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Topic: hyperactivity

Seminar
2 seminars
ePoster
1 ePoster

In Neuroscience and Vision Science

Seminar · Vision Science

An inconvenient truth: pathophysiological remodeling of the inner retina in photoreceptor degeneration

Michael Telias · University of Rochester

Tue, Apr 8, 2025 · 16:00 UTC

Photoreceptor loss is the primary cause behind vision impairment and blindness in diseases such as retinitis pigmentosa and age-related macular degeneration. However, the death of rods and cones allows retinoids to permeate the inner retina, causing retinal ganglion cells to become spontaneously hyperactive, severely reducing the signal-to-noise ratio, and creating interference in the communication between the surviving retina and the brain. Treatments aimed at blocking or reducing hyperactivity improve vision initiated from surviving photoreceptors and could enhance the signal fidelity genera

Seminar · Vision Science

Understanding how photoreceptor degeneration alters retinal signaling, and how to intervene to rescue vision

Richard Kramer · UC Berkeley

Mon, Jan 18, 2021 · 15:00 UTC

Age-related Macular Degeneration (AMD) and Retinitis Pigmentosa (RP) are vision disorders caused by loss of rod and cone photoreceptors, but downstream retinal neurons also show physiological and morphological changes, resulting in the emergence of hyperactivity and rhythmic firing in many retinal ganglion cells (RGC). We recently discovered that retinoic acid (RA) is a key signal that triggers hyperactivity and that blockers of RA unmask light responses in RGCs that would otherwise be obscured. Recent work is revealing where in the retina circuit RA initiates functional changes. Moreover, int

ePoster · Neuroscience

The predictive power of neurological factors for differentiated attention functions in children and adolescents with the genetic disorder neurofibromatosis type 1

Rita Hansl, David Steyrl, Lena Fichtinger, Amedeo Azizi, Ulrike Leiss, Thomas Pletschko · FENS Forum 2024

Neurofibromatosis type 1 (NF1) is one of the most prevalent rare genetic diseases, confronting patients with numerous medical (neurological, cutaneous, osseous) and neuropsychological symptoms. To identify risk factors and allow for targeted neuropsychological intervention, potential associations between the heterogenous somatic and cognitive phenotype have been proposed.The present study harnesses the benefits of machine learning analysis to investigate potential non-/linear associations between the medical and neuropsychological profiles of n=236 pediatric NF1 patients. A total of 14 models