Biology subjects

Smith, D. V.

Publications and source records attributed to Smith, D. V..

4 recordsLinked to original sources

bioRxiv2018

Reduced gray matter volume in the orbitofrontal cortex is associated with greater body mass index: a coordinate-based meta-analysis.

Meta-analyses of neuroimaging studies have not found a clear relationship between the orbitofrontal cortex and obesity, despite animal and human studies suggesting the contrary. Our primary meta-analysis examined what regions are associated with reduced gray matter volume, given increased body mass index. We identified 23 voxel-based morphometry studies examining the association between gray matter volume and body mass index. In a sample of 6,788 participants, we found that greater body mass index is associated with decreased gray matter volume in the right Brodmanns area 10 and 11, forming part of the right orbitofrontal cortex (FWE, p=0.05). Use of Brodmanns areas 10 and 11 as seeds in a Neurosynth network coactivation and text decoding analysis revealed that these regions are associated with studies of emotional regulation and processing, clinical symptoms and disorder, mentalizing and social cognition, and the Default mode network. Our finding uniquely contributes to the literature in showing a relationship between the orbitofrontal cortex and obesity and showing the wide-ranging impact these differences may have on social, mental, and emotional functioning as well as on the Default mode network. Exploratory analyses suggest the need for studies examining the effect of age on these findings.

neuroscience↗

bioRxiv2018

Meta-analysis of Reward Processing in Major Depressive Disorder: Distinct Abnormalities within the Reward Circuit?

Many neuroimaging studies have investigated reward processing dysfunction in major depressive disorder. These studies have led to the common idea that major depressive disorder is associated with blunted responses within the reward circuit, particularly in the ventral striatum. Yet, the link between major depressive disorder and reward-related responses in other regions remains inconclusive, thus limiting our understanding of the pathophysiology of major depressive disorder. To address this issue, we performed a coordinate-based meta-analysis of 41 whole-brain neuroimaging studies encompassing reward-related responses from a total of 794 patients with major depressive disorder and 803 healthy controls. Our findings argue against the common idea that major depressive disorder is primarily linked to deficits within the reward system. Instead, our results demonstrate that major depressive disorder is associated with opposing abnormalities in the reward circuit: hypo-responses in the ventral striatum and hyper-responses in the orbitofrontal cortex. The current findings suggest that dysregulated corticostriatal connectivity may underlie reward-processing abnormalities in major depressive disorder, providing an empirical foundation for a more refined understanding of abnormalities in the reward circuitry in major depressive disorder.

neuroscience↗

bioRxiv2017

Functional Parcellation of the Default Mode Network: A Large-Scale Meta-Analysis

The default mode network (DMN) consists of several regions that selectively interact to support distinct domains of cognition. Of the various sites that partake in DMN function, the posterior cingulate cortex (PCC), temporal parietal junction (TPJ), and medial prefrontal cortex (MPFC) are frequently identified as key contributors. Yet, it remains unclear whether these subcomponents of the DMN make unique contributions to specific cognitive processes and health conditions. To address this issue, we applied a meta-analytic parcellation approach used in prior work. This approach used the Neurosynth database and classification methods to quantify the association between PCC, TPJ, and MPFC activation and specific topics related to cognition and health (e.g., decision making and smoking). Our analyses replicated prior observations that the PCC, TPJ, and MPFC collectively support multiple cognitive functions such as decision making, memory, and awareness. To gain insight into the functional organization of each region, we parceled each region based on its coactivation pattern with the rest of the brain. This analysis indicated that each region could be further subdivided into functionally distinct subcomponents. Taken together, we further delineate DMN function by demonstrating the relative strengths of association among subcomponents across a range of cognitive processes and health conditions. A continued attentiveness to the specialization within the DMN allows future work to consider the nuances in sub-regional contributions necessary for healthy cognition, as well as create the potential for more targeted treatment protocols in various health conditions.

neuroscience↗

bioRxiv2017

Reason’s Enemy Is Not Emotion: Engagement of Cognitive Control Networks Explains Biases in Gain/Loss Framing

In the classic gain/loss framing effect, describing a gamble as a potential gain or loss biases people to make risk-averse or risk-seeking decisions, respectively. The canonical explanation for this effect is that frames differentially modulate emotional processes - which in turn leads to irrational choice behavior. Here, we evaluate the source of framing biases by integrating functional magnetic resonance imaging (fMRI) data from 143 human participants performing a gain/loss framing task with meta-analytic data from over 8000 neuroimaging studies. We found that activation during choices consistent with the framing effect were most correlated with activation associated with the resting or default brain, while activation during choices inconsistent with the framing effect most correlated with the task-engaged brain. Our findings argue against the common interpretation of gain/loss framing as a competition between emotion and control. Instead, our study indicates that this effect results from differential cognitive engagement across decision frames.\n\nSignificance StatementThe biases frequently exhibited by human decision-makers have often been attributed to the presence of emotion. Using a large fMRI sample and analysis of whole-brain networks defined with the meta-analytic tool Neurosynth, we find that neural activity during frame-biased decisions are more significantly associated with default behaviors (and the absence of executive control) than with emotion. These findings point to a role for neuroscience in shaping longstanding psychological theories in decision science.

neuroscience↗