Linking Brain Structure to Function to Value-Based Choice

What humans choose and how their brains make choices are central questions in psychology and neuroscience. Neuroimaging research is advancing models of functional brain activity that not only correlate with, but also predict, value-based choices in humans. Physiological research in animals suggests that monosynaptic axons structurally connect the brain circuits predictive of choice. However, similar structural connections have only recently been characterized in humans, and researchers are now starting to explore links from structural brain connections to functional brain activity to behavioral choice. In this lecture, Leong presents recent findings that link multimodal neuroimaging measurements to individual differences in value-based choice. Together this work demonstrates the promise of combining measures of brain structure, brain function, and behavior to better explain how people choose

brainlife.io: A decentralized and open source cloud platform to support neuroscience research

Neuroscience research has expanded dramatically over the past 30 years by advancing standardization and tool development to support rigor and transparency. Consequently, the complexity of the data pipeline has also increased, hindering access to FAIR data analysis to portions of the worldwide research community. brainlife.io was developed to reduce these burdens and democratize modern neuroscience research across institutions and career levels. Using community software and hardware infrastructure, the platform provides open-source data standardization, management, visualization, and processing and simplifies the data pipeline. brainlife.io automatically tracks the provenance history of thousands of data objects, supporting simplicity, efficiency, and transparency in neuroscience research. Here brainlife.io's technology and data services are described and evaluated for validity, reliability, reproducibility, replicability, and scientific utility. Using data from 4 modalities and 3,200 participants, we demonstrate that brainlife.io's services produce outputs that adhere to best practices in modern neuroscience research

brainlife.io: a decentralized and open-source cloud platform to support neuroscience research

Neuroscience is advancing standardization and tool development to support rigor and transparency. Consequently, data pipeline complexity has increased, hindering FAIR (findable, accessible, interoperable and reusable) access. brainlife.io was developed to democratize neuroimaging research. The platform provides data standardization, management, visualization and processing and automatically tracks the provenance history of thousands of data objects. Here, brainlife.io is described and evaluated for validity, reliability, reproducibility, replicability and scientific utility using four data modalities and 3,200 participants

Semantic Representation in the Mirror Neuron System

The mirror neuron system is a fronto-parietal network of neurons that is activated both when a person performs an action and when he or she observes that action. The goal of this study was to investigate the semantic representation in this system during action language and gesture processing. This was done in a set of two behavioral experiments. Experiment 1 employed a simple priming paradigm—subjects viewed videos of symbolic gestures or landscapes, which served as the prime, followed by a word that was congruent or unrelated to the video prime, or a pseudo-word. The subject performed a lexical decision task on the target word. The study found a significant priming effect for semantically congruent target words, relative to semantically unrelated target words. However, this same priming effect was found for the video primes of landscapes.  In experiment 2 we aimed to determine whether the videos were primed through effector-specific means, that is, whether hand and arm gestures would activate mirror neurons somatotopically and lead to different priming results when comparing hand responses to foot responses. We used the same priming study as experiment 1 except that subjects made their lexical decision responses on a foot pedal rather than a keyboard. Results suggest that symbolic gestures prime in a very diffuse way, such that semantic priming occurs independent of the effector being used to respond

Semantic Representation in the Mirror Neuron System

The mirror neuron system is a fronto-parietal network of neurons that is activated both when a person performs an action and when he or she observes that action. The goal of this study was to investigate the semantic representation in this system during action language and gesture processing. This was done in a set of two behavioral experiments. Experiment 1 employed a simple priming paradigm—subjects viewed videos of symbolic gestures or landscapes, which served as the prime, followed by a word that was congruent or unrelated to the video prime, or a pseudo-word. The subject performed a lexical decision task on the target word. The study found a significant priming effect for semantically congruent target words, relative to semantically unrelated target words. However, this same priming effect was found for the video primes of landscapes.  In experiment 2 we aimed to determine whether the videos were primed through effector-specific means, that is, whether hand and arm gestures would activate mirror neurons somatotopically and lead to different priming results when comparing hand responses to foot responses. We used the same priming study as experiment 1 except that subjects made their lexical decision responses on a foot pedal rather than a keyboard. Results suggest that symbolic gestures prime in a very diffuse way, such that semantic priming occurs independent of the effector being used to respond

THE POST-NEIGHBOURHOOD CONDITION: NEIGHBOURHOOD-DIRECTED PUBLIC SPACES IN A DIGITALLY CONNECTED SOCIETY

Master'sMASTER OF ARCHITECTURE (M.ARCH

Distinct neural circuits support incentivized inhibition

The ability to inhibit responses under high stakes, or "incentivized inhibition," is critical for adaptive impulse control. While previous research indicates that right ventrolateral prefrontal cortical (VLPFC) activity plays a key role in response inhibition, less research has addressed how incentives might influence this circuit. By combining a novel behavioral task, functional magnetic resonance imaging (FMRI), and diffusion-weighted imaging (DWI), we targeted and characterized specific neural circuits that support incentivized inhibition. Behaviorally, large incentives enhanced responses to obtain money, but also reduced response inhibition. Functionally, activity in both right VLPFC and right anterior insula (AIns) predicted successful inhibition for high incentives. Structurally, characterization of a novel white-matter tract connecting the right AIns and VLPFC revealed an association of tract coherence with incentivized inhibition performance. Finally, individual differences in right VLPFC activity statistically mediated the association of right AIns-VLPFC tract coherence with incentivized inhibition performance. These multimodal findings bridge brain structure, brain function, and behavior to clarify how individuals can inhibit impulses, even in the face of high stakes