Stroke affects nearly 800,000 individuals only in the United States each year and is one of the main causes of disability in adults (Dobkin, 2005). In contrast with the significant progress in acute therapy (i.e., thrombolysis and thrombectomy), there have not been rehabilitation therapeutic breakthroughs enabling patients to substantially recover from neurological deficits beyond 24 h after stroke (Grefkes and Fink, 2020). New strategies to improve recovery after stroke may benefit from a better understanding of network effects induced by focal brain lesions. Indeed, it is currently well recognized that focal lesions, such as stroke, cause direct and indirect effects that extend beyond the borders of the primary anatomical lesions (Carrera and Tononi, 2014).

Here, the concept of diaschisis refers to any remote alteration directly caused by the lesion, including a spectrum of neurophysiological effects, from focal to connectomal (Carrera and Tononi, 2014).

The underlying network alterations have been studied mainly via neuroimaging techniques such as functional magnetic resonance imaging (fMRI), diffusion tensor imaging (DTI), and positron emission tomography (PET) (He et al., 2007; Baldassarre et al., 2016; Forkel and de Schotten, 2020). An important result derived from this new network-based perspective has been the evidence that functional disconnection correlates with neurological deficits and behavioral outcomes after stroke and the normalization of the functional connectivity patterns predicts longitudinal behavioral recovery (Siegel et al., 2016). This evidence is relevant for its clinical implications, such as the adoption of neuromodulation aiming at restoring network dysfunction (Griffis et al., 2020).

Network effects of focal lesions can be of multiple natures (e.g., functional, structural, and electro-cortical). Despite the extensive adoption of fMRI and DTI in research studies, these techniques do not allow us to distinguish areas with slow-wave activities (similar to sleep and thus potentially “arousable”) that could be potential targets of neuromodulation versus silent (and therefore irreversibly damaged) areas. Moreover, the high cost of fMRI and DTI neuroimaging techniques limits their application in clinical practice.

Transcranial magnetic stimulation–EEG (TMS-EEG) is a promising tool that can distinguish between inactivated regions versus regions with slow-wave activities (Sarasso et al., 2020)_. However, this technique requires prolonged acquisitions. High-density EEG (HD-EEG) also can distinguish between regions that are silent versus regions displaying slow activity, and it is more portable and lower cost. HD-EEG overcomes the limit of the low spatial resolution of standard EEG. HD-EEG quantitative analysis has been demonstrated to be more sensitive to detecting focal slowing (Boly et al., 2017) and allows us to perform connectivity analysis in source space that is more comparable to previous fMRI connectivity studies. So far, only a minority of studies have applied HD-EEG in acute stroke patients. The studies show the presence of slow-wave activity in the delta and theta range at the scalp level ipsilateral to the infarct (Poryazova et al., 2015). Some studies also observe an increase in delta power in the contralateral hemisphere (Assenza et al., 2013) suggesting distant effects.

However, compared to these previous studies, we wanted to highlight the feasibility and the significance of mapping the local and network consequences of focal lesions using HD-EEG in the acute phase as the starting point for clinical/therapeutic applications that, of necessity, need to be personalized and detailed.

In other words, the mapping of the unique neurophysiological signatures of the patient and his/her neurological deficits is the conditio sine qua non if we want to implement neuromodulation strategies in the clinical practice at the bedside for a particular patient.

Moreover, this single study’s HD-EEG source reconstruction was not applied in previous studies to distinguish more accurately the slowing in lesional vs. perilesional or remote areas. First, we quantified the presence and the cortical source of local and distant slowing associated with the ischemic/hypoperfused regions. Second, an explorative connectivity analysis was performed to search for possible long-range connectivity effects in the delta band induced by the focal lesion.

The main findings of this HD-EEG stroke case study were (1) the presence of delta activity beyond the ischemic focus, in both perilesional and distant regions (Figures 2, 3); (2) the loss of posterior alpha activity (Figure 2); and (3) delta connectivity over the stroke hemisphere (Figure 4).

Our findings of percolation of slow-wave activity around the ischemic core are in line with studies using TMS-EEG, which revealed the presence of sleep-like responses during wake over the perilesional areas (Sarasso et al., 2020). Considering that HD-EEG, as shown in this study, has the advantages of being more feasible and accessible than TMS-EEG, its application is promising on a larger scale for stroke patients that could benefit from neurophysiological brain mapping.

Similarly, in recent years, studies applying EEG and HD-EEG in acute stroke patients have found distant neurophysiological effects ipsilateral to the infarct (Poryazova et al., 2015), but with also some evidence in the contralateral hemisphere (Assenza et al., 2013; Wu et al., 2016).

However, only a minority of the studies applied HD-EEG, despite the fact that HD-EEG provides better quality of the signal and better data for more sophisticated and detailed analysis (Lanzone et al., 2023), and it is more sensitive in the detection of focal slowing (Boly et al., 2017).

Here, we applied HD-EEG to obtain an individualized neurophysiological mapping and, implementing the use of source reconstruction analysis, we could clarify how slowing was localized not only in the lesion but also in specific perilesional and contralateral regions that are interconnected with the infarct area (Figure 3).

A post-stroke individual and high-spatial resolution mapping approach can ultimately better translate into the development of neuromodulatory strategies for rehabilitation that, of necessity, need to be personalized.

Of note, in our patient, there was also a loss of alpha power over the occipital regions (Figure 2). As these regions were neither ischemic nor hypoperfused, this effect may also represent a sign of long-range cortical–subcortical effect via the thalamus and inter-hemispheric (dis)-connections (Juhász et al., 1997).

Understanding network effects induced by focal lesions has relevant clinical implications. Neurological symptoms, especially cognitive deficits, seem to correlate better with their impact on brain networks, rather than solely the lesion site (Siegel et al., 2016). This has already been demonstrated in syndromes like neglect using fMRI and DTI [e.g., functional impairment of the dorsal attention network (DAN) induced by lesions belonging to the ventral attention network (VAN) (Corbetta and Shulman, 2011); increased latencies of visual evoked potentials in neglect patients (Spinelli et al., 1994)].

Interestingly, our patient had right-sided neglect fitting with evidence on HD-EEG of delta activity over the left superior parietal lobule (i.e., the posterior node of the left dorsal attention network) vis-a-vis a lesion involving the ventral system (Figure 3).

Instead, there was a difference in the involvement of the two language streams (ventral affected vs. dorsal not affected).

Intriguingly, at the neurological follow-up in the chronic phase, neglect was still present while aphasia was improved.

We hypothesized that the different degrees of involvement of the 2 function-related systems could account for the different evolution of the deficits in the recovery phase.

Understanding the cortical topography of the network dysfunction via HD-EEG could be predictive of behavioral deficits in a way complementary to fMRI and DTI. However, detailed neuropsychological assessment in the acute and chronic phases is necessary. Moreover, an exploratory connectivity analysis on delta power using graph theory showed the presence of delta connectivity in the lesioned hemisphere (Figure 4), though without reaching statistical significance in the difference with the contralateral hemisphere. Future studies may try to investigate whether delta connectivity” reflects a pathological synchronization of cortical regions (due to disconnection) or a reflection of plastic changes in areas interconnected with the focal lesion.

In this case report, we confirmed the feasibility of performing HD-EEG in the acute phase of stroke to quantify the network effects of focal lesions. HD-EEG analysis revealed the presence of slowing not only around the lesion but also in specific cortical regions distant from the stroke, prominently in the ipsilateral hemisphere (Figures 2–4).

For this case study, the comparison between neuroimaging and delta source maps was based on the review of the two modalities by clinical experts.

For future studies, multimodal analysis would benefit from the development/use of software/toolboxes able to easily represent different signals on the patient’s anatomical brain. Studies with cohorts of stroke patients and controls may further clarify the relationship between electro-cortical disconnection observed with HD-EEG and the structural and functional disconnections induced by focal lesions quantified by fMRI, DTI, and PET (Monai et al., 2023). Finally, the correlation between electro-cortical network effects and clinical deficits needs to be further investigated in future studies.

In the long run, electro-cortical network disconnection with HD-EEG may become a personalized predictive biomarker to guide rehabilitation strategies with neuromodulation techniques. In particular, neuromodulation strategies may aim to target distant regions that are dysfunctional (and therefore likely contributing to the neurological deficits), though still anatomically intact, and therefore potentially “arousable,” with the final aim to improve the recovery from neurological/neuropsychological deficits. In our patient, we would expect that neuromodulation of the dorsal attention network (shown to be deactivated by HD-EEG while still intact Figure 3), could contribute to the recovery from neglect.

In conclusion, we show that modern tools of EEG, in particular the use of source reconstruction with HD-EEG to better increase spatial information, can gain insightful findings when applied to individual patients to envision a personalized neuromodulation approach.