Biology subjects

Dang, W.

Publications and source records attributed to Dang, W..

15 recordsLinked to original sources

bioRxiv2026

Disentanglement of persistent and dynamic neural substrates of working memory

Competing theories of working memory have alternatively emphasized the importance of persistent and dynamic substrates of this cognitive function. Here, we directly tested these theories by computationally isolating the contributions of persistent and dynamic activity to working memory. We analyzed neuronal population activity recordings in macaques doing match/non-match working memory tasks. We first extracted signatures of persistent and dynamic activity through cue-specific temporal means, temporal principal components, and correlations of activity patterns across task epochs. We then generated synthetic data constrained by these signatures, and decoded cue stimuli from these data, separately from persistent and non-persistent neurons. We found that high decoding performance arose from a nuanced interplay of persistent and dynamic activity. Specifically, we could decode stimuli at empirical or above-chance levels across all tasks only from persistent neurons, but only after constraining correlations of activity patterns across epochs. In this way, we showed distinct roles for persistent and dynamic neuronal activity that help to unify two competing theories of working memory. More broadly, we also advanced computational controlled experiments as a principled framework for adjudicating between competing models of neuronal population activity.

neuroscience↗

bioRxiv2026

The cost of efficiency in flexible neural representations

Working memory depends on the flexible representation of stimulus information in neural activity, which changes dynamically depending on task. Stimulus transformations are thought to be efficient in use of neural resources and optimal for task performance. However, these transformations are often opaque, and efficiency may conflict with optimal performance. Here we show that in a working memory task requiring selective recall of one of two stimuli based on a context cue, the prefrontal cortex of two male monkeys prioritized efficiency by overwriting information within a shared neural subspace rather than maintaining distinct subspaces for each stimulus. In neural activity and recurrent neural networks such efficiency incurs a cost, in that efficient representations are more prone to errors. Conversely, stimulation of the cholinergic forebrain which improves behavior altered this default mechanism by encoding distinct contexts in higher dimensions. These findings demonstrate a fundamental tradeoff between efficiency and effectiveness in flexibly updating working memory.

neuroscience↗

bioRxiv2026

Prefrontal Mechanisms of Rule Learning

Rule learning is associated with lasting changes in prefrontal activity. However, experiments typically focus on learning a single set of rules or task and there remains a significant gap regarding how related mechanisms may reflect behavioral improvements in different contexts, especially when examining across different tasks and modalities. We therefore recorded single units from chronic electrode arrays implanted in the prefrontal cortex of four monkeys as they were trained to perform spatial and object working memory tasks with the goal of assessing the resulting activity changes that would be induced by rule learning. Progression of training allowed behavioral improvements to be correlated with a variety of neural effects that could be observed across different task contexts, including increases or decreases of both firing rate and decoding, increases in the proportion of firing rate variance that was unexplained by sensory stimuli and motor actions, and the increased separation of population response trajectories in state space. Our results thus reveal how rule learning induces plasticity of prefrontal cortical activity, and the aspects of neural activity changes that were unique to individual tasks and modalities or common across them. Our results ultimately reveal new patterns of training effects, identifying the generalized prefrontal mechanisms that are responsible for rule learning.

neuroscience↗

bioRxiv2026

Repeatable, low-drift recordings in behaving non-human primates using flexible microelectrodes

Neurophysiological recordings from non-human primates (NHPs) have traditionally relied on rigid microelectrode arrays made from stainless steel or silicon. While these devices enable high-quality recordings, a fundamental mechanical mismatch between rigid materials and soft brain tissue leads to inflammation, gliosis, and signal instability. In particular, brain micromotion causes continuous drifting of neurons relative to fixed electrodes, compromising single-unit tracking during both chronic and acute recordings. Flexible, penetrating electrodes offer a promising solution, but their adoption in NHPs has been hindered by the technical challenges of delivering ultra-thin polymers through thick dura mater. Here, we demonstrate a comprehensive approach for acute, repeated recordings in awake, behaving NHPs using flexible arrays. We fabricated a microelectrode array that spans cortical layers with 32 cellular-scale recording sites embedded in 7 m-thick Parylene-C. We developed a novel "telescopic" insertion method that combines concentric guide tubes with a retractable microwire shuttle. Our technique is compatible with standard chronic recording chambers and allowed for repeated penetration of free-floating arrays through intact dura over weeks without the need for a new craniotomy. Across two awake rhesus macaques, we optimized the electrode geometry and insertion procedure to achieve an 80% single-unit recording success rate. As animals performed an oculomotor delayed response task, we recorded task-responsive neurons from prefrontal and posterior parietal cortex with stable single-unit activity throughout 1-2-hour behavioral sessions. Critically, by comparing our flexible arrays to rigid probes in the same animals and recording chambers, we provide quantitative evidence that flexible electrodes reduce total single-unit drift from hundreds to tens of microns. Our work establishes flexible microelectrode arrays as a practical, dependable technology for NHP neuroscience and paves the way toward long-term, ultra-stable neurophysiology in large animal models.

neuroscience↗

bioRxiv2025

Asynchronous firing and off-states in working memory maintenance

Persistent spiking activity and activity-silent mechanisms have been proposed as neural correlates of working memory. To determine their relative contribution, we recorded neural activity from the lateral prefrontal and posterior parietal cortex of two male macaques using high-density microelectrode probes. We found that, when averaged across all neurons, persistent delay activity was observable throughout the duration of single trials in populations of prefrontal neurons with silent periods that did not deviate significantly from chance. However, temporal fluctuations in activity-dependent mnemonic information were present and weakly correlated between the prefrontal and posterior parietal cortices, suggesting at least partial, long-distance synchronization of off-states. Decoding accuracy of neurons recorded simultaneously was also reduced relatively to pseudo-populations constructed by splicing different trials together. Our results support an asynchronous state of working memory, maintained by the distributed pattern of persistent discharges across cortical neurons, which is subject to widely distributed fluctuations in information representation fidelity.

neuroscience↗

bioRxiv2025

Nucleosome stability safeguards cell identity, stress resilience and healthy aging

Nucleosomes are the minimal repeating units of chromatin. Their dynamic assembly and disassembly underpins chromatin organization and genome regulation. However, it remains unclear how intrinsic nucleosome stability contributes to higher-level yet fundamental cellular and organismal properties--such as preservation of cell identity, lineage specification, stress resilience and ultimately healthy aging. To address this, we tested the impact of decreased intrinsic nucleosome stability across multiple cell, tissue and organismal models by introducing histone mutants that weaken histone-histone interactions. While nucleosome instability did not broadly alter global chromatin accessibility, DNA damage, cell proliferation or viability, it impaired lineage-specific gene expression programs, altered lineage specification and activated intrinsic inflammatory and stress pathways in a manner reminiscent of aging in mouse tissues and human cells. Consistently, nucleosome instability accelerated the onset of age-associated transcriptional alterations and functional decline in Caenorhabditis elegans and Drosophila melanogaster, and reduced cellular resilience to exogenous perturbations-- including environmental, epigenetic and mitotic stress--in human cells and Saccharomyces cerevisiae. These cross-species findings identify nucleosome stability as an evolutionarily conserved epigenetic safeguard that preserves cell identity and stress resilience and supports organismal function and healthy aging.

genomics↗

bioRxiv2025

Lysosomes Signal through Epigenome to Regulate Longevity across Generations

Epigenome is sensitive to metabolic inputs and crucial for aging. Lysosomes emerge as a signaling hub to sense metabolic cues and regulate longevity. We unveil that lysosomal metabolic pathways signal through the epigenome to regulate transgenerational longevity in Caenorhabditis elegans. We discovered that the induction of lysosomal lipid signaling and lysosomal AMP-activated protein kinase (AMPK), or the reduction of lysosomal mechanistic-target-of-rapamycin (mTOR) signaling, increases the expression of histone H3.3 variant and elevates H3K79 methylation, leading to lifespan extension across multiple generations. This transgenerational pro-longevity effect requires intestine-to-germline transportation of H3.3 and a germline-specific H3K79 methyltransferase, and can be recapitulated by overexpressing H3.3 or the H3K79 methyltransferase. This work uncovers a lysosome-epigenome signaling axis linking soma and germline to mediate the transgenerational inheritance of longevity.

genetics↗

bioRxiv2023

Yeast EndoG prevents genome instability by degrading cytoplasmic DNA

In metazoans release of mitochondrial DNA or retrotransposon cDNA to cytoplasm can cause sterile inflammation and disease. Cytoplasmic nucleases degrade these DNA species to limit inflammation. It remains unknown whether degradation these DNA also prevents nuclear genome instability. To address this question, we decided to identify the nuclease regulating transfer of these cytoplasmic DNA species to the nucleus. We used an amplicon sequencing-based method in yeast enabling analysis of millions of DSB repair products. Nuclear mtDNA (NUMTs) and retrotransposon cDNA insertions increase dramatically in nondividing stationary phase cells. Yeast EndoG (Nuc1) nuclease limits insertions of cDNA and transfer of very long mtDNA (>10 kb) that forms unstable circles or rarely insert in the genome, but it promotes formation of short NUMTs ([~]45-200 bp). Nuc1 also regulates transfer of cytoplasmic DNA to nucleus in aging or during meiosis. We propose that Nuc1 preserves genome stability by degrading retrotransposon cDNA and long mtDNA, while short NUMTs can originate from incompletely degraded mtDNA. This work suggests that nucleases eliminating cytoplasmic DNA play a role in preserving genome stability.

genetics↗

bioRxiv2023

Local organization of spatial and shape information during working memory in the primate prefrontal cortex

The current understanding of sensory and motor cortical areas has been defined by the existence of topographical maps across the brain surface, however, higher cortical areas, such as the prefrontal cortex, seem to lack an equivalent organization, and only limited evidence of functional clustering of neurons with similar stimulus properties is evident in them. We thus sought to examine whether neurons that represent similar spatial and object information are clustered in the monkey prefrontal cortex and whether such an organization only emerges as a result of training. To this end, we analyzed neurophysiological recordings from male macaque monkeys before and after training in spatial and shape working memory tasks. Neurons with similar spatial or shape selectivity were more likely than chance to be encountered at short distances from each other. Some aspects of organization were present even in naive animals, however other changes appeared after cognitive training. Our results reveal that prefrontal microstructure automatically supports orderly representations of spatial and object information.

neuroscience↗

bioRxiv2023

Decoding working memory information from persistent and activity-silent neurons in the primate prefrontal cortex

Persistent activity of neurons in the prefrontal cortex has been thought to represent the information maintained in working memory, though alternative models have recently challenged this idea. Activity-silent theories posit that stimulus information may be maintained by the activity pattern of neurons that do not produce firing rate significantly elevated about their baseline during the delay period of working memory tasks. We thus tested the ability of neurons that do and do not generate persistent activity in the prefrontal cortex of monkeys to represent spatial and object information in working memory. Neurons that generated persistent activity represented more information about the stimuli in both spatial and object working memory tasks. The amount of information that could be decoded from neural activity depended on the choice of decoder and parameters used but neurons with persistent activity outperformed non-persistent neurons consistently. Although averaged across all neurons and stimuli, firing rate did not appear clearly elevated above baseline during the maintenance of neural activity particularly for object working memory, this grant average masked neurons that generated persistent activity selective for their preferred stimuli, which carried the majority of information about the stimulus identity. These results reveal that prefrontal neurons with generate persistent activity constitute the primary mechanism of working memory maintenance in the cortex. NEW AND NOTEWORTHYCompeting theories suggest that neurons that generate persistent activity or do not are primarily responsible for the maintenance of information, particularly regarding object working memory. While the two models have been debated on theoretical terms, direct comparison of empirical results have been lacking. Analysis of neural activity in a large database of prefrontal recordings revealed that neurons that generate persistent activity were primarily responsible for the maintenance of both spatial and object working memory.

neuroscience↗

bioRxiv2022

Prefrontal neuronal dynamics in the absence of task execution

Prefrontal cortical activity represents stimuli in working memory tasks in a low-dimensional manifold that transforms over the course of a trial. Such transformations reflect specific cognitive operations, so that, for example, the rotation of stimulus representations is thought to reduce interference by distractor stimuli. Here we show that rotations occur in the low-dimensional activity space of prefrontal neurons in naive monkeys, while passively viewing familiar stimuli. Moreover, some aspects of these rotations remain remarkably unchanged after training to perform working memory tasks. Significant training effects are still present in population dynamics, which further distinguish correct and error trials during task execution. Our results reveal automatic functions of prefrontal neural circuits, allow transformations that may aid cognitive flexibility.

neuroscience↗

bioRxiv2022

Localized Synaptic Potentiation is Necessary and Sufficient for Context Fear Memory

The nature and distribution of the synaptic changes that underlie memory are not well understood. We examined the synaptic plasticity behind context fear conditioning and found that learning produced synaptic potentiation specifically onto engram neurons in the basolateral amygdala. This potentiation lasted at least 7 days, was reversed by extinction, and its disruption impaired memory recall. High frequency optogenetic stimulation of the CS and US-activated ensembles, or biochemical induction of synaptic potentiation in US-responsive neurons alone, was sufficient to produce a context fear association without prior associative training. These results suggest that plasticity of CS inputs onto US-responsive amygdala neurons underlies memory formation and is necessary and sufficient to establish context fear associations.

neuroscience↗

bioRxiv2020

Protein-protein interaction probability landscapes for yeast replicative aging

We proposed a novel probability landscape approach to map the systems-level profile changes of gene networks during replicative aging in Saccharomyces cerevisiae. This approach enabled us to apply quasi-potentials, the negative logarithm of the probabilities, to calibrate the elevation of the landscapes with young cells as a reference state. Our approach detected opposite landscape changes based on protein abundances from transcript levels, especially for intra-essential gene interactions. We showed that essential proteins play different roles from hub proteins on the age-dependent landscapes. We verified that hub proteins tend to avoid other hub proteins, but essential proteins are attractive to other essential proteins. Overall, we showed that the probability landscape is promising for inferring network profile change during aging and that the essential hub proteins may play an important role in the uncoupling between protein and transcript levels during replicative aging.

systems biology↗

bioRxiv2020

Emergence of Non-Linear Mixed Selectivity in Prefrontal Cortex after Training

Neurons in the prefrontal cortex (PFC) are typically activated by different cognitive tasks, and also by different stimuli and abstract variables within these tasks. A single neurons selectivity for a given stimulus dimension often changes depending on its context, a phenomenon known as nonlinear mixed selectivity (NMS). It has previously been hypothesized that NMS emerges as a result of training to perform tasks in different contexts. We tested this hypothesis directly by examining the neuronal responses of different PFC areas before and after monkeys were trained to perform different working memory tasks involving visual stimulus locations and/or shapes. We found that training induces a modest increase in the proportion of PFC neurons with NMS exclusively for spatial working memory, but not shape working memory tasks, with area 9/46 undergoing the most significant increase in NMS cell proportion. We also found that increased working memory task complexity, in the form of simultaneously storing location and shape combinations, does not increase the degree of NMS for stimulus shape with other task variables. Lastly, in contrast to the previous studies, we did not find evidence that NMS is predictive of task performance. Our results thus provide critical insights on the representation of stimuli and task information in neuronal populations, which may pave the way to a greater understanding of neural selectivity in working memory. SIGNIFICANCE STATEMENTHow multiple types of information are represented in working memory remains a complex computational problem. It has been hypothesized that nonlinear mixed selectivity allows neurons to efficiently encode multiple stimuli in different contexts, after subjects have been trained in complex tasks. Our analysis of prefrontal recordings obtained before and after training monkeys to perform working memory tasks only partially agreed with this prediction, in that nonlinear mixed selectivity emerged for spatial but not shape information, and mostly in mid-dorsal PFC. Nonlinear mixed selectivity also displayed little modulation across either task complexity or correct performance. These results point to other mechanisms, in addition to nonlinear mixed selectivity, to represent complex information about stimulus and context in neuronal activity.

neuroscience↗

bioRxiv2019

Complementary Performances of Convolutional and Capsule Neural Networks on Classifying Microfluidic Images of Dividing Yeast Cells

Microfluidic-based assays have become effective high-throughput approaches to examining replicative aging of budding yeast cells. Deep learning may offer an efficient way to analyze a large number of images collected from microfluidic experiments. Here, we compare three deep learning architectures to classify microfluidic time-lapsed images of dividing yeast cells into categories that represent different stages in the yeast replicative aging process. We found that convolutional neural networks outperformed capsule networks in terms of accuracy, precision, and recall. The capsule networks had the most robust performance at detecting one specific category of cell images. An ensemble of three best-fitted single-architecture models achieves the highest overall accuracy, precision, and recall due to complementary performances. In addition, extending classification classes and augmentation of the training dataset can improve the predictions of the biological categories in our study. This work lays a useful framework for sophisticated deep-learning processing of microfluidics-based assays of yeast replicative aging.

bioinformatics↗