1,502 research outputs found

    A data-driven approach to the automated study of cross-species homologies

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    Behavioral neuroscience has made great strides in developing animal models of human behavior and psychiatric disorders. Animal models allow for the formulation of hypotheses regarding the mechanisms underlying psychiatric disorders, and the opportunity to test these hypotheses using procedures that are too invasive for human participants. However, recent scientific reviews have highlighted the low success rate of translating results from animal models into clinical interventions in humans. A potential roadblock is that bidirectional functional mappings between the human and rodent brain are incomplete. To narrow this gap, we created a framework, Neurobabel, for performing large-scale automated synthesis of human neuroimaging data and behavioral neuroscience data. By leveraging the semantics of how researchers within each field describe their studies, this framework enables region to region mapping of brain regions across species, as well as cross-species mapping of psychological functions. As a proof of concept, we utilize the framework to create a functional cross-species mapping between the amygdala and hippocampus for fear-related and spatial memories, respectively. We then proceed to address two open questions in the field: (1) Do rodents have a dorsolateral prefrontal cortex? (2) Which human brain region corresponds to the rodent prelimbic cortex

    Changepoint detection versus reinforcement learning: Separable neural substrates approximate different forms of Bayesian inference

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    Adaptive behavior in even the simplest decision-making tasks requires predicting future events in an environment that is generally nonstationary. As an inductive problem, this prediction requires a commitment to the statistical process underlying environmental change. This challenge can be formalized in a Bayesian framework as a question of choosing a generative model for the task dynamics. Previous learning models assume, implicitly or explicitly, that nonstationarity follows either a continuous diffusion process or a discrete changepoint process. Each approach is slow to adapt when its assumptions are violated. A new mixture of Bayesian experts framework proposes separable brain systems approximating inference under different assumptions regarding the statistical structure of the environment. This model explains data from a laboratory foraging task, in which rats experienced a change in reward contingencies after pharmacological disruption of dorsolateral (DLS) or dorsomedial striatum (DMS). The data and model suggest DLS learns under a diffusion prior whereas DMS learns under a changepoint prior. The combination of these two systems offers a new explanation for how the brain handles inference in an uncertain environment

    A data-driven approach to the automated study of cross-species homologies

    Get PDF
    Behavioral neuroscience has made great strides in developing animal models of human behavior and psychiatric disorders. Animal models allow for the formulation of hypotheses regarding the mechanisms underlying psychiatric disorders, and the opportunity to test these hypotheses using procedures that are too invasive for human participants. However, recent scientific reviews have highlighted the low success rate of translating results from animal models into clinical interventions in humans. A potential roadblock is that bidirectional functional mappings between the human and rodent brain are incomplete. To narrow this gap, we created a framework, Neurobabel, for performing large-scale automated synthesis of human neuroimaging data and behavioral neuroscience data. By leveraging the semantics of how researchers within each field describe their studies, this framework enables region to region mapping of brain regions across species, as well as cross-species mapping of psychological functions. As a proof of concept, we utilize the framework to create a functional cross-species mapping between the amygdala and hippocampus for fear-related and spatial memories, respectively. We then proceed to address two open questions in the field: (1) Do rodents have a dorsolateral prefrontal cortex? (2) Which human brain region corresponds to the rodent prelimbic cortex

    Neural computations underlying inverse reinforcement learning in the human brain

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    In inverse reinforcement learning an observer infers the reward distribution available for actions in the environment solely through observing the actions implemented by another agent. To address whether this computational process is implemented in the human brain, participants underwent fMRI while learning about slot machines yielding hidden preferred and non-preferred food outcomes with varying probabilities, through observing the repeated slot choices of agents with similar and dissimilar food preferences. Using formal model comparison, we found that participants implemented inverse RL as opposed to a simple imitation strategy, in which the actions of the other agent are copied instead of inferring the underlying reward structure of the decision problem. Our computational fMRI analysis revealed that anterior dorsomedial prefrontal cortex encoded inferences about action-values within the value space of the agent as opposed to that of the observer, demonstrating that inverse RL is an abstract cognitive process divorceable from the values and concerns of the observer him/herself

    A high-resolution probabilistic in vivo atlas of human subcortical brain nuclei

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    Recent advances in magnetic resonance imaging methods, including data acquisition, pre-processing and analysis, have benefited research on the contributions of subcortical brain nuclei to human cognition and behavior. At the same time, these developments have led to an increasing need for a high-resolution probabilistic in vivo anatomical atlas of subcortical nuclei. In order to address this need, we constructed high spatial resolution, three-dimensional templates, using high-accuracy diffeomorphic registration of T_1- and T_2- weighted structural images from 168 typical adults between 22 and 35 years old. In these templates, many tissue boundaries are clearly visible, which would otherwise be impossible to delineate in data from individual studies. The resulting delineations of subcortical nuclei complement current histology-based atlases. We further created a companion library of software tools for atlas development, to offer an open and evolving resource for the creation of a crowd-sourced in vivoprobabilistic anatomical atlas of the human brain

    Regional specialization within the human striatum for diverse psychological functions

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    Decades of animal and human neuroimaging research have identified distinct, but overlapping, striatal zones, which are interconnected with separable corticostriatal circuits, and are crucial for the organization of functional systems. Despite continuous efforts to subdivide the human striatum based on anatomical and resting-state functional connectivity, characterizing the different psychological processes related to each zone remains a work in progress. Using an unbiased, data-driven approach, we analyzed large-scale coactivation data from 5,809 human imaging studies. We (i) identified five distinct striatal zones that exhibited discrete patterns of coactivation with cortical brain regions across distinct psychological processes and (ii) identified the different psychological processes associated with each zone. We found that the reported pattern of cortical activation reliably predicted which striatal zone was most strongly activated. Critically, activation in each functional zone could be associated with distinct psychological processes directly, rather than inferred indirectly from psychological functions attributed to associated cortices. Consistent with well-established findings, we found an association of the ventral striatum (VS) with reward processing. Confirming less well-established findings, the VS and adjacent anterior caudate were associated with evaluating the value of rewards and actions, respectively. Furthermore, our results confirmed a sometimes overlooked specialization of the posterior caudate nucleus for executive functions, often considered the exclusive domain of frontoparietal cortical circuits. Our findings provide a precise functional map of regional specialization within the human striatum, both in terms of the differential cortical regions and psychological functions associated with each striatal zone

    Changepoint detection versus reinforcement learning: Separable neural substrates approximate different forms of Bayesian inference

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    Adaptive behavior in even the simplest decision-making tasks requires predicting future events in an environment that is generally nonstationary. As an inductive problem, this prediction requires a commitment to the statistical process underlying environmental change. This challenge can be formalized in a Bayesian framework as a question of choosing a generative model for the task dynamics. Previous learning models assume, implicitly or explicitly, that nonstationarity follows either a continuous diffusion process or a discrete changepoint process. Each approach is slow to adapt when its assumptions are violated. A new mixture of Bayesian experts framework proposes separable brain systems approximating inference under different assumptions regarding the statistical structure of the environment. This model explains data from a laboratory foraging task, in which rats experienced a change in reward contingencies after pharmacological disruption of dorsolateral (DLS) or dorsomedial striatum (DMS). The data and model suggest DLS learns under a diffusion prior whereas DMS learns under a changepoint prior. The combination of these two systems offers a new explanation for how the brain handles inference in an uncertain environment

    Behavioural evidence for parallel outcome-sensitive and outcome-insensitive Pavlovian learning systems in humans

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    There is a dichotomy in instrumental conditioning between goal-directed actions and habits that are distinguishable on the basis of their relative sensitivity to changes in outcome value. It is less clear whether a similar distinction applies in Pavlovian conditioning, where responses have been found to be predominantly outcome-sensitive. To test for both devaluation-insensitive and devaluation-sensitive Pavlovian conditioning in humans, we conducted four experiments combining Pavlovian conditioning and outcome-devaluation procedures while measuring multiple conditioned responses. Our results suggest that Pavlovian conditioning involves two distinct types of learning: one that learns the current value of the outcome, which is sensitive to devaluation, and one that learns about the spatial localization of the outcome, which is insensitive to devaluation. Our findings have implications for the mechanistic understanding of Pavlovian conditioning and provide a more nuanced understanding of Pavlovian mechanisms that might contribute to a number of psychiatric disorders

    Mutation analysis in a German family identified a new cataract-causing allele in the CRYBB2 gene

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    The study demonstrates the functional candidate gene analysis in a cataract family of German descent. METHODS: We screened a German family, clinically documented to have congenital cataracts, for mutation in the candidate genes CRYG (A to D) and CRYBB2 through polymerase chain reaction analyses and sequencing. RESULTS: Congenital cataract was first observed in a daughter of healthy parents. Her two children (a boy and a girl) also suffer from congenital cataracts and have been operated within the first weeks of birth. Morphologically, the cataract is characterized as nuclear with an additional ring-shaped cortical opacity. Molecular analysis revealed no causative mutation in any of the CRYG genes. However, sequencing of the exons of the CRYBB2 gene identified a sequence variation in exon 5 (383 A>T) with a substitution of Asp to Val at position 128. All three affected family members revealed this change but it was not observed in any of the unaffected persons of the family. The putative mutation creates a restriction site for the enzyme TaiI. This mutation was checked for in controls of randomly selected DNA samples from ophthalmologically normal individuals from the population-based KORA S4 study (n=96) and no mutation was observed. Moreover, the Asp at position 128 is within a stretch of 12 amino acids, which are highly conserved throughout the animal kingdom. For the mutant protein, the isoelectric point is raised from pH 6.50 to 6.75. Additionally, the random coil structure of the protein between the amino acids 126-139 is interrupted by a short extended strand structure. In addition, this region becomes hydrophobic (from neutral to +1) and the electrostatic potential in the region surrounding the exchanged amino acid alters from a mainly negative potential to an enlarged positive potential. CONCLUSIONS: The D128V mutation segregates only in affected family members and is not seen in representative controls. It represents the first mutation outside exon 6 of the human CRYBB2 gene
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