scholarly journals A high-resolution brain proteome map uncovers the Inter-hemispheric laterality & Inter-regional protein expression changes

2020 ◽  
Author(s):  
Sanjeeva Srivast ◽  
Deeptarup Biswas ◽  
Sanjyot Shenoy ◽  
Chetanya Chetanya ◽  
Arunachalam Athithyan ◽  
...  
Keyword(s):  
High Resolution ◽  
Brain Regions ◽  
Protein Markers ◽  
Hemispheric Differences ◽  
Brain Disorder ◽  
High Resolution Data ◽  
Brain Proteome ◽  
Proteome Database ◽  
Left And Right ◽  
The Brain

Abstract The human brain has always been a black box full of mysteries. Here we present one of the most comprehensive proteomics investigation of the brain, focusing on inter-hemispheric differences. An extensive mass spectrometry-based analysis of 19 brain regions from both left and right hemispheres measured more than 3300 proteins and 38700 peptides. This high-resolution data provides a comprehensive coverage of experimentally measured (non-hypothetical) proteins across various regions to characterize inter-hemispheric differences. We also tried to understand the brain proteins in terms of synapse analysis. The study has attempted to investigate the expression of neuroanatomical allied region and brain disorder protein markers in 19 region and sub-region of brain. Furthermore, we have developed the most comprehensive Brain Proteome Database, based on our, and publicly available curated data representing more than 9000 proteins (with isoforms) and around 90000 peptides at www.brainprot.org, which can aid in understanding the human brain’s complexity.

scholarly journals Synaptic Plasticity and its Modulation by Alcohol

2020 ◽  
Vol 6 (1) ◽  
pp. 103-111 ◽  
Author(s):  
Yosef Avchalumov ◽  
Chitra D. Mandyam
Keyword(s):  
Synaptic Plasticity ◽  
Learning And Memory ◽  
Dorsal Striatum ◽  
Long Term Potentiation ◽  
Brain Regions ◽  
Public Health Issue ◽  
Cellular Mechanisms ◽  
Brain Disorder ◽  
The Brain

Alcohol is one of the oldest pharmacological agents used for its sedative/hypnotic effects, and alcohol abuse and alcohol use disorder (AUD) continues to be major public health issue. AUD is strongly indicated to be a brain disorder, and the molecular and cellular mechanism/s by which alcohol produces its effects in the brain are only now beginning to be understood. In the brain, synaptic plasticity or strengthening or weakening of synapses, can be enhanced or reduced by a variety of stimulation paradigms. Synaptic plasticity is thought to be responsible for important processes involved in the cellular mechanisms of learning and memory. Long-term potentiation (LTP) is a form of synaptic plasticity, and occurs via N-methyl-D-aspartate type glutamate receptor (NMDAR or GluN) dependent and independent mechanisms. In particular, NMDARs are a major target of alcohol, and are implicated in different types of learning and memory. Therefore, understanding the effect of alcohol on synaptic plasticity and transmission mediated by glutamatergic signaling is becoming important, and this will help us understand the significant contribution of the glutamatergic system in AUD. In the first part of this review, we will briefly discuss the mechanisms underlying long term synaptic plasticity in the dorsal striatum, neocortex and the hippocampus. In the second part we will discuss how alcohol (ethanol, EtOH) can modulate long term synaptic plasticity in these three brain regions, mainly from neurophysiological and electrophysiological studies. Taken together, understanding the mechanism(s) underlying alcohol induced changes in brain function may lead to the development of more effective therapeutic agents to reduce AUDs.

Interhemispheric compensation: A hypothesis of TMS-induced effects on language-related areas

2008 ◽  
Vol 23 (4) ◽  
pp. 281-288 ◽  
Author(s):  
Jamila Andoh ◽  
Jean-Luc Martinot
Keyword(s):  
Language Processing ◽  
Repetitive Transcranial Magnetic Stimulation ◽  
Brain Regions ◽  
Auditory Hallucinations ◽  
Language Recovery ◽  
Functional Organisation ◽  
Virtual Lesion ◽  
Left And Right ◽  
Local Interference ◽  
The Brain

AbstractRepetitive transcranial magnetic stimulation (rTMS) applied over brain regions responsible for language processing is used to curtail potentially auditory hallucinations in schizophrenia patients and to investigate the functional organisation of language-related areas. Variability of effects is, however, marked across studies and between subjects. Furthermore, the mechanisms of action of rTMS are poorly understood.Here, we reviewed different factors related to the structural and functional organisation of the brain that might influence rTMS-induced effects. Then, by analogy with aphasia studies, and the plastic-adaptive changes in both the left and right hemispheres following aphasia recovery, a hypothesis is proposed about rTMS mechanisms over language-related areas (e.g. Wernicke, Broca). We proposed that the local interference induced by rTMS in language-related areas might be analogous to aphasic stroke and might lead to a functional reorganisation in areas connected to the virtual lesion for language recovery.

Connectomics: a need for comparative studies

e-Neuroforum ◽  
2016 ◽  
Vol 22 (3) ◽  
Author(s):  
Gilles Laurent ◽  
G. Laurent
Keyword(s):  
High Resolution ◽  
Comparative Studies ◽  
Brain Area ◽  
Theoretical Understanding ◽  
High Resolution Data ◽  
The Brain ◽  
Resolution Data ◽  
Single Synapse

AbstractConnectomics, the study of circuit architecture, has the potential to reveal the connectivity of any brain or brain area with single-synapse resolution. This is extremely exciting but at the same time quite daunting. The exciting part is obvious. The daunting part is less so, and relates to the challenge of extracting principles from overwhelming masses of high-resolution data. You might say that it is a nice problem to have, and I will agree. What I will argue here is that, if our goal is to derive from such data a general and theoretical understanding of the brain, wemust nowmore than ever take advantage of comparative approaches.

scholarly journals Early Detection of Alzheimer’s Disease: Detecting Asymmetries with a Return Random Walk Link Predictor

Entropy ◽  
2020 ◽  
Vol 22 (4) ◽  
pp. 465
Author(s):  
Manuel Curado ◽  
Francisco Escolano ◽  
Miguel A. Lozano ◽  
Edwin R. Hancock
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Random Walk ◽  
Early Stage ◽  
Directed Graphs ◽  
Brain Regions ◽  
Functional Magnetic Resonance ◽  
Left And Right ◽  
The Brain ◽  
Analyze Data

Alzheimer’s disease has been extensively studied using undirected graphs to represent the correlations of BOLD signals in different anatomical regions through functional magnetic resonance imaging (fMRI). However, there has been relatively little analysis of this kind of data using directed graphs, which potentially offer the potential to capture asymmetries in the interactions between different anatomical brain regions. The detection of these asymmetries is relevant to detect the disease in an early stage. For this reason, in this paper, we analyze data extracted from fMRI images using the net4Lap algorithm to infer a directed graph from the available BOLD signals, and then seek to determine asymmetries between the left and right hemispheres of the brain using a directed version of the Return Random Walk (RRW). Experimental evaluation of this method reveals that it leads to the identification of anatomical brain regions known to be implicated in the early development of Alzheimer’s disease in clinical studies.

scholarly journals The topology of higher-order complexes associated with brain hubs in human connectomes

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Miroslav Andjelković ◽  
Bosiljka Tadić ◽  
Roderick Melnik
Keyword(s):  
Complex Dynamics ◽  
Simplicial Complexes ◽  
Brain Regions ◽  
Higher Order ◽  
Core Networks ◽  
Right Cerebral Hemisphere ◽  
Left And Right ◽  
Order Complexes ◽  
The Brain

Abstract Higher-order connectivity in complex systems described by simplexes of different orders provides a geometry for simplex-based dynamical variables and interactions. Simplicial complexes that constitute a functional geometry of the human connectome can be crucial for the brain complex dynamics. In this context, the best-connected brain areas, designated as hub nodes, play a central role in supporting integrated brain function. Here, we study the structure of simplicial complexes attached to eight global hubs in the female and male connectomes and identify the core networks among the affected brain regions. These eight hubs (Putamen, Caudate, Hippocampus and Thalamus-Proper in the left and right cerebral hemisphere) are the highest-ranking according to their topological dimension, defined as the number of simplexes of all orders in which the node participates. Furthermore, we analyse the weight-dependent heterogeneity of simplexes. We demonstrate changes in the structure of identified core networks and topological entropy when the threshold weight is gradually increased. These results highlight the role of higher-order interactions in human brain networks and provide additional evidence for (dis)similarity between the female and male connectomes.

scholarly journals Neuronal connectivity, regional differentiation, and brain damage in humans

1999 ◽  
Vol 22 (5) ◽  
pp. 854-855
Author(s):  
Dahlia W. Zaidel
Keyword(s):  
Cognitive Psychology ◽  
Brain Damage ◽  
Human Behavior ◽  
Cognitive Neuroscience ◽  
Brain Regions ◽  
Cerebral Hemispheres ◽  
Regional Differentiation ◽  
Neuronal Connectivity ◽  
Left And Right ◽  
The Brain

When circumscribed brain regions are damaged in humans, highly specific impairments in language, memory, problem solving, and cognition are observed. Neurosurgery such as “split brain” or hemispherectomy, for example, has shown that encompassing regions, the left and right cerebral hemispheres, each control human behavior in unique ways. Observations stretching over 100 years of patients with unilateral focal brain damage have revealed, without the theoretical benefits of “cognitive neuroscience” or “cognitive psychology,” that human behavior is indeed controlled by the brain and its neurons.

scholarly journals Brain CHID1 Expression Correlates with NRGN and CALB1 in Healthy Subjects and AD Patients

Cells ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 882
Author(s):  
Paola Castrogiovanni ◽  
Cristina Sanfilippo ◽  
Rosa Imbesi ◽  
Grazia Maugeri ◽  
Debora Lo Furno ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Calcium Binding ◽  
Meta Analysis ◽  
Inverse Correlation ◽  
Brain Regions ◽  
Brain Disorder ◽  
Expression Levels ◽  
Healthy Control ◽  
The Brain

Alzheimer’s disease is a progressive, devastating, and irreversible brain disorder that, day by day, destroys memory skills and social behavior. Despite this, the number of known genes suitable for discriminating between AD patients is insufficient. Among the genes potentially involved in the development of AD, there are the chitinase-like proteins (CLPs) CHI3L1, CHI3L2, and CHID1. The genes of the first two have been extensively investigated while, on the contrary, little information is available on CHID1. In this manuscript, we conducted transcriptome meta-analysis on an extensive sample of brains of healthy control subjects (n = 1849) (NDHC) and brains of AD patients (n = 1170) in order to demonstrate CHID1 involvement. Our analysis revealed an inverse correlation between the brain CHID1 expression levels and the age of NDHC subjects. Significant differences were highlighted comparing CHID1 expression of NDHC subjects and AD patients. Exclusive in AD patients, the CHID1 expression levels were correlated positively to calcium-binding adapter molecule 1 (IBA1) levels. Furthermore, both in NDHC and in AD patient’s brains, the CHID1 expression levels were directly correlated with calbindin 1 (CALB1) and neurogranin (NRGN). According to brain regions, correlation differences were shown between the expression levels of CHID1 in prefrontal, frontal, occipital, cerebellum, temporal, and limbic system. Sex-related differences were only highlighted in NDHC. CHID1 represents a new chitinase potentially involved in the principal processes underlying Alzheimer’s disease.

scholarly journals A High-Resolution In Vivo Atlas of the Human Brain’s Benzodiazepine Binding Site of GABAA Receptors

2020 ◽  
Author(s):  
Martin Nørgaard ◽  
Vincent Beliveau ◽  
Melanie Ganz ◽  
Claus Svarer ◽  
Lars H Pinborg ◽  
...  
Keyword(s):  
High Resolution ◽  
Human Brain ◽  
Mrna Expression ◽  
Brain Regions ◽  
Mrna Levels ◽  
Gamma Aminobutyric Acid ◽  
Healthy Human ◽  
Brain Functions ◽  
The Brain

ABSTRACTGamma-aminobutyric acid (GABA) is the main inhibitory neurotransmitter in the human brain and plays a key role in several brain functions and neuropsychiatric disorders such as anxiety, epilepsy, and depression. The binding of benzodiazepines to the benzodiazepine receptor sites (BZR) located on GABAA receptors (GABAARs) potentiates the inhibitory effect of GABA leading to the anxiolytic, anticonvulsant and sedative effects used for treatment of those disorders. However, the function of GABAARs and the expression of BZR protein is determined by the GABAAR subunit stoichiometry (19 genes coding for individual subunits), and it remains to be established how the pentamer composition varies between brain regions and individuals.Here, we present a quantitative high-resolution in vivo atlas of the human brain BZRs, generated on the basis of [11C]flumazenil Positron Emission Tomography (PET) data. Next, based on autoradiography data, we transform the PET-generated atlas from binding values into BZR protein density. Finally, we examine the brain regional association with mRNA expression for the 19 subunits in the GABAAR, including an estimation of the minimally required expression of mRNA levels for each subunit to translate into BZR protein.This represents the first publicly available quantitative high-resolution in vivo atlas of the spatial distribution of BZR densities in the healthy human brain. The atlas provides a unique neuroscientific tool as well as novel insights into the association between mRNA expression for individual subunits in the GABAAR and the BZR density at each location in the brain.

scholarly journals Proteomics reveals profound metabolic changes in the alcohol use disorder brain

2018 ◽  
Author(s):  
Charmaine Enculescu ◽  
Edward D. Kerr ◽  
K. Y. Benjamin Yeo ◽  
Peter R. Dodd ◽  
Gerhard Schenk ◽  
...  
Keyword(s):  
Alcohol Use ◽  
Alcohol Use Disorder ◽  
Brain Regions ◽  
Substantial Effect ◽  
Biochemical Processes ◽  
Data Independent Acquisition ◽  
Metabolic Adaptations ◽  
Brain Proteome ◽  
Acetate Utilization ◽  
The Brain

AbstractChanges in brain metabolism are a hallmark of Alcohol Use Disorder (AUD). Determining how AUD changes the brain proteome is critical for understanding the effects of alcohol consumption on biochemical processes in the brain. We used data-independent acquisition mass spectrometry proteomics to study differences in the abundance of proteins associated with AUD in pre-frontal lobe and motor cortex from autopsy brain. AUD had a substantial effect on the overall brain proteome exceeding the inherent differences between brain regions. Proteins associated with glycolysis, trafficking, the cytoskeleton, and excitotoxicity were altered in abundance in AUD. We observed extensive changes in the abundance of key metabolic enzymes, consistent with a switch from glucose to acetate utilization in the AUD brain. We propose that metabolic adaptations allowing efficient acetate utilization contribute to ethanol dependence in AUD.

scholarly journals EEGG: An Analytic Brain-computer Interface Algorithm

2021 ◽  
Author(s):  
Gang Liu ◽  
Jing Wang
Keyword(s):  
Brain Activity ◽  
Brain Regions ◽  
Classification Performance ◽  
Data Driven ◽  
Computer Interface ◽  
Eeg Signals ◽  
Eeg Data ◽  
Data Driven Approach ◽  
Left And Right ◽  
The Brain

<div><div> <p><a></a></p><div> <p><a></a><a><i>Objective. </i></a>Modeling the brain as a white box is vital for investigating the brain. However, the physical properties of the human brain are unclear. Therefore, BCI algorithms using EEG signals are generally a data-driven approach and generate a black- or gray-box model. This paper presents the first EEG-based BCI algorithm (EEGBCI using Gang neurons, EEGG) decomposing the brain into some simple components with physical meaning and integrating recognition and analysis of brain activity. </p> <p><i>Approach. </i>Independent and interactive components of neurons or brain regions can fully describe the brain. This paper constructed a relationship frame based on the independent and interactive compositions for intention recognition and analysis using a novel dendrite module of Gang neurons. A total of 4,906 EEG data of left- and right-hand motor imagery(MI) from 26 subjects were obtained from GigaDB. Firstly, this paper explored EEGG’s classification performance by cross-subject accuracy. Secondly, this paper transformed the trained EEGG model into a relation spectrum expressing independent and interactive components of brain regions. Then, the relation spectrum was verified using the known ERD/ERS phenomenon. Finally, this paper explored the previously unreachable further BCIbased analysis of the brain. </p> <p><i>Main results. </i>(1) EEGG was more robust than typical “CSP+” algorithms for the poorquality data. (2) The relation spectrum showed the known ERD/ERS phenomenon. (3) Interestingly, EEGG showed that interactive components between brain regions suppressed ERD/ERS effects on classification. This means that generating fine hand intention needs more centralized activation in the brain. </p> <p><i>Significance. </i>EEGG decomposed the biological EEG-intention system of this paper into the relation spectrum inheriting the Taylor series (<i>in analogy with the data-driven but human-readable Fourier transform and frequency spectrum</i>), which offers a novel frame for analysis of the brain.</p> </div> </div></div><div><p></p></div>

Sign in / Sign up

Export Citation Format

Share Document