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.

Short association fibres (SAF) are the most abundant fibre pathways in the human white matter. Until recently, SAF could not be mapped comprehensively in vivo because diffusion weighted magnetic resonance imaging with sufficiently high spatial resolution needed to map these thin and short pathways was not possible. Recent developments in acquisition hardware and sequences allowed us to create a dedicated in vivo method for mapping the SAF based on sub-millimetre spatial resolution diffusion weighted tractography, which we validated in the human primary (V1) and secondary (V2) visual cortex against the expected SAF retinotopic order. Here, we extended our original study to assess the feasibility of the method to map SAF in higher cortical areas by including SAF up to V3. Our results reproduced the expected retinotopic order of SAF in the V2-V3 and V1-V3 stream, demonstrating greater robustness to the shorter V1-V2 and V2-V3 than the longer V1-V3 connections. The demonstrated ability of the method to map higher-order SAF connectivity patterns in vivo is an important step towards its application across the brain.

UNASSIGNED: A retinal mosaic, the spatial organization of a population of homotypic neurons, is thought to sample a specific visual feature into the feedforward visual pathway. The purpose of this study was to propose a universal modeling approach for precisely generating retinal mosaics and overcoming the limitations of previous models, especially in modeling abnormal mosaic patterns under disease conditions.
UNASSIGNED: Here, we developed the optimization-based pairwise interaction point process (O-PIPP). It incorporates optimization techniques into previous simulation approaches, enabling directional control of the simulation process according to the user-designed optimization target. For the convenience of the community, we implemented the O-PIPP approach into a Python package and a website application.
UNASSIGNED: We showed that the O-PIPP can generate more precise neural spatial patterns of healthy and diseased mosaics compared to previous phenomenological approaches. Notably, through modeling the retinal neural circuitry with O-PIPP-simulated retinitis pigmentosa cone mosaics, we elucidated how the cone mosaic rearrangement impacted the information processing of ganglion cells.
UNASSIGNED: The O-PIPP provides a precise and universal tool to simulate realistic mosaics, which could help to investigate the function of retinal mosaics in vision.

The existence of cortical columns, regarded as computational units underlying both lower and higher-order information processing, has long been associated with highly evolved brains, and previous studies suggested their absence in rodents. However, recent discoveries have unveiled the presence of ocular dominance columns (ODCs) in the primary visual cortex (V1) of Long-Evans rats. These domains exhibit continuity from layer 2 through layer 6, confirming their identity as genuine ODCs. Notably, ODCs are also observed in Brown Norway rats, a strain closely related to wild rats, suggesting the physiological relevance of ODCs in natural survival contexts, although they are lacking in albino rats. This discovery has enabled researchers to explore the development and plasticity of cortical columns using a multidisciplinary approach, leveraging studies involving hundreds of individuals-an endeavor challenging in carnivore and primate species. Notably, developmental trajectories differ depending on the aspect under examination: while the distribution of geniculo-cortical afferent terminals indicates matured ODCs even before eye-opening, consistent with prevailing theories in carnivore/primate studies, examination of cortical neuron spiking activities reveals immature ODCs until postnatal day 35, suggesting delayed maturation of functional synapses which is dependent on visual experience. This developmental gap might be recognized as \'critical period\' for ocular dominance plasticity in previous studies. In this article, I summarize cross-species differences in ODCs and geniculo-cortical network, followed by a discussion on the development, plasticity, and evolutionary significance of rat ODCs. I discuss classical and recent studies on critical period plasticity in the venue where critical period plasticity might be a component of experience-dependent development. Consequently, this series of studies prompts a paradigm shift in our understanding of species conservation of cortical columns and the nature of plasticity during the classical critical period.

The retina, an anatomical extension of the brain, forms physiological connections with the visual cortex of the brain. Although retinal structures offer a unique opportunity to assess brain disorders, their relationship to brain structure and function is not well understood. In this study, we conducted a systematic cross-organ genetic architecture analysis of eye-brain connections using retinal and brain imaging endophenotypes. We identified novel phenotypic and genetic links between retinal imaging biomarkers and brain structure and function measures from multimodal magnetic resonance imaging (MRI), with many associations involving the primary visual cortex and visual pathways. Retinal imaging biomarkers shared genetic influences with brain diseases and complex traits in 65 genomic regions, with 18 showing genetic overlap with brain MRI traits. Mendelian randomization suggests bidirectional genetic causal links between retinal structures and neurological and neuropsychiatric disorders, such as Alzheimer\'s disease. Overall, our findings reveal the genetic basis for eye-brain connections, suggesting that retinal images can help uncover genetic risk factors for brain disorders and disease-related changes in intracranial structure and function.

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Aim and objectives: Visual dysfunction in diabetes mellitus (DM) is multifactorial and can be due to vascular disease, and metabolic abnormalities that can affect the retina, optic nerve, and visual pathways. Visual evoked potential (VEP) is an electrophysiological test that can quantify the functional integrity of the visual pathways from the retina via the optic nerves, and optic tracts to the visual cortices. In this study, we aimed to investigate the visual pathway dysfunction among diabetics without retinopathy compared with healthy controls and to look for any correlation with diabetic neuropathy, duration of diabetes, or HbA1c level. Methods: The study included 75 diabetic patients and 75 age and sex-matched controls. VEPs were recorded using the pattern reversal stimulation method on the Medtronic EMG EP machine, and P100 latency and N75-P100 amplitude were recorded in both diabetic patients and healthy controls. Results: Mean P100 latency was significantly prolonged and N75-P100 amplitude significantly reduced among diabetic cases compared to healthy controls (p < 0.001). Among diabetics with peripheral neuropathy, P100 latency was significantly prolonged and N75-P100 amplitude was significantly reduced compared to diabetics without peripheral neuropathy. A significant positive correlation of VEP P100 latency (p < 0.001) and a negative correlation with N75-P100 amplitude (p < 0.001) with duration of disease were also found. Conclusion: VEP changes are observed in diabetics before the development of retinopathy or peripheral neuropathy indicating optic pathway dysfunction, which precedes the development of these complications. Early preclinical visual pathway dysfunction can warrant taking the necessary measures to reduce diabetic complications. Abbreviations: DM = Diabetes Mellitus, VEP = Visual Evoked Potential, HbA1c = Hemoglobin A1 c, MRI = Magnetic Resonance Imaging, EEG = Electroencephalography, P100 = Positive wave peak at latency 100 ms (millisecond), N75 = Negative wave peak at latency 75 ms (millisecond), N145 = Negative wave peak at latency 145 ms (millisecond), OCT = Optical coherence tomography, PRVEP = Pattern Reversal Visual Evoked Potential, NCS = Nerve Conduction Study, SSR = Sympathetic Skin Response, IL1 = Interleukin-1, LIF = Leukemia inhibitory factor, CNTF = Ciliary neurotrophic factor, TNF alpha = Tumor necrosis factor-alpha, TGF-beta = Transforming growth factor-beta.

Area V4 is an intermediate-level area of the macaque visual cortical hierarchy that serves key functions in visual processing by integrating inputs from lower areas such as V1 and V2 and providing feedforward inputs to many higher cortical areas. Previous V4 imaging studies have focused on differential responses to color, orientation, disparity, and motion stimuli, but many details of the spatial organization of significant hue and orientation tuning have not been fully described. We used support vector machine (SVM) decoding of intrinsic cortical single-condition responses to generate high-resolution maps of hue and orientation tuning and to describe the organization of hue and orientation pinwheels in V4. Like V1 and V2, V4 contains maps of orientation that are organized as pinwheels. V4 also contains maps of hue that are organized as pinwheels, whose circular organization more closely represents the perception of hue than is observed in antecedent cortical areas. Unlike V1, where orientation is continuously mapped across the surface, V4 hue and orientation pinwheels are organized in limited numbers of pinwheel sequences. The organization of these sequences and the distance between pinwheels may provide insight into the functional organization of V4. Regions significantly tuned for hue occupy roughly four times that of the orientation, are largely separated from each other, and overlap by roughly 5%. This spatial organization is largely consistent with segregated inputs arising from V2 thin and interstripes. This modular organization of V4 suggests that further integration of color and shape might occur in higher areas in inferotemporal cortical.NEW & NOTEWORTHY The representation of hue and orientation in macaque monkey area V4 was determined by intrinsic cortical imaging of responses to isoluminant hues and achromatic grating stimuli. Vector summation of support vector machine (SVM) decoded single-condition responses was used to generate hue and orientation maps that, like V1 orientation maps, were both characterized by distinct pinwheel patterns. These data suggest that pinwheels are an important structure to represent different stimulus features across multiple visual cortical areas.