Low frequency fluctuations reveal integrated and segregated processing among the cerebral hemispheres

Abstract

Resting-state functional magnetic resonance imaging (fMRI) has provided a novel approach for examining interhemispheric interaction, demonstrating a high degree of functional connectivity between homotopic regions in opposite hemispheres. However, heterotopic resting-state functional connectivity (RSFC) remains relatively uncharacterized. In the present study, we examine non-homotopic regions, characterizing heterotopic RSFC and comparing it to intrahemispheric RSFC, to examine the impact of hemispheric separation on the integration and segregation of processing in the brain. Resting-state fMRI scans were acquired from 59 healthy participants to examine inter-regional correlations in spontaneous low frequency fluctuations in BOLD signal. Using a probabilistic atlas, we correlated probability-weighted time series from 112 regions (56 per hemisphere) distributed throughout the entire cerebrum. We compared RSFC for pairings of non-homologous regions located in different hemispheres (heterotopic connectivity) to RSFC for the same pairings when located within hemisphere (intrahemispheric connectivity). For positive connections, connectivity strength was greater within each hemisphere, consistent with integrated intrahemispheric processing. However, for negative connections, RSFC strength was greater between the hemispheres, consistent with segregated interhemispheric processing. These patterns were particularly notable for connections involving frontal and heteromodal regions. The distribution of positive and negative connectivity was nearly identical within and between the hemispheres, though we demonstrated detailed regional variation in distribution. We discuss implications for leading models of interhemispheric interaction. The future application of our analyses may provide important insight into impaired interhemispheric processing in clinical and aging populations.

Figure 1. (a) Regional masks

A total of 112 regional masks (56 in each hemisphere) comprising the entire cerebrum were generated from the Harvard–Oxford Structural Atlas, a validated probabilistic atlas that divides each hemisphere into regions corresponding to portions of cortical gyri and subcortical gray matter nuclei. Atlas-derived values corresponding to each voxel's probability of inclusion in a given region were used to derive probability-weighted time series for all 112 regions. For visualization, all three-dimensional reconstructions are thresholded to include voxels with >25% probability of inclusion in a given region.(Reproduced from Stark et al., 2008 with permission from the Society for Neuroscience © 2008). (b) Brain schematic. Intrahemispheric connections are defined as those between distinct anatomical regions (A, B) located within the same hemisphere (LL = regions A and B are in the left hemisphere; RR = regions A and B are in the right hemisphere). Heterotopic connections are defined as those between distinct anatomical regions located in opposite hemispheres (LR = region A is in the left hemisphere and B in right; RL = region A is in the right hemisphere and B in left). To determine the impact of interhemispheric separation, we contrasted intrahemispheric and heterotopic connectivity (LL vs. LR, LL vs. RL, RR vs. LR, RR vs. RL).

Figure 2. Differences in mean connectivity strengths

In order to test for differences in the connectivity strength of intrahemispheric versus heterotopic RSFC, for each participant, we first calculated the mean connectivity strength across eligible regional pairings (positive and negative separately) for each of the four hemispheric configurations (LL, LR, RL, RR). For both positive and negative connectivity, we then carried out pairwise t-tests (paired variable = participant; degrees of freedom = 58) to examine differences in the mean RSFC strength between the hemispheric configurations. Intrahemispheric configurations demonstrated greater positive connectivity than heterotopic configurations (LL > RL: p < 1.0 × 10^-26; LL > LR: p < 1.0 × 10^-25; RR > LR: p < 1.0 × 10^-27; RR > RL: p < 1.0 × 10^-25), whereas heterotopic configurations demonstrated greater negative connectivity than their corresponding intrahemispheric configurations (RL > LL: p < 1.0 × 10^-19; LR > LL: p < 1.0 × 10^-10; RL > RR: p < 1.0 × 10^-10; LR > RR: p < 1.0 × 10^-11). This figure also demonstrates within-hemisphere comparisons (i.e., LL>RR and RR>LL). Note: (1) Eligible regional pairings are defined as those for which at least one of the four possible hemispheric configurations was significantly connected (p < 0.05, Bonferroni corrected; positive or negative), (2) In order to facilitate visual comparison with positive connectivity strength, negative connectivity strengths were multiplied by -1, so that larger values for both positive and negative indicate greater connectivity strength.

Figure 3. Intrahemispheric versus heterotopic RSFC strength

The relative dominance index (RDI) was developed to compare intrahemispheric versus heterotopic RSFC strength at the level of each individual connection. For each eligible regional pairing that was significantly connected in at least one of the hemispheric configurations, we carried out paired t-tests comparing each intrahemispheric configuration with each heterotopic configuration (Bonferroni corrected). Then, for each regional pairing, t-test results were used to calculate: (1) the intrahemispheric RDI, defined as the number of intrahemispheric configurations that were greater than their heterotopic counterparts ([LL>LR] + [LL>RL] + [RR>LR] + [RR>RL]), and (2) the heterotopic RDI, defined as the number of heterotopic configurations that were greater than their intrahemispheric counterparts ([LR>LL] + [RL>LL] + [LR>RR] + [RL>RR]). RDI analyses demonstrated greater dominance for positive connectivity among intrahemispheric connections, and greater dominance for negative connectivity among heterotopic connections.

Figure 4. Localizing intrahemispheric and heterotopic dominance: Lobar classification

Regional pairings exhibiting either intrahemispheric dominance (intrahemispheric RDI of 1 or higher) or heterotopic dominance (heterotopic RDI of 1 or higher) were sorted based upon lobe (F=frontal, T=temporal, P=parietal, O=occipital, SC = subcortical). Positively and negatively connected pairings are illustrated separately, as intrahemispheric dominance was primarily noted for positively connected pairings, and heterotopic dominance was primarily noted for negatively connected pairings. These results indicate that regional pairings were stronger within the hemispheres for positive connections and stronger between the hemispheres for negative connections.

Figure 5. Localizing intrahemispheric and heterotopic dominance: Hierarchical classification

Regional pairings exhibiting either intrahemispheric dominance (intrahemispheric RDI of 1 or higher) or heterotopic dominance (heterotopic RDI of 1 or higher) were sorted based upon functional hierarchy (P = primary sensory-motor areas, U = unimodal association areas, H = heteromodal association areas, PL = paralimbic areas, L = limbic areas, SC = subcortical). Positively and negatively connected pairings are illustrated separately, as intrahemispheric dominance was primarily noted for positively connected pairings, and heterotopic dominance was primarily noted for negatively connected pairings.

Figure 6. Distribution of significant connections: Lobar and hierarchical classifications

For each of the two regional classification systems (lobar, hierarchical), we depict the regional distribution of the percentage of positive, negative, and non-significant connections (homotopic connections excluded) across the four hemispheric configurations (LL, LR, RL, RR; 1,540 connections per configuration). Highly consistent patterns of connectivity were observed across the four hemispheric configurations, regardless of classification system.