Neocortex

Functional connectivity analysis was performed by a meta-analysis of published functional imaging results. The concept behind mapping functional connectivity via meta-analysis originates from the notion that functional connectivity should represent the correlation of spatially removed neurophysiologic events, which implies that functionally connected regions should coactivate above chance in functional imaging studies.
This concept of meta-analytic connectivity modeling (MACM) was first used to investigate functional connectivity based on the frequency distributions of concurrent activation foci (Koski and Paus, 2000 (link)). Following the emergence of databases on functional neuroimaging results (Fox and Lancaster, 2002 (link); Laird et al., 2009a ), this approach was extended to provide voxelwise co-occurrence maps across the whole brain (Toro et al., 2008 (link)). The concept of MACM has then been integrated with the activation likelihood estimation (ALE) approach for quantitative meta-analysis (Turkeltaub et al., 2002 (link)) to yield functional connectivity maps of the human amygdala (Robinson et al., 2009 (link)). More recently, finally, the mapping of functional connectivity via coordinate-based meta-analysis has been validated by comparison to resting-state connectivity (Smith et al., 2009 (link)), showing very good concordance between both approaches.
Here, MACM was performed using the BrainMap database (www.brainmap.org), which contains a summary of the results for (at the time of analysis) ~6500 individual functional neuroimaging experiments. Given the high standardization of neuroimaging data reports and in particular the ubiquitous adherence to standard coordinate systems, the results reported in these studies can readily be compared to each other with respect to the location of significant activation. Using this broad pool of neuroimaging results, MACM can then be used to test for associations between activation probabilities of different areas. Importantly, this inference is performed independently of the applied paradigms or other experimental factors, but rather is solely based on the likelihood of observing activation in a target region [e.g., the premotor cortex (PMC)], given that activation is present within the seed area (e.g., OP 1 or OP 4). Results from such an analysis are therefore robust across many different experimental designs. Database-aided MACM that assesses the coactivation pattern of OP 1 and OP 4 as defined by their MPM representation across a large number of imaging studies should hence allow the delineation and comparison of their functional connectivity. However, functional connectivity per se only allows the delineation of interacting networks but not the causal influences therein. In practice, MACM was performed using the following approach. Studies causing activation within OP 1 or OP 4 were obtained through the BrainMap database. Criteria for retrieval were as follows: only fMRI and positron emission tomography studies in healthy subjects that reported functional mapping experiments containing a somatosensory or motor component were considered. Those investigating age, gender, disease, or drug effects were excluded. No further constraints (e.g., on acquisition and analysis details, experimental design, or stimulation procedures) were enforced. Hereby we tried to avoid any bias in the data, but rather pool across as many different studies as possible.
Experiments that activate OP 1 or OP 4 were identified by comparing the foci reported for each of the ~1500 eligible experiments (functional mapping experiments available at the time of analysis that contained a somatosensory or motor component) in the BrainMap database to the cytoarchitectonic location of these cortical fields in the same reference space. The experiments used for the analysis of the functional connectivity of OP 1 (S2) were defined by the fact that (following correction for coordinates reported according to the Talairach reference space) they featured at least one focus of activation within the volume of cortex histologically delineated as OP 1, but no activation within the histologically delineated volume of OP 4. Hereby, the experiments that activated OP 1 or OP 4 were objectively identified. That is, activation within our seed areas was assessed observer independently by comparing the coordinates reported for all studies within the BrainMap database to the anatomical location of cytoarchitectonically defined OP 1 and OP 4 within the same reference space, independent of how this activation was termed in the original publication. Hereby, we avoided any influence of the fact that various labels have been used for activation in the region, e.g., SII, parietal operculum, Brodmann’s area (BA) 43, BA 40, parietal cortex, or subcentral gyrus. Studies activating exclusively one of these two areas (either OP 1 or OP 4) were defined by at least one reported focus in the MPM representation of this area and the absence of any reported activation focus in the respective other area or, to increase specificity, a four voxel border zone between OP 1 and OP 4.
Given that OP 1 (S2) and OP 4 (PV) share a common border at which the face, hands, and feet are represented in either area, and acknowledging the fact that these two cortical fields are difficult to differentiate from each other functionally in nonhuman primates, the question evidently arises as to whether isolated activation in only one of these areas may be conceptually meaningful or most likely artificial. However, while S2 and PV tend to show concurrent activation in many experiments, there is already good evidence for differences in response properties between the various cortical fields on the parietal operculum of nonhuman primates (Robinson and Burton, 1980 (link); Hsiao et al., 1993 (link); Fitzgerald et al., 2004 (link), 2006a (link), 2006b (link)). Compared with electrophysiological experiments in monkeys, however, the range of tasks that may be assessed is considerably larger in human functional imaging experiments, including, in particular, experimental paradigms that investigate cognitive or affective influences on sensory-motor processing. It thus seems plausible that differences in response properties of opercular fields that have not yet been reported in monkeys may be unraveled in humans simply because the necessary paradigms are difficult to perform in animals. Moreover, differential response properties may manifest themselves as apparent shifts in somatotopic location in functional imaging data, in particular if differential contrasts between two conditions are considered. In this case, homogenous activation of both cortical fields by one condition may offset, leaving only an isolated peak of activation well within the cortical field that was more responsive to the other condition. This phenomenon, to which neurophysiologic mechanisms at the neuronal level may also contribute, has been discussed in great detail in a recent study by Burton et al. (2008b) (link). It is therefore very well conceivable that isolated activations within OP 1 or OP 4 are observed in human neuroimaging data despite their close proximity and the similarities in response characteristics.
It should be noted that the seeds representing OP 1 and OP 4, respectively, in the functional connectivity analysis were defined bilaterally. This approach was based on the observation that activation of the secondary somatosensory cortex is frequently bilateral, resulting in a much reduced and ultimately insufficient sample of studies reporting unilateral activation. These, however, would be required for a separate analysis of ipsilateral and contralateral connections.