Biology subjects

Muthuraman, M.

Publications and source records attributed to Muthuraman, M..

9 recordsLinked to original sources

bioRxiv2026

Probabilistic mouse-human brain correspondence by multimodal optimal transport

The mouse is the principal model for brain mechanism and disease, allowing experiments that cannot be performed in humans. However, findings often translate poorly because homologous regions differ in relative size and some human territories have no clear mouse counterpart. Here we present OTTER, which learns mouse-human brain correspondence as a probabilistic, parcel-resolution coupling using multimodal fused Gromov-Wasserstein optimal transport, integrating functional and structural connectivity with spatial position and curated homologies. OTTER recovers established homologues on a transcriptomic benchmark and preserves broad cross-species organisation along the cortical areal hierarchy. Applying the coupling to human functional connectivity reveals a graded decline in mouse-based reconstruction across evolutionarily expanded association cortex, with the lowest values in lateral prefrontal territory. Finally, the bidirectional map generates testable human predictions from mouse experiments and ranks mouse circuits corresponding to human clinical targets.

neuroscience↗

bioRxiv2025

Spinal electrophysiology reveals frequency-specific spatial patterns of neural activity and corticospinal coherence during pincer-grip

BackgroundNeural dynamics within sensory-motor networks involved in motor control exhibit well-established frequency-dependent patterns of cortical activity. In contrast, corresponding neural patterns of spinal cord activity remain poorly understood. As an active functional part of motor control, characterising spinal cord activity is essential for understanding sensorimotor function. High-density electrospinography presents a novel technique to assess spinal neural dynamics by non-invasively recording task-relevant electrical activity. ObjectiveTo non-invasively investigate spatio-spectral patterns of task-related spinal activity and its functional connectivity with cortical regions during isometric pincer-grip contraction. MethodologyHere, we simultaneously recorded 128-channel electroencephalography (EEG), 64-channel electrospinography (ESG), and two bipolar electromyography (EMG) signals during an isometric pincer-grip task. Frequency-specific spatial patterns of spinal activity and cortico-spinal connectivity were evaluated by calculating task-related ESG power and cortico-spinal coherence between ESG and EEG signals during the isometric hold. ResultsDistinct frequency-specific spatial patterns of spinal activity were observed at lower cervical levels during sustained hold, with significant activation over the ipsilateral anterolateral region. In the beta band, task-related spinal activity was significantly ipsilateralised, and exhibited significant cortico-spinal connectivity between contralateral motor cortex and ipsi-anterolateral spinal region. ConclusionsThis first-of-its-kind application of HD non-invasive spinal electrophysiology revealed that the spinal cord exhibits distinct frequency-specific spatial activation and cortical connectivity patterns during pincer-grip sustained hold. Specifically, the ipsi-anterolateral spinal region demonstrated high task-relevance, potentially indicating anterior horn activity and its connectivity with motor cortex. Furthermore, beta-band activation was observed as a key signature during sustained hold, further underpinning its relevance during motor control.

neuroscience↗

bioRxiv2024

SC10X/U: A High-density Electrode System for Non-Invasive Recording of Neural Activity of the Cervical Spinal Cord

ObjectiveTo design and develop a high-density (HD) electrode system that describes the position of surface electrodes for recording electrophysiological signals from the human cervical spinal cord. The system is intended to standardize experimental recordings and facilitate the subsequent analysis of evoked and spontaneous spinal cord neural activity, using high-density electrospinography (HD-ESG). MethodThe proposed system (SC10-X/U) describes the locations of up to 76 channels with a unique nomenclature, where the division of the spinal cord (SC) electrode space was inspired by the EEG 10-10 system. As proof of concept, spinal evoked potentials in response to median nerve stimulation at the wrist were recorded from 10 participants and characterized based on a 64-channel derivation from the SC10-X/U system. ResultsFollowing the design criteria, the SC10-X/U defines 76 electrode positions and its configuration. HD-ESG system was utilized to successfully record evoked spinal responses and significant N13 and P9 potential were observed in response to the stimulation. The spinal N13 potential had a latency of 13.2 +-1.1ms (mean +-SD) after stimulation. A topographic map of the N13 electro-spinal activity using the 64-channel recording system revealed an epicentre at C5-C7 dorsal-vertebral locations (ML4 - ML6 electrodes). ConclusionThe proposed SC10-X/U system will facilitate standardized recording and analysis of high-density ESG signals from the human cervical spinal cord. The system defines electrode locations to promote standardization across different individuals, studies, and clinical and research centres. The HD-ESG evoked potentials recorded using the proposed system were comparable to those observed in previous non-HD studies. The presented topographic maps conform to known neurophysiological and neuroanatomical findings. This served to validate the design and development of the electrode system and patch for future studies.

neuroscience↗

bioRxiv2022

The aperiodic exponent of subthalamic field potentials reflects excitation/inhibition balance in Parkinsonism: a cross-species study in vivo

AO_SCPLOWBSTRACTC_SCPLOWPeriodic features of neural time series data, such as local field potentials (LFP), are often quantified using power spectra. While the aperiodic exponent of spectra is typically disregarded, it is nevertheless modulated in a physiologically-relevant manner and was recently hypothesised to reflect excitation/inhibition (E/I) balance in neuronal populations. Here, we used a cross-species in vivo electrophysiological approach to test the E/I hypothesis in the context of experimental and idiopathic Parkinsonism. We demonstrate in dopamine-depleted rats that aperiodic exponents and power at 30-100 Hz in subthalamic nucleus (STN) LFPs reflect defined changes in basal ganglia network activity; higher aperiodic exponents tally with lower levels of STN neuron firing and a balance tipped towards inhibition. Using STN-LFPs recorded from awake Parkinsons patients, we show that higher exponents accompany dopaminergic medication and deep brain stimulation (DBS) of STN, consistent with untreated Parkinsons manifesting as reduced inhibition and hyperactivity of STN. These results suggest that the aperiodic exponent of STN-LFPs in Parkinsonism reflects E/I balance, and might be a candidate biomarker for adaptive DBS.

neuroscience↗

bioRxiv2022

Neural underpinnings of action adaptation in the subthalamic nucleus.

Adapting our actions to changing goals and environments is central to intelligent behavior. There is substantial evidence that the basal ganglia play a crucial role in reinforcing actions that have led to favorable outcomes. However, little is known about the neural mechanisms underlying action adaptation following unfavorable outcomes when change is warranted. Here, we recorded electrophysiological activity and applied bursts of electrical stimulation to the subthalamic nucleus (STN), a core area of the basal ganglia, in patients with Parkinsons disease using deep brain stimulation electrodes. During a task where patients continuously had to adapt their force depending on changing action-value associations, decreases in STN beta (13-30 Hz) activity in two critical time windows were associated with poorer outcomes and stronger action adaptation. STN stimulation reduced beta activity and led to stronger action adaptation if applied within the time windows when STN activity reflected action evaluation and adaptation. These results suggest that dynamic modulation of STN activity facilitates adaptive behavior.

neuroscience↗

bioRxiv2019

Non-Parametric Rank Statistics for Spectral Power and Coherence

Despite advances in multivariate spectral analysis of neural signals, the statistical inference of measures such as spectral power and coherence in practical and real-life scenarios remains a challenge. The non-normal distribution of the neural signals and presence of artefactual components make it difficult to use the parametric methods for robust estimation of measures or to infer the presence of specific spectral components above the chance level. Furthermore, the bias of the coherence measures and their complex statistical distributions are impediments in robust statistical comparisons between 2 different levels of coherence. Non-parametric methods based on the median of auto-/cross-spectra have shown promise for robust estimation of spectral power and coherence estimates. However, the statistical inference based on these non-parametric estimates remain to be formulated and tested. In this report a set of methods based on non-parametric rank statistics for 1-sample and 2-sample testing of spectral power and coherence is provided. The proposed methods were demonstrated and tested using simulated neural signals in different conditions. The results show that non-parametric methods provide robustness against artefactual components. Moreover, they provide new possibilities for robust 1-sample and 2-sample testing of the complex coherency function, including both the magnitude and phase, where existing methods fall short of functionality. The utility of the methods were further demonstrated by examples on experimental neural data. The proposed approach provides a new framework for non-parametric spectral analysis of digital signals. These methods are especially suited to neuroscience and neural engineering applications, given the attractive properties such as minimal assumption on distributions, statistical robustness, and the diverse testing scenarios afforded.

bioinformatics↗

bioRxiv2019

Community driven dynamics of oscillatory network responses to threat

Physiological responses to threat stimuli involve neural synchronized oscillations in cerebral networks with distinct organization properties. Community architecture within these networks and its dynamic adaptation could play a critical role in achieving optimal physiological responses.\n\nHere we applied dynamic network analyses to address the early phases of threat processing at the millisecond level, describing multi-frequency (theta and alpha) integration and basic reorganization properties (flexibility and clustering) that drive physiological responses. We quantified cortical and subcortical network interactions and captured illustrative reconfigurations using community allegiance as essential fingerprints of large-scale adaptation.\n\nA theta band driven community reorganization of key anatomical regions forming the threat network (TN) along with transitions of nodes from the dorsal attention (DAN) and salience (SN) circuits predict the optimal physiological response to threat. We show that increase flexibility of the community network architecture drives the physiological responses during instructed threat processing. Nodal switches modulate the directionality of information flows in the involved circuits.\n\nThese results provide a captivating perspective of flexible network responses to threat and shed new light on basic physiological principles relevant for the development of stress- and threat-related mental disorders.

neuroscience↗

bioRxiv2018

Cortical network fingerprints predict deep brain stimulation outcome in dystonia

BackgroundDeep brain stimulation (DBS) is an effective evidence-based therapy for dystonia. However, no unequivocal predictors of therapy responses exist. We investigate whether patients optimally responding to DBS present distinct brain network organization and structural patterns.\n\nMethodsBased on a German multicentre cohort of eighty-two dystonia patients with segmental and generalized dystonia, who received DBS implantation in the globus pallidus internus patients were classified based on the clinical response 36 months after DBS, as superior-outcome group or moderate-outcome group, as above or below 70% motor improvement, respectively. Fifty-one patients met MRI-quality and treatment response requirements (mean age 51.3 {+/-} 13.2 years; 25 female) and were included into further analysis. From preoperative MRI we assessed cortical thickness and structural covariance, which were then fed into network analysis using graph theory. We designed a support vector machine to classify subjects for the clinical response based on group network properties and individual grey matter fingerprints.\n\nResultsThe moderate-outcome group showed cortical atrophy mainly in the sensorimotor and visuomotor areas and disturbed network topology in these regions. From all the structural integrity of the cortical mantle explained about 45% of the stimulation amplitude. Classification analyses achieved 88% of accuracy using individual grey matter atrophy patterns to predict DBS outcome.\n\nConclusionsThe analysis of cortical integrity and network properties could be developed into independent predictors to identify dystonia patients who benefit from DBS.

neuroscience↗

bioRxiv2018

Excitability regulation in the dorsomedial prefrontal cortex during sustained instructed fear responses: a TMS-EEG study

BackgroundThreat detection is essential for protecting individuals from precarious situations. Early studies suggested a network of amygdala, limbic regions and dorsomedial prefrontal cortex (dmPFC) involved in fear processing. Excitability regulation in the dmPFC might be crucial for physiological fear processing, while an abnormal excitability pattern could lead to mental illness. Non-invasive paradigms to measure excitability regulation during fear processing in humans are missing.\n\nMethodsWe adapted an experimental approach of excitability characterization using electroencephalography (EEG) recordings and transcranial magnetic stimulation (TMS) over the dmPFC during an instructed fear paradigm to dynamically dissect its role in fear processing. Event-related (ERP) and TMS-evoked potentials (TEP) were analyzed to trace dmPFC excitability in healthy young volunteers (n = 40, age = 27.6 {+/-} 5.7 years, 22 females). Moreover, we linked the excitability regulation patterns to individual structural MRI-derived properties of gray matter microstructural integrity of the fear network.\n\nResultsAn increased cortical excitability was demonstrated in the threat (T) condition in comparison to no-threat (NT) as showed by increased amplitude of evoked potentials. Furthermore, TMS over the dmPFC induced markedly increased evoked responses during T condition in relation to NT. Moreover, we found that the structural integrity of the dmPFC and the amygdala predict excitability regulation patterns as measured by ERP and TEP during fear processing.\n\nConclusionsWe describe the dynamic range of excitability regulation in dmPFC during fear processing. The applied paradigm can be used to non-invasively track response abnormalities to threat stimuli in healthy subjects or patients with mental disorders.

neuroscience↗