Additive and interaction effects of working memory and motor sequence training on brain functional connectivity

Dexterity in the Acute Phase of Stroke: Impairments and Neural Substrates

BACKGROUND

Stroke can impair manual dexterity, leading to loss of independence following incomplete recovery. Enhancing our understanding of dexterity impairment may improve neurorehabilitation.

OBJECTIVES

The study aimed to measure dexterity components in acute stroke patients with and without hand motor deficits, compare them to those of healthy controls (HC), and to explore the neural substrates involved in specific components of dexterity.

METHODS

We used the Dextrain Manipulandum to quantify fine finger force control, finger selection accuracy, coactivation, and reaction time (RT). Dexterity was evaluated twice (2 days apart) in 74 patients and 14 HC. Voxel-Lesion-Symptom-Mapping (VLSM) was used to analyze the relationship between tissue damage and dexterity. Results. Due to severe paresis or fatigue, 24 patients could not perform these tasks. In 50 patients (included 4.6 ± 3.3 days post-stroke), finger force control improved (P < .001), as it did in HC (P = .03) who performed better than patients on both evaluations. Accuracy of finger selection did not improve significantly in any group, but the HC performed better on both evaluations. Unexpectedly, coactivation was better in patients than in HC at D3 (P = .03). There were no between-group differences in RT. VLSM showed that damage to the superior temporal gyrus (STG) impaired finger force control while damage to the posterior limb of the internal capsule (PLIC) impaired finger selectivity.

CONCLUSIONS

Acute stroke affecting the STG or PLIC impaired selective components of dexterity. Patients with mild to moderate impairment showed better finger force control and accuracy selection within 48 hours, suggesting the feasibility of detecting early dexterity improvements.

Reduction of Interhemispheric Homotopic Connectivity in Cognitive and Visual Information Processing Pathways in Patients With Thyroid-Associated Ophthalmopathy

Purpose

Thyroid-associated ophthalmopathy (TAO) is a vision threatening autoimmune and inflammatory orbital disease, and has been reported to be associated with a wide range of structural and functional abnormalities of bilateral hemispheres. However, whether the interhemisphere functional connectivity (FC) of TAO patients is altered still remain unclear. A new technique called voxel-mirrored homotopic connectivity (VMHC) combined with support vector machine (SVM) method was used in the present study to explore interhemispheric homotopic functional connectivity alterations in patients with TAO.

Methods

A total of 21 TAO patients (14 males and 7 females) and 21 wellmatched healthy controls (HCs, 14 males and 7 females), respectively, underwent functional magnetic resonance imaging (fMRI) scanning in the resting state. We evaluated alterations in the resting state functional connectivity between hemispheres by applying VMHC method and then selected these abnormal brain regions as seed areas for subsequent study using FC method. Furthermore, the observed changes of regions in the VMHC analysis were chosen as classification features to differentiate patients with TAO from HCs through support vector machine (SVM) method.

Results

The results showed that compared with HCs, TAO patients showed significantly lower VMHC values in the bilateral postcentral gyrus, lingual gyrus, calcarine, middle temporal gyrus, middle occipital gyrus and angular. Moreover, significantly decreased FC values were found between the right postcentral gyrus/lingual gyrus/calcarine and left lingual gyrus/cuneus/superior occipital gyrus, left postcentral gyrus/lingual gyrus/calcarine and right lingual gyrus/ middle temporal gyrus, right middle temporal gyrus and left cerebellum-8/lingual gyrus/middle occipital gyrus/supplementary motor area, left middle temporal gyrus and right middle occipital gyrus, right middle occipital gyrus/angular and left middle temporal pole (voxel-level p < 0.01, Gaussian random field correction, cluster-level p < 0.05). The SVM classification model achieved good performance in differentiating TAO patients from HCs (total accuracy: 73.81%; area under the curve: 0.79).

Conclusion

The present study revealed that the altered interhemisphere interaction and integration of information involved in cognitive and visual information processing pathways including the postcentral gyrus, cuneus, cerebellum, angular, widespread visual cortex and temporal cortex in patients with TAO relative to HC group. VMHC variability had potential value for accurately and specifically distinguishing patients with TAO from HCs. The new findings may provide novel insights into the neurological mechanisms underlying visual and cognitive disorders in patients with TAO.

Local-to-Remote Brain Functional Connectivity in Patients with Thyroid-Associated Ophthalmopathy and Assessment of Its Predictive Value Using Machine Learning

Purpose

To explore the alterations in both local and remote brain connectivity in patients with thyroid-associated ophthalmopathy (TAO) and to investigate whether the alterations of local neural function could be used to distinguish patients with TAO from healthy controls (HCs) using support vector machine (SVM) classifier.

Materials and Methods

In total, 21 patients with TAO and 21 well-matched HCs were enrolled in our study and underwent resting-state functional magnetic resonance imaging (rs-fMRI) scanning. We employed regional homogeneity (ReHo) algorithm to evaluate local neural function and selected significantly altered brain regions as seed areas for subsequent study of the remote functional connectivity (FC). Moreover, we chose the observed alterations in the ReHo analysis as classification features to differentiate patients with TAO from HCs through SVM classification method.

Results

Compared with the HCs, TAO patients showed significantly lower ReHo values in the right middle occipital gyrus (MOG) and right angular (ANG). In contrast, TAO patients displayed higher ReHo values in the left hippocampus (Hipp). We further found TAO patients exhibited decreased FC between the left and right Hipp, right MOG and left cerebellum (CER), right ANG and left rectus, right superior temporal pole gyrus (PSTG) (voxel-level p < 0.01, Gaussian random field correction, cluster-level p < 0.05). The alterations in local neural function exhibited an accuracy of 78.57% and area under curve of 0.81 for distinguishing the patients from HCs.

Conclusion

We mainly found the results that patients with TAO showed significantly dysfunctional local and remote brain functional connectivity in several brain regions associated with visual and cognitive functions. The ReHo variability has potential value in differentiating patients with TAO from HCs. These findings may provide novel insights into the neurological mechanisms underlying visual and cognitive disorders in patients with TAO.

Age-Related Changes in Functional Connectivity during the Sensorimotor Integration Detected by Artificial Neural Network

Large-scale functional connectivity is an important indicator of the brain’s normal functioning. The abnormalities in the connectivity pattern can be used as a diagnostic tool to detect various neurological disorders. The present paper describes the functional connectivity assessment based on artificial intelligence to reveal age-related changes in neural response in a simple motor execution task. Twenty subjects of two age groups performed repetitive motor tasks on command, while the whole-scalp EEG was recorded. We applied the model based on the feed-forward multilayer perceptron to detect functional relationships between five groups of sensors located over the frontal, parietal, left, right, and middle motor cortex. Functional dependence was evaluated with the predicted and original time series coefficient of determination. Then, we applied statistical analysis to highlight the significant features of the functional connectivity network assessed by our model. Our findings revealed the connectivity pattern is consistent with modern ideas of the healthy aging effect on neural activation. Elderly adults demonstrate a pronounced activation of the whole-brain theta-band network and decreased activation of frontal–parietal and motor areas of the mu-band. Between-subject analysis revealed a strengthening of inter-areal task-relevant links in elderly adults. These findings can be interpreted as an increased cognitive demand in elderly adults to perform simple motor tasks with the dominant hand, induced by age-related working memory decline.