Biology subjects

Li, Y.-t.

Publications and source records attributed to Li, Y.-t..

4 recordsLinked to original sources

bioRxiv2026

Decoding natural scenes from patterned optogenetic responses in mouse visual cortex

A central challenge in developing visual cortical prostheses is to determine how visual stimuli should be transformed into effective patterns of cortical stimulation. Although advances in stimulation technologies, including optogenetics, provide increasingly precise control over cortical activity, it remains unclear whether artificially evoked activity can reproduce the information content of naturally evoked visual representations. Here we establish a quantitative framework for evaluating visual encoding strategies by decoding cortical responses evoked by natural vision and patterned optogenetic stimulation. We developed a novel dual-modal paradigm in awake mice to bridge the gap between endogenous photostimulation and artificial network driving. By co-expressing the high-performance calcium indicator GCaMP6s and the red-shifted, ultra-sensitive opsin rsChRmine-oScarlet in the primary visual cortex (V1), we successfully translated dynamic natural movie frames into patterned, spatiotemporal optogenetic stimulation. Quantitative comparisons of macro-scale dynamics demonstrated that this patterned optogenetic injection evokes cortical states highly comparable and representationally aligned with those driven by actual visual photostimulation. To systematically evaluate the fidelity of these responses, we developed STAR, a deep learning model featuring spatial and temporal attention mechanisms, and successfully reconstructed the frames of natural movies from V1 signals under both experimental modalities. Collectively, our results demonstrate that complex sensory information can be both naturally encoded and synthetically injected into V1 circuits with high decoding fidelity. This work provides an empirical and computational proof-of-concept for intelligent, closed-loop biomimetic encoders, establishing a robust framework for next-generation cortical visual neuroprostheses and bidirectional brain-machine interfaces.

neuroscience↗

bioRxiv2025

Rank- and Threat-Dependent Social Modulation of Innate Defensive Behaviors

Fear and defense are among the most fundamental survival behaviors and are profoundly influenced by the social environment in group-living animals. However, it remains poorly understood how social context--and particularly dominance hierarchy, a defining feature of many social species--modulates defensive strategies under ethologically relevant conditions. To address this question, we investigated the social modulation of innate fear in mice exposed to two ethologically relevant threats: a transient visual looming stimulus and a sustained predatory threat posed by a live rat. We found that social presence alleviated threat-induced stress and modulated defensive behaviors in a rank- and threat-specific manner. During looming exposure, it reduced immediate defensive responses and alleviated post-looming anxiety, with dominants showing greater benefit. During rat exposure, it promoted a shift from passive to active defense, again most prominently in dominants. These behavioral changes were accompanied by reorganization of transitions between defensive states, indicating that social hierarchy shapes both the expression and temporal organization of innate defensive behaviors. Conversely, threat exposure strengthened social engagement, with dominant mice exhibiting more proactive social behaviors and subordinate mice responding more readily to dominant social initiations. Together, these findings demonstrate how dominance hierarchy modulates defensive responses to distinct naturalistic threats and, in turn, how threat experience shapes social behavior, providing a behavioral framework for probing the neural basis of socially modulated innate fear.

neuroscience↗

bioRxiv2025

Economic and Social Modulations of Innate Decision-Making in Mice Exposed to Visual Threats

When confronted by predators, animals make innate decisions with rapid reaction times--a trait shaped by natural selection to maximize survival. However, rapid reactions are effective only when grounded in accurate judgments and appropriate choices, which often require cognitive control. To address how such choices are shaped, we developed a behavioral paradigm to investigate how threat intensity, reward value, and social hierarchy shape decision-making in foraging mice exposed to overhead visual threats. Using a machine learning-based approach, we classified defensive responses into four distinct decision types. Mice showed rapid habituation to repeated looming threats, with substantial inter-individual variability in the rate of habituation. Across both early and late phases of habituation, threat intensity emerged as the primary determinant of decision-making, strongly biasing behavior toward escape. In contrast, the influence of reward value was context-dependent and became evident primarily in the late phase: under low-threat conditions, higher reward value suppressed defensive responses, consistent with value-based decision theory; whereas under high-threat conditions, higher reward value promoted escape, potentially reflecting heightened vigilance. Innate decision-making was further modulated by social hierarchy, with dominant mice showing greater vigilance and a stronger bias toward risk-averse behaviors, while subordinates were more reward-driven. To understand the underlying decision-making process, we developed a drift-diffusion leaky integrator model that successfully captures how threat intensity, reward value, and vigilance interact to shape defensive decisions. Together, these findings reveal how economic and social factors modulate innate decisions and provide a computational framework for understanding the interplay between instinctive reactions and cognitive control.

neuroscience↗

bioRxiv2019

TCR repertoire analysis reveals effector memory T cells differentiation into Th17 cells in rheumatoid arthritis

The pathogenesis of rheumatoid arthritis (RA), a systemic autoimmune disease characterized by autoreactive T-cell accumulation and pro-inflammatory cytokine overproduction, is unclear. Systematically addressing T-cell receptor (TCR) repertoires of different CD4+ T-cell subsets could help understand RA pathogenesis. Here, peripheral CD4+ T cells from treatment-naive RA patients and healthy controls were sorted into seven subsets including naive, effector, central memory, effector memory (EMT), Th1, Th17, and regulatory T cells. T-cell receptor {beta} chain repertoires were then analyzed by next-generation sequencing. We identified T-cell clonal expansion in EMT and Th17 cells, with highly similar TCR repertoires between them. Ex vivo experiments demonstrated the preferred differentiation from EMT to Th17 cells in RA. Moreover, TCR diversity in subsets including Th17 was negatively correlated with RA disease activity indices such as C-reactive protein and erythrocyte sedimentation rate. Thus, shared and abnormally expanded EMT and Th17 TCR repertoires might be pivotal for RA pathogenesis.

immunology↗