The Program for the Education and Enrichment of Relational Skills (PEERS^®) is an evidence-based intervention developed for autistic individuals to support social communication, peer interactions, independence, and interpersonal relationships. Despite a demonstrated effectiveness for young autistic individuals in the US and several other countries, PEERS has yet to be modified to support the needs of autistic adults across the lifespan. The present study describes how our team sought autistic voices to adapt PEERS for adults of any age. Specifically, we aimed to address the needs of middle-aged and older adults and adapt the curriculum to be more neurodiversity-affirming. Between two cohorts that completed the program consecutively, we evaluated the acceptability of the adapted PEERS program and made refinements based on feedback from autistic participants and their study partners. Results indicated that Cohort 2 reported higher satisfaction with the PEERS components and overall program than Cohort 1, suggesting effective refinement. We present a framework of adaptations that more specifically address the needs of middle-aged and older adults in a neurodiverse-affirming way compared to previous iterations. Our approach to implementing an adapted PEERS curriculum across the adult lifespan may serve as a model for improved clinical care and cultivate the acceptance of neurodiversity in the interpersonal domains of autistic adults’ lives.

Introduction: Mindfulness‐based stress reduction (MBSR) reduces depression, anxiety, and pain for people suffering from a variety of illnesses, and there is a growing need to understand the neurobiological networks implicated in self‐reported psychological change as a result of training. Combining complementary and alternative treatments such as MBSR with other therapies is helpful; however, the time commitment of the traditional 8‐week course may impede accessibility. This pilot study aimed to (1) determine if an abbreviated MBSR course improves symptoms in chronic back pain patients and (2) examine the neural and behavioral correlates of MBSR treatment.Methods: Participants were assigned to 4 weeks of weekly MBSR training (n = 12) or a control group (stress reduction reading; n = 11). Self‐report ratings and task‐based functional MRI were obtained prior to, and after, MBSR training, or at a yoked time point in the control group.Results: While both groups showed significant improvement in total depression symptoms, only the MBSR group significantly improved in back pain and somatic‐affective depression symptoms. The MBSR group also uniquely showed significant increases in regional frontal lobe hemodynamic activity associated with gaining awareness to changes in one's emotional state.Conclusions: An abbreviated MBSR course may be an effective complementary intervention that specifically improves back pain symptoms and frontal lobe regulation of emotional awareness, while the traditional 8‐week course may be necessary to detect unique improvements in total anxiety and cognitive aspects of depression.

BACKGROUND AND PURPOSE: Perfusion MR imaging measures of relative CBV can distinguish recurrent tumor from posttreatment radiation effects in high-grade gliomas. Currently, relative CBV measurement requires normalization based on user-defined reference tissues. A recently proposed method of relative CBV standardization eliminates the need for user input. This study compares the predictive performance of relative CBV standardization against relative CBV normalization for quantifying recurrent tumor burden in high-grade gliomas relative to posttreatment radiation effects. MATERIALS AND METHODS: We recruited 38 previously treated patients with high-grade gliomas (World Health Organization grades III or IV) undergoing surgical re-resection for new contrast-enhancing lesions concerning for recurrent tumor versus posttreatment radiation effects. We recovered 112 image-localized biopsies and quantified the percentage of histologic tumor content versus posttreatment radiation effects for each sample. We measured spatially matched normalized and standardized relative CBV metrics (mean, median) and fractional tumor burden for each biopsy. We compared relative CBV performance to predict tumor content, including the Pearson correlation (r), against histologic tumor content (0%–100%) and the receiver operating characteristic area under the curve for predicting high-versus-low tumor content using binary histologic cutoffs (≥50%; ≥80% tumor). RESULTS: Across relative CBV metrics, fractional tumor burden showed the highest correlations with tumor content (0%–100%) for normalized (r = 0.63, P < .001) and standardized (r = 0.66, P < .001) values. With binary cutoffs (ie, ≥50%; ≥80% tumor), predictive accuracies were similar for both standardized and normalized metrics and across relative CBV metrics. Median relative CBV achieved the highest area under the curve (normalized = 0.87, standardized = 0.86) for predicting ≥50% tumor, while fractional tumor burden achieved the highest area under the curve (normalized = 0.77, standardized = 0.80) for predicting ≥80% tumor. CONCLUSIONS: Standardization of relative CBV achieves similar performance compared with normalized relative CBV and offers an important step toward workflow optimization and consensus methodology.

BACKGROUND AND PURPOSE: MR imaging–based modeling of tumor cell density can substantially improve targeted treatment of glioblastoma. Unfortunately, interpatient variability limits the predictive ability of many modeling approaches. We present a transfer learning method that generates individualized patient models, grounded in the wealth of population data, while also detecting and adjusting for interpatient variabilities based on each patient9s own histologic data. MATERIALS AND METHODS: We recruited patients with primary glioblastoma undergoing image-guided biopsies and preoperative imaging, including contrast-enhanced MR imaging, dynamic susceptibility contrast MR imaging, and diffusion tensor imaging. We calculated relative cerebral blood volume from DSC-MR imaging and mean diffusivity and fractional anisotropy from DTI. Following image coregistration, we assessed tumor cell density for each biopsy and identified corresponding localized MR imaging measurements. We then explored a range of univariate and multivariate predictive models of tumor cell density based on MR imaging measurements in a generalized one-model-fits-all approach. We then implemented both univariate and multivariate individualized transfer learning predictive models, which harness the available population-level data but allow individual variability in their predictions. Finally, we compared Pearson correlation coefficients and mean absolute error between the individualized transfer learning and generalized one-model-fits-all models. RESULTS: Tumor cell density significantly correlated with relative CBV (r = 0.33, P < .001), and T1-weighted postcontrast (r = 0.36, P < .001) on univariate analysis after correcting for multiple comparisons. With single-variable modeling (using relative CBV), transfer learning increased predictive performance (r = 0.53, mean absolute error = 15.19%) compared with one-model-fits-all (r = 0.27, mean absolute error = 17.79%). With multivariate modeling, transfer learning further improved performance (r = 0.88, mean absolute error = 5.66%) compared with one-model-fits-all (r = 0.39, mean absolute error = 16.55%). CONCLUSIONS: Transfer learning significantly improves predictive modeling performance for quantifying tumor cell density in glioblastoma.

The male preponderance in autism spectrum disorder (ASD) led to the hypothesis that aspects of female biology are protective against ASD. Females with ASD (ASD-F) report more compensatory behaviors (i.e. “camouflaging”) to overcome ASD-related social differences, which may be a mechanism of protection. No studies have examined sex-related brain pathways supporting camouflaging in ASD-F, despite its potential to inform mechanisms underlying the ASD sex bias. We used functional connectivity (FC) to investigate “sex-atypical” and “sex-typical” FC patterns linked to camouflaging in adults with ASD and examined multimodal coherence of findings via structural connectometry. Exploratory associations with cognitive/emotional functioning examined the adaptive nature of FC patterns. We found (i) “sex-atypical” FC patterns linked to camouflaging in the hypothalamus and precuneus and (ii) “sex-typical” patterns in the right anterior cingulate and anterior parahippocampus. Higher hypothalamic FC with a limbic reward cluster also correlated with better cognitive control/emotion recognition. Structural connectometry validated FC results with consistent brain pathways/effect patterns implicated in ASD-F. In summary, “male-typical” and “female-typical” brain connectivity patterns support camouflaging in ASD-F in circuits implicated in reward, emotion, and memory retrieval. “Sex-atypical” results are consistent with fetal steroidogenic/neuroinflammatory hypotheses. However, female genetics/biology may contribute to “female-typical” patterns implicated in camouflaging.

Many studies suggest sex differences in memory and hippocampal size, and that hormone therapy (HT) may positively affect these measures in women; however, the parameters of HT use that most likely confer benefits are debated. We evaluated the impact of sex and postmenopausal HT use on verbal learning and memory and hippocampal size in 94 cognitively intact women and 49 men. Using analysis of covariance that controlled for age and education, women had better total word learning and delayed verbal memory performance than men. HT analyses showed that non-HT users performed similarly to men, while HT users performed better than men in Delayed Memory regardless of whether use was current or in the past. Women had larger hippocampal volumes than men regardless of whether they were HT users. Using univariate linear models, we assessed group differences in the predictive value of hippocampal volumes for verbal learning and memory. Hippocampal size significantly predicted memory performance for men and non-HT users, but not for HT users. This lack of relationship between hippocampal size and verbal learning and memory performance in HT users suggests HT use may impact memory through extra-hippocampal neural systems.