Biology subjects

Kheirbek, M.

Publications and source records attributed to Kheirbek, M..

3 recordsLinked to original sources

bioRxiv2026

vCA1 SST neurons represent avoidance states that guide anxiety-related behavioral choices

In uncertain, threatening environments, rapid and flexible behavioral decisions are essential for survival. The ventral CA1 region of the hippocampus encodes threatening contexts and can regulate avoidance-related behaviors. While activity patterns in excitatory neurons of vCA1 have been well characterized, the contributions of specific interneuron subtypes to avoidance decisions in threatening situations remain to be fully elucidated. Here, we show that somatostatin expressing (SST) interneurons in vCA1 are selectively recruited during avoidance behavior and play a causal role in shaping behavioral responses in aversive spaces. We find that vCA1 SST interneurons ramp their activity in anticipation of, and during, avoidance. This contrasted with parvalbumin (PV) and vasoactive intestinal peptide (VIP) interneurons, which are preferentially active during exploratory approach behaviors. Unlike other classes of vCA1 interneurons, SST neuron activity more reliably represented the animals intention to avoid rather than its spatial position. Moreover, optogenetic silencing of SST interneurons reduced the efficiency of approach-avoidance decisions. These findings identify vCA1 SST interneurons as key regulators of threat assessment, revealing a cell-type-specific mechanism by which vCA1 microcircuits govern avoidance behaviors. This work provides a new framework for understanding hippocampal control of avoidance behavior and highlights SST-expressing interneurons as key contributors to anxiety-related behaviors.

neuroscience↗

bioRxiv2023

Neural signatures of stress susceptibility and resilience in the amygdala-hippocampal network

The neural dynamics that underlie divergent anhedonic responses to stress remain unclear. Here, we identified neuronal dynamics in an amygdala-hippocampal circuit that distinguish stress resilience and susceptibility. In a reward-choice task, basolateral amygdala (BLA) activity in resilient mice showed enhanced discrimination of upcoming reward choices. In contrast, a rumination-like signature emerged in the BLA of susceptible mice; a linear decoder could classify the intention to switch or stay on a previously chosen reward. Spontaneous activity in the BLA of susceptible mice was higher dimensional than controls, reflecting the exploration of a larger number of distinct neural states. Manipulation of vCA1-BLA inputs rescued dysfunctional neural dynamics and anhedonia in susceptible mice, suggesting that targeting this pathway can enhance BLA circuit function and ameliorate of depression-related behaviors. One-Sentence SummaryIdentification and rescue of dysfunctional vCA1-BLA population dynamics and behavior in stress-susceptible mice.

neuroscience↗

bioRxiv2018

A distributed neural code in ensembles of dentate gyrus granule cells

The tuning properties of neurons in a given brain region have been traditionally viewed as the under-pinnings of computation in neural circuits. However, at the higher levels of processing, specialization is often elusive, instead a mix of sensory, cognitive and behavioural quantities drive neural activity. In such networks, ensembles of neurons, rather than single units with easily interpretable tuning properties, encode behaviourally relevant variables. Here we show that this is the case also in the dentate gyrus and CA1 subregions of the hippocampus. Using calcium imaging in freely moving mice, we decoded the instantaneous position, direction of motion and speed from the activity of hundreds of cells in the hippocampus of mice freely exploring an arena. For the vast majority of neurons in both regions, their response properties were not predictive of their importance for encoding position. Furthermore, we could decode position from populations of cells that were important for decoding direction of motion and vice versa, showing that these quantities are encoded by largely overlapping ensembles as in distributed neural code. Finally, we found that correlated activities had an impact on decoding performance in CA1 but not in dentate gyrus, suggesting different enconding strategies for these areas. Our analysis indicates that classical methods of analysis based on single cell response properties might be insufficient to accurately characterize the neural computation in a given area. In contrast, population analysis may help highlight previously overlooked properties of hippocampal circuits.

neuroscience↗