Psychometric properties of the Greek version of Affective Lability Scale - Short Form (ALS-18) in a sample of adults with neurodevelopmental disorders.

Affect dysregulation refers to maladaptive patterns of emotional regulation that impair daily life functioning, common in many psychiatric disorders. It is expressed with the form of affective lability, an emotional construct composed of frequent and intense fluctuations in emotion in response to both pleasant and unpleasant events or the interpretations of events. The Affective Lability Scale (ALS) is a widely used self-reporting questionnaire that measures the tendency of emotions to shift from one to another as well as their tendency to oscillate between depression and elation and between depression and anxiety. The original scale had 54 items, but a shorter form of 18-items (ALS-18) was created, with three domains: anxiety-depression shift, depression-elation shift and anger shift. The aim of the present study was to evaluate the psychometric properties of the ALS-18 Greek version. The translation was conducted by two of the authors. The study took place in the 1st Department of Psychiatry of the National and Kapodistrian University of Athens, Eginition hospital. A sample of 108 adults was included in the survey in two groups, neurodevelopmental disorder group (attention deficit hyperactivity disorder or autism spectrum disorder) and controls. They all completed ALS-18, The State - Trait Anxiety Inventory (STAIT), Difficulties in Emotion Regulation Scale (DERS), The Hospital Anxiety and Depression Scale (HADS). The ALS-18 had satisfactory internal consistency; Cronbach's α value was 0.91 for the total scale and 0.89 for Anxiety/Depression, 0.86 for Depression/Elation and 0.85 for Anger. The three-factor structure was replicated in our data. The internal consistency reliability of all the ALS-18 factors in our study could be considered satisfactory with a Cronbach's alpha coefficient of 0.85 or above for all factors. Significantly higher mean values were found for all the subscales, Anxiety/Depression, Depression/Elation and Anger, in NDD subjects as compared to controls, showing good discriminative ability. The ALS factors discriminated well between clinical and non-clinical sample. The present study reveals that the Greek version of ALS-18 presents good psychometric properties, showing good internal consistency reliability as well as concurrent and discriminative validity. It has an elevated score in NDD and thus, our results indicate that affective lability could and maybe should, be a target integrated in therapeutic strategies.

Differences in Performance of ASD and ADHD Subjects Facing Cognitive Loads in an Innovative Reasoning Experiment.

We aim to investigate whether EEG dynamics differ in adults with ASD (Autism Spectrum Disorders) and ADHD (attention-deficit/hyperactivity disorder) compared with healthy subjects during the performance of an innovative cognitive task, Aristotle's valid and invalid syllogisms, and how these differences correlate with brain regions and behavioral data for each subject. We recorded EEGs from 14 scalp electrodes (channels) in 21 adults with ADHD, 21 with ASD, and 21 healthy, normal subjects. The subjects were exposed in a set of innovative cognitive tasks (inducing varying cognitive loads), Aristotle's two types of syllogism mentioned above. A set of 39 questions were given to participants related to valid-invalid syllogisms as well as a separate set of questionnaires, in order to collect a number of demographic and behavioral data, with the aim of detecting shared information with values of a feature extracted from EEG, the multiscale entropy (MSE), in the 14 channels ('brain regions'). MSE, a nonlinear information-theoretic measure of complexity, was computed to extract a feature that quantifies the complexity of the EEG. Behavior-Partial Least Squares Correlation, PLSC, is the method to detect the correlation between two sets of data, brain, and behavioral measures. -PLSC, a variant of PLSC, was applied to build a functional connectivity of the brain regions involved in the reasoning tasks. Graph-theoretic measures were used to quantify the complexity of the functional networks. Based on the results of the analysis described in this work, a mixed 14 × 2 × 3 ANOVA showed significant main effects of group factor and brain region* syllogism factor, as well as a significant brain region* group interaction. There are significant differences between the means of MSE (complexity) values at the 14 channels of the members of the 'pathological' groups of participants, i.e., between ASD and ADHD, while the difference in means of MSE between both ASD and ADHD and that of the control group is not significant. In conclusion, the valid-invalid type of syllogism generates significantly different complexity values, MSE, between ASD and ADHD. The complexity of activated brain regions of ASD participants increased significantly when switching from a valid to an invalid syllogism, indicating the need for more resources to 'face' the task escalating difficulty in ASD subjects. This increase is not so evident in both ADHD and control. Statistically significant differences were found also in the behavioral response of ASD and ADHD, compared with those of control subjects, based on the principal brain and behavior saliences extracted by PLSC. Specifically, two behavioral measures, the emotional state and the degree of confidence of participants in answering questions in Aristotle's valid-invalid syllogisms, and one demographic variable, age, statistically and significantly discriminate the three groups' ASD. The seed-PLC generated functional connectivity networks for ASD, ADHD, and control, were 'projected' on the regions of the Default Mode Network (DMN), the 'reference' connectivity, of which the structural changes were found significant in distinguishing the three groups. The contribution of this work lies in the examination of the relationship between brain activity and behavioral responses of healthy and 'pathological' participants in the case of cognitive reasoning of the type of Aristotle's valid and invalid syllogisms, using PLSC, a machine learning approach combined with MSE, a nonlinear method of extracting a feature based on EEGs that captures a broad spectrum of EEGs linear and nonlinear characteristics. The results seem promising in adopting this type of reasoning, in the future, after further enhancements and experimental tests, as a supplementary instrument towards examining the differences in brain activity and behavioral responses of ASD and ADHD patients. The application of the combination of these two methods, after further elaboration and testing as new and complementary to the existing ones, may be considered as a tool of analysis in helping detecting more effectively such types of disorders.

Complexity analysis of the brain activity in Autism Spectrum Disorder (ASD) and Attention Deficit Hyperactivity Disorder (ADHD) due to cognitive loads/demands induced by Aristotle's type of syllogism/reasoning. A Power Spectral Density and multiscale entropy (MSE) analysis.

OBJECTIVE: We aim to investigate whether EEG dynamics differ in adults with ASD (Autism Spectrum Disorders), ADHD (attention-deficit/hyperactivity disorder), compared with healthy subjects during the performance of an innovative cognitive task: Aristotle's valid and invalid syllogisms. We follow the Neuroanatomical differences type of criterion in assessing the results of our study in supporting or not the dual-process theory of Kahneman, 2011) (Systems I & II of thinking). METHOD: We recorded EEGs from 14 scalp electrodes in 30 adults with ADHD, 30 with ASD and 24 healthy, normal subjects. The subjects were exposed in a set of innovative cognitive tasks (inducing varying cognitive loads), the Aristotle's four types of syllogism mentioned above. The multiscale entropy (MSE), a nonlinear information-theoretic measure or tool was computed to extract features that quantify the complexity of the EEG. RESULTS: The dynamics of the curves of the grand average of MSE values of the ADHD and ASD participants was significantly in higher levels for the majority of time scales, than the healthy subjects over a number of brain regions (electrodes locations), during the performance of both valid and invalid types of syllogism. This result is seemingly not in accordance of the broadly accepted 'theory' of complexity loss in 'pathological' subjects, but actually this is not the case as explained in the text. ADHD subjects are engaged in System II of thinking, for both Valid and Invalid syllogism, ASD and Control in System I for valid and invalid syllogism, respectively. A surprising and 'provocative' result of this paper, as shown in the next sections, is that the Complexity-variability of ASD and ADHD subjects, when they face Aristotle's types of syllogisms, is higher than that of the control subjects. An explanation is suggested as described in the text. Also, in the case of invalid type of Aristotelian syllogisms, the linguistic and visuo-spatial systems are both engaged ONLY in the temporal and occipital regions of the brain, respectively, of ADHD subjects. In the case of valid type, both above systems are engaged in the temporal and occipital regions of the brain, respectively, of both ASD and ADHD subjects, while in the control subjects only the visuo-spatial type is engaged (Goel et al., 2000; Knauff, 2007). CONCLUSION: Based on the results of the analysis described in this work, the differences in the EEG complexity between the three groups of participants lead to the conclusion that cortical information processing is changed in ASD and ADHD adults, therefore their level of cortical activation may be insufficient to meet the peculiar cognitive demand of Aristotle's reasoning. SIGNIFICANCE: The present paper suggest that MSE, is a powerful and efficient nonlinear measure in detecting neural dysfunctions in adults with ASD and ADHD characteristics, when they are called on to perform in a very demanding as well as innovative set of cognitive tasks, that can be considered as a new diagnostic 'benchmark' in helping detecting more effectively such type of disorders. A linear measure alone, as the typical PSD, is not capable in making such a distinction. The work contributes in shedding light on the neural mechanisms of syllogism/reasoning of Aristotelian type, as well as toward understanding how humans reason logically and why 'pathological' subjects deviate from the norms of formal logic.

Trait-Based Dimensions Discriminating Adults with Attention Deficit Hyperactivity Disorder (ADHD), Autism Spectrum Disorder (ASD) and, Co-occurring ADHD/ASD.

This study assessed the co-occurrence of attention deficit hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) in newly diagnosed adults of normal intelligence and the contribution of trait-based dimensions deriving from the Barkley Adult ADHD Rating Scale-IV (BAARS-IV), the Autism-Spectrum Quotient (AQ), and the Empathy Quotient (EQ) to the differentiation of patients with ADHD, ASD, and ADHD/ASD. A total of 16.1% of patients with ADHD received a co-occurring ASD diagnosis, while 33.3% of patients with ASD received an ADHD diagnosis. Subjects with ADHD or ADHD/ASD had higher scores in all ADHD traits compared to ASD subjects. Compared to the ADHD group, the ASD group had AQ scores that were significantly greater, except for attention to detail. ADHD/ASD co-occurrence significantly increased the score of attention to detail. The total EQ score was greater in the ADHD group. In the stepwise logistic regression analyses, past hyperactivity, current inattention and impulsivity, attention switching, communication, imagination, and total EQ score discriminated ADHD patients from ASD patients. Attention to detail, imagination, and total EQ score discriminated ADHD cases from ADHD/ASD cases, while past hyperactivity and current impulsivity discriminated ASD subjects from ADHD/ASD subjects. Our findings highlight the importance of particular trait-based dimensions when discriminating adults with ADHD, ASD, and co-occurring ADHD/ASD.

Lifetime co-occurring psychiatric disorders in newly diagnosed adults with attention deficit hyperactivity disorder (ADHD) or/and autism spectrum disorder (ASD).

BACKGROUND: Co-occurring psychiatric disorders in adults with Attention Deficit Hyperactivity Disorder (ADHD) and/or Autism Spectrum Disorder (ASD) contribute to the burden of the healthcare and possibly to the delay of diagnosis. Aim of the study was to clinically assess the prevalence and compare lifetime co-occurring psychopathology in a sample of newly diagnosed ADHD and/or ASD adults and discuss the diagnostic challenges they pose. METHODS: The lifetime prevalence rates of ten of the most frequently co-occurring psychiatric diagnoses was registered in 336 adults of normal intelligence who underwent a thorough clinical evaluation for the diagnosis of ADHD and/or ASD for the first time in their lives. Four study groups were formed: the ADHD (n = 151), the ASD (n = 58), the ADHD+ASD (n = 28) and the nonADHD/nonASD (NN) (n = 88) group. RESULTS: At least one co-occurring psychopathology was found in 72.8% of the ADHD group, in 50% of the ASD group, in 72.4% of the ADHD+ASD group and in 76.1% of the NN group (p = 0.004). In all groups the most frequent psychiatric disorder was depressive disorder. The only significant difference regarding the patterns of psychiatric co-occurrence between the ADHD and the nonADHD groups (ASD and NN groups) was found for SUD (p = 0.001). Also, the proportion of subjects with Bipolar Disorder was significantly greater in the NN group as compared to those with ASD (p = 0.025). CONCLUSIONS: Our results support the high prevalence of co-occurring psychiatric disorders in adults with ADHD and/or ASD with the ASD group presenting the lowest rate. The most marked difference between the ADHD and the nonADHD groups was found for SUD. Moreover, our findings highlight the need for a thorough clinical assessment of all referred patients both in the presence and absence of ADHD and/or ASD.