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1.
Epidemiol Psychiatr Sci ; 33: e32, 2024 Jun 26.
Article in English | MEDLINE | ID: mdl-38920396

ABSTRACT

AIMS: Identifying children and/or adolescents who are at highest risk for developing chronic depression is of utmost importance, so that we can develop more effective and targeted interventions to attenuate the risk trajectory of depression. To address this, the objective of this study was to identify young people with persistent depressive symptoms across adolescence and young adulthood and examine the prospective associations between factors and persistent depressive symptoms in young people. METHODS: We used data from 6711 participants in the Avon Longitudinal Study of Parents and Children. Depressive symptoms were assessed at 12.5, 13.5, 16, 17.5, 21 and 22 years with the Short Mood and Feelings Questionnaire, and we further examined the influence of multiple biological, psychological and social factors in explaining chronic depressive symptoms. RESULTS: Using latent class growth analysis, we identified four trajectories of depressive symptoms: persistent high, persistent low, persistent moderate and increasing high. After applying several logistic regression models, we found that loneliness and feeling less connected at school were the most relevant factors for chronic course of depressive symptoms. CONCLUSIONS: Our findings contribute with the identification of those children who are at highest risk for developing chronic depressive symptoms.


Subject(s)
Depression , Humans , Adolescent , Depression/psychology , Depression/epidemiology , United Kingdom/epidemiology , Male , Female , Young Adult , Longitudinal Studies , Chronic Disease/psychology , Risk Factors , Child , Loneliness/psychology , Surveys and Questionnaires , Cohort Studies , Adult , Prospective Studies
2.
Nat Commun ; 11(1): 5363, 2020 10 23.
Article in English | MEDLINE | ID: mdl-33097714

ABSTRACT

Inter-areal synchronization of neuronal oscillations at frequencies below ~100 Hz is a pervasive feature of neuronal activity and is thought to regulate communication in neuronal circuits. In contrast, faster activities and oscillations have been considered to be largely local-circuit-level phenomena without large-scale synchronization between brain regions. We show, using human intracerebral recordings, that 100-400 Hz high-frequency oscillations (HFOs) may be synchronized between widely distributed brain regions. HFO synchronization expresses individual frequency peaks and exhibits reliable connectivity patterns that show stable community structuring. HFO synchronization is also characterized by a laminar profile opposite to that of lower frequencies. Importantly, HFO synchronization is both transiently enhanced and suppressed in separate frequency bands during a response-inhibition task. These findings show that HFO synchronization constitutes a functionally significant form of neuronal spike-timing relationships in brain activity and thus a mesoscopic indication of neuronal communication per se.


Subject(s)
Brain/pathology , Cerebral Cortex/physiology , Cortical Synchronization/physiology , Adult , Brain Mapping , Electric Stimulation , Electroencephalography , Humans , Male , Neurons/physiology , Young Adult
3.
Neuroimage ; 195: 59-66, 2019 07 15.
Article in English | MEDLINE | ID: mdl-30930309

ABSTRACT

Frequency tagging has been widely used to study the role of visual selective attention. Presenting a visual stimulus flickering at a specific frequency generates so-called steady-state visually evoked responses. However, frequency tagging is mostly done at lower frequencies (<30 Hz). This produces a visible flicker, potentially interfering with both perception and neuronal oscillations in the theta, alpha and beta band. To overcome these problems, we used a newly developed projector with a 1440 Hz refresh rate allowing for frequency tagging at higher frequencies. We asked participants to perform a cued spatial attention task in which imperative pictorial stimuli were presented at 63 Hz or 78 Hz while measuring whole-head magnetoencephalography (MEG). We found posterior sensors to show a strong response at the tagged frequency. Importantly, this response was enhanced by spatial attention. Furthermore, we reproduced the typical modulations of alpha band oscillations, i.e., decrease in the alpha power contralateral to the attentional cue. The decrease in alpha power and increase in frequency tagged signal with attention correlated over subjects. We hereby provide proof-of-principle for the use of high-frequency tagging to study sensory processing and neuronal excitability associated with attention.


Subject(s)
Attention/physiology , Evoked Potentials, Visual/physiology , Photic Stimulation/methods , Visual Cortex/physiology , Adult , Female , Humans , Magnetoencephalography/methods , Male , Visual Perception/physiology
4.
Neuroimage ; 185: 565-574, 2019 01 15.
Article in English | MEDLINE | ID: mdl-30317018

ABSTRACT

Neurofeedback requires a direct translation of neuronal brain activity to sensory input given to the user or subject. However, decoding certain states, e.g., mindfulness or wandering thoughts, from ongoing brain activity remains an unresolved problem. In this study, we used magnetoencephalography (MEG) to acquire brain activity during mindfulness meditation and thought-inducing tasks mimicking wandering thoughts. We used a novel real-time feature extraction to decode the mindfulness, i.e., to discriminate it from the thought-inducing tasks. The key methodological novelty of our approach is usage of MEG power spectra and functional connectivity of independent components as features underlying mindfulness states. Performance was measured as the classification accuracy on a separate session but within the same subject. We found that the spectral- and connectivity-based classification approaches allowed discriminating mindfulness and thought-inducing tasks with an accuracy around 60% compared to the 50% chance-level. Both classification approaches showed similar accuracy, although the connectivity approach slightly outperformed the spectral one in a few cases. Detailed analysis showed that the classification coefficients and the associated independent components were highly individual among subjects and a straightforward transfer of the coefficients over subjects provided near chance-level classification accuracy. Thus, discriminating between mindfulness and wandering thoughts seems to be possible, although with limited accuracy, by machine learning, especially on the subject-level. Our hope is that the developed spectral- and connectivity-based decoding methods can be utilized in real-time neurofeedback to decode mindfulness states from ongoing neuronal activity, and hence, provide a basis for improved, individualized mindfulness training.


Subject(s)
Attention/physiology , Brain/physiology , Machine Learning , Mindfulness , Neurofeedback/methods , Adult , Brain Mapping/methods , Female , Humans , Magnetoencephalography/methods , Male , Meditation/methods , Mindfulness/methods
5.
Voen Med Zh ; 336(10): 54-60, 2015 Oct.
Article in Russian | MEDLINE | ID: mdl-26827508

ABSTRACT

Computed tomography is currently one of the most informative methods of diagnostics of a broad range of injuries and diseases, as well as an effective additional mean for various surgical interventions thank to intraoperative use. In this regard, the question of the necessity of the use of this diagnostic technology in mobile hospitals is one of the current tasks. The article analyses the experience of the use of mobile CT scanners at the medical service of the armed forces of foreign states and provides calculations indicating the necessity of the introduction of mobile CT scanners into the hospital link. The review and classification of mobile CT scanners have allowed to formulate technical requirements for their hardware capabilities, as well as to draw conclusions about the conditions of their effective use.


Subject(s)
Magnetic Resonance Imaging/instrumentation , Military Medicine/instrumentation , Tomography Scanners, X-Ray Computed/supply & distribution , Tomography, X-Ray Computed/instrumentation , Russia
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