Advances in Microscopy for Visualizing Neurologic Disease*
Date: October 18, 2026
Time: 1:30 pm to 3:00 pm
Room: Pacific Jewel Ballroom
Track: Plenary - Presidential Symposium
Session Description
Understanding neurologic disease requires tools that can resolve the brain across molecular, cellular, and systems‑level scales. This session highlights how super‑resolution imaging, organelle‑level analysis, and AI‑driven single‑cell profiling together provide a multidimensional view of disease mechanisms in neuronal model systems.
Super‑resolution microscopy breaks the diffraction limit to visualize nanoscale structures in living neurons. Techniques such as STED, PALM, and STORM reveal early pathogenic changes in synaptic nanodomains, receptor clustering, cytoskeletal organization, and axonal transport. These methods capture dynamic molecular events—such as protein aggregation or trafficking defects—that precede overt degeneration, offering insight into how subtle disruptions propagate through neural circuits.
Advanced electron microscopy complements this by exposing ultrastructural abnormalities in organelles central to neuronal health. Serial block‑face EM, cryo‑EM, and focused ion beam tomography reconstruct neurons in 3D, revealing mitochondrial swelling, cristae loss, lysosomal dysfunction, ER–mitochondria contact disruption, and impaired autophagosome maturation. These organelle‑level defects illuminate how metabolic stress, proteostasis failure, and calcium imbalance contribute to disease vulnerability.
AI‑driven analysis integrates these imaging datasets with single‑cell transcriptomics and spatial profiling. Machine‑learning models classify neuronal and glial subtypes, detect subtle phenotypes invisible to human observers, quantify organelle dynamics, and map disease trajectories across thousands of cells. By linking structural abnormalities to gene‑expression states and spatial context, AI identifies vulnerable cell populations and mechanistic pathways that drive pathology.
Together, these approaches form a unified framework.
Learning Objectives
At the conclusion of this session, attendees will be able to:
- Describe AI-based single-cell analytics and the integration of multimodal datasets.
- Explain the principles of super-resolution imaging and how these techniques overcome diffraction limits.
- Identify early nanoscale disease signatures and their relevance for clinical translation.
Speakers
- (Chair) Dimitri Krainc, MD, PhD, FANA
- (Co-Chair, Speaker) Craig Blackstone, MD, PhD, FANA
- (Speaker) Erika Holzbaur, PhD
- (Speaker) Steve Finkbeiner, MD, PhD, FANA
NeuroZoom: Super-Resolution for Neurologic Disease Discovery
Description
In this presentation Dr. Blackstone will discuss how advances in super‑resolution light microscopy and electron microscopy are increasingly employed to reveal dynamic nanoscale changes in neurons and glia that drive neurologic disease. These tools can be applied to cellular and in vivo models to map synaptic architecture, track protein movement and aggregation, and visualize changes in organelle morphology, movement and function, enabling precise pathologic insights and accelerating therapeutic discovery.
Advanced Imaging Approaches to Deipher Cellular Mechanisms of Neurodevelopmental and Neurodegenerative Disease
Description
In this presentation, Dr. Holzbaur will present how labs use state-of-the-art imaging approaches to decipher the molecular mechanisms driving neurodevelopmental and neurodegenerative disease. We live-image organelle dynamics in human iPSC-derived neurons, studying mechanisms that regulate cellular homeostasis. Our work focuses on mitochondrial dynamics and autophagy, and how defects in these pathways contribute to pathogenesis in diseases including Fragile X Syndrome, KAND, Parkinson’s disease, and ALS.
State-of-the-Art Technologies to Generate and Analyze Large Amounts of Imaging and Genetic Data, Including Robotic Microscopy and AI
Description
In this presentation, Dr. Finkbeiner will discuss state-of-the-art technologies that generate and analyze large amounts of imaging and genetic data, including robotic microscopy and AI.
