bioRxiv Science⌕ Search

bioRxiv · 10.64898/2026.10.26.761837

How well does electrical source imaging reconstruct neural time series? Evidence from simultaneous scalp and intracranial EEG recordings

Abstract

Electrical source imaging (ESI) estimates neural activity from scalp EEG, but its ability to reconstruct the temporal dynamics of spontaneous brain activity beyond source localization remains unclear. This is assessed using simultaneous high-density EEG and intracranial EEG (iEEG) recordings during spontaneous activity in 34 patients with drug-resistant focal epilepsy. Four ESI approaches (three distributed source models and one beamformer) are applied to estimate neural activity, which is then projected onto iEEG electrode locations to generate virtual iEEG signals for comparison with measured recordings. Reconstruction fidelity is quantified using Pearson correlations between actual and virtual iEEG signals, while spatial accuracy is assessed through peak localization error and spatial deviation derived from point-spread and cross-talk functions. Analyses are performed in broadband and delta, theta, alpha, and beta bands. Temporal reconstruction remains limited, with the highest estimated correlation reaching 0.126, localization errors of approximately 3 cm, and substantial spatial leakage. Reconstruction quality decreases with electrode depth and increasing frequency, while improving with higher epileptic spike rates. No single method is optimal across all metrics, although beamforming shows the weakest temporal reconstruction. These findings indicate that ESI only partially captures spontaneous intracranial dynamics and define spatial and temporal constraints for interpreting EEG-based source reconstructions.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Dimou, M., Beumer, S., Pigorini, A., Mikulan, E., Calcagno, A., Spinelli, L., Momjian, S., Seeck, M., Vulliemoz, S., Roehri, N.. 2026-10-27. How well does electrical source imaging reconstruct neural time series? Evidence from simultaneous scalp and intracranial EEG recordings. https://doi.org/10.64898/2026.10.26.761837

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

Rapid switching of in-phase and anti-phase interhemispheric rhythms within a single theta cycle: a mechanistic explanation

The granular retrosplenial cortex (RSG) supports memory consolidation and spatial navigation. In vivo recordings of local field potential (LFP) from RSG reveal coexisting gamma (30-80 Hz) and spline (100-160 Hz) oscillations, coupled to distinct phases of the background theta ([~]8 Hz) rhythm. Remarkably, bilateral recordings reveal that gamma and splines exhibit divergent interhemispheric phase relationships: gamma is in-phase across hemispheres, while splines are anti-phase. Here, using numerical bifurcation analysis of next-generation neural mass models, we show that RSG oscillations within a single hemisphere can be understood as alternation of PING (pyramidal-interneuron gamma) and ING (interneuron gamma) mechanisms in an excitatory-inhibitory network. Theta-frequency external drive to the inhibitory population switches the network between these two rhythms. Next, we build canonical interhemispheric circuits, composed of two such excitatory-inhibitory modules, delay-coupled across hemispheres. These circuits switch between in-phase gamma and anti-phase splines within a single theta cycle, reproducing the cross-spectral statistics of experimental RSG recordings. Finally, we present analytical results for threshold-linear neural mass models, showing cross-hemispheric phase patterning is governed by the ratio of cross-hemispheric delay to local inhibitory delay; we obtain explicit ranges of this ratio for which RSG-like patterning could be expected. Our work establishes that the unique oscillatory profile of RSG can be explained parsimoniously by minimal interhemispheric circuit configurations and provides a framework for experimental interrogation of interhemispheric rhythms.

neuroscience↗

Brain representations of visual short-term memories during healthy human aging: occipital decline and frontoparietal compensation

Visual short-term memory declines steeply with age, but the link to neural representations of memory content remains unknown. We used fMRI decoding to relate remembered motion-direction representations in visual and frontoparietal cortex to age and performance, in 115 adults, aged 25-87, from the Cambridge Centre for Ageing and Neuroscience (Cam-CAN) cohort. Decoding was strongest in visual cortex, but also significant in frontoparietal regions, with different profiles. Visual representations weakened with memory load and age, and statistically mediated age-related performance decline, especially during recall. This coupling, however, weakened with age: some older adults retained stronger visual representations than performance implied, suggesting impaired access to a partially preserved memory trace. Frontoparietal representations, instead, were largely insensitive to load and strengthened with age during maintenance, partially offsetting performance decline. Therefore, interventions to boost VSTM in older adults might target compensatory frontoparietal representations during memory maintenance, and readout of untapped visual representations at recall.

neuroscience↗

Lexical surprisal drives pupil dilation during continuous story listening

The pupil famously adjusts its dilation in response to light, but its role extends far beyond this basic sensory function. Its fluctuations index arousal and mental effort, beyond luminance-related dynamics, making it a sensitive marker of internal cognitive states. A growing body of work shows that these pupil-linked signals extend beyond the visual domain. However, which processes drive pupil responses in more naturalistic settings remains unclear as most evidence comes from tightly controlled paradigms that strip away the richness of real-world experience. Language offers a uniquely powerful window into this question, as it can allow us to create rich paradigms without having any visual, i.e. luminance, confounds. Moreover, language comprehension hinges on continuous prediction: listeners constantly generate expectations about upcoming input, and the discrepancy between expectation and actual input - contextual prediction error, or surprisal - carries measurable cognitive costs. Here, we tested the hypothesis that pupil-linked arousal indexes these linguistic surprisal signals during naturalistic listening. We recorded pupil responses while volunteers listened to naturalistic spoken stories in darkness, which were either intact or reversed. Reversed speech preserves the acoustics of the signal while destroying its intelligibility. Pupil dilation selectively tracked lexical surprisal within a late window of 1,700 to 2,350 milliseconds following word onset, in forward, but not control, backward speech. These findings indicate that pupil-linked arousal is tuned to global, context-dependent processing, tracking the cognitive cost of updating a predictive model during naturalistic listening.

neuroscience↗