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Zhu, H. W.

Publications and source records attributed to Zhu, H. W..

3 recordsLinked to original sources

Cell-type-specific cortical feedback coordinates hierarchical credit assignment

Learning is thought to arise from synaptic modifications across brain-wide circuits, yet how these networks coordinate plasticity to support complex behaviour is not known. Inspired by deep learning, we introduce a theory of hierarchical credit assignment in which pathway-specific cortical feedback drives dendrite-dependent burst plasticity across the cortex. We show that this principle enables learning in dynamic settings, complex visual recognition, and goal-directed tasks, mechanistically linking credit assignment to cell-type-specific regulation of dendritic excitation-inhibition balance. Our framework provides a unified account of diverse experimental phenomena -- including cell-type-specific modulation of synaptic plasticity, learning-dependent changes in interneurons, and neuron-specific dendritic error signals. Furthermore, the theory predicts that interneurons constrain the dimensionality of error feedback, offering a functional rationale for cortex-wide gradients in interneuron density. Together, these findings reveal how distinct cortical cell types cooperatively coordinate learning, bridging the gap between synaptic plasticity, circuit-level computation, and behaviour.

neuroscience↗

Active locomotion predictively rescues head direction attractor dynamics in head-fixed mice

Head direction (HD) cells in the anterodorsal thalamic nuclei form the brains internal compass, and are often modeled as a ring attractor maintaining azimuth coding by leveraging continuous visual and inertial sensory input. Here, we test how the common experimental preparation of head-fixed animals alters this code. Complete head-fixation that creates vestibular conflict disrupts both unit and population encoding of head direction, while selectively constraining head-on-body movements either in real or virtual reality uniquely impairs HD population activity. More specifically, attractor dynamics is altered in head-restrained mice during periods of immobility, but remarkably recover several hundred milliseconds prior to locomotion onset. The rescue preceding movement onset suggests that an efference copy or prediction of a re-afferent signal is necessary to maintain HD network activity during head restraint. A computational model recapitulates these effects by perturbing lateral connectivity among HD neurons. More generally, the results indicate that the HD network is a context- and state-dependent predictive estimator, stabilized by forthcoming self-motion signals. The classic ring-attractor models should be revised to integrate context-dependent dynamics with prospective motor signals, offering a more complete account of how the brains compass remains stable across both naturalistic and constrained conditions.

neuroscience↗

Hippocampal OLM interneurons regulate CA1 place cell plasticity and remapping

OLM interneurons selectively target inhibition to the distal dendrites of CA1 pyramidal cells in the hippocampus but the role of this unique morphology in controlling place cell physiology remains a mystery. Here we show that OLM activity prevents associative synaptic plasticity at Schaffer collateral synapses on CA1 pyramidal cells by inhibiting dendritic Ca2+ signalling initiated by entorhinal synaptic inputs. Furthermore, we find that OLM activity is reduced in novel environments suggesting that reducing OLM activity and thereby enhancing excitatory synaptic plasticity is important for the formation of new place cell representations. Supporting this, we show that selectively increasing OLM activity in novel environments enhances place cell stability and reduces remapping of newly formed place cells whilst increasing OLM activity in familiar environments led only to a transient silencing of place cells. Our results therefore demonstrate a critical role for distal dendrite targeting interneurons in regulating plasticity of neuronal representations.

neuroscience↗