Structural and diffusion-weighted brain imaging predictors of attention-deficit/hyperactivity disorder and its symptomology in very young (4- to 7-year-old) children.

The current study aimed to identify the key neurobiology of attention-deficit/hyperactivity disorder (ADHD), as it relates to ADHD diagnostic category and symptoms of hyperactive/impulsive behaviour and inattention. To do so, we adapted a predictive modelling approach to identify the key structural and diffusion-weighted brain imaging measures and their relative standing with respect to teacher ratings of executive function (EF) (measured by the Metacognition Index of the Behavior Rating Inventory of Executive Function [BRIEF]) and negativity and emotion regulation (ER) (measured by the Emotion Regulation Checklist [ERC]), in a critical young age range (ages 4 to 7, mean age 5.52 years, 82.2% Hispanic/Latino), where initial contact with educators and clinicians typically take place. Teacher ratings of EF and ER were predictive of both ADHD diagnostic category and symptoms of hyperactive/impulsive behaviour and inattention. Among the neural measures evaluated, the current study identified the critical importance of the largely understudied diffusion-weighted imaging measures for the underlying neurobiology of ADHD and its associated symptomology. Specifically, our analyses implicated the inferior frontal gyrus as a critical predictor of ADHD diagnostic category and its associated symptomology, above and beyond teacher ratings of EF and ER. Collectively, the current set of findings have implications for theories of ADHD, the relative utility of neurobiological measures with respect to teacher ratings of EF and ER, and the developmental trajectory of its underlying neurobiology.

Is there any incremental benefit to conducting neuroimaging and neurocognitive assessments in the diagnosis of ADHD in young children? A machine learning investigation.

Given the negative trajectories of early behavior problems associated with ADHD, early diagnosis is considered critical to enable intervention and treatment. To this end, the current investigation employed machine learning to evaluate the relative predictive value of parent/teacher ratings, behavioral and neural measures of executive function (EF) in predicting ADHD in a sample consisting of 162 young children (ages 4-7, mean age 5.55, 82.6 % Hispanic/Latino). Among the target measures, teacher ratings of EF were the most predictive of ADHD. While a more extensive evaluation of neural measures, such as diffusion-weighted imaging, may provide more information as they relate to the underlying cognitive deficits associated with ADHD, the current study indicates that measures of cortical anatomy obtained in research studies, as well cognitive measures of EF often obtained in routine assessments, have little incremental value in differentiating typically developing children from those diagnosed with ADHD. It is important to note that the overlap between some of the EF questions in the BRIEF, and the ADHD symptoms could be enhancing this effect. Thus, future research evaluating the importance of such measures in predicting children's functional impairment in academic and social areas would provide additional insight into their contributing role in ADHD.

Linguistic analysis of the autobiographical memories of individuals with major depressive disorder.

BACKGROUND: Major depressive disorder (MDD) is characterized by biases in memory, attention, and cognition. The present study utilized the Linguistic Inquiry and Word Count (LIWC) to examine the content of specific autobiographical memories (AMs) recalled by individuals with MDD during an autobiographical memory task. METHODS: We examined various features of the text (including use of affective, cognitive, and self-referential terms), as well as their associations with clinical and cognitive features of MDD (depression severity, autobiographical memory specificity, amygdala activity), in 45 unmedicated adults with MDD compared to 61 healthy controls. RESULTS: When recalling positive memories MDD individuals used the word "I" less, fewer positive words, more words indicating present focus (present tense verbs), and fewer words overall to describe memories compared to controls. When recalling negative memories, MDD individuals used "I" more, more words indicating present focus, and more words overall to describe memories relative to controls. Depression severity was correlated with word count, the use of "I", and words indicating present focus in negative memories and inversely correlated with word count and the use of "I" in positive memories. Autobiographical memory specificity was correlated with word count, the use of "I", and words indicating present focus for positive memories and inversely correlated with the use of "I" and words indicating present focus for negative memories. LIMITATIONS: Due to the nature of AM recall, we could not control for the number of memories which participants recalled in each mnemonic category. CONCLUSIONS: Results align with literature implicating rumination and intensive self-focus in depression and suggest that interventions targeting specific word use may be therapeutically beneficial in the treatment of MDD.