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ObjectiveAquaporin-4-antibody-seropositive (AQP4-IgG+) Neuromyelitis Optica Spectrum Disorder (NMOSD) and Myelin Oligodendrocyte Glycoprotein Antibody-Associated Disorder (MOGAD) are relapsing neuroinflammatory diseases, frequently leading to chronic pain. In both diseases, the spinal cord (SC) is often affected by myelitis attacks. We hypothesized that regional SC volumes differ between AQP4-IgG + NMOSD and MOGAD and that pain intensity is associated with lower SC volumes. To evaluate changes in the SC white matter (WM), gray matter (GM), and pain intensity in patients with recent relapses (myelitis or optic neuritis), we further profiled phenotypes in a case series with longitudinal imaging and clinical data.MethodsCross-sectional data from 36 participants were analyzed in this retrospective study, including 20 AQP4-IgG + NMOSD and 16 MOGAD patients. Pain assessment was performed in all patients by the Brief Pain Inventory and painDETECT questionnaires. Segmentation of SC WM, GM, cervical cord volumes (combined volume of WM + GM) was performed at the C2/C3 cervical level. WM% and GM% were calculated using the cervical cord volume as a whole per patient. The presence of pain, pain severity, and clinical disability was evaluated and tested for associations with SC segmentations. Additionally, longitudinal data were deeply profiled in a case series of four patients with attacks between two MRI visits within one year.ResultsIn AQP4-IgG + NMOSD, cervical cord volume was associated with mean pain severity within 24 h (β = −0.62, p = 0.009) and with daily life pain interference (β = −0.56, p = 0.010). Cross-sectional analysis showed no statistically significant SC volume differences between AQP4-IgG + NMOSD and MOGAD. However, in AQP4-IgG + NMOSD, SC WM% tended to be lower with increasing time from the last attack (β = −0.41, p = 0.096). This tendency was not observed in MOGAD. Our case series including two AQP4-IgG + NMOSD patients revealed SC GM% increased by roughly 2% with either a myelitis or optic neuritis attack between visits. Meanwhile, GM% decreased by 1–2% in two MOGAD patients with a myelitis attack between MRI visits.ConclusionIn AQP4-IgG + NMOSD, lower cervical cord volume was associated with increased pain. Furthermore, cord GM changes were detected between MRI visits in patients with disease-related attacks in both groups. Regional SC MRI measures are pertinent for monitoring disease-related cord pathology in AQP4-IgG + NMOSD and MOGAD.

Neural system identification aims at learning the response function of neurons to arbitrary stimuli using experimentally recorded data, but typically does not leverage normative principles such as efficient coding of natural environments. Visual systems, however, have evolved to efficiently process input from the natural environment. Here, we present a normative network regularization for system identification models by incorporating, as a regularizer, the efficient coding hypothesis, which states that neural response properties of sensory representations are strongly shaped by the need to preserve most of the stimulus information with limited resources. Using this approach, we explored if a system identification model can be improved by sharing its convolutional filters with those of an autoencoder which aims to efficiently encode natural stimuli. To this end, we built a hybrid model to predict the responses of retinal neurons to noise stimuli. This approach did not only yield a higher performance than the "stand-alone" system identification model, it also produced more biologically plausible filters, meaning that they more closely resembled neural representation in early visual systems. We found these results applied to retinal responses to different artificial stimuli and across model architectures. Moreover, our normatively regularized model performed particularly well in predicting responses of direction-of-motion sensitive retinal neurons. The benefit of natural scene statistics became marginal, however, for predicting the responses to natural movies. In summary, our results indicate that efficiently encoding environmental inputs can improve system identification models, at least for noise stimuli, and point to the benefit of probing the visual system with naturalistic stimuli.

Neurons in the dorsolateral geniculate nucleus (dLGN) of the thalamus receive a substantial proportion of modulatory inputs from corticothalamic (CT) feedback and brain stem nuclei. Hypothesizing that these modulatory influences might be differentially engaged depending on the visual stimulus and behavioral state, we performed in vivo extracellular recordings from mouse dLGN while optogenetically suppressing CT feedback and monitoring behavioral state by locomotion and pupil dilation. For naturalistic movie clips, we found CT feedback to consistently increase dLGN response gain and promote tonic firing. In contrast, for gratings, CT feedback effects on firing rates were mixed. For both stimulus types, the neural signatures of CT feedback closely resembled those of behavioral state, yet effects of behavioral state on responses to movies persisted even when CT feedback was suppressed. We conclude that CT feedback modulates visual information on its way to cortex in a stimulus-dependent manner, but largely independently of behavioral state.