Immediate neural impact and incomplete compensation after semantic hub disconnection
<p>Data repository for "Immediate neural impact and incomplete compensation after semantic hub disconnection"</p> <p>Abstract: The human brain extracts meaning using an extensive neural system for semantic knowledge. <br> Whether broadly distributed systems depend on or can compensate after losing a highly interconnected hub is controversial. <br> We report rare intracranial recordings from two patients during a speech prediction task, <br> obtained minutes before and after neurosurgical treatment requiring disconnection of the left anterior temporal lobe (ATL), <br> a candidate semantic knowledge hub. Informed by modern diaschisis and predictive coding frameworks, <br> we tested hypotheses ranging from solely neural network disruption to complete compensation by <br> the indirectly affected language-related and speech processing sites. Immediately after ATL disconnection, <br> we observed substantial neurophysiological alterations in the recorded frontal and auditory sites, <br> providing direct evidence for the importance of the ATL as a semantic hub. We also obtained evidence for rapid, albeit incomplete, <br> attempts at neural network compensation, with neural impact largely in the forms stipulated by the predictive coding framework, <br> in specificity, and the modern diaschisis framework, more generally. The overall results validate these frameworks and reveal <br> a remarkable immediate impact and capability of the human brain to adjust after losing a brain hub.</p> <p>In this dataset, you will be able to access the intracranial recordings from 2 subjects, <br> with the description of recording channels, along with event codes and times in ms. Both the raw data, <br> and the preprocessed (DBT denoised and SVD applied; matrix in times x channels format, 1000 Hz sampling rate) data are available. For further information, please consult the paper (currently in press, but will provide a DOI when available), <br> or email zsuzsanna-kocsis@uiowa.edu or zkocsis@andrew.cmu.edu<br> </p>
ShareScore
40/100
Overall dataset sharing score
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These five areas show where the dataset supports — or may limit — practical reuse.
- Stewardship
- 8
- Harmonization
- 4
- Access
- 16
- Reuse readiness
- 8
- Engagement
- 4