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Parcellating speech networks using connectivity and multivariate meta-analysis

Creative Commons 'BY' version 4.0 license

A densely interconnected patchwork of cortical areas tiles the brain, balancing the integration and segregation of functions. The eminent strategy for charting the functions of this landscape has involved pinning tightly controlled behavioral tasks onto large and often isolated patches of cortex in piecemeal. Recent developments have made it possible to study the organization of this rich functional landscape from the bottom-up, by mapping the connectivity networks that underpin brain areas situated within larger functional regions. At the same time, the availability of large databases that aggregate published functional neuroimaging work make it possible to infer the functions of such connectivity-defined areas from a much broader behavioral space than can be accessed by any individual study. In the first study of the present work, this bottom-up approach was leveraged to elucidate functional organization around the planum temporale (PT), an anatomical region that has been shown to be critical to speech production, but which has also been associated with a variety of other functions in functional neuroimaging studies. Functional connectivity estimated from multiecho resting state data (N =137) was used to map areas within the posterior perisylvian zone that functional neuroimaging studies have associated with the PT. A deliberate parcellation of this zone was produced by forming cluster ensembles from complementary unsupervised learning algorithms that produced reliable parcellations (12 clustering approaches were tested for their reliability). The resulting parcellation was well-aligned with observer-independent architectonic work, and even outperformed several popular atlases when used to classify external data. Registering the networks and areas within this parcellation to published functional neuroimaging work revealed that the functional zone associated with the PT was comprised of multiple speech areas, including an area involved in rehearsal and an area involved in production. Further, multiple areas were associated with receptive speech, auditory, and sensorimotor processing. At a broad level, a second study tested the extent to which there can be agreement between areas defined from the bottom-up based on connectivity data, and functional areas embedded in published neuroimaging work. That is, a parcellation of temporal and inferior parietal cortex based on structural connectivity (N = 70) was compared to a parcellation resulting from the same clustering approach adapted to brain-behavior associations (i.e., meta-analyses of behaviors). This functional parcellation carved out areas with similar behavioral profiles and was implemented in the service of localizing areas involved in speech perception. Prior meta-analytic studies with the same goal have used sample sizes now known to be insufficient, produced incompatible results, and failed to consider whether speech responsive areas are involved in other functions. Clustering was performed over lower-dimensional functional networks extracted from brain-behavior associations. Auditory and speech processes were robustly distinguished irrespective of how many functional networks were defined. A more optimal set of functional networks showed evidence of a posteriorly directed speech processing hierarchy that implicated an area in ventral superior temporal gyrus, posterior to auditory cortex, in speech sound analysis. The functional parcellation isolated areas along this speech hierarchy and captured the extent to which they were shared across functional networks. Overall, there was significant spatial correspondence between the functional and structural parcellations, and the parcel associated with speech sound processing showed the best fit to structural connectivity data. Structural data indicated that this parcel could be distinguished based on its strong connectivity along the middle longitudinal fasciculus. A third study investigated a more targeted hypothesis about the role of pMTG in error correction. The results of this study helped better characterize the function of one of two areas from the functional parcellation presented in the second study that were both associated with the pMTG, but difficult to functionally distinguish in a precise way. Previous work has demonstrated suggestive evidence of internal error detection and correction in left posterior middle temporal gyrus (pMTG) on the basis that this area tended toward showing a stronger response when potential speech errors (i.e., not realized) are biased towards nonwords compared to words. Building on this prior work, an experiment was designed introducing novel tongue twister stimuli that attempted to further tax internal error correction and detection mechanisms by biasing potential speech errors towards taboo words. Although the pMTG demonstrated significantly greater response to taboo words than neutral words in a large sample of participants (N=40), other areas also showed an effect. Behavioral associations in the wider neuroimaging literature were used to better understand the functional significance of activity outside the pMTG, demonstrating that only activity within this area was likely to signal word-level processing, and therefore explain the internal error correction mechanism investigated. Taken together, these studies present a more nuanced description of the functional and structural networks underpinning the speech system and point to more specific functions that these networks may support.

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