Context-Dependent Sensory Processing across Primary and Secondary Somatosensory Cortex

Condylis, Cameron; Lowet, Eric; Ni, Jianguang; Bistrong, Karina; Ouellette, Timothy; Josephs, Nathaniel; Chen, Jerry L.

doi:10.1016/j.neuron.2020.02.004

Cited by 59 publications

(61 citation statements)

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“…Inhibitory neurons had an earlier onset of spiking with a peak latency of 8.2±0.6 ms (mean±std) in L4 (Figure 2C), which corresponds to <3 ms conduction delay, calculated from the population peristimulus time histograms (Figure 2C). These delays are similar to previous observations in vivo (Condylis et al, 2020; Dudai et al, 2020; Sermet et al, 2019; Swadlow, 2003, 1995). In terms of the latency to an action potential, neurons across the entire depth of L4 were homogenous with the exception that those closer to the L3 border showed a delayed spiking (Figure 2D).…”

Section: Resultssupporting

confidence: 91%

Cortical representation of touchin silico

Huang

Zeldenrust

Celikel

2020

Preprint

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With its six layers and ~12000 neurons, a cortical column is a complex network whose function is plausibly greater than the sum of its constituents'. Functional characterization of its network components will require going beyond the brute-force modulation of the neural activity of a small group of neurons. Here we introduce an open-source, biologically inspired, computationally efficient network model of the somatosensory cortex's granular and supragranular layers after reconstructing the barrel cortex in soma resolution. Comparisons of the network activity to empirical observations showed that the in silico network replicates the known properties of touch representations and whisker deprivation-induced changes in synaptic strength induced in vivo. Simulations show that the history of the membrane potential acts as a spatial filter that determines the presynaptic population of neurons contributing to a post-synaptic action potential; this spatial filtering might be critical for synaptic integration of top-down and bottom-up information.

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Section: Resultssupporting

confidence: 91%

Cortical representation of touchin silico

Huang

Zeldenrust

Celikel

2020

Preprint

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“…Animals were trained on a head-fixed, whisker-based delayed non-match to sample using equipment and training protocol previously described 26 . Whiskers were trimmed to a single row corresponding to the selected imaging region for high-speed videography.…”

Section: Methodsmentioning

confidence: 99%

“…High-speed videography of whisker movement was acquired at 500 Hz as previously described 26,54 . For analysis, whiskers were automatically traced 54 .…”

Section: Methodsmentioning

confidence: 99%

“…To identify functional differences between transcriptomically-defined cell populations in L2/3 of S1, we performed two-photon calcium imaging on expert wild type mice ( n = 7) performing a head-fixed whisker-based delayed non-match to sample (DNMS) task 26 ( Supplementary Fig. 6 ).…”

Section: Introductionmentioning

confidence: 99%

“…We previously reported diverse task-related responses in L2/3 of S1 during the DNMS task 26 . To characterize task-related responses for each recorded cell in a more comprehensive manner, we fit a generalized linear model (GLM) to each neuron’s estimated spiking activity against a range of ‘task variables’ 27 ( Fig.…”

Section: Introductionmentioning

confidence: 99%

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Dense Functional and Molecular Readout of a Circuit Hub in Sensory Cortex

Condylis

Ghanbari

et al. 2021

Preprint

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Information processing in the neocortex is carried out by neuronal circuits composed of different cell types. Recent census of the neocortex using single cell transcriptomic profiling has uncovered more than 100 putative cell types which subdivide major classes of excitatory and inhibitory neurons into distinct subclasses. The extent to which this molecular classification predicts distinct functional roles during behavior is unclear. Here, we combined population recordings using two-photon calcium imaging with spatial transcriptomics using multiplexed fluorescent in situ hybridization to achieve dense functional and molecular readout of cortical circuits during behavior. We characterized task-related responses across major transcriptomic neuronal subclasses and types in layer 2/3 of primary somatosensory cortex as mice performed a tactile working memory task. We find that as neurons are segregated into increasingly discrete molecular types, their task-related properties continue to differentiate. We identify an excitatory cell type, Baz1a, that is highly driven by tactile stimuli. Baz1a neurons homeostatically maintain stimulus responsiveness during altered sensory experience and show persistent enrichment of subsets of immediately early genes including Fos. Measurements of functional and anatomical connectivity reveal that upper layer 2/3 Baz1a neurons preferentially innervate somatostatin-expressing inhibitory neurons. We propose that this connection motif reflects a sensory-driven circuit hub that orchestrates local sensory processing in superficial layers of the neocortex.

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Cortical Representation of Touch in Silico

2022

View full text Add to dashboard Cite

With its six layers and ~ 12,000 neurons, a cortical column is a complex network whose function is plausibly greater than the sum of its constituents’. Functional characterization of its network components will require going beyond the brute-force modulation of the neural activity of a small group of neurons. Here we introduce an open-source, biologically inspired, computationally efficient network model of the somatosensory cortex’s granular and supragranular layers after reconstructing the barrel cortex in soma resolution. Comparisons of the network activity to empirical observations showed that the in silico network replicates the known properties of touch representations and whisker deprivation-induced changes in synaptic strength induced in vivo. Simulations show that the history of the membrane potential acts as a spatial filter that determines the presynaptic population of neurons contributing to a post-synaptic action potential; this spatial filtering might be critical for synaptic integration of top-down and bottom-up information.

show abstract

Context-Dependent Sensory Processing across Primary and Secondary Somatosensory Cortex

Cited by 59 publications

References 50 publications

Cortical representation of touchin silico

Cortical representation of touchin silico

Dense Functional and Molecular Readout of a Circuit Hub in Sensory Cortex

Cortical Representation of Touch in Silico

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