Dissociating frontoparietal brain networks with neuroadaptive Bayesian optimization

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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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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Meta-analysis of the neural representation of first language and second language

Applied Psycholinguistics ◽

10.1017/s0142716411000075 ◽

2011 ◽

Vol 32 (4) ◽

pp. 799-819 ◽

Cited By ~ 44

Author(s):

RAJANI SEBASTIAN ◽

ANGELA R. LAIRD ◽

SWATHI KIRAN

Keyword(s):

Second Language ◽

Language Proficiency ◽

Language Processing ◽

Functional Neuroimaging ◽

Meta Analysis ◽

First Language ◽

Likelihood Estimation ◽

Neural Representation ◽

Second Language Processing ◽

Meta Analyses

ABSTRACTThis study reports an activation likelihood estimation meta-analysis of published functional neuroimaging studies of bilingualism. Four parallel meta-analyses were conducted by taking into account the proficiency of participants reported in the studies. The results of the meta-analyses suggest differences in the probabilities of activation patterns between high proficiency and moderate/low proficiency bilinguals. The Talairach coordinates of activation in first language processing were very similar to that of second language processing in the high proficient bilinguals. However, in the low proficient group, the activation clusters were generally smaller and distributed over wider areas in both the hemispheres than the clusters identified in the ALE maps from the high proficient group. These findings draw attention to the importance of language proficiency in bilingual neural representation.

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Meta-analysis of functional neuroimaging data: current and future directions

Social Cognitive and Affective Neuroscience ◽

10.1093/scan/nsm015 ◽

2007 ◽

Vol 2 (2) ◽

pp. 150-158 ◽

Cited By ~ 222

Author(s):

Tor D. Wager ◽

Martin Lindquist ◽

Lauren Kaplan

Keyword(s):

Functional Neuroimaging ◽

Meta Analysis ◽

Future Directions ◽

Neuroimaging Data

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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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Neural bases of Frustration-Aggression Theory: A multi-domain meta-analysis of functional neuroimaging studies.

10.1101/2021.05.12.21257119 ◽

2021 ◽

Author(s):

Jules R Dugre ◽

Stephane Potvin

Keyword(s):

Functional Neuroimaging ◽

Meta Analysis ◽

Insular Cortex ◽

Posterior Cingulate Cortex ◽

Aggressive Behaviors ◽

Brain Functions ◽

Neural Processes ◽

Definition Of ◽

Meta Analyses

Early evidence suggests that unexpected non-reward may increase the risk for aggressive behaviors. Despite the growing interest in understanding brain functions that may be implicated in aggressive behaviors, the neural processes underlying such frustrative events remain largely unknown. Furthermore, meta-analytic results have produced discrepant results, potentially due to substantial differences in the definition of anger/aggression constructs. Therefore, coordinate-based meta-analyses on unexpected non-reward and retaliatory behaviors in healthy subjects were conducted. Conjunction analyses were further examined to discover overlapping brain activations across these meta-analytical maps. Frustrative non-reward deactivated the orbitofrontal cortex, ventral striatum and posterior cingulate cortex, whereas increased activations were observed in midcingulo-insular regions, as well as dorsomedial prefrontal cortex, amygdala, thalamus and periaqueductal gray, when using liberal threshold. Retaliation activated of midcingulo-insular regions, the dorsal caudate and the primary somatosensory cortex. Conjunction analyses revealed that both strongly activated midcingulo-insular regions. Our results underscore the role of anterior midcingulate/pre-supplementary motor area and fronto-insular cortex in both frustration and retaliatory behaviors. A neurobiological framework for understanding frustration-based impulsive aggression is provided.

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Beyond the intraclass correlation: A hierarchical modeling approach to test-retest assessment

10.1101/2021.01.04.425305 ◽

2021 ◽

Author(s):

Gang Chen ◽

Daniel S. Pine ◽

Melissa A. Brotman ◽

Ashley R. Smith ◽

Robert W. Cox ◽

...

Keyword(s):

Individual Differences ◽

Hierarchical Modeling ◽

Functional Neuroimaging ◽

Intraclass Correlation ◽

Population Level ◽

Relative Magnitude ◽

Psychological State ◽

Cognitive Tasks ◽

Neuroimaging Data ◽

Foundational Work

AbstractThe concept of test-retest reliability (TRR) indexes the repeatability or consistency of a measurement across time. High TRR of measures is critical for any scientific study, specifically for the study of individual differences. Evidence of poor TRR of commonly used behavioral and functional neuroimaging tasks is mounting (e.g., Hedge et al., 2018; Elliot et al., 2020). These reports have called into question the adequacy of using even the most common, well-characterized cognitive tasks with robust population-level task effects, to measure individual differences. Here, we demonstrate the limitations of the intraclass correlation coefficient (ICC), the classical metric that captures TRR as a proportional variance ratio. Specifically, the ICC metric is limited when characterizing TRR of cognitive tasks that rely on many individual trials to repeatedly evoke a psychological state or behavior. We first examine when and why conventional ICCs underestimate TRR. Further, based on recent foundational work (Rouder and Haaf, 2019; Haines et al., 2020), we lay out a hierarchical framework that takes into account the data structure down to the trial level and estimates TRR as a correlation divorced from trial-level variability. As part of this process, we examine several modeling issues associated with the conventional ICC formulation and assess how different factors (e.g., trial and subject sample sizes, relative magnitude of cross-trial variability) impact TRR. We reference the tools of TRR and 3dLMEr for the community to apply these models to behavior and neuroimaging data.

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

10.1101/012310 ◽

2014 ◽

Cited By ~ 11

Author(s):

Andrew S Fox ◽

Luke J Chang ◽

Krzysztof J Gorgolewski ◽

Tal Yarkoni

Keyword(s):

Biological Sciences ◽

Cognitive Processes ◽

Large Scale ◽

Functional Neuroimaging ◽

Psychological Phenomena ◽

Allen Brain ◽

Neuroimaging Data ◽

Meta Analyses ◽

Or Genes ◽

Novel Associations

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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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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