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EEG

EEG: explore 4 source-linked works published from 2026 to 2026, with original documents and citations.

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Sources: pubmed. Collection updated 2026-10-11. Counts describe this index, not the complete source archives.

PubMed2026

Electroencephalographic evidence of cortical network disruption preceding overt cardioinhibition during tilt-induced reflex syncope.

OBJECTIVE: Reflex syncope is a common cause of transient loss of consciousness. However, the early cerebral mechanisms underlying cardiovascular changes remain poorly understood. Our objective was to investigate early cerebral changes by quantitatively analyzing EEG activity preceding overt cardioinhibition during tilt-induced reflex syncope. METHODS: EEG recordings from patients undergoing tilt testing were retrospectively analyzed. Patients who experienced reflex syncope were compared to those who did not. Spectral and functional connectivity analyses were performed across baseline, pre-cardioinhibition, and syncopal phases. RESULTS: Prior to the onset of cardioinhibitory pathological reflex, a significant increase in theta-band spectral power was observed in the right temporal region, accompanied by a widespread increase in functional connectivity within the same frequency band. These findings suggest the involvement of brain networks before cardioinhibition. CONCLUSIONS: EEG changes in the theta band (power and functional connectivity) were observed before overt cardioinhibition during tilt-induced reflex syncope. SIGNIFICANCE: Our findings support the hypothesis of cortical processing preceding cardioinhibition in reflex syncope. EEG may represent a valuable complementary tool for improving the understanding and diagnosis of these events.

Humans↗

PubMed2026

Predicting training outcomes for developmental dyslexia from EEG data.

Developmental dyslexia (DD) is characterised by lower-than-average reading abilities and is diagnosed in approximately 10% of individuals. The societal barriers may limit professional fulfilment and psychological wellbeing of individuals with DD, calling for the development of effective interventions to counteract them. As DD is associated with challenges in both phonological and visuo-attentional domains, different longitudinal training approaches were developed to strengthen them. However, they require a considerable amount of personal, social and economic resources and the outcomes may vary depending on individual differences in behavioural and neurophysiological functionality. Hence, predicting training outcomes might help in developing personalised treatment protocols and optimising the use of resources. In the present work we applied machine learning to resting-state EEG to predict longitudinal training outcomes in adults with DD enrolled in a randomized clinical trial. In particular, one group received a visuo-attentional training combined with transcranial alternating current stimulation (tACS), another group received visuo-attentional training with sham/placebo stimulation, and the third group received a phonological training with sham/placebo stimulation. The improvement in text reading speed was associated with spectral power in low-beta and individual frequencies in the alpha (IAF) and beta (IBF) bands, while the improvement in pseudoword reading was associated with IBF. The findings highlight the potential of capturing neural markers of treatment responsiveness in DD. Future studies should focus on the generalisability of predictive models to real-world settings, while investigating whether specific EEG markers predict responsiveness to distinct remediation protocols, thus supporting the development of personalised interventions.

Humans↗

PubMed2026

Dissociable neural mechanisms of cognitive enhancement through transcranial stimulation and behavioral training.

BACKGROUND: Transcranial direct current stimulation (tDCS) and adaptive working memory (WM) training are promising cognitive enhancement approaches; however, their neural mechanisms and potential synergies remain poorly understood. OBJECTIVE: We directly compared how tDCS and WM training modulate neural oscillations during WM performance and examined whether combining both interventions produces additive effects. METHODS: We randomized 112 healthy adults into four groups: control (sham tDCS + non-adaptive 1-back), tDCS-only (active tDCS + non-adaptive 1-back), training-only (sham tDCS + adaptive n-back training), or combined (active tDCS + adaptive training). Participants underwent five daily intervention sessions. We recorded high-density EEG during transfer n-back tasks at baseline, post-intervention, and one-week follow-up. RESULTS: All active interventions improved WM performance relative to the control group, with the combined group showing the largest gains (n-back accuracy: +15.6% vs. + 10.1% tDCS-only, +9.7% training-only, +0.7% control; all p < 0.001). Critically, tDCS selectively increased gamma-band (30-50 Hz) power in the frontal and parietal regions (cluster p = 0.018, d > 1.0), whereas WM training enhanced frontal theta-band (4-8 Hz) power and theta-gamma phase-amplitude coupling (both cluster p < 0.012, d > 0.85). The combined group exhibited both neural signatures. Brain-behavior correlations revealed dissociable relationships: gamma increases predicted n-back accuracy improvements (r = 0.61, p < 0.001), whereas theta enhancements correlated with operation span gains (r = 0.58, p = 0.002). CONCLUSIONS: tDCS and WM training enhance cognition through distinct yet complementary neural mechanisms: tDCS via gamma-mediated cortical excitability and WM training via theta-mediated cognitive control. These findings provide neurophysiological evidence for multimodal enhancement strategies that target parallel pathways within WM networks.

Humans↗

PubMed2026

Catecholaminergic Contributions to Inhibitory Control Following Physical Fatigue: Behavioral and Neurophysiological Findings.

Acute physical fatigue can impair cognitive control, yet its underlying neurochemical mechanisms remain unclear. This study investigated whether catecholaminergic modulation influences behavioral and neural markers of inhibitory control following physical fatigue. Eighteen healthy, recreationally active adults (9 males, 9 females; 23.4 ± 2.2 years) completed a randomized, triple-blind, placebo-controlled crossover study. On separate visits, participants received methylphenidate (MPH; 20 mg; a dopamine and noradrenaline reuptake inhibitor), reboxetine (REB; 8 mg; a noradrenaline reuptake inhibitor), or placebo. Physical fatigue was induced by repeated bilateral leg extensions to task failure. Cognitive performance was assessed before and after physical fatigue using a Go/No-Go task with electroencephalographic recording. Behavioral outcomes included reaction time and accuracy, while event-related potentials measured neural stages of response execution and inhibition (N2 and P3). Mixed-effects models were used for statistical analysis. For No-Go trials, a significant MPH × Time interaction was observed for accuracy (p = 0.008), with improved post-fatigue performance following MPH administration (p = 0.048). At the neural level, MPH was associated with shorter fronto-central No-Go N2 latency (p = 0.038) and altered fatigue-related changes in No-Go P3 latency (p = 0.047). REB did not produce comparable behavioral or neural effects. These findings provide pharmacological evidence that catecholaminergic mechanisms contribute to inhibitory control following physical fatigue. The differential effects of MPH and REB suggest that selective noradrenergic enhancement alone is insufficient to maintain inhibitory control following physical fatigue. Instead, the findings implicate broader dopaminergic and noradrenergic mechanisms, potentially involving alterations in the temporal dynamics of inhibitory processing. TRIAL REGISTRATION: (G095422N and identifier NCT05880342).

Adult↗

Compare source metadata on this page

Work	Published	Source identifier	Source
Electroencephalographic evidence of cortical network disruption preceding overt cardioinhibition during tilt-induced reflex syncope.	2026-08-15	PMID 42617512	pubmed
Predicting training outcomes for developmental dyslexia from EEG data.	2026-08-14	PMID 42600369	pubmed
Dissociable neural mechanisms of cognitive enhancement through transcranial stimulation and behavioral training.	2026-08-12	PMID 42586193	pubmed
Catecholaminergic Contributions to Inhibitory Control Following Physical Fatigue: Behavioral and Neurophysiological Findings.	2026	PMID 42608643	pubmed

These are bibliographic comparisons, not experimental rankings. Follow the original document for methods and conditions.