Neuronal activity in the human lateral temporal lobe. II. Responses to the subjects own voice.

We have recorded neuronal responses in the lateral temporal lobe of man to overt speech during open brain surgery for epilepsy. Tests included overt naming of objects and reading words or short sentences shown on a projector screen, repetition of tape recorded words or sentences presented over a loudspeaker, and free conversation. Neuronal activity in the dominant and non-dominant temporal lobe were about equally affected by overt speech. As during listening to language (see Creutzfeldt et al. 1989), responses differed between recordings from sites in the superior and the middle or inferior temporal gyrus. In the superior temporal gyrus all neurons responded clearly and each in a characteristic manner. Activation could be related to phonemic aspects, to segmentation or to the length of spoken words or sentences. However, neurons were mostly differently affected by listening to words and language as compared to overt speaking. In neuronal populations recorded simultaneously with one or two microelectrodes, some neurons responded predominantly to one or the other type of speech. Excitatory responses during overt speaking were always auditory. In the middle temporal gyrus more neurons (about 2/3) responded to overt speaking than to listening alone. Activations elicited during overt speech were seen in about 1/3 of our sample, but they were more sluggish than those recorded in the superior gyrus. A prominent feature was suppression of on-going activity, which we found in about 1/3 of middle and in some superior temporal gyrus neurons. This suppression could preced vocalization by up to a few hundred ms, and could outlast it by up to 1 s. Evoked ECoG-potentials to words heard or spoken were different, and those to overt speech were more widespread

Neuronal activity in the human lateral temporal lobe. I. Responses to speech.

Single and multiple unit neuronal activity was recorded from the cortex of the lateral temporal lobe in conscious humans during open brain surgery for the treatment of epilepsy. Recordings were obtained from the right and left superior, middle and inferior temporal gyrus of 34 patients (41 recording sites). Recordings were restricted to regions to be resected during subsequent surgery. This excluded recordings from language areas proper. Neuronal responses to words and sentences presented over a loudspeaker and during free conversation were recorded. No significant differences between the right and left hemisphere were obvious. All neurons in the superior temporal gyrus responded to various aspects of spoken language with temporally well defined activation/inhibition patterns, but not or only little to non-linguistic noises or tones. Excitatory responses were typically short or prolonged (up to several hundred ms) bursts of discharges at rates above 20/sec, reaching peak rates of 50–100/s. Such responses could be specifically related to certain combinations of consonants suggesting a function in categorization, they could depend on word length, could differentiate between polysyllabic and compound words of the same length or could be unspecifically related to language as such. No formant specific responses were found, but the prolonged excitations across syllables suggest that consonant/vowel combinations may play a role for some activation patterns. Responses of some neurons (or neuronal populations) depended on the attention paid to the words and sentences, or the task connected with them (repeat words, speech addressed to the patient demanding something). Neurons in the middle and inferior temporal gyrus were only little affected by listening to single words or sentences, but some were unspecifically activated by words or while listening to sentences. Excitatory responses varied within a limited range of discharge rates usually below 5–10/s. Phonetic distortion of spoken language could reduce responses in superior temporal gyrus neurons, but also the slight changes in discharge rate of middle temporal neurons could be absent during distorted and uncomprehensible speech sounds. We conclude that superior temporal gyrus neuron responses reflect some general phonetic but not semantic aspects of spoken language. Middle and inferior temporal gyrus neurons do not signal phonetic aspects of language, but may be involved in understanding language under certain conditions

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

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

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

Evaluating spatial normalization methods for the human brain

Cortical stimulation mapping (CSM) studies have shown cortical locations for language function are highly variable from one subject to the next. If individual variation can be normalized, patterns of language organization may emerge that were heretofore hidden. In order to uncover this pattern, computer-aided spatial normalization to a common atlas is required. Our problem was how to determine which spatial normalization method was best for the given research application. We developed key metrics to measure accuracy of a surface-based (Caret) and volume-based (SPM2) method. We specified that the optimal method would i) minimize variation as measured by spread reduction between CSM language sites across subjects while also ii) preserving anatomical localization of all CSM sites. Eleven subject’s structural MR data and corresponding CSM site coordinates were registered to the colin27 human brain atlas using each method. Local analysis showed that mapping error rates for both methods were highest in morphological regions with the greatest difference between source and target. Also, SPM2 mapped significantly less type 2 errors. Although our experiment did not show statistically significant global differences between the methods, our methodology provided valuable insights into the pros and cons of each

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