Dataset Information

Working Memory-Related Effective Connectivity in Huntington's Disease Patients.

ABSTRACT: Huntington's disease (HD) is a genetically caused neurodegenerative disorder characterized by heterogeneous motor, psychiatric, and cognitive symptoms. Although motor symptoms may be the most prominent presentation, cognitive symptoms such as memory deficits and executive dysfunction typically co-occur. We used functional magnetic resonance imaging (fMRI) and task fMRI-based dynamic causal modeling (DCM) to evaluate HD-related changes in the neural network underlying working memory (WM). Sixty-four pre-symptomatic HD mutation carriers (preHD), 20 patients with early manifest HD symptoms (earlyHD), and 83 healthy control subjects performed an n-back fMRI task with two levels of WM load. Effective connectivity was assessed in five predefined regions of interest, comprising bilateral inferior parietal cortex, left anterior cingulate cortex, and bilateral dorsolateral prefrontal cortex. HD mutation carriers performed less accurately and more slowly at high WM load compared with the control group. While between-group comparisons of brain activation did not reveal differential recruitment of the cortical WM network in mutation carriers, comparisons of brain connectivity as identified with DCM revealed a number of group differences across the whole WM network. Most strikingly, we observed decreasing connectivity from several regions toward right dorsolateral prefrontal cortex (rDLPFC) in preHD and even more so in earlyHD. The deterioration in rDLPFC connectivity complements results from previous studies and might mirror beginning cortical neural decline at premanifest and early manifest stages of HD. We were able to characterize effective connectivity in a WM network of HD mutation carriers yielding further insight into patterns of cognitive decline and accompanying neural deterioration.

SUBMITTER: Lahr J

PROVIDER: S-EPMC5994408 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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Working Memory-Related Effective Connectivity in Huntington's Disease Patients.

Lahr Jacob J Minkova Lora L Tabrizi Sarah J SJ Stout Julie C JC Klöppel Stefan S Scheller Elisa E

Frontiers in neurology 20180604

Huntington's disease (HD) is a genetically caused neurodegenerative disorder characterized by heterogeneous motor, psychiatric, and cognitive symptoms. Although motor symptoms may be the most prominent presentation, cognitive symptoms such as memory deficits and executive dysfunction typically co-occur. We used functional magnetic resonance imaging (fMRI) and task fMRI-based dynamic causal modeling (DCM) to evaluate HD-related changes in the neural network underlying working memory (WM). Sixty-f ...[more]

PMID: 29915555

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Project description:BackgroundVisual working memory (VWM) helps us store visual information to prepare for subsequent behavior. The neuronal mechanisms for sustaining coherent visual information and the mechanisms for limited VWM capacity have remained uncharacterized. Although numerous studies have utilized behavioral accuracy, neural activity, and connectivity to explore the mechanism of VWM retention, little is known about the load-related changes in functional connectivity for hemi-field VWM retention.Methodology/principal findingsIn this study, we recorded electroencephalography (EEG) from 14 normal young adults while they performed a bilateral visual field memory task. Subjects had more rapid and accurate responses to the left visual field (LVF) memory condition. The difference in mean amplitude between the ipsilateral and contralateral event-related potential (ERP) at parietal-occipital electrodes in retention interval period was obtained with six different memory loads. Functional connectivity between 128 scalp regions was measured by EEG phase synchronization in the theta- (4-8 Hz), alpha- (8-12 Hz), beta- (12-32 Hz), and gamma- (32-40 Hz) frequency bands. The resulting matrices were converted to graphs, and mean degree, clustering coefficient and shortest path length was computed as a function of memory load. The results showed that brain networks of theta-, alpha-, beta-, and gamma- frequency bands were load-dependent and visual-field dependent. The networks of theta- and alpha- bands phase synchrony were most predominant in retention period for right visual field (RVF) WM than for LVF WM. Furthermore, only for RVF memory condition, brain network density of theta-band during the retention interval were linked to the delay of behavior reaction time, and the topological property of alpha-band network was negative correlation with behavior accuracy.Conclusions/significanceWe suggest that the differences in theta- and alpha- bands between LVF and RVF conditions in functional connectivity and topological properties during retention period may result in the decline of behavioral performance in RVF task.

Project description:Brain connectivity analysis plays an essential role in the research of working memory that involves complex coordination of various brain regions. In this research, we present a comprehensive view of trans-states brain connectivity variation based on continuous scalp EEG, extending beyond traditional stimuli-lock averaging or restriction to short time scales of hundreds of milliseconds after stimulus onset. The scalp EEG was collected under three conditions: quiet, memory, and control. The only difference between the memory and control conditions was that in the memory condition, subjects made an effort to retain information. We started our investigation with calibrations of Pearson correlation in EEG analysis and then derived two indices, link strength and node connectivity, to make comparisons between different states. Finally, we constructed and studied trans-state brain connectivity variation topography. Comparing memory and control states with quiet state, we found that the beta topography highlights links between T5/T6 and O1/O2, which represents the visual ventral stream, and the gamma topography conveys strengthening of inter-hemisphere links and weakening of intra-hemisphere frontal-posterior links, implying parallel inter-hemisphere coordination combined with sequential intra-hemisphere coordination when subjects are confronted with visual stimuli and a motor task. For comparison between memory and control states, we also found that the node connectivity of T6 stands out in gamma topography, which provides strong proof from scalp EEG for the information binding or relational processing function of the temporal lobe in memory formation. To our knowledge, this is the first time for any method to effectively capture brain connectivity variation associated with working memory from a relatively large scale both in time (from a second to a minute) and in space (from the scalp). The method can track brain activity continuously with minimal manual interruptions; therefore, it has promising potential in applications such as brain computer interfaces and brain training.

Project description:Transcranial direct and alternating current stimulation (tDCS and tACS, respectively) entail capability to modulate human brain dynamics and cognition. However, the comparability of these approaches at the level of large-scale functional networks has not been thoroughly investigated. In this study, 44 subjects were randomly assigned to receive sham (N = 15), tDCS (N = 15), or tACS (N = 14). The first electrode (anode in tDCS) was positioned over the left dorsolateral prefrontal cortex, the target area, and the second electrode (cathode in tDCS) was placed over the right supraorbital region. tDCS was delivered with a constant current of 2 mA. tACS was fixed to 2 mA peak-to-peak with 6 Hz frequency. Stimulation was applied concurrently with functional magnetic resonance imaging (fMRI) acquisitions, both at rest and during the performance of a verbal working memory (WM) task. After stimulation, subjects repeated the fMRI WM task. Our results indicated that at rest, tDCS increased functional connectivity particularly within the default-mode network (DMN), while tACS decreased it. When comparing both fMRI WM tasks, it was observed that tDCS displayed decreased brain activity post-stimulation as compared to online. Conversely, tACS effects were driven by neural increases online as compared to post-stimulation. Interestingly, both effects primarily occurred within DMN-related areas. Regarding the differences in each fMRI WM task, during the online fMRI WM task, tACS engaged distributed neural resources which did not overlap with the WM-dependent activity pattern, but with some posterior DMN regions. In contrast, during the post-stimulation fMRI WM task, tDCS strengthened prefrontal DMN deactivations, being these activity reductions associated with faster responses. Furthermore, it was observed that tDCS neural responses presented certain consistency across distinct fMRI modalities, while tACS did not. In sum, tDCS and tACS modulate fMRI-derived network dynamics differently. However, both effects seem to focus on DMN regions and the WM network-DMN shift, which are highly affected in aging and disease. Thus, albeit exploratory and needing further replication with larger samples, our results might provide a refined understanding of how the DMN functioning can be externally modulated through commonly used non-invasive brain stimulation techniques, which may be of eventual clinical relevance.

Dataset Information

Working Memory-Related Effective Connectivity in Huntington's Disease Patients.

Publications

Working Memory-Related Effective Connectivity in Huntington's Disease Patients.

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