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Autism Spectrum Disorder (ASD) is a complex neurodevelopmental disorder that can be associated with intellectual disability (ID) and epilepsy (E). The etiology and the pathogenesis of this disorder is in most cases still to be clarified. Several studies have underlined that the EEG recordings in children with these clinical pictures are abnormal, however the precise frequency of these abnormalities and their relationship with the pathogenic mechanisms and in particular with epileptic seizures are still unknown. We retrospectively reviewed 292 routine polysomnographic EEG tracings of preschool children (age < 6 years) who had received a first multidisciplinary diagnosis of ASD according to DSM-5 clinical criteria. Children (mean age: 34.6 months) were diagnosed at IRCCS E. Medea (Bosisio Parini, Italy). We evaluated: the background activity during wakefulness and sleep, the presence and the characteristics (focal or diffuse) of the slow-waves abnormalities and the interictal epileptiform discharges. In 78.0% of cases the EEG recordings were found to be abnormal, particularly during sleep. Paroxysmal slowing and epileptiform abnormalities were found in the 28.4% of the subjects, confirming the high percentage of abnormal polysomnographic EEG recordings in children with ASD. These alterations seem to be more correlated with the characteristics of the underlying pathology than with intellectual disability and epilepsy. In particular, we underline the possible significance of the prevalence of EEG abnormalities during sleep. Moreover, we analyzed the possibility that EEG data reduces the ASD clinical heterogeneity and suggests the exams to be carried out to clarify the etiology of the disorder.
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http://dx.doi.org/10.3390/brainsci13020345 | DOI Listing |
J Affect Disord
September 2025
Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, ON, Canada; Peter Boris Centre for Addictions Research, St. Joseph's Healthcare Hamilton, Hamilton, ON, Canada; Seniors Mental Health Program, Department of Psychiatry and Neurosciences, McMaster University, Hamil
Electroencephalography (EEG) is a comparatively inexpensive and non-invasive recording technique of neural activity, making it a valuable tool for biomarker discovery in transcranial magnetic stimulation (TMS). This systematic review aimed to examine mechanistic and predictive biomarkers, identified through TMS-EEG or resting-state EEG, of treatment response to TMS in psychiatric and neurocognitive disorders. Nineteen articles were obtained via Embase, APA PsycInfo, MEDLINE, and manual search; conditions included, unipolar depression (k = 13), Alzheimer's disease (k = 3), bipolar depression (k = 2), and schizophrenia (k = 2).
View Article and Find Full Text PDFBiomed Phys Eng Express
September 2025
electrical engineering department, Indian Institute of Technology Roorkee, Research wing, electrical department, Roorkee, uttrakhand, 247664, INDIA.
Imagined speech classification involves decoding brain signals to recognize verbalized thoughts or intentions without actual speech production. This technology has significant implications for individuals with speech impairments, offering a means to communicate through neural signals. The prime objective of this work is to propose an innovative machine learning (ML) based classification methodology that combines electroencephalogram (EEG) data augmentation using a sliding window technique with statistical feature extraction from the amplitude and phase spectrum of frequency domain EEG segments.
View Article and Find Full Text PDFJ Clin Exp Neuropsychol
September 2025
Program in Physical Therapy and Department of Neurology, Washington University School of Medicine, St. Louis, Missouri, USA.
Introduction: An important frontier for neuropsychology involves developing additional technologies that could complement current behavioral approaches. Concurrent electroencephalographic (EEG) markers are especially promising for informing the neural processes underlying cognitive performance during neuropsychological assessments. The EEG aperiodic exponent shows sensitivity to both age and task-related effects, with prior studies relating smaller exponents to poorer performance in older adults, and larger exponents to greater task engagement in general.
View Article and Find Full Text PDFNat Methods
September 2025
Department of Radiology, Michigan State University, East Lansing, MI, USA.
Concurrent recording of electroencephalogram (EEG) and functional magnetic resonance imaging (fMRI) signals reveals cross-scale neurovascular dynamics crucial for explaining fundamental linkages between function and behaviors. However, MRI scanners generate artifacts for EEG detection. Despite existing denoising methods, cabled connections to EEG receivers are susceptible to environmental fluctuations inside MRI scanners, creating baseline drifts that complicate EEG signal retrieval from the noisy background.
View Article and Find Full Text PDFEpileptic Disord
September 2025
Unit of Child Neurology and Psychiatry, ASST-Spedali Civili of Brescia, Brescia, Italy.
Protein ufymilation is a post-translational modification implicated in the regulation of several cellular processes. Biallelic variants in UBA5 causing a functional alteration of its protein product have been associated with early-onset epileptic encephalopathy 44 (EIEE44), a rare disease for which 28 patients have been described in the literature at present. We here report on the clinical and detailed EEG phenotype of a novel patient affected by EIEE44.
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