Biology subjects

Ramele, R.

Publications and source records attributed to Ramele, R..

2 recordsLinked to original sources

bioRxiv2026

Closed-loop acoustic stimulation promotes local slow oscillation train initiation and persistence in elderly adults

Slow oscillations (SOs) during non-rapid eye movement (NREM) sleep support memory consolidation and metabolic waste clearance. Aging is associated with reduced SO amplitude and density and disrupted temporal organization, characterized by more isolated events and shorter SO trains. We investigated whether closed-loop acoustic stimulation (CLAS) could enhance the initiation and persistence of rhythmic SO activity in elderly adults. Twenty-seven participants underwent a baseline night followed by an experimental night, during which online-detected SOs were either stimulated using CLAS (STIM; n = 16) or left unstimulated (SHAM; n = 11). We quantified the proportions of isolated and consecutive SOs, train-initiation probability, and SO train length. Analyses assessed local effects around online-detected SOs and global effects across NREM sleep using offline detection. Locally, CLAS reduced the proportion of isolated SOs and increased the proportion of consecutive SOs, train-initiation probability, and mean train length. Global overnight effects were weaker but directionally consistent, primarily reflecting a shift toward longer SO trains. These changes occurred without a significant between-group difference in the change in SO density, and local effects remained significant after adjustment for SO density. Thus, CLAS promoted sustained rhythmic activity beyond changes in SO occurrence. These findings suggest that CLAS can modify the temporal organization of SOs in elderly adults, supporting its potential to mitigate age-related disruptions in SO dynamics. Temporal organization measures may complement conventional amplitude and density measures when evaluating CLAS effects. Further studies should establish whether these changes translate into cognitive benefits or improvements in other aspects of brain health.

neuroscience↗

bioRxiv2026

Beyond Ground Truth in K-Complex Detection: A Waveform-Based SVM Classifier and the Limits of Expert Agreement

ObjectiveK-complexes (KCs) are large-amplitude EEG events that represent N2 sleep stage and have been linked to sensory gating, sleep protection, and memory consolidation. Their detection remains limited by inter-rater variability in visual scoring and by the reliance of detectors on features that discard temporal information. We propose a two-stage detector that combines a rule-based candidate localization algorithm with a Support Vector Machine (SVM) classifier operating directly on the raw 2-seconds waveform, and we evaluate it against an adjudicated expert consensus of two different datasets. MethodsPolysomnographic recordings from 10 healthy adults (Dataset 1) were independently annotated by two human scorers; discordant events were adjudicated by a senior expert, yielding 240 consensus KCs. The automatic classifier was evaluated using subject-level 10-fold Group K-Fold cross-validation and compared directly against the two human scorers under identical conditions. Cross-dataset generalization was further assessed on the public DREAMS database (Dataset 2) under both external and internal training criteria. ResultsThe SVM classifier achieved the highest F1-score (79.4%) and accuracy (78.8%) among all scorers, with balanced recall (81.7%) and specificity (75.8%). Of the 58 false positives, 42 originated from events both experts had rejected yet displayed canonical KC morphology and received high classifier confidence (P(KC)>0.7 in 45.2% of cases). This pattern was replicated on Dataset 2. ConclusionA waveform-based classifier matches expert performance and systematically flags morphologically valid KCs that fall outside conventional visual-scoring criteria. SignificanceThese findings question the existence of an unambiguous ground truth for KC detection and support a data-driven redefinition of the event boundary, with implications for sleep staging and memory-consolidation research.

bioengineering↗