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Róbert Bódizs - One of the best experts on this subject based on the ideXlab platform.
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circadian preference towards morningness is associated with lower slow Sleep Spindle amplitude and intensity in adolescents
Scientific Reports, 2017Co-Authors: Róbert Bódizs, Ilona Merikanto, Jari Lahti, Liisa Kuula, Tommi Makkonen, Kati Heinonen, Katri Räikkönen, Risto Halonen, Anu-katriina PesonenAbstract:Individual circadian preference types and Sleep EEG patterns related to Spindle characteristics, have both been associated with similar cognitive and mental health phenotypes. However, no previous study has examined whether Sleep Spindles would differ by circadian preference. Here, we explore if Spindle amplitude, density, duration or intensity differ by circadian preference and whether these associations are moderated by Spindle location, frequency, and time distribution across the night. The participants (N = 170, 59% girls; mean age = 16.9, SD = 0.1 years) filled in the shortened 6-item Horne-Ostberg Morningness-Eveningness Questionnaire. We performed an overnight Sleep EEG at the homes of the participants. In linear mixed model analyses, we found statistically significant lower Spindle amplitude and intensity in the morning as compared to intermediate (P 0.06 for Spindle duration and density). Spindle frequency moderated the associations (P 0.2 for fast (>13 Hz)). Growth curve analyses revealed a distinct time distribution of Spindles across the night by the circadian preference: both Spindle amplitude and intensity decreased more towards morning in the morning preference group than in other groups. Our results indicate that circadian preference is not only affecting the Sleep timing, but also associates with Sleep microstructure regarding Sleep Spindle phenotypes.
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Nap Sleep Spindle correlates of intelligence
Scientific reports, 2015Co-Authors: Péter P. Ujma, Róbert Bódizs, Ferenc Gombos, Johannes Stintzing, Boris N. Konrad, Lisa Genzel, Axel Steiger, Martin DreslerAbstract:Sleep Spindles are thalamocortical oscillations in non-rapid eye movement (NREM) Sleep, that play an important role in Sleep-related neuroplasticity and offline information processing. Several studies with full-night Sleep recordings have reported a positive association between Sleep Spindles and fluid intelligence scores, however more recently it has been shown that only few Sleep Spindle measures correlate with intelligence in females, and none in males. Sleep Spindle regulation underlies a circadian rhythm, however the association between Spindles and intelligence has not been investigated in daytime nap Sleep so far. In a sample of 86 healthy male human subjects, we investigated the correlation between fluid intelligence and Sleep Spindle parameters in an afternoon nap of 100 minutes. Mean Sleep Spindle length, amplitude and density were computed for each subject and for each derivation for both slow and fast Spindles. A positive association was found between intelligence and slow Spindle duration, but not any other Sleep Spindle parameter. As a positive correlation between intelligence and slow Sleep Spindle duration in full-night polysomnography has only been reported in females but not males, our results suggest that the association between intelligence and Sleep Spindles is more complex than previously assumed.
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a comparison of two Sleep Spindle detection methods based on all night averages individually adjusted vs fixed frequencies
Frontiers in Human Neuroscience, 2015Co-Authors: Péter P. Ujma, Róbert Bódizs, Ferenc Gombos, Boris N. Konrad, Lisa Genzel, Martin Dresler, A Steiger, Peter SimorAbstract:Sleep Spindles are frequently studied for their relationship with state and trait cognitive variables, and they are thought to play an important role in Sleep-related memory consolidation. Due to their frequent occurrence in NREM Sleep, the detection of Sleep Spindles is only feasible using automatic algorithms, of which a large number is available. We compared subject averages of the Spindle parameters computed by a fixed frequency (FixF) (11-13 Hz for slow Spindles, 13-15 Hz for fast Spindles) automatic detection algorithm and the individual adjustment method (IAM), which uses individual frequency bands for Sleep Spindle detection. Fast Spindle duration and amplitude are strongly correlated in the two algorithms, but there is little overlap in fast Spindle density and slow Spindle parameters in general. The agreement between fixed and manually determined Sleep Spindle frequencies is limited, especially in case of slow Spindles. This is the most likely reason for the poor agreement between the two detection methods in case of slow Spindle parameters. Our results suggest that while various algorithms may reliably detect fast Spindles, a more sophisticated algorithm primed to individual Spindle frequencies is necessary for the detection of slow Spindles as well as individual variations in the number of Spindles in general.
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Nap Sleep Spindle correlates of
2015Co-Authors: Péter P. Ujma, Róbert Bódizs, Ferenc Gombos, Johannes Stintzing, Boris N. Konrad, Lisa Genzel, Axel Steiger, Martin DreslerAbstract:Sleep Spindles are thalamocortical oscillations in non-rapid eye movement (NREM) Sleep, that play an important role in Sleep-related neuroplasticity and offline information processing. Several studies with full-night Sleep recordings have reported a positive association between Sleep Spindles and fluid intelligence scores, however more recently it has been shown that only few Sleep Spindle measures correlate with intelligence in females, and none in males. Sleep Spindle regulation underlies a circadian rhythm, however the association between Spindles and intelligence has not been investigated in daytime nap Sleep so far. In a sample of 86 healthy male human subjects, we investigated the correlation between fluid intelligence and Sleep Spindle parameters in an afternoon nap of 100 minutes. Mean Sleep Spindle length, amplitude and density were computed for each subject and for each derivation for both slow and fast Spindles. A positive association was found between intelligence and slow Spindle duration, but not any other Sleep Spindle parameter. As a positive correlation between intelligence and slow Sleep Spindle duration in full-night polysomnography has only been reported in females but not males, our results suggest that the association between intelligence and Sleep Spindles is more complex than previously assumed.
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Sleep Spindles and intelligence: evidence for a sexual dimorphism
The Journal of neuroscience : the official journal of the Society for Neuroscience, 2014Co-Authors: Péter P. Ujma, Ferenc Gombos, Boris N. Konrad, Lisa Genzel, Axel Steiger, Janos Kormendi, Peter Simor, Annabell Bleifuss, Adrián Pótári, Róbert BódizsAbstract:Sleep Spindles are thalamocortical oscillations in nonrapid eye movement Sleep, which play an important role in Sleep-related neuroplasticity and offline information processing. Sleep Spindle features are stable within and vary between individuals, with, for example, females having a higher number of Spindles and higher Spindle density than males. Sleep Spindles have been associated with learning potential and intelligence; however, the details of this relationship have not been fully clarified yet. In a sample of 160 adult human subjects with a broad IQ range, we investigated the relationship between Sleep Spindle parameters and intelligence. In females, we found a positive age-corrected association between intelligence and fast Sleep Spindle amplitude in central and frontal derivations and a positive association between intelligence and slow Sleep Spindle duration in all except one derivation. In males, a negative association between intelligence and fast Spindle density in posterior regions was found. Effects were continuous over the entire IQ range. Our results demonstrate that, although there is an association between Sleep Spindle parameters and intellectual performance, these effects are more modest than previously reported and mainly present in females. This supports the view that intelligence does not rely on a single neural framework, and stronger neural connectivity manifesting in increased thalamocortical oscillations in Sleep is one particular mechanism typical for females but not males.
Ilona Merikanto - One of the best experts on this subject based on the ideXlab platform.
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Polygenic impact of morningness on the overnight dynamics of Sleep Spindle amplitude.
Genes brain and behavior, 2020Co-Authors: Anu-katriina Pesonen, Péter P. Ujma, Ilona Merikanto, Jari Lahti, Tommi Makkonen, Katri Räikkönen, Risto Halonen, Liisa KuulaAbstract:Sleep Spindles are thalamocortical oscillations that contribute to Sleep maintenance and Sleep-related brain plasticity. The current study is an explorative study of the circadian dynamics of Sleep Spindles in relation to a polygenic score (PGS) for circadian preference towards morningness. The participants represent the 17-year follow-up of a birth cohort having both genome-wide data and an ambulatory Sleep electroencephalography measurement available ( N = 154, Mean age = 16.9, SD = 0.1 years, 57% girls). Based on a recent genome-wide association study, we calculated a PGS for circadian preference towards morningness across the whole genome, including 354 single-nucleotide polymorphisms. Stage 2 slow (9-12.5 Hz, N = 186 739) and fast (12.5-16 Hz, N = 135 504) Sleep Spindles were detected using an automated algorithm with individual time tags and amplitudes for each Spindle. There was a significant interaction of PGS for morningness and timing of Sleep Spindles across the night. These growth curve models showed a curvilinear trajectory of Spindle amplitudes: those with a higher PGS for morningness showed higher slow Spindle amplitudes in frontal derivations, and a faster dissipation of Spindle amplitude in central derivations. Overall, the findings provide new evidence on how individual Sleep Spindle trajectories are influenced by genetic factors associated with circadian type. The finding may lead to new hypotheses on the associations previously observed between circadian types, psychiatric problems and Spindle activity.
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adhd symptoms are associated with decreased activity of fast Sleep Spindles and poorer procedural overnight learning during adolescence
Neurobiology of Learning and Memory, 2019Co-Authors: Ilona Merikanto, Jari Lahti, Liisa Kuula, Tommi Makkonen, Kati Heinonen, Katri Räikkönen, Risto Halonen, Anu-katriina PesonenAbstract:Abstract ADHD and its subclinical symptoms have been associated with both disturbed Sleep and weakened overnight memory consolidation. As Sleep Spindle activity during NREM Sleep plays a key role in both Sleep maintenance and memory consolidation, we examined the association between subclinical ADHD symptoms and Sleep Spindle activity. Furthermore, we hypothesized that Sleep Spindle activity mediates the effect of ADHD symptoms on overnight learning outcome in a procedural memory task. We studied these questions in a community-based cohort of 170 adolescents (58% girls, mean age = 16.9, SD = 0.1 years), who filled in the Adult ADHD Self-Report Scale (ASRS-v1.1), and underwent an overnight Sleep EEG coupled with a mirror tracing task before and after Sleep. Elevated ADHD symptoms were associated with weaker fast Sleep Spindle activity, and poorer overnight learning in the procedural memory test. However, Sleep Spindles, contrary to the hypothesis, did not mediate the association between ADHD symptoms and overnight learning. Our results showed that a higher level of ADHD symptoms in adolescence is associated with similar alterations in Sleep Spindle activity as observed in many neuropsychiatric conditions and might contribute to altered synaptic connectivity and Sleep fragmentation observed in ADHD.
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Genetic risk factors for schizophrenia associate with Sleep Spindle activity in healthy adolescents.
Journal of sleep research, 2018Co-Authors: Ilona Merikanto, Siddheshwar Utge, Jari Lahti, Liisa Kuula, Tommi Makkonen, Marius Lahti-pulkkinen, Kati Heinonen, Katri Räikkönen, Sture Andersson, Timo E. StrandbergAbstract:Schizophrenia has been associated with disturbed Sleep, even before the onset of the disorder, and also in non-schizophrenic first-order relatives. This may point to an underlying genetic influence. Here we examine whether weighted polygenic risk scores (PRS) for schizophrenia are associated with Sleep Spindle activity in healthy adolescents. Our sample comes from a community-based cohort of 157 non-schizophrenic adolescents (57% girls) having both genetic data and an overnight Sleep EEG measurement available. Based on a recent genome-wide association study, we calculated PRS for schizophrenia across the whole genome. We also calculated PRS for the CACNA1l gene region, which has been associated with both schizophrenia and Sleep Spindle formation. We performed an overnight Sleep EEG at the homes of the participants. Stage two Sleep Spindles were detected using an automated algorithm. Sleep Spindle amplitude, duration, intensity and density were measured separately for central and frontal derivations and for fast (13-16 Hz) and slow (10-13 Hz) Spindles. PRS for schizophrenia was associated with higher fast Spindle amplitude (p = 0.04), density (p = 0.006) and intensity (p = 0.04) at the central derivation, and PRS in the CACNA1l region associated with higher slow Spindle amplitude (p = 0.01), duration (p = 0.03) and intensity (p = 0.002) at the central derivation. A positive association between genetic variants for schizophrenia and Sleep Spindle activity among healthy adolescents supports a view that Sleep Spindles and schizophrenia share similar genetic pathways. This study suggests that altered Sleep Spindle activity might serve as an endophenotype of schizophrenia.
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circadian preference towards morningness is associated with lower slow Sleep Spindle amplitude and intensity in adolescents
Scientific Reports, 2017Co-Authors: Róbert Bódizs, Ilona Merikanto, Jari Lahti, Liisa Kuula, Tommi Makkonen, Kati Heinonen, Katri Räikkönen, Risto Halonen, Anu-katriina PesonenAbstract:Individual circadian preference types and Sleep EEG patterns related to Spindle characteristics, have both been associated with similar cognitive and mental health phenotypes. However, no previous study has examined whether Sleep Spindles would differ by circadian preference. Here, we explore if Spindle amplitude, density, duration or intensity differ by circadian preference and whether these associations are moderated by Spindle location, frequency, and time distribution across the night. The participants (N = 170, 59% girls; mean age = 16.9, SD = 0.1 years) filled in the shortened 6-item Horne-Ostberg Morningness-Eveningness Questionnaire. We performed an overnight Sleep EEG at the homes of the participants. In linear mixed model analyses, we found statistically significant lower Spindle amplitude and intensity in the morning as compared to intermediate (P 0.06 for Spindle duration and density). Spindle frequency moderated the associations (P 0.2 for fast (>13 Hz)). Growth curve analyses revealed a distinct time distribution of Spindles across the night by the circadian preference: both Spindle amplitude and intensity decreased more towards morning in the morning preference group than in other groups. Our results indicate that circadian preference is not only affecting the Sleep timing, but also associates with Sleep microstructure regarding Sleep Spindle phenotypes.
Gari D Clifford - One of the best experts on this subject based on the ideXlab platform.
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stage independent single lead eeg Sleep Spindle detection using the continuous wavelet transform and local weighted smoothing
Frontiers in Human Neuroscience, 2015Co-Authors: Athanasios Tsanas, Gari D CliffordAbstract:Sleep Spindles are critical in characterizing Sleep and have been associated with cognitive function and pathophysiological assessment. Typically, their detection relies on the subjective and time-consuming visual examination of electroencephalogram (EEG) signal(s) by experts, and has led to large inter-rater variability as a result of poor definition of Sleep Spindle characteristics. Hitherto, many algorithmic Spindle detectors inherently make signal stationarity assumptions (e.g. Fourier transform-based approaches) which are inappropriate for EEG signals, and frequently rely on additional information which may not be readily available in many practical settings (e.g. more than one EEG channels, or prior hypnogram assessment). This study proposes a novel signal processing methodology relying solely on a single EEG channel, and provides objective, accurate means towards probabilistically assessing the presence of Sleep Spindles in EEG signals. We use the intuitively appealing continuous wavelet transform (CWT) with a Morlet basis function, identifying regions of interest where the power of the CWT coefficients corresponding to the frequencies of Spindles (11-16 Hz) is large. The potential for assessing the signal segment as a Spindle is refined using local weighted smoothing techniques. We evaluate our findings on two databases: the MASS database comprising 19 healthy controls and the DREAMS Sleep Spindle database comprising eight participants diagnosed with various Sleep pathologies. We demonstrate that we can replicate the experts’ Sleep Spindles assessment accurately in both databases (MASS database: sensitivity: 84%, specificity: 90%, false discovery rate 83%, DREAMS database: sensitivity: 76%, specificity: 92%, false discovery rate: 67%), outperforming six competing automatic Sleep Spindle detection algorithms in terms of correctly replicating the experts’ assessment of detected Spindles.
Fabio Ferrarelli - One of the best experts on this subject based on the ideXlab platform.
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Sleep Spindle and slow wave abnormalities in schizophrenia and other psychotic disorders recent findings and future directions
Schizophrenia Research, 2020Co-Authors: Yingyi Zhang, Gonzalo M Quinones, Fabio FerrarelliAbstract:Abstract Sleep Spindles and slow waves are the two main oscillatory activities occurring during NREM Sleep. Slow waves are ∼1 Hz, high amplitude, negative-positive deflections that are primarily generated and coordinated within the cortex, whereas Sleep Spindles are 12–16 Hz, waxing and waning oscillations that are initiated within the thalamus and regulated by thalamo-cortical circuits. In healthy subjects, these oscillations are thought to be responsible for the restorative aspects of Sleep and have been increasingly shown to be involved in learning, memory and plasticity. Furthermore, deficits in Sleep Spindles and, to lesser extent, slow waves have been reported in both chronic schizophrenia (SCZ) and early course psychosis patients. In this article, we will first describe Sleep Spindle and slow wave characteristics, including their putative functional roles in the healthy brain. We will then review electrophysiological, genetic, and cognitive studies demonstrating Spindle and slow wave impairments in SCZ and other psychotic disorders, with particularly emphasis on recent findings in early course patients. Finally, we will discuss how future work, including Sleep studies in individuals at clinical high risk for psychosis, may help position Spindles and slow waves as candidate biomarkers, as well as novel treatment targets, for SCZ and related psychotic disorders.
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reduced Sleep Spindle activity point to a trn md thalamus pfc circuit dysfunction in schizophrenia
Schizophrenia Research, 2017Co-Authors: Fabio Ferrarelli, Giulio TononiAbstract:Sleep disturbances have been reliably reported in patients with schizophrenia, thus suggesting that abnormal Sleep may represent a core feature of this disorder. Traditional electroencephalographic studies investigating Sleep architecture have found reduced deep non-rapid eye movement (NREM) Sleep, or slow wave Sleep (SWS), and increased REM density. However, these findings have been inconsistently observed, and have not survived meta-analysis. By contrast, several recent EEG studies exploring brain activity during Sleep have established marked deficits in Sleep Spindles in schizophrenia, including first-episode and early-onset patients, compared to both healthy and psychiatric comparison subjects. Spindles are waxing and waning, 12-16Hz NREM Sleep oscillations that are generated within the thalamus by the thalamic reticular nucleus (TRN), and are then synchronized and sustained in the cortex. While the functional role of Sleep Spindles still needs to be fully established, increasing evidence has shown that Sleep Spindles are implicated in learning and memory, including Sleep dependent memory consolidation, and Spindle parameters have been associated to general cognitive ability and IQ. In this article we will review the EEG studies demonstrating Sleep Spindle deficits in patients with schizophrenia, and show that Spindle deficits can predict their reduced cognitive performance. We will then present data indicating that Spindle impairments point to a TRN-MD thalamus-prefrontal cortex circuit deficit, and discuss about the possible molecular mechanisms underlying thalamo-cortical Sleep Spindle abnormalities in schizophrenia.
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reduced Sleep Spindle activity in schizophrenia patients
American Journal of Psychiatry, 2007Co-Authors: Fabio Ferrarelli, Reto Huber, Michael J Peterson, Marcello Massimini, Michael Murphy, Brady A Riedner, Adam J Watson, Pietro Bria, Giulio TononiAbstract:Objective: High-density EEG during Sleep represents a powerful new tool to reveal potential abnormalities in rhythm-generating mechanisms while avoiding confounding factors associated with waking activities. As a first step in this direction, the authors employed high-density EEG to explore whether Sleep rhythms differ between schizophrenia subjects, healthy individuals, and a psychiatric control group with a history of depression. Method: Healthy comparison subjects (N=17), medicated schizophrenia patients (N=18), and subjects with a history of depression (N=15) were recruited. Subjects were recorded during the first Sleep episode of the night with a 256-electrode high-density EEG. Recordings were analyzed for changes in EEG power spectra, power topography, and Sleep-specific cortical oscillations. Results: The authors found that the schizophrenia group had a significant re
Kevin R Peters - One of the best experts on this subject based on the ideXlab platform.
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age differences in the variability and distribution of Sleep Spindle and rapid eye movement densities
PLOS ONE, 2014Co-Authors: Kevin R Peters, Stuart Fogel, Laura B Ray, Valerie Smith, Carlyle SmithAbstract:The present study had two main objectives. The first objective was to compare the Sleep architecture of young and older adults, with an emphasis on Sleep Spindle density and REM density. The second objective was to examine two aspects of age differences that have not been considered in previous studies: age differences in the variability of Sleep measures as well as the magnitude of age differences in phasic events across the distribution of values (i.e., at each decile rather than a single measure of location such as the mean or median. A total of 24 young (mean age = 20.75±1.78 years) and 24 older (mean age = 71.17±6.15 years) adults underwent in-home polysomnography. Whole-night Spindle density was significantly higher in young adults than older adults. The two age groups did not differ significantly in whole-night REM density, although significant increases in REM density across the night were observed in both age groups. These results suggest that Spindle density is more affected by age than REM density. Although age differences were observed in the degree of absolute variability (older adults had significantly larger variances than young adults for Sleep efficiency and time spent awake after Sleep onset), a similar pattern was also observed within the two age groups: the four Sleep measures with the lowest degrees of relative variability were the same and included time spent in REM and Stage 2 Sleep, total Sleep time, and Sleep efficiency. The distributional analysis of age differences in Sleep Spindle density revealed that the largest age differences were initially observed in the middle of the distributions, but as the night progressed, they were seen at the upper end of the distributions. The results reported here have potential implications for the causes and functional implications of age-related changes in Sleep architecture.
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validating an automated Sleep Spindle detection algorithm using an individualized approach
Journal of Sleep Research, 2010Co-Authors: Laura B Ray, Stuart Fogel, Carlyle Smith, Kevin R PetersAbstract:The goal of the current investigation was to develop a systematic method to validate the accuracy of an automated method of Sleep Spindle detection that takes into consideration individual differences in Spindle amplitude. The benchmarking approach used here could be employed more generally to validate automated Spindle scoring from other detection algorithms. In a sample of Stage 2 Sleep from 10 healthy young subjects, Spindles were identified both manually and automatically. The minimum amplitude threshold used by the Prana (PhiTools, Strasbourg, France) software Spindle detection algorithm to identify a Spindle was subject-specific and determined based upon each subject's mean peak Spindle amplitude. Overall sensitivity and specificity values were 98.96 and 88.49%, respectively, when compared to manual scoring. Selecting individual amplitude thresholds for Spindle detection based on systematic benchmarking data may validate automated Spindle detection methods and improve reproducibility of experimental results. Given that interindividual differences are accounted for, we feel that automatic Spindle detection provides an accurate and efficient alternative approach for detecting Sleep Spindles.