State-aware detection of sensory stimuli in the cortex of the awake mouse

Sederberg, Audrey; Pala, Aurélie; Zheng, Hangping; He, Biyu J.; Stanley, Garrett B.

doi:10.1371/journal.pcbi.1006716

Cited by 28 publications

(35 citation statements)

References 69 publications

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“…Desynchronized states are characterized by lower noise correlations, and it has been hypothesized that the resulting improvement in representation of sensory stimuli underlies improved performance in sensory discrimination tasks [ 14 , 15 , 20 ]. However, we did not find a strong correlation between desynchronization and increased behavioral accuracy, or with better decoding of stimuli from cortical activity, which this hypothesis would predict for our task.…”

Section: Discussionmentioning

confidence: 99%

“…Recordings in primates showed that low-frequency “noise correlations” (signatures of a more synchronized state) decrease with spatially selective attention, specifically in the region of visual cortex representing an attended part of the visual field [ 14 , 15 , 16 ]. Theoretical arguments suggest that correlated low-frequency fluctuations can impair information coding [ 17 , 18 , 19 , 20 ], and recordings in rodents suggest that cortical sensory representations are more reliable in desynchronized states [ 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 ]. This indicates that cortex might desynchronize in a localized manner, with the resulting decreased noise correlations improving representation of attended sensory stimuli.…”

Section: Introductionmentioning

confidence: 99%

“…A second, non-exclusive, hypothesis is that desynchronization is a consequence of a global change in brain state that covaries with performance on sensory tasks but need not causally contribute to it. Indeed, correlated fluctuations only impair sensory coding when their structure mimics that of sensory stimuli [ 17 , 18 , 19 , 20 ]. At least in mouse visual cortex, this is not the case: spontaneous fluctuations occur along dimensions largely orthogonal to visual responses [ 30 , 31 ].…”

Section: Introductionmentioning

confidence: 99%

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Cortical State Fluctuations during Sensory Decision Making

et al. 2020

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Cortical State Fluctuations during Sensory Decision Making

et al. 2020

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“…To estimate the depth of L4 in S1 and S2 recordings we considered the LFP, CSD and multi-unit (MUA) responses evoked by contralateral whisker stimuli (Sederberg et al 2019). The average LFP response was obtained by down-sampling to 3 kHz and low-pass filtering the raw signal (forward and reverse, 200 Hz cutoff frequency).…”

Section: Methodsmentioning

confidence: 99%

Ipsilateral stimulus encoding in primary and secondary somatosensory cortex of awake mice

Pala

Stanley

2021

Preprint

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Lateralization is a hallmark of somatosensory processing in the mammalian brain. However, in addition to their contralateral representation, unilateral tactile stimuli also modulate neuronal activity in somatosensory cortices of the ipsilateral hemisphere. The cellular organization and functional role of these ipsilateral stimulus responses in awake somatosensory cortices, especially regarding stimulus coding, are unknown. Here, we targeted silicon probe recordings to the vibrissa region of primary (S1) and secondary (S2) somatosensory cortex of awake head-fixed male and female mice while delivering ipsilateral and contralateral whisker stimuli. Ipsilateral stimuli drove larger and more reliable responses in S2 than in S1, and activated a larger fraction of stimulus-responsive neurons. Ipsilateral stimulus-responsive neurons were rare in layer 4 of S1, but were located in equal proportion across all layers in S2. Linear classifier analyses further revealed that decoding of the ipsilateral stimulus was more accurate in S2 than S1, while S1 decoded contralateral stimuli most accurately. These results reveal substantial encoding of ipsilateral stimuli in S1 and especially S2, consistent with the hypothesis that higher cortical areas may integrate tactile inputs across larger portions of space, spanning both sides of the body.

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“…We used a precise, computer-controlled galvanometer (Cambridge Technologies) with attached tube to stimulate individual whiskers (Liew et al, 2020;Sederberg et al, 2019;Waiblinger et al, 2018;. The galvanometer was controlled using either a custom Matlab GUI and Simulink Real-Time (Mathworks), or the Real-time eXperiment Interface application (http://rtxi.org/), sampling at 1 kHz.…”

Section: Whisker Stimulationmentioning

confidence: 99%

Rapid Cortical Adaptation and the Role of Thalamic Synchrony During Wakefulness

Borden

Liew

et al. 2020

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Rapid sensory adaptation is observed across all sensory systems, and strongly shapes sensory percepts in complex sensory environments. Yet despite its ubiquity and likely necessity for survival, the mechanistic basis is poorly understood. A wide range of studies primarily in in-vitro and anesthetized preparations have pointed to the emergence of adaptation effects at the level of primary sensory cortex, with only modest signatures in earlier stages of processing. The nature of rapid adaptation and how it shapes sensory representations during wakefulness, and thus the potential role in adaptive changes in perception, is unknown, as are the mechanisms that underlie this phenomenon. To address these unknowns, we recorded spiking activity in primary somatosensory cortex (S1) and the upstream ventral posteromedial (VPm) thalamic nucleus in the vibrissa pathway of the awake mouse, and quantified responses to whisker stimuli delivered in isolation and embedded in an adapting sensory background. We found that during wakefulness, cortical sensory responses were indeed adapted by persistent sensory stimulation; putative excitatory neurons were profoundly adapted, and inhibitory neurons only modestly so. Further optogenetic manipulation experiments and network modeling suggest this largely reflects adaptive changes in synchronous thalamic firing combined with robust engagement of feedforward inhibition, with little contribution from synaptic depression. Taken together, these results suggest that cortical adaptation largely reflects changes in timing of thalamic input, and the way in which this differentially impacts cortical excitation and feedforward inhibition, pointing to a prominent role of thalamic gating in rapid adaptation of primary sensory cortex.Significance StatementRapid adaptation of sensory activity strongly shapes representations of sensory inputs across all sensory pathways over the timescale of seconds, and has profound effects on sensory perception. Despite its ubiquity and theoretical role in the efficient encoding of complex sensory environments, the mechanistic basis is poorly understood, particularly during wakefulness. In this study in the vibrissa pathway of awake mice, we show that cortical representations of sensory inputs are strongly shaped by rapid adaptation, and that this is mediated primarily by adaptive gating of the thalamic inputs to primary sensory cortex and the differential way in which these inputs engage cortical sub-populations of neurons.

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State-aware detection of sensory stimuli in the cortex of the awake mouse

Cited by 28 publications

References 69 publications

Cortical State Fluctuations during Sensory Decision Making

Cortical State Fluctuations during Sensory Decision Making

Ipsilateral stimulus encoding in primary and secondary somatosensory cortex of awake mice

Rapid Cortical Adaptation and the Role of Thalamic Synchrony During Wakefulness

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