Bridging psychology and genetics using large-scale spatial analysis of neuroimaging and neurogenetic data

Understanding how microscopic molecules give rise to complex cognitive processes is a major goal of the biological sciences. The countless hypothetical molecule-cognition relationships necessitate discovery-based techniques to guide scientists toward the most productive lines of investigation. To this end, we present a novel discovery tool that uses spatial patterns of neural gene expression from the Allen Brain Institute (ABI) and large-scale functional neuroimaging meta-analyses from the Neurosynth framework to bridge neurogenetic and neuroimaging data. We quantified the spatial similarity between over 20,000 genes from the ABI and 48 psychological topics derived from lexical analysis of neuroimaging articles, producing a comprehensive set of gene/cognition mappings that we term the Neurosynth-gene atlas. We demonstrate the ability to independently replicate known gene/cognition associations (e.g., between dopamine and reward), and subsequently use it to identify a range of novel associations between individual molecules or genes and complex psychological phenomena such as reward, memory and emotion. Our results complement existing discovery-based methods such as GWAS, and provide a novel means of generating hypotheses about the neurogenetic substrates of complex cognitive functions.

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Functional Neuroimaging and Psychology: What Have You Done for Me Lately?

Journal of Cognitive Neuroscience ◽

10.1162/jocn_a_00380 ◽

2013 ◽

Vol 25 (6) ◽

pp. 834-842 ◽

Cited By ~ 12

Author(s):

Joseph M. Moran ◽

Jamil Zaki

Keyword(s):

Functional Imaging ◽

Brain Mapping ◽

Functional Neuroimaging ◽

Brain Activity ◽

Psychological Theory ◽

Quarter Century ◽

Psychological Phenomena ◽

Neuroimaging Data ◽

Subsequent Behavior ◽

Reverse Inference

Functional imaging has become a primary tool in the study of human psychology but is not without its detractors. Although cognitive neuroscientists have made great strides in understanding the neural instantiation of countless cognitive processes, commentators have sometimes argued that functional imaging provides little or no utility for psychologists. And indeed, myriad studies over the last quarter century have employed the technique of brain mapping—identifying the neural correlates of various psychological phenomena—in ways that bear minimally on psychological theory. How can brain mapping be made more relevant to behavioral scientists broadly? Here, we describe three trends that increase precisely this relevance: (i) the use of neuroimaging data to adjudicate between competing psychological theories through forward inference, (ii) isolating neural markers of information processing steps to better understand complex tasks and psychological phenomena through probabilistic reverse inference, and (iii) using brain activity to predict subsequent behavior. Critically, these new approaches build on the extensive tradition of brain mapping, suggesting that efforts in this area—although not initially maximally relevant to psychology—can indeed be used in ways that constrain and advance psychological theory.

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A Meta-analysis of Functional Neuroimaging Studies of Self- and Other Judgments Reveals a Spatial Gradient for Mentalizing in Medial Prefrontal Cortex

Journal of Cognitive Neuroscience ◽

10.1162/jocn_a_00233 ◽

2012 ◽

Vol 24 (8) ◽

pp. 1742-1752 ◽

Cited By ~ 411

Author(s):

Bryan T. Denny ◽

Hedy Kober ◽

Tor D. Wager ◽

Kevin N. Ochsner

Keyword(s):

Functional Organization ◽

Functional Neuroimaging ◽

Meta Analysis ◽

Brain Regions ◽

The Self ◽

Spatial Gradient ◽

Self And Other ◽

Neuroimaging Data ◽

Medial Pfc ◽

Meta Analyses

The distinction between processes used to perceive and understand the self and others has received considerable attention in psychology and neuroscience. Brain findings highlight a role for various regions, in particular the medial PFC (mPFC), in supporting judgments about both the self and others. We performed a meta-analysis of 107 neuroimaging studies of self- and other-related judgments using multilevel kernel density analysis [Kober, H., & Wager, T. D. Meta-analyses of neuroimaging data. Wiley Interdisciplinary Reviews, 1, 293–300, 2010]. We sought to determine what brain regions are reliably involved in each judgment type and, in particular, what the spatial and functional organization of mPFC is with respect to them. Relative to nonmentalizing judgments, both self- and other judgments were associated with activity in mPFC, ranging from ventral to dorsal extents, as well as common activation of the left TPJ and posterior cingulate. A direct comparison between self- and other judgments revealed that ventral mPFC as well as left ventrolateral PFC and left insula were more frequently activated by self-related judgments, whereas dorsal mPFC, in addition to bilateral TPJ and cuneus, was more frequently activated by other-related judgments. Logistic regression analyses revealed that ventral and dorsal mPFC lay at opposite ends of a functional gradient: The z coordinates reported in individual studies predicted whether the study involved self- or other-related judgments, which were associated with increasingly ventral or dorsal portions of mPFC, respectively. These results argue for a distributed rather than localizationist account of mPFC organization and support an emerging view on the functional heterogeneity of mPFC.

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Dissociating frontoparietal brain networks with neuroadaptive Bayesian optimization

10.1101/128678 ◽

2017 ◽

Cited By ~ 3

Author(s):

Romy Lorenz ◽

Ines R. Violante ◽

Ricardo Pio Monti ◽

Giovanni Montana ◽

Adam Hampshire ◽

...

Keyword(s):

Deductive Reasoning ◽

Functional Neuroimaging ◽

Meta Analysis ◽

Bayesian Optimization ◽

Cognitive Tasks ◽

Optimization Approach ◽

Real Time Analysis ◽

Starting Point ◽

Neuroimaging Data ◽

Meta Analyses

AbstractUnderstanding the unique contributions of frontoparietal networks (FPN) in cognition is challenging because different FPNs spatially overlap and are co-activated for diverse tasks. In order to characterize these networks involves studying how they activate across many different cognitive tasks, which previously has only been possible with meta-analyses. Here, building upon meta-analyses as a starting point, we use neuroadaptive Bayesian optimization, an approach combining real-time analysis of functional neuroimaging data with machine-learning, to discover cognitive tasks that dissociate ventral and dorsal FPN activity from a large pool of tasks. We identify and subsequently refine two cognitive tasks (Deductive Reasoning and Tower of London) that are optimal for dissociating the FPNs. The identified cognitive tasks are not those predicted by meta-analysis, highlighting a different mapping between cognitive tasks and FPNs than expected. The optimization approach converged on a similar neural dissociation independently for the two different tasks, suggesting a possible common underlying functional mechanism and the need for neurally-derived cognitive taxonomies.

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Toward a Global and Reproducible Science for Brain Imaging in Neurotrauma: The ENIGMA Adult Moderate/Severe Traumatic Brain Injury Working Group

10.31234/osf.io/jnsb2 ◽

2019 ◽

Cited By ~ 1

Author(s):

Alexander Olsen ◽

Talin Babikian ◽

Erin D. Bigler ◽

Karen Caeyenberghs ◽

Virginia Conde ◽

...

Keyword(s):

Traumatic Brain Injury ◽

Data Analysis ◽

Brain Injury ◽

Working Group ◽

Large Scale ◽

Functional Neuroimaging ◽

Meta Analysis ◽

Small Sample ◽

Mortality And Morbidity ◽

Neuroimaging Data

The global burden of mortality and morbidity caused by traumatic brain injury (TBI) is significant and the heterogeneity of TBI patients and the relatively small sample sizes of most current neuroimaging studies is a major challenge for scientific advances and clinical translation. The ENIGMA (Enhancing NeuroImaging Genetics through Meta-Analysis) Adult moderate/severe TBI (AMS-TBI) working group aims to be a driving force for new discoveries in AMS-TBI by providing researchers world-wide with an effective framework and platform for large-scale cross-border collaboration and data sharing. Based on the principles of transparency, rigor, reproducibility and collaboration, we will facilitate the development and dissemination of multiscale and big data analysis pipelines for harmonized analyses in AMS-TBI using structural and functional neuroimaging in combination with nonimaging biomarkers, genetics, as well as clinical and behavioral measures. Ultimately, we will offer investigators an unprecedented opportunity to test important hypotheses about recovery and morbidity in AMS-TBI by taking advantage of our robust methods for largescale neuroimaging data analysis. In this consensus statement we outline the working group’s short-term, intermediate, and long-term goals.

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Bridging the gap between perception and action: the case for neuroimaging, AI and video games

10.31234/osf.io/3epws ◽

2019 ◽

Author(s):

Pierre Bellec ◽

Julie A. Boyle

Keyword(s):

Neural Networks ◽

Video Games ◽

Cognitive Processes ◽

Video Game ◽

Large Scale ◽

Human Performance ◽

Brain Activity ◽

Challenges And Opportunities ◽

Neuroimaging Data ◽

Planning Decision

A fundamental goal of computational neuroscience is to account for the implementation of cognitive processes in the brain, yet current models tend to focus on elementary cognitive processes. By contrast, video games have been designed to fully engage players, and require to constantly monitor the state of the game, in parallel to integrating strategic planning, decision making and taking action. While playing video games is hard, recent advances in artificial intelligence (AI) have made it possible to train deep neural networks that reach or even surpass human performance. We discuss challenges and opportunities in training artificial neural networks that could account jointly for human brain activity and behaviour during video game play. We argue that large-scale neuroimaging data may help to constrain the training of artificial networks and open new avenues for research at the intersection of neuroscience and AI.

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Cerebellum and Emotion in Morality

10.31234/osf.io/n6s2t ◽

2021 ◽

Author(s):

Hyemin Han

Keyword(s):

Large Scale ◽

Functional Neuroimaging ◽

Brain Regions ◽

Moral Functioning ◽

Neuroimaging Data ◽

Crus I ◽

The Right ◽

Brain Image Analysis ◽

The Relationship

In the current chapter, I examined the relationship between the cerebellum, emotion, and morality with evidence from large-scale neuroimaging data analysis. Although the aforementioned relationship has not been well studied in neuroscience, recent studies have shown that the cerebellum is closely associated with emotional and social processes at the neural level. Also, debates in the field of moral philosophy, psychology, and neuroscience have supported the importance of emotion in moral functioning. Thus, I explored the potentially important but less-studies topic with NeuroSynth, a tool for large-scale brain image analysis, while addressing issues associated with reverse inference. The result from analysis demonstrated that brain regions in the cerebellum, the right Crus I and Crus II in particular, were specifically associated with morality in general. I discussed the potential implications of the finding based on clinical and functional neuroimaging studies of the cerebellum, emotional functioning, and neural networks for diverse psychological processes.

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Common and separable neural alterations in substance use disorders: evidence from coordinate-based meta-analyses of functional neuroimaging studies in human

10.1101/2020.02.19.956755 ◽

2020 ◽

Cited By ~ 1

Author(s):

Benjamin Klugah-Brown ◽

Xin Di ◽

Jana Zweerings ◽

Klaus Mathiak ◽

Benjamin Becker ◽

...

Keyword(s):

Substance Use ◽

Substance Use Disorders ◽

Cognitive Processes ◽

Functional Neuroimaging ◽

Meta Analysis ◽

Treatment Strategies ◽

Specific Treatment ◽

Behavioral Alterations ◽

Meta Analyses

AbstractDelineating common and separable neural alterations in substance use disorders (SUD) is imperative to understand the neurobiological basis of the addictive process and to inform substance-specific treatment strategies. Given numerous functional MRI (fMRI) studies in different SUDs, meta-analysis could provide an opportunity to determine robust shared and substance-specific alterations. The present study employed a coordinate-based meta-analysis covering fMRI studies in individuals with addictive cocaine, cannabis, alcohol, and nicotine use. The primary meta-analysis demonstrated common alterations in primary dorsal striatal, and frontal circuits engaged in reward/salience processing, habit formation, and executive control across different substances and task-paradigms. Subsequent sub-analyses revealed substance-specific alterations in frontal and limbic regions, with marked frontal and insula-thalamic alterations in alcohol and nicotine use disorders respectively. Finally, examining task-specific alterations across substances revealed pronounced frontal alterations during cognitive processes yet stronger striatal alterations during reward-related processes. Together the findings emphasize the role of dysregulations in striato-frontal circuits and dissociable contributions of these systems in the domains of reward-related and cognitive processes which may contribute to substance-specific behavioral alterations.

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An fMRI Study Using a Combined Task of Interval Discrimination and Oddball Could Reveal Common Brain Circuits of Cognitive Change

Frontiers in Psychiatry ◽

10.3389/fpsyt.2021.786113 ◽

2021 ◽

Vol 12 ◽

Author(s):

María Sol Garcés ◽

Irene Alústiza ◽

Anton Albajes-Eizagirre ◽

Javier Goena ◽

Patricio Molero ◽

...

Keyword(s):

Cognitive Processes ◽

Healthy Subjects ◽

Functional Neuroimaging ◽

Meta Analysis ◽

Brain Structures ◽

Cognitive Change ◽

Brain Regions ◽

Task Type ◽

Meta Analyses ◽

The Brain

Recent functional neuroimaging studies suggest that the brain networks responsible for time processing are involved during other cognitive processes, leading to a hypothesis that time-related processing is needed to perform a range of tasks across various cognitive functions. To examine this hypothesis, we analyze whether, in healthy subjects, the brain structures activated or deactivated during performance of timing and oddball-detection type tasks coincide. To this end, we conducted two independent signed differential mapping (SDM) meta-analyses of functional magnetic resonance imaging (fMRI) studies assessing the cerebral generators of the responses elicited by tasks based on timing and oddball-detection paradigms. Finally, we undertook a multimodal meta-analysis to detect brain regions common to the findings of the two previous meta-analyses. We found that healthy subjects showed significant activation in cortical areas related to timing and salience networks. The patterns of activation and deactivation corresponding to each task type partially coincided. We hypothesize that there exists a time and change-detection network that serves as a common underlying resource used in a broad range of cognitive processes.

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Delineating visual, auditory and motor regions in the human brain with functional neuroimaging: a BrainMap-based meta-analytic synthesis

Scientific Reports ◽

10.1038/s41598-021-88773-9 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Marisa K. Heckner ◽

Edna C. Cieslik ◽

Vincent Küppers ◽

Peter T. Fox ◽

Simon B. Eickhoff ◽

...

Keyword(s):

Large Scale ◽

Functional Neuroimaging ◽

Motor Task ◽

Brain Regions ◽

Affective Processing ◽

Resting State Functional Connectivity ◽

Motor Processes ◽

Brain Correlates ◽

Meta Analyses ◽

The Brain

AbstractMost everyday behaviors and laboratory tasks rely on visual, auditory and/or motor-related processes. Yet, to date, there has been no large-scale quantitative synthesis of functional neuroimaging studies mapping the brain regions consistently recruited during such perceptuo-motor processing. We therefore performed three coordinate-based meta-analyses, sampling the results of neuroimaging experiments on visual (n = 114), auditory (n = 122), or motor-related (n = 251) processing, respectively, from the BrainMap database. Our analyses yielded both regions known to be recruited for basic perceptual or motor processes and additional regions in posterior frontal cortex. Comparing our results with data-driven network definitions based on resting-state functional connectivity revealed good overlap in expected regions but also showed that perceptual and motor task-related activations consistently involve additional frontal, cerebellar, and subcortical areas associated with “higher-order” cognitive functions, extending beyond what is captured when the brain is at “rest.” Our resulting sets of domain-typical brain regions can be used by the neuroimaging community as robust functional definitions or masks of regions of interest when investigating brain correlates of perceptual or motor processes and their interplay with other mental functions such as cognitive control or affective processing. The maps are made publicly available via the ANIMA database.

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