scholarly journals A Study of the Brain Network Connectivity in Visual-Word Pairing Associative Learning and Episodic Memory Reactivating Task

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Mingxin Zhang ◽  
Feng Duan ◽  
Shan Wang ◽  
Kai Zhang ◽  
Xuyi Chen ◽  
...  
Keyword(s):  
Episodic Memory ◽  
Posterior Parietal Cortex ◽  
Parietal Lobe ◽  
Occipital Lobe ◽  
Brain Regions ◽  
Brain Network ◽  
Directed Network ◽  
Superior Parietal Lobule ◽  
Parietal Lobule ◽  
The Brain

Episodic memory allows a person to recall and mentally reexperience specific episodes from one’s personal past. Studies of episodic memory are of great significance for the diagnosis and the exploration of the mechanism of memory generation. Most of the current studies focus on certain brain regions and pay less attention to the interrelationship between multiple brain regions. To explore the interrelationship in the brain network, we use an open fMRI dataset to construct the brain functional connectivity and effective connectivity network. We establish a binary directed network of the memory when it is reactivated. The binary directed network shows that the occipital lobe and parietal lobe have the most causal connections. The number of edges starting from the superior parietal lobule is the highest, with 49 edges, and 31 of which are connected to the occipital cortex. This means that the interaction between the superior parietal lobule and the occipital lobe plays the most important role in episodic memory, and the superior parietal lobule plays a more causal role in causality. In addition, memory regions such as the precuneus and fusiform also have some edges. The results show that the posterior parietal cortex plays an important role of hub node in the episodic memory network. From the brain network model, more information can be obtained, which is conducive to exploring the brain’s changing pattern in the whole memory process.

Alice in Wonderland Syndrome: An Update of Present Data With A Special View to Body Position, Traumatic and Genetic Aspects

2020 ◽  
Author(s):  
Stefan Bittmann
Keyword(s):  
Depressive Disorders ◽  
Parietal Lobe ◽  
Body Position ◽  
Occipital Lobe ◽  
Brain Regions ◽  
Lewis Carroll ◽  
Temporoparietal Junction ◽  
Alice In Wonderland ◽  
First Time ◽  
The Brain

Alice in Wonderland Syndrome (AIWS) was named after the description of Lewis Carroll in his novel. In 1955, John Todd, a psychiatrist described this entity for the first time and results in a distortion of perception. Todd described it as „Alice's Adventures in Wonderland“ by Lewis Carroll. The author Carroll suffered from severe migraine attacks. Alice in Wonderland Syndrome is a disorienting condition of seizures affecting visual perception. AIWS is a neurological form of seizures influencing the brain, thereby causing a disturbed perception. Patients describe visual, auditory, and tactile hallucinations and disturbed perceptions. The causes of AIWS are still not known exactly. Cases of migraine, brain tumors, depression episodes, epilepsy, delirium, psychoactive drugs, ischemic stroke, depressive disorders, and EBV, mycoplasma, and malaria infections are correlating with AIWS like seizures. Often no EEG correlate is found. Neuroimaging studies reveal disturbances of brain regions including the temporoparietal junction, the temporal and occipital lobe as typical localization of the visual pathway. A decrease of perfusion of the visual pathways could induce these disturbances, especially in the temporal lobe in patients with AIWS. Other theories suggest distorted body illusions stem from the parietal lobe. The concrete origin of this mysterious syndrome is to date not clearly defined.

scholarly journals The Role of the Parietal Lobe in Visual Extinction Studied with Transcranial Magnetic Stimulation

2009 ◽  
Vol 21 (10) ◽  
pp. 1946-1955 ◽  
Author(s):  
Lorella Battelli ◽  
George A. Alvarez ◽  
Thomas Carlson ◽  
Alvaro Pascual-Leone
Keyword(s):  
Transcranial Magnetic Stimulation ◽  
Visual Tracking ◽  
Magnetic Stimulation ◽  
Posterior Parietal Cortex ◽  
Parietal Lobe ◽  
Repetitive Transcranial Magnetic Stimulation ◽  
Visual Fields ◽  
Brain Regions ◽  
Visual Extinction ◽  
Interhemispheric Competition

Interhemispheric competition between homologous areas in the human brain is believed to be involved in a wide variety of human behaviors from motor activity to visual perception and particularly attention. For example, patients with lesions in the posterior parietal cortex are unable to selectively track objects in the contralesional side of visual space when targets are simultaneously present in the ipsilesional visual field, a form of visual extinction. Visual extinction may arise due to an imbalance in the normal interhemispheric competition. To directly assess the issue of reciprocal inhibition, we used fMRI to localize those brain regions active during attention-based visual tracking and then applied low-frequency repetitive transcranial magnetic stimulation over identified areas in the left and right intraparietal sulcus to asses the behavioral effects on visual tracking. We induced a severe impairment in visual tracking that was selective for conditions of simultaneous tracking in both visual fields. Our data show that the parietal lobe is essential for visual tracking and that the two hemispheres compete for attentional resources during tracking. Our results provide a neuronal basis for visual extinction in patients with parietal lobe damage.

scholarly journals A Computational Network Control Theory Analysis of Depression Symptoms

2018 ◽  
Vol 1 ◽  
Author(s):  
Yoed N. Kenett ◽  
Roger E. Beaty ◽  
John D. Medaglia
Keyword(s):  
Control Theory ◽  
Diffusion Tensor ◽  
Brain Regions ◽  
Brain Network ◽  
Network Control ◽  
Depression Symptoms ◽  
Theory Approach ◽  
Imaging Data ◽  
The Brain ◽  
Subclinical Depression

AbstractRumination and impaired inhibition are considered core characteristics of depression. However, the neurocognitive mechanisms that contribute to these atypical cognitive processes remain unclear. To address this question, we apply a computational network control theory approach to structural brain imaging data acquired via diffusion tensor imaging in a large sample of participants, to examine how network control theory relates to individual differences in subclinical depression. Recent application of this theory at the neural level is built on a model of brain dynamics, which mathematically models patterns of inter-region activity propagated along the structure of an underlying network. The strength of this approach is its ability to characterize the potential role of each brain region in regulating whole-brain network function based on its anatomical fingerprint and a simplified model of node dynamics. We find that subclinical depression is negatively related to higher integration abilities in the right anterior insula, replicating and extending previous studies implicating atypical switching between the default mode and Executive Control Networks in depression. We also find that subclinical depression is related to the ability to “drive” the brain system into easy to reach neural states in several brain regions, including the bilateral lingual gyrus and lateral occipital gyrus. These findings highlight brain regions less known in their role in depression, and clarify their roles in driving the brain into different neural states related to depression symptoms.

scholarly journals A Graphlet-Based Topological Characterization of the Resting-State Network in Healthy People

2021 ◽  
Vol 15 ◽  
Author(s):  
Paolo Finotelli ◽  
Carlo Piccardi ◽  
Edie Miglio ◽  
Paolo Dulio
Keyword(s):  
Resting State ◽  
Brain Regions ◽  
Brain Network ◽  
Induced Subgraphs ◽  
Topological Characterization ◽  
Network Information ◽  
The Subject ◽  
Euclidean Distances ◽  
The Brain

In this paper, we propose a graphlet-based topological algorithm for the investigation of the brain network at resting state (RS). To this aim, we model the brain as a graph, where (labeled) nodes correspond to specific cerebral areas and links are weighted connections determined by the intensity of the functional magnetic resonance imaging (fMRI). Then, we select a number of working graphlets, namely, connected and non-isomorphic induced subgraphs. We compute, for each labeled node, its Graphlet Degree Vector (GDV), which allows us to associate a GDV matrix to each one of the 133 subjects of the considered sample, reporting how many times each node of the atlas “touches” the independent orbits defined by the graphlet set. We focus on the 56 independent columns (i.e., non-redundant orbits) of the GDV matrices. By aggregating their count all over the 133 subjects and then by sorting each column independently, we obtain a sorted node table, whose top-level entries highlight the nodes (i.e., brain regions) most frequently touching each of the 56 independent graphlet orbits. Then, by pairwise comparing the columns of the sorted node table in the top-k entries for various values of k, we identify sets of nodes that are consistently involved with high frequency in the 56 independent graphlet orbits all over the 133 subjects. It turns out that these sets consist of labeled nodes directly belonging to the default mode network (DMN) or strongly interacting with it at the RS, indicating that graphlet analysis provides a viable tool for the topological characterization of such brain regions. We finally provide a validation of the graphlet approach by testing its power in catching network differences. To this aim, we encode in a Graphlet Correlation Matrix (GCM) the network information associated with each subject then construct a subject-to-subject Graphlet Correlation Distance (GCD) matrix based on the Euclidean distances between all possible pairs of GCM. The analysis of the clusters induced by the GCD matrix shows a clear separation of the subjects in two groups, whose relationship with the subject characteristics is investigated.

Graph Theory-Based Brain Network Connectivity Analysis and Classification of Alzheimer’s Disease

2021 ◽  
Author(s):  
A. Thushara ◽  
C. Ushadevi Amma ◽  
Ansamma John
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Graph Theory ◽  
Neurodegenerative Disorder ◽  
Brain Networks ◽  
Network Connectivity ◽  
Brain Regions ◽  
Brain Network ◽  
Fiber Tracts ◽  
The Brain

Alzheimer’s Disease (AD) is basically a progressive neurodegenerative disorder associated with abnormal brain networks that affect millions of elderly people and degrades their quality of life. The abnormalities in brain networks are due to the disruption of White Matter (WM) fiber tracts that connect the brain regions. Diffusion-Weighted Imaging (DWI) captures the brain’s WM integrity. Here, the correlation betwixt the WM degeneration and also AD is investigated by utilizing graph theory as well as Machine Learning (ML) algorithms. By using the DW image obtained from Alzheimer’s Disease Neuroimaging Initiative (ADNI) database, the brain graph of each subject is constructed. The features extracted from the brain graph form the basis to differentiate between Mild Cognitive Impairment (MCI), Control Normal (CN) and AD subjects. Performance evaluation is done using binary and multiclass classification algorithms and obtained an accuracy that outperforms the current top-notch DWI-based studies.

First and Second Language Patterns of Brain Activation in Korean Layrngeal Contrasts

2008 ◽  
Vol 14 ◽  
pp. 1-19 ◽  
Author(s):  
Haeil Park ◽  
Gregory Iverson
Keyword(s):  
Second Language ◽  
Native Speakers ◽  
Occipital Lobe ◽  
Brain Regions ◽  
Second Language Speakers ◽  
Significant Difference ◽  
Native Speakers Of English ◽  
Specific Activities ◽  
The Right ◽  
The Brain

Abstract. This study aims to localize the brain regions involved in the apprehension of Korean laryngeal contrasts and to investigate whether the Internal Model advanced by Callan et al. (2004) extends to first versus second language perception of these unique three-way laryngeal distinctions. The results show that there is a significant difference in activation between native and second-language speakers, consistent with the findings of Callan et al. Specific activities unique to younger native speakers of Korean relative to native speakers of English were seen in the cuneus (occipital lobe) and the right middle frontal gyrus (Brodmann Area [BA] 10), areas of the brain associated with pitch perception. The current findings uphold Silva's (2006) conclusion that the laryngeal contrasts of Korean are increasingly distinguished less by VOT differences than by their effect on pitch in the following vowel. A subsequent experiment was conducted to establish whether more traditional, older native speakers of Korean who still make clear VOT distinctions also activate both the cuneus and BA 10 in the same task. Preliminary results indicate that they do not, whereas speakers with overlapping VOT distinctions do show intersecting activations in these areas, thus corroborating Silva's claim of emergent pitch sensitivity in the Korean laryngeal system.

scholarly journals Transient brain networks underlying interpersonal strategies during synchronized action

2020 ◽  
Author(s):  
Ole Adrian Heggli ◽  
Ivana Konvalinka ◽  
Joana Cabral ◽  
Elvira Brattico ◽  
Morten L Kringelbach ◽  
...  
Keyword(s):  
Computational Models ◽  
Brain Activity ◽  
Brain Regions ◽  
Brain Network ◽  
Human Interaction ◽  
Action Perception ◽  
Network Information ◽  
Mutual Adaptation ◽  
Underlying Mechanisms ◽  
The Brain

Abstract Interpersonal coordination is a core part of human interaction, and its underlying mechanisms have been extensively studied using social paradigms such as joint finger-tapping. Here, individual and dyadic differences have been found to yield a range of dyadic synchronization strategies, such as mutual adaptation, leading–leading, and leading–following behaviour, but the brain mechanisms that underlie these strategies remain poorly understood. To identify individual brain mechanisms underlying emergence of these minimal social interaction strategies, we contrasted EEG-recorded brain activity in two groups of musicians exhibiting the mutual adaptation and leading–leading strategies. We found that the individuals coordinating via mutual adaptation exhibited a more frequent occurrence of phase-locked activity within a transient action–perception-related brain network in the alpha range, as compared to the leading–leading group. Furthermore, we identified parietal and temporal brain regions that changed significantly in the directionality of their within-network information flow. Our results suggest that the stronger weight on extrinsic coupling observed in computational models of mutual adaptation as compared to leading–leading might be facilitated by a higher degree of action–perception network coupling in the brain.

The Posterior Parietal Cortex in Humans and Monkeys

Physiology ◽  
1997 ◽  
Vol 12 (4) ◽  
pp. 166-171 ◽  
Author(s):  
C Galletti ◽  
PP Battaglini ◽  
P Fattori
Keyword(s):  
Parietal Cortex ◽  
Posterior Parietal Cortex ◽  
Visual Space ◽  
Superior Parietal Lobule ◽  
Monkey Brain ◽  
Posterior Parietal ◽  
Parietal Lobule

The recently reported existence of neurons able to encode visual space in the superior parietal lobule of the monkey brain suggests that human and monkey superior parietal lobules are homologous structures.

Biochemical changes in the brain of hemiplegic migraine patients measured with 7 tesla 1H-MRS

Cephalalgia ◽  
2014 ◽  
Vol 34 (12) ◽  
pp. 959-967 ◽  
Author(s):  
R Zielman ◽  
WM Teeuwisse ◽  
F Bakels ◽  
J Van der Grond ◽  
A Webb ◽  
...  
Keyword(s):  
Occipital Lobe ◽  
Brain Regions ◽  
Biochemical Changes ◽  
High Spectral Resolution ◽  
7 Tesla ◽  
Healthy Controls ◽  
Hemiplegic Migraine ◽  
1H Mrs ◽  
Total N ◽  
The Brain

Aim The aim of this study was to assess biochemical changes in the brain of patients with hemiplegic migraine in between attacks. Methods Eighteen patients with hemiplegic migraine (M:F, 7:11; age 38 ± 14 years) of whom eight had a known familial hemiplegic migraine (FHM) mutation (five in the CACNA1A gene (FHM1), three in the ATP1A2 gene (FHM2)) and 19 age- and sex-matched healthy controls (M:F, 7:12; mean age 38 ±  12 years) were studied. We used single-voxel 7 tesla 1H-MRS (STEAM, TR/TM/TE = 2000/19/21 ms) to investigate four brain regions in between attacks: cerebellum, hypothalamus, occipital lobe, and pons. Results Patients with hemiplegic migraine showed a significantly lower total N-acetylaspartate/total creatine ratio (tNAA/tCre) in the cerebellum (median 0.73, range 0.59–1.03) than healthy controls (median 0.79, range (0.67–0.95); p = 0.02). In FHM1 patients with a CACNA1A mutation, the tNAA/tCre was lowest. Discussion We found a decreased cerebellar tNAA/tCre ratio that might serve as an early biomarker for neuronal dysfunction and/or loss. This is the first high-spectral resolution 7 tesla 1H-MRS study of interictal biochemical brain changes in hemiplegic migraine patients.

Gray matter blood flow change is unevenly distributed during moderate isocapnic hypoxia in humans

2008 ◽  
Vol 104 (1) ◽  
pp. 212-217 ◽  
Author(s):  
Andrew P. Binks ◽  
Vincent J. Cunningham ◽  
Lewis Adams ◽  
Robert B. Banzett
Keyword(s):  
Blood Flow ◽  
Nucleus Accumbens ◽  
Positron Emission Tomography Imaging ◽  
Occipital Lobe ◽  
Brain Regions ◽  
Functional Brain Imaging ◽  
Regions Of Interest ◽  
Breath Hold ◽  
Obstructive Sleep ◽  
The Brain

Hypoxia increases cerebral blood flow (CBF), but it is unknown whether this increase is uniform across all brain regions. We used H215O positron emission tomography imaging to measure absolute blood flow in 50 regions of interest across the human brain ( n = 5) during normoxia and moderate hypoxia. Pco2 was kept constant (∼44 Torr) throughout the study to avoid decreases in CBF associated with the hypocapnia that normally occurs with hypoxia. Breathing was controlled by mechanical ventilation. During hypoxia (inspired Po2 = 70 Torr), mean end-tidal Po2 fell to 45 ± 6.3 Torr (means ± SD). Mean global CBF increased from normoxic levels of 0.39 ± 0.13 to 0.45 ± 0.13 ml/g during hypoxia. Increases in regional CBF were not uniform and ranged from 9.9 ± 8.6% in the occipital lobe to 28.9 ± 10.3% in the nucleus accumbens. Regions of interest that were better perfused during normoxia generally showed a greater regional CBF response. Phylogenetically older regions of the brain tended to show larger vascular responses to hypoxia than evolutionary younger regions, e.g., the putamen, brain stem, thalamus, caudate nucleus, nucleus accumbens, and pallidum received greater than average increases in blood flow, while cortical regions generally received below average increases. The heterogeneous blood flow distribution during hypoxia may serve to protect regions of the brain with essential homeostatic roles. This may be relevant to conditions such as altitude, breath-hold diving, and obstructive sleep apnea, and may have implications for functional brain imaging studies that involve hypoxia.

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