Biased inter-columnar communication and short-term plasticity in mouse barrel cortex

Abstract The barrel cortex (BC) processes complex direction-, frequency-, and phase-dependent input from whiskers to analyze objects in the immediate environment. Little is known about how BC microcircuits process this information and integrate input from multiple whiskers. To investigate these circuits we targeted a hybrid voltage sensor (hVOS) to Scnn1a excitatory neurons in cortical layer 4 (L4), and imaged population responses to electrical stimulation. BC in coronal and sagittal slices presented the laminar structure of the cortex with barrels aligned along stereotyped whisking directions. Voltage imaging tracked activity along an L4→L2/3→L4 relay during inter-barrel communication. AMPA receptor blockade demonstrated that this relay depends on excitatory synaptic transmission, and revealed intra- and inter-barrel feedforward inhibition. Communication between barrels was isotropic in response amplitude, half-width, and conduction velocity, but latency was longer for communication to caudal barrels. Furthermore, paired-pulse depression was weakest and recovery slowest for protraction-related directions, especially to caudally adjacent barrels. Such biases will preferentially enhance repetitive inputs in this direction. These results identify direction-dependent synaptic circuitry that shapes inter-barrel communication. Anisotropy in short-term plasticity aligns with whisker motion kinematics, suggesting that BC microcircuits are tuned to preserve temporal fidelity and selectively filter inputs according to whisking phase and direction.

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Publication Details

Journal
eNeuro
Published
2026-08-28
DOI
https://doi.org/10.1523/eneuro.0109-26.2026
Primary Topic
Neural dynamics and brain function
Type
article
Field-Weighted Citation Impact
0.00

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article

Biased inter-columnar communication and short-term plasticity in mouse barrel cortex

Meyer B. Jackson, John M Judge
eNeuro
Neural dynamics and brain function
article

Biased inter-columnar communication and short-term plasticity in mouse barrel cortex

Meyer B. Jackson, John M Judge
article en

Abstract

Abstract The barrel cortex (BC) processes complex direction-, frequency-, and phase-dependent input from whiskers to analyze objects in the immediate environment. Little is known about how BC microcircuits process this information and integrate input from multiple whiskers. To investigate these circuits we targeted a hybrid voltage sensor (hVOS) to Scnn1a excitatory neurons in cortical layer 4 (L4), and imaged population responses to electrical stimulation. BC in coronal and sagittal slices presented the laminar structure of the cortex with barrels aligned along stereotyped whisking directions. Voltage imaging tracked activity along an L4→L2/3→L4 relay during inter-barrel communication. AMPA receptor blockade demonstrated that this relay depends on excitatory synaptic transmission, and revealed intra- and inter-barrel feedforward inhibition. Communication between barrels was isotropic in response amplitude, half-width, and conduction velocity, but latency was longer for communication to caudal barrels. Furthermore, paired-pulse depression was weakest and recovery slowest for protraction-related directions, especially to caudally adjacent barrels. Such biases will preferentially enhance repetitive inputs in this direction. These results identify direction-dependent synaptic circuitry that shapes inter-barrel communication. Anisotropy in short-term plasticity aligns with whisker motion kinematics, suggesting that BC microcircuits are tuned to preserve temporal fidelity and selectively filter inputs according to whisking phase and direction.

eNeuro
University of Wisconsin System (US), University of Wisconsin–Madison (US), Wisconsin Institutes for Discovery (US)
National Institute of Neurological Disorders and Stroke
Openalex Percentile: Top 99%
Neural dynamics and brain function
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Biased inter-columnar communication and short-term plasticity in mouse barrel cortex — Meyer B. Jackson, John M Judge · eNeuro (2026) | TGRS Research Map | TGRS