Arend, L. A. | bioRxiv Science

bioRxiv2026

Temporal Coding rather than Circuit Wiring allows Hippocampal CA3 Neurons to Dynamically Distinguish Different Cortical Inputs

Memory relies on associating and indexing multimodal information. How does this occur within single neurons? The hippocampus integrates multisensory information from medial (MEC) and lateral (LEC) entorhinal cortices to form environmental representations1-6, yet their synaptic dynamics, circuit organization, and integrative functions remain elusive. Contrary to canonical models emphasizing anatomical and functional segregation, our dual-color optogenetic7 circuit mapping revealed that both MEC and LEC inputs converge on virtually every CA3 pyramidal neuron and exhibit similar input-output functions and modulation via GABAergic microcircuitry. Divergence occurs in their frequency-dependent short-term plasticity. With increasing frequencies, facilitating LEC-evoked responses undergo synaptic depression, whereas MEC-evoked responses continue facilitating. In vivo, MEC-originating dentate spikes fire CA3 more than LEC, likely due to their distinct temporal relationship with oscillatory activity. Our findings support that hippocampal area CA3 processes region-specific information from MEC and LEC via temporal coding, rather than hard-wired circuit organization, at both single-neuron and network levels.

neuroscience↗

bioRxiv2018

Closed-Loop Control of Active Sensing Movements Regulates Sensory Slip.

Active sensing involves the production of motor signals for the purpose of acquiring sensory information [1-3]. The most common form of active sensing, found across animal taxa and behaviors, involves the generation of movements--e.g. whisking [4-6], touching [7,8], sniffing [9,10], and eye movements [11]. Active-sensing movements profoundly affect the information carried by sensory feedback pathways [12-15] and are modulated by both top-down goals (e.g. measuring weight vs. texture [1,16]) and bottom-up stimuli (e.g. lights on/off [12]) but it remains unclear if and how these movements are controlled in relation to the ongoing feedback they generate. To investigate the control of movements for active sensing, we created an experimental apparatus for freely swimming weakly electric fish, Eigenmannia virescens, that modulates the gain of reafferent feedback by adjusting the position of a refuge based on real time videographic measurements of fish position. We discovered that fish robustly regulate sensory slip via closed-loop control of active-sensing movements. Specifically, as fish performed the task of maintaining position inside the refuge [17-22], they dramatically up- or down-regulated fore-aft active-sensing movements in relation to a 4-fold change of experimentally modulated reafferent gain. These changes in swimming movements served to maintain a constant magnitude of sensory slip. The magnitude of sensory slip depended on the presence or absence of visual cues. These results indicate that fish use two controllers: one that controls the acquisition of information by regulating feedback from active sensing movements, and another that maintains position in the refuge, a control structure that may be ubiquitous in animals [23,24].

animal behavior and cognition↗