Biology subjects

Sheth, S.

Publications and source records attributed to Sheth, S..

36 records · Page 2Linked to original sources

bioRxiv2024

Eye movements organize excitability state, information coding and network connectivity in the human hippocampus

Natural vision is an active sensing process that entails frequent eye movements to sample the environment. Nonetheless vision is often studied using passive viewing with eye position held constant. Using closed-loop eye-tracking, with saccade-contingent stimulation and simultaneous intracranial recordings in surgical epilepsy patients, we tested the critical role of eye movement signals during natural visual processing in the hippocampus and hippocampal-amygdala circuit. Prior work shows that saccades elicit phase reset of ongoing neural excitability fluctuations across a broad array of cortical and subcortical areas. Here we show that saccade-related reset systematically modulates neuronal ensemble responses to visual input, enables phase-coding of information across the saccade-fixation cycle and modulates network connectivity between hippocampus and amygdala. The saccade-fixation cycle thus emerges as a fundamental sampling unit, organizing a range of neural operations including input representation, network connectivity and information coding. One-Sentence SummarySaccade-fixation cycle: a fundamental sampling unit, organizing input representation, information coding and network activation

neuroscience↗

bioRxiv2024

Common AAV gene therapy vectors show indiscriminate transduction of living human brain cell types

The development of cell-type-specific gene therapy vectors for treating neurological diseases holds great promise, but has relied on animal models with limited translational utility. We have adapted an ex vivo organotypic model to evaluate adeno-associated virus (AAV) transduction properties in living slices of human brain tissue. Using fluorescent reporter expression and single-nucleus RNA sequencing, we found that common AAV vectors show broad transduction of normal cell types, with protein expression most apparent in astrocytes; this work introduces a pipeline for identifying and optimizing AAV gene therapy vectors in human brain samples.

bioengineering↗

bioRxiv2024

InTraSeq: A Multimodal Assay that Uncovers New Single-Cell Biology and Regulatory Mechanisms

Single-cell RNA sequencing (scRNA-seq) has revolutionized cell biology by enabling the profiling of transcriptomes at a single-cell resolution, leading to important discoveries that have advanced our understanding of cellular and tissue heterogeneity, developmental trajectories, and disease progression. Despite these important advances, scRNA-seq is limited to measuring the transcriptome providing a partial view of cellular function. To address this limitation, multimodal scRNA-seq assays have emerged, allowing for the simultaneous measurement of RNA expression and protein. Intracellular Transcriptomic and Protein Sequencing (InTraSeq), a novel multimodal scRNA-seq technology described here, enables the concurrent measurement of mRNA, surface markers, cytoplasmic proteins, and nuclear proteins within individual cells through oligo-barcoded antibodies. This method offers a comprehensive approach to studying cellular function by combining RNA and protein profiling from the same sample and utilizing a relatively simple protocol. The InTraSeq method enables researchers to expand their view of critical intracellular protein expression including post-translational modifications (PTMs) and transcription factors, allowing for the identification of novel cellular subtypes and states that may be obscured by RNA-based analyses alone. This is particularly valuable in understanding the heterogeneity of cell populations and identifying distinct functional states. In this report, we used InTraSeq to characterize the complex cellular states and regulatory mechanisms during Th17 cell differentiation. We simultaneously profiled RNA and protein expression in over 85,000 cells, capturing transcriptional changes, changes in protein expression and the dynamics of signaling pathways at a high resolution. Our results revealed novel insights into Th17 cell differentiation, including the identification of key regulatory factors and their target genes. By simultaneously measuring mRNA, extra and intra-cellular proteins, signaling proteins, and PTMs, InTraSeq offers a comprehensive understanding of cellular processes and enables the identification of novel regulatory mechanisms.

cell biology↗

bioRxiv2024

Spectral-switching analysis reveals real-time neuronal network representations of concurrent spontaneous naturalistic behaviors in human brain

Despite abundant evidence of functional networks in the human brain, their neuronal underpinnings, and relationships to real-time behavior have been challenging to resolve. Analyzing brain-wide intracranial-EEG recordings with video monitoring, acquired in awake subjects during clinical epilepsy evaluation, we discovered the tendency of each brain region to switch back and forth between 2 distinct power spectral densities (PSDs 2-55Hz). We further recognized that this spectral switching occurs synchronously between distant sites, even between regions with differing baseline PSDs, revealing long-range functional networks that would be obscured in analysis of individual frequency bands. Moreover, the real-time PSD-switching dynamics of specific networks exhibited striking alignment with activities such as conversation and hand movements, revealing a multi-threaded functional network representation of concurrent naturalistic behaviors. Network structures and their relationships to behaviors were stable across days, but were altered during N3 sleep. Our results provide a new framework for understanding real-time, brain-wide neural-network dynamics.

neuroscience↗

bioRxiv2024

Integrating Data Across Oscillatory Power Bands Predicts the Epileptogenic Zone: the Frequency Range Explorer Epileptogenic Zone (FREEZ) Identification Algorithm

Accurate identification of the seizure onset zone (SOZ) using intracranial electroencephalography (iEEG) remains challenging. Although diverse methods have leveraged spectral features to classify patient outcomes, few approaches focus on identifying individual electrodes within the SOZ or integrate a broad spectrum of frequency ranges within a single model. We developed an interpretable machine learning model that integrates power across delta, theta, alpha, beta, gamma, and high-gamma frequencies over time to identify the SOZ. For 1,511 electrodes implanted across 21 patients, we computed the mean spectral power in each frequency band for the first 20 seconds after seizure onset and analyzed the differences in power between SOZ and non-SOZ electrodes. In patients who were seizure-free after surgery (n = 14), electrodes within the SOZ showed significantly higher area under the curve (AUC) for mean power over time in the first 20 seconds after seizure onset compared to electrodes outside the SOZ in the alpha (p = 0.0272), beta (p = 0.0263), gamma (p = 0.0013), and high gamma (p = 0.0086) ranges. Additionally, electrodes within the SOZ in patients that became seizure-free after surgery had significantly higher AUC compared to equivalent electrodes in patients who did not become seizure-free after surgery (n = 7) in the gamma (p = 0.0145) and high gamma (p = 0.0024) power ranges. We trained a stacked random forest ensemble model using these features over time to label electrodes within the SOZ. Leave-one-out patient cross validation of the machine learning model yielded a 96.6% positive predictive value and 99.9% specificity for identifying electrodes within the SOZ. Our dataset included a diverse array of seizure onset patterns, which were all classified accurately by the model. A second model was trained to predict post-operative seizure freedom, yielding 95.2% accuracy for predicting seizure outcome based on a planned resection. This two-model design mirrors clinical workflow, first localizing SOZ electrodes to support surgical planning, then predicting outcome based on a surgical plan. An advantage of our interpretable machine learning approach is the ability to interrogate our models to understand how predictions are made. For electrode classification, the model weighed beta (0.66 {+/-} 0.07), high gamma (0.54 {+/-} 0.06), and delta (0.51 {+/-} 0.06) power bands most heavily. Viewing the models frequency band weights over time reveals that the model identified a pattern resembling the "fingerprint of the epileptogenic zone", reinforcing the importance of this dominant fundamental neurophysiologic signature of seizure onset.

neuroscience↗

bioRxiv2024

Individualized fMRI neuromodulation enhances visuospatial perception: a guided approach targeted towards the neuro-rehabilitation of cortical blindness and deceleration of subjective cognitive impairment.

Neuromodulation is a growing precision-medicine approach to modulating neural activity that can be used to treat neuropsychiatric, and general pathophysiologic conditions. We developed individualized fMRI neuromodulation (iNM) to study the mechanisms of visuospatial perception modulation with the long-term goal of applying it in low-vision patient populations having cortical blindness or visuospatial impairment preceding subjective cognitive impairment. To determine these mechanisms, we developed a direction and coherence discrimination task to engage visual perception (VP), visual imagery (VI), selective extero-intero-ceptive attention (SEIA), and motor planning (MP) networks. Participants discriminated up and down direction, at full and subthreshold coherence under iNM or control (no iNM). We determined the blood-oxygen-level-dependent (BOLD) magnitude as area under the curve (AUC) for VI, SEIA, and MP encoded networks and used a decoder to predict the stimulus from brain maps. The increased AUC BOLD magnitude under iNM across directions and coherences ranged from: 48-76% for SEIA, 26-59% for MP, 20-47% for VI, and 100% for strong VP coherences, but decreased for weak coherences. iNM increased classification performance. Our results imply a causal role of iNM-induced visuospatial mechanisms in strengthening these networks and provide a pathway for more accurate encoding models and effective treatment.

neuroscience↗

bioRxiv2023

A biophysically constrained brain connectivity model based on stimulation-evoked potentials.

BackgroundSingle-pulse electrical stimulation (SPES) is an established technique used to map functional effective connectivity networks in treatment-refractory epilepsy patients undergoing intracranial-electroencephalography monitoring. While the connectivity path between stimulation and recording sites has been explored through the integration of structural connectivity, there are substantial gaps, such that new modeling approaches may advance our understanding of connectivity derived from SPES studies. New MethodUsing intracranial electrophysiology data recorded from a single patient undergoing sEEG evaluation, we employ an automated detection method to identify early response components, C1, from pulse-evoked potentials (PEPs) induced by SPES. C1 components were utilized for a novel topology optimization method, modeling 3D conductivity propagation from stimulation sites. Additionally, PEP features were compared with tractography metrics, and model results were analyzed with respect to anatomical features. ResultsThe proposed optimization model resolved conductivity paths with low error. Specific electrode contacts displaying high error correlated with anatomical complexities. The C1 component strongly correlates with additional PEP features and displayed stable, weak correlations with tractography measures. Comparison with existing methodsExisting methods for estimating conductivity propagation are imaging-based and thus rely on anatomical inferences. ConclusionsThese results demonstrate that informing topology optimization methods with human intracranial SPES data is a feasible method for generating 3D conductivity maps linking electrical pathways with functional neural ensembles. PEP-estimated effective connectivity is correlated with but distinguished from structural connectivity. Modeled conductivity resolves connectivity pathways in the absence of anatomical priors.

neuroscience↗

bioRxiv2023

A survey of Rare Disease awareness among healthcare professionals and researchers in India

Rare diseases (RDs) are diseases that occur infrequently and affect a small fraction of the population. Although these diseases individually affect small number of people, together they affect 400 million people globally at any given time. In India, where resources are scarce, healthcare infrastructure and policy framework are focused on mitigating diseases that affect many people. Further, the level of RD awareness among healthcare professionals, researchers, and general public is considerably low. As a result, many cases of RDs remain unreported, undiagnosed, and untreated. To frame policies regarding RDs, it is crucial to understand the current level of RD awareness among healthcare professional and researchers, as they are key stakeholders in diagnosis, treatment, policy making, and drug development. We conducted an exploratory survey to understand the current level of RD awareness among healthcare professionals and researchers based on identification of an RD, time for diagnosis, treatment options, and relationship with family history and geographic location. We noted that our respondents have considerably low level of RD awareness. They correctly identified the importance of family history but failed to realize the association with geographic location. After presenting the survey findings, we have made recommendation to improve RD awareness in India. Our findings will be helpful to design awareness campaigns and frame relevant policies.

scientific communication and education↗

bioRxiv2023

Using interactive platforms to encode, manage and explore immune-related adverse outcome pathways

We address the need for modelling and predicting adverse outcomes in immunotoxicology to improve non-clinical assessments of immunomodulatory therapy safety and efficacy. The integrated approach includes, first, the adverse outcome pathway concept established in the toxicology field, and, second, the systems medicine disease map approach for describing molecular mechanisms involved in a particular pathology. The proposed systems immunotoxicology workflow is demonstrated with CAR T cell treatment as a use case. To this end, the linear adverse outcome pathway (AOP) is expanded into a molecular interaction model in standard systems biology formats. Then it is shown how knowledge related to immunotoxic events can be integrated, encoded, managed and explored to benefit the research community. The map is accessible online via the MINERVA Platform for browsing, commenting and data visualisation (https://minerva.pages.uni.lu). Our work transforms a graphical illustration of an AOP into a digitally structured and standardised form, featuring precise and controlled vocabulary and supporting reproducible computational analyses. Because of annotations to source literature and databases, the map can be further expanded to match the evolving knowledge and research questions.

systems biology↗

bioRxiv2022

Frontotemporal network engagement by human intracranial stimulation in limbic hubs

BackgroundPrefrontal circuits in the human brain play an important role in cognitive and affective processing. Neuromodulation therapies delivered to certain key hubs within these circuits are being used with increasing frequency to treat a host of neuropsychiatric disorders. However, the detailed neurophysiological effects of stimulation to these hubs are largely unknown. MethodsHere, we performed intracranial recordings across prefrontal networks while delivering electrical stimulation to two well-established white matter hubs involved in cognitive regulation and depression: the subcallosal cingulate (SCC) and ventral capsule/ventral striatum (VC/VS). ResultsWe demonstrate a shared frontotemporal circuit consisting of the ventromedial PFC, amygdala, and lateral orbitofrontal cortex where gamma oscillations are differentially modulated by stimulation target. Additionally, we found subject-specific responses to stimulation in the dorsal anterior cingulate cortex and demonstrate the capacity for further tuning of neural activity using current-steered stimulation. ConclusionsOur findings indicate a potential neurophysiological mechanism for the dissociable therapeutic effects seen across the SCC and VC/VS DBS targets for psychiatric neuromodulation and our results lay the groundwork for personalized, network-guided neurostimulation therapy.

neuroscience↗

bioRxiv2021

The Spatial Reach of Neuronal Coherence and Spike-field Coupling across the Human Neocortex

Neuronal coherence is thought to be a fundamental mechanism of communication in the brain, where synchronized field potentials coordinate synaptic and spiking events to support plasticity and learning. Although the spread of field potentials has garnered great interest, little is known about the spatial reach of phase synchronization, or neuronal coherence. Functional connectivity between different brain regions is known to occur across long distances, but the locality of coherence within a brain region is understudied. Here we used simultaneous recordings from electrocorticography (ECoG) grids and high-density microelectrode arrays to estimate the spatial reach of neuronal coherence and spike-field coherence (SFC) across frontal, temporal, and occipital cortices during cognitive tasks in humans. We observed the strongest coherence within a 2-3 cm distance from the microelectrode arrays, potentially defining an effective range for local communication. This range was relatively consistent across brain regions, spectral frequencies, and cognitive tasks. The magnitude of coherence showed power law decay with increasing distance from the microelectrode arrays, where the highest coherence occurred between ECoG contacts, followed by coherence between ECoG and deep cortical LFP, and then SFC (i.e., ECoG > LFP > SFC). The spectral frequency of coherence also affected its magnitude. Alpha coherence (8-14 Hz) was generally higher than other frequencies for signals nearest the microelectrode arrays, whereas delta coherence (1-3 Hz) was higher for signals that were farther away. Action potentials in all brain regions were most coherent with the phase of alpha oscillations, which suggests that alpha waves could play a larger, more spatially local role in spike timing than other frequencies. These findings provide a deeper understanding of the spatial and spectral dynamics of neuronal coherence, further advancing knowledge about how activity propagates across the human brain.

neuroscience↗

bioRxiv2021

Pre-trial predictors of conflict response efficacy in human dorsolateral prefrontal cortex

The ability to perform motor actions depends, in part, on the brains initial state, that is, the ensemble firing rate pattern prior to the initiation of action. We hypothesized that the same principle would apply to cognitive functions as well. To test this idea, we examined a unique set of single unit data collected in human dorsolateral prefrontal (dlPFC) cortex. Data were collected in a conflict task that interleaves Simon (motor-type) and Eriksen (flanker-type) conflict trials. In dlPFC, variability in pre-trial firing rate predicted the ability to resolve conflict, as inferred from reaction times. Ensemble patterns that predicted faster Simon reaction times overlapped slightly with those predicting Erikson performance, indicating that the two conflict types are associated with near-orthogonal initial states, and suggesting that there is a weak abstract or amodal conflict preparatory state in this region. These codes became fully orthogonalized in the response state. We interpret these results in light of the initial state hypothesis, arguing that the firing patterns in dlPFC immediately preceding the start of a task predispose it for the efficient implementation of cognitive action.

neuroscience↗

bioRxiv2020

CRTC1-MAML2 Establishes a PGC1α-IGF1 Circuit that Confers Vulnerability to PPARγ Inhibition

Mucoepidermoid carcinoma (MEC) is a life-threatening salivary gland cancer that is driven primarily by the transcriptional co-activator fusion CRTC1-MAML2. The mechanisms by which the chimeric CRTC1-MAML2 oncoprotein rewires gene expression programs that promote tumorigenesis remain poorly understood. Here, we show that CRTC1-MAML2 induces transcriptional activation of the non-canonical PGC-1 splice variant PGC-14, which regulates PPAR{gamma}-dependent IGF-1 expression. This mitogenic transcriptional circuitry is consistent across cell lines and primary tumors. CRTC1-MAML2 positive tumors are dominated by IGF-1 pathway activation and small molecule drug screens reveal that tumor cells harboring the fusion gene are selectively sensitive to IGF-1R inhibition. Furthermore, this dependence on autocrine regulation of IGF-1 transcription renders MEC cells susceptible to PPAR{gamma}inhibition with inverse agonists. These results yield insights into the aberrant co-regulatory functions of CRTC1-MAML2 and identify a specific vulnerability that can be exploited for precision therapy.

cancer biology↗

bioRxiv2020

Dual mechanisms of ictal high frequency oscillations in human rhythmic onset seizures

High frequency oscillations (HFOs) recorded from intracranial electrodes during epileptiform discharges are a proposed biomarker of epileptic brain tissue and may also be useful for seizure forecasting, with mixed results. Despite such potential for HFOs, there is limited investigation into the spatial context of HFOs and their relationship to simultaneously recorded neuronal activity. We sought to further understand the biophysical underpinnings of ictal HFOs using unit recordings in the human neocortex and mesial temporal lobe during rhythmic onset seizures. We compare features of ictal discharges in both the seizure core and penumbra (spatial seizure domains defined by multiunit activity patterns). We report differences in spectral features, unit-local field potential coupling, and information theoretic characteristics of HFOs before and after local seizure invasion. Furthermore, we tie these timing-related differences to spatial domains of seizures, showing that penumbral discharges are widely distributed and less useful for seizure localization.

physiology↗

bioRxiv2020

Human dorsal anterior cingulate neurons signal conflict by amplifying task-relevant information

Hemodynamic activity in dorsal anterior cingulate cortex (dACC) correlates with conflict, suggesting it contributes to conflict processing. This correlation could be explained by multiple neural processes that can be disambiguated by population firing rates patterns. We used targeted dimensionality reduction to characterize activity of populations of single dACC neurons as humans performed a task that manipulates two forms of conflict. Although conflict enhanced firing rates, this enhancement did not come from a discrete population of domain-general conflict-encoding neurons, nor from a distinct conflict-encoding response axis. Nor was it the epiphenomenal consequence of simultaneous coactivation of action plans. Instead, conflict amplified the task-relevant information encoded across the neuronal population. Effects of conflict were weaker and more heterogeneous in the dorsolateral prefrontal cortex (dlPFC), suggesting that dACCs role in conflict processing may be somewhat specialized. Overall, these results support the theory that conflict biases competition between sensorimotor transformation processes occurring in dACC.

neuroscience↗

bioRxiv2018

Single neurons in the human entorhinal cortex remap to distinguish individual spatial memories

The entorhinal cortex (EC) is known to play a key role in both memory and spatial navigation. Despite this overlap in spatial and mnemonic circuits, it is unknown how spatially responsive neurons contribute to our ability to represent and distinguish past experiences. Recording from medial temporal lobe (MTL) neurons in subjects performing cued recall of object-location memories in a virtual-reality environment, we identified \"trace cells\" in the EC that remap their spatial fields to locations subjects were cued to recall on each trial. In addition to shifting its firing field according to the memory cue, this neuronal activity exhibited a firing rate predictive of the cued memorys content. Critically, this memory-specific neuronal activity re-emerged when subjects were cued for recall without entering the environment, indicating that trace-cell memory representations generalized beyond navigation. These findings suggest a general mechanism for memory retrieval via trace-cell activity and remapping in the EC.

neuroscience↗

bioRxiv2017

Electrophysiological signatures of spatial boundaries in the human subiculum

Environmental boundaries play a crucial role in spatial navigation and memory across a wide range of distantly-related species. In rodents, boundary representations have been identified at the single-cell level in the subiculum and entorhinal cortex of the hippocampal formation. While studies of hippocampal function and spatial behavior suggest that similar representations might exist in humans, boundary-related neural activity has not been identified electrophysiologically in humans until now. Here we present direct intracranial recordings from the hippocampal formation of surgical epilepsy patients while they performed a virtual spatial navigation task. Our results suggest that encoding target locations near boundaries elicited stronger theta oscillations than for target locations near the center of the environment and that this difference cannot be explained by variables such as trial length, speed, or movement. These findings provide the first direct evidence of boundary-dependent neural activity localized in humans to the subiculum, the homologue of the hippocampal subregion in which most rodent boundary cells are found.\n\nSignificance StatementSpatial computations using environmental boundaries are an integral part of the brains spatial mapping system. In rodents, border/boundary cells in the subiculum and entorhinal cortex reveal boundary coding at the single-neuron level. Although there is good reason to believe that such representations also exist in humans, the evidence has thus far been limited to fMRI studies that broadly implicate the hippocampus in boundary-based navigation. By combining intracranial recordings with high-resolution imaging of hippocampal subregions we identified, for the first time in humans, a neural marker of boundary representation in the subiculum.

neuroscience↗

bioRxiv2017

The medial temporal lobe organizes memory across time and space: Causal evidence from brain stimulation

The medial temporal lobe (MTL) is widely implicated in supporting episodic memory and navigation, but its precise functional role in organizing memory across time and space remains elusive. Here we examine the specific cognitive processes implemented by MTL structures (hippocampus and entorhinal cortex) to organize memory by using electrical brain stimulation, leveraging its ability to establish causal links between brain regions and features of behavior. We studied neurosurgical patients who performed spatial-navigation and verbal-episodic memory tasks while brain stimulation was applied in various regions during learning. During the verbal memory task, stimulation in the MTL disrupted the temporal organization of encoded memories such that items learned with stimulation tended to be recalled in a more randomized order. During the spatial task, MTL stimulation impaired subjects abilities to remember items using view-independent (allocentric) navigation strategies. These stimulation effects were specific to the MTL. Our findings thus provide the first causal demonstration in humans of the specific memory processes that are performed by the MTL to encode when and where events occurred.\n\nSignificance StatementNumerous studies have implicated the medial temporal lobe (MTL) in encoding spatial and temporal memories, but they have not been able to causally demonstrate the nature of the cognitive processes by which this occurs in real-time. Electrical brain stimulation is able to demonstrate causal links between a brain region and a given function with high temporal precision. By examining behavior in a memory task as subjects received MTL stimulation, we provide the first causal evidence demonstrating the role of the MTL in organizing the spatial and temporal aspects of episodic memory.

neuroscience↗