Biology subjects

Mankili, A.

Publications and source records attributed to Mankili, A..

4 recordsLinked to original sources

bioRxiv2026

Decoding instrumental lever pressing from prefrontal, accumbens, and hippocampal local field potentials: conservation across sex, task, and dopamine depletion

During operant behavior, oscillatory activity is coordinated across multiple brain regions and can change under different task conditions. In this study, we use a decoding approach to characterize these patterns and predict lever pressing behavior in rats from local field potentials (LFP) recorded bilaterally in the hippocampus, nucleus accumbens, and prefrontal cortex. We extract LFP features for band power and peak frequency and predict behavior across animals and conditions with a Poisson Generalized Linear Model (GLM). We use data from both male and female rats performing either fixed-ratio (FR40) or progressive (PROG) operant lever-pressing tasks, under vehicle (VEH) or tetrabenazine (TBZ), a vesicular monoamine transport (VMAT-2) inhibitor that depletes dopamine and induces depressive-like motivation dysfunction. We find that we can accurately predict lever pressing from multi-region LFP within-animals on a timescale of seconds with >30% variance explained. Although within-animal and within-condition predictions are highest, we also find, interestingly, that these decoders generalize across animals and across drug, sex, and task conditions, suggesting a stable association between LFP and behavior. We then evaluate whether LFP features can be used to decode long-term task variables, such as the number of presses since or until the next reinforcer. We find that LFP features can predict these long-term task variables, but that decoding relies on different LFP features for prediction than those used for immediate lever pressing. Altogether these results suggest that there are robust distributed patterns of LFP associated with lever-pressing behavior under multiple drug, task, and sex conditions.

neuroscience↗

bioRxiv2026

Tracking long-term natural changes in hippocampal excitatory to inhibitory synapses from spikes

Although long-term synaptic plasticity is often studied using controlled electrical or optogenetic stimulation, it also occurs spontaneously during natural, ongoing brain activity. Here, using large-scale spike recordings in mice from the Allen Institute Visual Coding Neuropixels dataset, we examine to what extent fluctuations in putative synaptic efficacy can be tracked and explained by models of activity-dependent long-term plasticity. We first detect putative excitatory synaptic connections within the hippocampus based on cross-correlations between the spike trains of thousands of pairs of neurons. Most of these putative connections are between presynaptic neurons with broad spike waveforms and postsynaptic neurons with narrow spike waveforms and are consistent with synapses from excitatory to inhibitory units. For the subset of pairs where a transient, excitatory effect was detected, we use a model-based approach to track fluctuations in synaptic efficacy. Previous work found that these fluctuations can be partially predicted from pre- and postsynaptic firing rates and models of short-term plasticity. Here we model naturally occurring long-term potentiation and depression using rate-based learning rules. We find that modeling the covariance of pre- and postsynaptic activity improves prediction of efficacy fluctuations. We also examine synaptic changes associated with hippocampal sharp-wave ripples, but do not find clear evidence of systematic SWR-associated changes for the putative synapses studied here.

neuroscience↗

bioRxiv2025

Disruption of theta-timescale spiking impairs learning but spares hippocampal replay

The ability to rapidly learn and retrieve salient information about new environments is critical for survival. In mammals, the hippocampus plays a crucial role in that learning. Specialized features of hippocampal population coding, including network-level theta oscillatory activity, location-specific firing of principal cells, and reactivation of experience during immobility (replay), have been implicated in rapid storage and retrieval of spatial information. Disruptions of theta and replay jointly, or replay alone, are sufficient to impair learning; however, the specific contribution of theta-associated temporal structure during locomotion remains unknown. In this study, we manipulated hippocampal spiking activity in rats specifically during locomotion by optogenetically activating septal parvalbumin-expressing GABAergic neurons. We developed a closed-loop, theta phase-specific stimulation protocol that reliably reduced theta power shortly after stimulation onset. This manipulation preserved the place codes of individual cells but disrupted the fine temporal structure of endogenous spatio-temporal representations (i.e., theta sequences) at the pairwise and population level. Theta disruption during locomotion was also sufficient to cause pronounced deficits in learning the more cognitively challenging component of a spatial alternation task, even though disruption was applied on only [~]66% of trials. Notably, network effects accompanying theta disruption were restricted to locomotor periods; we did not observe changes in replay rate, length, or content during immobility. Together, these results demonstrate the importance of the precise temporal microstructure of locomotion-associated spatial representations in the hippocampus for learning.

neuroscience↗

bioRxiv2022

Dynamic Synchronization between Hippocampal Spatial Representations and the Stepping Rhythm

Summary paragraphThe hippocampus is a vertebrate brain structure that expresses spatial representations1 and is critical for navigation2,3. Navigation in turn intricately depends on locomotion; however, current accounts suggest a dissociation between hippocampal spatial representations and the details of locomotor processes. Specifically, the hippocampus is thought to primarily represent higher-order cognitive and locomotor variables like position, speed, and direction of movement4-7, while the limb movements that propel the animal are thought to be computed and represented primarily in subcortical circuits, including the spinal cord, brainstem, and cerebellum8-11. Whether hippocampal representations are actually decoupled from the detailed structure of locomotor processes remains unknown. To address this question, we simultaneously monitored hippocampal spatial representations and ongoing limb movements underlying locomotion at fast timescales. We found that the forelimb stepping cycle in freely behaving rats is rhythmic and peaks at ~8 Hz during movement, matching the ~8 Hz organization of information processing in the hippocampus during locomotion12. We also discovered precisely timed coordination between the time at which the forelimbs touch the ground ( plant times of the stepping cycle) and the hippocampal representation of space. Notably, plant times coincide with hippocampal representations closest to the actual position of the animal, while in-between these plant times, the hippocampal representation progresses towards possible future locations. This synchronization was specifically detectable when animals approached upcoming spatial decisions. Taken together, our results reveal profound and dynamic coordination on a timescale of tens of milliseconds between central cognitive representations and peripheral motor processes. This coordination engages and disengages rapidly in association with cognitive demands and is well suited to support rapid information exchange between cognitive and sensory-motor circuits.

neuroscience↗