2026 American Academy of Neurology Abstract Website

Calvin Howard¹, Simon Kwon², Savir Madan³, Arun Garimella³, Frederic Schaper⁴, Isaiah Kletenik⁵, Marcus Ng⁶, Philip Mosley⁷, Jordan Grafman⁸, Rohit Bakshi³, Bonnie Glanz⁹, Lisa Fosdick¹⁰, Amy Johnson⁶, Ryan Colyer¹¹, Constantine Lyketsos¹², Mae Morton-Dutton³, John Giftakis¹³, Yasin Temel¹⁴, Rob Rouhl¹⁴, Ji Hyun Ko⁶, Rabea Schmahl¹⁵, Juan Baldermann¹⁵, Pablo Andrade-Montemayor¹⁵, Veerle Visser-Vandewalle¹⁵, Jens Kuhn¹⁵, Maurizio Corbetta¹⁶, Robert Fisher¹⁷, Thomas Picht¹⁸, Katharina Faust¹⁹, Molly Hermiller²⁰, Joel Voss²¹, Tanuja Chitnis², Michael Kahana¹¹, Gwenn Smith¹², Andres Lozano²², Shan Siddiqi³, Andreas Horn²³, Michael Fox²⁴
¹Calvin Howard, ²Brigham and Women's Hospital, ³Harvard Medical School, ⁴Brigham and Women's, ⁵BRIGHAM AND WOMEN’S HOSPITAL, ⁶University of Manitoba, ⁷Queensland Brain Institute, ⁸Cognitive Neuroscience Section, ⁹Brigham and Women'S Hospital, ¹⁰Functional Neuromodulation Inc., ¹¹University of Pennsylvania, ¹²Johns Hopkins Medicine, ¹³Medtronic, ¹⁴Maastricht University Medical Center, ¹⁵University of Cologne, ¹⁶Department of Neurology, Washington University School of Medicine, ¹⁷Stanford University Medical Center, ¹⁸Charite Universitatmedizin Berlin, ¹⁹Dusseldorf University, ²⁰Florida State University, ²¹, University of Chicago, ²²Toronto Western Hosp, ²³University Hospital Cologne, ²⁴Brigham and Women's Hospital / Harvard Medical School

Objective:

Identify a brain‐stimulation network target for memory dysfunction.

Background:

Therapeutic brain stimulation holds promise in treating memory impairment, but results have been inconsistent in part due to uncertainty in the neuroanatomical target. Here we combine data from patients with brain lesions, DBS, and TMS to map out a convergent memory network and evaluate if its potential as a therapeutic stimulation target.

Design/Methods:

We analyzed 12 independent datasets (n=1,247): focal lesions (n=985), DBS (n=207), and TMS (n=72). For each lesion or stimulation site, we computed normative functional connectivity and mapped connections covarying with episodic memory outcomes within each dataset. (1) We tested whether lesion-, DBS-, and TMS-derived maps converged on a common brain network. (2) We evaluated whether connectivity to this network explained memory variance in held-out lesion, DBS, and TMS cohorts. (3) We assessed if connectivity to the convergent memory network could explain prior outcomes from Alzheimer’s disease (AD) brain stimulation trials. (4) In retrospective AD DBS patients, we derived theoretically optimal DBS parameters that maximally engaged the convergent memory network and assessed if being closer to these optimal parameters was associated with better memory outcomes.

Results:

Lesion, DBS, and TMS maps converged on a common memory network (spatial R=0.75, p=0.0092) with significant nodes in hippocampus, precuneus, cerebellum, lateral parietal, retrosplenial, and prefrontal cortex. Connectivity to this network explained memory variance in held-out datasets and explained significantly more variance than connectivity to prior localizations like the hippocampus, Papez circuit, or default mode network (average ΔR²=23%, p=0.0361). Across 19 AD stimulation trials, sites more positively connected to the convergent network were associated with better memory outcomes (t=4.76, p=0.0005). In AD DBS cohorts, outcomes improved as clinician-programmed settings approached theoretically optimal parameters (ρ=0.55, p=0.0021).

Conclusions:

Lesion, DBS, and TMS effects on memory map on to a common brain network which may be a memory neuromodulation target.