Intrinsic Connectivity Networks: the adult form
In my last two posts I introduced the concept of ICNs and the form they take over developmental time-frame. This post focuses on the most common and consistent ICNs that have been found in the adult humans. To recap, ICNs are found by Independent Component Analysis (ICA) of Resting state functional connectivity MRI (rs-fcMRI) and the number and components of ICNs have been found to vary over the developmental time-frame.
Different studies find different number of components/ICNs and some of the variance is due to different methods used to estimate an delineate the number of components. For eg., in one study multiple methods were used and they led to estimates ranging from 8 to 20 + for the number of components using the same rs-fcMRI scan.
The same study listed the following ICNs out of which 4 are clearly a result of artifact and not true ICN’s.
We sorted the 20 components into two broad classes – functionally relevant components (i.e., ICNs) and scanner/physiological artifactual components – based on visual inspection of each component’s spatial profile (e.g., biological plausibility, comparability to patterns previously reported in ICA-based studies) and timeseries-based power spectrum profile (e.g., whether or not signals < 0.1Hz were prominent). We noted 4 components that appeared to be associated with artifactual sources: cerebrospinal fluid (IC01), white matter (IC03), head motion (IC05), and large vessels (IC16). These four components accounted for 39.4% of the total variance in the resting state fMRI data. Several functionally relevant components consistent with prior reports were also revealed in our results. Two components (IC04 and IC15) are involved in vision. IC09 combines visual and motor regions including the occipital pole, superior parietal cortex and precentral gyrus. IC13 includes brain regions such as the primary motor cortex and primary and association auditory cortices. Several components include regions related to various high-order brain functions: fronto-parietal networks corresponding to cognition and language functions (IC07 and IC19), medial-frontal including anterior cingulate and paracingulate associated with executive control (IC08) and three “default mode” networks (IC10, IC12 and IC14). We found six other components that are rarely reported or investigated systematically corresponding to the cerebellum (IC11 and IC18), a motor-striatal component (IC02), a ventromedial prefrontal component (IC17), a brainstem component (IC06), and a temporal-lobe component (IC20). Of note, we found several components that exhibit anticorrelation relationships between regions (IC04, IC08, IC14 and IC15). In particular, the executive and attentional network (IC08) and the “default mode” network (IC14) demonstrated prominent anti-correlation relationships (Figure S1).
We detected the classic “default mode” network, although in the form of three components that we interpret as sub-networks. The first is a medial-prefrontal subsystem (IC12), the second is a posterior cingulate/precuneus subsystem (IC10), and the third is a temporal subsystem (IC14). These three subsystems mainly overlap in the posterior cingulate cortex and medial prefrontal cortex (Figure S2). As we discuss below, the existence of three overlapping but differentiable sub-networks may account for some of the variations in the specific spatial distributions or functional specialization of the “default mode” network reported across ICA studies (Buckner et al., 2008; Harrison et al., 2008).
In another famous study by Damoiseaux they found 10 components as follows:
The 10 components showed low-frequency variations in time (mean peak frequency: 0.015 Hz; range 0.005–0.030 Hz) and can be described as follows. Fig. 1 A and A’ shows a pattern that consists predominantly of the peristriate area, and lateral and superior occipital gyrus [Brodmann area (BA) 19], which are areas recognized as part of the visual cortex. Fig. 1 B and B’ shows a cluster consisting of the prefrontal (BA 11), anterior cingulate (BA 32), posterior cingulate (BA 23’31), the inferior temporal gyrus (BA 20’37), and the superior parietal region (BA 7), known as the default-mode network as described by Raichle et al. (18) and Greicius et al. (17). Hippocampal involvement in this component, as described by Greicius et al. (22), is not found. Fig. 1 C, C’, D, and D’ shows components that are predominantly in the left (C and C’) and right (D and D’) hemispheres, the middle frontal and orbital (BA ‘6’9’10), superior parietal (BA 7’40), middle temporal gyrus (BA 21), and the posterior cingulate (BA 23’31; C and C’ only). These are the only components that show strong lateralization and are areas known to be involved in memory function. Fig. 1 E and E’ encompasses part of the striate and parastriate (BA 17’18). The visual cortex is apparent in two separate components. The more lateral visual areas are in Fig. 1 A and A’, and the more medial visual areas are in this figure. Fig. 1 F and F’ shows the pre- and postcentral gyri (BA 1’2’3’4) in one component, representing the motor and sensory network. Fig. 1 G and G’ shows the superior temporal (BA 22) area as the main element of this spatial map. Involvement of the cingulate (BA 23) and superior frontal (BA 9’10) areas is also seen. This cluster of brain regions bears a strong resemblance to the occipitotemporal pathway (ventral stream). Fig. 1 H and H’ involves mainly the superior parietal cortex (BA 7) with additional involvement in the occipitotemporal (BA 37) and precentral (BA 4) areas. Fig. 1 I and I’ involves the superior temporal (BA 22) and insular and postcentral cortex (BA 1’2), which are areas acknowledged to represent the auditory cortex.
To simplify things I propose the following eight ICNs listed in the order of strength/developmental unfolding/ evolutionary precedence, following my proven eight stage evo-devo model. All ICNs referred below are those in study by Zuo et al. unless otherwise stated.
- Visual (IC4) fig 1A in Damoeseoux- occipital
- Sensorimotorfig 1 F in Damoseousx -pre-post central gyrus
- Auditory/memory (IC13) fig 1 I -auditory/temporal cortex
- Language/spatial (IC7/IC19) Fig 1C and Fig 1D of damoseoux – fronto-parietal, strongly lateralized in two hemispheres
- SALience(also Known as SAL) Anterior Insula+ anterior Cingulate
- Balance and co-ordination (IC 11) – Cerebellum
- Default Mode Network(IC10, IC12, IC14) , Fig 1 B- Medial frontal, posterior cingulate, Angular gyrus
- Executive Control Network (IC8)Fig 1J – dorsolateral, prefrontal + sup parietal
Some may doubt why I include CERebellum ICN as a basic ICN, but it has been shown that cerebellum not only provides distinct components to existing ICNs , there is an separate Cerebellum ICN also. For eg. Peterson et al used a Cerebellar component in their analysis of how ICNs change over developmental time-frame.
A Structural Covariance Networks (SCNs) based approach to delineate the devlopemental time course of networks in brain comes closest to the eight stage /networks elaborated above. The study is by Zielenksi et al and use seeds from well known ICNs to grow SCNs in children, adolescents and adults. These are the eight SCNs/ICNs (seeds given in brackets) they studied :
- Visual (ccalcerine sulcus)
- Motor (pre-central gyrus)
- Auditory (Heschel’s gyrus)
- Syntax (Inferior Frontal Gyrus)
- Semantics (temporal pole)
- SALience (Fronto Insula)
- DMN (Angular Gyrus)
- ECN (DLPFC)
I am convinced that there are only 8 basic ICNs/SCNs with perhaps the DMN split into 3 sub-networks (as is usual for stage 7) and Speech/syntax split or lateralizaed into 2 distinct ICNs. (as is sometimes the case with stage 4) . If you come across other such basic ICNs do let me know.
Zuo, X., Kelly, C., Adelstein, J., Klein, D., Castellanos, F., & Milham, M. (2010). Reliable intrinsic connectivity networks: Test–retest evaluation using ICA and dual regression approach NeuroImage, 49 (3), 2163-2177 DOI: 10.1016/j.neuroimage.2009.10.080
Damoiseaux, J., Rombouts, S., Barkhof, F., Scheltens, P., Stam, C., Smith, S., & Beckmann, C. (2006). Consistent resting-state networks across healthy subjects Proceedings of the National Academy of Sciences, 103 (37), 13848-13853 DOI: 10.1073/pnas.0601417103
Fair, D., Cohen, A., Power, J., Dosenbach, N., Church, J., Miezin, F., Schlaggar, B., & Petersen, S. (2009). Functional Brain Networks Develop from a “Local to Distributed” Organization PLoS Computational Biology, 5 (5) DOI: 10.1371/journal.pcbi.1000381
Zielinski, B., Gennatas, E., Zhou, J., & Seeley, W. (2010). Network-level structural covariance in the developing brain Proceedings of the National Academy of Sciences, 107 (42), 18191-18196 DOI: 10.1073/pnas.1003109107
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