Mast Syndrome Outside the Amish Community: SPG21 in Europe

Background:Mast syndrome is a rare disorder belonging to the group of hereditary spastic paraplegias (HSPs). It is caused by bi-allelic mutations in the ACP33 gene, and is originally described in Old Order Amish. Outside this population, only one Japanese and one Italian family have been reported. Herein, we describe five subjects from the first three SPG21 families of German and Austrian descent.Methods:Five subjects with complicated HSP were referred to our centers. The workup consisted of neurological examination, neurophysiological and neuropsychological assessments, MRI, and genetic testing.Results:Onset varied from child- to adulthood. All patients exhibited predominant spastic para- or tetraparesis with positive pyramidal signs, pronounced cognitive impairment, ataxia, and extrapyramidal signs. Neurophysiological workup showed abnormal motor and sensory evoked potentials in all the patients. Sensorimotor axonal neuropathy was present in one patient. Imaging exhibited thin corpus callosum and global brain atrophy. Genetic testing revealed one heterozygous compound and two homozygous mutations in the ACP33 gene.Conclusion:Herein, we report the first three Austrian and two German patients with SPG21, presenting a detailed description of their clinical phenotype and disease course. Our report adds to the knowledge of this extremely rare disorder, and highlights that SPG21 must also be considered in the differential diagnosis of complicated HSP outside the Amish community.

Harmonized-Multinational qEEG Norms (HarMNqEEG)

This paper extends our 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 Hermitian 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 Hermitian Riemannian descriptive parameters 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 Hermitian 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. We provide data and software for constructing norms. 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.

Binocular Integrated Visual Field Deficits Are Associated With Changes in Local Network Function in Primary Open-Angle Glaucoma: A Resting-State fMRI Study

In glaucoma participants, both structural and functional brain changes have been observed, but we still have insufficient understanding of how these changes also affect the integrity of cortical functional networks, and how these changes relate to visual function. This is relevant, as functional network integrity may affect the applicability of future treatments, as well as the options for rehabilitation or training. Here, we compare global and local functional connectivity in local and global brain networks between glaucoma and control participants. Moreover, we study the relationship between functional connectivity and visual field (VF) loss. For our study, 20 subjects with primary open-angle glaucoma (POAG) and 24 age-similar healthy participants were recruited to undergo an ophthalmic assessment followed by two resting-state (RS) (f)MRI scans. For each scan and for each group, the ROIs with eigenvector centrality (EC) values higher than the 95th percentile were considered the most central brain regions (“hubs”). Hubs for which we found a significant difference in EC in both scans between glaucoma and healthy participants were considered to provide evidence for network changes. In addition, we tested the notion that a brain region's hub function in POAG might relate to the severity of a participant's VF defect, irrespective of which eye contributed mostly to this. To determine this, for each participant, eye-independent scores were derived for: (1) sensitivity of the worse eye – indicating disease severity, (2) sensitivity of both eyes combined – with one eye potentially compensating for loss in the other, or (3) difference in eye sensitivity – potentially requiring additional network interactions. By correlating each of these VF scores and the EC values, we assessed whether VF defects could be associated with centrality alterations in POAG. Our results show that no functional connectivity disruptions were found at the global brain level in POAG participants. This indicates that in glaucoma global brain network communication is preserved. Furthermore, for the Lingual Gyrus, identified as a brain hub, we found a positive correlation between the EC value and the VF sensitivity of both eyes combined. The fact that reduced local network functioning is associated with reduced binocular VF sensitivity suggests the presence of local brain reorganization that has a bearing on functional visual abilities.

Cortical glutamatergic projection neuron types contribute to distinct functional subnetworks

The cellular basis of cerebral cortex functional architecture remains not well understood. A major challenge is to monitor and decipher neural network dynamics across broad cortical areas yet with projection neuron (PN) type resolution in real time during behavior. Combining genetic targeting and wide-field imaging, we monitored activity dynamics of subcortical-projecting (PTFezf2) and intratelencephalic-projecting (ITPlxnD1) types across dorsal cortex of mice during multiple brain states and behaviors. ITPlxnD1 and PTFezf2 showed distinct activation patterns during wakeful resting, spontaneous movements, and upon sensory stimulation. Distinct ITPlxnD1 and PTFezf2 subnetworks dynamically tuned to different sensorimotor components of a naturalistic feeding behavior, and optogenetic inhibition of subnetwork nodes disrupted specific behavioral components. ITPlxnD1 and PTFezf2 projection patterns supported their subnetwork activation patterns. Our results suggest that, in addition to the concept of columnar organization, dynamic areal and PN type-specific subnetworks is a key feature of cortical functional architecture linking microcircuit components with global brain networks.

Comparing Brain Asymmetries Independently of Brain Size

Studies examining cerebral asymmetries typically divide the L-R Measure (e.g., Left-Right Volume) by the L+R Measure to obtain an Asymmetry Index (AI). However, contrary to widespread belief, such a division fails to render the AI independent from the L+R Measure and/or from total brain size. As a result, variations in brain size may bias correlation estimates with the AI or group differences in AI. We investigated how to analyze brain asymmetries in to distinguish global from regional effects, and report unbiased group differences in cerebral asymmetries. We analyzed the extent to which the L+R Measure, Total Cerebral Measure (TCM, e.g., Total Brain Volume), and L-R TCM predict regional asymmetries. As a case study, we assessed the consequences of omitting each of these predictors on the magnitude and significance of sex differences in asymmetries. We found that the L+R Measure, the TCM, and the L-R TCM predicted the AI of more than 89% of regions and that their relationships were generally linear. Removing any of these predictors changed the significance of sex differences in 33% of regions and the magnitude of sex differences across 13-42% of regions. Although we generally report similar sex and age effects on cerebral asymmetries to those of previous large-scale studies, properly adjusting for regional and global brain size revealed additional sex and age effects on brain asymmetry.

Hierarchical Spatiotemporal Electroencephalogram Feature Learning and Emotion Recognition With Attention-Based Antagonism Neural Network

Inspired by the neuroscience research results that the human brain can produce dynamic responses to different emotions, a new electroencephalogram (EEG)-based human emotion classification model was proposed, named R2G-ST-BiLSTM, which uses a hierarchical neural network model to learn more discriminative spatiotemporal EEG features from local to global brain regions. First, the bidirectional long- and short-term memory (BiLSTM) network is used to obtain the internal spatial relationship of EEG signals on different channels within and between regions of the brain. Considering the different effects of various cerebral regions on emotions, the regional attention mechanism is introduced in the R2G-ST-BiLSTM model to determine the weight of different brain regions, which could enhance or weaken the contribution of each brain area to emotion recognition. Then a hierarchical BiLSTM network is again used to learn the spatiotemporal EEG features from regional to global brain areas, which are then input into an emotion classifier. Especially, we introduce a domain discriminator to work together with the classifier to reduce the domain offset between the training and testing data. Finally, we make experiments on the EEG data of the DEAP and SEED datasets to test and compare the performance of the models. It is proven that our method achieves higher accuracy than those of the state-of-the-art methods. Our method provides a good way to develop affective brain–computer interface applications.

A functional topography within the cholinergic basal forebrain for encoding sensory cues and behavioral reinforcement outcomes

Basal forebrain cholinergic neurons (BFCNs) project throughout the cortex to regulate arousal, stimulus salience, plasticity, and learning. Although often treated as a monolithic structure, the basal forebrain features distinct connectivity along its rostrocaudal axis that could impart regional differences in BFCN processing. Here, we performed simultaneous bulk calcium imaging from rostral and caudal BFCNs over a one-month period of variable reinforcement learning in mice. BFCNs in both regions showed equivalently weak responses to unconditioned visual stimuli and anticipated rewards. Rostral BFCNs in the horizontal limb of the diagonal band were more responsive to reward omission, more accurately classified behavioral outcomes, and more closely tracked fluctuations in pupil-indexed global brain state. Caudal tail BFCNs in globus pallidus and substantia innominata were more responsive to unconditioned auditory stimuli, orofacial movements, aversive reinforcement, and showed robust associative plasticity for punishment-predicting cues. These results identify a functional topography that diversifies cholinergic modulatory signals broadcast to downstream brain regions.

Pierre Teilhard de Chardin’s Phenomenology of the Noosphere

Although Pierre Teilhard de Chardin (1881–1955) was thoroughly trained in philosophy and theology, he was first and foremost a paleoanthropologist, directly involved in the discovery of Homo erectus pekinensis (“Sinanthropus”) in China in the 1920s and 1930s. He came from a Catholic aristocratic background, was ordained a priest in 1911, survived World War I (as a stretcher-bearer, distinguished with the Legion of Honour), joined the Jesuit Order, conducted paleoanthropological field work during the interbellum, and became entangled in a conflict with his Jesuit superiors (over pantheism and the concept of original sin) until his death in New York (in exile more or less). When his writings were published (shortly after his death, as his superiors forbade publication during his lifetime), he quickly became an intellectual celebrity. Currently, he is credited with having anticipated Gaia theory (King, 2006), the global village concept (McLuhan, 1962), the Internet (Barlow, 1992; Cobb, 1998), the WWW (Garreau, 2005, p. 256; Greenfield, 2014, p. 9), transhumanism (Delio, 2014; Steinhart, 2008), the “global brain” (Stock, 1993), and the Anthropocene (e.g. Crutzen, 2002; Steffen et al., 2011).