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The phase slips are generally extracted from the EEG using Hilbert transforms but could also be extracted from the derivatives of EEG, providing additional information about the formation of cortical phase transitions. We examined this from the 30 s long, 256-channel resting state, eyes open EEG data of a 30-year-old male subject. The phase slip rates, PSR1 from EEG, PSR2 from the first-order derivative of EEG, and PSR3 from the second-order derivative of EEG, respectively, were extracted. The study was performed in the alpha (7-12 Hz) band only. The spatiotemporal plots of the EEG and phase slip rates over a 3.0 s period with a 0.5 s resolution were made with a montage layout of the 256 electrode positions. The spatiotemporal patterns of EEG and its derivatives exhibited shifting activity from posterior visual areas to the central and frontal regions over the 3.0 s period. The PSR1, PSR2, and PSR3 activity areas were different from the EEG and were distributed in larger areas as compared with the EEG and its derivatives. Also, the PSR2 and PSR3 activity areas and magnitudes were significantly different as compared with the PSR1 alone. This was also confirmed ( < 0.01) by the one-way ANOVA analysis of the means of PSR1, PSR2, and PSR3. These results show that PSR2 and PSR3 carry additional information that could potentially be biomarkers for studying the rate of formation of phase slips and the related cortical activity from the derivatives of EEG data.
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http://dx.doi.org/10.3389/fnint.2025.1471120 | DOI Listing |
J Alzheimers Dis
September 2025
Department of Medicine and Surgery, Unit of Neurology, Neurophysiology, Neurobiology and Psychiatry, Università Campus Bio-Medico di Roma, Roma, Italy.
BackgroundAlzheimer's disease (AD) is the most common neurodegenerative disorder. While AD diagnosis traditionally relies on clinical criteria, recent trends favor a precise biological definition. Existing biomarkers efficiently detect AD pathology but inadequately reflect the extent of cognitive impairment or disease heterogeneity.
View Article and Find Full Text PDFCereb Cortex
August 2025
School of Psychology, University of Surrey, Stag Hill, Guildford, Surrey, GU2 7XH, United Kingdom.
Alpha oscillations have been implicated in the maintenance of working memory representations. Notably, when memorised content is spatially lateralised, the power of posterior alpha activity exhibits corresponding lateralisation during the retention interval, consistent with the retinotopic organisation of the visual cortex. Beyond power, alpha frequency has also been linked to memory performan ce, with faster alpha rhythms associated with enhanced retention.
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August 2025
Department of Psychology, University of Lübeck, Ratzeburger Allee 160, Lübeck 23562, Germany.
The human auditory system must distinguish relevant sounds from noise. Severe hearing loss can be treated with cochlear implants (CIs), but how the brain adapts to electrical hearing remains unclear. This study examined adaptation to unilateral CI use in the first and seventh months after CI activation using speech comprehension measures and electroencephalography recordings, both during passive listening and an active spatial listening task.
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August 2025
Functional Imaging Laboratory (FIL), Department of Imaging Neuroscience, University College London, 12 Queen Square, London WC1N 3AR, United Kingdom.
This paper marks the 30th anniversary of the Statistical Parametric Mapping (SPM) software and the journal Cerebral Cortex: two modest milestones that mark the inception of cognitive neuroscience. We take this opportunity to reflect on SPM, a generation after its introduction. Each of the authors of this paper-who represent a small selection of the many contributors to SPM-were asked to consider lessons learned, what has gone well, and where there is room for improvement in future development.
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August 2025
Translational Neuromodeling Unit (TNU), Institute for Biomedical Engineering, University of Zurich & ETH Zurich, Zurich, Switzerland.
Statistical Parametric Mapping (SPM) is a statistical framework and open source software package for neuroimaging data analysis. Originally created by Karl Friston in the early 1990s, it has been used by a vast number of scientific studies over the last three decades. SPM has not only revolutionized the analysis of neuroimaging data but also catalyzed the development of cognitive neuroscience.
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