Biology subjects

Li, V. Y.

Publications and source records attributed to Li, V. Y..

4 recordsLinked to original sources

bioRxiv2026

Distinct NMDA Receptor Pools Determine Diverse Forms of Cortical Plasticity

NMDA receptors (NMDARs) are well-established as coincidence detectors in Hebbian learning, but this requires postsynaptic localization. Presynaptic NMDARs, however, remain controversial due to limitations of pharmacology and calcium imaging. We therefore dissected the function of distinct NMDAR pools using more direct techniques, including immunogold EM, sparse genetic deletion, and paired recordings from layer-5 (L5) pyramidal cell (PC) synapses in mouse primary visual cortex (V1). We found that pre- but not postsynaptic NMDARs regulate both spontaneous and evoked neurotransmitter release. In spike-timing-dependent plasticity, we uncovered a double dissociation: timing-dependent long-term depression (tLTD) requires pre- but not postsynaptic NMDARs, whereas timing-dependent long-term potentiation (tLTP) needs post- but not presynaptic NMDARs. Postsynaptic NMDAR loss also caused developmentally delayed dendritic spine loss and altered axonal and dendritic architecture. In summary, NMDARs do not act as a unified plasticity signal but rather confer location-specific control over diverse forms of synaptic signaling, plasticity, and circuit structure.

neuroscience↗

bioRxiv2025

Evaluation of full-length 16S rRNA amplicon sequencing using Oxford Nanopore Technologies for diversity surveys of understudied microbiomes

O_LIThe use of long-read sequencing using portable Oxford Nanopore Technologies (ONT) is becoming increasingly popular in the study of host-associated microbiomes. However, its application has not yet been optimized for characterizing understudied microbiomes, such as those in marine environments. C_LIO_LIWe evaluated the accuracy and consistency of ONT sequencing of full-length 16S rRNA genes for diversity surveys of symbiotic dinoflagellate (family Symbiodiniaceae) microbiomes. C_LIO_LIWhen comparing amplicon sequencing of the full-length bacterial 16S rRNA gene with only its V4 hypervariable gene region using a known microbial community, the former recapitulated the bacterial taxonomic composition more accurately. C_LIO_LIONT sequencing was also highly consistent between sequencing runs and flow cells. C_LIO_LILong-read sequencing technologies enable microbiome surveys using the full-length 16S rRNA gene, achieving higher accuracy and resolution. C_LIO_LIThis work validates ONT long-read sequencing as a powerful tool for marine microbiome studies to catalyze advancements in the fields of ecology and evolution, resource management, and conservation. C_LI

ecology↗

bioRxiv2024

Perineuronal nets in motor circuitry regulate the performance of learned vocalizations in songbirds

The accurate and reliable production of learned behaviors can be important for survival and reproduction; for example, the performance of learned vocalizations (e.g., speech and birdsong) modulates the efficacy of social communication in humans and songbirds. Consequently, it is critical to understand the factors that regulate the performance of learned behaviors. Across various taxa, neural circuits that regulate motor learning are replete with perineuronal nets (PNNs), extracellular matrices that surround neurons and shape neural dynamics and plasticity. Perineuronal nets in circuits for sensory and cognitive processes have been found to affect sensory processing and behavioral plasticity. However, the function of PNNs in motor circuits remains largely unknown. Here, we analyzed the causal contribution of PNNs in motor circuitry to the performance of learned vocalizations in songbirds. Songbirds like the zebra finch are powerful models for this endeavor because the performance of their learned songs is regulated by activity within discrete and specialized circuits (i.e., song system) that are dense with PNNs. We first report that developmental increases in the density and intensity of PNNs throughout the song system [including in the motor nucleus HVC (acronym used as proper name)] are associated with developmental increases in song performance. We next discovered that enzymatically degrading PNNs in HVC acutely affected song performance. In particular, PNN degradation caused song structure to deviate from pre-surgery song due to changes in syllable sequencing and production. Collectively, our data provide compelling evidence for a causal contribution of PNNs to the performance of learned behaviors. SIGNIFICANCE STATEMENTMotor circuits are replete with perineuronal nets (PNNs) but little is known about their contribution to motor performance. Here, we analyzed how PNNs within vocal motor circuits modulate the ability of songbirds to consistently produce their learned songs. We report that developmental increases in PNN expression in vocal circuitry were associated with developmental increases in the ability to consistently perform their learned song. Moreover, degrading PNNs in the vocal motor nucleus HVC reduced the ability of adult birds to accurately produce their learned song. Our findings indicate a causal contribution of PNNs in motor circuitry to the performance of learned behaviors and, because PNNs are expressed in brain areas regulating speech, suggest that PNNs could modulate speech production in humans.

neuroscience↗

bioRxiv2023

Principles of visual cortex excitatory microcircuit organization

Microcircuit function is determined by patterns of connectivity and short-term plasticity that vary with synapse type. Elucidating microcircuit function therefore requires synapse-specific investigation. The state of the art for synapse-specific measurements has long been paired recordings. Although powerful, this method is slow, leading to a throughput problem. To improve yield, we therefore created optomapping -- an approximately 100-fold faster 2-photon optogenetic method -- which we validated with paired-recording data. Using optomapping, we tested 15,433 candidate excitatory inputs to find 1,184 connections onto pyramidal, basket, and Martinotti cells in mouse primary visual cortex, V1. We measured connectivity, synaptic weight, and short-term dynamics across the V1 layers. We found log-normal synaptic strength distributions, even in individual inhibitory cells, which was previously not known. We reproduced the canonical circuit for pyramidal cells but found surprising and differential microcircuit structures, with excitation of basket cells concentrated to layer 5, and excitation of Martinotti cells dominating in layer 2/3. Excitation of inhibitory cells was denser, stronger, and farther-reaching than excitation of excitatory cells, which promotes stability and difference-of-Gaussian connectivity. We gathered an excitatory short-term plasticitome, which revealed that short-term plasticity is simultaneously target-cell specific and dependent on presynaptic cortical layer. Peak depolarization latency in pyramidal cells also emerged as more heterogeneous, suggesting heightened sensitivity to redistribution of synaptic efficacy. Optomapping additionally revealed high-order connectivity patterns including shared-input surplus for interconnected pyramidal cells in layer 6. Optomapping thus offered both resolution to the throughput problem and novel insights into the principles of neocortical excitatory fine structure. HIGHLIGHTSO_LI2-photon optomapping of microcircuits is verified as fast, accurate, and reliable C_LIO_LISynaptic weights distribute log-normally even for individual inhibitory neurons C_LIO_LIMaximal excitation of basket and Martinotti cells in layer 5 and 2/3, respectively C_LIO_LIShort-term plasticity depends on layer in addition to target cell C_LI

neuroscience↗