Cognitive impairment in Parkinson's disease (CIPD) is present in approximately 40% of patients. Language deficits, evidenced by poor word- retrieval, have historically characterized memory weaknesses in PD. That is, the "retrieval deficit hypothesis," suggests successful memory encoding, but poor retrieval subsequent to language and executive dysfunction, another prominent area of CIPD. However, recent studies suggest that memory impairments in PD are instead at the level of learning. At present, several suggested etiologies to explain learning impairments in PD exist that are not related to language, for example that processing speed deficits (another characteristic of CIPD) impact learning; however, other studies present evidence against this theory. Therefore, we hypothesize that deficits in language continue to be a primary component of memory impairment in PD, but at the level of learning rather than retrieval

85 adults (age M = 61.54, SD = 10.00; %female = 26.7; Dementia Rating Scale M = 137.77, SD = 5.63) diagnosed with Parkinson's disease according to the UK Brain Bank criteria for idiopathic PD, completed a neuropsychological test battery when "off" levodopa medication. The battery included the Boston Naming Test (BNT), verbal fluency tests (Controlled Oral Word Association [COWA] and category fluency), the California Verbal Learning Test, 2nd Edition (CVLT-II), and the Oral Symbol Digit Modalities Test (SDMT). Separate linear regression models were used to examine BNT, COWA, category fluency, and SDMT performance as predictors of total learning (sum of trials 1-5), short-delay free recall, long-delay free recall, and recognition discriminability on the CVLT-II. Analyses were adjusted for age, sex, education, and disease severity (MDS-Unified Parkinson's Disease Rating Scale, part 3 score). Follow up analyses adjusted for processing speed (oral SDMT).

Adjusted linear regression models revealed that both verbal fluencies predicted verbal learning (letter: ß = .37, p < .01; category: ß = .45, p < .01), long-delay free recall (letter: ß = .25, p = .05; category: ß = .34, p = .01), and recognition discriminability (letter: ß = .36, p = .02; category: ß =.33, p = .03) on the CVLT-II. Confrontation naming significantly predicted only long-delay free recall (ß =.31, p = .01). Processing speed predicted verbal learning (ß = .51, p < .01), short-delay free recall (ß = .35, p = .03), and long-delay free recall (ß = .44, p < .01). After adjusting for processing speed, letter fluency significantly predicted learning (ß = .23, p = .05) and discriminability (ß = .33, p = .04). Category fluency significantly predicted learning only (ß = .28, p = .04). Finally, confrontation naming significantly predicted only long-delay free recall (ß= .28, p = .01).

While processing speed was associated with verbal learning and recall, components of language predicted variance in verbal learning in PD that was not accounted for by speed. Additionally, discriminability was related to aspects of language that are more reliant on executive functioning. It is therefore suggested that verbal memory in PD is interpreted within the context of one's language ability. Other potential mechanisms and clinical implications are discussed.

Obesity is highly prevalent and disabling, especially in individuals with severe mental illness including bipolar disorders (BD). The brain is a target organ for both obesity and BD. Yet, we do not understand how cortical brain alterations in BD and obesity interact.

We obtained body mass index (BMI) and MRI-derived regional cortical thickness, surface area from 1231 BD and 1601 control individuals from 13 countries within the ENIGMA-BD Working Group. We jointly modeled the statistical effects of BD and BMI on brain structure using mixed effects and tested for interaction and mediation. We also investigated the impact of medications on the BMI-related associations.

BMI and BD additively impacted the structure of many of the same brain regions. Both BMI and BD were negatively associated with cortical thickness, but not surface area. In most regions the number of jointly used psychiatric medication classes remained associated with lower cortical thickness when controlling for BMI. In a single region, fusiform gyrus, about a third of the negative association between number of jointly used psychiatric medications and cortical thickness was mediated by association between the number of medications and higher BMI.

We confirmed consistent associations between higher BMI and lower cortical thickness, but not surface area, across the cerebral mantle, in regions which were also associated with BD. Higher BMI in people with BD indicated more pronounced brain alterations. BMI is important for understanding the neuroanatomical changes in BD and the effects of psychiatric medications on the brain.