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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

The spatial distribution of the interested source signals from ICA analysis. Results were from 14 of the 16 subjects, and subjects S 11 and S 15 were excluded. No right source components were found in subjects S4, S5, S9, and S10 and the rest subjects had normal source distributions. Signal space distribution was denoted by selected color circles and color intensity (–1 to 1) on the map. Blue represents –1, Red represents 1.
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Figure 4: The spatial distribution of the interested source signals from ICA analysis. Results were from 14 of the 16 subjects, and subjects S 11 and S 15 were excluded. No right source components were found in subjects S4, S5, S9, and S10 and the rest subjects had normal source distributions. Signal space distribution was denoted by selected color circles and color intensity (–1 to 1) on the map. Blue represents –1, Red represents 1.

Mentions: As described in the “Methods” above, the decomposed 384 sources of the 14 subjects were manually selected (Table 1). Eight subjects (S1, S2, S3, S7, S8, S12, S13, and S16) had one interested IC (Figure 4) and two subjects (S6, S14) had two interested ICs. Four subjects (S4, S5, S9, and S10) had no suitable source selected. The spatial distribution of source signals of the 14 subjects is also displayed in Figure 4. The signal space distribution is denoted by selected color circles and by the intensity of the color (–1 to 1) on the map in each IC region. Each circle was given an intensity distribution value from 0 to 1 based on the intensity distribution of the corresponding source component in the measuring lead as described in methods. The source signal distributions in the Pz and C3/C4 regions are also depicted in Table 1; where the source signals was expressed as the sum of intensity distribution values for an IC in the a region. Figure 4 and Table 1 show that while many subjects had a source component near Pz region, five subjects (S3, S7, S8, S13, S16) had weak source signals (intensity distribution value < 1.0) located in the primary motor cortex region near C3 or C4; and five (S1, S2, S6, S12, S14) had strong source signals (value ≥1.0) in the region (Figure 4 and Table 1).


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)

The spatial distribution of the interested source signals from ICA analysis. Results were from 14 of the 16 subjects, and subjects S 11 and S 15 were excluded. No right source components were found in subjects S4, S5, S9, and S10 and the rest subjects had normal source distributions. Signal space distribution was denoted by selected color circles and color intensity (–1 to 1) on the map. Blue represents –1, Red represents 1.
© Copyright Policy
Related In: Results  -  Collection

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

Figure 4: The spatial distribution of the interested source signals from ICA analysis. Results were from 14 of the 16 subjects, and subjects S 11 and S 15 were excluded. No right source components were found in subjects S4, S5, S9, and S10 and the rest subjects had normal source distributions. Signal space distribution was denoted by selected color circles and color intensity (–1 to 1) on the map. Blue represents –1, Red represents 1.
Mentions: As described in the “Methods” above, the decomposed 384 sources of the 14 subjects were manually selected (Table 1). Eight subjects (S1, S2, S3, S7, S8, S12, S13, and S16) had one interested IC (Figure 4) and two subjects (S6, S14) had two interested ICs. Four subjects (S4, S5, S9, and S10) had no suitable source selected. The spatial distribution of source signals of the 14 subjects is also displayed in Figure 4. The signal space distribution is denoted by selected color circles and by the intensity of the color (–1 to 1) on the map in each IC region. Each circle was given an intensity distribution value from 0 to 1 based on the intensity distribution of the corresponding source component in the measuring lead as described in methods. The source signal distributions in the Pz and C3/C4 regions are also depicted in Table 1; where the source signals was expressed as the sum of intensity distribution values for an IC in the a region. Figure 4 and Table 1 show that while many subjects had a source component near Pz region, five subjects (S3, S7, S8, S13, S16) had weak source signals (intensity distribution value < 1.0) located in the primary motor cortex region near C3 or C4; and five (S1, S2, S6, S12, S14) had strong source signals (value ≥1.0) in the region (Figure 4 and Table 1).

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