement related signals in most visual thalamic neurons, but it abolishes the 3-5 Hz oscillation. Silencing of the visual thalamus similarly eradicates the alpha-like rhythm and perturbs arousal/movement-related activation in V1. Finally, we observed that whisker movement or locomotion is not required for rapid increases in cortical activation. Our results indicate that thalamocortical interactions together with cell-intrinsic properties of thalamocortical cells play a crucial role in shaping state-dependent activity in V1 of the awake animal. HighlightsO_LIWhisker movements correlate with rapid synaptic activation in V1 and visual thalamus C_LIO_LISilencing of V1 does not abolish movement related activation in most dLGN or LP cells C_LIO_LISilencing of visual thalamus strongly reduces movement related activation in V1 C_LIO_LIThalamocortical interactions generate state-dependent alpha frequency oscillation C_LIO_LIVisual thalamic cells exhibit LTS firing during alpha oscillation in the awake mouse C_LI

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Movement and performance predict widespread cortical activity in a visual detection task

Recent studies in mice reveal widespread cortical signals during task performance, however the various task-related and task-independent processes underlying this activity are incompletely understood. Here we recorded wide-field neural activity, as revealed by GCaMP6s, from dorsal cortex while simultaneously monitoring orofacial movements, walking, and arousal (pupil diameter) of head-fixed mice performing a Go/NoGo visual detection task and examined the ability of task performance and spontaneous or task-related movements to predict cortical activity. A linear model was able to explain a significant fraction (33-55% of variance) of widefield dorsal cortical activity, with the largest factors being movements (facial, walk, eye), response choice (hit, miss, false alarm), and arousal, and indicate that a significant fraction of trial-to-trial variability arises from both spontaneous and task-related changes in state (e.g. movements, arousal). Importantly, secondary motor cortex was highly correlated with lick rate, critical for optimal task performance (high d), and was the first region to significantly predict the lick response on target trials. These findings suggest that secondary motor cortex is critically involved in the decision and performance of learned movements and indicate that a significant fraction of trial-to-trial variation in cortical activity results from spontaneous and task-related movements and variations in behavioral/arousal state.

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Phasic arousal optimizes decision computations in mice and humans

Decisions are often made by accumulating ambiguous evidence over time. The brains arousal systems are activated during such decisions. In previous work in humans, we showed that evoked responses of arousal centers during decisions are reported by rapid dilations of the pupil, and predict a suppression of biases in the accumulation of decision-relevant evidence (de Gee et al. 2017). Here, we show that this arousal-related suppression in decision bias acts on both conservative and liberal biases, and generalizes across species (humans / mice), sensory systems (visual / auditory), and domains of decision-making (perceptual / memory-based). In challenging sound-detection tasks, the impact of spontaneous or experimentally induced choice biases was reduced under high arousal. Similar bias suppression occurred when evidence was drawn from memory. All these behavioral effects were explained by reduced evidence accumulation biases. Our results pinpoint a general principle of the interplay between phasic arousal and decision-making.

neuroscience↗

Distinct waking states for strong evoked responses in primary visual cortex and optimal visual detection performance

Variability in cortical neuronal responses to sensory stimuli and in perceptual decision making performance is substantial. Moment-to-moment fluctuations in waking state or arousal can account for much of this variability. Yet, the nature of this variability across the full spectrum of waking states is often not completely characterized, leaving the characteristics of the optimal state for sensory processing unresolved. Using pupillometry in concert with extracellular multiunit and intracellular whole-cell recordings, we found that the magnitude and reliability of visually evoked responses in primary visual cortex (V1) of awake, passively behaving male mice increase as a function of arousal and are largest during sustained locomotion periods. During these high-arousal, sustained locomotion periods, cortical neuronal membrane potential was at its most depolarized and least variable. Contrastingly, behavioral performance of mice on two distinct visual detection tasks was generally best at a range of intermediate arousal levels, but worst during locomotion. These results suggest that large, reliable responses to visual stimuli in V1 occur at a distinct arousal level from that associated with optimal visual detection performance. Our results clarify the relation between neuronal responsiveness and the continuum of waking states, and suggest new complexities in the relation between primary sensory cortical activity and behavior.

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