Brain Disconnection Research Articles

Surgical Anatomy and Technique of Peri-Insular Hemispherotomy in Pediatric Epilepsy.

Hemispherotomy is a highly complex procedure that demands a steep learning curve. An incomplete brain disconnection often results in failure of seizure control. The purpose of this article was to present a step-by-step guide to the surgical anatomy of this procedure. It is composed of a 7-stage approach, enhancing access to and improving visualization of deep structures. A retrospective analysis of 39 pediatric patients with refractory epilepsy who underwent this technique was conducted. Engel scores were assessed 1 year postsurgery. Cadaveric dissections were performed to illustrate the procedure. Between 2015 and 2022, 39 patients were surgically treated using the peri-insular technique. The technique involved 7 stages: patient positioning, operative approach, opercular resection, transventricular callosotomy, fronto-orbital disconnection, anterior temporal disconnection, and posterior temporal disconnection. Most of the patients (92.30%) were seizure-free (Engel class I) at 1 year postoperative, 5.13% were nearly seizure-free (Engel II), and 2.56% showed significant improvement (Engel III). Complications occurred in 8% of cases, including 1 infection, 2 cases of aseptic meningitis, and 1 non-shunt-requiring acute hydrocephalus. The peri-insular hemispherotomy technique offers excellent seizure control with a low complication rate. Our visual documentation of surgical anatomy, complemented by detailed descriptions of surgical nuances, significantly contributes to a comprehensive understanding of this technique.

Damaging a few millimeters of the deep white matter tracts during glioma surgery may result in a large-scale brain disconnection.

Damaging a few millimeters of the deep white matter tracts during glioma surgery may result in a large-scale brain disconnection.

Neural Substrates of Psychomotor Speed Deficits in Cerebral Small Vessel Disease: A Brain Disconnectome Mapping Study.

It remains unknown which factors influence how brain disconnectivity derived from White Matter Hyperintensity (WMH) lesions leads to psychomotor speed dysfunction, one of the earliest and most common cognitive manifestations in the cerebral Small Vessel Disease (cSVD) population. While the burden of WMH has been strongly linked to psychomotor speed performance, the effect that different locations and volumes of WMH may have on cSVD-related cognitive impairment remains unclear. Therefore, we aimed to explore (1) whether global WMH, deep WMH (DWMH), and periventricular (PVWMH) volumes display different psychomotor speed associations; (2) whether tract-specific WMH volume shows stronger cognitive associations compared with global measures of WMH volume; (3) whether specific patterns of WMH location lead to different degrees of disconnectivity. Using the BCBToolkit, we investigated which pattern of distribution and which locations of WMH lesion result in impaired psychomotor speed in a well-characterized sample (n = 195) of cSVD patients without dementia. Two key findings emerge from our study. First, global (and not tract-specific) measures of WMH volume were associated with psychomotor speed performance. Second, disconnection maps revealed the involvement of callosal tracts, association and projection fibers, and frontal and parietal cortical brain areas related to psychomotor speed, while the lesion location influenced such associations. In conclusion, psychomotor deficits are affected differently by WMH burden and topographic distribution through brain disconnection in non-demented cSVD patients.

Thalamocortical disconnection involved in pusher syndrome.

The presence of both isolated thalamic and isolated cortical lesions have been reported in the context of pusher syndrome-a disorder characterized by a disturbed perception of one's own upright body posture, following unilateral left- or right-sided stroke. In recent times, indirect quantification of functional and structural disconnection increases the knowledge derived from focal brain lesions by inferring subsequent brain network damage from the respective lesion. We applied both measures to a sample of 124 stroke patients to investigate brain disconnection in pusher syndrome. Our results suggest a hub-like function of the posterior and lateral portions of the thalamus in the perception of one's own postural upright. Lesion network symptom mapping investigating functional disconnection indicated cortical diaschisis in cerebellar, frontal, parietal and temporal areas in patients with thalamic lesions suffering from pusher syndrome, but there was no evidence for functional diaschisis in pusher patients with cortical stroke and no evidence for the convergence of thalamic and cortical lesions onto a common functional network. Structural disconnection mapping identified posterior thalamic disconnection to temporal, pre-, post- and paracentral regions. Fibre tracking between the thalamic and cortical pusher lesion hotspots indicated that in cortical lesions of patients with pusher syndrome, it is disconnectivity to the posterior thalamus caused by accompanying white matter damage, rather than the direct cortical lesions themselves, that lead to the emergence of pusher syndrome. Our analyses thus offer the first evidence for a direct thalamo-cortical (or cortico-thalamic) interconnection and, more importantly, shed light on the location of the respective thalamo-cortical disconnections. Pusher syndrome seems to be a consequence of direct damage or of disconnection of the posterior thalamus.

Latent disconnectome prediction of long-term cognitive-behavioural symptoms in stroke.

Stroke significantly impacts the quality of life. However, the long-term cognitive evolution in stroke is poorly predictable at the individual level. There is an urgent need to better predict long-term symptoms based on acute clinical neuroimaging data. Previous works have demonstrated a strong relationship between the location of white matter disconnections and clinical symptoms. However, rendering the entire space of possible disconnection-deficit associations optimally surveyable will allow for a systematic association between brain disconnections and cognitive-behavioural measures at the individual level. Here we present the most comprehensive framework, a composite morphospace of white matter disconnections (disconnectome) to predict neuropsychological scores 1 year after stroke. Linking the latent disconnectome morphospace to neuropsychological outcomes yields biological insights that are available as the first comprehensive atlas of disconnectome-deficit relations across 86 scores-a Neuropsychological White Matter Atlas. Our novel predictive framework, the Disconnectome Symptoms Discoverer, achieved better predictivity performances than six other models, including functional disconnection, lesion topology and volume modelling. Out-of-sample prediction derived from this atlas presented a mean absolute error below 20% and allowed personalize neuropsychological predictions. Prediction on an external cohort achieved an R2 = 0.201 for semantic fluency. In addition, training and testing were replicated on two external cohorts achieving an R2 = 0.18 for visuospatial performance. This framework is available as an interactive web application (http://disconnectomestudio.bcblab.com) to provide the foundations for a new and practical approach to modelling cognition in stroke. We hope our atlas and web application will help to reduce the burden of cognitive deficits on patients, their families and wider society while also helping to tailor future personalized treatment programmes and discover new targets for treatments. We expect our framework's range of assessments and predictive power to increase even further through future crowdsourcing.

Longitudinal prediction of motor dysfunction after stroke: a disconnectome study

Motricity is the most commonly affected ability after a stroke. While many clinical studies attempt to predict motor symptoms at different chronic time points after a stroke, longitudinal acute-to-chronic studies remain scarce. Taking advantage of recent advances in mapping brain disconnections, we predict motor outcomes in 62 patients assessed longitudinally two weeks, three months, and one year after their stroke. Results indicate that brain disconnection patterns accurately predict motor impairments. However, disconnection patterns leading to impairment differ between the three-time points and between left and right motor impairments. These results were cross-validated using resampling techniques. In sum, we demonstrated that while some neuroplasticity mechanisms exist changing the structure–function relationship, disconnection patterns prevail when predicting motor impairment at different time points after stroke.

The emergent properties of the connected brain.

There is more to brain connections than the mere transfer of signals between brain regions. Behavior and cognition emerge through cortical area interaction. This requires integration between local and distant areas orchestrated by densely connected networks. Brain connections determine the brain's functional organization. The imaging of connections in the living brain has provided an opportunity to identify the driving factors behind the neurobiology of cognition. Connectivity differences between species and among humans have furthered the understanding of brain evolution and of diverging cognitive profiles. Brain pathologies amplify this variability through disconnections and, consequently, the disintegration of cognitive functions. The prediction of long-term symptoms is now preferentially based on brain disconnections. This paradigm shift will reshape our brain maps and challenge current brain models.

Altered functional association and couplings: Effective diagnostic neuromarkers for Alzheimer's disease.

Alzheimer’s disease (AD) is a common neurodegenerative disorder causing dementia in the elderly population. Functional disconnection of brain is considered to be the main cause of AD. In this study, we applied a newly developed association (Asso) mapping approach to directly quantify the functional disconnections and to explore the diagnostic effects for AD with resting-state functional magnetic resonance imaging data from 36 AD patients and 42 age-, gender-, and education-matched healthy controls (HC). We found that AD patients showed decreased Asso in left dorsoanterior insula (INS) while increased functional connections of INS with right medial prefrontal cortex (MPFC) and left posterior cingulate cortex (PCC). The changed Asso and functional connections were closely associated with cognitive performances. In addition, the reduced Asso and increased functional connections could serve as effective neuromarkers to distinguish AD patients from HC. Our research provided new evidence for functional disconnections in AD and demonstrated that functional disconnections between cognition-memory networks may be potential early biomarkers for AD.

Regional Disruption of White Matter Integrity and Network Connectivity Are Related to Cognition.

Cognitive impairment is common in the elderly population. Exploring patterns of white matter damage at the microstructural level would give important indications for the underlying mechanisms. To investigate the spatial patterns of white matter microstructure and structural network alternations in relation to different cognition domainsMethods:Participants from the community-based Shunyi Study were included to investigate the association between white matter measurements and cognition cross-sectionally, via both global and local analysis. Cognitive functions were assessed using digit span, trail making test (TMT)-A/B, Fuld object Memory, and 12-Word Philadelphia Verbal Learning Test (PVLT). White matter measurements including fractional anisotropy (FA), mean diffusivity (MD), and structural network parameters were calculated based on diffusion tensor imaging. Of the 943 participants included, the mean (SD) age was 55.8 (9.1) years, and the mean (SD) education level was 6.7 (3.2) years. We found the whole set of cognitive measurements was related to diffused white matter microstructural integrity damage and lower global efficiency. Poor executive functions (TMTA/B complete time) were related to lower FA and higher MD predominantly on the anterior white matter skeleton, while verbal memory loss (PVLT test scores) was related to sub-network dysconnectivity in the midline and the right temporal lobe. The anterior brain is dominantly involved in executive dysfunction, while midline and right temporal brain disconnection are more prominent in verbal memory loss. Global and regional disruption of white matter integrity and network connectivity is the anatomical basis of the cognitive impairment in the aging population.

Indirect structural disconnection-symptom mapping.

In vivo tracking of white matter fibres catalysed a modern perspective on the pivotal role of brain connectome disruption in neuropsychological deficits. However, the examination of white matter integrity in neurological patients by diffusion-weighted magnetic resonance imaging bears conceptual limitations and is not widely applicable, as it requires imaging-compatible patients and resources beyond the capabilities of many researchers. The indirect estimation of structural disconnection offers an elegant and economical alternative. For this approach, a patient's structural lesion information and normative connectome data are combined to estimate different measures of lesion-induced structural disconnection. Using one of several toolboxes, this method is relatively easy to implement and is even available to scientists without expertise in fibre tracking analyses. Nevertheless, the anatomo-behavioural statistical mapping of structural brain disconnection requires analysis steps that are not covered by these toolboxes. In this paper, we first review the current state of indirect lesion disconnection estimation, the different existing measures, and the available software. Second, we aim to fill the remaining methodological gap in statistical disconnection-symptom mapping by providing an overview and guide to disconnection data and the statistical mapping of their relationship to behavioural measurements using either univariate or multivariate statistical modelling. To assist in the practical implementation of statistical analyses, we have included software tutorials and analysis scripts.

Effect of cerebellum stimulation on cognitive recovery in patients with Alzheimer disease: A randomized clinical trial

IntroductionEvidence indicates that the cerebellum is involved in cognitive processing. However, the specific mechanisms through which the cerebellum repetitive transcranial magnetic stimulation (rTMS) contributes to the cognitive state are unclear. MethodsIn the current randomized, double-blind, sham-controlled trial, 27 patients with Alzheimer's disease (AD) were randomly allotted to one of the two groups: rTMS-real or rTMS-sham. We investigated the efficacy of a four-week treatment of bilateral cerebellum rTMS to promote cognitive recovery and alter specific cerebello-cerebral functional connectivity. ResultsThe cerebellum rTMS significantly improves multi-domain cognitive functions, directly associated with the observed intrinsic functional connectivity between the cerebellum nodes and the dorsolateral prefrontal cortex (DLPFC), medial frontal cortex, and the cingulate cortex in the real rTMS group. In contrast, the sham stimulation showed no significant impact on the clinical improvements and the cerebello-cerebral connectivity. ConclusionOur results depict that 5 Hz rTMS of the bilateral cerebellum is a promising, non-invasive treatment of cognitive dysfunction in AD patients. This cognitive improvement is accompanied by brain connectivity modulation and is consistent with the pathophysiological brain disconnection model in AD patients.

Potential Diffusion Tensor Imaging Biomarkers for Elucidating Intra-Individual Age-Related Changes in Cognitive Control and Processing Speed.

Cognitive aging, especially cognitive control, and processing speed aging have been well-documented in the literature. Most of the evidence was reported based on cross-sectional data, in which inter-individual age effects were shown. However, there have been some studies pointing out the possibility of overlooking intra-individual changes in cognitive aging. To systematically examine whether age-related differences and age-related changes might yield distinctive patterns, this study directly compared cognitive control function and processing speed between different cohorts versus follow-up changes across the adult lifespan. Moreover, considering that cognitive aging has been attributed to brain disconnection in white matter (WM) integrity, this study focused on WM integrity via acquiring diffusion-weighted imaging data with an MRI instrument that are further fitted to a diffusion tensor model (i.e., DTI) to detect water diffusion directionality (i.e., fractional anisotropy, FA; mean diffusivity, MD; radial diffusivity, RD; axial diffusivity, AxD). Following data preprocessing, 114 participants remained for further analyses in which they completed the two follow-up sessions (with a range of 1–2 years) containing a series of neuropsychology instruments and computerized cognitive control tasks. The results show that many significant correlations between age and cognitive control functions originally shown on cross-sectional data no longer exist on the longitudinal data. The current longitudinal data show that MD, RD, and AxD (especially in the association fibers of anterior thalamic radiation) are more strongly correlated to follow-up aging processes, suggesting that axonal/myelin damage is a more robust phenomenon for observing intra-individual aging processes. Moreover, processing speed appears to be the most prominent cognitive function to reflect DTI-related age (cross-sectional) and aging (longitudinal) effects. Finally, converging the results from regression analyses and mediation models, MD, RD, and AxD appear to be the representative DTI measures to reveal age-related changes in processing speed. To conclude, the current results provide new insights to which indicator of WM integrity and which type of cognitive changes are most representative (i.e., potentially to be neuroimaging biomarkers) to reflect intra-individual cognitive aging processes.

Aberrant static and dynamic functional connectivity of amygdala subregions in patients with major depressive disorder and childhood maltreatment

Major depressive disorder (MDD) with childhood maltreatment is a heterogeneous clinical phenotype of depression with prominent features of brain disconnectivity in areas linked to maltreatment-related emotion processing (e.g., the amygdala). However, static and dynamic alterations of functional connectivity in amygdala subregions have not been investigated in MDD with childhood maltreatment. Here, we explored whether amygdala subregions (i.e., medial amygdala [MeA] and lateral amygdala [LA]) exhibited static functional connectivity (sFC) and dynamic functional connectivity (dFC) disruption, and whether these disruptions were related to childhood maltreatment. We compared sFC and dFC patterns in MDD with childhood maltreatment (n = 48), MDD without childhood maltreatment (n = 30), healthy controls with childhood maltreatment (n = 57), and healthy controls without childhood maltreatment (n = 46). The bilateral MeA and LA were selected as the seeds in the FC analysis. The results revealed a functional connectivity disruption pattern in maltreated MDD patients, characterized by sFC and dFC abnormalities involving the MeA, LA, and theory of mind-related brain areas including the middle occipital area, middle frontal gyrus, superior medial frontal gyrus, angular gyrus, supplementary motor areas, middle temporal gyrus, middle cingulate gyrus, and calcarine gyrus. Significant correlations were detected between impaired dFC patterns and childhood maltreatment. Furthermore, the dFC disruption pattern served as a moderator in the relationship between sexual abuse and depression severity. Our findings revealed neurobiological features of childhood maltreatment, providing new evidence regarding vulnerability to psychiatric disorders.

Brain disconnectome mapping derived from white matter lesions and serum neurofilament light levels in multiple sclerosis: A longitudinal multicenter study

Background and ObjectivesConnectivity-based approaches incorporating the distribution and magnitude of the extended brain network aberrations caused by lesions may offer higher sensitivity for axonal damage in patients with multiple sclerosis (MS) than conventional lesion characteristics. Using individual brain disconnectome mapping, we tested the longitudinal associations between putative imaging-based brain network aberrations and levels of serum neurofilament light chain (NfL) as a neuroaxonal injury biomarker. MethodsMS patients (n = 312, mean age 42.9 years, 71 % female) and healthy controls (HC) (n = 59, mean age 39.9 years, 78 % female) were prospectively enrolled at four European MS centres, and reassessed after two years (MS, n = 242; HC, n = 30). Post-processing of 3 Tesla (3 T) MRI data was performed at one centre using a harmonized pipeline, and disconnectome maps were calculated using BCBtoolkit based on individual lesion maps. Global disconnectivity (GD) was defined as the average disconnectome probability in each patient’s white matter. Serum NfL concentrations were measured by single molecule array (Simoa). Robust linear mixed models (rLMM) with GD or T2-lesion volume (T2LV) as dependent variables, patient as a random factor, serum NfL, age, sex, timepoint for visit, diagnosis, treatment, and center as fixed factors were run. ResultsrLMM revealed significant associations between GD and serum NfL (t = 2.94, p = 0.003), age (t = 4.21, p = 2.5 × 10−5), and longitudinal changes in NfL (t = -2.29, p = 0.02), but not for sex (t = 0.63, p = 0.53) or treatments (t = 0.80–0.83, p = 0.41–0.42). Voxel-wise analyses revealed significant associations between dysconnectivity in cerebellar and brainstem regions and serum NfL (t = 7.03, p < 0.001). DiscussionIn our prospective multi-site MS cohort, rLMMs demonstrated that the extent of global and regional brain disconnectivity is sensitive to a systemic biomarker of axonal damage, serum NfL, in patients with MS. These findings provide a neuroaxonal correlate of advanced disconnectome mapping and provide a platform for further investigations of the functional and potential clinical relevance of brain disconnectome mapping in patients with brain disorders.

Human Brain Networks in Physiological and Pathological Aging: Reproducibility of Electroencephalogram Graph Theoretical Analysis in Cortical Connectivity.

Background: Physiological and pathological brain aging plays a central role in brain network modulation. The aim of the present article was to assess the stability of a proposed method for evaluation of small-world (SW) characteristics for the study of the human connectome. Subjects and Methods: Eighty subjects were recruited: 36 young healthy controls, 32 elderly healthy controls, and 12 patients affected by Alzheimer's disease (AD). Electroencephalograms (EEGs) were recorded during six separate sessions (480 recordings) at an average intersession interval of 3.8 ± 0.2 days. We applied graph theory functions to the weighted and undirected networks obtained by the lagged linear coherence estimated by exact low-resolution electromagnetic tomography (eLORETA). We explored the following frequency bands: delta (2-4 Hz), theta (4-8 Hz), alpha 1 (8-10.5 Hz), alpha 2 (10.5-13 Hz), beta 1 (13-20 Hz), beta 2 (20-30 Hz), and gamma (30-40 Hz). Results: The proposed method for evaluation of SW characteristics exhibited good reproducibility and stability. Furthermore, results showed the pattern, Young>Elderly>AD, in low-frequency delta and theta bands and vice versa in the higher alpha band. Finally, a correlation with age was confirmed in healthy subjects, showing that the older the age, the higher the SW values for alpha 2. Discussion: Evidences from the present study confirm the stability of the SW index and suggest that the analysis of connectivity patterns evaluated from EEGs can be supported by the graph theory. The proposed method for evaluation of SW characteristics has shown good reproducibility and stability. This technique, applied to patient data, could provide more information on the pathophysiological processes underlying age-related brain disconnection, as well as on administration of rehabilitation treatments at the right time, which could allow patients to avoid unnecessary interventions. Impact statement The graph analysis tools described in this study represent an interesting approach to study the distinctive characteristics of physiological aging by focusing on functional connectivity networks. The proposed method for evaluation of small-world characteristics has shown good reproducibility and stability. This technique, applied to patient data, could provide more information on the pathophysiological processes underlying age-related brain disconnection, as well as on delivery of rehabilitation treatments at the right time, which could allow patients to avoid unnecessary interventions.

Ventral tegmental area disconnection contributes two years early to correctly classify patients converted to Alzheimer’s disease: Implications for treatment

The loss of dopaminergic neurons in the ventral tegmental area (VTA) has been recently recognised as an early pathophysiological event of Alzheimer’s disease (AD). Using resting-state fMRI (RS-fMRI), we aimed here to investigate longitudinally, in a group of patients with mild cognitive impairment (MCI) due to AD, the impact of VTA-driven brain disconnection in predicting the conversion to AD.

Resting-State Brain Connectivity via Multivariate EMD in Mild Cognitive Impairment

Mild cognitive impairment (MCI) is regarded as a brain disconnection syndrome. The functional connectivity from resting state functional magnetic resonance imaging (rs-fMRI) shows that the number and the strength of the connectivity in MCI will decrease. However, many studies have confirmed that, the decrease and increase in MCI actually coexist. This paper proposes a novel intrinsic-frequency connectivity to study the statistical significance between MCI and normal control (NC), especially stronger positive connectivity on an MCI group mean level. We use a multivariate empirical model decomposition to get intrinsic modal functions (IMFs) and calculate the correlations of the IMFs. In experiments, we use public data to test the proposed coefficient. When some dimension-reduction criteria are adopted, we can find some stronger intrinsic frequency correlation in MCI, which cannot be observed in traditional correlations. After further searched, the stronger connectivity is mainly distributed in the regions of MCI functional compensation and abnormal neuron recruitment hypothesis. From an intrinsic frequency spectrum, the reason for MCI’s stronger positive intrinsic frequency correlation is that NC’s correlation becomes smaller. One of explanations is that, the common respiration and cardiac noises in the intrinsic frequency correlation are removed, so that the positive correlation is weakened.

Structural brain disconnectivity mapping of post-stroke fatigue

Stroke patients commonly suffer from post stroke fatigue (PSF). Despite a general consensus that brain perturbations constitute a precipitating event in the multifactorial etiology of PSF, the specific predictive value of conventional lesion characteristics such as size and localization remains unclear. The current study represents a novel approach to assess the neural correlates of PSF in chronic stroke patients. While previous research has focused primarily on lesion location or size, with mixed or inconclusive results, we targeted the extended structural network implicated by the lesion, and evaluated the added explanatory value of a structural disconnectivity approach with regards to the brain correlates of PSF. To this end, we estimated individual structural brain disconnectome maps in 84 S survivors in the chronic phase (≥3 months post stroke) using information about lesion location and normative white matter pathways obtained from 170 healthy individuals. PSF was measured by the Fatigue Severity Scale (FSS). Voxel wise analyses using non-parametric permutation-based inference were conducted on disconnectome maps to estimate regional effects of disconnectivity. Associations between PSF and global disconnectivity and clinical lesion characteristics were tested by linear models, and we estimated Bayes factor to quantify the evidence for the null and alternative hypotheses, respectively. The results revealed no significant associations between PSF and disconnectome measures or lesion characteristics, with moderate evidence in favor of the null hypothesis. These results suggest that symptoms of post-stroke fatigue among chronic stroke patients are not simply explained by lesion characteristics or the extent and distribution of structural brain disconnectome, and are discussed in light of methodological considerations.

Relationship between the disrupted topological efficiency of the structural brain connectome and glucose hypometabolism in normal aging

Normal aging is accompanied by structural degeneration and glucose hypometabolism in the human brain. However, the relationship between structural network disconnections and hypometabolism in normal aging remains largely unknown. In the present study, by combining MRI and PET techniques, we investigated the metabolic mechanism of the structural brain connectome and its relationship with normal aging in a cross-sectional, community-based cohort of 42 cognitively normal elderly individuals aged 57–84 years. The structural connectome was constructed based on diffusion MRI tractography, and the network efficiency metrics were quantified using graph theory analyses. FDG-PET scanning was performed to evaluate the glucose metabolic level in the cortical regions of the individuals. The results of this study demonstrated that both network efficiency and cortical metabolism decrease with age (both p < 0.05). In the subregions of the bilateral thalamus, significant correlations between nodal efficiency and cortical metabolism could be observed across subjects. Individual-level analyses indicated that brain regions with higher nodal efficiency tend to exhibit higher metabolic levels, implying a tight coupling between nodal efficiency and glucose metabolism (r = 0.56, p = 1.15 × 10−21). Moreover, efficiency-metabolism coupling coefficient significantly increased with age (r = 0.44, p = 0.0046). Finally, the main findings were also reproducible in the ADNI dataset. Together, our results demonstrate a close coupling between structural brain connectivity and cortical metabolism in normal elderly individuals and provide new insight that improve the present understanding of the metabolic mechanisms of structural brain disconnections in normal aging.

Approximate Entropy of Brain Network in the Study of Hemispheric Differences.

Human brain, a dynamic complex system, can be studied with different approaches, including linear and nonlinear ones. One of the nonlinear approaches widely used in electroencephalographic (EEG) analyses is the entropy, the measurement of disorder in a system. The present study investigates brain networks applying approximate entropy (ApEn) measure for assessing the hemispheric EEG differences; reproducibility and stability of ApEn data across separate recording sessions were evaluated. Twenty healthy adult volunteers were submitted to eyes-closed resting EEG recordings, for 80 recordings. Significant differences in the occipital region, with higher values of entropy in the left hemisphere than in the right one, show that the hemispheres become active with different intensities according to the performed function. Besides, the present methodology proved to be reproducible and stable, when carried out on relatively brief EEG epochs but also at a 1-week distance in a group of 36 subjects. Nonlinear approaches represent an interesting probe to study the dynamics of brain networks. ApEn technique might provide more insight into the pathophysiological processes underlying age-related brain disconnection as well as for monitoring the impact of pharmacological and rehabilitation treatments.