Dimitri Marques Abramova, Henrique Santos Lima b, Vladimir Lazareva,Paulo Ricardo Galhanone,a and Constantino TsalliscMarch 25, 2024ABSTRACTThere are reasons to suggest that a number of mental disorders may be related to alteration in the neural complexity (NC). Thus, quantitative analysis of NC could be helpful in classifying mental conditions and clarifying our understanding about them. Here, we have worked with youths, typical and with attention-deficit/hyperactivity disorder (ADHD), whose neural complexity was assessed using q-statistics applied to the electroencephalogram (EEG). The EEG was recorded while subjects performed the visual Attention Network Test (ANT) based on the OddBall paradigm and during a shortpretask period of resting state. Time intervals of the EEG amplitudes that passed a threshold (signal regularity indicator) were collected from task and pretask signals from each subject. The data were satisfactorily fitted with a stretched q-exponential including a power-law prefactor(characterized by the exponent c), thus determining the best (c, q) for each subject, indicative of their individual complexity. We found larger values of q and c in ADHD subjects as compared with the typical subjects both at task and pretask periods, the task values for both groups being larger than at rest. The c parameter was highly specific in relation to DSM diagnosis for inattention, where well-defined clusters were observed. The parameter values were organized in four well-defined clusters in (c, q)- space. As expected, the tasks apparently induced greater complexity in neural functional states with likely greater amount of internal information processing. The results suggest that complexity is higher in ADHD subjects than in typical pairs. The distribution of values in the (c, q)-space derived from q-statistics seems to be a promising biomarker for ADHD diagnosis.
The averaged parameters c and q from samples were statistically lower for typical subjects compared to ADHD pairs (all p < 0.01, see Table 1), with very low standard deviations. Comparing conditions, only q in ADHD differed between Task and pretask (p = 0.0004, Mann-Whitney U test, see means and std. deviations, Table 1). Fig. 3 shows the space (c q), where all individual values form well-defined clusters relative to each group and condition. We observed 100 % accuracy in differentiating typical ADHD in the task condition since there was no overlapping regarding the values of (c q) from these different groups. From all distributions taken together, the global values for q and c differed from averaged ones from individual fittings.
id: f6fa866b906a512d8d79615c66403771 - page: 6
There is no monotonic correlation between c and q and DSM scores for Inattention (Fig. 4), nor for total scores (result not shown). However, well-defined clusters are observed in scatter plots for both c and q(task), which appears to roughly coincide with the DSM cutoff for inattention (i.e., six criteria satisfied). 6 A PREPRINT MARCH 25, 2024 2.1 6 2.0 8 r=0.55 1.9 10DSM-IN 2 1.8 Typical ADHD 0 2.2q(pretask) 4 Typical 1.95 1.90 2 2.20q(task) 2.15 10DSM-IN ADHD 2.00 2.05 8 4 2.10 6 0 1.85 4 1.65 0 1.80 Typical 1.95 1.90 2.00c(pretask) 6 2 1.70 8 10DSM-IN ADHD 1.75 2 Typical 6 1.75 0 4 8 2.10c(task) 2.00 1.80 2.05 1.90 1.85 ADHD 1.95 10DSM-IN q (pretask), q (task), c (pretask), and c (task) versus DSM score (top left, top right, bottom left, and Figure 4: bottom right, respec.). Notice that q (pretask) can be roughly fitted with an increasing straight line (dashed red) with r(Pearson)=0.55.
id: 26af5f7f1d938b6a411153ebf787d3f6 - page: 6
Discussion The traditional analytical-reductionist approach for studying the relationship between the human brain and mind usually comes down to correlating mental processes with the dynamics of neural networks. However, this approach cannot be considered fully adequate, since it does not take into account the complexity of the phenomena that are being compared. The science of complexity is gaining space every day for studying the cerebral basis of the mind and its disorders . The informativeness in complex systems is non-addictive and non-extensive due to the systems inviolable completeness: the whole is larger than the sum of its parts. Studying the molecular receptor or neuronal cell activity mechanisms, outside their intricate network of correlations, might not be the most appropriate way to understand brain dynamics related to mental processes.
id: 73d7845ee9b884634409e932d4ad50dd - page: 7
Here, we have shown that the q parameter, a complexity measure from NESM, seems to accurately discriminate ADHD young boys from their typical pairs. Corroborating other studies [10, 18], which used alternative procedures to infer brain complexity, here the NESM has shown that NC from EEG of ADHD subjects is higher than that of the typical 7 A PREPRINT MARCH 25, 2024
id: c4d877745b429917e55f5d87783699c1 - page: 7