Disrupted functional brain network organization in patients with obstructive sleep apnea.

IntroductionObstructive sleep apnea (OSA) subjects show impaired autonomic, affective, executive, sensorimotor, and cognitive functions. Brain injury in OSA subjects appears in multiple sites regulating these functions, but the integrity of functional networks within the regulatory sites remains unclear. Our aim was to examine the functional interactions and the complex network organization of these interactions across the whole brain in OSA, using regional functional connectivity (FC) and brain network topological properties.MethodsWe collected resting-state functional magnetic resonance imaging (MRI) data, using a 3.0-Tesla MRI scanner, from 69 newly diagnosed, treatment-naïve, moderate-to-severe OSA (age, 48.3 ± 9.2 years; body mass index, 31 ± 6.2 kg/m(2); apnea-hypopnea index (AHI), 35.6 ± 23.3 events/h) and 82 control subjects (47.6 ± 9.1 years; body mass index, 25.1 ± 3.5 kg/m(2)). Data were analyzed to examine FC in OSA over controls as interregional correlations and brain network topological properties.ResultsObstructive sleep apnea subjects showed significantly altered FC in the cerebellar, frontal, parietal, temporal, occipital, limbic, and basal ganglia regions (FDR, P < 0.05). Entire functional brain networks in OSA subjects showed significantly less efficient integration, and their regional topological properties of functional integration and specialization characteristics also showed declined trends in areas showing altered FC, an outcome which would interfere with brain network organization (P < 0.05; 10,000 permutations). Brain sites with abnormal topological properties in OSA showed significant relationships with AHI scores.ConclusionsOur findings suggest that the dysfunction extends to resting conditions, and the altered FC and impaired network organization may underlie the impaired responses in autonomic, cognitive, and sensorimotor functions. The outcomes likely result from the prominent structural changes in both axons and nuclear structures, which occur in the condition

Divergences Between Resting State Networks and Meta-Analytic Maps Of Task-Evoked Brain Activity

Background: Spontaneous human neural activity is organized into resting state networks, complex patterns of synchronized activity that account for the major part of brain metabolism. The correspondence between these patterns and those elicited by the performance of cognitive tasks would suggest that spontaneous brain activity originates from the stream of ongoing cognitive processing. Objective: To investigate a large number of meta-analytic activation maps obtained from Neurosynth (www.neurosynth.org), establishing the extent of task-rest similarity in large-scale human brain activity. Methods: We applied a hierarchical module detection algorithm to the Neurosynth activation map similarity network, and then compared the average activation maps for each module with a set of resting state networks by means of spatial correlations. Results: We found that the correspondence between resting state networks and task-evoked activity tended to hold only for the largest spatial scales. We also established that this correspondence could be biased by the inclusion of maps related to neuroanatomical terms in the database (e.g. “parietal”, “occipital”, “cingulate”, etc.). Conclusion: Our results establish divergences between brain activity patterns related to spontaneous cognition and the spatial configuration of RSN, suggesting that anatomically-constrained homeostatic processes could play an important role in the inception and shaping of human resting state activity fluctuations.Fil: Palmucci, Matías Damian. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Física de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Física de Buenos Aires; Argentina. Universidad Nacional de San Martín. Escuela de Ciencia y Tecnología; ArgentinaFil: Tagliazucchi, Enzo Rodolfo. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Física de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Física de Buenos Aires; Argentina. Universidad Adolfo Ibañez; Chil

Effects of Transcranial Magnetic Stimulation on the Default Mode Network in Minimal Cognitive Impairment and Alzheimer's disease: An ALE meta-analysis and systematic review

openObjective: This systematic review and meta-analysis sought to comprehensively assess the efficacy of repetitive transcranial magnetic stimulation (rTMS) on the default mode network (DMN) through functional magnetic resonance imaging (fMRI) among individuals diagnosed with mild cognitive impairment (MCI) and Alzheimer's disease (AD). The primary objective was to unravel the neuroimaging mechanisms underpinning cognitive intervention. Methods: A search encompassing English articles published until July 30, 2023, was conducted across prominent databases, including PubMed, Web of Science, Embase, and Cochrane Library. The study specifically focused on randomized controlled trials utilizing resting-state fMRI to investigate the impact of rTMS within the MCI and AD populations. The analysis of fMRI data was executed using GingerALE. Results: Our meta-analysis encompassed a total of seven studies focusing on AD, collectively 116 patients in the treatment group and 90 patients in the sham group. Additionally, in MCI group comprised 34 patients in the treatment groups and 39 patients in the sham group. The combined ALE quantitative analyses on group contrasts between Alzheimer's patients and the sham group showed no significant clusters of convergence. A similar outcome was observed when conducting meta-analyses of the MCI group. The restricted pool of eligible studies may have hindered our ability to detect meaningful clusters of convergence. Conclusions: The outcomes of this meta-analysis and systematic review collectively underscore the potential effectiveness and safety of rTMS intervention in addressing the needs of patients coping with MCI and AD. These improvements could likely be attributed to the favorable modulation that rTMS imparts upon spontaneous neural activity and cognitive networks. By elucidating the intricate neural mechanisms involved, this study contributes insights into the burgeoning field of cognitive intervention strategie

A Meta-analysis of Structural and Functional Brain Abnormalities in Early-Onset Schizophrenia

Early-onset schizophrenia (EOS) patients demonstrate brain changes that are similar to severe cases of adult-onset schizophrenia. Neuroimaging research in EOS is limited due to the rarity of the disorder. The present meta-analysis aims to consolidate MRI and functional MRI findings in EOS. Seven voxel-based morphometry (VBM) and 8 functional MRI studies met the inclusion criteria, reporting whole-brain analyses of EOS vs healthy controls. Activation likelihood estimation (ALE) was conducted to identify aberrant anatomical or functional clusters across the included studies. Separate ALE analyses were performed, first for all task-dependent studies (Cognition ALE) and then only for working memory ones (WM ALE). The VBM ALE revealed no significant clusters for gray matter volume reductions in EOS. Significant hypoactivations peaking in the right anterior cingulate cortex (rACC) and the right temporoparietal junction (rTPJ) were detected in the Cognition ALE. In the WM ALE, consistent hypoactivations were found in the left precuneus (lPreC), the right inferior parietal lobule (rIPL) and the rTPJ. These hypoactivated areas show strong associations with language, memory, attention, spatial, and social cognition. The functional co-activated networks of each suprathreshold ALE cluster, identified using the BrainMap database, revealed a core co-activation network with similar topography to the salience network. Our results add support to posterior parietal, ACC and rTPJ dysfunction in EOS, areas implicated in the cognitive impairments characterizing EOS. The salience network lies at the core of these cognitive processes, co-activating with the hypoactivating regions, and thus highlighting the importance of salience dysfunction in EOS

Sex differences in brain homotopic co-activations: a meta-analytic study

An element of great interest in functional connectivity is ‘homotopic connectivity’ (HC), namely the connectivity between two mirrored areas of the two hemispheres, mainly mediated by the fibers of the corpus callosum. Despite a long tradition of studying sexual dimorphism in the human brain, to our knowledge only one study has addressed the influence of sex on HC. We investigated the issue of homotopic co-activations in women and men using a coordinate-based meta-analytic method and data from the BrainMap database. A first unexpected observation was that the database was affected by a sex bias: women-only groups are investigated less often than men-only ones, and they are more often studied in certain domains such as emotion compared to men, and less in cognition. Implementing a series of sampling procedures to equalize the size and proportion of the datasets, our results indicated that females exhibit stronger interhemispheric co-activation than males, suggesting that the female brain is less lateralized and more integrated than that of males. In addition, males appear to show less intense but more extensive co-activation than females. Some local differences also appeared. In particular, it appears that primary motor and perceptual areas are more co-activated in males, in contrast to the opposite trend in the rest of the brain. This argues for a multidimensional view of sex brain differences and suggests that the issue should be approached with more complex models than previously thought. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00429-022-02572-0

Analgesia da placebo, anticipazione dolorifica e i possibili correlati neurali dell'effetto nocebo

The nocebo effect is a psychobiological effect that occurs when a negative psychosocial context that accompanies a therapy. Since the study of pain anticipation takes into account the temporal phase of the “expectation of hyperalgesia”, and considering that it is possible to stimulate such anticipatory processes merely through the use of negative verbalizations, this model is appropriate for studying the nocebo response. To date, there are no univocal data about the brain areas involved in these processes or their cognitive roles. We conducted a meta-analysis on pain anticipation fMRI studies. We then applied a meta-analytic connectivity model to activations in the anterior cingulate cortex and the anterior insula, which correlate with the behavioral domains of action, emotion and perception. Our results support the hypothesis that there is a highly-distributed supramodal system, activated by pain anticipation, for processing information that enhances the self-regulation of adaptive responses to the environment

Behavior, sensitivity, and power of activation likelihood estimation characterized by massive empirical simulation

Given the increasing number of neuroimaging publications, the automated knowledge extraction on brain-behavior associations by quantitative meta-analyses has become a highly important and rapidly growing field of research. Among several methods to perform coordinate-based neuroimaging meta-analyses, Activation Likelihood Estimation (ALE) has been widely adopted. In this paper, we addressed two pressing questions related to ALE meta-analysis: i) Which thresholding method is most appropriate to perform statistical inference? ii) Which sample size, i.e., number of experiments, is needed to perform robust meta-analyses? We provided quantitative answers to these questions by simulating more than 120,000 meta-analysis datasets using empirical parameters (i.e., number of subjects, number of reported foci, distribution of activation foci) derived from the BrainMap database. This allowed to characterize the behavior of ALE analyses, to derive first power estimates for neuroimaging meta-analyses, and to thus formulate recommendations for future ALE studies. We could show as a first consequence that cluster-level family-wise error (FWE) correction represents the most appropriate method for statistical inference, while voxel-level FWE correction is valid but more conservative. In contrast, uncorrected inference and false-discovery rate correction should be avoided. As a second consequence, researchers should aim to include at least 20 experiments into an ALE meta-analysis to achieve sufficient power for moderate effects. We would like to note, though, that these calculations and recommendations are specific to ALE and may not be extrapolated to other approaches for (neuroimaging) meta-analysis