441 research outputs found

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

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    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

    Localizing Pain Matrix and Theory of Mind networks with both verbal and non-verbal stimuli

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    Functional localizer tasks allow researchers to identify brain regions in each individual's brain, using a combination of anatomical and functional constraints. In this study, we compare three social cognitive localizer tasks, designed to efficiently identify regions in the "Pain Matrix," recruited in response to a person's physical pain, and the "Theory of Mind network," recruited in response to a person's mental states (i.e. beliefs and emotions). Participants performed three tasks: first, the verbal false-belief stories task; second, a verbal task including stories describing physical pain versus emotional suffering; and third, passively viewing a non-verbal animated movie, which included segments depicting physical pain and beliefs and emotions. All three localizers were efficient in identifying replicable, stable networks in individual subjects. The consistency across tasks makes all three tasks viable localizers. Nevertheless, there were small reliable differences in the location of the regions and the pattern of activity within regions, hinting at more specific representations. The new localizers go beyond those currently available: first, they simultaneously identify two functional networks with no additional scan time, and second, the non-verbal task extends the populations in whom functional localizers can be applied. These localizers will be made publicly available.National Institutes of Health (U.S.) (Grant 1R01 MH096914-01A1

    Introducing alternative-based thresholding for defining functional regions of interest in fMRI

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    In fMRI research, one often aims to examine activation in specific functional regions of interest (fROIs). Current statistical methods tend to localize fROIs inconsistently, focusing on avoiding detection of false activation. Not missing true activation is however equally important in this context. In this study, we explored the potential of an alternative-based thresholding (ABT) procedure, where evidence against the null hypothesis of no effect and evidence against a prespecified alternative hypothesis is measured to control both false positives and false negatives directly. The procedure was validated in the context of localizer tasks on simulated brain images and using a real data set of 100 runs per subject. Voxels categorized as active with ABT can be confidently included in the definition of the fROI, while inactive voxels can be confidently excluded. Additionally, the ABT method complements classic null hypothesis significance testing with valuable information by making a distinction between voxels that show evidence against both the null and alternative and voxels for which the alternative hypothesis cannot be rejected despite lack of evidence against the null

    Sound-induced enhancement of low-intensity vision: multisensory influences on human sensory-specific cortices and thalamic bodies relate to perceptual enhancement of visual detection sensitivity

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    Combining information across modalities can affect sensory performance. We studied how co-occurring sounds modulate behavioral visual detection sensitivity (d'), and neural responses, for visual stimuli of higher or lower intensity. Co-occurrence of a sound enhanced human detection sensitivity for lower-but not higher-intensity visual targets. Functional magnetic resonance imaging (fMRI) linked this to boosts in activity-levels for sensory-specific visual and auditory cortex, plus multisensory superior temporal sulcus (STS), specifically for a lower-intensity visual event when paired with a sound. Thalamic structures in visual and auditory pathways, the lateral and medial geniculate bodies, respectively (LGB, MGB), showed a similar pattern. Subject-by-subject psychophysical benefits correlated with corresponding fMRI signals in visual, auditory, and multisensory regions. We also analyzed differential "coupling" patterns of LGB and MGB with other regions in the different experimental conditions. Effective-connectivity analyses showed enhanced coupling of sensory-specific thalamic bodies with the affected cortical sites during enhanced detection of lower-intensity visual events paired with sounds. Coupling strength between visual and auditory thalamus with cortical regions, including STS, covaried parametrically with the psychophysical benefit for this specific multisensory context. Our results indicate that multisensory enhancement of detection sensitivity for low-contrast visual stimuli by co-occurring sounds reflects a brain network involving not only established multisensory STS and sensory-specific cortex but also visual and auditory thalamus

    In praise of tedious anatomy

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    Functional neuroimaging is fundamentally a tool for mapping function to structure, and its success consequently requires neuroanatomical precision and accuracy. Here we review the various means by which functional activation can be localized to neuroanatomy and suggest that the gold standard should be localization to the individual’s or group’s own anatomy through the use of neuroanatomical knowledge and atlases of neuroanatomy. While automated means of localization may be useful, they cannot provide the necessary accuracy, given variability between individuals. We also suggest that the field of functional neuroimaging needs to converge on a common set of methods for reporting functional localization including a common “standard” space and criteria for what constitutes sufficient evidence to report activation in terms of Brodmann’s areas

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

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    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

    Multimodal MRI characterization of visual word recognition: an integrative view

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    228 p.The ventral occipito-temporal (vOT) association cortex contributes significantly to recognize different types of visual patterns. It is widely accepted that a subset of this circuitry, including the visual word form area (VWFA), becomes trained to perform the task of rapidly identifying word forms. An important open question is the computational role of this circuitry: To what extent is part of a bottom-up hierarchical processing of information on visual word recognition and/or is involved in processing top-down signals from higher-level language regions. This doctoral dissertation thesis proposal is aimed at characterizing the vOT reading circuitry using behavioral, functional, structural and quantitative MRI indexes, and linking its computations to the other two important regions within the language network: the posterior parietal cortex (pPC) and the inferior frontal gyrus (IFG). Results revealed that two distinct word-responsive areas can be segregated in the vOT: one responsible for visual feature extraction that is connected to the intraparietal sulcus via the vertical occipital fasciculus and a second one responsible for semantic processing that is connected to the angular gyrus via the posterior arcuate fasciculus and to the IFG via the anterior arcuate fasciculus. Importantly, reading behavior was predicted by functional activation in regions identified along the vOT, pPC and IFG, as well as by structural properties of the white matter fiber tracts linking them. The present work constitutes a critical step in the creation of a highly detailed characterization of the early stages of reading at the individual-subject level and to establish a baseline model and parameter range that might serve to clarify functional and structural differences between typical, poor and atypical readers.BCBL: basque center on cognition, brain and languag

    Task-dependent functional and effective connectivity during conceptual processing

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    Conceptual knowledge is central to cognition. Previous neuroimaging research indicates that conceptual processing involves both modality-specific perceptual-motor areas and multimodal convergence zones. For example, our previous functional magnetic resonance imaging (fMRI) study revealed that both modality-specific and multimodal regions respond to sound and action features of concepts in a task-dependent fashion (Kuhnke P, Kiefer M, Hartwigsen G. 2020b. Task-dependent recruitment of modality-specific and multimodal regions during conceptual processing. Cereb Cortex. 30:3938-3959.). However, it remains unknown whether and how modality-specific and multimodal areas interact during conceptual tasks. Here, we asked 1) whether multimodal and modality-specific areas are functionally coupled during conceptual processing, 2) whether their coupling depends on the task, 3) whether information flows top-down, bottom-up or both, and 4) whether their coupling is behaviorally relevant. We combined psychophysiological interaction analyses with dynamic causal modeling on the fMRI data of our previous study. We found that functional coupling between multimodal and modality-specific areas strongly depended on the task, involved both top-down and bottom-up information flow, and predicted conceptually guided behavior. Notably, we also found coupling between different modality-specific areas and between different multimodal areas. These results suggest that functional coupling in the conceptual system is extensive, reciprocal, task-dependent, and behaviorally relevant. We propose a new model of the conceptual system that incorporates task-dependent functional interactions between modality-specific and multimodal areas
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