Biology subjects

Thompson, J. A.

Publications and source records attributed to Thompson, J. A..

14 recordsLinked to original sources

bioRxiv2026

Stable Network Motifs with Divergent Engagement Across Memory Outcomes

Visual recognition memory depends on coordinated interactions across distributed medial temporal, prefrontal, and limbic networks, yet the sub-second large-scale network dynamics distinguishing successful from unsuccessful recognition remain poorly understood. Here we used intracranial EEG recordings from seven patients (4 female, 3 male) with medically refractory epilepsy performing a new-old visual recognition memory task to characterize time-resolved directed functional connectivity and dynamic network organization. Directed effective connectivity was estimated using bivariate Granger causality in a sliding-window framework, and dynamic community structure was identified using the Louvain modularity algorithm. Successful recognition (Hits) was associated with a qualitatively distinct network configuration: low modularity (Q = 0.05 vs. 0.09-0.15 in other conditions), a cross-hemispheric community structure integrating left medial temporal lobe (MTL) with right prefrontal cortex, and sustained network integration throughout the post-stimulus period. Right-hemisphere nodes within this cross-hemispheric community showed stronger within-community directed connectivity than left-hemisphere nodes (mean asymmetry index = 0.33, p < 0.001), consistent with right prefrontal dominance in driving network integration during successful retrieval. In contrast, Correct Rejections were characterized by early transient network segregation (onset 32 ms) dominated by right-hemisphere activity. Hub regions were non-overlapping across conditions--left-lateralized during Hits, right-lateralized during Correct Rejections. These findings imply that successful visual recognition is distinguished not by stronger connectivity per se, but by a reorganization of large-scale network topology that transiently integrates left MTL with right prefrontal cortex into a unified functional community.

neuroscience↗

bioRxiv2026

Genuinely Blind Identification of Sleep Spindles through Trispectral Modulation Analysis

Sleep spindles, transient 11-16 Hz oscillatory bursts, are a defining electrographic feature of non-rem (NREM) sleep and a key biomarker of sleep physiology. A need for efficient and reliable identification of spindles motivates a large literature on automated detection algorithms. In this literature, annotation by trained sleep specialists remains the gold standard against which automated methods are trained, tuned and evaluated. However, inter-scorer agreement among experts is modest, which leaves a significant role for subjective judgment in the definition of a spindle. Finding objective, scorer-independent, criteria for identifying spindles remains an unresolved challenge. We report here a robust, highly specific, and previously unrecognized signature of spindle activity in the fourth-order spectrum (trispectrum), from which we identify the presence of spindles, characterize their waveforms, and obtain an optimal detection filter through a decomposition of the trispectrum (HOSD). Although it is a strictly blind, data-driven method, HOSD-based spindle identification and detection agrees well with expert annotation (median AUROC ~0.9), yet identifies many more events at the native threshold than both human scorers and comparison detectors. Many of these additional detections are confirmed as meeting AASM spindle criteria by four blinded specialists, demonstrating that spindle-like oscillatory bursting is prevalent below conventional human and automated detection thresholds. We observe that N2 sleep is distinguished principally by high-amplitude bursts, while low-amplitude bursting persists throughout NREM sleep, being globally suppressed only in REM sleep. We also describe robust identification of recording-specific spindle waveform properties such as frequency deceleration.

neuroscience↗

bioRxiv2025

Order-Selective Cells Tile Temporal Space and Predict Order Memory in Humans

Remembering the temporal order of events is critical for episodic memory, allowing us to link individual events into sequences. While the medial temporal lobe and prefrontal cortex are essential for this process, the underlying neural mechanisms remain poorly understood. Here we characterized the representation of order information at the level of single neurons and field potentials recorded from human neurosurgical patients watching naturalistic videos of everyday events and later recalling the order and content of the events depicted. We found order-selective cells (OSCs) in the human hippocampus, amygdala, and orbitofrontal cortex that responded selectively to specific event orders, independent of event content or absolute time. OSCs exhibited transient theta phase precession following their preferred order during both memory encoding and retrieval, the strength of which predicted participants order memory accuracy. During retrieval, OSC spike timing relative to theta varied with the relative position of their preferred event within the recalled event sequence, enabling selective retrieval of relevant events. These findings reveal a neural substrate for representing, encoding into and retrieving from memory absolute and relative ordinal relationships between discrete events. OSCs tile temporal space into discrete ordinal positions, thereby weaving episodic experiences into coherent temporal narratives.

neuroscience↗

bioRxiv2024

Element partitioning, element localisation and transcriptome responses of date palms exposed to NaCl

Date palm (Phoenix dactylifera L.) is an economically important fruit crop in many (semi)arid regions. Large intra-species variation in susceptibility to NaCl has been reported. Controlled experiments were conducted to evaluate sodium (Na) and chlorine (Cl) partitioning in two-year old plants of six date palm varieties and to determine tissue location of Na and Cl and transcriptome responses to NaCl of two varieties. The largest Na concentrations were found in secondary roots, especially under NaCl treatment. By contrast, only small differences in within-plant partitioning of Cl were observed with less differences between varieties than for Na. Variety Sultana had the largest Na translocation factor. The variety Khalas exhibited better restriction of Na mobility, which may be a consequence of Na hotspots in roots, presumably immobilising Na in roots, which were absent in Sultana. In the root, shoot base and lower part of leaves, Cl accumulated in fibre bands and sclerenchyma sheaths of vascular bundles. RNAseq analysis revealed that Sultana and Khalas respond very differently to NaCl: Khalas modified expression of NaCl-specific genes in both roots and leaves, while Sultana responded manly in leaves. Gene ontology analysis showed that the expression changes for genes linked with photosynthesis and carbohydrate metabolism predominated as a response to NaCl. In Khalas, differentially expressed genes encoding for metal transporters and those reported to be involved in heat, salt and osmotic stress response were found. Large variability in Na and Cl accumulation in different date palm varieties may have practical agronomical consequences.

plant biology↗

bioRxiv2022

Microglial STAT1-sufficiency is required for resistance to toxoplasmic encephalitis

Toxoplasma gondii is a ubiquitous intracellular protozoan parasite that establishes a life-long chronic infection largely restricted to the central nervous system (CNS). Constant immune pressure, notably IFN-{gamma}-STAT1 signaling, is required for preventing fatal pathology during T. gondii infection. Here, we report that abrogation of STAT1 signaling in microglia, the resident immune cells of the CNS, is sufficient to induce a loss of parasite control in the CNS and susceptibility to toxoplasmic encephalitis during the early stages of chronic infection. Using a microglia-specific genetic labeling and targeting system that discriminates microglia from blood-derived myeloid cells that infiltrate the brain during infection, we find that, contrary to previous in vitro reports, microglia do not express inducible nitric-oxide synthase (iNOS) during T. gondii infection in vivo. Instead, transcriptomic analyses of microglia reveal that STAT1 regulates both (i) a transcriptional shift from homeostatic to "disease-associated microglia" (DAM) phenotype conserved across several neuroinflammatory models, including T. gondii infection, and (ii) the expression of anti-parasitic cytosolic molecules that are required for eliminating T. gondii in a cell-intrinsic manner. Further, genetic deletion of Stat1 from microglia during T. gondii challenge leads to fatal pathology despite largely equivalent or enhanced immune effector functions displayed by brain-infiltrating immune populations. Finally, we show that microglial STAT1-deficiency results in the overrepresentation of the highly replicative, lytic tachyzoite form of T. gondii, relative to its quiescent, semi-dormant bradyzoite form typical of chronic CNS infection. Our data suggest an overall protective role of CNS-resident microglia against T. gondii infection, illuminating (i) general mechanisms of CNS-specific immunity to infection (ii) and a clear role for IFN-STAT1 signaling in regulating a microglial activation phenotype observed across diverse neuroinflammatory disease states.

immunology↗

bioRxiv2021

Differential and synergistic effects of low birth weight and Western diet on skeletal muscle vasculature, mitochondrial lipid metabolism and insulin signaling in male guinea pigs

Low birth weight (LBW) offspring are at increased risk for developing insulin resistance, a key precursor in metabolic syndrome and type 2 diabetes mellitus. Altered skeletal muscle vasculature, extracellular matrix, amino acid and mitochondrial lipid metabolism, and insulin signaling are implicated in this pathogenesis. Using uteroplacental insufficiency (UPI) to induce intrauterine growth restriction (IUGR) and LBW in the guinea pig, we investigated the relationship between UPI-induced IUGR/LBW and later life skeletal muscle arteriole density, fibrosis, amino acid and mitochondrial lipid metabolism, markers of insulin signaling and glucose uptake, and how a postnatal high-fat, high-sugar "Western" diet (WD) modulates these changes. Muscle of 145-day-old male LBW glucose tolerant offspring displayed diminished vessel density and altered acylcarnitine levels. Disrupted muscle insulin signaling despite maintained whole-body glucose homeostasis also occurred in both LBW and WD-fed male lean offspring. Additionally, postnatal WD unmasked LBW-induced impairment of mitochondrial lipid metabolism as reflected by increased acylcarnitine accumulation. This study provides evidence that early markers of skeletal muscle metabolic dysfunction appear to be influenced by the in utero environment and interact with a high fat-sugar postnatal environment to exacerbate altered mitochondrial lipid metabolism promoting mitochondrial overload.

physiology↗

bioRxiv2021

Glycan-Based Shaping Of The Microbiota During Primate Evolution

Genes encoding certain glycosyltransferases are thought to be under relatively high selection pressure, due to the involvement of the glycans that they synthesize in host-microbe interactions. Here we used a mouse model to investigate whether the loss of -1,3-galactosyltransferase (GGTA1) function and Gal1-3Gal{beta}1-4GlcNAc{beta}1-R (Gal) expression during primate evolution might have affected host-microbiota interactions. We found that Ggta1 deletion in mice shaped the composition of the gut microbiota in relation to the bacterial species present. This occurred via an immunoglobulin (Ig)-dependent mechanism, associated with IgA targeting of Gal-expressing bacteria. Systemic infection by the Ig-shaped microbiota elicited a less severe form of sepsis than infection with the non-Ig-shaped microbiota. This suggests that in the absence of host Gal, the microbiota is shaped towards lower pathogenicity, likely providing a fitness gain to the host. We infer that high selection pressure exerted by bacterial sepsis may have contributed to increase frequency of GGTA1 loss-of-function mutations in ancestral primates that gave rise to humans.

evolutionary biology↗

bioRxiv2021

Training neural networks to recognize speech increased their correspondence to the human auditory pathway but did not yield a shared hierarchy of acoustic features

The correspondence between the activity of artificial neurons in convolutional neural networks (CNNs) trained to recognize objects in images and neural activity collected throughout the primate visual system has been well documented. Shallower layers of CNNs are typically more similar to early visual areas and deeper layers tend to be more similar to later visual areas, providing evidence for a shared representational hierarchy. This phenomenon has not been thoroughly studied in the auditory domain. Here, we compared the representations of CNNs trained to recognize speech (triphone recognition) to 7-Tesla fMRI activity collected throughout the human auditory pathway, including subcortical and cortical regions, while participants listened to speech. We found no evidence for a shared representational hierarchy of acoustic speech features. Instead, all auditory regions of interest were most similar to a single layer of the CNNs: the first fully-connected layer. This layer sits at the boundary between the relatively task-general intermediate layers and the highly task-specific final layers. This suggests that alternative architectural designs and/or training objectives may be needed to achieve fine-grained layer-wise correspondence with the human auditory pathway. HighlightsO_LITrained CNNs more similar to auditory fMRI activity than untrained C_LIO_LINo evidence of a shared representational hierarchy for acoustic features C_LIO_LIAll ROIs were most similar to the first fully-connected layer C_LIO_LICNN performance on speech recognition task positively associated with fmri similarity C_LI

neuroscience↗

bioRxiv2020

Disrupted basal ganglia output during movement preparation in hemi-parkinsonian mice accounts for behavioral deficits

Parkinsonian motor deficits are associated with elevated inhibitory output from the basal ganglia (BG). However, several features of Parkinsons disease (PD) have not been accounted for by this simple "rate model" framework, including the observation in PD patients that movements guided by external stimuli are less impaired than otherwise-identical movements generated based on internal goals. Is this difference in impairment due to divergent processing within the BG itself, or to the recruitment of extra-BG pathways by sensory processing? In addition, surprisingly little is known about precisely when, in the sequence from selecting to executing movements, BG output is altered by PD. Here, we address these questions by recording activity in the SNr, a key BG output nucleus, in hemiparkinsonian (hemi-PD) mice performing a well-controlled behavioral task requiring stimulus-guided and internally-specified directional movements. We found that hemi-PD mice exhibited a bias ipsilateral to the side of dopaminergic cell loss that was stronger when movements were internally specified rather than stimulus guided, consistent with clinical observations in parkinsonian patients. We further found that changes in parkinsonian SNr activity during movement preparation could account for the ipsilateral behavioral bias, as well as its greater magnitude for internally-specified movements, consistent with some aspects of the rate model. These results suggest that parkinsonian changes in BG output underlying movement preparation contribute to the greater deficit in internally-specified than stimulus-guided movements.

neuroscience↗

bioRxiv2020

Gasdermin-D-dependent IL-1α release from microglia promotes protective immunity during chronic Toxoplasma gondii infection

Microglia, the resident immune cells of the brain parenchyma, are thought to be first-line defenders against CNS infections. We sought to identify specific roles of microglia in the control of the eukaryotic parasite Toxoplasma gondii, an opportunistic infection that can cause severe neurological disease. In order to identify the specific function of microglia in the brain during infection, we sorted microglia and infiltrating myeloid cells from infected microglia reporter mice. Using RNA-sequencing, we find strong NF-{kappa}B and inflammatory cytokine signatures overrepresented in blood-derived macrophages versus microglia. Interestingly, we also find that IL-1 is enriched in microglia and IL-1{beta} in macrophages, which was also evident at the protein level. We find that mice lacking IL-1R1 or IL-1, but not IL-1{beta}, have impaired parasite control and immune cell infiltration specifically within the brain. Further, by sorting purified populations from infected brains, we show that microglia, not peripheral myeloid cells, release IL-1 ex vivo. Finally, using knockout mice as well as chemical inhibition, we show that ex vivo IL-1 release is gasdermin-D dependent, and that gasdermin-D and caspase-1/11 deficient mice show deficits in immune infiltration into the brain and parasite control. These results demonstrate that microglia and macrophages are differently equipped to propagate inflammation, and that in chronic T. gondii infection, microglia specifically can release the alarmin IL-1, a cytokine that promotes neuroinflammation and parasite control.

immunology↗

bioRxiv2019

Equivalent Change Enrichment Analysis: Assessing Equivalent and Inverse Change in Genes and Biological Pathways between Diverse Experiments

In silico functional genomics have become a driving force in the way we interpret and use gene expression data, enabling researchers to understand which biological pathways are likely to be affected by the treatments or conditions being studied. There are many approaches to functional genomics, but a number of popular methods determine if a set of modified genes has a higher than expected overlap with genes known to function as part of a pathway (functional enrichment testing). Recently, researchers have started to apply such analyses in a new way: to ask if the data they are collecting show similar disruptions to biological functions compared to reference data. Examples include studying whether similar pathways are perturbed in smokers vs. users of e-cigarettes, or whether a new mouse model of schizophrenia is justified, based on its similarity in cytokine expression to a previously published model. However, there is a dearth of robust statistical methods for testing hypotheses related to these questions and most researchers resort to ad hoc approaches. In this work, we propose a statistical approach to answering such questions. First, we propose a statistic for measuring the degree of equivalent change in individual genes across different treatments. Using this statistic, we propose applying gene set enrichment analysis to identify pathways enriched in genes that are affected in similar or opposing ways across treatments. We evaluate this approach in comparison to ad hoc methods on a simulated dataset, as well as two biological datasets and show that it provides robust results.

bioinformatics↗

bioRxiv2019

A Bayesian framework for identifying consistent patterns of microbial abundance between body sites

Recent studies have found that the microbiome in both gut and mouth are associated with diseases of the gut, including cancer. If resident microbes could be found to exhibit consistent patterns between the mouth and gut, disease status could potentially be assessed non-invasively through profiling of oral samples. Currently, there exists no generally applicable method to test for such associations. Here we present a Bayesian framework to identify microbes that exhibit consistent patterns between body sites, with respect to a phenotypic variable. For a given operational taxonomic unit (OTU), a Bayesian regression model is used to obtain Markov-Chain Monte Carlo estimates of abundance among strata, calculate a correlation statistic, and conduct a formal test based on its posterior distribution. Extensive simulation studies demonstrate overall viability of the approach, and provide information on what factors affect its performance. Applying our method to a dataset containing oral and gut microbiome samples from 77 pancreatic cancer patients revealed several OTUs exhibiting consistent patterns between gut and mouth with respect to disease subtype. Our method is well powered for modest sample sizes and moderate strength of association and can be flexibly extended to other research settings using any currently established Bayesian analysis programs.

microbiology↗

bioRxiv2018

The damage signal IL-33 promotes a focal protective myeloid cell response to Toxoplasma gondii in the brain

Understanding how invading pathogens are sensed within the brain is necessary to uncover how effective immune response are mounted in immunoprivileged sites. The eukaryotic parasite Toxoplasma gondii colonizes the brain of its hosts and initiates robust immune cell recruitment, but little is known about innate recognition of T. gondii within brain tissue. The host damage signal IL-33 is one protein that has been implicated in control of chronic T. gondii infection, but the specific impact of IL-33 signaling within the brain is unclear. Here, we show that IL-33 is expressed by oligodendrocytes and astrocytes during T. gondii infection, is released into the cerebrospinal fluid of T. gondii-infected animals, and is required for control of infection. IL-33 signaling promotes chemokine expression within brain tissue and is required for the recruitment of peripheral anti-parasitic immune cells, including IFN-{gamma}-expressing T cells and iNOS-expressing monocytes. Importantly, we find that the beneficial effects of IL-33 during chronic infection are not a result of signaling on infiltrating immune cells, but rather on radio-resistant responders, and specifically, astrocytes. Mice with IL-33R-deficient astrocytes fail to promote an adaptive immune response in the CNS and control parasite burden, demonstrating that astrocytes can directly respond to IL-33 in vivo. Together, these results indicate a brain-specific mechanism by which IL-33 is released and sensed locally, to engage the peripheral immune system in controlling a neurotropic pathogen.

immunology↗

bioRxiv2017

Methylation-To-Expression Feature Models of Breast Cancer Accurately Predict Overall Survival, Distant-Recurrence Free Survival, And Pathologic Complete Response in Multiple Cohorts

BackgroundApproaches that capitalize on the benefits of multi-omic data integration in invasive breast carcinoma to define prognostic biomarkers for precision medicine have been slow to emerge. In this work, we examined the efficacy of our methylation-to-expression feature model (M2EFM) approach to combining molecular and clinical predictors as part of a single analysis to create prognostic risk scores for overall survival, distant metastasis, and chemosensitivity.\n\nMethodsGene expression and DNA methylation values as well as clinical variables were integrated via M2EFM to build prognostic models of overall survival using 1028 breast tumor samples and further applied to external validation cohorts of 61 and 327 samples. Data-integrated prognostic models of distant recurrence-free survival and pathologic complete response were built using 306 samples and validated on 182 samples of external validation data. Additionally, we compared the discrimination and calibration of M2EFM models to other approaches.\n\nResultsDespite different populations and assays, M2EFM models validated with good accuracy (C-index or AUC [≥] .7) for all outcomes in all validation data. M2EFM models had the most consistent performance overall and superior calibration, suggesting a greater likelihood of clinical utility. Finally, we demonstrated that M2EFM identifies functionally relevant genes, which could be useful in translating an M2EFM biomarker to the clinic.\n\nConclusionM2EFM uses multiple levels of genomic data to infer disrupted regulatory patterns, thus providing a gene signature that connects loss of regulatory control with cancer prognosis.\n\nFundingThe analyses described in this report were supported by NIH grants R01ES022222, P30CA138292, P30ES019776, and R01DE022772.\n\nConflicts of InterestThe authors declare no potential conflicts of interest.

bioinformatics↗