Defining functional SMA and pre-SMA subregions in human MFC using resting state fMRI: Functional connectivity-based parcellation method

Abstract

Noninvasive parcellation of the human cerebral cortex is an important goal for understanding and examining brain functions. Recently, the patterns of anatomical connections using diffusion tensor imaging (DTI) have been used to parcellate brain regions. Here, we present a noninvasive parcellation approach that uses “functional fingerprints” obtained by correlation measures on resting-state functional Magnetic Resonance Imaging (fMRI) data to parcellate brain regions. In other terms, brain regions are parcellated based on the similarity of their connection – as reflected by correlation during resting-state – to the whole brain. The proposed method was used to parcellate the medial frontal cortex (MFC) into supplementary motor areas (SMA) and pre-SMA subregions. In agreement with anatomical landmark-based parcellation, we find that functional fingerprint clustering of the MFC results in anterior and posterior clusters. The probabilistic maps from 12 subjects showed that the anterior cluster is mainly located rostral to the vertical commissure anterior (VCA) line, whereas the posterior cluster is mainly located caudal to VCA line, suggesting the homologues of pre-SMA and SMA. The functional connections from the putative pre-SMA cluster were connected to brain regions which are responsible for complex/cognitive motor control, whereas those from the putative SMA cluster were connected to brain regions which are related to the simple motor control. These findings demonstrate the feasibility of the functional connectivity-based parcellation of the human cerebral cortex using resting state fMRI.

Large-Scale Meta-Analysis of Human Medial Frontal Cortex Reveals Tripartite Functional Organization

“…We first clustered MFC voxels into functionally separable regions at several spatial scales based on their coactivation across studies with the rest of the brain (Kober et al, 2008;Toro et al, 2008;Robinson et al, 2010). In contrast to cytoarchitechtonic and connectivity-based parcellations, the present analysis identified clusters with distinct signatures of activation across a wide range of psychological manipulations.…”

Distinct Regions within Medial Prefrontal Cortex Process Pain and Cognition

“…Anteriorly, the dACC is divided from the rACC by the genu of the corpus callosum. Dorsal to the dACC is the pre-SMA, bounded posteriorly by a vertical line extending from the anterior commissure and bounded anteriorly by a vertical line extending from the genu of the corpus callosum (Picard and Strick, 2001;Kim et al, 2010).…”

“…In pCgS ϩ subjects, activity dorsal to the pCgS is considered to fall within the pre-SMA region, whereas within pCgS Ϫ subjects, activity dorsal to the cingulate sulcus is considered pre-SMA (Kim et al, 2010). Furthermore, the presence of a pCgS increases the amount of cortical volume of the dACC relative to that of the pre-SMA (Fig.…”

Feature-reduction and semi-simulated data in functional connectivity-based cortical parcellation

“…The use of restingstate functional magnetic resonance imaging (rs-fMRI) has led to a number of studies in recent years that have investigated this functional 'connectional fingerprint' in relation to cortical parcellation [11][12][13][14][15][16][17][18][19][20][21][22] . By measuring the cross-correlation of low-frequency blood oxygenation level-dependent fluctuations between brain voxels while subjects are at rest [23] , one can calculate the functional connectivity between any pair of voxels.…”

“…This method using rs-fMRI to perform cortical parcellation has provided finegrained functional subdivisions of the anterior cingulate cortex [11] , precuneus [24,25] , thalamus [22] , basal ganglia [13] , lateral parietal cortex [14] , medial frontal cortex [12,18] , and insular cortex [15,16] , as well as the subdivision of the whole brain [17,26] . The fine-grained functional subdivisions of brain regions can be further used to investigate the organization Xiaoguang Tian, et al Feature-reduction and semi-simulated data in functional connectivity-based cortical parcellation 335 analysis were more reliable.…”