An algorithmic method for functionally defining regions of interest in the ventral visual pathway

In a widely used functional magnetic resonance imaging (fMRI) data analysis method, functional regions of interest (fROIs) are handpicked in each participant using macroanatomic landmarks as guides, and the response of these regions to new conditions is then measured. A key limitation of this standard handpicked fROI method is the subjectivity of decisions about which clusters of activated voxels should be treated as the particular fROI in question in each subject. Here we apply the Group-Constrained Subject-Specific (GSS) method for defining fROIs, recently developed for identifying language fROIs (Fedorenko et al., 2010), to algorithmically identify fourteen well-studied category-selective regions of the ventral visual pathway (Kanwisher, 2010). We show that this method retains the benefit of defining fROIs in individual subjects without the subjectivity inherent in the traditional handpicked fROI approach. The tools necessary for using this method are available on our website (http://web.mit.edu/bcs/nklab/GSS.shtml).Ellison Medical Foundatio

Representational similarity precedes category selectivity in the developing ventral visual pathway

© 2019 Many studies have investigated the development of face-, scene-, and body-selective regions in the ventral visual pathway. This work has primarily focused on comparing the size and univariate selectivity of these neural regions in children versus adults. In contrast, very few studies have investigated the developmental trajectory of more distributed activation patterns within and across neural regions. Here, we scanned both children (ages 5–7) and adults to test the hypothesis that distributed representational patterns arise before category selectivity (for faces, bodies, or scenes) in the ventral pathway. Consistent with this hypothesis, we found mature representational patterns in several ventral pathway regions (e.g., FFA, PPA, etc.), even in children who showed no hint of univariate selectivity. These results suggest that representational patterns emerge first in each region, perhaps forming a scaffold upon which univariate category selectivity can subsequently develop. More generally, our findings demonstrate an important dissociation between category selectivity and distributed response patterns, and raise questions about the relative roles of each in development and adult cognition

Auditory feedback control mechanisms do not contribute to cortical hyperactivity within the voice production network in adductor spasmodic dysphonia

Adductor spasmodic dysphonia (ADSD), the most common form of spasmodic dysphonia, is a debilitating voice disorder characterized by hyperactivity and muscle spasms in the vocal folds during speech. Prior neuroimaging studies have noted excessive brain activity during speech in ADSD participants compared to controls. Speech involves an auditory feedback control mechanism that generates motor commands aimed at eliminating disparities between desired and actual auditory signals. Thus, excessive neural activity in ADSD during speech may reflect, at least in part, increased engagement of the auditory feedback control mechanism as it attempts to correct vocal production errors detected through audition. To test this possibility, functional magnetic resonance imaging was used to identify differences between ADSD participants and age-matched controls in (i) brain activity when producing speech under different auditory feedback conditions, and (ii) resting state functional connectivity within the cortical network responsible for vocalization. The ADSD group had significantly higher activity than the control group during speech (compared to a silent baseline task) in three left-hemisphere cortical regions: ventral Rolandic (sensorimotor) cortex, anterior planum temporale, and posterior superior temporal gyrus/planum temporale. This was true for speech while auditory feedback was masked with noise as well as for speech with normal auditory feedback, indicating that the excess activity was not the result of auditory feedback control mechanisms attempting to correct for perceived voicing errors in ADSD. Furthermore, the ADSD group had significantly higher resting state functional connectivity between sensorimotor and auditory cortical regions within the left hemisphere as well as between the left and right hemispheres, consistent with the view that excessive motor activity frequently co-occurs with increased auditory cortical activity in individuals with ADSD.First author draf

Connectivity precedes function in the development of the visual word form area

What determines the cortical location at which a given functionally specific region will arise in development? We tested the hypothesis that functionally specific regions develop in their characteristic locations because of pre-existing differences in the extrinsic connectivity of that region to the rest of the brain. We exploited the visual word form area (VWFA) as a test case, scanning children with diffusion and functional imaging at age 5, before they learned to read, and at age 8, after they learned to read. We found the VWFA developed functionally in this interval and that its location in a particular child at age 8 could be predicted from that child's connectivity fingerprints (but not functional responses) at age 5. These results suggest that early connectivity instructs the functional development of the VWFA, possibly reflecting a general mechanism of cortical development.National Institutes of Health (U.S.) (Grant F32HD079169)Eunice Kennedy Shriver National Institute of Child Health and Human Development (U.S.) (Grant F32HD079169)National Institutes of Health (U.S.) (Grant R01HD067312)Eunice Kennedy Shriver National Institute of Child Health and Human Development (U.S.) (Grant R01HD067312

Hemispheric Asymmetry in White Matter Connectivity of the Temporoparietal Junction with the Insula and Prefrontal Cortex

The temporoparietal junction (TPJ) is a key node in the brain's ventral attention network (VAN) that is involved in spatial awareness and detection of salient sensory stimuli, including pain. The anatomical basis of this network's right-lateralized organization is poorly understood. Here we used diffusion-weighted MRI and probabilistic tractography to compare the strength of white matter connections emanating from the right versus left TPJ to target regions in both hemispheres. Symmetry of structural connectivity was evaluated for connections between TPJ and target regions that are key cortical nodes in the right VAN (insula and inferior frontal gyrus) as well as target regions that are involved in salience and/or pain (putamen, cingulate cortex, thalamus). We found a rightward asymmetry in connectivity strength between the TPJ and insula in healthy human subjects who were scanned with two different sets of diffusion-weighted MRI acquisition parameters. This rightward asymmetry in TPJ-insula connectivity was stronger in females than in males. There was also a leftward asymmetry in connectivity strength between the TPJ and inferior frontal gyrus, consistent with previously described lateralization of language pathways. The rightward lateralization of the pathway between the TPJ and insula supports previous findings on the roles of these regions in stimulus-driven attention, sensory awareness, interoception and pain. The findings also have implications for our understanding of acute and chronic pains and stroke-induced spatial hemineglect

Common and Unique Representations in pFC for Place Attractiveness

Although previous neuroimaging research has identified overlapping correlates of subjective value across different reward types in the ventromedial pFC (vmPFC), it is not clear whether this “common currency” evaluative signal extends to the aesthetic domain. To examine this issue, we scanned human participants with fMRI while they made attractiveness judgments of faces and places—two stimulus categories that are associated with different underlying rewards, have very different visual properties, and are rarely compared with each other. We found overlapping signals for face and place attractiveness in the vmPFC, consistent with the idea that this region codes a signal for value that applies across disparate reward types and across both economic and aesthetic judgments. However, we also identified a subregion of vmPFC within which activity patterns for face and place attractiveness were distinguishable, suggesting that some category-specific attractiveness information is retained in this region. Finally, we observed two separate functional regions in lateral OFC: one region that exhibited a category-unique response to face attractiveness and another region that responded strongly to faces but was insensitive to their value. Our results suggest that vmPFC supports a common mechanism for reward evaluation while also retaining a degree of category-specific information, whereas lateral OFC may be involved in basic reward processing that is specific to only some stimulus categories

The role of motion in the neural representation of social interactions in the posterior temporal cortex

Humans are an inherently social species, with multiple focal brain regions sensitive to various visual social cues such as faces, bodies, and biological motion. More recently, research has begun to investigate how the brain responds to more complex, naturalistic social scenes, identifying a region in the posterior superior temporal sulcus (SI-pSTS; i.e., social interaction pSTS), among others, as an important region for processing social interaction. This research, however, has presented images or videos, and thus the contribution of motion to social interaction perception in these brain regions is not yet understood. In the current study, 22 participants viewed videos, image sequences, scrambled image sequences and static images of either social interactions or non-social independent actions. Combining univariate and multivariate analyses, we confirm that bilateral SI-pSTS plays a central role in dynamic social interaction perception but is much less involved when ‘interactiveness’ is conveyed solely with static cues. Regions in the social brain, including SI-pSTS and extrastriate body area (EBA), showed sensitivity to both motion and interactive content. While SI-pSTS is somewhat more tuned to video interactions than is EBA, both bilateral SI-pSTS and EBA showed a greater response to social interactions compared to non-interactions and both regions responded more strongly to videos than static images. Indeed, both regions showed higher responses to interactions than independent actions in videos and intact sequences, but not in other conditions. Exploratory multivariate regression analyses suggest that selectivity for simple visual motion does not in itself drive interactive sensitivity in either SI-pSTS or EBA. Rather, selectivity for interactions expressed in point-light animations, and selectivity for static images of bodies, make positive and independent contributions to this effect across the LOTC region. Our results strongly suggest that EBA and SI-pSTS work together during dynamic interaction perception, at least when interactive information is conveyed primarily via body information. As such, our results are also in line with proposals of a third visual stream supporting dynamic social scene perception

Individual-subject Functional Localization Increases Univariate Activation but Not Multivariate Pattern Discriminability in the "Multiple-demand" Frontoparietal Network.

The frontoparietal "multiple-demand" (MD) control network plays a key role in goal-directed behavior. Recent developments of multivoxel pattern analysis (MVPA) for fMRI data allow for more fine-grained investigations into the functionality and properties of brain systems. In particular, MVPA in the MD network was used to gain better understanding of control processes such as attentional effects, adaptive coding, and representation of multiple taskrelevant features, but overall low decoding levels have limited its use for this network. A common practice of applying MVPA is by investigating pattern discriminability within a ROI using a template mask, thus ensuring that the same brain areas are studied in all participants. This approach offers high sensitivity but does not take into account differences between individuals in the spatial organization of brain regions. An alternative approach uses independent localizer data for each subject to select the most responsive voxels and define individual ROIs within the boundaries of a group template. Such an approach allows for a refined and targeted localization based on the unique pattern of activity of individual subjects while ensuring that functionally similar brain regions are studied for all subjects. In the current study, we tested whether using individual ROIs leads to changes in decodability of task-related neural representations as well as univariate activity across the MD network compared with when using a group template. We used three localizer tasks to separately define subject-specific ROIs: spatial working memory, verbal working memory, and a Stroop task. We then systematically assessed univariate and multivariate results in a separate rule-based criterion task. All the localizer tasks robustly recruited the MD network and evoked highly reliable activity patterns in individual subjects. Consistent with previous studies, we found a clear benefit of the subject-specific ROIs for univariate results from the criterion task, with increased activity in the individual ROIs based on the localizers' data, compared with the activity observed when using the group template. In contrast, there was no benefit of the subject-specific ROIs for the multivariate results in the form of increased discriminability, as well as no cost of reduced discriminability. Both univariate and multivariate results were similar in the subject-specific ROIs defined by each of the three localizers. Our results provide important empirical evidence for researchers in the field of cognitive control for the use of individual ROIs in the frontoparietal network for both univariate and multivariate analysis of fMRI data and serve as another step toward standardization and increased comparability across studies.This work was funded by a Royal Society Dorothy Hodgkin Research Fellowship (United Kingdom) to Yaara Erez (DH130100). Sneha Shashidhara was supported by a scholarship from the Gates Cambridge Trust, Cambridge, United Kingdom. Floortje Spronkers was supported by an Erasmus+ Traineeship grant and a Stichting A.S.C. Academy grant