A fundamental assumption in neuroscience is that brain structure determines function. Accordingly, functionally distinct regions of cortex should be structurally distinct in their connections to other areas. We tested this hypothesis in relation to face selectivity in the fusiform gyrus. By using only structural connectivity, as measured through diffusion weighted imaging, we are able to predict functional activation to faces in the fusiform gyrus. These predictions outperformed two control models and a standard group-average benchmark. The structure-function relationship discovered from these participants was highly robust in predicting activation in a second group of participants, despite differences in acquisition parameters and stimuli. This approach can thus reliably estimate activation in participants who cannot perform functional imaging tasks, and is an alternative to group-activation maps. Additionally, we identified cortical regions whose connectivity is highly influential in predicting face-selectivity within the fusiform, suggesting a possible mechanistic architecture underlying face processing in humans.

Fluid intelligence is important for successful functioning in the modern world, but much evidence suggests that fluid intelligence is largely immutable after childhood. Recently, however, researchers have reported gains in fluid intelligence after multiple sessions of adaptive working memory training in adults. The current study attempted to replicate and expand those results by administering a broad assessment of cognitive abilities and personality traits to young adults who underwent 20 sessions of an adaptive dual n-back working memory training program and comparing their post-training performance on those tests to a matched set of young adults who underwent 20 sessions of an adaptive attentional tracking program. Pre- and post-training measurements of fluid intelligence, standardized intelligence tests, speed of processing, reading skills, and other tests of working memory were assessed. Both training groups exhibited substantial and specific improvements on the trained tasks that persisted for at least 6 months post-training, but no transfer of improvement was observed to any of the non-trained measurements when compared to a third untrained group serving as a passive control. These findings fail to support the idea that adaptive working memory training in healthy young adults enhances working memory capacity in non-trained tasks, fluid intelligence, or other measures of cognitive abilities.

Context-Current behavioral measures poorly predict treatment outcome in social anxiety disorder (SAD). To our knowledge, this is the first study to examine neuroimaging-based treatment prediction in SAD.Objective-To measure brain activation in patients with SAD as a biomarker to predict subsequent response to cognitive behavioral therapy (CBT).Design-Functional magnetic resonance imaging (fMRI) data were collected prior to CBT intervention. Changes in clinical status were regressed on brain responses and tested for selectivity for social stimuli.

We asked whether brain connectomics can predict response to treatment for a neuropsychiatric disorder better than conventional clinical measures. Pre-treatment resting-state brain functional connectivity and diffusion-weighted structural connectivity were measured in 38 patients with social anxiety disorder (SAD) to predict subsequent treatment response to cognitive behavioral therapy (CBT). We used a priori bilateral anatomical amygdala seed-driven resting connectivity and probabilistic tractography of the right inferior longitudinal fasciculus together with a data-driven multivoxel pattern analysis of whole-brain resting-state connectivity before treatment to predict improvement in social anxiety after CBT. Each connectomic measure improved the prediction of individuals' treatment outcomes significantly better than a clinical measure of initial severity, and combining the multimodal connectomics yielded a fivefold improvement in predicting treatment response. Generalization of the findings was supported by leave-one-out cross-validation. After dividing patients into better or worse responders, logistic regression of connectomic predictors and initial severity combined with leave-one-out cross-validation yielded a categorical prediction of clinical improvement with 81% accuracy, 84% sensitivity and 78% specificity. Connectomics of the human brain, measured by widely available imaging methods, may provide brain-based biomarkers (neuromarkers) supporting precision medicine that better guide patients with neuropsychiatric diseases to optimal available treatments, and thus translate basic neuroimaging into medical practice.

In addition to the classic motor symptoms, Parkinson’s disease (PD) is associated with a variety of non-motor symptoms that significantly reduce quality of life, even in the early stages of the disease. There is an urgent need to develop evidence-based treatments for these symptoms, which include mood disturbances, cognitive dysfunction, and sleep disruption. We focus here on exercise interventions, which have been used to improve mood, cognition, and sleep in healthy older adults and clinical populations, but to date have primarily targeted motor symptoms in PD. We synthesize the existing literature on the benefits of aerobic exercise and strength training on mood, sleep, and cognition as demonstrated in healthy older adults and adults with PD, and suggest that these types of exercise offer a feasible and promising adjunct treatment for mood, cognition, and sleep difficulties in PD. Across stages of the disease, exercise interventions represent a treatment strategy with the unique ability to improve a range of non-motor symptoms while also alleviating the classic motor symptoms of the disease. Future research in PD should include non-motor outcomes in exercise trials with the goal of developing evidence-based exercise interventions as a safe, broad-spectrum treatment approach to improve mood, cognition, and sleep for individuals with PD.

Parkinson’s disease (PD) is characterized by motor symptoms, but nonmotor symptoms also significantly impair daily functioning and reduce quality of life. Anxiety is prevalent and debilitating in PD, but remains understudied and undertreated. Much affective research in PD focuses on depression rather than anxiety, and as such, there are no evidence-based treatments for anxiety in this population. Cognitive-behavioral therapy (CBT) has shown promise for treating depression in PD and may be efficacious for anxiety. This exploratory study implemented a multiple-baseline single-case experimental design to evaluate the utility and feasibility of CBT for individuals with PD who also met criteria for a DSM-5 anxiety disorder ( n = 9). Participants were randomized to a 2-, 4-, or 6-week baseline phase, followed by 12 CBT sessions, and two post treatment assessments (immediately post treatment and 6-week follow-up). Multiple outcome measures of anxiety and depression were administered weekly during baseline and intervention. Weekly CBT sessions were conducted in-person ( n = 5) or via secure videoconferencing ( n = 4). At post treatment, seven of the nine participants showed significant reductions in anxiety and/or depression, with changes functionally related to treatment and most improvements maintained at 6-week follow-up. Effects of CBT on secondary outcomes varied across participants, with preliminary evidence for reduction in fear of falling. Adherence and retention were high, as were treatment satisfaction and acceptability. The findings of this pilot study provide preliminary evidence for the utility of CBT as a feasible treatment for anxiety and comorbid depressive symptoms in PD and highlight the potential of telehealth interventions for mood in this population.

Objective Parkinson’s disease (PD) has long been conceptualized as a motor disorder, but non-motor symptoms also manifest in the disease and significantly reduce quality of life. Anxiety and cognitive dysfunction are prevalent non-motor symptoms, even in early disease stages, but the relation between these symptoms remains poorly understood. We examined self-reported anxiety and neurocognitive function, indexed by measures of executive function (set-shifting and phonemic fluency), categorical fluency, and attention/working memory. We hypothesized that anxiety would correlate with cognitive performance. Method The Beck Anxiety Inventory and cognitive tests (Trail Making, Verbal Fluency, Digit Span) were administered to 77 non-demented adults with mild to moderate idiopathic PD (39 men, 38 women; mean age = 62.9 years). Results Higher anxiety was associated with more advanced disease stage and severity and with poorer set-shifting, when using a derived metric to account for motoric slowing. Depression correlated with greater anxiety and disease severity, but not with cognitive performance. Conclusions Our findings support the association of anxiety with a specific domain of executive function, set-shifting, in non-demented individuals with mild to moderate PD, raising the possibility that treatment of anxiety may alleviate aspects of executive dysfunction in this population.

ImportanceNational Institute on Aging–Alzheimer’s Association (NIA-AA) workgroups have proposed biological research criteria intended to identify individuals with preclinical Alzheimer disease (AD).ObjectiveTo assess the clinical value of these biological criteria to identify older individuals without cognitive impairment who are at near-term risk of developing symptomatic AD.Design, Setting, and ParticipantsThis longitudinal cohort study used data from 4 independent population-based cohorts (PREVENT-AD, HABS, AIBL, and Knight ADRC) collected between 2003 and 2021. Participants were older adults without cognitive impairment with 1 year or more of clinical observation after amyloid β and tau positron emission tomography (PET). Median clinical follow-up after PET ranged from 1.94 to 3.66 years.ExposuresBased on binary assessment of global amyloid burden (A) and a composite temporal region of tau PET uptake (T), participants were stratified into 4 groups (A+T+, A+T−, A−T+, A−T−). Presence (+) or absence (−) of neurodegeneration (N) was assessed using temporal cortical thickness.Main Outcomes and MeasuresEach cohort was analyzed separately. Primary outcome was clinical progression to mild cognitive impairment (MCI), identified by a Clinical Dementia Rating score of 0.5 or greater in Knight ADRC and by consensus committee review in the other cohorts. Clinical raters were blind to imaging, genetic, and fluid biomarker data. A secondary outcome was cognitive decline, based on a slope greater than 1.5 SD below the mean of an independent subsample of individuals without cognitive impairment. Outcomes were compared across the biomarker groups.ResultsAmong 580 participants (PREVENT-AD, 128; HABS, 153; AIBL, 48; Knight ADRC, 251), mean (SD) age ranged from 67 (5) to 76 (6) years across cohorts, with between 55% (137/251) and 74% (95/128) female participants. Across cohorts, 33% to 83% of A+T+ participants progressed to MCI during follow-up (mean progression time, 2-2.72 years), compared with less than 20% of participants in other biomarker groups. Progression further increased to 43% to 100% when restricted to A+T+(N+) individuals. Cox proportional hazard ratios for progression to MCI in the A+T+ group vs other biomarker groups were all 5 or greater. Many A+T+ nonprogressors also showed longitudinal cognitive decline, while cognitive trajectories in other groups remained predominantly stable.Conclusions and RelevanceThe clinical prognostic value of NIA-AA research criteria was confirmed in 4 independent cohorts, with most A+T+(N+) older individuals without cognitive impairment developing AD symptoms within 2 to 3 years.