scholarly journals Preserved representations and decodability of diverse cognitive functions across the cortex, cerebellum, and subcortex

2021 ◽  
Author(s):  
Tomoya Nakai ◽  
Shinji Nishimoto
Keyword(s):  
Cognitive Functions ◽  
Principal Component ◽  
Cognitive Tasks ◽  
Sufficient Information ◽  
The Novel ◽  
Imaging Data ◽  
Functional Representations ◽  
Model Training ◽  
Task Representations ◽  
The Brain

Which part of the brain contributes to our complex cognitive processes? Studies have revealed contributions of the cerebellum and subcortex to higher-order cognitive functions; however it is unclear whether such functional representations are preserved across the cortex, cerebellum, and subcortex. In this study, we used functional magnetic resonance imaging data with 103 cognitive tasks and constructed three voxel-wise encoding and decoding models independently using cortical, cerebellar, and subcortical voxels. Representational similarity analysis revealed that the structure of task representations is preserved across the three brain parts. Principal component analysis visualized distinct organizations of abstract cognitive functions in each part of the cerebellum and subcortex. More than 90% of the cognitive tasks were decodable from the cerebellum and subcortical activities, even for the novel tasks not included in model training. Furthermore, we discovered that the cerebellum and subcortex have sufficient information to reconstruct activity in the cerebral cortex.

scholarly journals The modular and integrative functional architecture of the human brain

2015 ◽  
Vol 112 (49) ◽  
pp. E6798-E6807 ◽  
Author(s):  
Maxwell A. Bertolero ◽  
B. T. Thomas Yeo ◽  
Mark D’Esposito
Keyword(s):  
Human Brain ◽  
Cognitive Functions ◽  
Topic Model ◽  
Brain Activity ◽  
Modular Function ◽  
Imaging Data ◽  
Functional Architecture ◽  
Brain Imaging Data ◽  
The Brain

Network-based analyses of brain imaging data consistently reveal distinct modules and connector nodes with diverse global connectivity across the modules. How discrete the functions of modules are, how dependent the computational load of each module is to the other modules’ processing, and what the precise role of connector nodes is for between-module communication remains underspecified. Here, we use a network model of the brain derived from resting-state functional MRI (rs-fMRI) data and investigate the modular functional architecture of the human brain by analyzing activity at different types of nodes in the network across 9,208 experiments of 77 cognitive tasks in the BrainMap database. Using an author–topic model of cognitive functions, we find a strong spatial correspondence between the cognitive functions and the network’s modules, suggesting that each module performs a discrete cognitive function. Crucially, activity at local nodes within the modules does not increase in tasks that require more cognitive functions, demonstrating the autonomy of modules’ functions. However, connector nodes do exhibit increased activity when more cognitive functions are engaged in a task. Moreover, connector nodes are located where brain activity is associated with many different cognitive functions. Connector nodes potentially play a role in between-module communication that maintains the modular function of the brain. Together, these findings provide a network account of the brain’s modular yet integrated implementation of cognitive functions.

scholarly journals Concomitant taurine exposure counteracts ethanol-induced changes in locomotor and anxiety-like responses in zebrafish

2019 ◽  
Vol 237 (3) ◽  
pp. 735-743 ◽  
Author(s):  
Barbara D. Fontana ◽  
Tamie Duarte ◽  
Talise E. Müller ◽  
Julia Canzian ◽  
Paola R. Ziani ◽  
...  
Keyword(s):  
Sulfonic Acid ◽  
Principal Component ◽  
The Novel ◽  
Complex Mechanism ◽  
Adult Zebrafish ◽  
Water Control ◽  
Principal Component Analyses ◽  
High Concentrations ◽  
Induced Changes ◽  
The Brain

AbstractTaurine (TAU) is a β-amino sulfonic acid with pleiotropic roles in the brain, including the neuromodulatory activity via GABAergic and glycinergic agonism. This molecule is found at high concentrations in energy drinks and is often mixed with alcohol in beverages. Although TAU has a neuroprotective role in the brain, the putative risks of mixing TAU and EtOH are not fully understood. Here, we investigated whether TAU modulates locomotor and anxiety-like behavior in adult zebrafish by using the novel tank and light-dark tests following acute EtOH exposure at anxiogenic and anxiolytic concentrations. Zebrafish were individually exposed to water (control), TAU (42, 150, and 400 mg/L), and EtOH (0.25% (v/v) and 1% (v/v)) both independently and cotreated for 1 h. EtOH 0.25% and TAU produced U-shape anxiolytic-like behavior in the light-dark test, TAU 42 and 400 positively modulated EtOH effects, and TAU 150 exerted a protective effect. All TAU concentrations counteracted EtOH 1%-induced locomotion impairment, as well as the anxiogenic-like behavior. Finally, all TAU concentrations when given independently or cotreated with EtOH 0.25% and 1% decreased the risk assessment of the lit compartment. Principal component analyses revealed that exploration and anxiety-like responses were the main behaviors that contribute to the effects of TAU and EtOH. Overall, we demonstrate that TAU differently modulates EtOH-induced anxiolytic- and anxiogenic-like behaviors depending on the concentration, suggesting a complex mechanism underlying TAU and EtOH interactions.

scholarly journals Cerebral 5-HT release correlates with [11C]Cimbi36 PET measures of 5-HT2A receptor occupancy in the pig brain

2016 ◽  
Vol 37 (2) ◽  
pp. 425-434 ◽  
Author(s):  
Louise M Jørgensen ◽  
Pia Weikop ◽  
Jonas Villadsen ◽  
Tanel Visnapuu ◽  
Anders Ettrup ◽  
...  
Keyword(s):  
Spatial Information ◽  
Receptor Occupancy ◽  
The Novel ◽  
Imaging Data ◽  
Pig Brain ◽  
Positron Emission ◽  
Brain Neurotransmitter ◽  
Acute Changes ◽  
First Time ◽  
The Brain

Positron emission tomography (PET) can, when used with appropriate radioligands, non-invasively generate temporal and spatial information about acute changes in brain neurotransmitter systems. We for the first time evaluate the novel 5-HT2A receptor agonist PET radioligand, [11C]Cimbi-36, for its sensitivity to detect changes in endogenous cerebral 5-HT levels, as induced by different pharmacological challenges. To enable a direct translation of PET imaging data to changes in brain 5-HT levels, we calibrated the [11C]Cimbi-36 PET signal in the pig brain by simultaneous measurements of extracellular 5-HT levels with microdialysis and [11C]Cimbi-36 PET after various acute interventions (saline, citalopram, citalopram + pindolol, fenfluramine). In a subset of pigs, para-chlorophenylalanine pretreatment was given to deplete cerebral 5-HT. The interventions increased the cerebral extracellular 5-HT levels to 2–11 times baseline, with fenfluramine being the most potent pharmacological enhancer of 5-HT release, and induced a varying degree of decline in [11C]Cimbi-36 binding in the brain, consistent with the occupancy competition model. The observed correlation between changes in the extracellular 5-HT level in the pig brain and the 5-HT2A receptor occupancy indicates that [11C]Cimbi-36 binding is sensitive to changes in endogenous 5-HT levels, although only detectable with PET when the 5-HT release is sufficiently high.

Brain plasticity, cognitive functions and neural stem cells: a pivotal role for the brain-specific neural master gene |-SRGAP2–FAM72-|

2017 ◽  
Vol 399 (1) ◽  
pp. 55-61 ◽  
Author(s):  
Nguyen Thi Thanh Ho ◽  
Arne Kutzner ◽  
Klaus Heese
Keyword(s):  
Cognitive Functions ◽  
Rho Gtpase ◽  
Brain Plasticity ◽  
Sequence Similarity ◽  
The Novel ◽  
Therapeutic Approaches ◽  
Cellular Events ◽  
Specific Regulation ◽  
Higher Cognitive Functions ◽  
The Brain

AbstractDue to an aging society with an increased dementia-induced threat to higher cognitive functions, it has become imperative to understand the molecular and cellular events controlling the memory and learning processes in the brain. Here, we suggest that the novel master gene pair |-SRGAP2–FAM72-| (SLIT-ROBO Rho GTPase activating the protein 2, family with sequence similarity to 72) reveals a new dogma for the regulation of neural stem cell (NSC) gene expression and is a distinctive player in the control of human brain plasticity. Insight into the specific regulation of the brain-specific neural master gene |-SRGAP2–FAM72-| may essentially contribute to novel therapeutic approaches to restore or improve higher cognitive functions.

Sex Differences in Cognition

2019 ◽  
pp. 41-66
Author(s):  
Elizabeth Hampson
Keyword(s):  
Central Nervous System ◽  
Nervous System ◽  
Sex Differences ◽  
Spatial Cognition ◽  
Sex Steroids ◽  
Cognitive Functions ◽  
Laboratory Animals ◽  
Human Central Nervous System ◽  
The Brain

Organizational and activational effects of sex steroids were first discovered in laboratory animals, but these concepts extend to hormonal actions in the human central nervous system. This chapter begins with a brief overview of how sex steroids act in the brain and how the organizational-activational hypothesis originated in the field of endocrinology. It then reviews common methods used to study these effects in humans. Interestingly, certain cognitive functions appear to be subject to modification by sex steroids, and these endocrine influences may help explain the sex differences often seen in these functions. The chapter considers spatial cognition as a representative example because the spatial family of functions has received the most study by researchers interested in the biological roots of sex differences in cognition. The chapter reviews evidence that supports an influence of both androgens and estrogens on spatial functions, and concludes with a glimpse of where the field is headed.

scholarly journals Content-Based Estimation of Brain MRI Tilt in Three Orthogonal Directions

2021 ◽  
Author(s):  
Pooja Prabhu ◽  
A. K. Karunakar ◽  
Sanjib Sinha ◽  
N. Mariyappa ◽  
G. K. Bhargava ◽  
...  
Keyword(s):  
Large Scale ◽  
Brain Mri ◽  
Similarity Measures ◽  
Principal Component ◽  
Brain Anatomy ◽  
Morphological Operations ◽  
Mr Images ◽  
Tilt Correction ◽  
Brain Mr Images ◽  
The Brain

AbstractIn a general scenario, the brain images acquired from magnetic resonance imaging (MRI) may experience tilt, distorting brain MR images. The tilt experienced by the brain MR images may result in misalignment during image registration for medical applications. Manually correcting (or estimating) the tilt on a large scale is time-consuming, expensive, and needs brain anatomy expertise. Thus, there is a need for an automatic way of performing tilt correction in three orthogonal directions (X, Y, Z). The proposed work aims to correct the tilt automatically by measuring the pitch angle, yaw angle, and roll angle in X-axis, Z-axis, and Y-axis, respectively. For correction of the tilt around the Z-axis (pointing to the superior direction), image processing techniques, principal component analysis, and similarity measures are used. Also, for correction of the tilt around the X-axis (pointing to the right direction), morphological operations, and tilt correction around the Y-axis (pointing to the anterior direction), orthogonal regression is used. The proposed approach was applied to adjust the tilt observed in the T1- and T2-weighted MR images. The simulation study with the proposed algorithm yielded an error of 0.40 ± 0.09°, and it outperformed the other existing studies. The tilt angle (in degrees) obtained is ranged from 6.2 ± 3.94, 2.35 ± 2.61, and 5 ± 4.36 in X-, Z-, and Y-directions, respectively, by using the proposed algorithm. The proposed work corrects the tilt more accurately and robustly when compared with existing studies.

scholarly journals Time lapse synchrotron IR chemical imaging for observing the acclimation of a single algal cell to CO2 treatment

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Ghazal Azarfar ◽  
Ebrahim Aboualizadeh ◽  
Simona Ratti ◽  
Camilla Olivieri ◽  
Alessandra Norici ◽  
...  
Keyword(s):  
Algal Cell ◽  
Principal Component ◽  
External Perturbation ◽  
Time Lapse ◽  
Chemical Imaging ◽  
Hyperspectral Data ◽  
Aqueous Environment ◽  
Ir Absorption ◽  
Imaging Data ◽  
Mid Infrared

AbstractAlgae are the main primary producers in aquatic environments and therefore of fundamental importance for the global ecosystem. Mid-infrared (IR) microspectroscopy is a non-invasive tool that allows in principle studying chemical composition on a single-cell level. For a long time, however, mid-infrared (IR) imaging of living algal cells in an aqueous environment has been a challenge due to the strong IR absorption of water. In this study, we employed multi-beam synchrotron radiation to measure time-resolved IR hyperspectral images of individual Thalassiosira weissflogii cells in water in the course of acclimation to an abrupt change of CO2 availability (from 390 to 5000 ppm and vice versa) over 75 min. We used a previously developed algorithm to correct sinusoidal interference fringes from IR hyperspectral imaging data. After preprocessing and fringe correction of the hyperspectral data, principal component analysis (PCA) was performed to assess the spatial distribution of organic pools within the algal cells. Through the analysis of 200,000 spectra, we were able to identify compositional modifications associated with CO2 treatment. PCA revealed changes in the carbohydrate pool (1200–950 cm$$^{-1}$$ - 1 ), lipids (1740, 2852, 2922 cm$$^{-1}$$ - 1 ), and nucleic acid (1160 and 1201 cm$$^{-1}$$ - 1 ) as the major response of exposure to elevated CO2 concentrations. Our results show a local metabolism response to this external perturbation.

scholarly journals The unbalanced reorganization of weaker functional connections induces the altered brain network topology in schizophrenia

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Rossana Mastrandrea ◽  
Fabrizio Piras ◽  
Andrea Gabrielli ◽  
Nerisa Banaj ◽  
Guido Caldarelli ◽  
...  
Keyword(s):  
Resting State ◽  
Functional Organization ◽  
Functional Integration ◽  
Brain Network ◽  
Modular Organization ◽  
Node Degree ◽  
Imaging Data ◽  
Brain Disorder ◽  
Functional Connections ◽  
The Brain

AbstractNetwork neuroscience shed some light on the functional and structural modifications occurring to the brain associated with the phenomenology of schizophrenia. In particular, resting-state functional networks have helped our understanding of the illness by highlighting the global and local alterations within the cerebral organization. We investigated the robustness of the brain functional architecture in 44 medicated schizophrenic patients and 40 healthy comparators through an advanced network analysis of resting-state functional magnetic resonance imaging data. The networks in patients showed more resistance to disconnection than in healthy controls, with an evident discrepancy between the two groups in the node degree distribution computed along a percolation process. Despite a substantial similarity of the basal functional organization between the two groups, the expected hierarchy of healthy brains' modular organization is crumbled in schizophrenia, showing a peculiar arrangement of the functional connections, characterized by several topologically equivalent backbones. Thus, the manifold nature of the functional organization’s basal scheme, together with its altered hierarchical modularity, may be crucial in the pathogenesis of schizophrenia. This result fits the disconnection hypothesis that describes schizophrenia as a brain disorder characterized by an abnormal functional integration among brain regions.

Individual Uniqueness in the Neonatal Functional Connectome

2021 ◽  
Author(s):  
Qiushi Wang ◽  
Yuehua Xu ◽  
Tengda Zhao ◽  
Zhilei Xu ◽  
Yong He ◽  
...  
Keyword(s):  
Individual Differences ◽  
Individual Identification ◽  
Imaging Data ◽  
Functional Connectome ◽  
Middle Range ◽  
Human Connectome Project ◽  
The Individual ◽  
And Behavior ◽  
Identification Analysis ◽  
The Brain

Abstract The functional connectome is highly distinctive in adults and adolescents, underlying individual differences in cognition and behavior. However, it remains unknown whether the individual uniqueness of the functional connectome is present in neonates, who are far from mature. Here, we utilized the multiband resting-state functional magnetic resonance imaging data of 40 healthy neonates from the Developing Human Connectome Project and a split-half analysis approach to characterize the uniqueness of the functional connectome in the neonatal brain. Through functional connectome-based individual identification analysis, we found that all the neonates were correctly identified, with the most discriminative regions predominantly confined to the higher-order cortices (e.g., prefrontal and parietal regions). The connectivities with the highest contributions to individual uniqueness were primarily located between different functional systems, and the short- (0–30 mm) and middle-range (30–60 mm) connectivities were more distinctive than the long-range (>60 mm) connectivities. Interestingly, we found that functional data with a scanning length longer than 3.5 min were able to capture the individual uniqueness in the functional connectome. Our results highlight that individual uniqueness is present in the functional connectome of neonates and provide insights into the brain mechanisms underlying individual differences in cognition and behavior later in life.

scholarly journals Deep-MEG: spatiotemporal CNN features and multiband ensemble classification for predicting the early signs of Alzheimer’s disease with magnetoencephalography

2021 ◽  
Author(s):  
Antonio Giovannetti ◽  
Gianluca Susi ◽  
Paola Casti ◽  
Arianna Mencattini ◽  
Sandra Pusil ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Brain Regions ◽  
Ensemble Classification ◽  
The Novel ◽  
Ensemble Classifiers ◽  
Deep Convolutional Neural Networks ◽  
Early Signs ◽  
Data Representations ◽  
The Brain

AbstractIn this paper, we present the novel Deep-MEG approach in which image-based representations of magnetoencephalography (MEG) data are combined with ensemble classifiers based on deep convolutional neural networks. For the scope of predicting the early signs of Alzheimer’s disease (AD), functional connectivity (FC) measures between the brain bio-magnetic signals originated from spatially separated brain regions are used as MEG data representations for the analysis. After stacking the FC indicators relative to different frequency bands into multiple images, a deep transfer learning model is used to extract different sets of deep features and to derive improved classification ensembles. The proposed Deep-MEG architectures were tested on a set of resting-state MEG recordings and their corresponding magnetic resonance imaging scans, from a longitudinal study involving 87 subjects. Accuracy values of 89% and 87% were obtained, respectively, for the early prediction of AD conversion in a sample of 54 mild cognitive impairment subjects and in a sample of 87 subjects, including 33 healthy controls. These results indicate that the proposed Deep-MEG approach is a powerful tool for detecting early alterations in the spectral–temporal connectivity profiles and in their spatial relationships.

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