Cognitive impairment is one of the most common symptoms of anti-leucine rich glioma inactivated 1 (anti-LGI-1) encephalitis, but little is known about the cognitive profile of these patients. This study characterized the cognitive profile of patients with anti-LGI-1 encephalitis and compared patterns of impairment to healthy controls and other patient groups with known temporal lobe/limbic involvement.

A retrospective analysis of adult patients with anti-LGI-1 encephalitis who underwent neuropsychological assessment was conducted. Performance patterns of anti-LGI-1 patients were compared to patients deemed cognitively healthy (HC), as well as patients with amnestic mild cognitive impairment (aMCI) and temporal lobe epilepsy (TLE).

Among 10 anti-LGI encephalitis patients (60% male, median age 67.5 years) who underwent neuropsychological testing (median = 38.5 months from symptom onset), cognitive deficits were common, with 100% of patients showing impairment (≤1.5 SD below mean) on 1+ measures and 80% on 2+ measures. Patients with anti-LGI-1 encephalitis performed worse than controls on measures of basic attention, vigilance, psychomotor speed, complex figure copy, and aspects of learning/memory. Of measures which differed from controls, there were no differences between the anti-LGI-1 and TLE patients, while the anti-LGI-1 patients exhibited higher rates of impairment in basic attention and lower rates of delayed verbal memory impairment compared to the aMCI patients.

Long-term cognitive deficits are common in patients with anti-LGI-1 encephalitis and involve multiple domains. Future research in larger samples is needed to confirm these findings.

The spread of media multitasking in the modern world determines researcher’s interest in studying the neurocognitive development features of children who strive to act in this mode since childhood (Minear et al., 2013; Uncapher et al., 2016).

The aim is to study neuropsychological profiles of children and adolescents with single-tasking and multitasking.

Quasi-experiment was conducted among 154 children of three age groups (7-10; 11-13; 14-16) and included simultaneous tasks performance on a computer and a smartphone. Neuropsychological indicators were studied (Akhutina, 2016): programming and control, serial organization, visual and auditory-speech memory, neurodynamics. The behavior social modeling and executive functions were studied with WISC (Information and Comprehension subtests) and Dots-test (Akhutina et al., 2017). The multitaskers groups were identified according to the number of returns to tasks: single-taskers (42.9%), single-taskers with multitasking elements (1-2 returns) (40.9%), multitaskers (3 and more returns) (16.2%).

The number of multitaskers increased by adolescence. In children aged 7-10 single-taskers were more productive than multitaskers in programming, switchability, the volume of auditory-speech and visual memory, neurodynamics. They performed Dots-test faster. At the age of 11-13, multitaskers had higher scores on the Comprehension subtest and higher verbal activity when composing a story. Regulation and switchability errors in multitaskers aged 11-13 were episodic. At the age of 14-16 multitaskers were more productive in some parameters of switchability.

In primary school single-taskers have a neurocognitive advantage, but by adolescence differences are leveled, and in some parameters multitaskers are ahead of single-taskers. The study was funded by RFBR, project No. 19-29-14181.

The reported study was funded by RFBR, project No. 19-29-14181.

Literature showed that patients suffering from disorders belonging to the schizophrenic (SZ) and bipolar (DB) spectrum have a qualitatively similar but quantitatively different neurocognitive impairment that correlates with the outcomes. However, the majority of former studies are conducted on patients in remission phase.

This study aims to compare cognitive functions between SZ and DB in the acute phase and their possible correlations with treatment outcomes.

In a prospective longitudinal study conducted at the SPDC Ausl unit of Romagna - Cesena, 57 SZ and 82 DB took part in the study. The diagnosis was based on the SCID5 CV and SCID5 DP. Symptom severity was assessed with BPRS and HONOS both at the beginning and at the end of hospitalization. Executive functions were measured with Tower of London (ToL) and Modified Wisconsin Card Sorting Test (MCST), attention with Attentive Matrices (MA) and Stroop Test (ST), non-verbal logic skills with Colored Matrices by Raven (PM47). The statistical analyzes applied are ANOVA and logistic regression.

The cognitive tests did not reveal significant differences between SZ and DB. The logistic regression analysis showed that the scores obtained at the MCST and MA positively correlate with the efficacy of the treatment for both groups.

Cognition in DB and SZ patients was similarly impaired, supporting recent theories that placed diagnoses on a continuum of severity. Moreover, the results indicated that also in the acute phase the best predictors of the outcome were flexibility in problem solving strategies and visuospatial attention.

No significant relationships.

Attention Deficit Hyperactivity Disorder (ADHD) is a Neurodevelopmental Disorder characterized by persistent pattern of inattention and hyperactivity / impulsivity. There is considerable difficulty in diagnosing ADHD, mainly to discriminate what could be symptoms arising from ADHD or typical age behaviors. The decision tree model is a statistical algorithm, a predictive model built with comparisons of values for a given objective that can be compared with other constant values, placing these variables in a database at hierarchical levels.

This study aims to apply the decision tree model in directing the screening of ADHD complaints to analyze which cognitive and behavioral parameters would be better associations with ADHD accurate diagnosis

We used a database of research protocol with 202 children assessed with complaints of ADHD and a control group with 185 participants. Decision tree analyzed parameters selected from the cognitive instruments, such voluntary attention, Continuous Performance Test indexes, WCST indexes, Wechsler Intelligence indexes and behavioral scales from CBCL/6-1 and TRF/6-18.

The highlighted results points to WCST index like: “Perseverative answers” and “Perseverative errors” and “learning to learn” joint to “CPT omissions” and behavioral scales as “CBCL ADHD”, and “CBCL Problems of Attention” produces accuracy of diagnosis discrimination from 84.7% to 60% in the precision of the decision tree.

The decision tree and machine learning approaches can be effective in directing the screening of typical ADHD complaints.

No significant relationships.