Papers
11
Total Citations
451
H-Index
9
About
Eric A. Pohlmeyer is a pioneering neuroscientist and biomedical engineer whose work sits at the dynamic intersection of neural decoding, brain-machine interfaces (BMIs), and neuroprosthetics. His early research established foundational methods for predicting upper limb muscle activity from motor cortical signals during reaching movements, a landmark 2007 contribution that has garnered over 120 citations and helped shape the theoretical and practical basis of modern BMI design. Alongside complementary work on biomimetic brain-machine interfaces, Pohlmeyer helped demonstrate how large-scale cortical recordings could enable real-time control of cursors and robotic limbs. A hallmark of his career has been the innovative application of reinforcement learning to BMI systems. His studies using actor-critic algorithms and Hebbian reinforcement learning showed that neuroprosthetic controllers could adaptively learn and remain stable even as neural signals reorganize over time — critical progress for translating BMIs from laboratory settings into everyday clinical use. His research using the common marmoset as a model organism further broadened the field's experimental toolkit. More recently, Pohlmeyer has pushed boundaries by demonstrating simultaneous bilateral hand gesture classification in a tetraplegic patient and exploring unconventional BMI applications such as flight simulation, underscoring both the clinical promise and imaginative reach of his contributions to neurotechnology.
Research Focus
Key Achievements
Top Papers
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- 3Biomimetic Brain Machine Interfaces for the Control of Movement69 citations · 2007
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- 6Flight simulation using a Brain-Computer Interface: A pilot, pilot study36 citations · 2016
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- 9Kernel Temporal Differences for Neural Decoding12 citations · 2015
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