Biology subjects

Voelcker, B.

Publications and source records attributed to Voelcker, B..

4 recordsLinked to original sources

bioRxiv2023

Representational drift in barrel cortex is receptive field dependent

Cortical populations often exhibit changes in activity even when behavior is stable. How behavioral stability is maintained in the face of such representational drift remains unclear. One possibility is that some neurons are stable despite broader instability. We examine whisker touch responses in superficial layers of primary vibrissal somatosensory cortex (vS1) over several weeks in mice stably performing an object detection task with two whiskers. While the number of touch neurons remained constant, individual neurons changed with time. Touch-responsive neurons with broad receptive fields were more stable than narrowly tuned neurons. Transitions between functional types were non-random: before becoming broadly tuned neurons, unresponsive neurons first pass through a period of narrower tuning. Broadly tuned neurons with higher pairwise correlations to other touch neurons were more stable than neurons with lower correlations. Thus, a small population of broadly tuned and synchronously active touch neurons exhibit elevated stability and may be particularly important for downstream readout.

neuroscience↗

bioRxiv2021

Transformation of Primary Sensory Cortical Representations from Layer 4 to Layer 2

Sensory input arrives from thalamus in cortical layer (L) 4, from which it flows predominantly to superficial layers, so that L4 to L2 constitutes one of the earliest cortical feedforward networks. Despite extensive study, the transformation performed by this network remains poorly understood. We use two-photon calcium imaging in L2-4 of primary vibrissal somatosensory cortex (vS1) to record neural activity as mice perform an object localization task with two whiskers. We find that touch responses sparsen but become more reliable from L4 to L2, with superficial neurons responding to a broader range of touches. Decoding of sensory features either improves from L4 to L2 or remains unchanged. Pairwise correlations increase superficially, with L2/3 containing ensembles of mostly broadly tuned neurons responding robustly to touch. Thus, from L4 to L2, cortex transitions from a dense probabilistic code to a sparse and robust ensemble-based code that improves stimulus decoding, facilitating perception.

neuroscience↗

bioRxiv2020

Two dynamically distinct circuits driving inhibition in sensory thalamus

Most sensory information destined for the neocortex is relayed through the thalamus, where considerable transformation occurs1,2. One powerful means of transformation involves interactions between excitatory thalamocortical neurons that carry data to cortex and inhibitory neurons of the thalamic reticular nucleus (TRN) that regulate flow of those data3-6. Despite enduring recognition of its importance7-9, understanding of TRN cell types, their organization, and their functional properties has lagged that of the thalamocortical systems they control. Here we address this, investigating somatosensory and visual circuits of the TRN. In the somatosensory TRN we observed two groups of genetically defined neurons that are topographically segregated, physiologically distinct, and connect reciprocally with independent thalamocortical nuclei via dynamically divergent synapses. Calbindin-expressing cells, located in the central core, connect with the ventral posterior nucleus (VP), the primary somatosensory thalamocortical relay. In contrast, somatostatin-expressing cells, residing along the surrounding edges of TRN, synapse with the posterior medial thalamic nucleus (POM), a higher-order structure that carries both top-down and bottom-up information10-12. The two TRN cell groups process their inputs in pathway-specific ways. Synapses from VP to central TRN cells transmit rapid excitatory currents that depress deeply during repetitive activity, driving phasic spike output. Synapses from POM to edge TRN cells evoke slower, less depressing excitatory currents that drive more persistent spiking. Differences in intrinsic physiology of TRN cell types, including state-dependent bursting, contribute to these output dynamics. Thus, processing specializations of two somatosensory TRN subcircuits appear to be tuned to the signals they carry--a primary central subcircuit to discrete sensory events, and a higher-order edge subcircuit to temporally distributed signals integrated from multiple sources. The structure and function of visual TRN subcircuits closely resemble those of the somatosensory TRN. These results provide fundamental insights about how subnetworks of TRN neurons may differentially process distinct classes of thalamic information.

neuroscience↗

bioRxiv2019

Recurrent interactions in local cortical circuits

The majority of cortical synapses are local and excitatory. Local recurrent circuits could implement amplification, allowing for pattern completion and other computations1. Cortical circuits contain subnetworks, consisting of neurons with similar receptive fields and elevated connectivity relative to the network average2,3. Understanding the computations performed by these subnetworks during behavior has been hampered by the fact that cortical neurons encoding different types of information are spatially intermingled and distributed over large brain volumes 4,5. We used computational modeling, optical recordings and manipulations to probe the function of recurrent coupling in layer (L) 2/3 of the somatosensory cortex during tactile discrimination. A model of L2/3 dynamics revealed that recurrent excitation enhances sensory signals via amplification, but only for subnetwork with elevated connectivity. Networks with high amplification were sensitive to damage: loss of a few subnetwork members degraded stimulus encoding. We tested this prediction experimentally by mapping neuronal selectivity5 and photoablating6,7 neurons with specific selectivity. In L2/3 of the somatosensory cortex, ablating a small proportion (10-20, < 5 % of the total) of neurons representing touch dramatically reduced responses in the spared touch representation, but not other representations. Network models further predicted that degradation following ablation should be greatest among spared neurons with stimulus responses that were most similar to the ablated population. Consistent with this prediction, ablations most strongly impacted neurons with selectivity similar to the ablated population. Our data shows that recurrence among cortical neurons with similar selectivity can drive input-specific amplification during behavior.

neuroscience↗