Brain Functional and Structural Connectivity and Cognition

Topic Information

Dear Colleagues,

Cognitive neuroscience has been impacted by the recent approach to structure–function relationships—a network-based approach, in which the product of structurally and functionally interconnected brain areas is the basis for higher brain functions such as attention, memory, language, emotion, or executive function. A large-scale distributed network integrating and interacting with relatively segregated and local networks is recognized as one of the principles for human information processing. The impaired functional segregation and integration of network organization may account for some cognitive and behavioral disorders.

Since the early 1990s, functional magnetic resonance imaging (fMRI) has become one of the most important tools in studies of the neuroanatomy of cognitive processes. Resting-state fMRI also provides measures regarding the balance between the segregated and integrated network architecture of functional connectivity. In addition, diffusion-weighted MRI and direct electrical brain stimulation have provided empirical findings demonstrating the importance of anatomical connectivity through white matter in multiple domains of cognition.

Our aim is for this Special Issue to present reviews or original articles that report recent findings in our understanding of functional and structural brain connectivity involved in a variety of cognitive functions and their impairments.

Prof. Dr. Shuhei Yamaguchi
Prof. Dr. Keiichi Onoda
Topic Editors

Keywords

Participating Journals

Journal Name	Impact Factor	CiteScore	Launched Year	First Decision (median)	APC
Life life	3.2	2.7	2011	17.5 Days	CHF 2600

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Published Papers (5 papers)

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22 pages, 422 KiB  

Open AccessReview

Overview of (f)MRI Studies of Cognitive Aging for Non-Experts: Looking through the Lens of Neuroimaging

by Toshikazu Kawagoe

Life 2022, 12(3), 416; https://doi.org/10.3390/life12030416 - 12 Mar 2022

Cited by 3 | Viewed by 2203

Abstract

This special issue concerning Brain Functional and Structural Connectivity and Cognition aims to expand our understanding of brain connectivity. Herein, I review related topics including the principle and concepts of functional MRI, brain activation, and functional/structural connectivity in aging for uninitiated readers. Visuospatial [...] Read more.

This special issue concerning Brain Functional and Structural Connectivity and Cognition aims to expand our understanding of brain connectivity. Herein, I review related topics including the principle and concepts of functional MRI, brain activation, and functional/structural connectivity in aging for uninitiated readers. Visuospatial attention, one of the well-studied functions in aging, is discussed from the perspective of neuroimaging. Full article

(This article belongs to the Topic Brain Functional and Structural Connectivity and Cognition)

20 pages, 7018 KiB  

Open AccessArticle

sEMG-Based Motion Recognition of Upper Limb Rehabilitation Using the Improved Yolo-v4 Algorithm

by Dongdong Bu, Shuxiang Guo and He Li

Life 2022, 12(1), 64; https://doi.org/10.3390/life12010064 - 03 Jan 2022

Cited by 11 | Viewed by 2351

Abstract

The surface electromyography (sEMG) signal is widely used as a control source of the upper limb exoskeleton rehabilitation robot. However, the traditional way of controlling the exoskeleton robot by the sEMG signal requires one to specially extract and calculate for complex sEMG features. [...] Read more.

The surface electromyography (sEMG) signal is widely used as a control source of the upper limb exoskeleton rehabilitation robot. However, the traditional way of controlling the exoskeleton robot by the sEMG signal requires one to specially extract and calculate for complex sEMG features. Moreover, due to the huge amount of calculation and individualized difference, the real-time control of the exoskeleton robot cannot be realized. Therefore, this paper proposes a novel method using an improved detection algorithm to recognize limb joint motion and detect joint angle based on sEMG images, aiming to obtain a high-security and fast-processing action recognition strategy. In this paper, MobileNetV2 combined the Ghost module as the feature extraction network to obtain the pretraining model. Then, the target detection network Yolo-V4 was used to estimate the six movement categories of the upper limb joints and to predict the joint movement angles. The experimental results showed that the proposed motion recognition methods were available. Every 100 pictures can be accurately identified in approximately 78 pictures, and the processing speed of every single picture on the PC side was 17.97 ms. For the train data, the mAP@0.5 could reach 82.3%, and mAP@0.5–0.95 could reach 0.42; for the verification data, the average recognition accuracy could reach 80.7%. Full article

(This article belongs to the Topic Brain Functional and Structural Connectivity and Cognition)

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15 pages, 1312 KiB  

Open AccessArticle

Elevated Systemic Inflammation Is Associated with Reduced Corticolimbic White Matter Integrity in Depression

by MacGregor Thomas, Jonathan Savitz, Ye Zhang, Kaiping Burrows, Ryan Smith, Leandra Figueroa-Hall, Rayus Kuplicki, Sahib S. Khalsa, Yasuyuki Taki, Tracy Kent Teague, Michael R. Irwin, Fang-Cheng Yeh, Martin P. Paulus, Haixia Zheng and on behalf of Tulsa 1000 Investigators

Life 2022, 12(1), 43; https://doi.org/10.3390/life12010043 - 28 Dec 2021

Cited by 7 | Viewed by 3133

Abstract

(1) Background: Growing evidence indicates that inflammation can induce neural circuit dysfunction and plays a vital role in the pathogenesis of major depressive disorder (MDD). Nevertheless, whether inflammation affects the integrity of white matter pathways is only beginning to be explored. (2) Methods: [...] Read more.

(1) Background: Growing evidence indicates that inflammation can induce neural circuit dysfunction and plays a vital role in the pathogenesis of major depressive disorder (MDD). Nevertheless, whether inflammation affects the integrity of white matter pathways is only beginning to be explored. (2) Methods: We computed quantitative anisotropy (QA) from diffusion magnetic resonance imaging as an index of white matter integrity and regressed QA on C-reactive protein (CRP), controlling for age, sex, and BMI, in 176 participants with MDD. (3) Results: The QA values of several white matter tracts were negatively correlated with CRP concentration (standardized beta coefficient = −0.22, 95%CI = −0.38–−0.06, FDR < 0.05). These tracts included the bilateral cortico-striatal tracts, thalamic radiations, inferior longitudinal fasciculi, corpus callosum (the forceps minor portion and the tapetum portion), cingulum bundles, and the left superior longitudinal fasciculus III. Importantly, the association remained robust after regressing up to twelve potential confounders. The bilateral fornix and a small portion of the thalamic radiation showed a positive association with CRP levels, but these associations did not remain significant after adjusting for confounders. (4) Conclusions: Peripheral inflammation may contribute to the etiology of MDD by impacting the microstructural integrity of brain corticolimbic white matter pathways. Full article

(This article belongs to the Topic Brain Functional and Structural Connectivity and Cognition)

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10 pages, 1988 KiB  

Open AccessArticle

Multiscale Entropy of Resting-State Functional Magnetic Resonance Imaging Differentiates Progressive Supranuclear Palsy and Multiple System Atrophy

by Katsuhiko Kadota, Keiichi Onoda, Satoshi Abe, Chizuko Hamada, Shingo Mitaki, Hiroaki Oguro, Atsushi Nagai, Hajime Kitagaki and Shuhei Yamaguchi

Life 2021, 11(12), 1411; https://doi.org/10.3390/life11121411 - 16 Dec 2021

Viewed by 2057

Abstract

Distinguishing progressive supranuclear palsy (PSP) from multiple system atrophy (MSA) in the early clinical stages is challenging; few sensitive and specific biomarkers are available for their differential diagnosis. Resting-state functional magnetic resonance imaging (rs-fMRI) is used to study the fluctuations in blood oxygen [...] Read more.

Distinguishing progressive supranuclear palsy (PSP) from multiple system atrophy (MSA) in the early clinical stages is challenging; few sensitive and specific biomarkers are available for their differential diagnosis. Resting-state functional magnetic resonance imaging (rs-fMRI) is used to study the fluctuations in blood oxygen level-dependent (BOLD) signals at rest, which provides evidence for aberrant brain functional networks in neurodegenerative diseases. We aimed to examine whether rs-fMRI data could differentiate between PSP and MSA via a multiscale entropy (MSE) analysis of BOLD signals, which estimates the complexity of temporal fluctuations in brain activity. We recruited 14 and 18 patients with PSP and MSA, respectively, who underwent neuropsychological tests and rs-fMRI. PSP patients demonstrated greater cognitive function impairments, particularly in the frontal executive function. The bilateral prefrontal cortex revealed lower entropy BOLD signal values in multiple time scales for PSP, compared to the values observed in MSA patients; however, the functional connectivity of the representative brain networks was comparable between the diseases. The reduced complexity of BOLD signals in the prefrontal cortex was associated with frontal dysfunction. Thus, an MSE analysis of rs-fMRI could differentiate between PSP and MSA, and the reduced complexity of BOLD signals could be associated with cognitive impairment. Full article

(This article belongs to the Topic Brain Functional and Structural Connectivity and Cognition)

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19 pages, 7593 KiB  

Open AccessArticle

A Mirror Bilateral Neuro-Rehabilitation Robot System with the sEMG-Based Real-Time Patient Active Participant Assessment

by Ziyi Yang, Shuxiang Guo, Hideyuki Hirata and Masahiko Kawanishi

Life 2021, 11(12), 1290; https://doi.org/10.3390/life11121290 - 24 Nov 2021

Cited by 12 | Viewed by 2440

Abstract

In this paper, a novel mirror visual feedback-based (MVF) bilateral neurorehabilitation system with surface electromyography (sEMG)-based patient active force assessment was proposed for upper limb motor recovery and improvement of limb inter-coordination. A mirror visual feedback-based human–robot interface was designed to facilitate the [...] Read more.

In this paper, a novel mirror visual feedback-based (MVF) bilateral neurorehabilitation system with surface electromyography (sEMG)-based patient active force assessment was proposed for upper limb motor recovery and improvement of limb inter-coordination. A mirror visual feedback-based human–robot interface was designed to facilitate the bilateral isometric force output training task. To achieve patient active participant assessment, an sEMG signals-based elbow joint isometric force estimation method was implemented into the proposed system for real-time affected side force assessment and participation evaluation. To assist the affected side limb efficiently and precisely, a mirror bilateral control framework was presented for bilateral limb coordination. Preliminary experiments were conducted to evaluate the estimation accuracy of force estimation method and force tracking accuracy of system performance. The experimental results show the proposed force estimation method can efficiently calculate the elbow joint force in real-time, and the affected side limb of patients can be assisted to track output force of the non-paretic side limb for better limb coordination by the proposed bilateral rehabilitation system. Full article

(This article belongs to the Topic Brain Functional and Structural Connectivity and Cognition)

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