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Background: In Germany, an estimated number of 70,000 people diagnosed with long COVID or post-COVID syndrome (PCS) had received inpatient medical rehabilitation by the end of 2022. Due to the heterogeneity of the clinical picture, the variability of interventions and inconsistent endpoints, previous studies on the effectiveness of rehabilitation are of limited value. It therefore remains unclear whether and to what extent rehabilitation measures established for, e.g., pulmonary, cardiovascular, or neurological diseases are suitable for patients with PCS., Objectives: To identify the experiences and perspectives of those affected by PCS, in relation to inpatient rehabilitation and to describe patients' values and wishes with respect to evidence-based medicine., Methods: In January/February 2023, the German initiative "Long COVID Deutschland" conducted a retrospective online survey (39 closed items, two open answer fields) among adult PCS sufferers on their experiences with inpatient rehabilitation. Recruitment was carried out via social media and websites of patient initiatives. The open answers were analyzed using a structuring and summarizing qualitative content analysis according to Mayring, supplemented by descriptive representations of the distribution of standardized information., Results: Of 1,191 participants in the survey, 733 used open response formats to additionally explain their experiences and the effects of individual measures on their general condition. 366 (50%) reported that their state of health deteriorated, mainly because of strength or endurance training and too extensive treatment plans. The presence of a post-exertional malaise (PEM) or its insufficient consideration during rehabilitation was described as the main barrier. Recognition and acceptance of individual performance limits, flexible and coordinated individual treatment plans tailored to the patient's limitations, and support in coping with the disease were described as supportive factors. From the participants' perspective, learning strategies to avoid deterioration in their state of health due to overexertion, the so-called pacing, should be the core treatment goal for patients affected by PEM., Discussion: The results are not statistically representative but ensure systematic insights into the subjective perspectives of those affected, the consideration of which represents one of the three principles of evidence-based medicine. The results show that for PCS patients with PEM, even minimum requirements for rehabilitation measures can lead to overexertion and aggravation., Conclusions: Common subject-specific rehabilitation concepts appear to be only partially suitable for dealing with the symptoms and the heterogeneity of the disease. Aims and interventions should be individually adapted, and the focus should be on pacing, disease coping and management. A reliable test for PEM and rehabilitation ability before the start of rehabilitation is needed to ensure safety for those affected. To adequately classify studies on the effectiveness of rehabilitation, risks and side effects should be disclosed., (Copyright © 2024. Published by Elsevier GmbH.)

Several regions of the brain are involved in smooth-pursuit eye movement (SPEM) control, including the cortical areas MST (medial superior temporal) and FEF (frontal eye field). It has been shown that the eye-movement responses to a brief perturbation of the visual target during ongoing pursuit increases with higher pursuit velocities. To further investigate the underlying neuronal mechanism of this nonlinear dynamic gain control and the contributions of different cortical areas to it, we recorded from MSTd (dorsal division of the MST area) neurons in behaving monkeys (Macaca mulatta) during step-ramp SPEM (5-20 degrees /s) with and without superimposed target perturbation (one cycle, 5 Hz, +/-10 degrees /s). Smooth-pursuit-related MSTd neurons started to increase their activity on average 127 ms after eye-movement onset. Target perturbation consistently led to larger eye-movement responses and decreasing latencies with increasing ramp velocities, as predicted by dynamic gain control. For 36% of the smooth-pursuit-related MSTd neurons the eye-movement perturbation was accompanied by detectable changes in neuronal activity with a latency of 102 ms, with respect to the eye-movement response. The remaining smooth-pursuit-related MSTd neurons (64%) did not reflect the eye-movement perturbation. For the large majority of cases this finding could be predicted by the dynamic properties of the step-ramp responses. Almost all these MSTd neurons had large visual receptive fields responding to motion in preferred directions opposite to the optimal SPEM stimulus. Based on these findings it is unlikely that MSTd plays a major role for dynamic gain control and initiation of the perturbation response. However, neurons in MSTd could still participate in SPEM maintenance. Due to their visual field properties they could also play a role in other functions such as self-motion perception.

Smooth pursuit eye movements are used to continuously track slowly moving visual objects. A peculiar property of the smooth pursuit system is the nonlinear increase in sensitivity to changes in target motion with increasing pursuit velocities. We investigated the role of the frontal eye fields (FEFs) in this dynamic gain control mechanism by application of transcranial magnetic stimulation. Subjects were required to pursue a slowly moving visual target whose motion consisted of 2 components: a constant velocity component at 4 different velocities (0, 8, 16, and 24 deg/s) and a superimposed high-frequency sinusoidal oscillation (4 Hz, +/-8 deg/s). Magnetic stimulation of the FEFs reduced not only the overall gain of the system, but also the efficacy of the dynamic gain control. We thus provide the first direct evidence that the FEF population is significantly involved in the nonlinear computation necessary for continuously adjusting the feedforward gain of the pursuit system. We discuss this with relation to current models of smooth pursuit.

The smooth pursuit eye movement (SPEM) system is much more sensitive to target motion perturbations during pursuit than during fixation. This sensitivity is commonly attributed to a dynamic gain control mechanism. Neither the neural substrate nor the functional architecture for this gain control has been fully revealed. There are at least two cortical areas that crucially contribute to smooth pursuit and are therefore eligible sites for dynamic gain control: the medial superior temporal area (MST) and the pursuit area of the frontal eye fields (FEFs), which both project to brain stem premotor structures via parallel pathways. The aim of this study was to develop a model of smooth pursuit based on behavioral, anatomical, and neurophysiological results to account for nonlinear dynamic gain control. Using a behavioral paradigm in humans consisting of a sinusoidal oscillation (4 Hz, +/-8 degrees/s) superimposed on a constant velocity target motion (0-24 degrees/s), we were able to identify relevant gain control parameters in the model. A salient feature of our model is the emergence of two parallel pathways from higher visual cortical to lower motor areas in the brain stem that correspond to the MST and FEF pathways. Detailed analysis of the model revealed that one pathway mainly carries eye velocity related signals, whereas the other is associated mostly with eye acceleration. From comparison with known neurophysiological results we conclude that the dynamic gain control can be attributed to the FEF pathway, whereas the MST pathway serves as the basic circuit for maintaining an ongoing SPEM.

Two cortical areas that crucially contribute to the generation and maintenance of smooth pursuit eye movements (SPEM) are the medial superior temporal area (MST) and the pursuit area of the frontal eye fields (FEF). They both project to the brainstem premotor structures via different parallel pathways. A special property of the pursuit system is the increased sensitivity to retinal image motion for increasing pursuit velocities (dynamic gain control), which might be attributed to the FEF. On the other hand, MST is regarded as the main site for estimating the target velocity in space and therefore for maintaining an ongoing SPEM. However, neural activities in these areas during visually driven SPEM have not been fully understood. We present a simple model of smooth pursuit gain control that comprises population activities, as well as single unit sensitivities with respect to eye and retinal image motion in MST and FEF. We show that the nonlinear computation necessary for dynamic gain control may be accomplished by units that exhibit a curvilinear sensitivity to retinal image motion and eye velocity.

Linear operations can only partially exploit the statistical redundancies of natural scenes, and nonlinear operations are ubiquitous in visual cortex. However, neither the detailed function of the nonlinearities nor the higher-order image statistics are yet fully understood. We suggest that these complicated issues can not be tackled by one single approach, but require a range of methods, and the understanding of the crosslinks between the results. We consider three basic approaches: (i) State space descriptions can theoretically provide complete information about statistical properties and nonlinear operations, but their practical usage is confined to very low-dimensional settings. We discuss the use of representation-related state-space coordinates (multivariate wavelet statistics) and of basic nonlinear coordinate transformations of the state space (e.g., a polar transform). (ii) Indirect methods, like unsupervised learning in multi-layer networks, provide complete optimization results, but no direct information on the statistical properties, and no simple model structures. (iii) Approximation by lower-order terms of power-series expansions is a classical strategy that has not yet received broad attention. On the statistical side, this approximation amounts to cumulant functions and higher-order spectra (polyspectra), on the processing side to Volterra Wiener systems. In this context we suggest that an important concept for the understanding of natural scene statistics, of nonlinear neurons, and of biological pattern recognition can be found in AND-like combinations of frequency components. We investigate how the different approaches can be related to each other, how they can contribute to the understanding of cortical nonlinearities such as complex cells, cortical gain control, end-stopping and other extraclassical receptive field properties, and how we can obtain a nonlinear perspective on overcomplete representations and invariant coding in visual cortex.