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Volk, C.

Publications and source records attributed to Volk, C..

7 recordsLinked to original sources

REM Sleep Iota Oscillations Across the Lifespan

Iota oscillations are a newly discovered marker of wakefulness and rapid eye movement (REM) sleep. So far, iota in REM sleep has only been reported in the surface electroencephalography (EEG) of a small sample of young adults and in intracranial recordings of epileptic patients. Here, we investigated the presence of these oscillations in a large dataset (N=937) of high-density sleep EEG recordings from individuals 7 to 70 years old. We found that iota spectral peaks during REM sleep were between 25 and 40 Hz, slightly faster than in wake (25-35 Hz). Iota power was significantly associated with REM sleep architecture, increasing with both REM duration and across progressive sleep cycles. Iota peaks were observed in individuals of all ages, although the prevalence decreased gradually with age, from 88% in children to 44% in older adults. Most iota spectral peak properties (frequency, amplitude, timing, topography) likewise shifted with age. The most striking effect, however, was in bandwidth, such that children had narrow iota peaks, older adults had broad iota peaks, and 20-30 year olds could have either. It remains unclear whether narrowband and broadband iota are functionally equivalent. On shorter time scales (< 1 year), iota properties remained stable across measurements. Analyses of a separate dataset of monozygotic and dizygotic twins revealed high heritability of all iota peak properties except bandwidth. Overall, these results establish iota as a genetically determined trait-like marker of REM sleep with unique age-related changes. Iota oscillations open new avenues to investigate the interaction between sleep, genetics, development, and aging.

neuroscience↗

The curriculum effect in visual learning: the role of readout dimensionality

Generalization of visual perceptual learning (VPL) to unseen conditions varies across tasks. Previous work suggests that training curriculum may be integral to generalization, yet a theoretical explanation is lacking. We propose an explanatory theory of visual learning generalization and curriculum effects by leveraging an artificial neural network (ANN) model of VPL in comparison with humans. We found that easy-to-hard sequential training improved generalization in both humans and ANNs. However, when easy and hard conditions were interleaved, humans and ANNs showed different behaviours: while ANNs performed worse than with sequential training, humans maintained good performance but with large inter-individual variability. Investigating ANN models trained with different curricula, we demonstrated that models relying on low-dimensional neural populations showed superior generalization. This readout subspace dimensionality was directly determined by curriculum: learners who learned from easy tasks early formed lower-dimensional subspaces and generalized better. Our theory provides a mechanistic framework linking curriculum design to VPL generalization through neural population dimensionality. Author SummaryLearning new skills is fundamental to humans and animals. However, a key challenge in learning is generalization: applying learned skills to new situations not encountered during training. While it is well known that training curriculum affects how well we generalize, the underlying mechanisms remain poorly understood. What makes certain training curricula more effective than others? Why do some learners generalize better than others even with similar training? We developed a computational theory to explain how curriculum design influences generalization in visual learning. Using a combination of human behavioural experiments and artificial neural network modeling, we posit that easy-to-hard training sequences lead learners to focus on fewer, more essential visual features. This creates low-dimensional neural representations that are robust and generalize well to new conditions. Importantly, we found this benefit even extends to learners who spontaneously adopt easy-to-hard strategies on their own, without explicit curriculum design. Our theory provides a mechanistic link between curriculum structure, neural population dynamics, and generalization performance. Moreover, these findings offer practical guidelines for designing effective training programs in education and rehabilitation.

neuroscience↗

The Infraslow Fluctuation of Sigma Power During Sleep in Young Individuals with Schizophrenia

A reduction in sleep spindles, a major electrophysiological characteristic of Non-Rapid Eye Movement sleep, has been suggested as a potential biomarker of schizophrenia. While research has primarily focused on the spindle quantity, recent studies have begun to explore their temporal dynamics throughout the night. In healthy individuals, sleep spindles fluctuate on an infraslow [~]50-second timescale, alternating between phases of high and low spindle activity. This fluctuation is referred to as the infraslow fluctuation of sigma power (ISFS), which is modulated by noradrenergic activity from the locus coeruleus and linked to the organization of arousal and memory reactivation processes during sleep. Given the known deficit in sleep spindles, dysregulation of noradrenergic activity, and impairments in sleep maintenance and memory in schizophrenia, this study investigates the ISFS in sleep electroencephalography data from individuals with either Childhood-Onset Schizophrenia (COS; N = 17) or Early-Onset Schizophrenia (EOS; N = 11), aged 9 to 21 years, alongside age- and sex-matched healthy controls (N = 56). The presence and strength of the ISFS were reduced in both COS and EOS groups compared to controls, particularly in central-parietal electrodes. No significant differences in these features of the ISFS were found between the two clinical groups, despite group differences in sleep spindle density and clinical characteristics. These findings suggest that the ISFS is observable but reduced in young patients with schizophrenia and support the notion that the timing of sleep spindles may inform pathomechanistic models of the disorder, as well as future diagnostic approaches and interventions.

neuroscience↗

The Infraslow Fluctuation of Sigma Power During Sleep: Links to Markers of Arousal and Memory Reactivation Across Development

Sleep is both a state of disconnection from the environment and a critical period for restoration. But how does sleep balance responsiveness with the protection of key functions? The infraslow fluctuation of sigma power (ISFS)--the clustering of sleep spindles over 10-100 seconds--is thought to regulate this trade-off in rodents. However, the organization of arousal and memory reactivation markers within the human ISFS and its conservation in younger ages remain unclear. This study characterizes the ISFS from childhood to young adulthood (N = 154; ages 8-26), examining its relationship with functional markers. Results indicate that the ISFS is present across all ages, with frequency, variability, and strength increasing from early to late adolescence. Notably, markers of arousal and memory reactivation are organized within the spindle-rich ISFS peak. The consistent presence and organization of the ISFS suggest it is intrinsic to sleep, with adolescence marking a dynamic window. These insights may guide interventions to promote healthier sleep across development.

neuroscience↗

Wake EEG oscillation dynamics reflect both sleep need and brain maturation across childhood and adolescence

1An objective measure of brain maturation is highly insightful for monitoring both typical and atypical development. Slow wave activity, recorded in the sleep electroencephalogram (EEG), reliably indexes age-related changes in sleep pressure as well as deficits related to developmental disorders such as attention-deficit hyperactivity disorder (ADHD). We aimed to determine whether wake EEG measured before and after sleep could index the same developmental changes in sleep pressure, using data collected from 163 participants 3-25 years old. We analyzed ageand sleep-dependent changes in two measures of oscillatory activity, amplitudes and density, as well as two measures of aperiodic activity, offsets and exponents. We then compared these wake measures to sleep slow wave amplitudes and slopes. Finally, we compared wake EEG in children with ADHD (N=58) to neurotypical controls. Of the four wake measures, only oscillation amplitudes consistently exhibited the same changes as sleep slow waves. Wake amplitudes decreased with age, decreased after sleep, and this overnight decrease decreased with age. Furthermore, wake amplitudes were significantly related to both sleep slow wave amplitudes and slopes. Wake oscillation densities decreased overnight in children but increased overnight in adolescents and adults. Aperiodic offsets decreased linearly with age, decreased after sleep, and were significantly related to sleep slow wave amplitudes. Aperiodic exponents also decreased with age, but increased after sleep. No wake measure showed significant effects of ADHD. Overall, our results indicate that wake oscillation amplitudes, and to some extent aperiodic offsets, behave like sleep slow waves across sleep and development. At the same time, overnight changes in oscillation densities independently reflect some yet-unknown shift in neural activity around puberty.

neuroscience↗

Changes in cross-frequency coupling following closed-loop auditory stimulation in non-rapid eye movement sleep

The activity of different brain networks in non-rapid eye movement (NREM) sleep is regulated locally in an experience-dependent manner, reflecting the extent of the network load during wakefulness. In particular, improved task performance after sleep correlates with the local post-learning power increase of neocortical slow waves and faster oscillations such as sleep spindles and their temporal coupling. Recently, it was demonstrated that by targeting slow waves in a particular region at a particular phase with closed-loop auditory stimulation it is possible to locally manipulate slow-wave activity and interact with training-induced neuroplastic changes. Based on this finding, we tested whether closed-loop auditory stimulation targeting the up-phase of slow-waves over the right sensorimotor area might affect power in delta, theta and sigma bands and coupling between these oscillations within the circumscribed region. We demonstrate that while closed-loop auditory stimulation globally enhances power in delta, theta and sigma bands, changes in cross-frequency coupling of these oscillations were more spatially restricted. In particular, stimulation induced a significant decrease of delta-theta coupling in frontal channels, within the area of the strongest baseline coupling between these frequency bands. In contrast, a significant increase in delta-sigma coupling was observed over the right parietal area, located directly posterior to the target electrode. These findings suggest that closed-loop auditory stimulation locally modulates coupling between delta phase and sigma power in a targeted region, which could be used to manipulate sleep-dependent memory formation within the brain network of interest.

neuroscience↗

Diurnal changes in glutamate/glutamine levels of healthy young adults assessed by proton magnetic resonance spectroscopy

Molecular and electrophysiological studies suggest that sleep ensures efficient functioning of the brain by maintaining synaptic homeostasis. The glutamate receptor -amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA receptor) is involved in synaptic plasticity processes and it was shown that its expression changes across the sleep wake cycle. Moreover, animal studies have shown that glutamate levels are reduced during non-rapid eye movement (NREM) sleep and that the rate of the decrease is positively correlated with sleep EEG slow wave activity (SWA). In this study, we aimed to assess if proton magnetic resonance spectroscopy (1H-MRS) is sensitive to diurnal changes of glutamate + glutamine (GLX) in healthy young adults and if potential overnight changes of GLX are correlated to SWA. 1H-MRS spectra of 16 adult subjects were measured in the parietal lobe in the evening and in the subsequent morning using a 3T MRI scanner. The night between the scans was recorded with high-density EEG. Our results revealed a significant overnight reduction in GLX levels, whereas other metabolites did not show any significant change. Moreover, the decrease in GLX was positively correlated with the decrease of SWA in the course of the night. Our study demonstrates that quantification of diurnal changes in GLX is possible by means of 1H-MRS and indicates a relationship between changes in GLX and SWA, a marker that is closely linked to the restorative function of sleep. This relationship might be of particular interest in clinical populations in which sleep is disturbed.

neuroscience↗