417 research outputs found

    Unsupervised decoding of long-term, naturalistic human neural recordings with automated video and audio annotations

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    Fully automated decoding of human activities and intentions from direct neural recordings is a tantalizing challenge in brain-computer interfacing. Most ongoing efforts have focused on training decoders on specific, stereotyped tasks in laboratory settings. Implementing brain-computer interfaces (BCIs) in natural settings requires adaptive strategies and scalable algorithms that require minimal supervision. Here we propose an unsupervised approach to decoding neural states from human brain recordings acquired in a naturalistic context. We demonstrate our approach on continuous long-term electrocorticographic (ECoG) data recorded over many days from the brain surface of subjects in a hospital room, with simultaneous audio and video recordings. We first discovered clusters in high-dimensional ECoG recordings and then annotated coherent clusters using speech and movement labels extracted automatically from audio and video recordings. To our knowledge, this represents the first time techniques from computer vision and speech processing have been used for natural ECoG decoding. Our results show that our unsupervised approach can discover distinct behaviors from ECoG data, including moving, speaking and resting. We verify the accuracy of our approach by comparing to manual annotations. Projecting the discovered cluster centers back onto the brain, this technique opens the door to automated functional brain mapping in natural settings

    Molecular characterization of microbiota in cerebrospinal fluid from patients with CSF shunt infections using whole genome amplification followed by shotgun sequencing

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    Understanding the etiology of cerebrospinal fluid (CSF) shunt infections and reinfections requires detailed characterization of associated microorganisms. Traditionally, identification of bacteria present in the CSF has relied on culture methods, but recent studies have used high throughput sequencing of 16S rRNA genes. Here we evaluated the method of shotgun DNA sequencing for its potential to provide additional genomic information. CSF samples were collected from 3 patients near the beginning and end of each of 2 infection episodes. Extracted total DNA was sequenced by: (1) whole genome amplification followed by shotgun sequencing (WGA) and (2) high-throughput sequencing of the 16S rRNA V4 region (16S). Taxonomic assignments of sequences from WGA and 16S were compared with one another and with conventional microbiological cultures. While classification of bacteria was consistent among the 3 approaches, WGA provided additional insights into sample microbiological composition, such as showing relative abundances of microbial versus human DNA, identifying samples of questionable quality, and detecting significant viral load in some samples. One sample yielded sufficient non-human reads to allow assembly of a high-qualit

    Cortical Topography of Error-Related High-Frequency Potentials During Erroneous Control in a Continuous Control Brain–Computer Interface

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    Brain–computer interfaces (BCIs) benefit greatly from performance feedback, but current systems lack automatic, task-independent feedback. Cortical responses elicited from user error have the potential to serve as state-based feedback to BCI decoders. To gain a better understanding of local error potentials, we investigate responsive cortical power underlying error-related potentials (ErrPs) from the human cortex during a one-dimensional center-out BCI task, tracking the topography of high-gamma (70–100 Hz) band power (HBP) specific to BCI error. We measured electrocorticography (ECoG) in three human subjects during dynamic, continuous control over BCI cursor velocity. Subjects used motor imagery and rest to move the cursor toward and subsequently dwell within a target region. We then identified and labeled epochs where the BCI decoder incorrectly moved the cursor in the direction opposite of the subject’s expectations (i.e., BCI error). We found increased HBP in various cortical areas 100–500 ms following BCI error with respect to epochs of correct, intended control. Significant responses were noted in primary somatosensory, motor, premotor, and parietal areas and generally regardless of whether the subject was using motor imagery or rest to move the cursor toward the target. Parts of somatosensory, temporal, and parietal areas exclusively had increased HBP when subjects were using motor imagery. In contrast, only part of the parietal cortex near the angular gyrus exclusively had an increase in HBP during rest. This investigation is, to our knowledge, the first to explore cortical fields changes in the context of continuous control in ECoG BCI. We present topographical changes in HBP characteristic specific to the generation of error. By focusing on continuous control, instead of on discrete control for simple selection, we investigate a more naturalistic setting and provide high ecological validity for characterizing error potentials. Such potentials could be considered as design elements for co-adaptive BCIs in the future as task-independent feedback to the decoder, allowing for more robust and individualized BCIs

    Tract-Based Spatial Statistical Analysis of Diffusion Tensor Imaging in Pediatric Patients with Mitochondrial Disease: Widespread Reduction in Fractional Anisotropy of White Matter Tracts

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    BACKGROUND AND PURPOSE: Often diagnosed at birth or in early childhood, mitochondrial disease presents with a variety of clinical symptoms, particularly in organs and tissues that require high energetic demand such as brain, heart, liver, and skeletal muscles. In a group of pediatric patients identified as having complex I or I/III deficits on muscle biopsy but with white matter tissue appearing qualitatively normal for age, we hypothesized that quantitative DTI analyses might unmask disturbance in microstructural integrity

    Superior verbal memory outcome after stereotactic laser amygdalohippocampotomy

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    Objective: To evaluate declarative memory outcomes in medically refractory epilepsy patients who underwent either a highly selective laser ablation of the amygdalohippocampal complex or a conventional open temporal lobe resection. Methods: Post-operative change scores were examined for verbal memory outcome in epilepsy patients who underwent stereotactic laser amygdalohippocampotomy (SLAH: n = 40) or open resection procedures (n = 40) using both reliable change index (RCI) scores and a 1-SD change metric. Results: Using RCI scores, patients undergoing open resection (12/40, 30.0%) were more likely to decline on verbal memory than those undergoing SLAH (2/40 [5.0%], p = 0.0064, Fisher's exact test). Patients with language dominant procedures were much more likely to experience a significant verbal memory decline following open resection (9/19 [47.4%]) compared to laser ablation (2/19 [10.5%], p = 0.0293, Fisher's exact test). 1 SD verbal memory decline frequently occurred in the open resection sample of language dominant temporal lobe patients with mesial temporal sclerosis (8/10 [80.0%]), although it rarely occurred in such patients after SLAH (2/14, 14.3%) (p = 0.0027, Fisher's exact test). Memory improvement occurred significantly more frequently following SLAH than after open resection. Interpretation: These findings suggest that while verbal memory function can decline after laser ablation of the amygdalohippocampal complex, it is better preserved when compared to open temporal lobe resection. Our findings also highlight that the dominant hippocampus is not uniquely responsible for verbal memory. While this is at odds with our simple and common heuristic of the hippocampus in memory, it supports the findings of non-human primate studies showing that memory depends on broader medial and lateral TL regions

    Interictal Functional Connectivity of Human Epileptic Networks Assessed by Intracerebral EEG and BOLD Signal Fluctuations

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    In this study, we aimed to demonstrate whether spontaneous fluctuations in the blood oxygen level dependent (BOLD) signal derived from resting state functional magnetic resonance imaging (fMRI) reflect spontaneous neuronal activity in pathological brain regions as well as in regions spared by epileptiform discharges. This is a crucial issue as coherent fluctuations of fMRI signals between remote brain areas are now widely used to define functional connectivity in physiology and in pathophysiology. We quantified functional connectivity using non-linear measures of cross-correlation between signals obtained from intracerebral EEG (iEEG) and resting-state functional MRI (fMRI) in 5 patients suffering from intractable temporal lobe epilepsy (TLE). Functional connectivity was quantified with both modalities in areas exhibiting different electrophysiological states (epileptic and non affected regions) during the interictal period. Functional connectivity as measured from the iEEG signal was higher in regions affected by electrical epileptiform abnormalities relative to non-affected areas, whereas an opposite pattern was found for functional connectivity measured from the BOLD signal. Significant negative correlations were found between the functional connectivities of iEEG and BOLD signal when considering all pairs of signals (theta, alpha, beta and broadband) and when considering pairs of signals in regions spared by epileptiform discharges (in broadband signal). This suggests differential effects of epileptic phenomena on electrophysiological and hemodynamic signals and/or an alteration of the neurovascular coupling secondary to pathological plasticity in TLE even in regions spared by epileptiform discharges. In addition, indices of directionality calculated from both modalities were consistent showing that the epileptogenic regions exert a significant influence onto the non epileptic areas during the interictal period. This study shows that functional connectivity measured by iEEG and BOLD signals give complementary but sometimes inconsistent information in TLE

    Human Processing of Behaviorally Relevant and Irrelevant Absence of Expected Rewards: A High-Resolution ERP Study

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    Acute lesions of the posterior medial orbitofrontal cortex (OFC) in humans may induce a state of reality confusion marked by confabulation, disorientation, and currently inappropriate actions. This clinical state is strongly associated with an inability to abandon previously valid anticipations, that is, extinction capacity. In healthy subjects, the filtering of memories according to their relation with ongoing reality is associated with activity in posterior medial OFC (area 13) and electrophysiologically expressed at 220–300 ms. These observations indicate that the human OFC also functions as a generic reality monitoring system. For this function, it is presumably more important for the OFC to evaluate the current behavioral appropriateness of anticipations rather than their hedonic value. In the present study, we put this hypothesis to the test. Participants performed a reversal learning task with intermittent absence of reward delivery. High-density evoked potential analysis showed that the omission of expected reward induced a specific electrocortical response in trials signaling the necessity to abandon the hitherto reward predicting choice, but not when omission of reward had no such connotation. This processing difference occurred at 200–300 ms. Source estimation using inverse solution analysis indicated that it emanated from the posterior medial OFC. We suggest that the human brain uses this signal from the OFC to keep thought and behavior in phase with reality
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