Retinal neuroaxonal thinning occurs in MCI/AD consistently with previous reports, as well as in FTD. Correlation with disease severity in AD suggests that retinal and brain neurodegeneration may occur in parallel to some extent, and prompts larger studies aimed at providing surrogate endpoints for clinical trials in AD.

Biological functions are carried out by groups of interacting molecules, cells or tissues, known as communities. Membership in these communities may overlap when biological components are involved in multiple functions. However, traditional clustering methods detect non-overlapping communities. These detected communities may also be unstable and difficult to replicate, because traditional methods are sensitive to noise and parameter settings. These aspects of traditional clustering methods limit our ability to detect biological communities, and therefore our ability to understand biological functions. To address these limitations and detect robust overlapping biological communities, we propose an unorthodox clustering method called SpeakEasy which identifies communities using top-down and bottom-up approaches simultaneously. Specifically, nodes join communities based on their local connections, as well as global information about the network structure. This method can quantify the stability of each community, automatically identify the number of communities, and quickly cluster networks with hundreds of thousands of nodes. SpeakEasy shows top performance on synthetic clustering benchmarks and accurately identifies meaningful biological communities in a range of datasets, including: gene microarrays, protein interactions, sorted cell populations, electrophysiology and fMRI brain imaging.

Optical coherence tomography (OCT) is gaining increasing relevance in the assessment of patients with multiple sclerosis. Converging evidence point to the view that neuro-retinal changes, in eyes without acute optic neuritis, reflect inflammatory and neurodegenerative processes taking place throughout the CNS. The present study aims at exploring the usefulness of OCT as a marker of inflammation and disease burden in the earliest phases of the disease. Thus, a cohort of 150 consecutive patients underwent clinical, neurophysiological and brain MRI assessment as well as lumbar puncture as part of their diagnostic workup for a neurological episode suggestive of inflammatory CNS disorder; among those 32 patients had another previous misdiagnosed episode. For the present study, patients also received a visual pathway assessment (OCT, visual evoked potentials, visual acuity), measurement of CSF inflammatory markers (17 cytokines-chemokines, extracellular vesicles of myeloid origin), and dosage of plasma neurofilaments. Subclinical optic nerve involvement is frequently found in clinically isolated syndromes by visual evoked potentials (19.2%). OCT reveals ganglion cell layer asymmetries in 6.8% of patients; retinal fibre layer asymmetries, despite being more frequent (17.8%), display poor specificity. The presence of subclinical involvement is associated with a greater disease burden. Second, ganglion cell layer thinning reflects the severity of disease involvement even beyond the anterior optic pathway. In fact, the ganglion cell layer in eyes without evidence of subclinical optic involvement is correlated with Expanded Disability Status Scale, low contrast visual acuity, disease duration, brain lesion load, presence of gadolinium enhancing lesions, abnormalities along motor and somatosensory evoked potentials, and frequency of CSF-specific oligoclonal bands. Third, the inner nuclear layer thickens in a post-acute (1.1–3.7 months) phase after a relapse, and this phenomenon is counteracted by steroid treatment. Likewise, a longitudinal analysis on 65 patients shows that this swelling is transient and returns to normal values after 1 year follow-up. Notwithstanding, the clinical, MRI, serological and CSF markers of disease activity considered in the study are strictly associated with one another, but none of them are associated with the inner nuclear layer. Our findings challenge the current hypothesis that the inner nuclear layer is an acute phase marker of inflammatory activity. The present study suggests that instrumental evidence of subclinical optic nerve involvement is associated with a greater disease burden in clinically isolated syndrome. Neuro-retinal changes are present since the earliest phases of the disease and yield important information regarding the neurodegenerative and inflammatory processes occurring in the CNS.

Artificial intelligence (AI)-based diagnostic algorithms have achieved ambitious aims through automated image pattern recognition. For neurological disorders, this includes neurodegeneration and inflammation. Scalable imaging technology for big data in neurology is optical coherence tomography (OCT). We highlight that OCT changes observed in the retina, as a window to the brain, are small, requiring rigorous quality control pipelines. There are existing tools for this purpose. Firstly, there are human-led validated consensus quality control criteria (OSCAR-IB) for OCT. Secondly, these criteria are embedded into OCT reporting guidelines (APOSTEL). The use of the described annotation of failed OCT scans advances machine learning. This is illustrated through the present review of the advantages and disadvantages of AI-based applications to OCT data. The neurological conditions reviewed here for the use of big data include Alzheimer disease, stroke, multiple sclerosis (MS), Parkinson disease, and epilepsy. It is noted that while big data is relevant for AI, ownership is complex. For this reason, we also reached out to involve representatives from patient organizations and the public domain in addition to clinical and research centers. The evidence reviewed can be grouped in a five-point expansion of the OSCAR-IB criteria to embrace AI (OSCAR-AI). The review concludes by specific recommendations on how this can be achieved practically and in compliance with existing guidelines.