Characterization of antiseizure medications effects on the EEG neurodynamic by fractal dimension.

Objectives: An important challenge in epilepsy is to define biomarkers of response to treatment. Many electroencephalography (EEG) methods and indices have been developed mainly using linear methods, e.g., spectral power and individual alpha frequency peak (IAF). However, brain activity is complex and non-linear, hence there is a need to explore EEG neurodynamics using nonlinear approaches. Here, we use the Fractal Dimension (FD), a measure of whole brain signal complexity, to measure the response to anti-seizure therapy in patients with Focal Epilepsy (FE) and compare it with linear methods. Materials: Twenty-five drug-responder (DR) patients with focal epilepsy were studied before (t1, named DR-t1) and after (t2, named DR-t2) the introduction of the anti-seizure medications (ASMs). DR-t1 and DR-t2 EEG results were compared against 40 age-matched healthy controls (HC). Methods: EEG data were investigated from two different angles: frequency domain-spectral properties in δ, θ, α, ß, and γ bands and the IAF peak, and time-domain-FD as a signature of the nonlinear complexity of the EEG signals. Those features were compared among the three groups. Results: The δ power differed between DR patients pre and post-ASM and HC (DR-t1 vs. HC, p < 0.01 and DR-t2 vs. HC, p < 0.01). The θ power differed between DR-t1 and DR-t2 (p = 0.015) and between DR-t1 and HC (p = 0.01). The α power, similar to the δ, differed between DR patients pre and post-ASM and HC (DR-t1 vs. HC, p < 0.01 and DR-t2 vs. HC, p < 0.01). The IAF value was lower for DR-t1 than DR-t2 (p = 0.048) and HC (p = 0.042). The FD value was lower in DR-t1 than in DR-t2 (p = 0.015) and HC (p = 0.011). Finally, Bayes Factor analysis showed that FD was 195 times more likely to separate DR-t1 from DR-t2 than IAF and 231 times than θ. Discussion: FD measured in baseline EEG signals is a non-linear brain measure of complexity more sensitive than EEG power or IAF in detecting a response to ASMs. This likely reflects the non-oscillatory nature of neural activity, which FD better describes. Conclusion: Our work suggests that FD is a promising measure to monitor the response to ASMs in FE.

Disrupting the epileptogenic network with stereoelectroencephalography-guided radiofrequency thermocoagulation.

Stereoelectroencephalography-guided radiofrequency thermocoagulation (SEEG-guided RF-TC) is a treatment option for focal drug-resistant epilepsy. In previous studies, this technique has shown seizure reduction by ≥50% in 50% of patients at 1 year. However, the relationship between the location of the ablation within the epileptogenic network and clinical outcomes remains poorly understood. Seizure outcomes were analyzed for patients who underwent SEEG-guided RF-TC and across subgroups depending on the location of the ablation within the epileptogenic network, defined as SEEG sites involved in seizure generation and spread. Eighteen patients who had SEEG-guided RF-TC were included. SEEG-guided seizure-onset zone ablation (SEEG-guided SOZA) was performed in 12 patients, and SEEG-guided partial seizure-onset zone ablation (SEEG-guided P-SOZA) in 6 patients. The early spread was ablated in three SEEG-guided SOZA patients. Five patients had ablation of a lesion. The seizure freedom rate in the cohort ranged between 22% and 50%, and the responder rate between 67% and 85%. SEEG-guided SOZA demonstrated superior results for both outcomes compared to SEEG-guided P-SOZA at 6 months (seizure freedom p = .294, responder rate p = .014). Adding the early spread ablation to SEEG-guided SOZA did not increase seizure freedom rates but exhibited comparable effectiveness regarding responder rates, indicating a potential network disruption.

Altered spread of waves of activities at large scale is influenced by cortical thickness organization in temporal lobe epilepsy: a magnetic resonance imaging-high-density electroencephalography study.

Temporal lobe epilepsy is a brain network disorder characterized by alterations at both the structural and the functional levels. It remains unclear how structure and function are related and whether this has any clinical relevance. In the present work, we adopted a novel methodological approach investigating how network structural features influence the large-scale dynamics. The functional network was defined by the spatio-temporal spreading of aperiodic bursts of activations (neuronal avalanches), as observed utilizing high-density electroencephalography in patients with temporal lobe epilepsy. The structural network was modelled as the region-based thickness covariance. Loosely speaking, we quantified the similarity of the cortical thickness of any two brain regions, both across groups and at the individual level, the latter utilizing a novel approach to define the subject-wise structural covariance network. In order to compare the structural and functional networks (at the nodal level), we studied the correlation between the probability that a wave of activity would propagate from a source to a target region and the similarity of the source region thickness as compared with other target brain regions. Building on the recent evidence that large-waves of activities pathologically spread through the epileptogenic network in temporal lobe epilepsy, also during resting state, we hypothesize that the structural cortical organization might influence such altered spatio-temporal dynamics. We observed a stable cluster of structure-function correlation in the bilateral limbic areas across subjects, highlighting group-specific features for left, right and bilateral temporal epilepsy. The involvement of contralateral areas was observed in unilateral temporal lobe epilepsy. We showed that in temporal lobe epilepsy, alterations of structural and functional networks pair in the regions where seizures propagate and are linked to disease severity. In this study, we leveraged on a well-defined model of neurological disease and pushed forward personalization approaches potentially useful in clinical practice. Finally, the methods developed here could be exploited to investigate the relationship between structure-function networks at subject level in other neurological conditions.

Assessing cortical excitability with electroencephalography: A pilot study with EEG-iTBS.

BACKGROUND: Cortical excitability measures neural reactivity to stimuli, usually delivered via Transcranial Magnetic Stimulation (TMS). Excitation/inhibition balance (E/I) is the ongoing equilibrium between excitatory and inhibitory activity of neural circuits. According to some studies, E/I could be estimated in-vivo and non-invasively through the modeling of electroencephalography (EEG) signals and termed 'intrinsic excitability' measures. Several measures have been proposed (phase consistency in the gamma band, sample entropy, exponent of the power spectral density 1/f curve, E/I index extracted from detrend fluctuation analysis, and alpha power). Intermittent theta burst stimulation (iTBS) of the primary motor cortex (M1) is a non-invasive neuromodulation technique allowing controlled and focal enhancement of TMS cortical excitability and E/I of the stimulated hemisphere. OBJECTIVE: Investigating to what extent E/I estimates scale with TMS excitability and how they relate to each other. METHODS: M1 excitability (TMS) and several E/I estimates extracted from resting state EEG recordings were assessed before and after iTBS in a cohort of healthy subjects. RESULTS: Enhancement of TMS M1 excitability, as measured through motor-evoked potentials (MEPs), and phase consistency of the cortex in high gamma band correlated with each other. Other measures of E/I showed some expected results, but no correlation with TMS excitability measures or strong consistency with each other. CONCLUSIONS: EEG E/I estimates offer an intriguing opportunity to map cortical excitability non-invasively, with high spatio-temporal resolution and with a stimulus independent approach. While different EEG E/I estimates may reflect the activity of diverse excitatory-inhibitory circuits, spatial phase synchrony in the gamma band is the measure that best captures excitability changes in the primary motor cortex.

High-frequency transcranial alternating current stimulation matching individual frequency of somatosensory evoked high-frequency oscillations can modulate the somatosensory system through thalamocortical pathway.

tACS (transcranial alternating current stimulation) is a technique for modulating brain activity through electrical current. Its effects depend on cortical entrainment, which is most effective when transcranial alternating current stimulation matches the brain's natural rhythm. High-frequency oscillations produced by external stimuli are useful for studying the somatosensory pathway. Our study aims to explore transcranial alternating current stimulation's impact on the somatosensory system when synchronized with individual high-frequency oscillation frequencies. We conducted a randomized, sham-controlled study with 14 healthy participants. The study had three phases: Individualized transcranial alternating current stimulation (matching the individual's high-frequency oscillation rhythm), Standard transcranial alternating current stimulation (600 Hz), and sham stimulation. We measured early and late HFO components after median nerve electrical stimulation at three time points: before (T0), immediately after (T1), and 10 min after transcranial alternating current stimulation (T2). Compared to Sham and Standard stimulation Individualized transcranial alternating current stimulation significantly enhanced high-frequency oscillations, especially the early component, immediately after stimulation and for at least 15 min. No other effects were observed for other high-frequency oscillation measures. In summary, our study provides initial evidence that transcranial alternating current stimulation synchronized with an individual's high-frequency oscillation frequency can precisely and time-specifically modulate thalamocortical activity. These insights may pave the way for innovative, personalized neuromodulation methods for the somatosensory system.

Effectiveness of rTMS and tDCS treatment for chronic TBI symptoms: A systematic review and meta-analysis.

INTRODUCTION: Traumatic brain injury (TBI) is a major cause of long-term disability with conventional treatments frequently falling short to restore a good quality-of-life. Non-invasive brain stimulation (NIBS) techniques have shown potential as therapeutic options for neuropsychiatric conditions, including TBI sequelae. This study aims at providing a systematic review and meta-analysis on the effectiveness of repetitive transcranial magnetic stimulation (TMS) and transcranial direct current stimulation (tDCS) on post-TBI symptoms. METHODS: Fifteen randomized controlled trials (RCTs) on adult TBI patients that examined the effects of multiple treatment sessions of NIBS techniques were selected from five databases. Symptoms were clustered into four categories: depression, anxiety, headache and cognitive dysfunctions. Meta-analysis was performed using correlated and hierarchical effects models. RESULTS: There were only few and heterogeneous studies with generally small sample sizes. Most studies targeted the dorsolateral prefrontal cortex (dlPFC). Overall, the effects of NIBS were small. However, there was a significant effect for overall symptoms (0.404, p = 0.031). Moreover, subgroup analyses revealed significant overall effects for anxiety (0.195, p = 0.020) and headache (0.354, p = 0.040). CONCLUSIONS: To date, there is limited evidence supporting the effectiveness of NIBS concerning treatment for TBI sequelae. The observed effect sizes were modest, suggesting subtle improvements rather than drastic changes. While NIBS techniques remain promising for treating neuropsychiatric conditions, larger RCT studies with longer follow-ups, optimized stimulation parameters and standardized methodology are required to establish their efficacy in addressing TBI sequelae.

From rubber hands to neuroprosthetics: Neural correlates of embodiment.

Our interaction with the world rests on the knowledge that we are a body in space and time, which can interact with the environment. This awareness is usually referred to as sense of embodiment. For the good part of the past 30 years, the rubber hand illusion (RHI) has been a prime tool to study embodiment in healthy and people with a variety of clinical conditions. In this paper, we provide a critical overview of this research with a focus on the RHI paradigm as a tool to study prothesis embodiment in individuals with amputation. The RHI relies on well-documented multisensory integration mechanisms based on sensory precision, where parietal areas are involved in resolving the visuo-tactile conflict, and premotor areas in updating the conscious bodily representation. This mechanism may be transferable to prosthesis ownership in amputees. We discuss how these results might transfer to technological development of sensorised prostheses, which in turn might progress the acceptability by users.

Auditory white noise exposure results in intrinsic cortical excitability changes.

Cortical excitability is commonly measured by applying magnetic stimulation in combination with measuring behavioral response. This measure has, however, some shortcomings including spatial limitation to the primary motor cortex and not accounting for intrinsic excitability fluctuations. Here, we use a measure for intrinsic excitability based on phase synchronization previously validated for epilepsy. We apply this measure in 30 healthy participants' magnetoencephalography (MEG) recordings during the exposure of auditory white noise, a stimulus that has been suggested to modify cortical excitability. Using cortical parcellation of the MEG source data, we could find a specific pattern of increased and decreased excitability while participants are exposed to white noise vs. silence. Specifically, excitability during white noise exposure decreases in the frontal lobe and increases in the temporal lobe. This study thus adds to the understanding of cortical excitability changes due to specific environmental stimuli as well as the spatial extent of these effects.

Validating MEG source imaging of resting state oscillatory patterns with an intracranial EEG atlas.

BACKGROUND: Magnetoencephalography (MEG) is a widely used non-invasive tool to estimate brain activity with high temporal resolution. However, due to the ill-posed nature of the MEG source imaging (MSI) problem, the ability of MSI to identify accurately underlying brain sources along the cortical surface is still uncertain and requires validation. METHOD: We validated the ability of MSI to estimate the background resting state activity of 45 healthy participants by comparing it to the intracranial EEG (iEEG) atlas (https://mni-open-ieegatlas. RESEARCH: mcgill.ca/). First, we applied wavelet-based Maximum Entropy on the Mean (wMEM) as an MSI technique. Next, we converted MEG source maps into intracranial space by applying a forward model to the MEG-reconstructed source maps, and estimated virtual iEEG (ViEEG) potentials on each iEEG channel location; we finally quantitatively compared those with actual iEEG signals from the atlas for 38 regions of interest in the canonical frequency bands. RESULTS: The MEG spectra were more accurately estimated in the lateral regions compared to the medial regions. The regions with higher amplitude in the ViEEG than in the iEEG were more accurately recovered. In the deep regions, MEG-estimated amplitudes were largely underestimated and the spectra were poorly recovered. Overall, our wMEM results were similar to those obtained with minimum norm or beamformer source localization. Moreover, the MEG largely overestimated oscillatory peaks in the alpha band, especially in the anterior and deep regions. This is possibly due to higher phase synchronization of alpha oscillations over extended regions, exceeding the spatial sensitivity of iEEG but detected by MEG. Importantly, we found that MEG-estimated spectra were more comparable to spectra from the iEEG atlas after the aperiodic components were removed. CONCLUSION: This study identifies brain regions and frequencies for which MEG source analysis is likely to be reliable, a promising step towards resolving the uncertainty in recovering intracerebral activity from non-invasive MEG studies.

Reduced connectivity of primary auditory and motor cortices during exposure to auditory white noise.

Auditory white noise (WN) is widely used in daily life for inducing sleep, and in neuroscience to mask unwanted environmental noise and cues. However, WN was recently reported to influence corticospinal excitability and behavioral performance. Here, we expand previous preliminary findings on the influence of WN exposure on cortical functioning, and we hypothesize that it may modulate cortical connectivity. We tested our hypothesis by performing magnetoencephalography in 20 healthy subjects. WN reduces cortical connectivity of the primary auditory and motor regions with very distant cortical areas, showing a right lateralized connectivity reduction for primary motor cortex. The present results, together with previous finding concerning WN impact on corticospinal excitability and behavioral performance, further support the role of WN as a modulator of cortical function. This suggest avoiding its unrestricted use as a masking tool, while purposely designed and controlled WN application could be exploited to harness brain function and to treat neuropsychiatric conditions.

Task matters: Individual MEG signatures from naturalistic and neurophysiological brain states.

The discovery that human brain connectivity data can be used as a "fingerprint" to identify a given individual from a population, has become a burgeoning research area in the neuroscience field. Recent studies have identified the possibility to extract these brain signatures from the temporal rich dynamics of resting-state magneto encephalography (MEG) recordings. Nevertheless, it is still uncertain to what extent MEG signatures can serve as an indicator of human identifiability during task-related conduct. Here, using MEG data from naturalistic and neurophysiological tasks, we show that identification improves in tasks relative to resting-state, providing compelling evidence for a task dependent axis of MEG signatures. Notably, improvements in identifiability were more prominent in strictly controlled tasks. Lastly, the brain regions contributing most towards individual identification were also modified when engaged in task activities. We hope that this investigation advances our understanding of the driving factors behind brain identification from MEG signals.

Hierarchical Bayesian modeling of the relationship between task-related hemodynamic responses and cortical excitability.

Investigating the relationship between task-related hemodynamic responses and cortical excitability is challenging because it requires simultaneous measurement of hemodynamic responses while applying noninvasive brain stimulation. Moreover, cortical excitability and task-related hemodynamic responses are both associated with inter-/intra-subject variability. To reliably assess such a relationship, we applied hierarchical Bayesian modeling. This study involved 16 healthy subjects who underwent simultaneous Paired Associative Stimulation (PAS10, PAS25, Sham) while monitoring brain activity using functional Near-Infrared Spectroscopy (fNIRS), targeting the primary motor cortex (M1). Cortical excitability was measured by Motor Evoked Potentials (MEPs), and the motor task-related hemodynamic responses were measured using fNIRS 3D reconstructions. We constructed three models to investigate: (1) PAS effects on the M1 excitability, (2) PAS effects on fNIRS hemodynamic responses to a finger tapping task, and (3) the correlation between PAS effects on M1 excitability and PAS effects on task-related hemodynamic responses. Significant increase in cortical excitability was found following PAS25, whereas a small reduction of the cortical excitability was shown after PAS10 and a subtle increase occurred after sham. Both HbO and HbR absolute amplitudes increased after PAS25 and decreased after PAS10. The probability of the positive correlation between modulation of cortical excitability and hemodynamic activity was 0.77 for HbO and 0.79 for HbR. We demonstrated that PAS stimulation modulates task-related cortical hemodynamic responses in addition to M1 excitability. Moreover, the positive correlation between PAS modulations of excitability and hemodynamics brought insight into understanding the fundamental properties of cortical function and cortical excitability.

Functional Source Separation-Identified Epileptic Network: Analysis Pipeline.

This proof-of-concept (PoC) study presents a pipeline made by two blocks: 1. the identification of the network that generates interictal epileptic activity; and 2. the study of the time course of the electrical activity that it generates, called neurodynamics, and the study of its functional connectivity to the other parts of the brain. Network identification is achieved with the Functional Source Separation (FSS) algorithm applied to electroencephalographic (EEG) recordings, the neurodynamics quantified through signal complexity with the Higuchi Fractal Dimension (HFD), and functional connectivity with the Directed Transfer Function (DTF). This PoC is enhanced by the data collected before and after neuromodulation via transcranial Direct Current Stimulation (tDCS, both Real and Sham) in a single drug-resistant epileptic person. We observed that the signal complexity of the epileptogenic network, reduced in the pre-Real, pre-Sham, and post-Sham, reached the level of the rest of the brain post-Real tDCS. DTF changes post-Real tDCS were maintained after one month. The proposed approach can represent a valuable tool to enhance understanding of the relationship between brain neurodynamics characteristics, the effects of non-invasive brain stimulation, and epileptic symptoms.

State-dependent tDCS modulation of the somatomotor network: A MEG study.

OBJECTIVE: Transcranial direct current stimulation (tDCS) is a non-invasive technique widely used to investigate brain excitability and activity. However, the variability in both brain and behavioral responses to tDCS limits its application for clinical purposes. This study aims to shed light on state-dependency, a phenomenon that contributes to the variability of tDCS. METHODS: To this aim, we investigated changes in spectral activity and functional connectivity in somatomotor regions after Real and Sham tDCS using generalized additive mixed models (GAMMs), which allowed us to investigate how modulation depends on the initial state of the brain. RESULTS: Results showed that changes in spectral activity, but not connectivity, in the somatomotor regions depend on the initial state of the brain, confirming state-dependent effects. Specifically, we found a non-linear interaction between stimulation conditions (Real vs Sham) and initial state: a reduction of alpha and beta power was observed only in participants that had higher alpha and beta power before Real tDCS. CONCLUSIONS: This study highlights the importance of considering state-dependency to tDCS and shows how it can be taken into account with appropriate statistical models. SIGNIFICANCE: Our findings bear insight into tDCS mechanisms, potentially leading to discriminate between tDCS responders and non-responders.

WHOCARES: WHOle-brain CArdiac signal REgression from highly accelerated simultaneous multi-Slice fMRI acquisitions.

Objective. To spatio-temporally resolve cardiac signals in functional magnetic resonance imaging (fMRI) time-series of the human brain using neither external physiological measurements nor ad hoc modelling assumptions.Approach. Cardiac pulsation is a physiological confound of fMRI time-series that introduces spurious signal fluctuations in proximity to blood vessels. fMRI alone is not sufficiently fast to resolve cardiac pulsation. Depending on the ratio between the instantaneous heart-rate and the acquisition sampling frequency (1/TR, with TR being the repetition time), the cardiac signal may alias into the frequency band of neural activation so that its removal through spectral filtering techniques is generally not possible. In this paper, we show that it is feasible to temporally and spatially resolve cardiac signals throughout the brain even when cardiac aliasing occurs by combining fMRI hyper-sampling with simultaneous multislice (SMS) imaging. The technique, which we name WHOle-brain CArdiac signal REgression from highly accelerated simultaneous multi-Slice fMRI acquisitions (WHOCARES), was developed on 695 healthy subjects selected from the Human Connectome Project and its performance validated against the RETROICOR, HAPPY and the pulse oxymeter signal regression methods.Main results.WHOCARES is capable of retrieving voxel-wise cardiac signal regressors. This is achieved without employing external physiological recordings nor through ad hoc modelling assumptions. The performance of WHOCARES was, on average, superior to RETROICOR, HAPPY and the pulse oxymeter regression methods.Significance.WHOCARES holds basis for the reliable mapping of cardiac activity in fMRI time-series. WHOCARES can be employed for the retrospective removal of cardiac noise in publicly available fMRI datasets where physiological recordings are not available. WHOCARES is freely available athttps://github.com/gferrazzi/WHOCARES.

Decompressive hemicraniectomy in patients with malignant middle cerebral artery infarction: A real-world study.

BACKGROUND: Malignant middle cerebral artery infarction (mMCA) is a devastating disease with rates of fatality as high as 80%. Decompressive hemicraniectomy (DHC) reduces mortality, but many survivors inevitably remain severely disabled. This study aimed to analyze patients with mMCA undergoing DHC or best medical treatment (BMT) baseline characteristics and factors linked to therapeutic choice and determinants of prognosis. METHODS: We recorded clinical and radiological features of patients undergoing BMT or DHC. The two groups were compared for epidemiology, clinical presentation, neuroimaging, and prognosis. Regression analysis was performed to identify predictors of surgical treatment and outcome. RESULTS: One hundred twenty-five patients were included (age 67.41 ± 1.39 yo; 65 M). Patients undergoing DHC (N = 57) were younger (DHC 55.71 ± 1.48 yo vs. BMT 77.22 ± 1.38) and had midline shift (DHC 96.5% (55/57) vs. BMT 35.3% (24/68), a larger volume of the affected hemisphere and reduced ventricles volume as compared to BMT. The chance of surgery depended on age (Exp(B) = 0.871, p < 0.001), clinical status at onset (NIHSS Exp(B) = 0.824, p = 0.030) and volume of the ventricle of the affected hemisphere (Exp(B) = 0.736, p = 0.006). Death rate during admission was significantly lower for DHC (DHC 15% (6/41) vs BMT 71.7% (38/53), Fisher's test = 30.234, p < 0.001). CONCLUSION: Although DHC may cause prolonged hospitalization and long-term disabled patients, it is a lifesaving therapy that should be considered for selected patients with mMCA but perioperative complications and cost-utility should be considered. Patients and families should be correctly counseled about this therapeutic choice and its short- and long-term consequences.

Stimulation with acoustic white noise enhances motor excitability and sensorimotor integration.

Auditory white noise (WN) is widely used in neuroscience to mask unwanted environmental noise and cues, e.g. TMS clicks. However, to date there is no research on the influence of WN on corticospinal excitability and potentially associated sensorimotor integration itself. Here we tested the hypothesis, if WN induces M1 excitability changes and improves sensorimotor performance. M1 excitability (spTMS, SICI, ICF, I/O curve) and sensorimotor reaction-time performance were quantified before, during and after WN stimulation in a set of experiments performed in a cohort of 61 healthy subjects. WN enhanced M1 corticospinal excitability, not just during exposure, but also during silence periods intermingled with WN, and up to several minutes after the end of exposure. Two independent behavioural experiments highlighted that WN improved multimodal sensorimotor performance. The enduring excitability modulation combined with the effects on behaviour suggest that WN might induce neural plasticity. WN is thus a relevant modulator of corticospinal function; its neurobiological effects should not be neglected and could in fact be exploited in research applications.

Auditory driven gamma synchrony is associated with cortical thickness in widespread cortical areas.

OBJECTIVE: Gamma synchrony is a fundamental functional property of the cerebral cortex, impaired in multiple neuropsychiatric conditions (i.e. schizophrenia, Alzheimer's disease, stroke etc.). Auditory stimulation in the gamma range allows to drive gamma synchrony of the entire cortical mantle and to estimate the efficiency of the mechanisms sustaining it. As gamma synchrony depends strongly on the interplay between parvalbumin-positive interneurons and pyramidal neurons, we hypothesize an association between cortical thickness and gamma synchrony. To test this hypothesis, we employed a combined magnetoencephalography (MEG) - Magnetic Resonance Imaging (MRI) study. METHODS: Cortical thickness was estimated from anatomical MRI scans. MEG measurements related to exposure of 40 Hz amplitude modulated tones were projected onto the cortical surface. Two measures of cortical synchrony were considered: (a) inter-trial phase consistency at 40 Hz, providing a vertex-wise estimation of gamma synchronization, and (b) phase-locking values between primary auditory cortices and whole cortical mantle, providing a measure of long-range cortical synchrony. A correlation between cortical thickness and synchronization measures was then calculated for 72 MRI-MEG scans. RESULTS: Both inter-trial phase consistency and phase locking values showed a significant positive correlation with cortical thickness. For inter-trial phase consistency, clusters of strong associations were found in the temporal and frontal lobes, especially in the bilateral auditory and pre-motor cortices. Higher phase-locking values corresponded to higher cortical thickness in the frontal, temporal, occipital and parietal lobes. DISCUSSION AND CONCLUSIONS: In healthy subjects, a thicker cortex corresponds to higher gamma synchrony and connectivity in the primary auditory cortex and beyond, likely reflecting underlying cell density involved in gamma circuitries. This result hints towards an involvement of gamma synchrony together with underlying brain structure in brain areas for higher order cognitive functions. This study contributes to the understanding of inherent cortical functional and structural brain properties, which might in turn constitute the basis for the definition of useful biomarkers in patients showing aberrant gamma synchronization.

Diffuse optical reconstructions of functional near infrared spectroscopy data using maximum entropy on the mean.

Functional near-infrared spectroscopy (fNIRS) measures the hemoglobin concentration changes associated with neuronal activity. Diffuse optical tomography (DOT) consists of reconstructing the optical density changes measured from scalp channels to the oxy-/deoxy-hemoglobin concentration changes within the cortical regions. In the present study, we adapted a nonlinear source localization method developed and validated in the context of Electro- and Magneto-Encephalography (EEG/MEG): the Maximum Entropy on the Mean (MEM), to solve the inverse problem of DOT reconstruction. We first introduced depth weighting strategy within the MEM framework for DOT reconstruction to avoid biasing the reconstruction results of DOT towards superficial regions. We also proposed a new initialization of the MEM model improving the temporal accuracy of the original MEM framework. To evaluate MEM performance and compare with widely used depth weighted Minimum Norm Estimate (MNE) inverse solution, we applied a realistic simulation scheme which contained 4000 simulations generated by 250 different seeds at different locations and 4 spatial extents ranging from 3 to 40[Formula: see text] along the cortical surface. Our results showed that overall MEM provided more accurate DOT reconstructions than MNE. Moreover, we found that MEM was remained particularly robust in low signal-to-noise ratio (SNR) conditions. The proposed method was further illustrated by comparing to functional Magnetic Resonance Imaging (fMRI) activation maps, on real data involving finger tapping tasks with two different montages. The results showed that MEM provided more accurate HbO and HbR reconstructions in spatial agreement with the main fMRI cluster, when compared to MNE.