Abstract
Alzheimer's disease (AD) is a neurodegenerative disease characterized by progressive loss of memory. Impairment of working memory was typically observed in AD. The concept of brain functional connectivity plays an important role in neuroscience as a useful tool to understand the organized behavior of brain. Hence, the purpose of this study is to investigate the possible mechanism of working memory deficits in AD from a new perspective of functional connectivity. Rats were randomly divided into 2 groups: Aβ injection group (Aβ1-42-induced toxicity rat model) and control group. Multi-channel local field potentials (LFPs) were obtained from rat prefrontal cortex with implanted microelectrode arrays while the rats performed a Y-maze working memory task. The short-time Fourier transform was utilized to analyze the power changes in LFPs and sub-bands (in particular theta and low gamma bands) were extracted via band filtering. Then the Directed transfer function (DTF) method was applied to calculate the functional connections among LFPs. From the DTF calculation, the causal networks in the sub-bands were identified. DTFmean (mean of connectivity matrix elements) was used to quantify connection strength as well as global efficiency (Eglob) was calculated to quantitatively describe the efficient of information transfer in the network. Our results showed that both connection strength and efficient of information transfer increased during the working memory task in the control group; by contrast, there was no significantly change in the Aβ injection group. These findings could lead to improve the understanding of the mechanism of working memory deficits in AD.
Keywords: Alzheimer's disease, directed transfer function, functional connectivity, global efficiency, local field potentials, working memory.
Current Alzheimer Research
Title:Functional Connectivity in a Rat Model of Alzheimer's Disease During a Working Memory Task
Volume: 11 Issue: 10
Author(s): Tiaotiao Liu, Wenwen Bai, Hu Yi, Tao Tan, Jing Wei, Ju Wang and Xin Tian
Affiliation:
Keywords: Alzheimer's disease, directed transfer function, functional connectivity, global efficiency, local field potentials, working memory.
Abstract: Alzheimer's disease (AD) is a neurodegenerative disease characterized by progressive loss of memory. Impairment of working memory was typically observed in AD. The concept of brain functional connectivity plays an important role in neuroscience as a useful tool to understand the organized behavior of brain. Hence, the purpose of this study is to investigate the possible mechanism of working memory deficits in AD from a new perspective of functional connectivity. Rats were randomly divided into 2 groups: Aβ injection group (Aβ1-42-induced toxicity rat model) and control group. Multi-channel local field potentials (LFPs) were obtained from rat prefrontal cortex with implanted microelectrode arrays while the rats performed a Y-maze working memory task. The short-time Fourier transform was utilized to analyze the power changes in LFPs and sub-bands (in particular theta and low gamma bands) were extracted via band filtering. Then the Directed transfer function (DTF) method was applied to calculate the functional connections among LFPs. From the DTF calculation, the causal networks in the sub-bands were identified. DTFmean (mean of connectivity matrix elements) was used to quantify connection strength as well as global efficiency (Eglob) was calculated to quantitatively describe the efficient of information transfer in the network. Our results showed that both connection strength and efficient of information transfer increased during the working memory task in the control group; by contrast, there was no significantly change in the Aβ injection group. These findings could lead to improve the understanding of the mechanism of working memory deficits in AD.
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Cite this article as:
Liu Tiaotiao, Bai Wenwen, Yi Hu, Tan Tao, Wei Jing, Wang Ju and Tian Xin, Functional Connectivity in a Rat Model of Alzheimer's Disease During a Working Memory Task, Current Alzheimer Research 2014; 11 (10) . https://dx.doi.org/10.2174/1567205011666141107125912
DOI https://dx.doi.org/10.2174/1567205011666141107125912 |
Print ISSN 1567-2050 |
Publisher Name Bentham Science Publisher |
Online ISSN 1875-5828 |
Call for Papers in Thematic Issues
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Aims and Scope: Introduction: Alzheimer's disease (AD) poses a significant global health challenge, with an increasing prevalence that demands concerted efforts to advance our understanding and strategies for prevention, diagnosis, treatment, and rehabilitation. This thematic issue aims to bring together cutting-edge research and innovative approaches from multidisciplinary perspectives to address ...read more
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Deep Learning for Advancing Alzheimer's Disease Research
Alzheimer's disease (AD) poses a significant global health challenge, with an increasing number of individuals affected yearly. Deep learning, a subfield of artificial intelligence, has shown immense potential in various domains, including healthcare. This thematic issue of Current Alzheimer Research explores the application of deep learning techniques in advancing our ...read more
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Dementia affects 18 million people worldwide. Dementia is a syndrome of symptoms caused by brain disease, usually chronic or progressive, clinically characterized by multiple impairments of higher cortical functions such as memory, thinking, orientation, and learning. In addition, in the course of dementia, cognitive deficits are observed, which often hinder ...read more
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