Biology subjects

Sun, Q.-Q.

Publications and source records attributed to Sun, Q.-Q..

12 recordsLinked to original sources

bioRxiv2026

Conservation of gene co-expression networks and neuropsychiatric-neurological disease gene programs between mouse and human frontal cortex at single-cell resolution

Mouse models are widely used in translational neuroscience, but whether a gene has the same partners in mouse and human prefrontal cortex (PFC) is unknown. The genes whose expression rises and falls with a given gene across samples (its co-expression partners) indicate the molecular program to which it belongs. We compared the co-expression of 13,214 genes between mouse medial PFC and human dorsolateral PFC in 246,211 single-nucleus RNA-sequencing profiles. These two regions are not homologous, so part of any measured difference may reflect region and not species. The study has five main findings. First, the similarity of partners for single genes was modest (median 0.169; 0, unrelated; 1, identical). This median was below that of every comparison among human datasets but within the range of comparisons among mouse datasets, and correction for measurement noise raised it to 0.349 at most. Second, groups of co-expressed genes (modules) were strongly preserved. Third, neuropsychiatric disease genes were modestly more conserved than other genes, but no more than control genes matched for mutational constraint and expression, consistent with general gene properties and with how these genes are discovered. Fourth, no disease gene was shown to have different partners in the two species. Fifth, four of five human modules recurred in an independent human dataset. We also identified two sources of error: analyzing only the most variable genes excludes most disease genes, and networks built from few samples, as for glial cells, underestimate the similarity between species. Scores and code are released for cross-species studies.

genomics↗

bioRxiv2026

The NeuroHab: A Low-Cost, Integrated System for Investigation of Neural Correlates of Behaviors

The development of a new integrated operant system was driven by two challenges in behavioral neuroscience: the high cost and technical complexity of commercial rigs, and their limited adaptability across experiments. We developed the NeuroHab, an integrated behavioral arena for high-fidelity operant conditioning and automated data collection in a single unified system. Food and water reward, conditioned-stimulus presentation, and event recording are tied together programmatically with easy-to-install open-source code to facilitate throughput and reproducibility. All behavioral events are processed by internal microcontrollers and logged with <1 ms latency (typical range 56-728 s). This precise timing is critical for integrating the system with two-photon imaging and electrophysiology, enabling real-time alignment of behavior with brain activity. The NeuroHab uses solenoid-actuated, capacitive-sensing Lickports that let an untethered mouse drink from an automated port, and delivers food via the Kravitz Lab FED3. Conditioned stimuli are presented by dedicated buzzer/LED modules. A central controller (the Core) coordinates all modules and logs event timestamps using TTL-low signaling between two microcontrollers, at a maximum recording rate of 16.67 Hz for single-pulse events. We have deployed the NeuroHab in over 50 behavior trials and over 20 sessions alongside a Mini two-photon microscope. At approximately $1,400, easily modified, and compatible with existing analysis tools, the NeuroHab lowers barriers to multimodal behavioral neuroscience. Significance StatementThe study of how neural activity gives rise to behavior depends on operant systems that are both temporally precise and affordable, yet commercial rigs are costly and difficult to adapt across experiments. We introduce the NeuroHab, an integrated, open-source operant platform that unifies reward delivery, conditioned-stimulus presentation, and event logging with sub-millisecond timing (typical latency 56-728 s). Built for approximately $1,400, the system forwards all behavioral timestamps to external acquisition hardware, enabling millisecond-scale alignment of behavior with two-photon imaging and electrophysiology. By lowering the cost and technical barriers to synchronized behavioral and neural recording, the NeuroHab makes multimodal, reproducible operant neuroscience accessible to a broad range of laboratories and adaptable to diverse experimental paradigms.

neuroscience↗

bioRxiv2026

Transcriptome-Inspired Spiking Simulations Uncover Human-Specific Prefrontal Dynamics and Provide a Mechanistic Platform for Species-Appropriate Disease Modeling.

Whole-brain transcriptomic atlases are now widely available, yet computational neural models are almost exclusively parameterized from rodent data and used to infer human brain function, an extrapolation whose cost remains unquantified. To address this, we constructed a biophysically detailed, conductance-based Hodgkin-Huxley spiking microcircuit of a five-population prefrontal network, where every ion-channel, receptor, and gap-junction conductance was scaled by cell-type-specific gene expression. We parameterized the identical circuit using single-nucleus RNA-seq from mouse mPFC and human DLPFC, alongside a literature-derived baseline, and compared their high-frequency-oscillation (HFO) outputs across seven physiological and pathological states. While population firing rates differed only modestly between the two refinements ([~]20% for pyramidal and PV cells), the oscillatory dynamics diverged dramatically. The human-refined circuit generated strongly synchronized PV activity and robust ripple- and fast-ripple-band power (e.g., healthy-wake ripple power, in arbitrary units: 322 vs. 24 and 22), whereas the mouse-refined and literature arms remained asynchronous (interneuron synchrony: 0.21 vs. 0.02). This human >>mouse {approx} original hierarchy was statistically consistent across all seven states (significant arm differences in 75/77 comparisons). Mechanistically, the human transcriptome drove markedly stronger PV-PV electrical coupling (gap-junction scale: 1.78 vs. 0.96) paired with stronger recurrent pyramidal excitation, which collectively synchronized the fast-spiking PV population into a coherent rhythm that perisomatic inhibition then imposed on the local field potential. Critically, these results are model-dependent; the gene-to-conductance mapping is phenomenological, and mRNA expression does not linearly translate to functional conductance. Nonetheless, under this mapping the divergence localizes PV-mediated coupling and excitation-inhibition balance as the parameters most in need of human-specific recalibration. More broadly, this work establishes transcriptome-informed spiking simulation as a powerful strategy for uncovering species-specific computational principles and for building mechanistically grounded, human-relevant models of prefrontal circuit dysfunction, an approach that moves beyond generic rodent defaults to enable targeted, species-appropriate modeling of neurological and psychiatric disorders.

neuroscience↗

bioRxiv2026

A Multidimensional Framework for Behavioral Persistence: Dissociable Dimensions of Effort, Endurance, and Sequence Stability in Mice

Behavioral persistence, the maintenance of goal-directed action despite obstacles, is a fundamental adaptive process, yet its scientific study remains fragmented across disciplines with disparate operational definitions. Here, we introduce the Persistence Spectrum (PERCS) framework, a five-dimensional model deconstructing persistence into Perseverance of Effort (P), Strategic Endurance (E), Resistance to Extinction (R), Temporal Consistency (C), and Repetitive Sequence Stability (S). Using programmable operant schedules via the FED3 system, we induced a continuum of persistent food-seeking in mice across four paradigms: Fixed Ratio (FR), Alternating 2x2 and 5x5, and Random Progressive Ratio (RPR). To objectively identify persistence periods, we developed a session-specific Gaussian mixture model, providing a data-driven alternative to arbitrary frequency thresholds. We found that persistence bouts were fundamentally driven by unrewarded effort, not reward delivery: instantaneous frequency for incorrect pokes significantly exceeded that for correct pokes in FR, 2x2, and 5x5 (all p < 0.05). This pattern was most pronounced in the high-demand RPR schedule, where high-rate poking continued unabated even after successes, directly challenging reinforcement-centric models and providing strong empirical support for frustration theory. Linear mixed-effects modeling revealed that frequency increased with consecutive unrewarded pokes across all paradigms, with a quadratic (inverted-U) relationship specific to FR and 2x2 (p < 0.001), suggesting effort invigoration followed by strategic disengagement in simpler tasks, whereas high-demand schedules maintained linear increases. Notably, the collapse of Sequence Stability (S) in RPR is partly constrained by the tasks environmental contingency: random reward rules mathematically restrict stable sequence learning. Aggregate analysis showed total poke counts and unrewarded effort scaled with task difficulty (all p < 2e-16), yet pellet retrieval rates remained stable, indicating goal achievement despite increased challenge. Crucially, PERCS profiles were robust across independent and continuous training histories, demonstrating they reflect stable phenotypes shaped by current contingencies rather than training artifacts. Application of PERCS revealed distinct fingerprints: FR produced near-zero P, E, R, and C but maximal S, characteristic of an efficient habit; 2x2 and 5x5 elevated P, E, and R while reducing S; and RPR generated highest P and R, lowest S, and marked inter-individual variability. These findings demonstrate that operant schedules dissociably shape distinct persistence dimensions, with unrewarded effort acting as a key motivational trigger, positioning frustrative nonreward as a primary engine of persistent behavior. The PERCS framework provides a unified, quantitative language for characterizing persistent behavior across species and paradigms, offering a powerful tool for linking dimensions to neural circuits and understanding their breakdown in neuropsychiatric disorders.

animal behavior and cognition↗

bioRxiv2025

Sensory Circuit Dynamics in a Mouse Model of Epileptic Encephalopathy

Epileptic encephalopathies (EEs) are severe developmental disorders with abnormal EEG activity that worsens neurodevelopmental deficits, yet underlying sensory and cognitive impairment mechanisms are unclear. We studied cortical circuit dynamics in Ank3-1b-/- mice, an EE model with parvalbumin interneuron dysfunction, using laminar electrophysiology, spike-field coherence (SFC), single-unit analyses, and behavioral assays. Ank3-1b-/- mice showed disrupted excitatory-inhibitory (E-I) balance, with reduced sink/source ratios (p = 0.0279) and elevated net currents (AVREC; p < 0.01), indicating hyperexcitability. In awake states, sensory-evoked intra-columnar connectivity was impaired, with lower Pearson correlations (p < 0.001) and increased low-frequency (3-30 Hz) SFC (p < 0.001), but intact gamma-band coherence, suggesting aberrant synchronization. Inhibitory neuron latencies were delayed in infragranular layers under anesthesia (p < 0.001) and supragranular layers when awake (p = 0.005), implying thalamocortical deficits. Despite preserved sensory adaptation and recognition memory, Ank3-1b-/- mice exhibited heightened anxiety (p < 0.05) and variable circadian rhythms, indicating selective affective and regulatory deficits. These results show that Ank3-1b loss disrupts cortical E-I balance and synchrony, delaying sensory processing, while compensatory mechanisms maintain critical sensory functions. This study links ANK3 mutations to layer-specific circuit dysfunction, offering insights into EE pathophysiology and sensory deficits.

neuroscience↗

bioRxiv2025

Distinct Roles of Somatostatin and Parvalbumin Interneurons in Regulating Predictive Actions and Emotional Responses During Trace Eyeblink Conditioning

Learning involves evaluating multiple dimensions of information and generating appropriate actions, yet how the brain assigns value to this information remains unclear. In this study, we show that two types of interneurons (INs) in the primary somatosensory cortex--somatostatin-expressing (SST-INs) and parvalbumin-expressing (PV-INs) neurons--differentially contribute to information evaluation during trace eyeblink conditioning (TEC). An air puff (unconditioned stimulus, US) delivered after a whisker stimulus (conditioned stimulus, CS) elicited both reflexive eye closure and stress-related locomotion. However, only self-initiated, anticipatory eye closure during the CS window, measured via electromyography (EMG), was directly relevant to learning performance. We found that SST-IN activity changes aligned with the learning induced changes of the anticipatory eye blinks during the CS period, correlated with the EMG changes across learning. In contrast, PV-IN activity was positively correlated with stress-related locomotion following the US and showed no learning related changes, suggesting a role in processing the emotional or aversive component of the task. Furthermore, cholinergic signaling via nicotinic receptors modulated both SST- and PV-IN activities, in a manner consistent with their distinctive roles, linking these interneurons to the regulation of learning-related actions and emotional responses, respectively. These findings demonstrate that distinct interneuron populations evaluate different dimensions of information--SST-INs for predictive, adaptive actions and PV-INs for stress-related emotional responses--to guide learning and behavior.

neuroscience↗

bioRxiv2024

Control of behavioral uncertainty by divergent frontal circuits

Both ambiguous inference from current input and internal belief from prior input causes uncertainty. The uncertainty is typically manifested as a normal distribution at behavioral level when only current inference is manipulated as variable. When prior belief is varying, some decision relevant neural representations are dissociated. Under this circumstance, it is unclear how to describe the uncertainty and how dissociated neural representations cooperate to control the uncertainty. By simulating an unpredictable environment, which incurs conflicting valence-dependent prior beliefs, we found that a behavioral outcome, waiting time, does not follow a normal, but a log-normal distribution. By combining electrophysiological recordings, computational modeling, optogenetic manipulation, scRNA-seq and MERFISH, we showed that the formation of this behavioral outcome requires the temporally hierarchical cooperation of the neural representation of decision confidence and B230216N24Rik marked neural representation of positive and negative belief in the medial prefrontal cortex (mPFC). In summary, our results provide a mechanistic link between the dynamics of valence-dependent prior beliefs and behavioral uncertainty.

neuroscience↗

bioRxiv2023

Learning induced neuronal identity switch in the superficial layers of the primary somatosensory cortex

During learning, multi-dimensional inputs are integrated within the sensory cortices. However, the strategies by which the sensory cortex employs to achieve learning remains poorly understood. We studied the sensory cortical neuronal coding of trace eyeblink conditioning (TEC) in head-fixed, freely running mice, where whisker deflection was used as a conditioned stimulus (CS) and an air puff to the cornea delivered after an interval was used as unconditioned stimulus (US). After training, mice learned the task with a set of stereotypical behavioral changes, most prominent ones include prolonged closure of eyelids, and increased reverse running between CS and US onset. The local blockade of the primary somatosensory cortex (S1) activities with muscimol abolished the behavior learning suggesting that S1 is required for the TEC. In naive animals, based on the response properties to the CS and US, identities of the small proportion ([~]20%) of responsive primary neurons (PNs) were divided into two subtypes: CR (i.e. CS-responsive) and UR neurons (i.e. US-responsive). After animals learned the task, identity of CR and UR neurons changed: while the CR neurons are less responsive to CS, UR neurons gain responsiveness to CS, a new phenomenon we defined as learning induced neuronal identity switch (LINIS). To explore the potential mechanisms underlying LINIS, we found that systemic and local (i.e. in S1) administration of the nicotinic receptor antagonist during TEC training blocked the LINIS, and concomitantly disrupted the behavior learning. Additionally, we monitored responses of two types of cortical interneurons (INs) and observed that the responses of the somatostatin-expressing (SST), but not parvalbumin-expressing (PV) INs are negatively correlated with the learning performance, suggesting that SST-INs contribute to the LINIS. Thus, we conclude that L2/3 PNs in S1 encode perceptual learning by LINIS like mechanisms, and cholinergic pathways and cortical SST interneurons are involved in the formation of LINIS.

animal behavior and cognition↗

bioRxiv2023

A prefrontal motor circuit initiates persistent movement

Persistence reinforces continuous action, which benefits animals in many aspects. Diverse information may trigger animals to start a persistent movement. However, it is unclear how the brain decides to persist with current actions by selecting specific information. Using single-unit extracellular recordings and opto-tagging in awake mice, we demonstrated that a group of dorsal mPFC (dmPFC) motor cortex projecting (MP) neurons initiate a persistent movement selectively encoding contextual information rather than natural valence. Inactivation of dmPFC MP neurons impairs the initiation and reduces neuronal activity in the insular and motor cortex. Finally, a computational model suggests that a successive sensory stimulus acts as an input signal for the dmPFC MP neurons to initiate a persistent movement. These results reveal a neural initiation mechanism on the persistent movement.

neuroscience↗

bioRxiv2022

A Proximity Sensor-Based Multipurpose Object Recognition Test System for Rodent Behavior Research

We report an automated, low-cost, and open-source methodology for rodent object recognition tasks (ORT), which are widely used behavior paradigms. The system was designed with an effort of behavior standardization and improvement. When it combined with easily accessible 3-D manufacturing technology, this proximity capacitive sensor based method provides an opportunity to explore new, and high throughput hardware for NORT. The systems software allows behavior data to be instantaneously monitored and its output can be plotted promptly immediately upon the completion of the behavior test, thus saving labor and time. The performance of this package is cross-verified with a widely used video-based automated software scoring method and examined its sensitivity to chemogenetic behavior manipulations. This integrated package is an affordable and accurate tool for translational recognition memory research and other type of research with frequent use of NORT paradigms. Visual Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=52 SRC="FIGDIR/small/518044v1_ufig1.gif" ALT="Figure 1"> View larger version (18K): org.highwire.dtl.DTLVardef@1205ca6org.highwire.dtl.DTLVardef@1a2d156org.highwire.dtl.DTLVardef@5d8ef9org.highwire.dtl.DTLVardef@5589ee_HPS_FORMAT_FIGEXP M_FIG C_FIG

animal behavior and cognition↗

bioRxiv2020

Urine metabolomics of rats with chronic atrophic gastritis

Background/Aim: To use liquid chromatography-mass spectrometry (LC-MS) to identify endogenous differential metabolites in the urine of rats with chronic atrophic gastritis (CAG). Materials and Methods: Methylnitronitrosoguanidine (MNNG) was used to produce a CAG model in Wistar rats, and HE staining was used to determine the pathological model. LC-MS was used to detect the differential metabolic profiles in rat urine. Diversified analysis was performed by the statistical method. Results: Compared with the control group, the model group had 68 differential metabolites, 25 that were upregulated and 43 that were downregulated. The main metabolic pathways were D-glutamine and D-glutamic acid metabolism, histidine metabolism and purine metabolism. Conclusion: By searching for differential metabolites and metabolic pathways in the urine of CAG rats, this study provides effective experimental data for the pathogenesis and clinical diagnosis of CAG.View Full Text

molecular biology↗

bioRxiv2020

Circuit mechanisms underlying chronic epilepsy in a mouse model of focal cortical malformation

HighlightsO_LIEctopic interlaminar excitatory inputs from infragranular layers to layer 2/3 pyramidal neurons is a key component of the hyperexcitable circuitry C_LIO_LIDisrupted E/I balance was located far away from cortical malformations C_LIO_LIDendritic inhibition from somatostatin interneurons play a key role in epileptogenesis C_LIO_LIClosed-loop optogenetic stimulation to activate remainder somatostatin interneurons irreversibly stops the spontaneous spike-wave discharges in vivo. C_LI In BriefYang et al. report abnormal synaptic reorganization in an epileptogenesis zone in a mouse model of cortical malformation. The authors further demonstrate that spontaneous spike-wave discharges can be curbed by selectively activating somatostatin interneurons using close-loop fiber optogenetic stimulation to a small cortical region away from the microgyrus. SummaryHow aberrant neural circuits contribute to chronic epilepsy remains unclear. Using a mouse model of focal cortical malformation with spontaneous seizures, we dissected the circuit mechanisms underlying epileptogenesis. Spontaneous and optogenetically induced hyperexcitable bursts in vivo were present in a cortical region distal to (> 1mm) freeze-lesion induced microgyrus, instead of a region near it. ChR2-assisted circuit mapping revealed ectopic interlaminar excitatory inputs from infragranular layers to layer 2/3 pyramidal neurons as a key component of the hyperexcitable circuitry. This disrupted balance between excitation and inhibition was prominent in the cortical region distal to the microgyrus. Consistently, the synapses of both parvalbumin-positive interneurons (PV) and somatostatin-positive interneurons (SOM) to pyramidal neurons were maladaptive in a layer- and site-specific fashion. Finally, closed-loop optogenetic stimulation of SOM, but not PV, terminated spontaneous spike-wave discharges. Together, these results demonstrate highly site- and cell-type specific synaptic reorganization underlying chronic cortical epilepsy and provide insights into potential treatment strategies for this devastating neurological disorder.

neuroscience↗