Biology subjects

Yeh, C.-H.

Publications and source records attributed to Yeh, C.-H..

17 recordsLinked to original sources

bioRxiv2026

Apoptotic Quality Control of Cellular Competence Limits Cryptic Germinal Center B Cell States

Germinal center (GC) B cells undergo extensive apoptosis, but how this process shapes evolving GC populations remains unclear. Using mice lacking intrinsic apoptotic effectors BAK and BAX in B cells, we found that mitochondrial apoptosis was dispensable for affinity maturation but critical for controlling GC size and cellular composition, showing that GC population dynamics and affinity maturation can be uncoupled. BAK/BAX-deficient mice mounted enlarged and prolonged GC responses, largely due to the accumulation of non-proliferating Ki-67loCD71lo dark zone (DZ) B cells. CD71hi and CD71lo DZ cells exhibited similar B-cell receptor (BCR) avidity, retained potential for proliferation and plasmacytic differentiation, and shared clonal lineages, indicating recurrent emergence of non-proliferating DZ populations. A subset also carried Somatic-hypermutation-derived defects that abolished antibody expression despite apparently productive V(D)J sequences; reversion of a single amino acid substitution often restored expression. Mitochondrial apoptosis thus enforces cellular quality control in the GC by limiting the persistence of non-proliferating and expression-defective states while remaining dispensable for affinity maturation.

immunology↗

bioRxiv2026

Asymmetric Boost Responses to an HIV-1 Vaccine: Boost-site Controls Secondary B-cell Fates

Induction of broadly neutralizing antibody (bnAb) responses remains a central challenge to designing efficacious HIV vaccines. Lineage design strategies, in which bnAb precursors are guided via iterative immunizations to their mature forms, depend on high levels of somatic mutation and the recall of antigen-specific B cells. Recent studies have identified spatial context as an important determinant of boosting efficacy, but the application of this to HIV vaccines and the underlying mechanisms are incompletely understood. Here, using mice harboring a V3-glycan bnAb lineage precursor knock-in combined with lineage-tracing and single-cell analyses, we show that persistent germinal centers (GCs) support continued affinity maturation of founder clones and ipsilateral boosting preferentially engages these lineages in secondary GCs. In contrast, contralateral boosting predominantly recruits naive B cells and memory B cells not directed towards the immunizing antigen. The few memory cells recruited at this site were biased towards a plasma cell fate. Finally, we identify disfavored mutational trajectories within the V3-glycan bnAb lineage, revealing intrinsic constraints on bnAb lineage evolution.

immunology↗

bioRxiv2026

Functional Convergence of Genetically Diverse B-Cell Receptors in Simian-HIV Infected Rhesus Macaques

Germline-targeting or lineage-design vaccine strategies are being used to induce HIV broadly neutralizing antibody (bnAb) responses. These strategies assume that genetically diverse individuals respond similarly to the same immunogen by mobilizing comparable germline precursors, although outcomes vary across bnAb epitopes. Here we explored this premise using a simian-HIV infection model in rhesus macaques. Antigen-unbiased Env- reactive B-cell populations were profiled, followed by systematic analysis of antibody function and B-cell receptor (BCR) genetics. We find that while global Env-reactive B-cell response profiles and antibody functional properties are similar across individuals, underlying BCR genetics are diverse, particularly among non-bnAbs. These results indicate that functional convergence of Env-reactive antibody responses does not necessarily require genetic convergence and suggest that specific germline-targeting may not be an absolute prerequisite for successful vaccine design. These findings support an epitope-focused framework in which bnAb epitopes are engineered to enhance population-level immunogenicity, with potential applicability to other challenging pathogens.

immunology↗

bioRxiv2023

Auditory cues modulate the short timescale dynamics of STN activity during stepping in Parkinson's disease

BackgroundGait impairment has a major impact on motor performance and quality of life in patients with Parkinsons disease (PD). The neurophysiological mechanisms of gait impairment remain poorly understood, meaning that treatment options are currently limited. It is believed that basal ganglia oscillatory activity at {beta} frequencies (15-30 Hz) may be a contributor to gait impairment in PD, but the precise dynamics of this oscillatory activity during gait remain unclear. Auditory cues are known to lead to improvements in gait kinematics in PD. If the neurophysiological mechanisms of this cueing effect were better understood they could be leveraged to treat gait impairments using brain-computer interface (BCI) technologies. ObjectiveWe aimed to characterize the dynamics of subthalamic nucleus (STN) oscillatory activity during stepping movements in PD and to establish the neurophysiological mechanisms by which auditory cues modulate gait. MethodsWe used local field potentials (LFPs) to study STN oscillatory activity in eight PD patients while stepping in place with auditory cueing. Hidden Markov Models (HMMs) were used to discover dynamic brain states that occurred pre-sound, on-sound, and post-sound cues. ResultsThe occurrence of {beta} bursts was suppressed during and after auditory cues. This manifested as a decrease in their fractional occupancy and state lifetimes. Interestingly, transients showed the opposite effect, with fractional occupancy and state lifetimes increasing during and after auditory cues. ConclusionsWe found transient oscillatory states in the STN LFP during stepping and showed that and {beta} oscillations are differentially modulated by auditory cues during stepping in PD.

neuroscience↗

bioRxiv2022

Odorant Mixture Separation in Drosophila Early Olfactory System

Natural odorant scenes are complex landscapes comprising mixtures of volatile compounds. It was previously proposed that the Antennal Lobe circuit recovers the odorant identity in a concentration-invariant manner via divisive normalization of Local Neurons. It remains unclear, however, how identities of odorant components in a mixture is represented or recovered in the fruit fly early olfactory pathway. In the current work, we take a different approach from the traditional steady-state analyses that classify odorant mixture encoding into configural vs. elemental schemes. Instead, we focus on the spatio-temporal responses of the early olfactory pathway at the levels of the Antennal Lobe and the Mushroom Body, and formulate the odorant demixing problem as a blind source separation problem - where the identities of each individual odorant component and their corresponding concentration waveforms are recovered from the spatio-temporal PSTH of Olfactory Sensory Neurons (OSNs), Projection Neurons (PNs), and Kenyon Cells (KCs) respectively. Building upon previous models of the Antenna and the Antennal Lobe, we advanced a feedback divisive normalization architecture of the Mushroom Body Calyx circuit comprised of PN, KC and the giant Anterior Paired Lateral (APL) neuron. We demonstrate that the PN-KC-APL circuit produces a high dimensional representation of odorant mixture with robust sparsity, and results in greater odorant demixing performance than the PN responses.

neuroscience↗

bioRxiv2022

Optogenetic Manipulation of Cell Migration with High Spatiotemporal Resolution Using Lattice Lightsheet Microscopy

Lattice lightsheet microscopy (LLSM) is modified with the aim of manipulating cellular behavior with subcellular resolution through three-dimensional (3D) optogenetic activation. In this study, we report a straightforward implementation of the activation source in LLSM in which the stimulating light can be generated by changing the spatial light modulator (SLM) patterns and the annual masks. As a result, a Bessel beam as a stimulation source is integrated into the LLSM without changing the optical configuration, achieving better spatiotemporal control of photoactivation. We show that the energy power required for optogenetic reactions is lower than 1 nW (or 24 mW/cm2), and membrane ruffling can be activated at different locations within a cell with subcellular resolution. We also demonstrate guided cell migration using optogenetic stimulation for up to 6 h, where 463 imaging volumes are collected, without noticeable damage to cells.

cell biology↗

bioRxiv2021

The Functional Logic of Odor Information Processing in the Drosophila Antennal Lobe

The early olfactory system of the fruit fly, while sensing a complex odorant landscape, encodes the odorant object identity (semantic information) and the odorant concentration waveform (syntactic information) into a combinatorial neural code. Single-channel physiology recordings at the output of the Antenna Lobe (AL) exhibit concentration-invariance and contrast-boosting properties, indicating a decoupling of the odorant object identity from the concentration waveform in steady-state while responding strongly to odorant concentration onset and offset in transient states. Through exhaustive computational explorations of the AL circuits, we show that the steady-state and transient response features of the AL are, respectively, due to presynaptic and postsynaptic Local Neurons (LNs). Theoretical analysis reveals that the LN pathways can be modeled as parallel differential Divisive Normalization Processors (DNPs). Differential DNPs robustly extract odorant identity (semantic information) and ON/OFF odorant event-timing (syntactic information), thereby providing for the AL the functional logic of ON-OFF odorant identity recovery.

neuroscience↗

bioRxiv2021

Recall of B cell memory depends on relative locations of prime and boost

Re-entry of memory B cells to recall germinal centers (GCs) is essential for updating their B-cell antigen receptors (BCRs). Using single B-cell culture and fate-mapping, we have characterized BCR repertoires in recall GCs following boost immunizations at sites local or distal to the priming. Local boosts with homologous antigen recruit to recall GCs progeny of primary GC B cells more efficiently than do distal boosts. Recall GCs following local boosts contain significantly more B cells with elevated levels of Ig mutations and higher avidity BCRs. This local preference is unaffected by blockade of CD40:CD154 interaction that terminate active, primary GC responses. Local boosts with heterologous antigens elicit secondary GCs with B-cell populations enriched for cross-reactivity to the priming and boosting antigens; in contrast, cross-reactive GC B cells are rare following distal boosts. Our findings indicate the importance of locality in humoral immunity and inform serial vaccination strategies for evolving viruses. One Sentence SummaryThe participation of memory B cells in recall germinal centers depends on whether the boost is local or distal to the priming site.

immunology↗

bioRxiv2021

White matter microstructural and morphometric alterations in autism: Implications for intellectual and verbal capabilities

BackgroundNeuroimage literature of autism spectrum disorder (ASD) has a moderate-to-high risk of bias, partially because those combined with intellectual impairment (II) and/or minimally verbal (MV) status are generally ignored. We aimed to provide more comprehensive insights into white matter alterations of ASD, inclusive of individuals with II (ASD-II-Only) or MV expression (ASD-MV). MethodsSixty-five participants with ASD (ASD-Whole; 16.6{+/-}5.9 years; comprising 34 intellectually able youth, ASD-IA, and 31 intellectually impaired youth, ASD-II, including 24 ASD-II-Only plus 7 ASD-MV) and 38 demographic-matched typically developing controls (TDC; 17.3{+/-}5.6 years) were scanned in accelerated diffusion-weighted MRI. Fixel-based analysis was undertaken to investigate the categorical differences in fiber density (FD), fiber cross-section (FC), and a combined index (FDC), and brain-symptom/cognition associations. ResultsASD-Whole had reduced FD in the anterior and posterior corpus callosum and left cerebellum Crus I, and smaller FDC in right cerebellum Crus II, compared to TDC. ASD-II, relative to TDC, showed almost identical alterations to those from ASD-Whole vs. TDC. ASD-II-Only had greater FD/FDC in the isthmus-splenium of callosum than ASD-MV. Autistic severity negatively correlated with FC in right Crus I. Non-verbal full-scale IQ positively correlated with FC/FDC in cerebellum VI. FD/FDC of the right dorsolateral prefrontal cortex showed a diagnosis-by-executive function interaction. LimitationsWe could not preclude the potential effects of age and sex from the ASD cohort, although statistical tests suggested that these factors were not influential. Our results could be confounded by variable psychiatric comorbidities and psychotropic medication uses in our ASD participants recruited from outpatient clinics, which is nevertheless closer to a real-world presentation of ASD. The outcomes related to ASD-MV were considered preliminaries due to the small sample size within this subgroup. Finally, our study design did not include intellectual impairment-only participants without ASD to disentangle the mixture of autistic and intellectual symptoms. ConclusionsASD-associated white matter alterations appear driven by individuals with II and potentially further by MV. Results suggest that changes in the corpus callosum and cerebellum are key for psychopathology and cognition associated with ASD. Our work highlights an essential to include understudied sub-populations on the spectrum in research.

neuroscience↗

bioRxiv2020

Neural signatures of pathological hyperdirect pathway activity in Parkinson's disease

Parkinsons disease (PD) is characterised by the emergence of pathological patterns of oscillatory synchronisation across the cortico-basal-ganglia circuit. The relationship between anatomical connectivity and oscillatory synchronisation within this system remains poorly understood. We address this by integrating evidence from invasive electrophysiology, magnetoencephalography, tractography and computational modelling in patients. Coupling between supplementary motor area (SMA) and subthalamic nucleus (STN) within the high beta frequency (21-30 Hz) range correlated with fibre tract densities between these two structures. Additionally within the STN, non-linear waveform features suggestive of cortical synchronisation correlated with cortico-STN fibre densities. Finally, computational modelling revealed that exaggerated hyperdirect cortical inputs to the STN in the upper beta frequency range can provoke the generation of widespread pathological synchrony at lower beta (13-20 Hz) frequencies. These observations reveal a spectral signature of the hyperdirect pathway at high beta frequencies and provide evidence for its pathophysiological role in oscillatory network dysfunction in PD. One sentence summarySignatures of the hyperdirect pathway and its likely role in pathological network disruption in Parkinsons disease are identified.

neuroscience↗

bioRxiv2019

The Fruit Fly Brain Observatory: From Structure to Function

The fruit fly is a key model organism for studying the activity of interconnected brain circuits. A large scattered global research community of neurobiologists and neurogeneticists, computational and theoretical neuroscientists, and computer scientists and engineers has been developing a vast trove of experimental and modeling data that has yet to be distilled into new knowledge and understanding of the functional logic of the brain. Developing open shared models, modelling tools and data repositories that can be accessed from anywhere in the world is the necessary engine for accelerating our understanding of how the brain works.\n\nTo that end we developed the Fruit Fly Brain Observatory (FFBO), the next generation open-source platform to support open, collaborative Drosophila neuroscience research. FFBO provides a (i) hub for storing and integrating fruit fly brain research data from multiple data sources worldwide, (ii) unified repository of tools and methods to build, emulate and compare fruit fly brain models in health and disease, and (iii) an open framework for fruit fly brain data processing and model execution. FFBO provides access to application tools for visualizing, configuring, simulating and analyzing computational models of brain circuits of the (i) cell type map, (ii) connectome, (iii) synaptome, and (iv) activity map using intuitive queries in plain English. Tools are provided to extract the function inherent in these structural maps. All applications can be accessed with any modern browser.

neuroscience↗

bioRxiv2019

MRtrix3: A fast, flexible and open software framework for medical image processing and visualisation

MRtrix3 is an open-source, cross-platform software package for medical image processing, analysis and visualization, with a particular emphasis on the investigation of the brain using diffusion MRI. It is implemented using a fast, modular and flexible general-purpose code framework for image data access and manipulation, enabling efficient development of new applications, whilst retaining high computational performance and a consistent command-line interface between applications. In this article, we provide a high-level overview of the features of the MRtrix3 framework and general-purpose image processing applications provided with the software.

neuroscience↗

bioRxiv2019

Is removal of weak connections necessary for graph-theoretical analysis of dense weighted structural connectomes?

Recent advances in diffusion MRI tractography permit the generation of dense weighted structural connectomes that offer greater insight into brain organization. However, these efforts are hampered by the lack of consensus on how to extract topological measures from the resulting graphs. Here we evaluate the common practice of removing the graphs weak connections, which is primarily intended to eliminate spurious connections and emphasize strong connections. Because this processing step requires arbitrary or heuristic-based choices (e.g., setting a threshold level below which connections are removed), and such choices might complicate statistical analysis and inter-study comparisons, in this work we test whether removing weak connections is indeed necessary. To this end, we systematically evaluated the effect of removing weak connections on a range of popular graph-theoretical metrics. Specifically, we investigated if (and at what extent) removal of weak connections introduces a statistically significant difference between two otherwise equal groups of healthy subjects when only applied to one of the groups. Using data from the Human Connectome Project, we found that removal of weak connections had no statistical effect even when removing the weakest ~70-90% connections. Removing yet a larger extent of weak connections, thus reducing connectivity density even further, did produce a predictably significant effect. However, metric values became sensitive to the exact connectivity density, which has ramifications regarding the stability of the statistical analysis. This pattern persisted whether connections were removed by connection strength threshold or connectivity density, and for connectomes generated using parcellations at different resolutions. Finally, we showed that the same pattern also applies for data from a clinical-grade MRI scanner. In conclusion, our analysis revealed that removing weak connections is not necessary for graph-theoretical analysis of dense weighted connectomes. Because removal of weak connections provides no practical utility to offset the undesirable requirement for arbitrary or heuristic-based choices, we recommend that this step is avoided in future studies. Declarations of interestnone.

neuroscience↗

bioRxiv2017

A Parallel Processing Model of Drosophila Olfactory Sensory Neurons and Its Biological Validation

In the past two decades, a substantial amount of work characterized the odorant receptors, neuroanatomy and odorant response properties of the early olfactory system of Drosophila melanogaster. Yet many odorant receptors remain only partially characterized and, the odorant transduction process and the axon hillock spiking mechanism of the olfactory sensory neurons (OSNs) have yet to be fully determined.\n\nIdentity and concentration, two key aspects of olfactory coding, originate in the odorant transduction process. Detailed molecular models of the odorant transduction process are, however, scarce for fruit flies. To address these challenges we advance a comprehensive model of fruit fly OSNs as a cascade consisting of an odorant transduction process (OTP) and a biophysical spike generator (BSG). We model identity and concentration in OTP using an odorant-receptor binding rate tensor, modulated by the odorant concentration profile, and an odorant-receptor dissociation rate tensor, and quantitatively describe the ligand binding/dissociation process. We model the BSG as a Connor-Stevens point neuron.\n\nThe resulting combinatorial encoding model of the Drosophila antenna provides a theoretical foundation for understanding the neural code of both odorant identity and odorant concentration and advances the state-of-the-art in a number of ways. First, it quantifies on the molecular level the combinatorial complexity of the transformation taking place in the antennae. The concentration-dependent combinatorial code determines the complexity of the input space driving olfactory processing in the downstream neuropils, such as odorant recognition and olfactory associative learning. Second, the model is biologically validated using multiple electrophysiology recordings. Third, the model demonstrates that the currently available data for odorant-receptor responses only enable the estimation of the affinity of the odorant-receptor pairs. The odorant-dissociation rate is only available for a few odorant-receptor pairs. Finally, our model calls for new experiments for massively identifying the odorant-receptor dissociation rates of relevance to flies.

neuroscience↗

bioRxiv2016

The Fruit Fly Brain Observatory: from structure to function

The Fruit Fly Brain Observatory (FFBO) is a collaborative effort between experimentalists, theorists and computational neuroscientists at Columbia University, National Tsing Hua University and Sheffield University with the goal to (i) create an open platform for the emulation and biological validation of fruit fly brain models in health and disease, (ii) standardize tools and methods for graphical rendering, representation and manipulation of brain circuits, (iii) standardize tools for representation of fruit fly brain data and its abstractions and support for natural language queries, (iv) create a focus for the neuroscience community with interests in the fruit fly brain and encourage the sharing of fruit fly brain structural data and executable code worldwide. NeuroNLP and NeuroGFX, two key FFBO applications, aim to address two major challenges, respectively: i) seamlessly integrate structural and genetic data from multiple sources that can be intuitively queried, effectively visualized and extensively manipulated, ii) devise executable brain circuit models anchored in structural data for understanding and developing novel hypotheses about brain function. NeuroNLP enables researchers to use plain English (or other languages) to probe biological data that are integrated into a novel database system, called NeuroArch, that we developed for integrating biological and abstract data models of the fruit fly brain. With powerful 3D graphical visualization, NeuroNLP presents a highly accessible portal for the fruit fly brain data. NeuroGFX provides users highly intuitive tools to execute neural circuit models with Neurokernel, an open-source platform for emulating the fruit fly brain, with full data support from the NeuroArch database and visualization support from an interactive graphical interface. Brain circuits can be configured with high flexibility and investigated on multiple levels, e.g., whole brain, neuropil, and local circuit levels. The FFBO is publicly available and accessible at http://fruitflybrain.org from any modern web browsers, including those running on smartphones.

neuroscience↗

bioRxiv2016

NeuroNLP: a natural language portal for aggregated fruit fly brain data

NeuroNLP, is a key application on the Fruit Fly Brain Observatory platform (FFBO, http://fruitflybrain.org), that provides a modern web-based portal for navigating fruit fly brain circuit data. Increases in the availability and scale of fruit fly connectome data, demand new, scalable and accessible methods to facilitate investigation into the functions of the latest complex circuits being uncovered. NeuroNLP enables in-depth exploration and investigation of the structure of brain circuits, using intuitive natural language queries that are capable of revealing the latent structure and information, obscured due to expansive yet independent data sources. NeuroNLP is built on top of a database system call NeuroArch that codifies knowledge about the fruit fly brain circuits, spanning multiple sources. Users can probe biological circuits in the NeuroArch database with plain English queries, such as \"show glutamatergic local neurons in the left antennal lobe\" and \"show neurons with dendrites in the left mushroom body and axons in the fan-shaped body\". This simple yet powerful interface replaces the usual, cumbersome checkboxes and dropdown menus prevalent in todays neurobiological databases. Equipped with powerful 3D visualization, NeuroNLP standardizes tools and methods for graphical rendering, representation, and manipulation of brain circuits, while integrating with existing databases such as the FlyCircuit. The userfriendly graphical user interface complements the natural language queries with additional controls for exploring the connectivity of neurons and neural circuits. Designed with an open-source, modular structure, it is highly scalable/flexible/extensible to additional databases or to switch between databases and supports the creation of additional parsers for other languages. By supporting access through a web browser from any modern laptop or smartphone, NeuroNLP significantly increases the accessibility of fruit fly brain data and improves the impact of the data in both scientific and educational exploration.

neuroscience↗

bioRxiv2016

NeuroGFX: a graphical functional explorer for fruit fly brain circuits

Recently, multiple focused efforts have resulted in substantial increase in the availability of connectome data in the fruit fly brain. Elucidating neural circuit function from such structural data calls for a scalable computational modeling methodology. We propose such a methodology that includes i) a brain emulation engine, with an architecture that can tackle the complexity of whole brain modeling, ii) a database that supports tight integration of biological and modeling data along with support for domain specific queries and circuit transformations, and iii) a graphical interface that allows for total flexibility in configuring neural circuits and visualizing run-time results, both anchored on model abstractions closely reflecting biological structure. Towards the realization of such a methodology, we have developed NeuroGFX and integrated it into the architecture of the Fruit Fly Brain Observatory (http://fruitflybrain.org). The computational infrastructure in NeuroGFX is provided by Neurokernel, an open source platform for the emulation of the fruit fly brain, and NeuroArch, a database for querying and executing fruit fly brain circuits. The integration of the two enables the algorithmic construction/manipulation/revision of executable circuits on multiple levels of abstraction of the same model organism. The power of this computational infrastructure can be leveraged through an intuitive graphical interface that allows visualizing execution results in the context of biological structure. This provides an environment where computational researchers can present configurable, executable neural circuits, and experimental scientists can easily explore circuit structure and function ultimately leading to biological validation. With these capabilities, NeuroGFX enables the exploration of function from circuit structure at whole brain, neuropil, and local circuit level of abstraction. By allowing for independently developed models to be integrated at the architectural level, NeuroGFX provides an open plug and play, collaborative environment for whole brain computational modeling of the fruit fly.

neuroscience↗