Biology subjects

Sych, Y.

Publications and source records attributed to Sych, Y..

5 recordsLinked to original sources

bioRxiv2026

Claustral pathway coordinates distributed cortical dynamics with hippocampal output during sleep to promote memory consolidation

The claustrum is a broadly connected subcortical structure proposed to coordinate distributed cortical activity. Claustral neurons are recruited during synchronized brain states and contribute to sleep-dependent memory consolidation, primarily through effects on cortical dynamics. Yet the claustrum also innervates the subicular complex, a major hippocampal output node, raising the possibility that it may regulate both cortical state and hippocampo-cortical dialogue during sleep. Here, we identify a projection-defined population of claustral neurons targeting the subicular complex, CLAsc, that is preferentially recruited during slow-wave sleep and tracks cortical and subicular sleep dynamics. Optogenetic activation of CLAsc neurons during post-learning sleep enhanced spatial memory consolidation without detectable changes in ripple occurrence or slow-oscillation-spindle coupling. Instead, CLAsc activation imposed a stereotyped cortical-subicular motif: a brief gamma-rich Up state followed by a coordinated Down state across prefrontal, retrosplenial and subicular regions. Within this gamma-rich Up state, interareal coherence increased, gamma bursts became synchronized, and lagged directed interactions were transiently reorganized, including an enhanced prefrontal-to-subicular component. Together, these findings identify the claustrum as a state-dependent coordinator that transforms ongoing cortical and hippocampal-output activity into coordinated network transitions during sleep, providing a circuit mechanism through which distributed brain states may support memory consolidation.

neuroscience↗

bioRxiv2023

Distinct hypothalamus-habenula circuits govern risk preference

Appropriate risk evaluation is essential for survival in complex, uncertain environments. Confronted with choosing between certain (safe) and uncertain (risky) options, animals show strong preference for either option consistently across extended time periods. How such risk preference is encoded in the brain remains elusive. A candidate region is the lateral habenula (LHb), which is prominently involved in value-guided behavior. Here, using a balanced two-alternative choice task and longitudinal two-photon calcium imaging, we identify LHb neurons with risk-preference-selective activity reflecting individual risk preference prior to action selection. By employing whole-brain anatomical tracing, multi-fiber photometry, and projection- and cell-type-specific optogenetics, we find that glutamatergic LHb projections from the medial (MH) but not lateral (LH) hypothalamus provide behavior-relevant synaptic input before action selection. Optogenetic stimulation of MH{lozenge}LHb axons evoked excitatory and inhibitory postsynaptic responses, whereas LH{lozenge}LHb projections were excitatory. We thus reveal functionally distinct hypothalamus-habenula circuits for risk preference in habitual economic decision-making.

neuroscience↗

bioRxiv2022

Conservative Significance Testing of Tripartite Interactions in Multivariate Neural Data

An important goal in systems neuroscience is to understand the structure of neuronal interactions, frequently approached by studying functional relations between recorded neuronal signals. Commonly used pairwise metrics (e.g. correlation coefficient) offer limited insight, neither addressing the specificity of estimated neuronal interactions nor potential synergistic coupling between neuronal signals. Tripartite metrics, such as partial correlation, variance partitioning, and partial information decomposition, address these questions by disentangling functional relations into interpretable information atoms (unique, redundant and synergistic). Here, we apply these tripartite metrics to simulated neuronal recordings to investigate their sensitivity to impurities (like noise or other unexplained variance) in the data. We find that all considered metrics are accurate and specific for pure signals but experience significant bias for impure signals. We show that permutation-testing of such metrics results in high false positive rates even for small impurities and large data sizes. We present a conservative null hypothesis for significance testing of tripartite metrics, which significantly decreases false positive rate at a tolerable expense of increasing false negative rate. We hope our study raises awareness about the potential pitfalls of significance testing and of interpretation of functional relations, offering both conceptual and practical advice. Author SummaryTripartite functional relation metrics enable the study of interesting effects in neural recordings, such as redundancy, functional connection specificity and synergistic coupling. However, common estimators of such relations are designed for pure (e.g. non-noisy) signals rare for such recordings. We study the performance of tripartite estimators using simulated impure neural signals. We demonstrate that permutation-testing is not a robust procedure for inferring ground truth interactions from studied estimators. We develop an adjusted conservative testing procedure, reducing false positive rate of studied estimators for impure data. Besides addressing significance testing, our results should aid in accurate interpretation of tripartite functional relations and functional connectivity.

neuroscience↗

bioRxiv2021

Striatum-projecting prefrontal cortex neurons support working memory maintenance

The medial prefrontal cortex (mPFC) and the dorsomedial striatum (dmStr) are linked to working memory (WM) but how striatum-projecting mPFC neurons contribute to WM encoding, maintenance, or retrieval remains unclear. Here, we probed mPFC[->]dmStr pathway function in freely-moving mice during a T-maze alternation test of spatial WM. Fiber photometry of GCaMP6m-labeled mPFC[->]dmStr projection neurons revealed strongest activity during the delay period that requires WM maintenance. Demonstrating causality, optogenetic inhibition of mPFC[->]dmStr neurons only during the delay period impaired performance. Conversely, enhancing mPFC[->]dmStr pathway activity--via pharmacological suppression of HCN1 or by optogenetic activation during the delay-- alleviated WM impairment induced by NMDA receptor blockade. Consistently, cellular-resolution miniscope imaging resolved preferred activation of >50% mPFC[->]dmStr neurons during WM maintenance. This subpopulation was distinct from neurons showing preference for encoding and retrieval. In all periods, including the delay, neuronal sequences were evident. Striatum-projecting mPFC neurons thus critically contribute to spatial WM maintenance.

neuroscience↗

bioRxiv2018

High-density multi-fiber photometry for studying large-scale brain circuit dynamics

Animal behavior originates from neuronal activity distributed and coordinated across brain-wide networks. However, techniques to assess large-scale brain circuit dynamics in behaving animals remain limited. Here we present compact, high-density arrays of optical fibers that can be chronically implanted into the mammalian brain, enabling multi-fiber photometry as well as optogenetic perturbations across many regions. In mice engaged in a texture discrimination task we achieved simultaneous photometric calcium recordings from networks of 12 to 48 brain regions, including striatal, thalamic, hippocampal, and cortical areas. Furthermore, we optically perturbed specific subsets of regions in VGAT-ChR2 mice by using a spatial light modulator to address the respective fiber channels. Perturbation of ventral thalamic nuclei caused distributed network modulation and behavioral deficits. Finally, we demonstrate multi-fiber photometry in freely moving animals, including simultaneous recordings from two mice during social interaction. Thus, high-density multi-fiber arrays are simple, low-cost, and versatile tools that open novel ways to investigate large-scale brain dynamics during behavior.

neuroscience↗