Limits...
Multi-scale integration and predictability in resting state brain activity.

Kolchinsky A, van den Heuvel MP, Griffa A, Hagmann P, Rocha LM, Sporns O, Goñi J - Front Neuroinform (2014)

Bottom Line: We look at how these measures scale when larger spatial regions as well as larger connectome sub-networks are considered.We also find a set of connectome regions that are both internally integrated and coupled to the rest of the brain, and which resemble previously reported resting-state networks.Finally, we argue that information-theoretic measures are useful for characterizing the functional organization of the brain at multiple scales.

View Article: PubMed Central - PubMed

Affiliation: Department of Informatics, School of Informatics and Computing, Indiana University Bloomington, IN, USA ; Instituto Gulbenkian de Ciência Oeiras, Portugal.

ABSTRACT
The human brain displays heterogeneous organization in both structure and function. Here we develop a method to characterize brain regions and networks in terms of information-theoretic measures. We look at how these measures scale when larger spatial regions as well as larger connectome sub-networks are considered. This framework is applied to human brain fMRI recordings of resting-state activity and DSI-inferred structural connectivity. We find that strong functional coupling across large spatial distances distinguishes functional hubs from unimodal low-level areas, and that this long-range functional coupling correlates with structural long-range efficiency on the connectome. We also find a set of connectome regions that are both internally integrated and coupled to the rest of the brain, and which resemble previously reported resting-state networks. Finally, we argue that information-theoretic measures are useful for characterizing the functional organization of the brain at multiple scales.

No MeSH data available.


(A) Cortical distribution of Total MI, the total amount of predictability available about each ROI from the ROIs in the rest of the hemisphere. On the upper right are the top 8 anatomical areas arranged according to maximum Total MI of ROIs with each area (maximum Total MI of intra-area ROIs indicated by light gray bars; the minimum indicated by dark gray bars) while on the lower right are the bottom 8 anatomical areas arranged according to maximum Total MI of ROIs within each area (maximum Total MI of intra-area ROIs indicated by light gray bars; the minimum indicated by dark gray bars). (B) Cortical distribution of Euclidean Coupling Range, the neighbor number at which Euclidean Seed-Environment MI drops below a threshold of 0.3 bits (see text for details). On the upper right are the top 8 anatomical areas arranged according to maximum Euclidean Coupling Range of ROIs with each area [light and dark gray bars indicating maximum and minimum values as in (A)] while on the lower right are the bottom 8 anatomical areas arranged according to maximum Euclidean Coupling Range of ROIs with each area [light and dark gray bars indicating maximum and minimum values as in (A)]. (C) Scatter plot of Total MI vs. Euclidean Coupling Range for left and right hemisphere ROIs. A few ROIs are labeled with the names of their corresponding anatomical areas.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC4109611&req=5

Figure 4: (A) Cortical distribution of Total MI, the total amount of predictability available about each ROI from the ROIs in the rest of the hemisphere. On the upper right are the top 8 anatomical areas arranged according to maximum Total MI of ROIs with each area (maximum Total MI of intra-area ROIs indicated by light gray bars; the minimum indicated by dark gray bars) while on the lower right are the bottom 8 anatomical areas arranged according to maximum Total MI of ROIs within each area (maximum Total MI of intra-area ROIs indicated by light gray bars; the minimum indicated by dark gray bars). (B) Cortical distribution of Euclidean Coupling Range, the neighbor number at which Euclidean Seed-Environment MI drops below a threshold of 0.3 bits (see text for details). On the upper right are the top 8 anatomical areas arranged according to maximum Euclidean Coupling Range of ROIs with each area [light and dark gray bars indicating maximum and minimum values as in (A)] while on the lower right are the bottom 8 anatomical areas arranged according to maximum Euclidean Coupling Range of ROIs with each area [light and dark gray bars indicating maximum and minimum values as in (A)]. (C) Scatter plot of Total MI vs. Euclidean Coupling Range for left and right hemisphere ROIs. A few ROIs are labeled with the names of their corresponding anatomical areas.

Mentions: Figure 4A shows Total MI, or total amount of predictability available about the activity of each ROI given the rest of ROIs in the hemisphere (note that this measure does not depend on choice of distance metric). In addition, we show the distribution of Total MI in different anatomical areas. As described in section MRI Data, ROIs in each hemisphere are grouped into 34 larger-scale “anatomical areas” that correspond to the FreeSurfer parcellation (Desikan et al., 2006). The bar chart on the upper right of the cortical Total MI plot shows the top 8 anatomical areas arranged according to maximum Total MI of ROIs within each area (maximum Total MI of ROIs in each area indicated by light gray bars; the minimum indicated by dark gray bars). The areas with the 8 largest maximum Total MIs are lateral occipital, lingual, precuneus, pericalcarine, superior parietal, inferior parietal, cuneus, and isthmus cingulate. The bar chart on the lower right of the cortical Total MI plot shows the lowest 8 anatomical areas arranged according to maximum Total MI of ROIs within each area (maximum Total MI of ROIs within each area indicated by light gray bars; the minimum indicated by dark gray bars). The areas with the 8 lowest maximum Total MIs are posterior cingulate, banks of the superior temporal sulcus (bankssts), lateral orbitofrontal, paracentral, temporal pole, entorhinal, frontral pole, and parahippocampal.


Multi-scale integration and predictability in resting state brain activity.

Kolchinsky A, van den Heuvel MP, Griffa A, Hagmann P, Rocha LM, Sporns O, Goñi J - Front Neuroinform (2014)

(A) Cortical distribution of Total MI, the total amount of predictability available about each ROI from the ROIs in the rest of the hemisphere. On the upper right are the top 8 anatomical areas arranged according to maximum Total MI of ROIs with each area (maximum Total MI of intra-area ROIs indicated by light gray bars; the minimum indicated by dark gray bars) while on the lower right are the bottom 8 anatomical areas arranged according to maximum Total MI of ROIs within each area (maximum Total MI of intra-area ROIs indicated by light gray bars; the minimum indicated by dark gray bars). (B) Cortical distribution of Euclidean Coupling Range, the neighbor number at which Euclidean Seed-Environment MI drops below a threshold of 0.3 bits (see text for details). On the upper right are the top 8 anatomical areas arranged according to maximum Euclidean Coupling Range of ROIs with each area [light and dark gray bars indicating maximum and minimum values as in (A)] while on the lower right are the bottom 8 anatomical areas arranged according to maximum Euclidean Coupling Range of ROIs with each area [light and dark gray bars indicating maximum and minimum values as in (A)]. (C) Scatter plot of Total MI vs. Euclidean Coupling Range for left and right hemisphere ROIs. A few ROIs are labeled with the names of their corresponding anatomical areas.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4109611&req=5

Figure 4: (A) Cortical distribution of Total MI, the total amount of predictability available about each ROI from the ROIs in the rest of the hemisphere. On the upper right are the top 8 anatomical areas arranged according to maximum Total MI of ROIs with each area (maximum Total MI of intra-area ROIs indicated by light gray bars; the minimum indicated by dark gray bars) while on the lower right are the bottom 8 anatomical areas arranged according to maximum Total MI of ROIs within each area (maximum Total MI of intra-area ROIs indicated by light gray bars; the minimum indicated by dark gray bars). (B) Cortical distribution of Euclidean Coupling Range, the neighbor number at which Euclidean Seed-Environment MI drops below a threshold of 0.3 bits (see text for details). On the upper right are the top 8 anatomical areas arranged according to maximum Euclidean Coupling Range of ROIs with each area [light and dark gray bars indicating maximum and minimum values as in (A)] while on the lower right are the bottom 8 anatomical areas arranged according to maximum Euclidean Coupling Range of ROIs with each area [light and dark gray bars indicating maximum and minimum values as in (A)]. (C) Scatter plot of Total MI vs. Euclidean Coupling Range for left and right hemisphere ROIs. A few ROIs are labeled with the names of their corresponding anatomical areas.
Mentions: Figure 4A shows Total MI, or total amount of predictability available about the activity of each ROI given the rest of ROIs in the hemisphere (note that this measure does not depend on choice of distance metric). In addition, we show the distribution of Total MI in different anatomical areas. As described in section MRI Data, ROIs in each hemisphere are grouped into 34 larger-scale “anatomical areas” that correspond to the FreeSurfer parcellation (Desikan et al., 2006). The bar chart on the upper right of the cortical Total MI plot shows the top 8 anatomical areas arranged according to maximum Total MI of ROIs within each area (maximum Total MI of ROIs in each area indicated by light gray bars; the minimum indicated by dark gray bars). The areas with the 8 largest maximum Total MIs are lateral occipital, lingual, precuneus, pericalcarine, superior parietal, inferior parietal, cuneus, and isthmus cingulate. The bar chart on the lower right of the cortical Total MI plot shows the lowest 8 anatomical areas arranged according to maximum Total MI of ROIs within each area (maximum Total MI of ROIs within each area indicated by light gray bars; the minimum indicated by dark gray bars). The areas with the 8 lowest maximum Total MIs are posterior cingulate, banks of the superior temporal sulcus (bankssts), lateral orbitofrontal, paracentral, temporal pole, entorhinal, frontral pole, and parahippocampal.

Bottom Line: We look at how these measures scale when larger spatial regions as well as larger connectome sub-networks are considered.We also find a set of connectome regions that are both internally integrated and coupled to the rest of the brain, and which resemble previously reported resting-state networks.Finally, we argue that information-theoretic measures are useful for characterizing the functional organization of the brain at multiple scales.

View Article: PubMed Central - PubMed

Affiliation: Department of Informatics, School of Informatics and Computing, Indiana University Bloomington, IN, USA ; Instituto Gulbenkian de Ciência Oeiras, Portugal.

ABSTRACT
The human brain displays heterogeneous organization in both structure and function. Here we develop a method to characterize brain regions and networks in terms of information-theoretic measures. We look at how these measures scale when larger spatial regions as well as larger connectome sub-networks are considered. This framework is applied to human brain fMRI recordings of resting-state activity and DSI-inferred structural connectivity. We find that strong functional coupling across large spatial distances distinguishes functional hubs from unimodal low-level areas, and that this long-range functional coupling correlates with structural long-range efficiency on the connectome. We also find a set of connectome regions that are both internally integrated and coupled to the rest of the brain, and which resemble previously reported resting-state networks. Finally, we argue that information-theoretic measures are useful for characterizing the functional organization of the brain at multiple scales.

No MeSH data available.