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Immediate neural impact and incomplete compensation after semantic hub disconnection

<p>Data repository for &quot;Immediate neural impact and incomplete compensation after semantic hub disconnection&quot;</p> <p>Abstract: The human brain extracts meaning using an extensive neural system for semantic knowledge.&nbsp;<br> Whether broadly distributed systems depend on or can compensate after losing a highly interconnected hub is controversial.&nbsp;<br> We report rare intracranial recordings from two patients during a speech prediction task,&nbsp;<br> obtained minutes before and after neurosurgical treatment requiring disconnection of the left anterior temporal lobe (ATL),&nbsp;<br> a candidate semantic knowledge hub. Informed by modern diaschisis and predictive coding frameworks,&nbsp;<br> we tested hypotheses ranging from solely neural network disruption to complete compensation by&nbsp;<br> the indirectly affected language-related and speech processing sites. Immediately after ATL disconnection,&nbsp;<br> we observed substantial neurophysiological alterations in the recorded frontal and auditory sites,&nbsp;<br> providing direct evidence for the importance of the ATL as a semantic hub. We also obtained evidence for rapid, albeit incomplete,&nbsp;<br> attempts at neural network compensation, with neural impact largely in the forms stipulated by the predictive coding framework,&nbsp;<br> in specificity, and the modern diaschisis framework, more generally. The overall results validate these frameworks and reveal&nbsp;<br> a remarkable immediate impact and capability of the human brain to adjust after losing a brain hub.</p> <p>In this dataset,&nbsp;you will be able to access the intracranial recordings from 2 subjects,&nbsp;<br> with the description of recording channels, along with event codes and times in ms. Both the raw data,&nbsp;<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,&nbsp;please consult the paper (currently in press, but will provide a DOI&nbsp;when available),&nbsp;<br> or email zsuzsanna-kocsis@uiowa.edu or zkocsis@andrew.cmu.edu<br> &nbsp;</p>

ShareScore

40/100

Overall dataset sharing score

Score breakdown

These five areas show where the dataset supports — or may limit — practical reuse.

Stewardship
8
Harmonization
4
Access
16
Reuse readiness
8
Engagement
4

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