Sensory encoding and memory in the mushroom body: signals, noise, and variability.

To survive in changing environments, animals need to learn to associate specific sensory stimuli with positive or negative valence. How do they form stimulus-specific memories to distinguish between positively/negatively associated stimuli and other irrelevant stimuli? Solving this task is one of the functions of the mushroom body, the associative memory center in insect brains. Here we summarize recent work on sensory encoding and memory in the Drosophila mushroom body, highlighting general principles such as pattern separation, sparse coding, noise and variability, coincidence detection, and spatially localized neuromodulation, and placing the mushroom body in comparative perspective with mammalian memory systems.

Evaluation of Retinal Arterial Occlusion and its Visual and Systemic Prognosis after Hyperbaric Oxygen Therapy.

PURPOSE: To evaluate the systemic and ocular outcomes of patients with branch retinal artery occlusion (BRAO) and central retinal artery occlusion (CRAO) after hyperbaric oxygen therapy (HBOT). METHODS: This is a single-institution study of 75 subjects diagnosed with BRAO (28, 37.3%) and CRAO (47, 62.7%) who visited the emergency department or stroke clinic. Twenty-seven (36%) subjects received HBOT on initial presentation (BRAO-14.3%, CRAO-48.9%). The primary outcome was the best corrective visual acuity (BCVA) change in non-HBOT and HBOT subjects. Secondary outcomes included subsequent development of an acute cerebrovascular accident (CVA)/stroke or neovascular glaucoma (NVG). RESULTS: Overall BCVA did not change from the initial presentation to the final timepoint (logMAR 1.5) in either the conservative management or HBOT cohorts for either BRAO subjects (non-HBOT-logMAR 0.4 vs. 0.6, p=0.658; HBOT-logMAR 0.1 vs. 0.4, p=0.207) or CRAO subjects (non-HBOT-logMAR 2.1 vs. 2.2, p=0.755; HBOT-logMAR 2.1 vs. 2.0, p=0.631). Seven (9.3%) subjects developed CVA (BRAO: non-HBOT-4.2% and HBOT-25.0%, p=0.207; CRAO: non-HBOT-16.7% and HBOT-4.3%, p=0.348) and five subjects (6.7%) developed NVG (BRAO: non-HBOT-4.2% and HBOT-0%, p=1.00; CRAO: non-HBOT-16.7% and HBOT-0%, p=0.109). CONCLUSIONS: Our findings suggest that HBOT does not significantly improve BCVA or mitigate the subsequent development of stroke and NVG in patients with RAOs.

Retinal structural changes after cessation of pentosan polysulfate sodium.

PURPOSE: To quantify baseline and longitudinal structural changes post-cessation in pentosan polysulfate sodium (PPS) retinopathy patients. METHODS: This is a retrospective cohort study. Retinal thickness and volume of choroidal and hyperreflective retinal pigment epithelium (RPE) excrescences were manually segmented from optical coherence tomography (OCT) volume scans. Baseline measurements were compared against age-matched controls. Longitudinal measurements were performed on patients with follow-up data. RESULTS: Twenty-four eyes of 13 patients were included. At baseline, the mean total retinal thickness was lower in the PPS retinopathy cohort than in age and sex-matched controls (269.1 µm vs. 290.2 µm, p = 0.006).The median (range) of follow-up was 18.6 (4.1 to 34.7) months, with the mean last follow-up of 35.2 months after cessation. During the follow-up period, the thickness of the retina decreased significantly by 11.3 µm (CI: 16.8, 5.8) (p<0.001), with an annual mean decrease of 6.70 µm. However, the mean hyperreflective RPE excrescence volume did not change significantly (p = 0.140) over the follow-up period. CONCLUSIONS: Following PPS discontinuation, although RPE excrescence volumes do not change significantly in volume, there continues to be a progressive long-term thinning of the retina which continues at a rate greater than that associated with normal aging. Consequently, long-term follow-up is suggested to monitor patients with PPS maculopathy.

Ultra-wide field and new wide field composite retinal image registration with AI-enabled pipeline and 3D distortion correction algorithm.

PURPOSE: This study aimed to compare a new Artificial Intelligence (AI) method to conventional mathematical warping in accurately overlaying peripheral retinal vessels from two different imaging devices: confocal scanning laser ophthalmoscope (cSLO) wide-field images and SLO ultra-wide field images. METHODS: Images were captured using the Heidelberg Spectralis 55-degree field-of-view and Optos ultra-wide field. The conventional mathematical warping was performed using Random Sample Consensus-Sample and Consensus sets (RANSAC-SC). This was compared to an AI alignment algorithm based on a one-way forward registration procedure consisting of full Convolutional Neural Networks (CNNs) with Outlier Rejection (OR CNN), as well as an iterative 3D camera pose optimization process (OR CNN + Distortion Correction [DC]). Images were provided in a checkerboard pattern, and peripheral vessels were graded in four quadrants based on alignment to the adjacent box. RESULTS: A total of 660 boxes were analysed from 55 eyes. Dice scores were compared between the three methods (RANSAC-SC/OR CNN/OR CNN + DC): 0.3341/0.4665/4784 for fold 1-2 and 0.3315/0.4494/4596 for fold 2-1 in composite images. The images composed using the OR CNN + DC have a median rating of 4 (out of 5) versus 2 using RANSAC-SC. The odds of getting a higher grading level are 4.8 times higher using our OR CNN + DC than RANSAC-SC (p < 0.0001). CONCLUSION: Peripheral retinal vessel alignment performed better using our AI algorithm than RANSAC-SC. This may help improve co-localizing retinal anatomy and pathology with our algorithm.