Plasticity of large-scale neural connectivity following working memory training

工作记忆训练后大规模神经连接的可塑性

基本信息

批准号：
315012713
负责人：
Professorin Dr. Kathrin Koch
金额：
--
依托单位：
Klinik und Poliklinik für Nuklearmedizin
依托单位国家：
德国
项目类别：
Research Grants
财政年份：
2016
资助国家：
德国
起止时间：
2015-12-31 至 2019-12-31
项目状态：
已结题

来源：
https://gepris.dfg.de/gepris/projekt/315012713?language=en
关键词：
Plasticity large scale neural connectivity

项目摘要

In an ageing society techniques to preserve and improve cognitive function are gaining increasing importance. Approaches such as working memory (WM) training were found to improve processing capacities. In neuroimaging studies, this improvement was associated with alterations in amplitude of regional brain signal, while changes in interaction, or connectivity, between brain regions remain unclear. Considering increasing evidence that the human brain represents a dynamic system of neural networks, there is a need for development of connectivity-based markers of neural plasticity. In the proposed study we will investigate neuronal substrates of training-induced cognitive improvement at the level of large-scale brain connectivity. Given a variety of mechanisms underlying neural plasticity, we will apply a combination of neuroimaging techniques such as fMRI, PET, and DTI in a group of middle-aged healthy participants. Using these modalities, functional, metabolic, and structural connectivity will be measured. Experimental subjects will undergo a systematic WM training, followed by a comparison with an active control group. Simultaneous acquisition of MRI and fluorodeoxyglucose PET data on a hybrid PET/MR system will take place before and after training. An extensive cognitive test battery will be administered at the same two time points, as well as at 3 and 12 months follow-up. We hypothesize an increase in connectivity indices of the default mode and central executive networks following training. However, given the distinct temporal dynamics and energy costs, different forms of training-induced neuroplasticity are expected to be differently related to cognitive gains in time. Specifically, we hypothesize that increase in network structural and metabolic connectivity predicts long-term (12 months after training) near-transfer effects with higher accuracy than does functional connectivity. Beside neurobiological relevance, results of the proposed study will contribute to the development of cognitive interventions against age- and disease-related cognitive deficits.

在衰老的社会技术中，维护和改善认知功能的技术正在越来越重要。发现工作记忆（WM）训练等方法可提高处理能力。在神经影像研究中，这种改善与区域脑信号振幅的改变有关，而大脑区域之间相互作用或连通性的变化仍然不清楚。考虑到越来越多的证据表明人脑代表了神经网络的动态系统，需要开发基于连通性的神经可塑性标记。在拟议的研究中，我们将研究大脑连通性水平上训练引起的认知改善的神经元底物。鉴于神经可塑性的各种机制，我们将在一组中年健康参与者中采用神经影像技术（例如fMRI，PET和DTI）的组合。使用这些方式，将测量功能，代谢和结构连接性。实验对象将接受系统的WM培训，然后与主动对照组进行比较。在训练之前和之后，将在混合宠物/MR系统上同时获得MRI和氟脱氧葡萄糖PET数据。将在相同的两个时间点以及3个月和12个月的随访中进行广泛的认知测试电池。我们假设培训后的默认模式和中央执行网络的连接指数增加。但是，考虑到独特的时间动力和能量成本，预计训练引起的神经塑性的不同形式与及时的认知增长有所不同。具体而言，我们假设网络结构和代谢连通性的增加可预测与功能连通性相比，准确性更高的近转移效应（训练后12个月）。除了神经生物学的相关性外，拟议的研究的结果还将有助于针对年龄和疾病相关的认知缺陷的认知干预措施的发展。