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Objective: Stress, pain, injury, and psychological trauma all induce arousal-mediated changes in brain network organization. The associated, high level of arousal may disrupt motor-sensory processing and result in aberrant patterns of motor function, including functional neurological symptoms. We used the auditory oddball paradigm to assess cortical arousal in children and adolescents with functional neurological symptom disorder. Method: Electroencephalogram (EEG) data was collected in fifty-seven children and adolescents (41 girls; 16 boys, aged 8.5–18 years) with acute functional neurological symptoms and age- sex- matched controls during a conventional auditory oddball task. The high-resolution fragmentary decomposition technique was used to analyse the amplitude of event-related potentials (ERPs) to target tones at midline sites (Fz, Cz, and Pz). Results: Compared to age- and sex-matched controls, and across all three midline sites, children and adolescents with functional neurological symptoms showed increased amplitude of all ERP components (P50, N100, P200, N200, and P300) (t-value range 2.28–8.20; p value-range 0.023 to

Probabilistic formalism of quantum mechanics is used to quantitatively link the global scale mass potential with the underlying electrical activity of excitable cells. Previous approaches implemented methods of classical physics to reconstruct the mass potential in terms of explicit physical models of participating cells and the volume conductor. However, the multiplicity of cellular processes with extremely intricate mixtures of deterministic and random factors prevents the creation of consistent biophysical parameter sets. To avoid the uncertainty inherent in physical attributes of cell ensembles, we undertake here a radical departure from deterministic equations of classical physics, instead applying the probabilistic reasoning of quantum mechanics. Crucial steps include: (1) the relocation of the elementary bioelectric sources from a cellular to a molecular level; (2) the creation of microscale particle models in terms of a non-homogenous birth-and-death process. To link the microscale processes with macroscale potentials, time-frequency analysis was applied for estimation of the empirical characteristic functions for component waveforms of electroencephalogram (EEG), eye-blink electromyogram (EMG), and electrocardiogram (ECG). We describe universal models for the amplitude spectra and phase functions of functional components of mass potentials. The corresponding time domain relationships disclose the dynamics of mass potential components as limit distribution functions produced by specific microscale transients. The probabilistic laws governing the microscale machinery, founded on an empirical basis, are presented. Computer simulations of particle populations with time dependent transition probabilities reveal that hidden deterministic chaos underlies development of the components of mass potentials. We label this kind of behaviour "transient deterministic chaos".