Interpretable deep learning of myelin histopathology in age-related cognitive impairment

Age-related cognitive impairment is multifactorial, with numerous underlying and frequently co-morbid pathological correlates. Amyloid beta (Aβ) plays a major role in Alzheimer's type age-related cognitive impairment, in addition to other etiopathologies such as Aβ-independent hyperphosphorylated tau, cerebrovascular disease, and myelin damage, which also warrant further investigation. Classical methods, even in the setting of the gold standard of postmortem brain assessment, involve semi-quantitative ordinal staging systems that often correlate poorly with clinical outcomes, due to imperfect cognitive measurements and preconceived notions regarding the neuropathologic features that should be chosen for study. Improved approaches are needed to identify histopathological changes correlated with cognition in an unbiased way. We used a weakly supervised multiple instance learning algorithm on whole slide images of human brain autopsy tissue sections from a group of elderly donors to predict the presence or absence of cognitive impairment (n = 367 with cognitive impairment, n = 349 without). Attention analysis allowed us to pinpoint the underlying subregional architecture and cellular features that the models used for the prediction in both brain regions studied, the medial temporal lobe and frontal cortex. Despite noisy labels of cognition, our trained models were able to predict the presence of cognitive impairment with a modest accuracy that was significantly greater than chance. Attention-based interpretation studies of the features most associated with cognitive impairment in the top performing models suggest that they identified myelin pallor in the white matter. Our results demonstrate a scalable platform with interpretable deep learning to identify unexpected aspects of pathology in cognitive impairment that can be translated to the study of other neurobiological disorders.

Juvenile delinquency, adult criminality, and adult psychiatric treatment: an epidemiological study

This report explores some associations among juvenile-delinquency, subsequent criminality, and subsequent psychiatric treatment. A sample of 255 males known to the juvenile court 25 years prior to the study is examined in terms of subsequent documented psychiatric treatment and/or criminal activity. Of the 255 former delinquents, 6% were known later to both criminal justice and psychiatric systems, 6% to psychiatric systems only, 28% to the criminal justice system only, and 60% to neither. Delinquents with later psychiatric histories were twice as likely to be known to the criminal justice system than were those without psychiatric histories. Those with adult psychiatric histories were also significantly younger at the time of their first delinquent offense and committed more juvenile offenses than the nonpsychiatric group. Only 2 of the 16 individuals later known to both systems were diagnosed sociopathic. The findings are discussed.