Biological Psychiatry: Cognitive Neuroscience and Neuroimaging
In This IssueIn This Issue
Section snippets
Special Issue: Techniques for Translational Neuroscience
Understanding brain connectivity will help to identify the changes in neural circuitry that underlie behavioral dysfunction. In this special issue, Snyder and Bauer (pages 510–521) review the mapping of brain activity and neural connectivity in rodents using optogenetics in conjunction with either functional magnetic resonance imaging (fMRI) or optical intrinsic signal imaging. The authors also discuss implementation strategies for brain connectivity mapping in humans using transcranial
Dissecting Heterogeneity of Autism With Normative Modeling
The high heterogeneity of autism spectrum disorder (ASD) has proven a barrier to the identification of neuroimaging biomarkers. To avoid the limitation of a case-control approach, Zabihi et al. (pages 567–578) used a normative modeling approach to estimate typical cortical thickness development and then mapped the deviation of each individual ASD participant. Despite few group-level differences, they found that the ASD cohort showed highly individualized patterns of cortical alterations that
Brain Iron Imaging in Cocaine Use Disorder
Brain iron is required for neural processes involved in addiction and can be lethal to cells if unbound, especially in excess. Using an advanced iron MRI method called magnetic field correlation imaging, Adisetiyo et al. (pages 579–588) demonstrate that, compared with healthy control subjects, individuals with cocaine use disorder have elevated iron in the globus pallidus internal segment and lack the age-related gradual iron deposition within the globus pallidus and striatum that is seen in
Machine Learning for Alcoholism, HIV, and Their Comorbidity
Alcohol use disorder (AUD) and human immunodeficiency virus (HIV), both of which are associated with structural brain deficits, are commonly comorbid. Here, Adeli et al. (pages 589–599) used a machine learning approach to test whether MRIs can be used to predict diagnosis and cognitive measures in individuals with AUD, HIV, or AUD+HIV. After first identifying diagnostic patterns, their analysis predicted diagnostic classification and cognitive performance of individuals with AUD, HIV, and