Biology subjects

Talamini, L. M.

Publications and source records attributed to Talamini, L. M..

5 recordsLinked to original sources

bioRxiv2025

Deepening sleep using an EEG wearable featuring modeling-based closed-loop neurostimulation

ObjectiveClosed-loop neurostimulation (CLNS) during slow-wave sleep (SWS) has been shown to enhance slow-wave activity, predominantly using laboratory equipment. To further advance CLNS research and its potential applications, there is a need for user-friendly EEG wearable equipment featuring CLNS that can support long-term CLNS studies in both clinical and home settings. ApproachHere we evaluate whether modeling-based CLNS (M-CLNS) with acoustic stimulation of slow oscillations (SOs) can be effectively implemented using a self-applicable EEG headband with forehead electrodes. We assess the performance of M-CLNS stimulus targeting over the EEG headband together with short-term, stimulus-locked, and more enduring enhancement of SWS. We validate our results against simultaneous recordings obtained using gold-standard laboratory PSG equipment. Main resultsOur findings demonstrate that the SO phase can be reliably assessed and accurately targeted using M-CLNS with the EEG headband. We show an immediate enhancement of SO dynamics in the short-term, as well as an enduring increase in power spectral density across SO and delta frequencies (0.75 - 5 Hz) across SWS. These results are in line with previous studies using M-CLNS with laboratory equipment. SignificanceThese findings demonstrate that M-CLNS with acoustic stimulation can successfully be applied using an EEG headband on the forehead to target SOs, leading to both immediate and enduring enhancements of SWS. In conclusion, M-CLNS in a self-applicable EEG headband may offer a promising tool for portable and non-invasive enhancement of SWS, with future potential for clinical and home-based applications.

neuroscience↗

bioRxiv2025

Precisely phase-locked acoustic stimuli globally enhance slow oscillations, but depress fast spindles

IntroductionSeveral studies have shown manipulation of slow oscillations (SO) and sigma power through auditory stimulation during sleep. Most of the evidence, however, regards effects immediately following stimulation rather than enduring effects. Moreover, effects on discrete fast and slow spindles have as yet not been assessed. Materials and MethodsHere we use a modeling-based approach to predict upcoming oscillatory activity in the EEG and precisely phase-lock subtle acoustic stimuli to the start of the SO positive deflection. We assess the effects of stimulation on discrete slow oscillations, fast and slow spindles in the seconds after stimulation and on the longer term. We relate our findings to observations at the level of spectral measures and stimulus evoked responses. ResultsOur observations show that slow wave measures were consistently increased, as apparent in measures of discrete SOs, SO and delta power and deflections in the ERP. On the other hand, fast spindle measures showed a temporally localized increase during a stimulus-induced SO positive deflection around 1 second after stimulation, but were globally decreased, both on the short and long term. The latter was apparent in measures of discrete fast spindles and PSD across longer periods of sleep. ConclusionsAcoustic stimuli, precisely phase locked to the SO onset, increase SOs and delta power globally, therewith deepening sleep. On the other hand, fast sleep spindles are globally depressed. This appears to be due, in part, to interruption of ongoing spindles by the stimulus and may furthermore reflect a depressing influence of slow oscillations on fast spindle dynamics. Future studies could evaluate the therapeutic potential of sleep deepening with acoustic stimulation in clinical populations who suffer from reduced deep sleep, such as in insomnia or post-traumatic stress disorder.

neuroscience↗

bioRxiv2024

Predicting and phase targeting brain oscillations in real-time

ObjectiveClosed-loop neurostimulation (CLNS) procedures, aligning stimuli with electrical brain activity, are quickly gaining popularity in neuroscience. They have been employed to reveal causal links between neural activity patterns and function, and to explore therapeutic effects of electroencephalography (EEG-)guided stimulations during sleep. Most CLNS procedures are developed for a single purpose, detecting one specific pattern of interest in the EEG. Furthermore, most procedures have limited, if any, flexibility to adapt to temporal or interindividual variance in the signal, which means they wouldnt work optimally across the full physiological phenomenology. ApproachHere we present a new approach to CLNS, based on real-time signal modelling to predict brain activity, allowing targeting of a broad variety of oscillatory dynamics. Intrinsic to the modelling approach is adaptation to signal variance, such that no personalization steps prior to use are necessary. We systematically assess stimulus targeting performance of modelling-based CLNS (M-CLNS), across a wide range of brain oscillation frequencies and phases in human and rodent neurophysiological signals. Main resultsOur results show high performance for all target phases and frequency bands, including slow oscillations, theta and alpha waves. SignificanceThese findings highlight the general applicability and adaptability of M-CLNS, which also favors its application in populations with an atypical oscillatory signature, like clinical or elderly populations. In conclusion, M-CLNS provides a promising new tool for neural activity-dependent stimulation in both experimental research and therapeutic applications, such as enhancing deep sleep in patients with sleep disorders.

neuroscience↗

bioRxiv2021

Sleep spindle dynamics suggest over-consolidation in post-traumatic stress disorder

Devastating and persisting traumatic memories are a central symptom of post-traumatic stress disorder (PTSD). Sleep problems are highly co-occurrent with PTSD and intertwined with its etiology. Notably, sleep hosts memory consolidation processes, supported by sleep spindles (11-16 Hz). Here we assess the hypothesis that intrusive memory symptoms in PTSD may arise from excessive memory consolidation, reflected in exaggerated spindling. We use a newly developed spindle detection method, entailing minimal assumptions regarding spindle phenotype, to assess spindle activity in PTSD patients and traumatized controls (n=2x14, matched on gender). Our results show increased spindle activity in PTSD, which positively correlates with daytime intrusive memory symptoms. Together, these findings provide a putative mechanism through which profound sleep disturbance in PTSD may contribute to memory problems. Due to its uniform and unbiased approach, the new, minimal assumption spindle detection method seems a promising tool to detect aberrant spindling in psychiatric disorders.

neuroscience↗

bioRxiv2017

The Spectral Fingerprint of Sleep Problems in Post-Traumatic Stress Disorder

BACKGROUNDSleep problems are a core feature of post-traumatic stress disorder (PTSD). However, a robust objective measure for the sleep disturbance in patients has yet to be found.\n\nMETHODSThe current study assessed EEG power across a wide frequency range and multiple scalp locations, in matched trauma-exposed individuals with and without PTSD, during rapid eye movement (REM) and non-REM (NREM) sleep. In addition, a full polysomnographical evaluation was performed, including sleep staging and assessment of respiratory function, limb movements and heart rate. The occurrence of sleep disorders was also assessed.\n\nRESULTSIn PTSD patients, NREM sleep shows a substantial loss of slow oscillation power and increased higher frequency activity compared to controls. The change is most pronounced in right-frontal brain areas and correlates with insomnia. PTSD REM sleep shows a large power shift in the opposite direction, with increased slow oscillation power in occipital areas, which is strongly related to nightmare activity and to lesser extent with insomnia. These pronounced spectral changes occur in the context of severe subjective sleep problems, increased occurrence of various sleep disorders and modest changes in sleep macrostructure.\n\nCONCLUSIONSThis is the first study to show pronounced changes in EEG spectral topologies during both NREM and REM sleep in PTSD. Importantly, the observed power changes reflect the hallmarks of PTSD sleep problems: insomnia and nightmares and may thus be specific for PTSD. A spectral index derived from these data distinguishes patients from controls with high effect size, bearing promise as a candidate biomarker.

neuroscience↗