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Distant functional connectivity for bimanual finger coordination declines with aging: an fMRI and SEM exploration.

Kiyama S, Kunimi M, Iidaka T, Nakai T - Front Hum Neurosci (2014)

Bottom Line: However, the model for the elderly group's anti-phase mode in which task performance dropped, did not exhibit significant connections within the aforementioned regions.These results suggest that: (1) the dominant PMd acts as an intermediary to invoke intense intra- and inter-hemispheric connectivity with distant regions among the higher motor areas including the dominant S1 and the non-dominant SPL in order to achieve successful bimanual finger coordination, and (2) the distant connectivity among the higher motor areas declines with aging, whereas the local connectivity within the bilateral M1 is enhanced for the complex anti-phase mode.The latter may underlie the elderly's decreased performance in the complex anti-phase mode of the bimanual finger movement task.

View Article: PubMed Central - PubMed

Affiliation: Neuroimaging and Informatics Lab, National Center for Geriatrics and Gerontology Ohbu, Japan.

ABSTRACT
Although bimanual finger coordination is known to decline with aging, it still remains unclear how exactly the neural substrates underlying the coordination differ between young and elderly adults. The present study focused on: (1) characterization of the functional connectivity within the motor association cortex which is required for successful bimanual finger coordination, and (2) to elucidate upon its age-related decline. To address these objectives, we utilized functional magnetic resonance imaging (fMRI) in combination with structural equation modeling (SEM). This allowed us to compare functional connectivity models between young and elderly age groups during a visually guided bimanual finger movement task using both stable in-phase and complex anti-phase modes. Our SEM exploration of functional connectivity revealed significant age-related differences in connections surrounding the PMd in the dominant hemisphere. In the young group who generally displayed accurate behavior, the SEM model for the anti-phase mode exhibited significant connections from the dominant PMd to the non-dominant SPL, and from the dominant PMd to the dominant S1. However, the model for the elderly group's anti-phase mode in which task performance dropped, did not exhibit significant connections within the aforementioned regions. These results suggest that: (1) the dominant PMd acts as an intermediary to invoke intense intra- and inter-hemispheric connectivity with distant regions among the higher motor areas including the dominant S1 and the non-dominant SPL in order to achieve successful bimanual finger coordination, and (2) the distant connectivity among the higher motor areas declines with aging, whereas the local connectivity within the bilateral M1 is enhanced for the complex anti-phase mode. The latter may underlie the elderly's decreased performance in the complex anti-phase mode of the bimanual finger movement task.

No MeSH data available.


Functional connectivity models between the ten ROIs within the motor association cortex during the bimanual finger movement task. The models are presented for each condition of the in-phase (model A) and anti-phase (model B) modes for the young group, and the in-phase (model C) and anti-phase (model D) modes for the elderly group. The ROIs applied to SEM as observed variables are presented in rectangles. The dependent measure was parameter estimate obtained from each ROI. Measurement error terms are not shown. M1, primary motor cortex; S1, primary somatosensory cortex; PMd, dorsal premotor cortex; SMA, supplementary motor area, SPL; superior parietal lobule, L; left, R; right. The thickness of the arrows represents the significance levels of standardized path coefficients (β) among the mean parameter estimates of the ROIs as follows: p < 0.001; p < 0.01; p ≥ 0.01.
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Figure 5: Functional connectivity models between the ten ROIs within the motor association cortex during the bimanual finger movement task. The models are presented for each condition of the in-phase (model A) and anti-phase (model B) modes for the young group, and the in-phase (model C) and anti-phase (model D) modes for the elderly group. The ROIs applied to SEM as observed variables are presented in rectangles. The dependent measure was parameter estimate obtained from each ROI. Measurement error terms are not shown. M1, primary motor cortex; S1, primary somatosensory cortex; PMd, dorsal premotor cortex; SMA, supplementary motor area, SPL; superior parietal lobule, L; left, R; right. The thickness of the arrows represents the significance levels of standardized path coefficients (β) among the mean parameter estimates of the ROIs as follows: p < 0.001; p < 0.01; p ≥ 0.01.

Mentions: The SEM result is graphically represented in Figure 5 as a path model illustration for each condition. The four models were confirmed to have a good fit with each condition of the current data, as all of the goodness-of-fit indices met the conventional criteria (Table 4). The standardized path coefficients (β) obtained from SEM for the four models are denoted in the Appendix as Supplementary Tables 1 (for the young group models A and B) and 2 (for the elderly group models C and D).


Distant functional connectivity for bimanual finger coordination declines with aging: an fMRI and SEM exploration.

Kiyama S, Kunimi M, Iidaka T, Nakai T - Front Hum Neurosci (2014)

Functional connectivity models between the ten ROIs within the motor association cortex during the bimanual finger movement task. The models are presented for each condition of the in-phase (model A) and anti-phase (model B) modes for the young group, and the in-phase (model C) and anti-phase (model D) modes for the elderly group. The ROIs applied to SEM as observed variables are presented in rectangles. The dependent measure was parameter estimate obtained from each ROI. Measurement error terms are not shown. M1, primary motor cortex; S1, primary somatosensory cortex; PMd, dorsal premotor cortex; SMA, supplementary motor area, SPL; superior parietal lobule, L; left, R; right. The thickness of the arrows represents the significance levels of standardized path coefficients (β) among the mean parameter estimates of the ROIs as follows: p < 0.001; p < 0.01; p ≥ 0.01.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4007017&req=5

Figure 5: Functional connectivity models between the ten ROIs within the motor association cortex during the bimanual finger movement task. The models are presented for each condition of the in-phase (model A) and anti-phase (model B) modes for the young group, and the in-phase (model C) and anti-phase (model D) modes for the elderly group. The ROIs applied to SEM as observed variables are presented in rectangles. The dependent measure was parameter estimate obtained from each ROI. Measurement error terms are not shown. M1, primary motor cortex; S1, primary somatosensory cortex; PMd, dorsal premotor cortex; SMA, supplementary motor area, SPL; superior parietal lobule, L; left, R; right. The thickness of the arrows represents the significance levels of standardized path coefficients (β) among the mean parameter estimates of the ROIs as follows: p < 0.001; p < 0.01; p ≥ 0.01.
Mentions: The SEM result is graphically represented in Figure 5 as a path model illustration for each condition. The four models were confirmed to have a good fit with each condition of the current data, as all of the goodness-of-fit indices met the conventional criteria (Table 4). The standardized path coefficients (β) obtained from SEM for the four models are denoted in the Appendix as Supplementary Tables 1 (for the young group models A and B) and 2 (for the elderly group models C and D).

Bottom Line: However, the model for the elderly group's anti-phase mode in which task performance dropped, did not exhibit significant connections within the aforementioned regions.These results suggest that: (1) the dominant PMd acts as an intermediary to invoke intense intra- and inter-hemispheric connectivity with distant regions among the higher motor areas including the dominant S1 and the non-dominant SPL in order to achieve successful bimanual finger coordination, and (2) the distant connectivity among the higher motor areas declines with aging, whereas the local connectivity within the bilateral M1 is enhanced for the complex anti-phase mode.The latter may underlie the elderly's decreased performance in the complex anti-phase mode of the bimanual finger movement task.

View Article: PubMed Central - PubMed

Affiliation: Neuroimaging and Informatics Lab, National Center for Geriatrics and Gerontology Ohbu, Japan.

ABSTRACT
Although bimanual finger coordination is known to decline with aging, it still remains unclear how exactly the neural substrates underlying the coordination differ between young and elderly adults. The present study focused on: (1) characterization of the functional connectivity within the motor association cortex which is required for successful bimanual finger coordination, and (2) to elucidate upon its age-related decline. To address these objectives, we utilized functional magnetic resonance imaging (fMRI) in combination with structural equation modeling (SEM). This allowed us to compare functional connectivity models between young and elderly age groups during a visually guided bimanual finger movement task using both stable in-phase and complex anti-phase modes. Our SEM exploration of functional connectivity revealed significant age-related differences in connections surrounding the PMd in the dominant hemisphere. In the young group who generally displayed accurate behavior, the SEM model for the anti-phase mode exhibited significant connections from the dominant PMd to the non-dominant SPL, and from the dominant PMd to the dominant S1. However, the model for the elderly group's anti-phase mode in which task performance dropped, did not exhibit significant connections within the aforementioned regions. These results suggest that: (1) the dominant PMd acts as an intermediary to invoke intense intra- and inter-hemispheric connectivity with distant regions among the higher motor areas including the dominant S1 and the non-dominant SPL in order to achieve successful bimanual finger coordination, and (2) the distant connectivity among the higher motor areas declines with aging, whereas the local connectivity within the bilateral M1 is enhanced for the complex anti-phase mode. The latter may underlie the elderly's decreased performance in the complex anti-phase mode of the bimanual finger movement task.

No MeSH data available.