paper:doi-10-1109-iembs-2003-1280959Long-term bidirectional neuron interfaces for robotic control, and in vitro learning studies
Original abstract (expand)
There are two fundamentally different goals for neural interfacing. On the biology side, to interface living neurons to external electronics allows the observation and manipulation of neural circuits to elucidate their fundamental mechanisms. On the engineering side, neural interfaces in animals, people, or in cell culture have the potential to restore missing functionality, or someday, to enhance existing functionality. At the Laboratory for NeuroEngineering at Georgia Tech, we are developing new technologies to help make both goals attainable. We culture dissociated mammalian neurons on multielectrode arrays, and use them as the brain of a 'Hybrot', or hybrid neural-robotic system. Distributed neural activity patterns are used to control mobile robots. We have created the hardware and software necessary to feed the robots' sensory inputs back to the cultures in real time, as electrical stimuli. By embodying cultured networks, we study learning and memory at the cellular and network level, using 2-photon laser-scanning microscopy to image plasticity while it happens. We have observed a very rich dynamical landscape of activity patterns in networks of only a few thousand cells. We can alter this landscape via electrical stimuli, and use the hybrot system to study the emergent properties of networks in vitro.
Related work— refs + corpus + external arXiv
Cited / in-corpus / arXiv badges show which signals surfaced each row. Multi-source rows weighted higher.
- Bidirectional Interaction between Visual and Motor Generative Models using Predictive Coding and Active InferenceAlexandre Pitti, Mathias Quoy Louis Annabi2021≈ 78%
- Artificial Intelligence Software Structured to Simulate Human Working Memory, Mental Imagery, and Mental ContinuityJared Edward Reser2026≈ 77%
- What Neuroscience Can Teach AI About Learning in Continuously Changing EnvironmentsBruno Averbeck, Georgia Koppe Daniel Durstewitz2025≈ 76%
- Neural mechanisms of predictive processing: a collaborative community experiment through the OpenScope programNicholas Audette, Ryszard Auksztulewicz, Krzysztof Basi\'nski, Andr\'e M. Bastos, Michael Berry, Andres Canales-Johnson, Hannah Choi, Claudia Clopath, Uri Cohen, Rui Ponte Costa, Roberto De Filippo, Roman Doronin, S\'everine Durand, Steven P. Errington, Jeffrey P. Gavornik, Colleen J. Gillon, Arno Granier, Jordan P. Hamm, Loreen Hert\"ag, Henry Kennedy, Sandeep Kumar, Alexander Ladd, Hugo Ladret, J\'er\^ome A. Lecoq, Alexander Maier, Patrick McCarthy, Jie Mei, Jorge Mejias, John Hongyu Meng, Fabian Mikulasch, Noga Mudrik, Farzaneh Najafi, Kevin Nejad, Hamed Nejat, Karim Oweiss, Mihai A. Petrovici, Viola Priesemann, Lucas Rudelt, Sarah Ruediger, Simone Russo, Alessandro Salatiello, Walter Senn, Eli Sennesh, Sepehr Sima, Cem Uran, Anna Vasilevskaya, Julien Vezoli, Martin Vinck, Xiao-Jing Wang, Jacob A. Westerberg, Katharina Wilmes, Yihan Sophy Xiong Ido Aizenbud2026≈ 76%
- Continual Developmental Neurosimulation Using Embodied Computational AgentsRishabh Chakrabarty, Stefan Dvoretskii, Akshara Gopi, Avery Lim, and Jesse Parent Bradly Alicea2024≈ 75%
- Towards hybrid primary intersubjectivity: a neural robotics library for human scienceAhmadreza Ahmadi, Jun Tani Hendry F. Chame2021≈ 75%
- Space as Time Through Neuron Position LearningJames C. Knight, Danyal Akarca, Thomas Nowotny Bal\'azs M\'esz\'aros2026≈ 75%
- Neuroscience-inspired perception-action in robotics: applying active inference for state estimation, control and self-perceptionMarcel van Gerven Pablo Lanillos2021≈ 75%
- Bioelectrical Interfaces Beyond Cellular Excitability: Cancer, Aging, and Gene Expression ReprogrammingMatthew Burgess, Catarina Franco Jones, Titouan Luciani, Marzia Iarossi, Manuel Schr\"oter, Nako Nakatsuka, Mustafa B. A. Djamgoz, Gil Gon\c{c}alves, Paola Sanju\'an-Alberte, Paula M. Mendes, Frankie J. Rawson, Malavika Nair, Michael Levin, Rosalia Moreddu Paolo Cadinu2025≈ 75%
- A Cognitive Architecture for Machine Consciousness and Artificial Superintelligence: Thought Is Structured by the Iterative Updating of Working MemoryJared Edward Reser2024≈ 75%
- Developmental Bioelectricity: the cognitive glue enabling evolutionary scaling from physiology to mindin corpus2023≈ 75%
- Modeling motor control in continuous-time Active Inference: a surveyFederico Maggiore, Antonella Maselli, Francesco Donnarumma, Domenico Maisto, Francesco Mannella, Ivilin Peev Stoianov and Giovanni Pezzulo Matteo Priorelli2024≈ 75%
- NeuroAI and Beyond: Bridging Between Advances in Neuroscience and ArtificialIntelligenceJean-Marc Fellous, Terrence Sejnowski, Gina Adam, James B Aimone, Akwasi Akwaboah, Yiannis Aloimonos, Carmen Amo Alonso, Chiara Bartolozzi, Michael J. Bennington, Michael Berry, Bing W. Brunton, Gert Cauwenberghs, Hillel J. Chiel, Tobi Delbruck, John Doyle, Jason Eshraghian, Ralph Etienne-Cummings, Cornelia Fermuller, Matthew Jacobsen, Ali A. Minai, Barbara Oakley, Alexander G. Ororbia II, Joe Paton, Blake Richards, Yulia Sandamirskaya, Abhronil Sengupta, Shihab Shamma, Michael P. Stryker, Seong Jong Yoo, Steven W. Zucker Anthony Zador2026≈ 75%
- Nonmodular architectures of cognitive systems based on active inferenceManuel Baltieri and Christopher L. Buckley2022≈ 75%
- ≈ 74%
- What happens next and when "next" happens: Mechanisms of spatial and temporal predictionDean Wyatte2014≈ 74%
- ≈ 74%
- The computational boundary of a 'self': developmental bioelectricity drives multicellularity and scale-free cognitionin corpus2019≈ 74%
- Learning without neurons in physical systemsin corpus2022≈ 73%
- ≈ 73%
- Collective intelligence: A unifying concept for integrating biology across scales and substratesin corpus2024≈ 72%
- The biogenic approach to cognitionin corpus2005≈ 72%
- ≈ 72%
- ≈ 72%
- Relating transformers to models and neural representations of the hippocampal formationin corpus2021≈ 71%
- ≈ 71%
- ≈ 71%
- ≈ 71%
- Manifold Steering Reveals the Shared Geometry of Neural Network Representation and Behaviorin corpus2026≈ 71%
Similar preprints — Semantic Scholar
Cited by (5)
- Biology, Buddhism, and AI: Care as the Driver of Intelligence
Care—defined as concern for the alleviation of stress (the delta between current and optimal states)—is proposed as the substrate-independent invariant that unifies biology, Buddhist philosophy, and a
- Endless forms most beautiful 2.0: teleonomy and the bioengineering of chimaeric and synthetic organisms
Cellular collectives exhibit goal-directed competency that is substrate-independent, composition-independent, and origin-independent — a property Clawson and Levin term teleonomy — and this invariant,
- Cellular signaling pathways as plastic, proto-cognitive systems: Implications for biomedicine
- Technological Approach to Mind Everywhere: An Experimentally-Grounded Framework for Understanding Diverse Bodies and Minds
TAME—Technological Approach to Mind Everywhere—formalizes a non-binary, empirically grounded framework for recognizing, comparing, and manipulating cognition across radically diverse substrates, from
- AI: a Bridge toward Diverse Intelligence and Humanity’s Future
Current AI debates are importantly incomplete because they fixate on large language models while ignoring the broader space of impending minds — including cyborgs, hybrots, genetically augmented human