Visualization-Based Mapping of Language Function in the Brain

Cortical language maps, obtained through intraoperative electrical stimulation studies, provide a rich source of information for research on language organization. Previous studies have shown interesting correlations between the distribution of essential language sites and such behavioral indicators as verbal IQ and have provided suggestive evidence for regarding human language cortex as an organization of multiple distributed systems. Noninvasive studies using ECoG, PET, and functional MR lend support to this model; however, there as yet are no studies that integrate these two forms of information. In this paper we describe a method for mapping the stimulation data onto a 3-D MRI-based neuroanatomic model of the individual patient. The mapping is done by comparing an intraoperative photograph of the exposed cortical surface with a computer-based MR visualization of the surface, interactively indicating corresponding stimulation sites, and recording 3-D MR machine coordinates of the indicated sites. Repeatability studies were performed to validate the accuracy of the mapping technique. Six observers—a neurosurgeon, a radiologist, and four computer scientists, independently mapped 218 stimulation sites from 12 patients. The mean distance of a mapping from the mean location of each site was 2.07 mm, with a standard deviation of 1.5 mm, or within 5.07 mm with 95% confidence. Since the surgical sites are accurate within approximately 1 cm, these results show that the visualization-based approach is accurate within the limits of the stimulation maps. When incorporated within the kind of information system envisioned by the Human Brain Project, this anatomically based method will not only provide a key link between noninvasive and invasive approaches to understanding language organization, but will also provide the basis for studying the relationship between language function and anatomical variability

Interactive Web Application for Exploring Matrices of Neural Connectivity

We present here a browser-based application for visualizing patterns of connectivity in 3D stacked data matrices with large numbers of pairwise relations. Visualizing a connectivity matrix, looking for trends and patterns, and dynamically manipulating these values is a challenge for scientists from diverse fields, including neuroscience and genomics. In particular, high-dimensional neural data include those acquired via electroencephalography (EEG), electrocorticography (ECoG), magnetoencephalography (MEG), and functional MRI. Neural connectivity data contains multivariate attributes for each edge between different brain regions, which motivated our lightweight, open source, easy-to-use visualization tool for the exploration of these connectivity matrices to highlight connections of interest. Here we present a client-side, mobile-compatible visualization tool written entirely in HTML5/JavaScript that allows in-browser manipulation of user-defined files for exploration of brain connectivity. Visualizations can highlight different aspects of the data simultaneously across different dimensions. Input files are in JSON format, and custom Python scripts have been written to parse MATLAB or Python data files into JSON-loadable format. We demonstrate the analysis of connectivity data acquired via human ECoG recordings as a domain-specific implementation of our application. We envision applications for this interactive tool in fields seeking to visualize pairwise connectivity.Comment: 4 pages, IEEE NER 201

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

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

Enhanced activation of the left inferior frontal gyrus in deaf and dyslexic adults during rhyming

Hearing developmental dyslexics and profoundly deaf individuals both have difficulties processing the internal structure of words (phonological processing) and learning to read. In hearing non-impaired readers, the development of phonological representations depends on audition. In hearing dyslexics, many argue, auditory processes may be impaired. In congenitally profoundly deaf individuals, auditory speech processing is essentially absent. Two separate literatures have previously reported enhanced activation in the left inferior frontal gyrus in both deaf and dyslexic adults when contrasted with hearing non-dyslexics during reading or phonological tasks. Here, we used a rhyme judgement task to compare adults from these two special populations to a hearing non-dyslexic control group. All groups were matched on non-verbal intelligence quotient, reading age and rhyme performance. Picture stimuli were used since this requires participants to generate their own phonological representations, rather than have them partially provided via text. By testing well-matched groups of participants on the same task, we aimed to establish whether previous literatures reporting differences between individuals with and without phonological processing difficulties have identified the same regions of differential activation in these two distinct populations. The data indicate greater activation in the deaf and dyslexic groups than in the hearing non-dyslexic group across a large portion of the left inferior frontal gyrus. This includes the pars triangularis, extending superiorly into the middle frontal gyrus and posteriorly to include the pars opercularis, and the junction with the ventral precentral gyrus. Within the left inferior frontal gyrus, there was variability between the two groups with phonological processing difficulties. The superior posterior tip of the left pars opercularis, extending into the precentral gyrus, was activated to a greater extent by deaf than dyslexic participants, whereas the superior posterior portion of the pars triangularis extending into the ventral pars opercularis, was activated to a greater extent by dyslexic than deaf participants. Whether these regions play differing roles in compensating for poor phonological processing is not clear. However, we argue that our main finding of greater inferior frontal gyrus activation in both groups with phonological processing difficulties in contrast to controls suggests greater reliance on the articulatory component of speech during phonological processing when auditory processes are absent (deaf group) or impaired (dyslexic group). Thus, the brain appears to develop a similar solution to a processing problem that has different antecedents in these two populations

Dynamic Modulation of Local Population Activity by Rhythm Phase in Human Occipital Cortex During a Visual Search Task

Brain rhythms are more than just passive phenomena in visual cortex. For the first time, we show that the physiology underlying brain rhythms actively suppresses and releases cortical areas on a second-to-second basis during visual processing. Furthermore, their influence is specific at the scale of individual gyri. We quantified the interaction between broadband spectral change and brain rhythms on a second-to-second basis in electrocorticographic (ECoG) measurement of brain surface potentials in five human subjects during a visual search task. Comparison of visual search epochs with a blank screen baseline revealed changes in the raw potential, the amplitude of rhythmic activity, and in the decoupled broadband spectral amplitude. We present new methods to characterize the intensity and preferred phase of coupling between broadband power and band-limited rhythms, and to estimate the magnitude of rhythm-to-broadband modulation on a trial-by-trial basis. These tools revealed numerous coupling motifs between the phase of low-frequency (δ, θ, α, β, and γ band) rhythms and the amplitude of broadband spectral change. In the θ and β ranges, the coupling of phase to broadband change is dynamic during visual processing, decreasing in some occipital areas and increasing in others, in a gyrally specific pattern. Finally, we demonstrate that the rhythms interact with one another across frequency ranges, and across cortical sites

Quantifying interictal intracranial EEG to predict focal epilepsy

Intracranial EEG (IEEG) is used for 2 main purposes, to determine: (1) if epileptic networks are amenable to focal treatment and (2) where to intervene. Currently these questions are answered qualitatively and sometimes differently across centers. There is a need for objective, standardized methods to guide surgical decision making and to enable large scale data analysis across centers and prospective clinical trials. We analyzed interictal data from 101 patients with drug resistant epilepsy who underwent presurgical evaluation with IEEG. We chose interictal data because of its potential to reduce the morbidity and cost associated with ictal recording. 65 patients had unifocal seizure onset on IEEG, and 36 were non-focal or multi-focal. We quantified the spatial dispersion of implanted electrodes and interictal IEEG abnormalities for each patient. We compared these measures against the 5 Sense Score (5SS), a pre-implant estimate of the likelihood of focal seizure onset, and assessed their ability to predict the clinicians choice of therapeutic intervention and the patient outcome. The spatial dispersion of IEEG electrodes predicted network focality with precision similar to the 5SS (AUC = 0.67), indicating that electrode placement accurately reflected pre-implant information. A cross-validated model combining the 5SS and the spatial dispersion of interictal IEEG abnormalities significantly improved this prediction (AUC = 0.79; p<0.05). The combined model predicted ultimate treatment strategy (surgery vs. device) with an AUC of 0.81 and post-surgical outcome at 2 years with an AUC of 0.70. The 5SS, interictal IEEG, and electrode placement were not correlated and provided complementary information. Quantitative, interictal IEEG significantly improved upon pre-implant estimates of network focality and predicted treatment with precision approaching that of clinical experts.Comment: 25 pages, 4 Figures, 1 tabl

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

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