Biology subjects

Worrell, G.

Publications and source records attributed to Worrell, G..

15 recordsLinked to original sources

bioRxiv2026

White matter conduction in the human brain is mostly slow, with rare high velocity connections

White matter bundles play a crucial role in cognitive functions by rapidly transmitting information between brain regions. Inter-areal conduction guides the integration of information and conduction velocity is a fundamental parameter in theories and models of brain function. However, distributions of conduction velocity remain difficult to characterize in vivo in humans. In this work, we integrated diffusion magnetic resonance imaging (dMRI) tractography with intracranial electrical stimulation during clinical stereo-electroencephalography (sEEG) monitoring in 17 subjects to measure conduction velocity within four major white matter bundles. Our findings reveal that human brain conduction is characterized by high variability both within and between bundles, reflecting a predominance of slow connections alongside rare high-speed connections. Because conduction velocity in myelinated fibers follows an approximately linear relationship with axon diameter, we derive underlying axon diameter distributions and show that these estimates are comparable to previous post-mortem studies. These findings demonstrate a heavily skewed distribution of human neural conduction velocities and show that structural heterogeneity shapes the timing and integration of information in large-scale networks.

neuroscience↗

bioRxiv2026

A Systematic Characterization of Causal Interactions Between Human Visual Areas

Human visual cortex comprises three interacting streams, but anatomy and correlated activity cannot determine the direction or reliability of interareal influence. Characterizing directional interactions among these streams can reveal the architecture through which activity can propagate across the visual system. Here, we used single-pulse electrical stimulation during intracranial EEG recordings in 23 patients to map directed effective connectivity among 22 atlas-defined visual cortical areas. The resulting effective connectivity matrix revealed a selective and asymmetric architecture of interareal influence. Feedforward influences from early visual areas to the dorsal and lateral streams were more reliable and more prevalent than the corresponding feedback influences, whereas interactions between early visual and ventral temporal areas were comparatively balanced. Cross-stream interactions favored temporal-to-parietal over parietal-to-temporal influence, with higher response reliability and a greater proportion of significant responses among sampled connections. Network-level profiles were consistent with source-like organization in early visual areas and the ventral stream, and integrator-like organization in the dorsal and lateral streams. Visual-task data collected in three of the same patients illustrated how stimulation-derived connectivity may relate to functional responses across connected visual regions. These findings reveal a directional architecture for activity propagation across the human visual cortex and provide empirical constraints for biologically grounded models of visual processing.

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bioRxiv2025

Generalized brain-state modeling with KenazLBM

The large-scale functional state of a human brain remains difficult to characterize, much less predict. Regardless, techniques have been engineered to electrically neuromodulate the brain to treat a subset of neurologic and psychiatric disorders with moderate efficacy. Accurate characterization of a brains instantaneous functional state has stymied the development of more effective neuromodulation paradigms. Advanced computational methods are required to address this gap and enable large-scale neuroscience. Here we define the concept of generalized brain-state modeling across humans as Large Brain-State Modeling (LBM) and present KenazLBM as the worlds first example. KenazLBM can instantaneously characterize the functional state of a persons brain with raw iEEG data, and predict future brain-states. KenazLBM was trained on over 17.9 billion unique multichannel tokens from people undergoing intracranial electroencephalography (iEEG) recordings, and has learned to interrelate brain-states between people into a common interpretable topology. Most importantly, the model generalizes to unseen subject data with significant recording channel heterogeneity from the training set. We offer KenazLBM as a first generalized brain-state model to serve as a new paradigm of basic neuroscience inquiry and potential translation into neuromodulation therapeutics.

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bioRxiv2025

Low and high frequency signatures of impaired consciousness in temporal lobe seizures

Impaired consciousness is a debilitating and unpredictable outcome of mesial temporal lobe seizures whose mechanisms to date remain unclear. Moreover, questions about the relationship between impaired consciousness and lateralization, hemispheric spread and electrophysiological characteristics of seizures are yet to be answered. To address these gaps, we conducted in-depth investigation of behavioral and intracranial EEG data from 186 mesial temporal lobe seizures of 51 patients with intractable mesial temporal lobe epilepsy. We found that bilateral mesial temporal spread of seizures is not a necessary condition for impaired consciousness, although seizures with bilateral mesial temporal involvement were significantly more likely to have impaired consciousness than unilateral seizures. Contrary to prior belief, we found no relationship between the onset side (left vs. right temporal lobe or language dominant vs. non-dominant lobe) of seizures and the probability of impaired consciousness. Lastly, we established that widespread increases in slow-wave activity (delta band) in extratemporal cortical areas, as well as increases in fast activity (beta band) in the temporal lobes were both robust markers of seizures with impaired consciousness and could predict ictal impairment with up to 86% accuracy. Our findings shed new light on networks that underlie impaired consciousness in temporal lobe epilepsy and may help guide deep brain stimulation of such systems (e.g. via thalamic nuclei) as a potential intervention to improve consciousness during seizures.

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bioRxiv2025

Exploring GPCR-mediated optogenetic modulation of seizure network in a pig model of Temporal Lobe Epilepsy

RationaleOptogenetics offers unmatched cellular specificity and control over cellular activity. Various opsins have been tested in animal models of epilepsy, each contributing to our understanding of seizure circuit dynamics. However, inhibitory optogenetic tools based on microbial rhodopsins have low light sensitivity and, thus, are less suitable for applications involving larger brains. We evaluated eOPN3, a red-shifted, highly sensitive inhibitory G-protein coupled receptor opsin in a porcine seizure model using integrated electro-optical sensing and modulation. The results demonstrated the feasibility of eOPN3 circuit modulation in a large animal epilepsy model. MethodsMRI-guided stereotactic surgery was used to deliver 20-60 {micro}L of AAV-eOPN3 (AAV5-/AAV9-CaMKII-eOPN3-mScarlet) into the hippocampus (HPC) of three Gottingen minipigs. Each hemisphere received either an active or a control viral vector (AAV5/9-CaMKII-mScarlet) with gadolinium to visualize the injection sites and diffusion volume via post-operative MRI. Two to three months post-injection, bilateral deep brain stimulation electrodes integrated with optic fibers were stereotactically implanted into the anterior nucleus of the thalamus (ANT) and HPC to assess: 1) opsin expression using fiber photometry, 2) optogenetic modulation of stimulation evoked response potentials (SERPs), 3) induction and propagation of seizure-like activity via intrahippocampal kainic acid (KA) injection, and 4) optogenetic modulation of KA-induced seizure activity. After the electrophysiology recording, brains were harvested for histological analysis to evaluate injection target precision, eOPN3 expression, and estimate eOPN3-modulated volume. ResultseOPN3 expression was confirmed during surgery via fiber photometry. ANT electrical stimulation elicited robust SERPs in the HPCs, which were attenuated by HPC light illumination. HPC stimulation similarly induced SERPs in the ipsilateral ANT and the contralateral HPC. The HPC stimulation-induced SERPs were significantly reduced by illuminating the site of the recording areas, the ipsilateral ANT and the contralateral HPC, demonstrating the optogenetic inhibition of the synaptic release from the HPC. KA injection into the HPC induced 20-30 Hz seizure-like activity. The ANT and HPC light illumination suppressed the localized KA-induced seizure activity in the early stage. However, after the generalization of KA-induced seizures, the ANT-HPC illumination lost efficacy for the control of seizures. Histological analysis confirmed eOPN3 expression in the HPC, ANT and other Papez circuit nodes. ConclusionOur pilot study highlights that eOPN3-mediated inhibition alters SERP and the latency and spread of KA-induced seizure-like activity. We developed a platform incorporating pre- and postoperative MRI for precise viral vector delivery, real-time fiber photometry for quantifying opsin expression, and integrated electro-optical sensing and stimulation to assess optogenetic efficacy in a large animal model. The large animal model provides a solid foundation for future translational research to develop electro-optical devices and cellular therapies for human epilepsy.

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bioRxiv2023

Method for cycle detection in sparse, irregularly sampled, long-term neuro-behavioral timeseries: Basis pursuit denoising with polynomial detrending of long-term, inter-ictal epileptiform activity

Numerous physiological processes are cyclical, but sampling these processes densely enough to perform frequency decomposition and subsequent analyses can be challenging. Mathematical approaches for decomposition and reconstruction of sparsely and irregularly sampled signals are well established but have been under-utilized in physiological applications. We developed a basis pursuit denoising with polynomial detrending (BPWP) model that recovers oscillations and trends from sparse and irregularly sampled timeseries. We validated this model on a unique dataset of long-term inter-ictal epileptiform discharge (IED) rates from human hippocampus recorded with a novel investigational device with continuous local field potential sensing. IED rates have well established circadian and multiday cycles related to sleep, wakefulness, and seizure clusters. Given sparse and irregular samples of IED rates from multi-month intracranial EEG recordings from ambulatory humans, we used BPWP to compute narrowband spectral power and polynomial trend coefficients and identify IED rate cycles in three subjects. In select cases, we propose that random and irregular sampling may be leveraged for frequency decomposition of physiological signals. Author SummaryCircadian and multiday cycles are an important part of many long-term neuro-behavioral phenomena such as pathological inter-ictal epileptiform discharges (IEDs) in epilepsy. Long-term, ambulatory, neuro-behavioral monitoring in human patients involves complex recording systems that can be subject to intermittent, irregular data loss and storage limitations, resulting in sparse, irregularly sampled data. Cycle identification in sparse data or irregular data using traditional frequency decomposition techniques typically requires interpolation to create a regular timeseries. Using unique, long-term recordings of pathological brain activity in patients with epilepsy implanted with an investigational device, we developed a method to identify cycles in sparse, irregular neuro-behavioral data without interpolation. We anticipate this approach will enable retrospective cycle identification in sparse neuro-behavioral timeseries and support prospective sparse sampling in monitoring systems to enable long-term monitoring of patients and to extend storage capacity in a variety of ambulatory monitoring applications.

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bioRxiv2022

Chronic modulation of human memory and thalamic-hippocampal theta activities.

Electrical stimulation is a powerful therapeutic tool for treating neurologic and neuropsychiatric disorders. Sensing and modulating electrophysiological biomarkers of memory over extended timescales is necessary for tracking and improving memory in humans. Here, we describe results from humans in their natural home environments using a novel, investigational system enabling chronic stimulation and multi-channel recording of anterior thalamic and hippocampal local field potentials during memory tasks. Four people with focal epilepsy performed a free recall verbal memory task repeatedly for up to fifty months on a touch-screen device with wireless signal acquisition with electrophysiology and behavioral data streaming to a cloud environment. Anterior thalamic-hippocampal spectral activities in the theta frequency range were found to correlate with memory processing, to predict task performance, and to be modulated by deep brain stimulation. Our results provide a new biomarker-based technology for chronic remote tracking of memory performance and modulation of the associated neural activities. One Sentence SummaryElectrical stimulation in the anterior thalamic nuclei modulates theta frequency activities and improves human verbal memory performance chronically.

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bioRxiv2022

Homunculus Interruptus: A motor association area in the depth of the central sulcus

Cells in the precentral gyrus of the human brain directly send signals to the periphery to generate movement and are topologically organized as a map of the body. We find that movement induced electrophysiological changes from implanted depth electrodes extend this map 3-dimensionally throughout the volume of the gyrus. Unexpectedly, this organization is interrupted by a motor association area in the depths of the central sulcus at its mid-lateral aspect that is active during many different types of movements from both sides of the body.

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bioRxiv2022

Microglial process dynamics enhance neuronal activity by shielding GABAergic synaptic inputs

Microglia are resident immune cells of the central nervous system (CNS) and play key roles in brain homeostasis. During anesthesia, microglia increase their dynamic process surveillance and interact more closely with neurons. However, the functional significance of microglial process dynamics and neuronal interaction has remained unclear. Using in vivo two-photon imaging in awake mice, we discover that microglia enhance neuronal activity after the cessation of general anesthesia. Hyperactive neuron somata are directly contacted by microglial processes, which specifically co-localize with GABAergic boutons. Electron microscopy-based synaptic reconstruction after two-photon imaging reveals that microglial processes enter into the synaptic cleft to shield GABAergic inputs. Microglial ablation or loss of microglial {beta}2-adrenergic receptors prevent post-anesthesia neuronal hyperactivity. Together, our study demonstrates a previously unappreciated function of microglial process dynamics, which allow microglia to transiently boost neuronal activity by physically shielding inhibitory inputs.

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bioRxiv2021

Distinct signatures of loss of consciousness during Focal Impaired Awareness (FIA) versus Focal to Bilateral Tonic-Clonic (FBTC) seizures

Loss of consciousness (LOC) is a hallmark of many epileptic seizures and carries risks of serious injury and sudden death. While cortical sleep-like activities accompany LOC during focal impaired awareness (FIA) seizures, the mechanisms of LOC during focal to bilateral tonic-clonic (FBTC) seizures remain unclear. Quantifying differences in markers of cortical activation and ictal recruitment between FIA and FBTC seizures may also help to understand their different consequences for clinical outcomes and to optimize neuromodulation therapies. We quantified clinical signs of LOC and intracranial EEG (iEEG) activity during 129 FIA and 50 FBTC from 41 patients. We characterized iEEG changes both in the seizure onset zone (SOZ) and in areas remote from SOZ with a total of 3386 electrodes distributed across brain areas. First, we compared the dynamics of iEEG sleep-like activities: slow-wave activity (SWA; 1-4 Hz) and beta/delta ratio (B/D; a validated marker of cortical activation) during FIA vs. FBTC. Second, we quantified differences between FBTC and FIA for a marker validated to detect ictal cross-frequency coupling: phase-locked high-gamma (PLHG; high gamma phased locked to low frequencies) and a marker of ictal recruitment: the epileptogenicity index (i.e. the number of channels crossing an energy ratio threshold for high vs. low frequency power). Third, we assessed changes in iEEG activity preceding and accompanying behavioral generalization onset and their correlation with electromyogram (EMG) channels. In addition, we analyzed human cortical multi-unit activity recorded with Utah arrays during three FBTC. Compared to FIA, FBTC seizures were characterized by deeper LOC and by stronger increases in SWA in parieto-occipital cortex. FBTC also displayed more widespread increases in cortical activation (B/D), ictal cross-frequency coupling (PLHG) and ictal recruitment (epileptogenicity index). Even before generalization, FBTC displayed deeper LOC; this early LOC was accompanied by a paradoxical increase in B/D in fronto-parietal cortex. Behavioral generalization coincided with complete loss of responsiveness and a subsequent increase in high-gamma in the whole brain, which was especially synchronous in deep sources and could not be explained by EMG. Similarly, multi-unit activity analysis of FBTC revealed sustained increases in cortical firing rates during and after generalization onset in areas remote from the SOZ. Unlike during FIA, LOC during FBTC is characterized by a paradoxical increase in cortical activation and neuronal firing. These findings suggest differences in the mechanisms of ictal LOC between FIA and FBTC and may account for the more negative prognostic consequences of FBTC.

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bioRxiv2019

Intracranial EEG reveals bihemispheric parietal and extra parietal brain networks supporting mental arithmetic

Mathematical reasoning is central to everyday life. Lesion data and functional MRI studies suggest that even simple arithmetic involves the coordination of multiple spatially diverse brain regions, but to date, math processing has not been well characterized using direct brain recordings, especially outside of the parietal cortex. To address this, we utilized an unparalleled data set of 310 subjects implanted with intracranial electrodes to investigate the spatial and temporal dynamics of arithmetic reasoning. Our data support the importance of regions previously implicated in numerosity such as the superior parietal lobule and intraparietal sulcus. However, we also identify contributions to arithmetic processing from regions such as the entorhinal cortex and temporal pole. Using the excellent bihemispheric coverage afforded by our data set and the precise temporal resolution of intracranial recordings, we characterize in detail the spatial and temporal characteristics of an arithmetic processing network, quantifying subtle hemispheric differences for selected regions. We also examine how activity in these regions predicts arithmetic ability and look for gender differences in the pattern of network activation. Our findings further define the complex network of regions involved in human arithmetical reasoning.

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bioRxiv2018

MTL functional connectivity predicts stimulation-induced theta power

Abstract/SummaryFocal electrical stimulation of the brain incites a cascade of neural activity that propagates from the stimulated region to both nearby and remote areas, offering the potential to control the activity of brain networks. Understanding how exogenous electrical signals perturb such networks in humans is key to its clinical translation. To investigate this, we applied electrical stimulation to subregions of the medial temporal lobe in 26 neurosurgical patients fitted with indwelling electrodes. Networks of low-frequency (5-13 Hz) spectral coherence predicted stimulation-evoked changes in theta (5-8 Hz) power, but only when stimulation was applied in or adjacent to white matter. Furthermore, these power changes aligned with control-theoretic predictions of how exogenous stimulation flows through complex networks, such as a dispersal of induced activity when functional hubs are targeted. Our results demonstrate that functional connectivity is predictive of causal changes in the brain, but that access to structural connections is necessary to observe such effects.

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bioRxiv2018

Predictive control of electrophysiological network architecture using direct, single-node neurostimulation in humans

Chronically implantable neurostimulation devices are becoming a clinically viable option for treating patients with neurological disease and psychiatric disorders. Neurostimulation offers the ability to probe and manipulate distributed networks of interacting brain areas in dysfunctional circuits. Here, we use tools from network control theory to examine the dynamic reconfiguration of functionally interacting neuronal ensembles during targeted neurostimulation of cortical and subcortical brain structures. By integrating multi-modal intracranial recordings and diffusion tensor imaging from patients with drug-resistant epilepsy, we test hypothesized structural and functional rules that predict altered patterns of synchronized local field potentials. We demonstrate the ability to predictably reconfigure functional interactions depending on stimulation strength and location. Stimulation of areas with structurally weak connections largely modulates the functional hubness of downstream areas and concurrently propels the brain towards more difficult-to-reach dynamical states. By using focal perturbations to bridge large-scale structure, function, and markers of behavior, our findings suggest that stimulation may be tuned to influence different scales of network interactions driving cognition.

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bioRxiv2018

Functional wiring of the human medial temporal lobe

The medial temporal lobe (MTL) is a locus of episodic memory in the human brain. It is comprised of cytologically distinct subregions that, in concert, give rise to successful encoding and retrieval of context-dependent memories. However, the functional connections between these subregions are poorly understood. To determine functional connectivity among MTL subregions, we had 126 subjects fitted with indwelling electrodes perform a verbal memory task, and asked how encoding or retrieval correlated with interregional synchronization. Using phase-based measures of connectivity, we found that synchronous theta (4-8 Hz) activity underlies successful episodic memory, whereas high-frequencies exhibit desynchronization. Moreover, theta functional connectivity during encoding aligned with key anatomic connections, including critical links between the entorhinal cortex, dentate gyrus, and CA1 of the hippocampus. Retrieval-associated networks demonstrated enhanced involvement of the subiculum, reflecting a substantial reorganization of the encoding-associated network. We posit that coherent theta activity within the MTL marks periods of successful memory, but distinct patterns of connectivity dissociate key stages of memory processing.\n\nSignificance StatementThe brain functions through the interaction of its distinct parts, but little is known about how such connectivity dynamics relate to learning and memory. We used a large dataset of 126 human subjects with intracranial electrodes to assess patterns of electrical connectivity within the medial temporal lobe - a key region for memory processing - as they performed a memory task. We discovered that unique networks of time-varying, low-frequency interactions correlate with memory encoding and retrieval, specifically in the theta band. Simultaneously, we observed elevated spectral power at high frequencies in these same regions. The result is a complete map of physiological dynamics within the MTL, highlighting how a reorganization of theta networks support distinct memory operations.

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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.

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