Category Ranking
98%
Total Visits
921
Avg Visit Duration
2 minutes
Citations
20
Article Abstract
The epilepsy diagnosis still represents a complex process, with misdiagnosis reaching 40%. We aimed at building an automatable workflow, helping the clinicians in the diagnosis of temporal lobe epilepsy (TLE). We hypothesized that neuronal avalanches (NA) represent a feature better encapsulating the rich brain dynamics compared to classically used functional connectivity measures (Imaginary Coherence; ImCoh). We analyzed large-scale activation bursts (NA) from source estimation of resting-state electroencephalography. Using a support vector machine, we reached a classification accuracy of TLE versus controls of 0.86 ± 0.08 (SD) and an area under the curve of 0.93 ± 0.07. The use of NA features increase by around 16% the accuracy of diagnosis prediction compared to ImCoh. Classification accuracy increased with larger signal duration, reaching a plateau at 5 min of recording. To summarize, NA represents an interpretable feature for an automated epilepsy identification, being related with intrinsic neuronal timescales of pathology-relevant regions.
Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11189588 | PMC |
| http://dx.doi.org/10.1038/s41598-024-64870-3 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
The ability to detect and transmit novel events is essential for adaptive behavior in uncertain environments. Here, we investigate how holographically triggered, unanticipated action potentials propagate through the primary visual cortex of resting mice, focusing on pyramidal neuron communication. We find that these novel spikes - uncorrelated with ongoing activity - exert a disproportionately large influence on neighboring neurons, whose response scales as a power law (exponent ∼0.
View Article and Find Full Text PDFLearning and criticality in a self-organizing model of connectome growth.
Sci Rep
August 2025
Institute of Technical Physics and Materials Science, HUN-REN Centre for Energy Research, P.O. Box 49, 1525, Budapest, Hungary.
The exploration of brain networks has reached an important milestone as relatively large and reliable information has been gathered for connectomes of different species. Analyses of connectome data sets reveal that the structural length follows the exponential rule, the distributions of in- and out-node strengths follow heavy-tailed lognormal statistics, while the functional network properties exhibit powerlaw tails, suggesting that the brain operates close to a critical point where computational capabilities and sensitivity to stimulus is optimal. Because these universal network features emerge from bottom-up (self-)organization, one can pose the question of whether they can be modeled via a common framework, particularly through the lens of criticality of statistical physical systems.
View Article and Find Full Text PDFNetwork structure influences self-organized criticality in neural networks with dynamical synapses.
Front Syst Neurosci
June 2025
Faculty of Culture and Information Science, Doshisha University, Kyotanabe, Kyoto, Japan.
The brain criticality hypothesis has been a central research topic in theoretical neuroscience for two decades. This hypothesis suggests that the brain operates near the critical point at the boundary between order and disorder, where it acquires its information-processing capabilities. The mechanism that maintains this critical state has been proposed as a feedback system known as self-organized criticality (SOC); brain parameters, such as synaptic plasticity, are regulated internally without external adjustment.
View Article and Find Full Text PDFIs criticality a unified setpoint of brain function?
Neuron
August 2025
Department of Physics, University of Arkansas, Fayetteville, AR 72701, USA. Electronic address:
Brains face selective pressure to optimize computation, broadly defined. This is achieved by mechanisms including development, plasticity, and homeostasis. Is there a universal optimum around which the healthy brain tunes itself, across time and individuals? The criticality hypothesis posits such a setpoint.
View Article and Find Full Text PDFGenetic contributions to brain criticality and its relationship with human cognitive functions.
Proc Natl Acad Sci U S A
July 2025
State Key Laboratory of Cognitive Science and Mental Health, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China.
Recently, extensive evidence has demonstrated that the brain operates close to a critical state, characterized by dynamic patterns known as neuronal avalanches. The critical state, reflecting the delicate balance between neural excitation and inhibition, offers numerous advantages in information processing. However, the role of genetics in shaping brain criticality is not fully understood.
View Article and Find Full Text PDF