36 research outputs found

    Differential functional connectivity underlying asymmetric reward-related activity in human and nonhuman primates

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    The orbitofrontal cortex (OFC) is a key brain region involved in complex cognitive functions such as reward processing and decision making. Neuroimaging studies have reported unilateral OFC response to reward-related variables; however, those studies rarely discussed this observation. Nevertheless, some lesion studies suggest that the left and right OFC contribute differently to cognitive processes. We hypothesized that the OFC asymmetrical response to reward could reflect underlying hemispherical difference in OFC functional connectivity. Using resting-state and reward-related functional MRI data from humans and from rhesus macaques, we first identified an asymmetrical response of the lateral OFC to reward in both species. Crucially, the subregion showing the highest reward-related asymmetry (RRA) overlapped with the region showing the highest functional connectivity asymmetry (FCA). Furthermore, the two types of asymmetries were found to be significantly correlated across individuals. In both species, the right lateral OFC was more connected to the default mode network compared to the left lateral OFC. Altogether, our results suggest a functional specialization of the left and right lateral OFC in primates.</jats:p

    Polarity of uncertainty representation during exploration and exploitation in ventromedial prefrontal cortex

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    Environments furnish multiple information sources for making predictions about future events. Here we use behavioural modelling and functional magnetic resonance imaging to describe how humans select predictors that might be most relevant. First, during early encounters with potential predictors, participants’ selections were explorative and directed towards subjectively uncertain predictors (positive uncertainty effect). This was particularly the case when many future opportunities remained to exploit knowledge gained. Then, preferences for accurate predictors increased over time, while uncertain predictors were avoided (negative uncertainty effect). The behavioural transition from positive to negative uncertainty-driven selections was accompanied by changes in the representations of belief uncertainty in ventromedial prefrontal cortex (vmPFC). The polarity of uncertainty representations (positive or negative encoding of uncertainty) changed between exploration and exploitation periods. Moreover, the two periods were separated by a third transitional period in which beliefs about predictors’ accuracy predominated. The vmPFC signals a multiplicity of decision variables, the strength and polarity of which vary with behavioural context

    Labeling lateral prefrontal sulci using spherical data augmentation and context-aware training

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    The inference of cortical sulcal labels often focuses on deep (primary and secondary) sulcal regions, whereas shallow (tertiary) sulcal regions are largely overlooked in the literature due to the scarcity of manual/well-defined annotations and their large neuroanatomical variability. In this paper, we present an automated framework for regional labeling of both primary/secondary and tertiary sulci of the dorsal portion of lateral prefrontal cortex (LPFC) using spherical convolutional neural networks. We propose two core components that enhance the inference of sulcal labels to overcome such large neuroanatomical variability: (1) surface data augmentation and (2) context-aware training. (1) To take into account neuroanatomical variability, we synthesize training data from the proposed feature space that embeds intermediate deformation trajectories of spherical data in a rigid to non-rigid fashion, which bridges an augmentation gap in conventional rotation data augmentation. (2) Moreover, we design a two-stage training process to improve labeling accuracy of tertiary sulci by informing the biological associations in neuroanatomy: inference of primary/secondary sulci and then their spatial likelihood to guide the definition of tertiary sulci. In the experiments, we evaluate our method on 13 deep and shallow sulci of human LPFC in two independent data sets with different age ranges: pediatric (N=60) and adult (N=36) cohorts. We compare the proposed method with a conventional multi-atlas approach and spherical convolutional neural networks without/with rotation data augmentation. In both cohorts, the proposed data augmentation improves labeling accuracy of deep and shallow sulci over the baselines, and the proposed context-aware training offers further improvement in the labeling of shallow sulci over the proposed data augmentation. We share our tools with the field and discuss applications of our results for understanding neuroanatomical-functional organization of LPFC and the rest of cortex (https://github.com/ilwoolyu/SphericalLabeling). ?? 2021 The Author(s

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    How prior preferences determine decision-making frames and biases in the human brain

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    Understanding how option values are compared when making a choice is a key objective for decision neuroscience. In natural situations, agents may have a priori on their preferences that create default policies and shape the neural comparison process. We asked participants to make choices between items belonging to different categories (e.g., jazz vs. rock music). Behavioral data confirmed that the items taken from the preferred category were chosen more often and more rapidly, which qualified them as default options. FMRI data showed that baseline activity in classical brain valuation regions, such as the ventromedial Prefrontal Cortex (vmPFC), reflected the strength of prior preferences. In addition, evoked activity in the same regions scaled with the default option value, irrespective of the eventual choice. We therefore suggest that in the brain valuation system, choices are framed as comparisons between default and alternative options, which might save some resource but induce a decision bias

    The human ventromedial prefrontal cortex: sulcal morphology and its influence on functional organization

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    The ventromedial prefrontal cortex (vmPFC), which comprises several distinct cytoarchitectonic areas, is a key brain region supporting decision-making processes and it has been shown to be one of the main hubs of the Default Mode Network, a network classically activated during resting state. We here examined the inter-individual variability in the vmPFC sulcal morphology in 57 humans (37 females) and demonstrated that the presence/absence of the inferior rostral sulcus and the subgenual intralimbic sulcus influences significantly the sulcal organization of this region. Furthermore, the sulcal organization influences the location of the vmPFC peak of the Default Mode Network, demonstrating that the location of functional activity can be affected by local sulcal patterns. These results are critical for the investigation of the function of the vmPFC and show that taking into account the sulcal variability might be essential to guide the interpretation of neuroimaging studies.SIGNIFICANCE STATEMENTThe ventromedial prefrontal cortex (vmPFC) is one of the main hubs of the Default Mode Network and plays a central role in value coding and decision-making. The present study provides a complete description of the inter-individual variability of anatomical morphology of this large portion of prefrontal cortex and its relation to functional organization. We have shown that two supplementary medial sulci predominantly determine the organization of the vmPFC, which in turn affect the location of the functional peak of activity in this region. Those results show that taking into account the variability in sulcal patterns might be essential to guide the interpretation of neuroimaging studies of the human brain and of the vmPFC in particular
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