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Frequency-specific network topologies in the resting human brain.

Sasai S, Homae F, Watanabe H, Sasaki AT, Tanabe HC, Sadato N, Taga G - Front Hum Neurosci (2014)

Bottom Line: In investigating the coherence spectrum among 87 brain regions, we found that two frequency bands, 0.01-0.03 Hz (very low frequency [VLF] band) and 0.07-0.09 Hz (low frequency [LF] band), mainly contributed to functional connectivity.Thus, depending on the timescale of brain activity, at least two distinct network topologies contributed to information segregation and integration.This suggests that the brain intrinsically has timescale-dependent functional organizations.

View Article: PubMed Central - PubMed

Affiliation: Graduate School of Education, University of Tokyo Tokyo, Japan ; Department of Psychiatry, University of Wisconsin - Madison Madison, WI, USA.

ABSTRACT
A community is a set of nodes with dense inter-connections, while there are sparse connections between different communities. A hub is a highly connected node with high centrality. It has been shown that both "communities" and "hubs" exist simultaneously in the brain's functional connectivity network (FCN), as estimated by correlations among low-frequency spontaneous fluctuations in functional magnetic resonance imaging (fMRI) signal changes (0.01-0.10 Hz). This indicates that the brain has a spatial organization that promotes both segregation and integration of information. Here, we demonstrate that frequency-specific network topologies that characterize segregation and integration also exist within this frequency range. In investigating the coherence spectrum among 87 brain regions, we found that two frequency bands, 0.01-0.03 Hz (very low frequency [VLF] band) and 0.07-0.09 Hz (low frequency [LF] band), mainly contributed to functional connectivity. Comparing graph theoretical indices for the VLF and LF bands revealed that the network in the former had a higher capacity for information segregation between identified communities than the latter. Hubs in the VLF band were mainly located within the anterior cingulate cortices, whereas those in the LF band were located in the posterior cingulate cortices and thalamus. Thus, depending on the timescale of brain activity, at least two distinct network topologies contributed to information segregation and integration. This suggests that the brain intrinsically has timescale-dependent functional organizations.

No MeSH data available.


Related in: MedlinePlus

Coherence spectrum estimated using simultaneously obtained NIRS data. (A) We obtained NIRS signals at 14 cortical regions indicated as blue rings. Cyan dots represent standard reference points used in locating channels of electroencephalography on the scalp. In a previous study, we identified 14 cortical regions, where NIRS signals were obtained, in MNI space to determine ROIs corresponding to each NIRS measurement region for each individual. For detailed methods for the identification and MNI coordinates, please refer to Sasai et al. (2012). As a result, we found one cortical region (medial prefrontal cortex [mPFC]) included in the default mode system (red filled circle) and two bilateral cortical regions (left and right anterior prefrontal cortices [laPFC and raPFC]) contained in the fronto-parietal system (blue filled circles). (B) Voxels corresponding to measured regions by NIRS are shown. Colors are the same as those defined in (A). (C) We calculated the coherence between laPFC and raPFC to investigate the intra-system coherence spectrum (fronto-parietal system), and also estimated the coherence between mPFC and laPFC, and between mPFC and raPFC, to examine the inter-system coherence spectrum (default-mode and fronto-parietal systems). A black line indicates an intra-system pair of ROIs, whereas cyan lines represent inter-system pairs. (D,E) Coherence spectrums of two NIRS signals (oxygenated [oxy-] hemoglobin and deoxygenated [deoxy-] hemoglobin) with two clear peaks corresponding to typical frequency bands of respiratory fluctuation around 0.3 Hz and cardiac pulsations around 1 Hz. High coherences in VLF and LF could still be observed in the spectrum, supporting the idea that higher coherences in these bands are not due to aliasing. (F) Coherence spectrum obtained using fMRI signals extracted from ROIs corresponding to NIRS measurement regions (as shown in B). We confirmed the high coherence values in VLF and LF in this spectrum, supporting the notion that characteristics of the coherence spectrum cannot be attributed to differences in ROI locations between our current and previous studies.
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Figure 3: Coherence spectrum estimated using simultaneously obtained NIRS data. (A) We obtained NIRS signals at 14 cortical regions indicated as blue rings. Cyan dots represent standard reference points used in locating channels of electroencephalography on the scalp. In a previous study, we identified 14 cortical regions, where NIRS signals were obtained, in MNI space to determine ROIs corresponding to each NIRS measurement region for each individual. For detailed methods for the identification and MNI coordinates, please refer to Sasai et al. (2012). As a result, we found one cortical region (medial prefrontal cortex [mPFC]) included in the default mode system (red filled circle) and two bilateral cortical regions (left and right anterior prefrontal cortices [laPFC and raPFC]) contained in the fronto-parietal system (blue filled circles). (B) Voxels corresponding to measured regions by NIRS are shown. Colors are the same as those defined in (A). (C) We calculated the coherence between laPFC and raPFC to investigate the intra-system coherence spectrum (fronto-parietal system), and also estimated the coherence between mPFC and laPFC, and between mPFC and raPFC, to examine the inter-system coherence spectrum (default-mode and fronto-parietal systems). A black line indicates an intra-system pair of ROIs, whereas cyan lines represent inter-system pairs. (D,E) Coherence spectrums of two NIRS signals (oxygenated [oxy-] hemoglobin and deoxygenated [deoxy-] hemoglobin) with two clear peaks corresponding to typical frequency bands of respiratory fluctuation around 0.3 Hz and cardiac pulsations around 1 Hz. High coherences in VLF and LF could still be observed in the spectrum, supporting the idea that higher coherences in these bands are not due to aliasing. (F) Coherence spectrum obtained using fMRI signals extracted from ROIs corresponding to NIRS measurement regions (as shown in B). We confirmed the high coherence values in VLF and LF in this spectrum, supporting the notion that characteristics of the coherence spectrum cannot be attributed to differences in ROI locations between our current and previous studies.

Mentions: Group-averaged coherence values were calculated and averaged within the following two categories of ROI pairs: ROIs within the same functional system (intra-system) and ROIs belonging to different functional systems (inter-system; Dosenbach et al., 2010; Figure 1B). The highest value of the averaged coherence in the intra-system was observed in the lowest frequency band; hereafter we refer to this frequency band (0.01–0.03 Hz) as VLF (very low frequency) represented by its center frequency (0.02 Hz) in Figure 2. There was one other frequency band in which the coherence values were higher than others; we call this frequency band (0.07–0.09 Hz) as the LF (low frequency band) indicated as 0.08 Hz in Figure 2. In both frequency bands, we found that the averaged coherence value obtained in the inter-system was also higher than other frequency bands. The result did not depend on the width of frequency bands where coherence values were averaged (Figure S1). In order to ensure that the observed frequency characteristics were reproducible in data sets obtained at other institutions, we estimated the above-mentioned coherence spectrum in a public resting state fMRI data set with 96 participants from the 1000 Functional Connectome Project (http://fcon_1000.projects.nitrc.org/index.html). Results confirmed that coherence values in the VLF and LF were larger than those in other frequency bands (Figure S2). Furthermore, to confirm that this frequency specificity was not due to aliasing of physiological noise contained in higher frequency regions, we investigated the coherence spectrum of a simultaneously obtained NIRS data set. NIRS signals were measured with a sufficiently higher sampling rate (10 Hz) to characterize hemoglobin signals including respiratory and cardiac pulsations, which were observed as separate peaks in the power spectrum. We confirmed that although there were peaks corresponding to typical respiratory and cardiac pulsations around 0.3 and 1 Hz in the coherence spectrum, VLF and LF were still signature frequency bands where the coherence values were higher than other frequency bands within the 0.01–0.10 Hz band (Figure 3). Collectively, these results demonstrate that there are two frequency components that strongly contribute to resting state functional connectivity within the frequency band (0.01–0.10 Hz), where functional connectivity has been estimated in many studies. Thus, we focused and conducted analyses on these two frequency bands.


Frequency-specific network topologies in the resting human brain.

Sasai S, Homae F, Watanabe H, Sasaki AT, Tanabe HC, Sadato N, Taga G - Front Hum Neurosci (2014)

Coherence spectrum estimated using simultaneously obtained NIRS data. (A) We obtained NIRS signals at 14 cortical regions indicated as blue rings. Cyan dots represent standard reference points used in locating channels of electroencephalography on the scalp. In a previous study, we identified 14 cortical regions, where NIRS signals were obtained, in MNI space to determine ROIs corresponding to each NIRS measurement region for each individual. For detailed methods for the identification and MNI coordinates, please refer to Sasai et al. (2012). As a result, we found one cortical region (medial prefrontal cortex [mPFC]) included in the default mode system (red filled circle) and two bilateral cortical regions (left and right anterior prefrontal cortices [laPFC and raPFC]) contained in the fronto-parietal system (blue filled circles). (B) Voxels corresponding to measured regions by NIRS are shown. Colors are the same as those defined in (A). (C) We calculated the coherence between laPFC and raPFC to investigate the intra-system coherence spectrum (fronto-parietal system), and also estimated the coherence between mPFC and laPFC, and between mPFC and raPFC, to examine the inter-system coherence spectrum (default-mode and fronto-parietal systems). A black line indicates an intra-system pair of ROIs, whereas cyan lines represent inter-system pairs. (D,E) Coherence spectrums of two NIRS signals (oxygenated [oxy-] hemoglobin and deoxygenated [deoxy-] hemoglobin) with two clear peaks corresponding to typical frequency bands of respiratory fluctuation around 0.3 Hz and cardiac pulsations around 1 Hz. High coherences in VLF and LF could still be observed in the spectrum, supporting the idea that higher coherences in these bands are not due to aliasing. (F) Coherence spectrum obtained using fMRI signals extracted from ROIs corresponding to NIRS measurement regions (as shown in B). We confirmed the high coherence values in VLF and LF in this spectrum, supporting the notion that characteristics of the coherence spectrum cannot be attributed to differences in ROI locations between our current and previous studies.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4273625&req=5

Figure 3: Coherence spectrum estimated using simultaneously obtained NIRS data. (A) We obtained NIRS signals at 14 cortical regions indicated as blue rings. Cyan dots represent standard reference points used in locating channels of electroencephalography on the scalp. In a previous study, we identified 14 cortical regions, where NIRS signals were obtained, in MNI space to determine ROIs corresponding to each NIRS measurement region for each individual. For detailed methods for the identification and MNI coordinates, please refer to Sasai et al. (2012). As a result, we found one cortical region (medial prefrontal cortex [mPFC]) included in the default mode system (red filled circle) and two bilateral cortical regions (left and right anterior prefrontal cortices [laPFC and raPFC]) contained in the fronto-parietal system (blue filled circles). (B) Voxels corresponding to measured regions by NIRS are shown. Colors are the same as those defined in (A). (C) We calculated the coherence between laPFC and raPFC to investigate the intra-system coherence spectrum (fronto-parietal system), and also estimated the coherence between mPFC and laPFC, and between mPFC and raPFC, to examine the inter-system coherence spectrum (default-mode and fronto-parietal systems). A black line indicates an intra-system pair of ROIs, whereas cyan lines represent inter-system pairs. (D,E) Coherence spectrums of two NIRS signals (oxygenated [oxy-] hemoglobin and deoxygenated [deoxy-] hemoglobin) with two clear peaks corresponding to typical frequency bands of respiratory fluctuation around 0.3 Hz and cardiac pulsations around 1 Hz. High coherences in VLF and LF could still be observed in the spectrum, supporting the idea that higher coherences in these bands are not due to aliasing. (F) Coherence spectrum obtained using fMRI signals extracted from ROIs corresponding to NIRS measurement regions (as shown in B). We confirmed the high coherence values in VLF and LF in this spectrum, supporting the notion that characteristics of the coherence spectrum cannot be attributed to differences in ROI locations between our current and previous studies.
Mentions: Group-averaged coherence values were calculated and averaged within the following two categories of ROI pairs: ROIs within the same functional system (intra-system) and ROIs belonging to different functional systems (inter-system; Dosenbach et al., 2010; Figure 1B). The highest value of the averaged coherence in the intra-system was observed in the lowest frequency band; hereafter we refer to this frequency band (0.01–0.03 Hz) as VLF (very low frequency) represented by its center frequency (0.02 Hz) in Figure 2. There was one other frequency band in which the coherence values were higher than others; we call this frequency band (0.07–0.09 Hz) as the LF (low frequency band) indicated as 0.08 Hz in Figure 2. In both frequency bands, we found that the averaged coherence value obtained in the inter-system was also higher than other frequency bands. The result did not depend on the width of frequency bands where coherence values were averaged (Figure S1). In order to ensure that the observed frequency characteristics were reproducible in data sets obtained at other institutions, we estimated the above-mentioned coherence spectrum in a public resting state fMRI data set with 96 participants from the 1000 Functional Connectome Project (http://fcon_1000.projects.nitrc.org/index.html). Results confirmed that coherence values in the VLF and LF were larger than those in other frequency bands (Figure S2). Furthermore, to confirm that this frequency specificity was not due to aliasing of physiological noise contained in higher frequency regions, we investigated the coherence spectrum of a simultaneously obtained NIRS data set. NIRS signals were measured with a sufficiently higher sampling rate (10 Hz) to characterize hemoglobin signals including respiratory and cardiac pulsations, which were observed as separate peaks in the power spectrum. We confirmed that although there were peaks corresponding to typical respiratory and cardiac pulsations around 0.3 and 1 Hz in the coherence spectrum, VLF and LF were still signature frequency bands where the coherence values were higher than other frequency bands within the 0.01–0.10 Hz band (Figure 3). Collectively, these results demonstrate that there are two frequency components that strongly contribute to resting state functional connectivity within the frequency band (0.01–0.10 Hz), where functional connectivity has been estimated in many studies. Thus, we focused and conducted analyses on these two frequency bands.

Bottom Line: In investigating the coherence spectrum among 87 brain regions, we found that two frequency bands, 0.01-0.03 Hz (very low frequency [VLF] band) and 0.07-0.09 Hz (low frequency [LF] band), mainly contributed to functional connectivity.Thus, depending on the timescale of brain activity, at least two distinct network topologies contributed to information segregation and integration.This suggests that the brain intrinsically has timescale-dependent functional organizations.

View Article: PubMed Central - PubMed

Affiliation: Graduate School of Education, University of Tokyo Tokyo, Japan ; Department of Psychiatry, University of Wisconsin - Madison Madison, WI, USA.

ABSTRACT
A community is a set of nodes with dense inter-connections, while there are sparse connections between different communities. A hub is a highly connected node with high centrality. It has been shown that both "communities" and "hubs" exist simultaneously in the brain's functional connectivity network (FCN), as estimated by correlations among low-frequency spontaneous fluctuations in functional magnetic resonance imaging (fMRI) signal changes (0.01-0.10 Hz). This indicates that the brain has a spatial organization that promotes both segregation and integration of information. Here, we demonstrate that frequency-specific network topologies that characterize segregation and integration also exist within this frequency range. In investigating the coherence spectrum among 87 brain regions, we found that two frequency bands, 0.01-0.03 Hz (very low frequency [VLF] band) and 0.07-0.09 Hz (low frequency [LF] band), mainly contributed to functional connectivity. Comparing graph theoretical indices for the VLF and LF bands revealed that the network in the former had a higher capacity for information segregation between identified communities than the latter. Hubs in the VLF band were mainly located within the anterior cingulate cortices, whereas those in the LF band were located in the posterior cingulate cortices and thalamus. Thus, depending on the timescale of brain activity, at least two distinct network topologies contributed to information segregation and integration. This suggests that the brain intrinsically has timescale-dependent functional organizations.

No MeSH data available.


Related in: MedlinePlus