Estimation of prevalence and treatment needs of mental disorders. The problem of diagnostic thresholds

Uncertainties in the context of threshold-based diagnostics represent a theoretically unsolved methodological problem that may require multidimensional solutions. Pragmatically, current research focuses on establishing reliable and valid operationalized criteria within the framework of diagnostic systems, such as the International Classification of Diseases (ICD-10) and the Diagnostic and Statistical Manual of Mental Disorders (DSM). By means of model calculations based on epidemiological data we show how exemplified changes in the disorder spectrum and diagnostic criteria influence case numbers. Furthermore, we investigate how threshold-based constructs, such as DSM-IV diagnoses, relate to the general criteria of illness and sickness. Variations in the disorder spectrum and thresholds lead to slight to moderate changes in case numbers. Regarding distress and impairment, mental disorders are associated with significantly reduced health-related quality of life and an increased number of days out of role (due to mental and/or physical problems). With increasing distress and impairment, the percentage of mental disorders increases significantly; in the 5 % of the general population with the highest distress and impairment, the proportion is nearly 80 %. Despite fuzzy boundaries, threshold-based diagnoses (DSM-IV) represent a satisfactory and reproducible disease classification (in terms of illness and sickness) for estimation of prevalence. There is a lack of definitions and instruments to assess treatment needs. It is still debated whether diagnostic symptom criteria always represent pathological disorders (i. e. disease)

The generation of Parkinsonian tremor as revealed by directional coupling analysis

To reveal the dynamic mechanism underlying Parkinsonian resting tremor, we applied a phase dynamics modelling technique to local field potentials and accelerometer signals recorded in three Parkinsonian patients with implanted depth electrodes. We detect a bidirectional coupling between the subcortical oscillation and the tremor. The tremor $\rightarrow$ brain driving is a linear effect with a small delay corresponding to the neural transmission time. In contrast, the brain $\rightarrow$ tremor driving is a nonlinear effect with a long delay in the order of 1-2 mean tremor periods. Our results are well reproduced for an ensemble of 41 tremor epochs in three Parkinsonian patients and confirmed by surrogate data tests and model simulations. The uncovered mechanism of tremor generation suggests to specifically counteract tremor by desynchronizing the subcortical oscillatory neural activity

The causal relationship between subcortical oscillations and parkinsonian resting tremor.

To study the dynamical mechanism which generates Parkinsonian resting tremor, we apply coupling directionality analysis to local field potentials (LFP) and accelerometer signals recorded in an ensemble of 48 tremor epochs in four Parkinsonian patients with depth electrodes implanted in the ventro-intermediate nucleus of the thalamus (VIM) or the subthalmic nucleus (STN). Apart from the traditional linear Granger causality method we use two nonlinear techniques: phase dynamics modelling and nonlinear Granger causality. We detect a bidirectional coupling between the subcortical (VIM or STN) oscillation and the tremor, in the theta range (around 5 Hz) as well as broadband (>2 Hz). In particular, we show that the theta band LFP oscillations definitely play an efferent role in tremor generation, while beta band LFP oscillations might additionally contribute. The brain-->tremor driving is a complex, nonlinear mechanism, which is reliably detected with the two nonlinear techniques only. In contrast, the tremor-->brain driving is detected with any of the techniques including the linear one, though the latter is less sensitive. The phase dynamics modelling (applied to theta band oscillations) consistently reveals a long delay in the order of 1-2 mean tremor periods for the brain-->tremor driving and a small delay, compatible with the neural transmission time, for the proprioceptive feedback. Granger causality estimation (applied to broadband signals) does not provide reliable estimates of the delay times, but is even more sensitive to detect the brain-->tremor influence than the phase dynamics modelling

Tremor entrainment by patterned low-frequency stimulation

High-frequency test stimulation for tremor suppression is a standard procedure for functional target localization during deep brain stimulation. This method does not work in cases where tremor vanishes intraoperatively, for example, due to general anaesthesia or due to an insertional effect. To overcome this difficulty, we developed a stimulation technique that effectively evokes tremor in a well-defined and quantifiable manner. For this, we used patterned low-frequency stimulation (PLFS), i.e. brief high-frequency pulse trains administered at pulse rates similar to neurons' preferred burst frequency. Unlike periodic single-pulse stimulation, PLFS enables one to convey effective and considerably greater integral charge densities without violation of safety requirements. In a computational investigation of an oscillatory neuronal network temporarily rendered inactive, we found that PLFS evokes synchronized activity, phase locked to the stimulus. While a stronger increase in the amount of synchrony in the neuronal population requires higher stimulus intensities, the portion of synchronously active neurons nevertheless becomes strongly phase locked to PLFS already at weak stimulus intensities. The phase entrainment effect of PLFS turned out to be robust against variations in the stimulation frequency, whereas enhancement of synchrony required precisely tuned stimulation frequencies. We applied PLFS to a patient with spinocerebellar ataxia type 2 (SCA2) with pronounced tremor that disappeared intraoperatively under general anaesthesia. In accordance with our computational results, PLFS evoked tremor, phase locked to the stimulus. In particular, weak PLFS caused low-amplitude, but strongly phase-locked tremor. PLFS test stimulations provided the only functional information about target localization. Optimal target point selection was confirmed by excellent post-operative tremor suppression

Subthalamic-thalamic DBS in a case with spinocerebellar ataxia type 2 and severe tremor - A unusual clinical benefit

This is a single case report of a patient with spinocerebellar ataxia type 2 (SCA2) and severe tremor. Whereas disease progression with prevailing ataxia and dysmetria was slow over the first symptomatic 6 years, 6 months prior to operation were characterized by the development of a severe, debilitating postural tremor rendering the patient unable to independently sit, stand, speak, or swallow. Deep brain stimulation (DBS) at a subthalamic-thalamic electrode position almost completely arrested her tremor. The patient regained the functional state prior to her rapid disease progression allowing a restricted range of daily activities. Her condition has remained approximately stable over the two postoperative years to date. In addition to the efficacy of DBS on cerebellar tremor, the results illustrate a remarkable improvement of the patient's general condition and independence

Pattern reversal visual evoked responses of V1/V2 and V5/MT as revealed by MEG combined with probabilistic cytoarchitectonic maps

Pattern reversal stimulation provides an established tool for assessing the integrity of the visual pathway and for studying early visual processing. Numerous magnetoencephalographic (MEG) and electroencephalographic (EEG) studies have revealed a three-phasic waveform of the averaged pattern reversal visual evoked potential/magnetic field, with components N75(m), P100(m), and N145(m). However, the anatomical assignment of these components to distinct cortical generators is still a matter of debate, which has inter alia connected with considerable interindividual variations of the human striate and extrastriate cortex. The anatomical variability can be compensated for by means of probabilistic cytoarchitectonic maps, which are three-dimensional maps obtained by an observer-independent statistical mapping in a sample of ten postmortem brains. Transformed onto a subject's brain under consideration, these maps provide the probability with which a given voxel of the subject's brain belongs to a particular cytoarchitectonic area. We optimize the spatial selectivity of the probability maps for V1 and V2 with a probability threshold which optimizes the self- vs. cross-overlap in the population of postmortem brains used for deriving the probabilistic cytoarchitectonic maps. For the first time, we use probabilistic cytoarchitectonic maps of visual cortical areas in order to anatomically identify active cortical generators underlying pattern reversal visual evoked magnetic fields as revealed by MEG. The generators are determined with magnetic field tomography (MFT), which reconstructs the current source density in each voxel. In all seven subjects, our approach reveals generators in V1/V2 (with a greater overlap with V1) and in V5 unilaterally (right V5 in three subjects, left V5 in four subjects) and consistent time courses of their stimulus-locked activations, with three peak activations in V1/V2 (contributing to C1m/N75m, P100m, and N145m) and two peak activations in V5 (contributing to P100m and N145m). The reverberating V1/V2 and V5 activations demonstrate the effect of recurrent activation mechanisms including V1 and extrastriate areas and/or corticofugal feedback loops. Our results demonstrate that the combined investigation of MEG signals with MFT and probabilistic cytoarchitectonic maps significantly improves the anatomical identification of active brain areas