Isolated effective coherence (iCoh): causal information flow excluding indirect paths

A problem of great interest in real world systems, where multiple time series measurements are available, is the estimation of the intra-system causal relations. For instance, electric cortical signals are used for studying functional connectivity between brain areas, their directionality, the direct or indirect nature of the connections, and the spectral characteristics (e.g. which oscillations are preferentially transmitted). The earliest spectral measure of causality was Akaike's (1968) seminal work on the noise contribution ratio, reflecting direct and indirect connections. Later, a major breakthrough was the partial directed coherence of Baccala and Sameshima (2001) for direct connections. The simple aim of this study consists of two parts: (1) To expose a major problem with the partial directed coherence, where it is shown that it is affected by irrelevant connections to such an extent that it can misrepresent the frequency response, thus defeating the main purpose for which the measure was developed, and (2) To provide a solution to this problem, namely the "isolated effective coherence", which consists of estimating the partial coherence under a multivariate auto-regressive model, followed by setting all irrelevant associations to zero, other than the particular directional association of interest. Simple, realistic, toy examples illustrate the severity of the problem with the partial directed coherence, and the solution achieved by the isolated effective coherence. For the sake of reproducible research, the software code implementing the methods discussed here (using lazarus free-pascal "www.lazarus.freepascal.org"), including the test data as text files, are freely available at: https://sites.google.com/site/pascualmarqui/home/icoh-isolated-effective-coherenceComment: 2014-02-21 pre-print, technical report, KEY Institute for Brain-Mind Research, University of Zurich, et a

Innovations orthogonalization: a solution to the major pitfalls of EEG/MEG "leakage correction"

The problem of interest here is the study of brain functional and effective connectivity based on non-invasive EEG-MEG inverse solution time series. These signals generally have low spatial resolution, such that an estimated signal at any one site is an instantaneous linear mixture of the true, actual, unobserved signals across all cortical sites. False connectivity can result from analysis of these low-resolution signals. Recent efforts toward "unmixing" have been developed, under the name of "leakage correction". One recent noteworthy approach is that by Colclough et al (2015 NeuroImage, 117:439-448), which forces the inverse solution signals to have zero cross-correlation at lag zero. One goal is to show that Colclough's method produces false human connectomes under very broad conditions. The second major goal is to develop a new solution, that appropriately "unmixes" the inverse solution signals, based on innovations orthogonalization. The new method first fits a multivariate autoregression to the inverse solution signals, giving the mixed innovations. Second, the mixed innovations are orthogonalized. Third, the mixed and orthogonalized innovations allow the estimation of the "unmixing" matrix, which is then finally used to "unmix" the inverse solution signals. It is shown that under very broad conditions, the new method produces proper human connectomes, even when the signals are not generated by an autoregressive model.Comment: preprint, technical report, under license "Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)", https://creativecommons.org/licenses/by-nc-nd/4.0

Brain charts for the human lifespan

Over the past few decades, neuroimaging has become a ubiquitous tool in basic research and clinical studies of the human brain. However, no reference standards currently exist to quantify individual differences in neuroimaging metrics over time, in contrast to growth charts for anthropometric traits such as height and weight1. Here we assemble an interactive open resource to benchmark brain morphology derived from any current or future sample of MRI data (http://www.brainchart.io/). With the goal of basing these reference charts on the largest and most inclusive dataset available, acknowledging limitations due to known biases of MRI studies relative to the diversity of the global population, we aggregated 123,984 MRI scans, across more than 100 primary studies, from 101,457 human participants between 115 days post-conception to 100 years of age. MRI metrics were quantified by centile scores, relative to non-linear trajectories2 of brain structural changes, and rates of change, over the lifespan. Brain charts identified previously unreported neurodevelopmental milestones3, showed high stability of individuals across longitudinal assessments, and demonstrated robustness to technical and methodological differences between primary studies. Centile scores showed increased heritability compared with non-centiled MRI phenotypes, and provided a standardized measure of atypical brain structure that revealed patterns of neuroanatomical variation across neurological and psychiatric disorders. In summary, brain charts are an essential step towards robust quantification of individual variation benchmarked to normative trajectories in multiple, commonly used neuroimaging phenotypes

Harmonized-Multinational qEEG Norms (HarMNqEEG)

This paper extends the frequency domain quantitative electroencephalography (qEEG) methods pursuing higher sensitivity to detect Brain Developmental Disorders. Prior qEEG work lacked integration of cross-spectral information omitting important functional connectivity descriptors. Lack of geographical diversity precluded accounting for site-specific variance, increasing qEEG nuisance variance. We ameliorate these weaknesses. i) Create lifespan Riemannian multinational qEEG norms for cross-spectral tensors. These norms result from the HarMNqEEG project fostered by the Global Brain Consortium. We calculate the norms with data from 9 countries, 12 devices, and 14 studies, including 1564 subjects. Instead of raw data, only anonymized metadata and EEG cross-spectral tensors were shared. After visual and automatic quality control, developmental equations for the mean and standard deviation of qEEG traditional and Riemannian DPs were calculated using additive mixed-effects models. We demonstrate qEEG "batch effects" and provide methods to calculate harmonized z-scores. ii) We also show that the multinational harmonized Riemannian norms produce z-scores with increased diagnostic accuracy to predict brain dysfunction at school-age produced by malnutrition only in the first year of life. iii) We offer open code and data to calculate different individual z-scores from the HarMNqEEG dataset. These results contribute to developing bias-free, low-cost neuroimaging technologies applicable in various health settings

Processing of Abstract Rule Violations in Audition

The ability to encode rules and to detect rule-violating events outside the focus of attention is vital for adaptive behavior. Our brain recordings reveal that violations of abstract auditory rules are processed even when the sounds are unattended. When subjects performed a task related to the sounds but not to the rule, rule violations impaired task performance and activated a network involving supratemporal, parietal and frontal areas although none of the subjects acquired explicit knowledge of the rule or became aware of rule violations. When subjects tried to behaviorally detect rule violations, the brain's automatic violation detection facilitated intentional detection. This shows the brain's capacity for abstraction – an important cognitive function necessary to model the world. Our study provides the first evidence for the task-independence (i.e. automaticity) of this ability to encode abstract rules and for its immediate consequences for subsequent mental processes

The Role of Gamma-Band Activity in the Representation of Faces: Reduced Activity in the Fusiform Face Area in Congenital Prosopagnosia

Congenital prosopagnosia (CP) describes an impairment in face processing that is presumably present from birth. The neuronal correlates of this dysfunction are still under debate. In the current paper, we investigate high-frequent oscillatory activity in response to faces in persons with CP. Such neuronal activity is thought to reflect higher-level representations for faces.Source localization of induced Gamma-Band Responses (iGBR) measured by magnetoencephalography (MEG) was used to establish the origin of oscillatory activity in response to famous and unknown faces which were presented in upright and inverted orientation. Persons suffering from congenital prosopagnosia (CP) were compared to matched controls.Corroborating earlier research, both groups revealed amplified iGBR in response to upright compared to inverted faces predominately in a time interval between 170 and 330 ms and in a frequency range from 50-100 Hz. Oscillatory activity upon known faces was smaller in comparison to unknown faces, suggesting a "sharpening" effect reflecting more efficient processing for familiar stimuli. These effects were seen in a wide cortical network encompassing temporal and parietal areas involved in the disambiguation of homogenous stimuli such as faces, and in the retrieval of semantic information. Importantly, participants suffering from CP displayed a strongly reduced iGBR in the left fusiform area compared to control participants.In sum, these data stress the crucial role of oscillatory activity for face representation and demonstrate the involvement of a distributed occipito-temporo-parietal network in generating iGBR. This study also provides the first evidence that persons suffering from an agnosia actually display reduced gamma band activity. Finally, the results argue strongly against the view that oscillatory activity is a mere epiphenomenon brought fourth by rapid eye-movements (micro saccades)

Mindful Aging: The Effects of Regular Brief Mindfulness Practice on Electrophysiological Markers of Cognitive and Affective Processing in Older Adults

There is growing interest in the potential benefits of mindfulness meditation practices in terms of counteracting some of the cognitive effects associated with aging. Pursuing this question, the aim of the present study was to investigate the influence of mindfulness training on executive control and emotion regulation in older adults, by means of studying behavioral and electrophysiological changes. Participants, 55 to 75 years of age, were randomly allocated to an 8-week mindful breath awareness training group or an active control group engaging in brain training exercises. Before and after the training period, participants completed an emotional-counting Stroop task, designed to measure attentional control and emotion regulation processes. Concurrently, their brain activity was measured by means of 64-channel electroencephalography. The results show that engaging in just over 10 min of mindfulness practice five times per week resulted in significant improvements in behavioral (response latency) and electrophysiological (N2 event-related potential) measures related to general task performance. Analyses of the underlying cortical sources (Variable Resolution Electromagnetic Tomography, VARETA) indicate that this N2-related effect is primarily associated with changes in the right angular gyrus and other areas of the dorsal attention network. However, the study did not find the expected specific improvements in executive control and emotion regulation, which may be due to the training instructions or the relative brevity of the intervention. Overall, the results indicate that engaging in mindfulness meditation training improves the maintenance of goal-directed visuospatial attention and may be a useful strategy for counteracting cognitive decline associated with aging

Country-level gender inequality is associated with structural differences in the brains of women and men

男女間の不平等と脳の性差 --男女間の不平等は脳構造の性差と関連する--. 京都大学プレスリリース. 2023-05-10.Gender inequality across the world has been associated with a higher risk to mental health problems and lower academic achievement in women compared to men. We also know that the brain is shaped by nurturing and adverse socio-environmental experiences. Therefore, unequal exposure to harsher conditions for women compared to men in gender-unequal countries might be reflected in differences in their brain structure, and this could be the neural mechanism partly explaining women’s worse outcomes in gender-unequal countries. We examined this through a random-effects meta-analysis on cortical thickness and surface area differences between adult healthy men and women, including a meta-regression in which country-level gender inequality acted as an explanatory variable for the observed differences. A total of 139 samples from 29 different countries, totaling 7, 876 MRI scans, were included. Thickness of the right hemisphere, and particularly the right caudal anterior cingulate, right medial orbitofrontal, and left lateral occipital cortex, presented no differences or even thicker regional cortices in women compared to men in gender-equal countries, reversing to thinner cortices in countries with greater gender inequality. These results point to the potentially hazardous effect of gender inequality on women’s brains and provide initial evidence for neuroscience-informed policies for gender equality

Country-level gender inequality is associated with structural differences in the brains of women and men

Gender inequality across the world has been associated with a higher risk to mental health problems and lower academic achievement in women compared to men. We also know that the brain is shaped by nurturing and adverse socio-environmental experiences. Therefore, unequal exposure to harsher conditions for women compared to men in gender-unequal countries might be reflected in differences in their brain structure, and this could be the neural mechanism partly explaining women's worse outcomes in gender-unequal countries. We examined this through a random-effects meta-analysis on cortical thickness and surface area differences between adult healthy men and women, including a meta-regression in which country-level gender inequality acted as an explanatory variable for the observed differences. A total of 139 samples from 29 different countries, totaling 7,876 MRI scans, were included. Thickness of the right hemisphere, and particularly the right caudal anterior cingulate, right medial orbitofrontal, and left lateral occipital cortex, presented no differences or even thicker regional cortices in women compared to men in gender-equal countries, reversing to thinner cortices in countries with greater gender inequality. These results point to the potentially hazardous effect of gender inequality on women's brains and provide initial evidence for neuroscience-informed policies for gender equality