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Bimodal electroencephalography-functional magnetic resonance imaging dataset for inner-speech recognition.

ABSTRACT: The recognition of inner speech, which could give a 'voice' to patients that have no ability to speak or move, is a challenge for brain-computer interfaces (BCIs). A shortcoming of the available datasets is that they do not combine modalities to increase the performance of inner speech recognition. Multimodal datasets of brain data enable the fusion of neuroimaging modalities with complimentary properties, such as the high spatial resolution of functional magnetic resonance imaging (fMRI) and the temporal resolution of electroencephalography (EEG), and therefore are promising for decoding inner speech. This paper presents the first publicly available bimodal dataset containing EEG and fMRI data acquired nonsimultaneously during inner-speech production. Data were obtained from four healthy, right-handed participants during an inner-speech task with words in either a social or numerical category. Each of the 8-word stimuli were assessed with 40 trials, resulting in 320 trials in each modality for each participant. The aim of this work is to provide a publicly available bimodal dataset on inner speech, contributing towards speech prostheses.

SUBMITTER: Simistira Liwicki F

PROVIDER: S-EPMC10264396 | biostudies-literature | 2023 Jun

REPOSITORIES: biostudies-literature

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Bimodal electroencephalography-functional magnetic resonance imaging dataset for inner-speech recognition.

Simistira Liwicki Foteini F Gupta Vibha V Saini Rajkumar R De Kanjar K Abid Nosheen N Rakesh Sumit S Wellington Scott S Wilson Holly H Liwicki Marcus M Eriksson Johan J

Scientific data 20230613 1

The recognition of inner speech, which could give a 'voice' to patients that have no ability to speak or move, is a challenge for brain-computer interfaces (BCIs). A shortcoming of the available datasets is that they do not combine modalities to increase the performance of inner speech recognition. Multimodal datasets of brain data enable the fusion of neuroimaging modalities with complimentary properties, such as the high spatial resolution of functional magnetic resonance imaging (fMRI) and th ...[more]

PMID: 37311807

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Project description:PurposeSimultaneous electroencephalography/functional magnetic resonance imaging (EEG/fMRI) recording can noninvasively map in the whole brain the hemodynamic response following an interictal epileptic discharge. EEG/fMRI is gaining interest as a presurgical evaluation tool. This study aims to determine how hemodynamic responses related to epileptic activity can help predict surgical outcome in patients considered for epilepsy surgery.MethodsThirty-five consecutive patients with focal epilepsy who had significant hemodynamic responses and eventually surgical resection, were studied. The statistical map of hemodynamic responses were generated and co-registered to postoperative anatomic imaging. Patients were classified into four groups defined by the relative relationship between the location of the maximum hemodynamic response and the resection: group 1, fully concordant; group 2, partially concordant; group 3, partially discordant; and group 4, fully discordant. These findings were correlated with surgical outcome with at least 12-month follow-up.Key findingsTen patients in group 1 had the maximum t value (t-max) inside the resection; nine in group 2 had the t-max outside but close to the resection and the cluster with t-max overlapped the resection; five in group 3 had the t-max remote from resection, but with another less significant cluster in the resection; and 11 in group 4 had no response in the resection. The degree of concordance correlated largely with surgical outcome: a good surgical outcome (Engel's class I) was found in 7 of 10 patients of group 1, 4 of 9 of group 2, 3 of 5 of group 3, and only 1 of 11 of group 4. These results indicate that the partially concordant and partially discordant groups are best considered as inconclusive. In contrast, in the fully concordant and fully discordant groups, the sensitivity, specificity, positive predictive value, and negative predictive value were high, 87.5%, 76.9%, 70%, and 90.9%, respectively.SignificanceThis study demonstrates that hemodynamic responses related to epileptic activity can help delineate the epileptogenic region. Full concordance between maximum response and surgical resection is indicative of seizure freedom, whereas a resection leaving the maximum response intact is likely to lead to a poor outcome. EEG/fMRI is noninvasive but is limited to patients in whom interictal epileptic discharges can be recorded during the 60-90 min scan.

Project description:The neural correlates of anesthetic-induced unconsciousness have yet to be fully elucidated. Sedative and anesthetic states induced by propofol have been studied extensively, consistently revealing a decrease of frontoparietal and thalamocortical connectivity. There is, however, less understanding of the effects of halogenated ethers on functional brain networks.The authors recorded simultaneous resting-state functional magnetic resonance imaging and electroencephalography in 16 artificially ventilated volunteers during sevoflurane anesthesia at burst suppression and 3 and 2 vol% steady-state concentrations for 700?s each to assess functional connectivity changes compared to wakefulness. Electroencephalographic data were analyzed using symbolic transfer entropy (surrogate of information transfer) and permutation entropy (surrogate of cortical information processing). Functional magnetic resonance imaging data were analyzed by an independent component analysis and a region-of-interest-based analysis.Electroencephalographic analysis showed a significant reduction of anterior-to-posterior symbolic transfer entropy and global permutation entropy. At 2 vol% sevoflurane concentrations, frontal and thalamic networks identified by independent component analysis showed significantly reduced within-network connectivity. Primary sensory networks did not show a significant change. At burst suppression, all cortical networks showed significantly reduced functional connectivity. Region-of-interest-based thalamic connectivity at 2 vol% was significantly reduced to frontoparietal and posterior cingulate cortices but not to sensory areas.Sevoflurane decreased frontal and thalamocortical connectivity. The changes in blood oxygenation level dependent connectivity were consistent with reduced anterior-to-posterior directed connectivity and reduced cortical information processing. These data advance the understanding of sevoflurane-induced unconsciousness and contribute to a neural basis of electroencephalographic measures that hold promise for intraoperative anesthesia monitoring.

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Bimodal electroencephalography-functional magnetic resonance imaging dataset for inner-speech recognition.

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Bimodal electroencephalography-functional magnetic resonance imaging dataset for inner-speech recognition.

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