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Gregg, N. M.

Publications and source records attributed to Gregg, N. M..

15 recordsLinked to original sources

Insulotaxy: Navigating the Human Insula with a Novel Stereotactic Framework

IntroductionThe insula is an increasingly important target for functional neurosurgery given its involvement in a range of neurological and neuropsychiatric disorders, including epilepsy and chronic pain. As this practice evolves, optimal targeting will require standardized outcome measures that relate electrode or laser trajectory to postprocedural outcome. Traditional whole- brain registration approaches fail to capture the substantial person-to-person variability in insular gyral configuration, including the relative internal rotation of the insular gyri with respect to standard stereotactic space. ObjectiveWe propose and validate a stereotactic coordinate system based on local anatomical landmarks to facilitate surgical planning and standardized outcome assessment within the insular cortex. MethodsOur approach transforms brain MRI first into standard AC-PC space, and then into an insular-specific space defined by five anatomical landmarks: four points along the central sulcus of the insula and one point at the middle cerebral artery (MCA) bifurcation (at the limen insulae). The system calculates two angles - {theta} (axial) and {varphi} (sagittal) - between the AC-PC line and the insular axis, and the brain volume undergoes sequential rotation through these angles followed by translation to place the coordinate systems origin along the insular axis. ResultsIn a sample of 32 patients, the angle between the AC-PC line and the insular axis ranged from -17{degrees} to 17{degrees} in the axial plane ({theta}) and 31{degrees} to 69{degrees} in the sagittal plane ({varphi}). In the resulting coordinate system, the insular axis defines z = 0 and the MCA turning point defines y = 0. We developed a custom, open-access MATLAB graphical interface that allows intuitive implementation of this system for both surgical planning and postoperative analysis; implanted electrodes, laser fiber position, and ablation geometry can each be localized within this common space. As a demonstration of its utility for pooling data across subjects, we applied the transformation to a previously acquired intracranial electrophysiology dataset and found that anatomically consistent, effector-specific motor representations emerged across 18 subjects once electrode positions were expressed in insular-specific coordinates. ConclusionAs stereotactic surgery for insular targets becomes more common with expanding scientific inquiry, an insular-specific coordinate system may facilitate operative planning and functional mapping, and may help standardize outcome assessment across patients and institutions. SIGNIFICANCE STATEMENTThe insular cortex represents an increasingly important surgical target for therapeutic interventions, yet substantial person-to-person anatomical variability hampers standardized targeting and outcome comparison. The insula is simultaneously the subject of expanding scientific inquiry -- into interoception, pain, autonomic regulation, salience processing, and sensorimotor representation -- much of it now pursued through intracranial recording and stimulation in humans, where cohorts are small, electrode sampling is idiosyncratic, and progress therefore depends on pooling data across patients in a frame that respects insular gyral architecture. We present "Insulotaxy," a stereotactic coordinate system built from consistent, easily identifiable local anatomical landmarks that accounts for the insulas unique rotational relationship to standard brain coordinates. An open-source MATLAB tool transforms imaging into insular-specific coordinates, facilitating surgical planning for ablation and electrode placement while enabling standardized outcome reporting across institutions. By providing locally anchored, anatomically aligned coordinates rather than relying on whole-brain registration, this framework addresses a practical gap in functional neurosurgery and lays a foundation for pooling clinical and electrophysiological data as insular interventions become more prevalent.

neuroscience↗

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.

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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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The Human Insula Encodes Somatotopic Representation of Motor Execution with an Effector-Specific Connectomic Map to Primary Motor Cortex

Understanding motor representation in the human brain requires mapping beyond the primary motor cortex, into the distributed networks that coordinate complex movements. The insular cortex, a multifunctional hub buried within the Sylvian fissure, has been implicated in motor control through clinical observations and neuroimaging. Yet its precise relation to movement processing remains one of the least understood aspects of motor neurophysiology. To address this gap, we quantified electrophysiological changes from implanted depth electrodes in patients performing simple movement tasks combined with single-pulse electrical stimulation (SPES) to map functional connectivity. The movement data reveal distinct somatotopic representation bilaterally, as well as inter-effector regions that are active for different movement types. Hand representation is centered along the ventral aspect of the middle and posterior short gyri bilaterally, while tongue/mouth tuned sites cluster in the dorsal posterior short gyrus and the dorsal long gyri. Insular activity temporally follows the primary motor cortex (M1) and precedes movement onset. SPES revealed somatotopically-specific connectivity between corresponding sites in M1 and insula (hand-to-hand, tongue-to-tongue) and between bilateral insulae. These observations establish that somatotopy is a conserved property of distributed motor control incorporating the insula, with direct implications for basic and clinical neuroscience.

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Single pulse electrical stimulation in white matter modulates iEEG visual responses in human early visual cortex

Electrical stimulation is increasingly used to modulate brain networks for clinical purposes. The basic unit of neurostimulation, a single electrical pulse, can travel through white matter to influence connected neuronal populations. However, the mechanisms by which it influences connected populations is not well understood: stimulation may excite, inhibit, or add noise to neuronal population activity. In this study, we investigated how single pulses modulate the neuronal processing of images in a well-controlled visual paradigm. In two human subjects implanted with iEEG electrodes for clinical purposes, single pulses were delivered to electrodes in white matter tracts connected to measurement electrodes in visual cortex. Images appeared on-screen at 0, 100, or 200 ms after each pulse. Using finite impulse response modeling, we decomposed the broadband and evoked potential responses into separate components induced by electrical stimulation and by visual processing. Single pulses induced transient broadband increases followed by suppression, but they did not modulate the visual broadband responses (i.e., stimulation response was additive to visual response). In contrast, single pulses elicited prominent brain stimulation evoked potentials and they modulated the visual evoked potentials. Specifically, visual evoked potentials were larger when stimulation occurred closer to visual onset. This indicates that a single electrical pulse can increase the strength or synchrony of visual inputs. Overall, these findings suggest that the effects of electrical stimulation in the visual system are two-fold: stimulation induces additive effects on broadband power, possibly by adding noise, and it interacts with synchronous visual inputs to amplify them.

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Human pulvinar stimulation engages select cortical pathways in epilepsy

The pulvinar has been proposed as an effective neuromodulation target for patients with posterior quadrant and temporal epilepsies. However, the pulvinar has a large tissue volume, multiple subnuclei, and widespread cortical connections. It remains unknown whether electrical stimulation of distinct pulvinar subregions affects the temporal, occipital, and parietal areas differently. To address this gap, we delivered single-pulse electrical stimulation to the pulvinar and measured the resulting brain stimulation evoked potentials in twelve patients undergoing stereotactic EEG for drug-resistant epilepsy. Brain stimulation evoked potentials were parameterized across the occipital, temporal and parietal cortex. Stimulation of the lateral pulvinar elicited significant brain stimulation evoked potentials in striate and extrastriate areas that diminish as stimulation shifts towards the medial pulvinar. Conversely, stimulation of the ventral aspect of the medial pulvinar produced significant lateral temporal evoked potentials, which diminish with lateral pulvinar stimulation. We also found that stimulation of the dorsomedial pulvinar evoked significant parietal responses with limited striate/extrastriate and lateral temporal responses. These results demonstrate that electrical stimulation of specific pulvinar subregions influences distinct occipital, parietal and lateral temporal areas. Selective targeting of pulvinar subregions to maximize seizure network engagement may be essential for individualized treatment of posterior quadrant and temporal epilepsies.

neuroscience↗

Large Animal Epilepsy Model Platform: Kainic Acid Porcine Model of Mesial Temporal Lobe Epilepsy

Translational large-animal models that can accommodate human-scale implantable devices are essential for advancing neuromodulation therapies in epilepsy. This study establishes a kainic acid (KA)-induced porcine model of mesial temporal lobe epilepsy (mTLE) using clinical imaging, stereotactic surgery, and a fully implantable neural stimulation and recording (INSR) device designed for humans. Seven pigs (six KA-treated and one saline control) underwent MRI-guided stereotactic implantation of electrodes targeting bilateral hippocampus (HPC) and anterior thalamus (ANT), followed by intra-hippocampal KA or saline infusion. Local field potentials (LFP) were recorded continuously with synchronized video monitoring. Seizures and LFP interictal epileptiform-like discharges (IEDs) were quantified using validated automated detectors. Histology was performed in the saline control and the longest surviving KA-treated pig. Intra-hippocampal KA infusion induced acute status epilepticus in all (6/6) treated pigs. Four animals survived to chronic monitoring with spontaneous seizures observed in three pigs (2,733 seizures; mean duration of 27.2 {+/-} 17.6 seconds). IEDs were observed in bilateral HPC of all animals, including saline control, with higher rates in the lesioned HPC (p <0.0001). While the IED morphology is consistent with epileptiform activity; IEDs alone are not specific for epilepsy and physiological transients (e.g. sharp-wave ripples) and injury-related hyperexcitability or strain-specific hyperexcitability cannot be excluded. Histological analysis revealed patchy neuronal loss and cytoarchitectural changes in HPC. This porcine model reproduces electrophysiological features of human mTLE. This approach provides a powerful translational bridge for developing and testing next-generation INSR and neuromodulation strategies in freely behaving large animals.

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Proper reference selection and re-referencing to mitigate bias in single pulse electrical stimulation data

Single pulse electrical stimulation experiments produce pulse-evoked potentials used to infer brain connectivity. The choice of recording reference for intracranial electrodes remains non-standardized and can significantly impact data interpretation. When the reference electrode is affected by stimulation or evoked brain activity, it can contaminate the pulse-evoked potentials recorded at all other electrodes and influence interpretation of findings. We highlight this specific issue in intracranial EEG datasets from two subjects recorded at separate institutions. We present several intuitive metrics to detect the presence of reference contamination and offer practical guidance on different mitigation strategies. Either switching the reference electrode or re-referencing to an adjusted common average effectively mitigated the reference contamination issue, as evidenced by increased variability in pulse-evoked potentials across the brain. Overall, we demonstrate the importance of clear quality checks and preprocessing steps that should be performed before analysis of single pulse electrical stimulation data. HighlightsO_LIA reference electrode close to active tissue can contaminate intracranial EEG signals C_LIO_LIInterpretation of pulse-evoked potentials can be biased by reference contamination C_LIO_LILow response variability between channels is indicative of reference contamination C_LIO_LIReference contamination can be resolved through data recollection or re-referencing C_LI

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ER-detect: a pipeline for robust detection of early evoked responses in BIDS-iEEG electrical stimulation data

Human brain connectivity can be measured in different ways. Intracranial EEG (iEEG) measurements during single pulse electrical stimulation provide a unique way to assess the spread of electrical information with millisecond precision. To provide a robust workflow to process these cortico-cortical evoked potential (CCEP) data and detect early evoked responses in a fully automated and reproducible fashion, we developed Early Response (ER)-detect. ER-detect is an open-source Python package and Docker application to preprocess BIDS structured iEEG data and detect early evoked CCEP responses. ER-detect can use three response detection methods, which were validated against 14 manually annotated CCEP datasets from two different sites by four independent raters. Results showed that ER-detects automated detection performed on par with the inter-rater reliability (Cohens Kappa of [~]0.6). Moreover, ER-detect was optimized for processing large CCEP datasets, to be used in conjunction with other connectomic investigations. ER-detect provides a highly efficient standardized workflow such that iEEG-BIDS data can be processed in a consistent manner and enhance the reproducibility of CCEP based connectivity results.

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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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Signatures of electrical stimulation driven network interactions in the human limbic system

Stimulation-evoked signals are starting to be used as biomarkers to indicate the state and health of brain networks. The human limbic network, often targeted for brain stimulation therapy, is involved in emotion and memory processing. Previous anatomical, neurophysiological and functional studies suggest distinct subsystems within the limbic network (Rolls, 2015). Previous studies using intracranial electrical stimulation, however, have emphasized the similarities of the evoked waveforms across the limbic network. We test whether these subsystems have distinct stimulation-driven signatures. In seven patients with drug-resistant epilepsy we stimulated the limbic system with single pulse electrical stimulation (SPES). Reliable cortico-cortical evoked potentials (CCEPs) were measured between hippocampus and the posterior cingulate cortex (PCC) and between the amygdala and the anterior cingulate cortex (ACC). However, the CCEP waveform in the PCC after hippocampal stimulation showed a unique and reliable morphology, which we term the limbic H-wave. This limbic H-wave was visually distinct and separately decoded from the amygdala to ACC waveform. Diffusion MRI data show that the measured endpoints in the PCC overlap with the endpoints of the parolfactory cingulum bundle rather than the parahippocampal cingulum, suggesting that the limbic H-wave may travel through fornix, mammillary bodies and the anterior nucleus of the thalamus (ANT). This was further confirmed by stimulating the ANT, which evoked the same limbic H-wave but with a shorter latency. Limbic subsystems have unique stimulation evoked signatures that may be used in the future to help develop stimulation therapies. Significance StatementThe limbic system is often compromised in diverse clinical conditions, such as epilepsy or Alzheimers disease, and it is important to characterize its typical circuit responses. Stimulation evoked waveforms have been used in the motor system to diagnose circuit pathology. We translate this framework to limbic subsystems using human intracranial stereo EEG (sEEG) recordings that measure deeper brain areas. Our sEEG recordings describe a stimulation evoked waveform characteristic to the memory and spatial subsystem of the limbic network that we term the limbic H-wave. The limbic H-wave follows anatomical white matter pathways from hippocampus to thalamus to the posterior cingulum and shows promise as a distinct biomarker of signaling in the human brain memory and spatial limbic network.

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Canonical Response Parameterization: Quantifying the structure of responses to single-pulse intracranial electrical brain stimulation

Single-pulse electrical stimulation in the nervous system, often called cortico-cortical evoked potential (CCEP) measurement, is an important technique to understand how brain regions interact with one another. Voltages are measured from implanted electrodes in one brain area while stimulating another with brief current impulses separated by several seconds. Historically, researchers have tried to understand the significance of evoked voltage polyphasic deflections by visual inspection, but no general-purpose tool has emerged to understand their shapes or describe them mathematically. We describe and illustrate a new technique to parameterize brain stimulation data, where voltage response traces are projected into one another using a semi-normalized dot product. The length of timepoints from stimulation included in the dot product is varied to obtain a temporal profile of structural significance, and the peak of the profile uniquely identifies the duration of the response. Using linear kernel PCA, a canonical response shape is obtained over this duration, and then single-trial traces are parameterized as a projection of this canonical shape with a residual term. Such parameterization allows for dissimilar trace shapes from different brain areas to be directly compared by quantifying cross-projection magnitudes, response duration, canonical shape projection amplitudes, signal-to-noise ratios, explained variance, and statistical significance. Artifactual trials are automatically identified by outliers in sub-distributions of cross-projection magnitude, and rejected. This technique, which we call "Canonical Response Parameterization" (CRP) dramatically simplifies the study of CCEP shapes, and may also be applied in a wide range of other settings involving event-triggered data. Author summaryWe introduce a new machine learning technique for quantifying the structure of responses to single-pulse intracranial electrical brain stimulation. This approach allows voltage response traces of very different shape to be compared with one another. A tool like this has been needed to replace the status quo, where researchers may understand their data in terms of discovered structure rather than in terms of a pre-assigned, hand-picked, feature. The method compares single-trial responses pairwise to understand if there is a reproducible shape and how long it lasts. When significant structure is identified, the shape underlying it is isolated and each trial is parameterized in terms of this shape. This simple parameterization enables quantification of statistical significance, signal-to-noise ratio, explained variance, and average voltage of the response. Differently-shaped voltage traces from any setting can be compared with any other in a succinct mathematical framework. This versatile tool to quantify single-pulse stimulation data should facilitate a blossoming in the study of brain connectivity using implanted electrodes.

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Electrical stimulation of temporal and limbic circuitry produces distinct responses in human ventral temporal cortex

The human ventral temporal cortex (VTC) is highly connected to integrate visual perceptual inputs with feedback from cognitive and emotional networks. In this study, we used electrical brain stimulation to understand how different inputs from multiple brain regions drive unique electrophysiological responses in the VTC. We recorded intracranial EEG data in 6 patients implanted with intracranial electrodes for epilepsy surgery evaluation. Pairs of electrodes were stimulated with single pulse electrical stimulation, and corticocortical evoked potential (CCEP) responses were measured at electrodes in the collateral sulcus and lateral occipitotemporal sulcus of the VTC. Using a novel unsupervised machine learning method, we uncovered 2 to 4 distinct response shapes, termed basis profile curves (BPCs), at each recording electrode in the 11 to 500 ms post-stimulation interval. CCEPs of unique shape and high amplitude were elicited following stimulation of several regions and classified into a set of four consensus BPCs across subjects. One of the consensus BPCs was primarily elicited by stimulation of the hippocampus; another by stimulation of the amygdala; a third by stimulation of lateral cortical sites, such as the middle temporal gyrus; and the final one by stimulation of multiple distributed sites. Stimulation also produced sustained high frequency power decreases and low frequency power increases that spanned multiple BPC categories. Characterizing distinct shapes in stimulation responses provides a novel description of connectivity to the VTC and reveals significant differences in input from cortical and limbic structures. SIGNIFICANCE STATEMENTDisentangling the numerous input influences on highly connected areas in the brain is a critical step toward understanding how different brain networks work together to produce function. Single pulse electrical stimulation is an effective tool to accomplish this goal because the shapes and amplitudes of signals recorded from electrodes are informative of the synaptic physiology of the stimulation-driven inputs. We focused on targets in the ventral temporal cortex because it is an area strongly implicated in visual object perception. By using a data-driven clustering algorithm, we identified anatomical regions with distinct input connectivity profiles to the ventral temporal cortex. Examining high frequency power changes revealed possible modulation of excitability at the recording site induced by electrical stimulation of connected regions.

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Distributed Brain Co-Processor for Neurophysiologic Tracking and Adaptive Stimulation: Application to Drug Resistant Epilepsy

Early implantable epilepsy therapy devices provided open-loop electrical stimulation without brain sensing, computing, or an interface for synchronized behavioral inputs from patients. Recent epilepsy stimulation devices provide brain sensing but have not yet developed analytics for accurately tracking and quantifying behavior and seizures. Here we describe a distributed brain co-processor providing an intuitive bi-directional interface between patient, implanted neural stimulation and sensing device, and local and distributed computing resources. Automated analysis of continuous streaming electrophysiology is synchronized with patient reports using a hand-held device and integrated with distributed cloud computing resources for quantifying seizures, interictal epileptiform spikes, and patient symptoms during therapeutic electrical brain stimulation. The classification algorithms for interictal epileptiform spikes and seizures were developed and parameterized using long-term ambulatory data from 9 humans and 8 canines with epilepsy, and then implemented prospectively in out-of-sample testing in 2 pet canines and 4 humans with drug resistant epilepsy living in their natural environments.

bioengineering↗

Typical somatomotor physiology of the hand is preserved in a patient with an amputated arm

Electrophysiological signals in the human motor system may change in different ways after deafferentation, with some studies emphasizing reorganization while others propose retained physiology. Understanding whether motor electrophysiology is retained over longer periods of time can be invaluable for patients with paralysis (e.g. ALS or brainstem stroke) when signals from sensorimotor areas may be used for communication or control over neural prosthetic devices. In addition, a maintained electrophysiology can potentially benefit the treatment of phantom limb pains through prolonged use of these signals in a brain-machine interface (BCI). Here, we were presented with the unique opportunity to investigate the physiology of the sensorimotor cortex in a patient with an amputated arm using electrocorticographic (ECoG) measurements. While implanted with an ECoG grid for clinical evaluation of electrical stimulation for phantom limb pain, the patient performed attempted finger movements with the contralateral (lost) hand and executed finger movements with the ipsilateral (healthy) hand. The electrophysiology of the sensorimotor cortex contralateral to the amputated hand remained very similar to that of hand movement in healthy people, with a spatially focused increase of high-frequency band (65-175Hz; HFB) power over the hand region and a distributed decrease in low-frequency band (15-28Hz; LFB) power. The representation of the three different fingers (thumb, index and little) remained intact and HFB patterns could be decoded using support vector learning at single-trial classification accuracies of >90%, based on the first 1-3s of the HFB response. These results demonstrate that hand representations are largely retained in the motor cortex. The intact physiological response of the amputated hand, the high distinguishability of the fingers and fast temporal peak are encouraging for neural prosthetic devices that target the sensorimotor cortex.

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