The early identification of individuals with radiologically isolated syndrome (RIS) who are at an elevated risk of progressing to multiple sclerosis (MS) is essential for making informed treatment decisions. This study aimed to evaluate the predictive potential of multifocal Visual Evoked Potentials (mfVEP) measures in individuals with RIS with respect to their conversion to MS. A prospective observational cohort study was conducted, involving 21 individuals with RIS recruited from a MS center. Baseline assessments, including mfVEP, magnetic resonance imaging (MRI), and clinical examinations, were performed, and participants were longitudinally followed for up to 24 months. The primary outcome measures were the conversion to MS. Over a clinical follow-up period of 24 months, five individuals (5/21) with RIS progressed to MS. MfVEP amplitude responses (interocular and monocular probability analysis) demonstrated abnormal cluster visual field defects in 47.6% of RIS eyes at baseline, whereas multifocal VEP latency analysis showed significant delays in 38.4%. A reduction in interocular amplitude [OR = 0.036, (95% CI 0.003-0.503); P = 0.014], monocular amplitude [OR = 0.083, (95% CI 0.007-0.982); P = 0.048], and a prolonged interocular latency [OR = 0.095, (95% CI 0.009-0.972); P = 0.047] were associated with a higher relative risk of clinical conversion at the 2-year follow-up. Multifocal VEP may serve as a novel and independent risk factor for predicting the conversion to MS in individuals with Radiologically Isolated Syndrome.

OBJECTIVE: Recovery of vision after acute optic neuritis (AON) is critical to improving the quality of life of people with demyelinating diseases. The objective of the study was to prospectively assess the changes in visual acuity, retinal layer thickness, and cortical visual network in patients with AON to identify the predictors of permanent visual disability.
METHODS: We studied a prospective cohort of 88 consecutive patients with AON with 6-month follow-up using high and low-contrast (2.5%) visual acuity, color vision, retinal thickness from optical coherence tomography, latencies and amplitudes of multifocal visual evoked potentials, mean deviation of visual fields, and diffusion-based structural (n = 53) and functional (n = 19) brain MRI to analyze the cortical visual network. The primary outcome was 2.5% low-contrast vision, and data were analyzed with mixed-effects and multivariate regression models.
RESULTS: We found that after 6 months, low-contrast vision and quality of vision remained moderately impaired. The thickness of the ganglion cell layer at baseline was a predictor of low-contrast vision 6 months later (ß = 0.49 [CI 0.11-0.88], p = 0.012). The structural cortical visual network at baseline predicted low-contrast vision, the best predictors being the betweenness of the right parahippocampal cortex (ß = -036 [CI -0.66 to 0.06], p = 0.021), the node strength of the right V3 (ß = 1.72 [CI 0.29-3.15], p = 0.02), and the clustering coefficient of the left intraparietal sulcus (ß = 57.8 [CI 12.3-103.4], p = 0.015). The functional cortical visual network at baseline also predicted low-contrast vision, the best predictors being the betweenness of the left ventral occipital cortex (ß = 8.6 [CI: 4.03-13.3], p = 0.009), the node strength of the right intraparietal sulcus (ß = -2.79 [CI: -5.1-0.4], p = 0.03), and the clustering coefficient of the left superior parietal lobule (ß = 501.5 [CI 50.8-952.2], p = 0.03).
CONCLUSIONS: The assessment of the visual pathway at baseline predicts permanent vision disability after AON, indicating that damage is produced early after disease onset and that it can be used for defining vision impairment and guiding therapy.

The mammalian retina is considered an autonomous circuit, yet work dating back to Ramon y Cajal indicates that it receives inputs from the brain. How such inputs affect retinal processing has remained unknown. We confirmed brain-to-retina projections of histaminergic neurons from the mouse hypothalamus. Histamine application ex vivo altered the activity of various retinal ganglion cells (RGCs), including direction-selective RGCs that gained responses to high motion velocities. These results were reproduced in vivo with optic tract recordings where histaminergic retinopetal axons were activated chemogenetically. Such changes could improve vision of fast-moving objects (e.g., while running), which fits with the known increased activity of histaminergic neurons during arousal. An antihistamine drug reduced optomotor responses to high-speed moving stimuli in freely moving mice. In humans, the same antihistamine nonuniformly modulated visual sensitivity across the visual field, indicating an evolutionary conserved function of the histaminergic system. Our findings expose a previously unappreciated role for brain-to-retina projections in modulating retinal function.

Protocadherin 19 (Pcdh19) is a homophilic cell adhesion molecule and is involved in a variety of neuronal functions. Here, we tested whether Pcdh19 has a regulatory role in axon guidance using the developing Xenopus retinotectal system. We performed targeted microinjections of a translation blocking antisense morpholino oligonucleotide to knock down the expression of Pcdh19 selectively in the central nervous system. Knocking down Pcdh19 expression resulted in navigational errors of retinal ganglion cell (RGC) axons specifically at the optic chiasm. Instead of projecting to the contralateral optic tectum, RGC axons in the Pcdh19-depleted embryo misprojected ipsilaterally. Although incorrectly delivered into the ipsilateral brain hemisphere, these axons correctly reached the optic tectum. These data suggest that Pcdh19 has a critical role in preventing mixing of RGC axons originating from the opposite eyes at the optic chiasm, highlighting the importance of cell adhesion in bundling of RGC axons.

A core challenge for the brain is to process information across various timescales. This could be achieved by a hierarchical organization of temporal processing through intrinsic mechanisms (e.g., recurrent coupling or adaptation), but recent evidence from spike recordings of the rodent visual system seems to conflict with this hypothesis. Here, we used an optimized information-theoretic and classical autocorrelation analysis to show that information- and correlation timescales of spiking activity increase along the anatomical hierarchy of the mouse visual system under visual stimulation, while information-theoretic predictability decreases. Moreover, intrinsic timescales for spontaneous activity displayed a similar hierarchy, whereas the hierarchy of predictability was stimulus-dependent. We could reproduce these observations in a basic recurrent network model with correlated sensory input. Our findings suggest that the rodent visual system employs intrinsic mechanisms to achieve longer integration for higher cortical areas, while simultaneously reducing predictability for an efficient neural code.

The occipital place area (OPA) is a scene-selective region on the lateral surface of human occipitotemporal cortex that spatially overlaps multiple visual field maps, as well as portions of cortex that are not currently defined as retinotopic. Here we combined population receptive field modeling and responses to scenes in a representational similarity analysis (RSA) framework to test the prediction that the OPA\'s visual field map divisions contribute uniquely to the overall pattern of scene selectivity within the OPA. Consistent with this prediction, the patterns of response to a set of complex scenes were heterogeneous between maps. To explain this heterogeneity, we tested the explanatory power of seven candidate models using RSA. These models spanned different scene dimensions (Content, Expanse, Distance), low- and high-level visual features, and navigational affordances. None of the tested models could account for the variation in scene response observed between the OPA\'s visual field maps. However, the heterogeneity in scene response was correlated with the differences in retinotopic profiles across maps. These data highlight the need to carefully examine the relationship between regions defined as category-selective and the underlying retinotopy, and they suggest that, in the case of the OPA, it may not be appropriate to conceptualize it as a single scene-selective region.

Retinal ganglion cell (RGC) axons provide direct input into several brain regions, including the dorsal lateral geniculate nucleus (dLGN), which is important for image-forming vision, and the ventrolateral geniculate nucleus (vLGN), which is associated with nonimage-forming vision. Through both activity- and morphogen-dependent mechanisms, retinal inputs play important roles in the development of dLGN, including the refinement of retinal projections, morphological development of thalamocortical relay cells (TRCs), timing of corticogeniculate innervation, and recruitment and distribution of inhibitory interneurons. In contrast, little is known about the role of retinal inputs in the development of vLGN. Grossly, vLGN is divided into two domains, the retinorecipient external vLGN (vLGNe) and nonretinorecipient internal vLGN (vLGNi). Studies previously found that vLGNe consists of transcriptionally distinct GABAergic subtypes distributed into at least four adjacent laminae. At present, it remains unclear whether retinal inputs influence the development of these cell-type-specific neuronal laminae in vLGNe. Here, we elucidated the developmental timeline for these laminae in the mouse vLGNe, and results indicate that these laminae are specified at or before birth. We observed that mutant mice without retinal inputs have a normal laminar distribution of GABAergic cells at birth; however, after the first week of postnatal development, these mutants exhibited a dramatic disruption in the laminar organization of inhibitory neurons and clear boundaries between vLGNe and vLGNi. Overall, our results show that while the formation of cell-type-specific layers in mouse vLGNe does not depend on RGC inputs, retinal signals are critical for their maintenance.

Understanding the computational mechanisms that underlie the encoding and decoding of environmental stimuli is a crucial investigation in neuroscience. Central to this pursuit is the exploration of how the brain represents visual information across its hierarchical architecture. A prominent challenge resides in discerning the neural underpinnings of the processing of dynamic natural visual scenes. Although considerable research efforts have been made to characterize individual components of the visual pathway, a systematic understanding of the distinctive neural coding associated with visual stimuli, as they traverse this hierarchical landscape, remains elusive. In this study, we leverage the comprehensive Allen Visual Coding-Neuropixels dataset and utilize the capabilities of deep learning neural network models to study neural coding in response to dynamic natural visual scenes across an expansive array of brain regions. Our study reveals that our decoding model adeptly deciphers visual scenes from neural spiking patterns exhibited within each distinct brain area. A compelling observation arises from the comparative analysis of decoding performances, which manifests as a notable encoding proficiency within the visual cortex and subcortical nuclei, in contrast to a relatively reduced encoding activity within hippocampal neurons. Strikingly, our results unveil a robust correlation between our decoding metrics and well-established anatomical and functional hierarchy indexes. These findings corroborate existing knowledge in visual coding related to artificial visual stimuli and illuminate the functional role of these deeper brain regions using dynamic stimuli. Consequently, our results suggest a novel perspective on the utility of decoding neural network models as a metric for quantifying the encoding quality of dynamic natural visual scenes represented by neural responses, thereby advancing our comprehension of visual coding within the complex hierarchy of the brain.

White matter (WM) functional activity has been reliably detected through functional magnetic resonance imaging (fMRI). Previous studies have primarily examined WM bundles as unified entities, thereby obscuring the functional heterogeneity inherent within these bundles. Here, for the first time, we investigate the function of sub-bundles of a prototypical visual WM tract-the optic radiation (OR). We use the 7T retinotopy dataset from the Human Connectome Project (HCP) to reconstruct OR and further subdivide the OR into sub-bundles based on the fiber\'s termination in the primary visual cortex (V1). The population receptive field (pRF) model is then applied to evaluate the retinotopic properties of these sub-bundles, and the consistency of the pRF properties of sub-bundles with those of V1 subfields is evaluated. Furthermore, we utilize the HCP working memory dataset to evaluate the activations of the foveal and peripheral OR sub-bundles, along with LGN and V1 subfields, during 0-back and 2-back tasks. We then evaluate differences in 2bk-0bk contrast between foveal and peripheral sub-bundles (or subfields), and further examine potential relationships between 2bk-0bk contrast and 2-back task d-prime. The results show that the pRF properties of OR sub-bundles exhibit standard retinotopic properties and are typically similar to the properties of V1 subfields. Notably, activations during the 2-back task consistently surpass those under the 0-back task across foveal and peripheral OR sub-bundles, as well as LGN and V1 subfields. The foveal V1 displays significantly higher 2bk-0bk contrast than peripheral V1. The 2-back task d-prime shows strong correlations with 2bk-0bk contrast for foveal and peripheral OR fibers. These findings demonstrate that the blood oxygen level-dependent (BOLD) signals of OR sub-bundles encode high-fidelity visual information, underscoring the feasibility of assessing WM functional activity at the sub-bundle level. Additionally, the study highlights the role of OR in the top-down processes of visual working memory beyond the bottom-up processes for visual information transmission. Conclusively, this study innovatively proposes a novel paradigm for analyzing WM fiber tracts at the individual sub-bundle level and expands understanding of OR function.

UNASSIGNED: To investigate the potential causal association between COVID-19 exposure and optic nerve and visual pathway disorders through a two-sample bidirectional Mendelian randomization (MR) analysis, and to provide empirical support for the lung-brain axis.
UNASSIGNED: This MR analysis utilized publicly accessible summary-level data from genome-wide association studies on COVID-19 (n=158,783) and optic nerve and visual pathway diseases (n=412,181), primarily involving individuals of European descent. The random-effect inverse-variance weighted estimation was applied as the main analytical approach, complemented by MR-Egger, weighted median, and weighted mode methods. The heterogeneity and pleiotropy of the instrumental variables were assessed using Cochran\'s Q test, leave-one-out sensitivity analysis, MR-Egger intercept test, MR-PRESSO, and funnel plot evaluations.
UNASSIGNED: In the forward analysis, the inverse-variance weighted method identified a significant causal effect of COVID-19 on optic nerve and visual pathway disorders (odds ratio = 1.697, 95% confidence interval: 1.086-2.652, p = 0.020). Directionally consistent results were also observed with MR-Egger regression, weighted median, and weighted mode approaches. Conversely, the reverse analysis revealed no causal effects of optic nerve and visual pathway disorders on COVID-19 susceptibility.
UNASSIGNED: Our findings suggest that COVID-19 exposure may increase the risk of developing optic nerve and visual pathway disorders, supporting the lung-brain axis hypothesis. These results underscore the importance of vigilant monitoring of the visual system in patients recovering from COVID-19 and suggest potential avenues for future therapeutic strategies.