Search

Personal pronouns, such as "I" and "you", require a speaker/listener to continuously re-map their reciprocal relation to their referent, depending on who is saying the pronoun. This process, called "deictic shifting", may underlie the incorrect production of these pronouns, or "pronoun reversals", such as referring to oneself with the pronoun "you", which has been reported in children with autism. The underlying neural basis of deictic shifting, however, is not understood, nor has the processing of pronouns been studied in adults with autism. The present study compared the brain activation pattern and functional connectivity (synchronization of activation across brain areas) of adults with high-functioning autism and control participants using functional magnetic resonance imaging in a linguistic perspective-taking task that required deictic shifting. The results revealed significantly diminished frontal (right anterior insula) to posterior (precuneus) functional connectivity during deictic shifting in the autism group, as well as reliably slower and less accurate behavioural responses. A comparison of two types of deictic shifting revealed that the functional connectivity between the right anterior insula and precuneus was lower in autism while answering a question that contained the pronoun "you", querying something about the participant's view, but not when answering a query about someone else's view. In addition to the functional connectivity between the right anterior insula and precuneus being lower in autism, activation in each region was atypical, suggesting over reliance on individual regions as a potential compensation for the lower level of collaborative interregional processing. These findings indicate that deictic shifting constitutes a challenge for adults with high-functioning autism, particularly when reference to one's self is involved, and that the functional collaboration of two critical nodes, right anterior insula and precuneus, may play a critical role for deictic shifting by supporting an attention shift between oneself and others.

Background: Late‐life depression (LLD) has been consistently linked to an increased risk of dementia, with studies showing that older adults with depression have a two fold risk of developing dementia. Dementia has proven difficult to treat, yet depression has several viable treatment options, particularly antidepressants. However, the efficacy of antidepressants in LLD has proven modest as antidepressants typically achieve around a 50% remission rate and only after 4‐6 weeks of treatment. In this analysis, we investigate the effectiveness of combining fMRI data with deep learning for predicting antidepressant driven depression remission. Method: In two LLD studies using venlafaxine (n = 51) and escitalopram or levomilnacipran (n = 29), resting state fMRI scans were collected at baseline and at day one of antidepressants. Region‐to‐region functional connectivity (FC) was calculated for each scan using the Shen50 atlas, and differential connectivity (DC) was calculated to compare baseline and day 1 FC. Clinical factors including age, race, education and cumulative illness burden and DC were used as input to a semi‐supervised variational autoencoder (VAE) to predict remission status at treatment end (Fig.1). Remission was encoded as a binary variable, defined as a final MADRS score of 10 or less after 12 weeks of treatment and subject to blinded clinician assessment. Monte Carlo cross‐validation over 30 repetitions was used to evaluate the model performance with 10% of the data held out for testing. The VAE was compared to a random forest classifier with the same cross validation methods using the area under the curve (AUC). Result: The VAE achieved an average mean‐squared error of.005 and AUC of 0.87 on a held out test set during cross validation. The VAE outperformed the random forest classifier which achieved an average AUC of 0.68. Conclusion: The VAE using DC in fMRI scans between baseline and day one shows the potential in accurately identifying responders to antidepressants as early as in one day. Our results show that acute changes to functional networks triggered by a single dose of antidepressants are promising as a means to improve patient outcomes. These results can contribute to optimizing treatment for LLD in the future. [ABSTRACT FROM AUTHOR]

Objectives: This study investigated subjective memory complaints in older adults and the roles of setting, response bias, and personality.Design: Cognitively normal older adults from two settings completed questionnaires measuring memory complaints, response bias, and personality.Settings: (A) Neuroimaging study with community-based recruitment and (B) academic memory clinic.Participants: Cognitively normal older adults who (A) volunteer for research (N = 92) or (B) self-referred to a memory clinic (N = 20).Measurements: Neuropsychological evaluation and adjudication of normal cognitive status were done by the neuroimaging study or memory clinic. This study administered self-reports of subjective memory complaints, response bias, five-factor personality, and depressive symptoms. Primary group differences were examined with secondary sensitivity analyses to control for sex, age, and education differences.Results: There was no significant difference in over-reporting response bias between study settings. Under-reporting response bias was higher in volunteers. Cognitive complaints were associated with response bias for two cognitive complaint measures. Neuroticism was positively associated with over-reporting in evaluation-seekers and negatively associated with under-reporting in volunteers. The relationship was reversed for Extraversion. Under-reporting bias was positively correlated with Agreeableness and Conscientiousness in volunteers.Conclusion: Evaluation-seekers do not show bias toward over-reporting symptoms compared to volunteers. Under-reporting response bias may be important to consider when screening for memory impairment in non-help-seeking settings. The Memory Functioning Questionnaire was less sensitive to reporting biases. Over-reporting may be a facet of higher Neuroticism. Findings help elucidate psychological influences on self-perceived cognitive decline and help seeking in aging and may inform different strategies for assessment by setting. [ABSTRACT FROM AUTHOR]