The functional consequences of focal brain injury are thought to be contingent on neuronal alterations extending beyond the area of structural damage. This phenomenon, also known as diaschisis, has clinical and metabolic correlates but lacks a clear electrophysiological counterpart, except for the long-standing evidence of a relative EEG slowing over the injured hemisphere. Here, we aim at testing whether this EEG slowing is linked to the pathological intrusion of sleep-like cortical dynamics within an awake brain. We used a combination of transcranial magnetic stimulation and electroencephalography (TMS/EEG) to study cortical reactivity in a cohort of 30 conscious awake patients with chronic focal and multifocal brain injuries of ischaemic, haemorrhagic and traumatic aetiology. We found that different patterns of cortical reactivity typically associated with different brain states (coma, sleep, wakefulness) can coexist within the same brain. Specifically, we detected the occurrence of prominent sleep-like TMS-evoked slow waves and off-periods—reflecting transient suppressions of neuronal activity—in the area surrounding focal cortical injuries. These perilesional sleep-like responses were associated with a local disruption of signal complexity whereas complex responses typical of the awake brain were present when stimulating the contralesional hemisphere. These results shed light on the electrophysiological properties of the tissue surrounding focal brain injuries in humans. Perilesional sleep-like off-periods can disrupt network activity but are potentially reversible, thus representing a principled read-out for the neurophysiological assessment of stroke patients, as well as an interesting target for rehabilitation.

The Brain Imaging Data Structure (BIDS) is a community-driven specification for organizing neuroscience data and metadata with the aim to make datasets more transparent, reusable, and reproducible. Intracranial electroencephalography (iEEG) data offer a unique combination of high spatial and temporal resolution measurements of the living human brain. To improve internal (re)use and external sharing of these unique data, we present a specification for storing and sharing iEEG data: iEEG-BIDS.

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