Drug use is a choice with immediate positive outcomes, but long-term negative consequences. Thus, the repeated use of drugs in the face of negative consequences suggests dysfunction in the cognitive mechanisms underpinning decision-making. This cognitive dysfunction can be mapped into three stages: the formation of preferences involving valuation of decision options; choice implementation including motivation, self-regulation and inhibitory processes; and feedback processing implicating reinforcement learning. This article reviews behavioral studies that have examined alterations in these three stages of decision-making in people with substance use disorders. Relative to healthy individuals, those with alcohol, cannabis, stimulant and opioid use disorders value risky options more highly during the formation of preferences; have a greater appetite for superficially attractive rewards during choice implementation; and are both more efficient in learning from rewards and less efficient in learning from losses during feedback processing. These observed decision-making deficits are most likely due to both premorbid factors and drug-induced effects. Because decision-making deficits have been prospectively associated with a greater risk of drug relapse, we advocate for greater research on modulating the component stages that give rise to dysfunctional decision-making in disorders of addiction.

To improve the translational predictability of treatment strategies for Huntington's disease (HD), sensitive and analogous cognitive outcomes are needed across HD animal models and humans. Spatial memory measures are promising candidates because they are based on 'visual' or 'non-verbal' cognition, and are commonly tested in both animals and humans. Here, we consider the suitability of spatial memory for strengthening translational links between animals and humans in HD research and clinical trials. We describe findings of spatial memory impairments in human HD and mouse models, including which aspects of spatial memory are most affected and at which time points in disease progression. We also describe the neural systems that underlie spatial memory and link spatial memory impairments to HD neuropathology, focussing on striatal and hippocampal systems. We provide a critical analysis of the literature in terms of the suitability of spatial memory for bridging the translational gap between species. Finally, we discuss possible neural mechanisms that might explain the spatial memory impairments seen in HD, and their relevance to potential treatments.

Normal volunteers, aged 30 to 99 years, were studied with MRI. Age was related to estimated volumes of: gray matter, white matter, and CSF of the cerebrum and cerebellum; gray matter, white matter, white matter abnormality, and CSF within each cerebral lobe; and gray matter of eight subcortical structures. The results were: 1) Age-related losses in the hippocampus were significantly accelerated relative to gray matter losses elsewhere in the brain. 2) Among the cerebral lobes, the frontal lobes were disproportionately affected by cortical volume loss and increased white matter abnormality. 3) Loss of cerebral and cerebellar white matter occurred later than, but was ultimately greater than, loss of gray matter. It is estimated that between the ages of 30 and 90 volume loss averages 14% in the cerebral cortex, 35% in the hippocampus, and 26% in the cerebral white matter. Separate analyses were conducted in which genetic risk associated with the Apolipoprotein E epsilon4 allele was either overrepresented or underrepresented among elderly participants. Accelerated loss of hippocampal volume was observed with both analyses and thus does not appear to be due to the presence of at-risk subjects. MR signal alterations in the tissues of older individuals pose challenges to the validity of current methods of tissue segmentation, and should be considered in the interpretation of the results.

We examined the Trail Making Test (TMT) in a sample of 767 participants with prodromal Huntington disease (prodromal HD) and 217 healthy comparisons to determine the contributions of motor, psychiatric, and cognitive changes to TMT scores. Eight traditional and derived TMT scores were also evaluated for their ability to differentiate prodromal participants closer to estimated age of diagnosis from those farther away and prodromal individuals from healthy comparisons. Results indicate that motor signs only mildly affected Part A, and psychiatric symptoms did not affect either part. Tests of perceptual processing, visual scanning, and attention were primarily associated with Part A, and executive functioning (response inhibition, set-shifting), processing speed, and working memory were associated with Part B. Additionally, TMT scores differentiated between healthy comparisons and prodromal HD individuals as far as 9-15 years before estimated diagnosis. In participants manifesting prodromal motor signs and psychiatric symptoms, the TMT primarily measures cognition and is able to discriminate between groups based on health status and estimated time to diagnosis.