Limits...
Space distribution of EEG responses to hanoi-moving visual and auditory stimulation with Fourier Independent Component Analysis.

Li S, Wang Y, Bin G, Huang X, Zhang D, Liu G, Lv Y, Gao X, Gao S, Ma L - Front Hum Neurosci (2015)

Bottom Line: F-ICA found more sensory stimuli-related independent components located within the sensorimotor region than ICA did.In the Pz region, the total source signal intensity distribution from F-ICA was 12.50 (Mean 0.89 ± 0.53); although exceeding that of traditional time-domain ICA 8.20 (Mean 0.59 ± 0.48), the difference was not statistically significant (p > 0.05).These results support the hypothesis that mu rhythm was sensitive to detection of the cognitive expression, which could be reflected by the function in the parietal lobe sensory-motor region.

View Article: PubMed Central - PubMed

Affiliation: Department of Medical Instruments, PLA General Hospital Beijing, China.

ABSTRACT

Background and objective: The relationship between EEG source signals and action-related visual and auditory stimulation is still not well-understood. The objective of this study was to identify EEG source signals and their associated action-related visual and auditory responses, especially independent components of EEG.

Methods: A hand-moving-Hanoi video paradigm was used to study neural correlates of the action-related visual and auditory information processing determined by mu rhythm (8-12 Hz) in 16 healthy young subjects. Independent component analysis (ICA) was applied to identify separate EEG sources, and further computed in the frequency domain by applying-Fourier transform ICA (F-ICA).

Results: F-ICA found more sensory stimuli-related independent components located within the sensorimotor region than ICA did. The total number of independent components of interest from F-ICA was 768, twice that of 384 from traditional time-domain ICA (p < 0.05). In the sensory-motor region C3 or C4, the total source signals intensity distribution values from all 14 subjects was 23.00 (Mean 1.64 ± 1.17) from F-ICA; which was more than the 10.5 (Mean 0.75 ± 0.62) from traditional time-domain ICA (p < 0.05). Furthermore, the intensity distribution of source signals in the C3 or C4 region was statistically significant between the ICA and F-ICA groups (strong 50 vs. 92%; weak 50 vs. 8% retrospectively; p < 0.05). In the Pz region, the total source signal intensity distribution from F-ICA was 12.50 (Mean 0.89 ± 0.53); although exceeding that of traditional time-domain ICA 8.20 (Mean 0.59 ± 0.48), the difference was not statistically significant (p > 0.05).

Conclusions: These results support the hypothesis that mu rhythm was sensitive to detection of the cognitive expression, which could be reflected by the function in the parietal lobe sensory-motor region. The results of this study could potentially be applied into early diagnosis for those with visual and hearing impairments in the near future.

No MeSH data available.


Related in: MedlinePlus

Thirty IC spatial distributions in a representative subject (blue represents –1, red represents 1).
© Copyright Policy
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC4508523&req=5

Figure 1: Thirty IC spatial distributions in a representative subject (blue represents –1, red represents 1).

Mentions: Thirty independent components of spatial patterns from one of the subjects are shown in Figure 1 with time-domain ICA (T-ICA) analysis method. The spatial distribution of source signals is denoted by color circles and the signal intensity (–1 to 1) by the color on the map. Corresponding power spectrum from each independent component is displayed in Figure 2. The results in Figure 2 also show that the mu rhythm's power at the motor cortex region was lower at post-learning phase than at pre-learning (IC4). According to the spatial pattern brain topographic map and the power spectra of each IC at pre-learning and post-learning phases, three typical IC components were identified: IC2, IC19, and IC4. The details of the interested source signals are as follows:


Space distribution of EEG responses to hanoi-moving visual and auditory stimulation with Fourier Independent Component Analysis.

Li S, Wang Y, Bin G, Huang X, Zhang D, Liu G, Lv Y, Gao X, Gao S, Ma L - Front Hum Neurosci (2015)

Thirty IC spatial distributions in a representative subject (blue represents –1, red represents 1).
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4508523&req=5

Figure 1: Thirty IC spatial distributions in a representative subject (blue represents –1, red represents 1).
Mentions: Thirty independent components of spatial patterns from one of the subjects are shown in Figure 1 with time-domain ICA (T-ICA) analysis method. The spatial distribution of source signals is denoted by color circles and the signal intensity (–1 to 1) by the color on the map. Corresponding power spectrum from each independent component is displayed in Figure 2. The results in Figure 2 also show that the mu rhythm's power at the motor cortex region was lower at post-learning phase than at pre-learning (IC4). According to the spatial pattern brain topographic map and the power spectra of each IC at pre-learning and post-learning phases, three typical IC components were identified: IC2, IC19, and IC4. The details of the interested source signals are as follows:

Bottom Line: F-ICA found more sensory stimuli-related independent components located within the sensorimotor region than ICA did.In the Pz region, the total source signal intensity distribution from F-ICA was 12.50 (Mean 0.89 ± 0.53); although exceeding that of traditional time-domain ICA 8.20 (Mean 0.59 ± 0.48), the difference was not statistically significant (p > 0.05).These results support the hypothesis that mu rhythm was sensitive to detection of the cognitive expression, which could be reflected by the function in the parietal lobe sensory-motor region.

View Article: PubMed Central - PubMed

Affiliation: Department of Medical Instruments, PLA General Hospital Beijing, China.

ABSTRACT

Background and objective: The relationship between EEG source signals and action-related visual and auditory stimulation is still not well-understood. The objective of this study was to identify EEG source signals and their associated action-related visual and auditory responses, especially independent components of EEG.

Methods: A hand-moving-Hanoi video paradigm was used to study neural correlates of the action-related visual and auditory information processing determined by mu rhythm (8-12 Hz) in 16 healthy young subjects. Independent component analysis (ICA) was applied to identify separate EEG sources, and further computed in the frequency domain by applying-Fourier transform ICA (F-ICA).

Results: F-ICA found more sensory stimuli-related independent components located within the sensorimotor region than ICA did. The total number of independent components of interest from F-ICA was 768, twice that of 384 from traditional time-domain ICA (p < 0.05). In the sensory-motor region C3 or C4, the total source signals intensity distribution values from all 14 subjects was 23.00 (Mean 1.64 ± 1.17) from F-ICA; which was more than the 10.5 (Mean 0.75 ± 0.62) from traditional time-domain ICA (p < 0.05). Furthermore, the intensity distribution of source signals in the C3 or C4 region was statistically significant between the ICA and F-ICA groups (strong 50 vs. 92%; weak 50 vs. 8% retrospectively; p < 0.05). In the Pz region, the total source signal intensity distribution from F-ICA was 12.50 (Mean 0.89 ± 0.53); although exceeding that of traditional time-domain ICA 8.20 (Mean 0.59 ± 0.48), the difference was not statistically significant (p > 0.05).

Conclusions: These results support the hypothesis that mu rhythm was sensitive to detection of the cognitive expression, which could be reflected by the function in the parietal lobe sensory-motor region. The results of this study could potentially be applied into early diagnosis for those with visual and hearing impairments in the near future.

No MeSH data available.


Related in: MedlinePlus