Klaus Linkenkaer-Hansen - Academia.edu (original) (raw)

Papers by Klaus Linkenkaer-Hansen

Research paper thumbnail of STXBP1 Syndrome Is Characterized by Inhibition-Dominated Dynamics of Resting-State EEG

Frontiers in Physiology, Dec 23, 2021

Research paper thumbnail of Scaling behaviour in music and cortical dynamics interplay to mediate music listening pleasure

Scientific Reports, Nov 27, 2019

neuromagnetic brain activity display 1/f β scaling under rest 25-28 and music 29. Self-similarity... more neuromagnetic brain activity display 1/f β scaling under rest 25-28 and music 29. Self-similarity further characterises the heartbeat variations 30 and such dynamical organization of the nervous system is functionally relevant 17,31-33. Humans can apprehend recursive fractal rules embedded in tone sequences 34 , predict 1/f better than random tempo fluctuations 35 and, a preferential cortical tracking of tones occurs when its pitches display long-range temporal correlations 36. Furthermore, electrophysiological evidence suggests humans process long-distance dependencies typical of music syntax 37. Altogether, it led us to hypothesise that the scaling of music shapes the neuronal scaling behaviour during listening and to posit that the brain's sensitivity to music-and the pleasure derived from listening-lies in their shared similar dynamical complex properties 38. Here, we characterise the self-similarity of fluctuations in loudness, pitch, and rhythm of 12 classical pieces (Fig. 1b,c) and analyse the scaling behaviour of multiscale neuronal activity from different scalp regions (Fig. 1d,e) and cardiac interbeat intervals (Fig. 1f) of healthy individuals-at baseline and during music listening-and associate self-reported pleasure with these measures (see also Table 1).

Research paper thumbnail of Critical-State Dynamics of Avalanches and Oscillations Jointly Emerge from Balanced Excitation/Inhibition in Neuronal Networks

The Journal of Neuroscience, Jul 18, 2012

Research paper thumbnail of Author response: Pre-stimulus phase and amplitude regulation of phase-locked responses are maximized in the critical state

Research paper thumbnail of An EEG nicotinic acetylcholine index to assess the efficacy of pro-cognitive compounds

Clinical Neurophysiology, Nov 1, 2018

General rights Copyright and moral rights for the publications made accessible in the public port... more General rights Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights. • Users may download and print one copy of any publication from the public portal for the purpose of private study or research. • You may not further distribute the material or use it for any profit-making activity or commercial gain • You may freely distribute the URL identifying the publication in the public portal ? Take down policy If you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim.

Research paper thumbnail of Strong long-range temporal correlations of beta/gamma oscillations are associated with poor sustained visual attention performance

European Journal of Neuroscience, Oct 6, 2017

Neuronal oscillations exhibit complex amplitude fluctuations with autocorrelations that persist o... more Neuronal oscillations exhibit complex amplitude fluctuations with autocorrelations that persist over thousands of oscillatory cycles. Such long-range temporal correlations (LRTC) are thought to reflect neuronal systems poised near a critical state, which would render them capable of quick reorganization and responsive to changing processing demands. When we concentrate, however, the influence of internal and external sources of distraction is better reduced, suggesting that neuronal systems involved with sustained attention could benefit from a shift towards the less volatile sub-critical state. To test these ideas, we recorded EEG from healthy volunteers during eyes-closed rest and during a sustained attention task requiring a speeded response to images deviating in their presentation duration. We show that for oscillations recorded during rest, high levels of alpha-band LRTC in the sensorimotor region predicted good reaction-time performance in the attention task. During task execution, however, fast reaction times were associated with high-amplitude beta and gamma oscillations with low LRTC. Finally, we show that reduced LRTC during the attention task compared to the rest condition correlates with better performance, while increased LRTC of oscillations from rest to attention is associated with reduced performance. To our knowledge, this is the first empirical evidence that "resting-state criticality" of neuronal networks predicts swift behavioral responses in a sensorimotor task, and that steady attentive processing of visual stimuli requires brain dynamics with suppressed temporal complexity.

Research paper thumbnail of A Quantitative‐EEG Assessment of Alpha‐1062, a Novel Pro‐Drug of Galantamine for the Treatment of Mild to Moderate Dementia Associated with Alzheimer’s Disease

Alzheimers & Dementia, Dec 1, 2022

Research paper thumbnail of Scale-Free Amplitude Modulation of Neuronal Oscillations Tracks Comprehension of Accelerated Speech

The Journal of Neuroscience, Dec 7, 2017

Speech comprehension is preserved up to a threefold acceleration, but deteriorates rapidly at hig... more Speech comprehension is preserved up to a threefold acceleration, but deteriorates rapidly at higher speeds. Current models posit that perceptual resilience to accelerated speech is limited by the brain's ability to parse speech into syllabic units using ␦/ oscillations. Here, we investigated whether the involvement of neuronal oscillations in processing accelerated speech also relates to their scale-free amplitude modulation as indexed by the strength of long-range temporal correlations (LRTC). We recorded MEG while 24 human subjects (12 females) listened to radio news uttered at different comprehensible rates, at a mostly unintelligible rate and at this same speed interleaved with silence gaps. ␦, , and low-␥ oscillations followed the nonlinear variation of comprehension, with LRTC rising only at the highest speed. In contrast, increasing the rate was associated with a monotonic increase in LRTC in high-␥ activity. When intelligibility was restored with the insertion of silence gaps, LRTC in the ␦, , and low-␥ oscillations resumed the low levels observed for intelligible speech. Remarkably, the lower the individual subject scaling exponents of ␦/ oscillations, the greater the comprehension of the fastest speech rate. Moreover, the strength of LRTC of the speech envelope decreased at the maximal rate, suggesting an inverse relationship with the LRTC of brain dynamics when comprehension halts. Our findings show that scale-free amplitude modulation of cortical oscillations and speech signals are tightly coupled to speech uptake capacity.

Research paper thumbnail of More Severe Insomnia Complaints in People with Stronger Long-Range Temporal Correlations in Wake Resting-State EEG

Frontiers in Physiology, Nov 29, 2016

The complaints of people suffering from Insomnia Disorder (ID) concern both sleep and daytime fun... more The complaints of people suffering from Insomnia Disorder (ID) concern both sleep and daytime functioning. However, little is known about wake brain temporal dynamics in people with ID. We therefore assessed possible alterations in Long-Range Temporal Correlations (LRTC) in the amplitude fluctuations of band-filtered oscillations in electroencephalography (EEG) recordings. We investigated whether LRTC differ between cases with ID and matched controls. Within both groups, we moreover investigated whether individual differences in subjective insomnia complaints are associated with LRTC. Resting-state high-density EEG (256-channel) was recorded in 52 participants with ID and 43 age-and sex-matched controls, during Eyes Open (EO) and Eyes Closed (EC). Detrended fluctuation analysis was applied to the amplitude envelope of band-filtered EEG oscillations (theta, alpha, sigma, beta-1, beta-2) to obtain the Hurst exponents (H), as measures of LRTC. Participants rated their subjective insomnia complaints using the Insomnia Severity Index (ISI). Through general linear models, we evaluated whether H, aggregated across electrodes and frequencies, differed between cases and controls, or showed within-group associations with individual differences in ISI. Additionally, we characterized the spatio-spectral profiles of group differences and associations using non-parametric statistics. H did not differ between cases with ID and controls in any of the frequency bands, neither during EO nor EC. During EO, however, within-group associations between H and ISI indicated that individuals who experienced worse sleep quality had stronger LRTC. Spatio-spectral profiles indicated that the associations held most prominently for the amplitude fluctuations of parietal theta oscillations within the ID group, and of centro-frontal beta-1 oscillations in controls. While people suffering from insomnia experience substantially worse sleep quality than controls, their brain dynamics express similar strength of LRTC. In each group, however, individuals experiencing worse sleep quality tend to have stronger LRTC during eyes open wakefulness, in a spatio-spectral range specific for each group. Taken together, Colombo et al. Insomnia Complaints and Wake-EEG Autocorrelations the findings indicate that subjective insomnia complaints involve distinct dynamical processes in people with ID and controls. The findings are in agreement with recent reports on decreasing LRTC with sleep depth, and with the hypothesis that sleep balances brain excitability.

Research paper thumbnail of Resting-state oscillations reveal disturbed excitation–inhibition ratio in Alzheimer’s disease patients

Scientific Reports, May 7, 2023

An early disruption of neuronal excitation-inhibition (E-I) balance in preclinical animal models ... more An early disruption of neuronal excitation-inhibition (E-I) balance in preclinical animal models of Alzheimer's disease (AD) has been frequently reported, but is difficult to measure directly and noninvasively in humans. Here, we examined known and novel neurophysiological measures sensitive to E-I in patients across the AD continuum. Resting-state magnetoencephalography (MEG) data of 86 amyloid-biomarker-confirmed subjects across the AD continuum (17 patients diagnosed with subjective cognitive decline, 18 with mild cognitive impairment (MCI) and 51 with dementia due to probable AD (AD dementia)), 46 healthy elderly and 20 young control subjects were reconstructed to source-space. E-I balance was investigated by detrended fluctuation analysis (DFA), a functional E/I (fE/I) algorithm, and the aperiodic exponent of the power spectrum. We found a disrupted E-I ratio in AD dementia patients specifically, by a lower DFA, and a shift towards higher excitation, by a higher fE/I and a lower aperiodic exponent. Healthy subjects showed lower fE/I ratios (< 1.0) than reported in previous literature, not explained by age or choice of an arbitrary threshold parameter, which warrants caution in interpretation of fE/I results. Correlation analyses showed that a lower DFA (E-I imbalance) and a lower aperiodic exponent (more excitation) was associated with a worse cognitive score in AD dementia patients. In contrast, a higher DFA in the hippocampi of MCI patients was associated with a worse cognitive score. This MEG-study showed E-I imbalance, likely due to increased excitation, in AD dementia, but not in early stage AD patients. To accurately determine the direction of shift in E-I balance, validations of the currently used markers and additional in vivo markers of E-I are required.

Research paper thumbnail of Consistency of EEG source localization and connectivity estimates

bioRxiv (Cold Spring Harbor Laboratory), Aug 31, 2016

As the EEG inverse problem does not have a unique solution, the sources reconstructed from EEG an... more As the EEG inverse problem does not have a unique solution, the sources reconstructed from EEG and their connectivity properties depend on forward and inverse modeling parameters such as the choice of an anatomical template and electrical model, prior assumptions on the sources, and further implementational details. In order to use source connectivity analysis as a reliable research tool, there is a need for stability across a wider range of standard estimation routines. Using resting state EEG recordings of N=65 participants acquired within two studies, we present the first comprehensive assessment of the consistency of EEG source localization and functional/effective connectivity metrics across two anatomical templates (ICBM152 and Colin27), three electrical models (BEM, FEM and spherical harmonics expansions), three inverse methods (WMNE, eLORETA and LCMV), and three software implementations (Brainstorm, Fieldtrip and our own toolbox). Source localizations were found to be more stable across reconstruction pipelines than subsequent estimations of functional connectivity, while effective connectivity estimates where the least consistent. All results were relatively unaffected by the choice of the electrical head model, while the choice of the inverse method and source imaging package induced a considerable variability. In particular, a relatively strong difference was found between LCMV beamformer solutions on one hand and eLORETA/WMNE distributed inverse solutions on the other hand. We also observed a gradual decrease of consistency when results are compared between studies, within individual participants, and between individual participants. In order to provide reliable findings in the face of the observed variability, additional simulations involving interacting brain sources are required. Meanwhile, we encourage verification of the obtained results using more than one source imaging procedure.

Research paper thumbnail of Intellectually able adults with autism spectrum disorder show typical resting-state EEG activity

Scientific Reports, Nov 8, 2022

There is broad interest in discovering quantifiable physiological biomarkers for psychiatric diso... more There is broad interest in discovering quantifiable physiological biomarkers for psychiatric disorders to aid diagnostic assessment. However, finding biomarkers for autism spectrum disorder (ASD) has proven particularly difficult, partly due to high heterogeneity. Here, we recorded five minutes eyesclosed rest electroencephalography (EEG) from 186 adults (51% with ASD and 49% without ASD) and investigated the potential of EEG biomarkers to classify ASD using three conventional machine learning models with two-layer cross-validation. Comprehensive characterization of spectral, temporal and spatial dimensions of source-modelled EEG resulted in 3443 biomarkers per recording. We found no significant group-mean or group-variance differences for any of the EEG features. Interestingly, we obtained validation accuracies above 80%; however, the best machine learning model merely distinguished ASD from the non-autistic comparison group with a mean balanced test accuracy of 56% on the entirely unseen test set. The large drop in model performance between validation and testing, stress the importance of rigorous model evaluation, and further highlights the high heterogeneity in ASD. Overall, the lack of significant differences and weak classification indicates that, at the group level, intellectually able adults with ASD show remarkably typical resting-state EEG. Autism spectrum disorder (ASD) is defined by persistent differences in social interactions, atypical sensory reactivity, and restricted and repetitive behavior 1. High heterogeneity exists among individuals receiving the diagnosis, since the criteria allow a broad spectrum of symptoms, and the neural mechanisms underlying ASD remain unclear. To elucidate the neurobiological mechanisms behind ASD, many studies have used neuroimaging 2-4. Discovery of biomarkers for ASD has the potential to support diagnosis and might disentangle the heterogeneity 5. Recently, there has been a growing interest in discovering resting-state electroencephalographic (EEG) biomarkers for various neuropsychiatric conditions, as EEG has good clinical practicality, due to being non-invasive, portable, widely available, and low cost. Many different resting-state EEG features have been investigated in regards to ASD, with spectral power being the most commonly used feature. Decreased theta power 6 , alpha power 7-10 and gamma power have been observed in ASD 11,12. However, increased alpha power 13 and gamma power have also been reported in ASD 14. Other spectral features, e.g., peak alpha frequency 15 , theta/beta ratio 16 and asymmetry 17 have also been associated with ASD. Besides spectral features, abnormal functional connectivity 18 , microstates 19 , and measurements of criticality 20,21 have also been found in ASD. The role of each individual feature and their implications on ASD are outside the scope of this paper (for reviews, see 2,3,22). In addition to identifying group mean differences of resting-state EEG features in ASD, many recent studies also investigated the potential of classifying ASD with predictive machine learning models. The advantages of predictive modelling is that it is optimized for predicting new subjects or future outcomes, which aligns with

Research paper thumbnail of Bumetanide As a Candidate Treatment for Behavioral Problems in Tuberous Sclerosis Complex

Frontiers in Neurology, Sep 8, 2017

Background: Recent studies indicate excitatory GABA action in and around tubers in patients with ... more Background: Recent studies indicate excitatory GABA action in and around tubers in patients with tuberous sclerosis complex (TSC). This may contribute to recurrent seizures and behavioral problems that may be treated by agents that enhance GABAergic transmission by influencing chloride regulation. Case presentation: Here, we used the chloride transporter antagonist bumetanide to treat a female adolescent TSC patient with refractory seizures, sensory hyper-reactivity, and a variety of repetitive and compulsive behaviors. Methods: To evaluate the effect of bumetanide on behavior, auditory sensory processing, and hyperexcitability, we obtained questionnaire data, event-related potentials (ERP), and resting state EEG at baseline, after 3 and 6 months of treatment and after 1 month washout period. Discussion: Six months of treatment resulted in a marked improvement in all relevant behavioral domains, as was substantiated by the parent questionnaires. In addition, resting-state electroencephalography and ERP suggested a favorable effect of bumetanide on hyperexcitability and sensory processing. These findings encourage further studies of bumetanide on neuropsychiatric outcome in TSC.

Research paper thumbnail of Resting-State Subjective Experience and EEG Biomarkers Are Associated with Sleep-Onset Latency

Frontiers in Psychology, Apr 12, 2016

Difficulties initiating sleep are common in several disorders, including insomnia and attention d... more Difficulties initiating sleep are common in several disorders, including insomnia and attention deficit hyperactivity disorder. These disorders are prevalent, bearing significant societal and financial costs which require the consideration of new treatment strategies and a better understanding of the physiological and cognitive processes surrounding the time of preparing for sleep or falling asleep. Here, we search for neuro-cognitive associations in the resting state and examine their relevance for predicting sleep-onset latency using multi-level mixed models. Multiple EEG recordings were obtained from healthy male participants (N = 13) during a series of 5 min eyes-closed resting-state trials (in total, n = 223) followed by a period-varying in length up to 30 min-that either allowed subjects to transition into sleep ("sleep trials," n sleep = 144) or was ended while they were still awake ("wake trials," n wake = 79). After both eyes-closed rest, sleep and wake trials, subjective experience was assessed using the Amsterdam Resting-State Questionnaire (ARSQ). Our data revealed multiple associations between eyes-closed rest alpha and theta oscillations and ARSQ-dimensions Discontinuity of Mind, Self, Theory of Mind, Planning, and Sleepiness. The sleep trials showed that the transition toward the first sleep stage exclusively affected subjective experiences related to Theory of Mind, Planning, and Sleepiness. Importantly, sleep-onset latency was negatively associated both with eyes-closed rest ratings on the ARSQ dimension of Sleepiness and with the long-range temporal correlations of parietal theta oscillations derived by detrended fluctuation analysis (DFA). These results could be relevant to the development of personalized tools that help evaluate the success of falling asleep based on measures of resting-state cognition and EEG biomarkers.

Research paper thumbnail of Non-zero mean and asymmetry of neuronal oscillations have different implications for evoked responses

Clinical Neurophysiology, Feb 1, 2010

The aim of the present study was to show analytically and with simulations that it is the non-zer... more The aim of the present study was to show analytically and with simulations that it is the non-zero mean of neuronal oscillations, and not an amplitude asymmetry of peaks and troughs, that is a prerequisite for the generation of evoked responses through a mechanism of amplitude modulation of oscillations. Secondly, we detail the rationale and implementation of the &amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;quot;baseline-shift index&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;quot; (BSI) for deducing whether empirical oscillations have non-zero mean. Finally, we illustrate with empirical data why the &amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;quot;amplitude fluctuation asymmetry&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;quot; (AFA) index should be used with caution in research aimed at explaining variability in evoked responses through a mechanism of amplitude modulation of ongoing oscillations. An analytical approach, simulations and empirical MEG data were used to compare the specificity of BSI and AFA index to differentiate between a non-zero mean and a non-sinusoidal shape of neuronal oscillations. Both the BSI and the AFA index were sensitive to the presence of non-zero mean in neuronal oscillations. The AFA index, however, was also sensitive to the shape of oscillations even when they had a zero mean. Our findings indicate that it is the non-zero mean of neuronal oscillations, and not an amplitude asymmetry of peaks and troughs, that is a prerequisite for the generation of evoked responses through a mechanism of amplitude modulation of oscillations. A clear distinction should be made between the shape and non-zero mean properties of neuronal oscillations. This is because only the latter contributes to evoked responses, whereas the former does not.

Research paper thumbnail of P.4.11 Bumetanide in Autism Medication and Biomarker (BAMBI) study: Medication response profiles

European Neuropsychopharmacology, 2019

Introduction: Gray matter (GM) reductions are often reported in schizophrenia, but their origins ... more Introduction: Gray matter (GM) reductions are often reported in schizophrenia, but their origins remain unknown. One potential source of neuroimaging abnormalities in psychotic disorders is the comorbidity with medical conditions known to affect the brain. Almost 20% of participants with first-episode psychosis (FEP) are obese [1]. Obesity is frequently associated with antipsychotic treatment as well as neurostructural alterations [2]. We previously reported that both the diagnosis of FEP and obesity/overweight were additively associated with advanced brain age [3]. Importantly, BMI increased significantly during hospitalization of participants with FEP, probably as effect of antipsychotic mediaction. Here, Based on our previous study we tested the hypothesis that both FEP and BMI are negatively associated with GM volumes. It is unclear to what extent weight gain related to antipsychotics contributes to these alterations. Materials and methods: We analyzed data from 120 patients with FES and 114 controls, the same sample as in our previous analyses [3]. We focused on individuals with FEP, who met the following inclusion criteria: 1) were undergoing their first psychiatric hospitalization, 2) had the ICD-10 diagnosis of schizophrenia (F20), or acute and transient psychotic disorders (F23) made by psychiatrist according to Mini-International Neuropsychiatric Interview, 3) had < 24 months of untreated psychosis, 4) were 18-35 years old. Average durration of ilness was 5.1 months and average durration of anstipsychotic treatment was 2 months. We conducted a multiple regression voxel-based morphometry analysis to assess the association between FEP, BMI, and GM volume. We added age and sex to the model as covariates of no interest. We used voxel-based morphometry (FSL-VBM; http://fsl.fmrib.ox.ac.uk/fsl/fslwiki/FSLVBM) for analyses and we applied permutation-based testing, corrected for multiple comparisons implementing threshold-free cluster enhancement (TFCE). We considered corrected p-values < 0.05 as significant. Results: FEP was associated with lower GM in the right cerebellum (pTFCE = 0.004; tmax = 4.37; kE = 1242 vox), left cerebellum (pTFCE = 0.004; tmax = 4.41; kE = 1207 vox), left frontal (pTFCE = 0.024; tmax = 4.70; kE = 151 vox) and right temporal cortices (pTFCE = 0.031; tmax = 4.25; kE = 110 vox,). Higher BMI was associated with lower GM in the left cerebellum (pTFCE; tmax = 4.56; kE = 858 vox). Conclusions: Diagnosis of FEP was associated with lower GM in fronto-temporal areas. The findings are consistent

Research paper thumbnail of Catecholamines, not acetylcholine, alter cortical and perceptual dynamics in line with increased excitation-inhibition ratio

bioRxiv (Cold Spring Harbor Laboratory), Aug 7, 2017

The ascending modulatory systems of the brain stem are powerful regulators of global brain state.... more The ascending modulatory systems of the brain stem are powerful regulators of global brain state. Disturbances of these systems are implicated in several major neuropsychiatric disorders. Yet, how these systems interact with specific neural computations in the cerebral cortex to shape perception, cognition, and behavior remains poorly understood. Here, we probed into the effect of two such systems, the catecholaminergic (dopaminergic and noradrenergic) and cholinergic systems, on an important aspect of cortical computation: its intrinsic variability. To this end, we combined placebo-controlled pharmacological intervention in humans, recordings of cortical population activity using magnetoencephalography (MEG), and psychophysical measurements of the perception of ambiguous visual input. A low-dose catecholaminergic, but not cholinergic, manipulation altered the rate of spontaneous perceptual fluctuations as well as the temporal structure of "scale-free" population activity of large swaths of the visual and parietal cortices. Computational analyses indicate that both effects were consistent with an increase in excitatory relative to inhibitory activity in the cortical areas underlying visual perceptual inference. We propose that catecholamines regulate the variability of perception and cognition through dynamically changing the cortical excitation-inhibition ratio. The combined readout of fluctuations in perception and cortical activity we established here may prove useful as an efficient and easily accessible marker of altered cortical computation in neuropsychiatric disorders.

Research paper thumbnail of Criticality theory applied to the 'wandering mind' problem in health and major depressive disorder

Research paper thumbnail of Catecholamines Alter the Intrinsic Variability of Cortical Population Activity and Perception

The ascending modulatory systems of the brainstem are powerful regulators of global brain state. ... more The ascending modulatory systems of the brainstem are powerful regulators of global brain state. Disturbances of these systems are implicated in several major neuropsychiatric disorders. Yet, how these systems interact with specific neural computations in the cerebral cortex to shape perception, cognition, and behavior remains poorly understood. Here, we probed into the effect of two such systems, the catecholaminergic (dopaminergic and noradrenergic) and cholinergic systems, on an important aspect of cortical computation: its intrinsic variability. To this end, we combined placebo-controlled pharmacological intervention in humans, magnetoencephalographic (MEG) recordings of cortical population activity, and psychophysical measurements of the perception of ambiguous visual input. A low-dose catecholaminergic, but not cholinergic, manipulation altered the rate of spontaneous perceptual fluctuations as well as the temporal structure of "scalefree" population activity of large swaths of visual and parietal cortex. Computational analyses indicate that both effects were consistent with an increase in excitatory relative to inhibitory activity in the cortical areas underlying visual perceptual inference. We propose that catecholamines regulate the variability of perception and cognition through dynamically changing the cortical excitation-inhibition ratio. The combined read-out of fluctuations in perception and cortical activity we established here may prove useful as an efficient, and easily accessible marker of altered cortical computation in neuropsychiatric disorders. .

Research paper thumbnail of Improved Manual Annotation of EEG Signals through Convolutional Neural Network Guidance

eneuro

The development of validated algorithms for automated handling of artifacts is essential for reli... more The development of validated algorithms for automated handling of artifacts is essential for reliable and fast processing of EEG signals. Recently, there have been methodological advances in designing machine-learning algorithms to improve artifact detection of trained professionals who usually meticulously inspect and manually annotate EEG signals. However, validation of these methods is hindered by the lack of a gold standard as data are mostly private and data annotation is time consuming and error prone. In the effort to circumvent these issues, we propose an iterative learning model to speed up and reduce errors of manual annotation of EEG. We use a convolutional neural network (CNN) to train on expert-annotated eyes-open and eyes-closed resting-state EEG data from typically developing children (n= 30) and children with neurodevelopmental disorders (n= 141). To overcome the circular reasoning of aiming to develop a new algorithm and benchmarking to a manually-annotated gold sta...

Research paper thumbnail of STXBP1 Syndrome Is Characterized by Inhibition-Dominated Dynamics of Resting-State EEG

Frontiers in Physiology, Dec 23, 2021

Research paper thumbnail of Scaling behaviour in music and cortical dynamics interplay to mediate music listening pleasure

Scientific Reports, Nov 27, 2019

neuromagnetic brain activity display 1/f β scaling under rest 25-28 and music 29. Self-similarity... more neuromagnetic brain activity display 1/f β scaling under rest 25-28 and music 29. Self-similarity further characterises the heartbeat variations 30 and such dynamical organization of the nervous system is functionally relevant 17,31-33. Humans can apprehend recursive fractal rules embedded in tone sequences 34 , predict 1/f better than random tempo fluctuations 35 and, a preferential cortical tracking of tones occurs when its pitches display long-range temporal correlations 36. Furthermore, electrophysiological evidence suggests humans process long-distance dependencies typical of music syntax 37. Altogether, it led us to hypothesise that the scaling of music shapes the neuronal scaling behaviour during listening and to posit that the brain's sensitivity to music-and the pleasure derived from listening-lies in their shared similar dynamical complex properties 38. Here, we characterise the self-similarity of fluctuations in loudness, pitch, and rhythm of 12 classical pieces (Fig. 1b,c) and analyse the scaling behaviour of multiscale neuronal activity from different scalp regions (Fig. 1d,e) and cardiac interbeat intervals (Fig. 1f) of healthy individuals-at baseline and during music listening-and associate self-reported pleasure with these measures (see also Table 1).

Research paper thumbnail of Critical-State Dynamics of Avalanches and Oscillations Jointly Emerge from Balanced Excitation/Inhibition in Neuronal Networks

The Journal of Neuroscience, Jul 18, 2012

Research paper thumbnail of Author response: Pre-stimulus phase and amplitude regulation of phase-locked responses are maximized in the critical state

Research paper thumbnail of An EEG nicotinic acetylcholine index to assess the efficacy of pro-cognitive compounds

Clinical Neurophysiology, Nov 1, 2018

General rights Copyright and moral rights for the publications made accessible in the public port... more General rights Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights. • Users may download and print one copy of any publication from the public portal for the purpose of private study or research. • You may not further distribute the material or use it for any profit-making activity or commercial gain • You may freely distribute the URL identifying the publication in the public portal ? Take down policy If you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim.

Research paper thumbnail of Strong long-range temporal correlations of beta/gamma oscillations are associated with poor sustained visual attention performance

European Journal of Neuroscience, Oct 6, 2017

Neuronal oscillations exhibit complex amplitude fluctuations with autocorrelations that persist o... more Neuronal oscillations exhibit complex amplitude fluctuations with autocorrelations that persist over thousands of oscillatory cycles. Such long-range temporal correlations (LRTC) are thought to reflect neuronal systems poised near a critical state, which would render them capable of quick reorganization and responsive to changing processing demands. When we concentrate, however, the influence of internal and external sources of distraction is better reduced, suggesting that neuronal systems involved with sustained attention could benefit from a shift towards the less volatile sub-critical state. To test these ideas, we recorded EEG from healthy volunteers during eyes-closed rest and during a sustained attention task requiring a speeded response to images deviating in their presentation duration. We show that for oscillations recorded during rest, high levels of alpha-band LRTC in the sensorimotor region predicted good reaction-time performance in the attention task. During task execution, however, fast reaction times were associated with high-amplitude beta and gamma oscillations with low LRTC. Finally, we show that reduced LRTC during the attention task compared to the rest condition correlates with better performance, while increased LRTC of oscillations from rest to attention is associated with reduced performance. To our knowledge, this is the first empirical evidence that "resting-state criticality" of neuronal networks predicts swift behavioral responses in a sensorimotor task, and that steady attentive processing of visual stimuli requires brain dynamics with suppressed temporal complexity.

Research paper thumbnail of A Quantitative‐EEG Assessment of Alpha‐1062, a Novel Pro‐Drug of Galantamine for the Treatment of Mild to Moderate Dementia Associated with Alzheimer’s Disease

Alzheimers & Dementia, Dec 1, 2022

Research paper thumbnail of Scale-Free Amplitude Modulation of Neuronal Oscillations Tracks Comprehension of Accelerated Speech

The Journal of Neuroscience, Dec 7, 2017

Speech comprehension is preserved up to a threefold acceleration, but deteriorates rapidly at hig... more Speech comprehension is preserved up to a threefold acceleration, but deteriorates rapidly at higher speeds. Current models posit that perceptual resilience to accelerated speech is limited by the brain's ability to parse speech into syllabic units using ␦/ oscillations. Here, we investigated whether the involvement of neuronal oscillations in processing accelerated speech also relates to their scale-free amplitude modulation as indexed by the strength of long-range temporal correlations (LRTC). We recorded MEG while 24 human subjects (12 females) listened to radio news uttered at different comprehensible rates, at a mostly unintelligible rate and at this same speed interleaved with silence gaps. ␦, , and low-␥ oscillations followed the nonlinear variation of comprehension, with LRTC rising only at the highest speed. In contrast, increasing the rate was associated with a monotonic increase in LRTC in high-␥ activity. When intelligibility was restored with the insertion of silence gaps, LRTC in the ␦, , and low-␥ oscillations resumed the low levels observed for intelligible speech. Remarkably, the lower the individual subject scaling exponents of ␦/ oscillations, the greater the comprehension of the fastest speech rate. Moreover, the strength of LRTC of the speech envelope decreased at the maximal rate, suggesting an inverse relationship with the LRTC of brain dynamics when comprehension halts. Our findings show that scale-free amplitude modulation of cortical oscillations and speech signals are tightly coupled to speech uptake capacity.

Research paper thumbnail of More Severe Insomnia Complaints in People with Stronger Long-Range Temporal Correlations in Wake Resting-State EEG

Frontiers in Physiology, Nov 29, 2016

The complaints of people suffering from Insomnia Disorder (ID) concern both sleep and daytime fun... more The complaints of people suffering from Insomnia Disorder (ID) concern both sleep and daytime functioning. However, little is known about wake brain temporal dynamics in people with ID. We therefore assessed possible alterations in Long-Range Temporal Correlations (LRTC) in the amplitude fluctuations of band-filtered oscillations in electroencephalography (EEG) recordings. We investigated whether LRTC differ between cases with ID and matched controls. Within both groups, we moreover investigated whether individual differences in subjective insomnia complaints are associated with LRTC. Resting-state high-density EEG (256-channel) was recorded in 52 participants with ID and 43 age-and sex-matched controls, during Eyes Open (EO) and Eyes Closed (EC). Detrended fluctuation analysis was applied to the amplitude envelope of band-filtered EEG oscillations (theta, alpha, sigma, beta-1, beta-2) to obtain the Hurst exponents (H), as measures of LRTC. Participants rated their subjective insomnia complaints using the Insomnia Severity Index (ISI). Through general linear models, we evaluated whether H, aggregated across electrodes and frequencies, differed between cases and controls, or showed within-group associations with individual differences in ISI. Additionally, we characterized the spatio-spectral profiles of group differences and associations using non-parametric statistics. H did not differ between cases with ID and controls in any of the frequency bands, neither during EO nor EC. During EO, however, within-group associations between H and ISI indicated that individuals who experienced worse sleep quality had stronger LRTC. Spatio-spectral profiles indicated that the associations held most prominently for the amplitude fluctuations of parietal theta oscillations within the ID group, and of centro-frontal beta-1 oscillations in controls. While people suffering from insomnia experience substantially worse sleep quality than controls, their brain dynamics express similar strength of LRTC. In each group, however, individuals experiencing worse sleep quality tend to have stronger LRTC during eyes open wakefulness, in a spatio-spectral range specific for each group. Taken together, Colombo et al. Insomnia Complaints and Wake-EEG Autocorrelations the findings indicate that subjective insomnia complaints involve distinct dynamical processes in people with ID and controls. The findings are in agreement with recent reports on decreasing LRTC with sleep depth, and with the hypothesis that sleep balances brain excitability.

Research paper thumbnail of Resting-state oscillations reveal disturbed excitation–inhibition ratio in Alzheimer’s disease patients

Scientific Reports, May 7, 2023

An early disruption of neuronal excitation-inhibition (E-I) balance in preclinical animal models ... more An early disruption of neuronal excitation-inhibition (E-I) balance in preclinical animal models of Alzheimer's disease (AD) has been frequently reported, but is difficult to measure directly and noninvasively in humans. Here, we examined known and novel neurophysiological measures sensitive to E-I in patients across the AD continuum. Resting-state magnetoencephalography (MEG) data of 86 amyloid-biomarker-confirmed subjects across the AD continuum (17 patients diagnosed with subjective cognitive decline, 18 with mild cognitive impairment (MCI) and 51 with dementia due to probable AD (AD dementia)), 46 healthy elderly and 20 young control subjects were reconstructed to source-space. E-I balance was investigated by detrended fluctuation analysis (DFA), a functional E/I (fE/I) algorithm, and the aperiodic exponent of the power spectrum. We found a disrupted E-I ratio in AD dementia patients specifically, by a lower DFA, and a shift towards higher excitation, by a higher fE/I and a lower aperiodic exponent. Healthy subjects showed lower fE/I ratios (< 1.0) than reported in previous literature, not explained by age or choice of an arbitrary threshold parameter, which warrants caution in interpretation of fE/I results. Correlation analyses showed that a lower DFA (E-I imbalance) and a lower aperiodic exponent (more excitation) was associated with a worse cognitive score in AD dementia patients. In contrast, a higher DFA in the hippocampi of MCI patients was associated with a worse cognitive score. This MEG-study showed E-I imbalance, likely due to increased excitation, in AD dementia, but not in early stage AD patients. To accurately determine the direction of shift in E-I balance, validations of the currently used markers and additional in vivo markers of E-I are required.

Research paper thumbnail of Consistency of EEG source localization and connectivity estimates

bioRxiv (Cold Spring Harbor Laboratory), Aug 31, 2016

As the EEG inverse problem does not have a unique solution, the sources reconstructed from EEG an... more As the EEG inverse problem does not have a unique solution, the sources reconstructed from EEG and their connectivity properties depend on forward and inverse modeling parameters such as the choice of an anatomical template and electrical model, prior assumptions on the sources, and further implementational details. In order to use source connectivity analysis as a reliable research tool, there is a need for stability across a wider range of standard estimation routines. Using resting state EEG recordings of N=65 participants acquired within two studies, we present the first comprehensive assessment of the consistency of EEG source localization and functional/effective connectivity metrics across two anatomical templates (ICBM152 and Colin27), three electrical models (BEM, FEM and spherical harmonics expansions), three inverse methods (WMNE, eLORETA and LCMV), and three software implementations (Brainstorm, Fieldtrip and our own toolbox). Source localizations were found to be more stable across reconstruction pipelines than subsequent estimations of functional connectivity, while effective connectivity estimates where the least consistent. All results were relatively unaffected by the choice of the electrical head model, while the choice of the inverse method and source imaging package induced a considerable variability. In particular, a relatively strong difference was found between LCMV beamformer solutions on one hand and eLORETA/WMNE distributed inverse solutions on the other hand. We also observed a gradual decrease of consistency when results are compared between studies, within individual participants, and between individual participants. In order to provide reliable findings in the face of the observed variability, additional simulations involving interacting brain sources are required. Meanwhile, we encourage verification of the obtained results using more than one source imaging procedure.

Research paper thumbnail of Intellectually able adults with autism spectrum disorder show typical resting-state EEG activity

Scientific Reports, Nov 8, 2022

There is broad interest in discovering quantifiable physiological biomarkers for psychiatric diso... more There is broad interest in discovering quantifiable physiological biomarkers for psychiatric disorders to aid diagnostic assessment. However, finding biomarkers for autism spectrum disorder (ASD) has proven particularly difficult, partly due to high heterogeneity. Here, we recorded five minutes eyesclosed rest electroencephalography (EEG) from 186 adults (51% with ASD and 49% without ASD) and investigated the potential of EEG biomarkers to classify ASD using three conventional machine learning models with two-layer cross-validation. Comprehensive characterization of spectral, temporal and spatial dimensions of source-modelled EEG resulted in 3443 biomarkers per recording. We found no significant group-mean or group-variance differences for any of the EEG features. Interestingly, we obtained validation accuracies above 80%; however, the best machine learning model merely distinguished ASD from the non-autistic comparison group with a mean balanced test accuracy of 56% on the entirely unseen test set. The large drop in model performance between validation and testing, stress the importance of rigorous model evaluation, and further highlights the high heterogeneity in ASD. Overall, the lack of significant differences and weak classification indicates that, at the group level, intellectually able adults with ASD show remarkably typical resting-state EEG. Autism spectrum disorder (ASD) is defined by persistent differences in social interactions, atypical sensory reactivity, and restricted and repetitive behavior 1. High heterogeneity exists among individuals receiving the diagnosis, since the criteria allow a broad spectrum of symptoms, and the neural mechanisms underlying ASD remain unclear. To elucidate the neurobiological mechanisms behind ASD, many studies have used neuroimaging 2-4. Discovery of biomarkers for ASD has the potential to support diagnosis and might disentangle the heterogeneity 5. Recently, there has been a growing interest in discovering resting-state electroencephalographic (EEG) biomarkers for various neuropsychiatric conditions, as EEG has good clinical practicality, due to being non-invasive, portable, widely available, and low cost. Many different resting-state EEG features have been investigated in regards to ASD, with spectral power being the most commonly used feature. Decreased theta power 6 , alpha power 7-10 and gamma power have been observed in ASD 11,12. However, increased alpha power 13 and gamma power have also been reported in ASD 14. Other spectral features, e.g., peak alpha frequency 15 , theta/beta ratio 16 and asymmetry 17 have also been associated with ASD. Besides spectral features, abnormal functional connectivity 18 , microstates 19 , and measurements of criticality 20,21 have also been found in ASD. The role of each individual feature and their implications on ASD are outside the scope of this paper (for reviews, see 2,3,22). In addition to identifying group mean differences of resting-state EEG features in ASD, many recent studies also investigated the potential of classifying ASD with predictive machine learning models. The advantages of predictive modelling is that it is optimized for predicting new subjects or future outcomes, which aligns with

Research paper thumbnail of Bumetanide As a Candidate Treatment for Behavioral Problems in Tuberous Sclerosis Complex

Frontiers in Neurology, Sep 8, 2017

Background: Recent studies indicate excitatory GABA action in and around tubers in patients with ... more Background: Recent studies indicate excitatory GABA action in and around tubers in patients with tuberous sclerosis complex (TSC). This may contribute to recurrent seizures and behavioral problems that may be treated by agents that enhance GABAergic transmission by influencing chloride regulation. Case presentation: Here, we used the chloride transporter antagonist bumetanide to treat a female adolescent TSC patient with refractory seizures, sensory hyper-reactivity, and a variety of repetitive and compulsive behaviors. Methods: To evaluate the effect of bumetanide on behavior, auditory sensory processing, and hyperexcitability, we obtained questionnaire data, event-related potentials (ERP), and resting state EEG at baseline, after 3 and 6 months of treatment and after 1 month washout period. Discussion: Six months of treatment resulted in a marked improvement in all relevant behavioral domains, as was substantiated by the parent questionnaires. In addition, resting-state electroencephalography and ERP suggested a favorable effect of bumetanide on hyperexcitability and sensory processing. These findings encourage further studies of bumetanide on neuropsychiatric outcome in TSC.

Research paper thumbnail of Resting-State Subjective Experience and EEG Biomarkers Are Associated with Sleep-Onset Latency

Frontiers in Psychology, Apr 12, 2016

Difficulties initiating sleep are common in several disorders, including insomnia and attention d... more Difficulties initiating sleep are common in several disorders, including insomnia and attention deficit hyperactivity disorder. These disorders are prevalent, bearing significant societal and financial costs which require the consideration of new treatment strategies and a better understanding of the physiological and cognitive processes surrounding the time of preparing for sleep or falling asleep. Here, we search for neuro-cognitive associations in the resting state and examine their relevance for predicting sleep-onset latency using multi-level mixed models. Multiple EEG recordings were obtained from healthy male participants (N = 13) during a series of 5 min eyes-closed resting-state trials (in total, n = 223) followed by a period-varying in length up to 30 min-that either allowed subjects to transition into sleep ("sleep trials," n sleep = 144) or was ended while they were still awake ("wake trials," n wake = 79). After both eyes-closed rest, sleep and wake trials, subjective experience was assessed using the Amsterdam Resting-State Questionnaire (ARSQ). Our data revealed multiple associations between eyes-closed rest alpha and theta oscillations and ARSQ-dimensions Discontinuity of Mind, Self, Theory of Mind, Planning, and Sleepiness. The sleep trials showed that the transition toward the first sleep stage exclusively affected subjective experiences related to Theory of Mind, Planning, and Sleepiness. Importantly, sleep-onset latency was negatively associated both with eyes-closed rest ratings on the ARSQ dimension of Sleepiness and with the long-range temporal correlations of parietal theta oscillations derived by detrended fluctuation analysis (DFA). These results could be relevant to the development of personalized tools that help evaluate the success of falling asleep based on measures of resting-state cognition and EEG biomarkers.

Research paper thumbnail of Non-zero mean and asymmetry of neuronal oscillations have different implications for evoked responses

Clinical Neurophysiology, Feb 1, 2010

The aim of the present study was to show analytically and with simulations that it is the non-zer... more The aim of the present study was to show analytically and with simulations that it is the non-zero mean of neuronal oscillations, and not an amplitude asymmetry of peaks and troughs, that is a prerequisite for the generation of evoked responses through a mechanism of amplitude modulation of oscillations. Secondly, we detail the rationale and implementation of the &amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;quot;baseline-shift index&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;quot; (BSI) for deducing whether empirical oscillations have non-zero mean. Finally, we illustrate with empirical data why the &amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;quot;amplitude fluctuation asymmetry&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;quot; (AFA) index should be used with caution in research aimed at explaining variability in evoked responses through a mechanism of amplitude modulation of ongoing oscillations. An analytical approach, simulations and empirical MEG data were used to compare the specificity of BSI and AFA index to differentiate between a non-zero mean and a non-sinusoidal shape of neuronal oscillations. Both the BSI and the AFA index were sensitive to the presence of non-zero mean in neuronal oscillations. The AFA index, however, was also sensitive to the shape of oscillations even when they had a zero mean. Our findings indicate that it is the non-zero mean of neuronal oscillations, and not an amplitude asymmetry of peaks and troughs, that is a prerequisite for the generation of evoked responses through a mechanism of amplitude modulation of oscillations. A clear distinction should be made between the shape and non-zero mean properties of neuronal oscillations. This is because only the latter contributes to evoked responses, whereas the former does not.

Research paper thumbnail of P.4.11 Bumetanide in Autism Medication and Biomarker (BAMBI) study: Medication response profiles

European Neuropsychopharmacology, 2019

Introduction: Gray matter (GM) reductions are often reported in schizophrenia, but their origins ... more Introduction: Gray matter (GM) reductions are often reported in schizophrenia, but their origins remain unknown. One potential source of neuroimaging abnormalities in psychotic disorders is the comorbidity with medical conditions known to affect the brain. Almost 20% of participants with first-episode psychosis (FEP) are obese [1]. Obesity is frequently associated with antipsychotic treatment as well as neurostructural alterations [2]. We previously reported that both the diagnosis of FEP and obesity/overweight were additively associated with advanced brain age [3]. Importantly, BMI increased significantly during hospitalization of participants with FEP, probably as effect of antipsychotic mediaction. Here, Based on our previous study we tested the hypothesis that both FEP and BMI are negatively associated with GM volumes. It is unclear to what extent weight gain related to antipsychotics contributes to these alterations. Materials and methods: We analyzed data from 120 patients with FES and 114 controls, the same sample as in our previous analyses [3]. We focused on individuals with FEP, who met the following inclusion criteria: 1) were undergoing their first psychiatric hospitalization, 2) had the ICD-10 diagnosis of schizophrenia (F20), or acute and transient psychotic disorders (F23) made by psychiatrist according to Mini-International Neuropsychiatric Interview, 3) had < 24 months of untreated psychosis, 4) were 18-35 years old. Average durration of ilness was 5.1 months and average durration of anstipsychotic treatment was 2 months. We conducted a multiple regression voxel-based morphometry analysis to assess the association between FEP, BMI, and GM volume. We added age and sex to the model as covariates of no interest. We used voxel-based morphometry (FSL-VBM; http://fsl.fmrib.ox.ac.uk/fsl/fslwiki/FSLVBM) for analyses and we applied permutation-based testing, corrected for multiple comparisons implementing threshold-free cluster enhancement (TFCE). We considered corrected p-values < 0.05 as significant. Results: FEP was associated with lower GM in the right cerebellum (pTFCE = 0.004; tmax = 4.37; kE = 1242 vox), left cerebellum (pTFCE = 0.004; tmax = 4.41; kE = 1207 vox), left frontal (pTFCE = 0.024; tmax = 4.70; kE = 151 vox) and right temporal cortices (pTFCE = 0.031; tmax = 4.25; kE = 110 vox,). Higher BMI was associated with lower GM in the left cerebellum (pTFCE; tmax = 4.56; kE = 858 vox). Conclusions: Diagnosis of FEP was associated with lower GM in fronto-temporal areas. The findings are consistent

Research paper thumbnail of Catecholamines, not acetylcholine, alter cortical and perceptual dynamics in line with increased excitation-inhibition ratio

bioRxiv (Cold Spring Harbor Laboratory), Aug 7, 2017

The ascending modulatory systems of the brain stem are powerful regulators of global brain state.... more The ascending modulatory systems of the brain stem are powerful regulators of global brain state. Disturbances of these systems are implicated in several major neuropsychiatric disorders. Yet, how these systems interact with specific neural computations in the cerebral cortex to shape perception, cognition, and behavior remains poorly understood. Here, we probed into the effect of two such systems, the catecholaminergic (dopaminergic and noradrenergic) and cholinergic systems, on an important aspect of cortical computation: its intrinsic variability. To this end, we combined placebo-controlled pharmacological intervention in humans, recordings of cortical population activity using magnetoencephalography (MEG), and psychophysical measurements of the perception of ambiguous visual input. A low-dose catecholaminergic, but not cholinergic, manipulation altered the rate of spontaneous perceptual fluctuations as well as the temporal structure of "scale-free" population activity of large swaths of the visual and parietal cortices. Computational analyses indicate that both effects were consistent with an increase in excitatory relative to inhibitory activity in the cortical areas underlying visual perceptual inference. We propose that catecholamines regulate the variability of perception and cognition through dynamically changing the cortical excitation-inhibition ratio. The combined readout of fluctuations in perception and cortical activity we established here may prove useful as an efficient and easily accessible marker of altered cortical computation in neuropsychiatric disorders.

Research paper thumbnail of Criticality theory applied to the 'wandering mind' problem in health and major depressive disorder

Research paper thumbnail of Catecholamines Alter the Intrinsic Variability of Cortical Population Activity and Perception

The ascending modulatory systems of the brainstem are powerful regulators of global brain state. ... more The ascending modulatory systems of the brainstem are powerful regulators of global brain state. Disturbances of these systems are implicated in several major neuropsychiatric disorders. Yet, how these systems interact with specific neural computations in the cerebral cortex to shape perception, cognition, and behavior remains poorly understood. Here, we probed into the effect of two such systems, the catecholaminergic (dopaminergic and noradrenergic) and cholinergic systems, on an important aspect of cortical computation: its intrinsic variability. To this end, we combined placebo-controlled pharmacological intervention in humans, magnetoencephalographic (MEG) recordings of cortical population activity, and psychophysical measurements of the perception of ambiguous visual input. A low-dose catecholaminergic, but not cholinergic, manipulation altered the rate of spontaneous perceptual fluctuations as well as the temporal structure of "scalefree" population activity of large swaths of visual and parietal cortex. Computational analyses indicate that both effects were consistent with an increase in excitatory relative to inhibitory activity in the cortical areas underlying visual perceptual inference. We propose that catecholamines regulate the variability of perception and cognition through dynamically changing the cortical excitation-inhibition ratio. The combined read-out of fluctuations in perception and cortical activity we established here may prove useful as an efficient, and easily accessible marker of altered cortical computation in neuropsychiatric disorders. .

Research paper thumbnail of Improved Manual Annotation of EEG Signals through Convolutional Neural Network Guidance

eneuro

The development of validated algorithms for automated handling of artifacts is essential for reli... more The development of validated algorithms for automated handling of artifacts is essential for reliable and fast processing of EEG signals. Recently, there have been methodological advances in designing machine-learning algorithms to improve artifact detection of trained professionals who usually meticulously inspect and manually annotate EEG signals. However, validation of these methods is hindered by the lack of a gold standard as data are mostly private and data annotation is time consuming and error prone. In the effort to circumvent these issues, we propose an iterative learning model to speed up and reduce errors of manual annotation of EEG. We use a convolutional neural network (CNN) to train on expert-annotated eyes-open and eyes-closed resting-state EEG data from typically developing children (n= 30) and children with neurodevelopmental disorders (n= 141). To overcome the circular reasoning of aiming to develop a new algorithm and benchmarking to a manually-annotated gold sta...