Extended Functional Connectivity of Convergent Structural Alterations Among Individuals with PTSD: A Neuroimaging Meta-Analysis

Background: Post-traumatic stress disorder (PTSD) is a debilitating disorder defined by the onset of intrusive, avoidant, negative cognitive or affective, and/or hyperarousal symptoms after witnessing or experiencing a traumatic event. Previous voxel-based morphometry studies have provided insight into structural brain alterations associated with PTSD with notable heterogeneity across these studies. Furthermore, how structural alterations may be associated with brain function, as measured by task-free and task-based functional connectivity, remains to be elucidated. Methods: Using emergent meta-analytic techniques, we sought to first identify a consensus of structural alterations in PTSD using the anatomical likelihood estimation (ALE) approach. Next, we generated functional profiles of identified convergent structural regions utilizing resting-state functional connectivity (rsFC) and meta-analytic co-activation modeling (MACM) methods. Finally, we performed functional decoding to examine mental functions associated with our ALE, rsFC, and MACM brain characterizations. Results: We observed convergent structural alterations in a single region located in the medial prefrontal cortex. The resultant rsFC and MACM maps identified functional connectivity across a widespread, whole-brain network that included frontoparietal and limbic regions. Functional decoding revealed overlapping associations with attention, memory, and emotion processes. Conclusions: Consensus-based functional connectivity was observed in regions of the default mode, salience, and central executive networks, which play a role in the tripartite model of psychopathology. Taken together, these findings have important implications for understanding the neurobiological mechanisms associated with PTSD

Neural Systems Underlying RDoC Social Constructs: An Activation Likelihood Estimation Meta-Analysis

Neuroscientists have sought to identify the underlying neural systems supporting social processing that allow interaction and communication, forming social relationships, and navigating the social world. Through the use of NIMH’s Research Domain Criteria (RDoC) framework, we evaluated consensus among studies that examined brain activity during social tasks to elucidate regions comprising the “social brain”. We examined convergence across tasks corresponding to the four RDoC social constructs, including Affiliation and Attachment, Social Communication, Perception and Understanding of Self, and Perception and Understanding of Others. We performed a series of coordinate-based meta-analyses using the activation likelihood estimate (ALE) method. Meta-analysis was performed on whole-brain coordinates reported from 864 fMRI contrasts using the NiMARE Python package, revealing convergence in medial prefrontal cortex, anterior cingulate cortex, posterior cingulate cortex, temporoparietal junction, bilateral insula, amygdala, fusiform gyrus, precuneus, and thalamus. Additionally, four separate RDoC-based meta-analyses revealed differential convergence associated with the four social constructs. These outcomes highlight the neural support underlying these social constructs and inform future research on alterations among neurotypical and atypical populations

Neuroimaging meta regression for coordinate based meta analysis data with a spatial model

Coordinate-based meta-analysis combines evidence from a collection of neuroimaging studies to estimate brain activation. In such analyses, a key practical challenge is to find a computationally ecient approach with good statistical interpretability to model the locations of activation foci. In this article, we propose a generative coordinate-based meta-regression (CBMR) framework to approximate a smooth activation intensity function and investigate the e↵ect of study-level covariates (e.g., year of publication, sample size). We employ a spline parameterization to model the spatial structure of brain activation and consider four stochastic models for modelling the random variation in foci. To examine the validity of CBMR, we estimate brain activation on 20 meta-analytic datasets, conduct spatial homogeneity tests at the voxel level, and compare the results to those generated by existing kernel-based and model-based approaches

The Human Affectome

Over the last decades, the interdisciplinary field of the affective sciences has seen proliferation rather than integration of theoretical perspectives. This is due to differences in metaphysical and mechanistic assumptions about human affective phenomena (what they are and how they work) which, shaped by academic motivations and values, have determined the affective constructs and operationalizations. An assumption on the purpose of affective phenomena can be used as a teleological principle to guide the construction of a common set of metaphysical and mechanistic assumptions—a framework for human affective research. In this capstone paper for the special issue “Towards an Integrated Understanding of the Human Affectome”, we gather the tiered purpose of human affective phenomena to synthesize assumptions that account for human affective phenomena collectively. This teleologically-grounded framework offers a principled agenda and launchpad for both organizing existing perspectives and generating new ones. Ultimately, we hope Human Affectome brings us a step closer to not only an integrated understanding of human affective phenomena, but an integrated field for affective research

The Human Affectome

Over the last decades, the interdisciplinary field of the affective sciences has seen proliferation rather than integration of theoretical perspectives. This is due to differences in metaphysical and mechanistic assumptions about human affective phenomena (what they are and how they work) which, shaped by academic motivations and values, have determined the affective constructs and operationalizations. An assumption on the purpose of affective phenomenacan be used as a teleological principle to guide the construction of a common set of metaphysical and mechanistic assumptions—a framework for human affective research. In this capstone paper for the special issue “Towards an Integrated Understanding of the Human Affectome”, we gather the tiered purpose of human affective phenomena to synthesize assumptions that account for human affective phenomenacollectively. This teleologically-grounded framework offers a principled agenda and launchpad for both organizing existing perspectives and generating new ones. Ultimately, we hope Human Affectome brings us a step closer to not only an integrated understanding of human affective phenomena, but an integrated field for affective research

The Human Affectome

Over the last decades, the interdisciplinary field of the affective sciences has seen proliferation rather than integration of theoretical perspectives. This is due to differences in metaphysical and mechanistic assumptions about human affective phenomena (what they are and how they work) which, shaped by academic motivations and values, have determined the affective constructs and operationalizations. An assumption on the purpose of affective phenomena can be used as a teleological principle to guide the construction of a common set of metaphysical and mechanistic assumptions-a framework for human affective research. In this capstone paper for the special issue "Towards an Integrated Understanding of the Human Affectome", we gather the tiered purpose of human affective phenomena to synthesize assumptions that account for human affective phenomena collectively. This teleologically-grounded framework offers a principled agenda and launchpad for both organizing existing perspectives and generating new ones. Ultimately, we hope Human Affectome brings us a step closer to not only an integrated understanding of human affective phenomena, but an integrated field for affective research