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Physical electronic devices that generate neuron-like spikes at biological voltages and timescales so they can exchange signals directly with living nerve cells and tissue.
Bio-interfacing artificial neurons are electronic devices built to produce spikes resembling a nerve cell's action potential, at voltages, energies and timescales close enough to biology that the device can drive living neurons or be driven by them. They are a proposed building block for Neuroprosthetics that would compute and signal in the nervous system's own format rather than through fixed stimulation pulses. As of October 2026 every demonstration of an artificial neuron coupled to living tissue has been an acute laboratory experiment in cells, brain slices or anaesthetized animals, and no study has reported implanting one in a person.
"Artificial neuron" names three different things, and news coverage regularly blurs them.
The oldest is mathematical. The units of a software neural network, descended from the McCulloch–Pitts model of 1943, are weighted sums passed through a nonlinearity. They have no physical form and no electrical contact with anything biological, and they are what the phrase means in machine learning and in debates about Artificial general intelligence.
The second is neuromorphic hardware: circuits that emulate spiking neurons physically, mostly to compute more efficiently. Mahowald and Douglas built an analog "silicon neuron" in 1991 that reproduced the ion currents behind a nerve impulse in real time.1 Most neuromorphic hardware since then has been designed for computing rather than for contact with tissue, and most artificial neurons have operated at signal amplitudes of half a volt or more.2
The third, the subject here, is the bio-interfacing subset: devices whose purpose is to sit in or next to living tissue and exchange signals with it. That imposes requirements computing does not. Biological action potentials are on the order of 100 millivolts and last about a millisecond; the device must work in salty, wet surroundings; and, ideally, it responds to the chemical signals neurons use as well as the electrical ones.
Three device families dominate.
Analog silicon neurons model each ion channel with a transistor circuit. A University of Bath team fitted conductance models to recordings from rat hippocampal and brainstem respiratory neurons and used the fitted parameters to configure silicon neurons, which responded nearly identically to the biological cells; the completed models matched recorded membrane voltage with 94–97% agreement across 60 current-injection protocols.3 The authors propose such circuits as a route to implants that repair failing neural circuits; the study itself compared chip and neuron offline and connected nothing to tissue.
Memristive neurons use a component whose resistance switches abruptly when a conductive filament forms and then dissolves, producing a spike in a simple circuit. The difficulty has been that most filamentary memristors switch above half a volt, several times the amplitude of a biological spike. A University of Massachusetts Amherst group used protein nanowires harvested from the bacterium Geobacter sulfurreducens to build memristors that switch at about 60 millivolts and 1.7 nanoamps, with a spiking energy of about 37 picojoules at a typical membrane capacitance, within the range the authors cite for real neurons.2 A Northwestern team instead printed graphene and molybdenum disulfide nanosheet inks onto flexible substrates, producing memristive neurons that fire single spikes, tonic trains and bursts at frequencies up to 20 kHz.4
Organic electrochemical neurons are built from transistors whose polymer channel conducts both ions and electrons, so ions in the surrounding fluid alter the firing directly. Linköping University researchers first made fully printed versions,5 then built a version whose firing approaches 100 Hz and can be modulated by sodium, glutamine or neurotransmitters.6 A Max Planck Institute for Polymer Research group built a two-transistor organic neuron that operates in liquid and changes its excitability in response to dopamine or small shifts in ion concentration; placed behind a layer of intestinal epithelial cells, its firing was suppressed by the layer's barrier to ion flow.7
Each claimed connection to living tissue is narrower than its headline.
Into tissue. The printed Northwestern neurons stimulated Purkinje neurons in slices of mouse cerebellum, work done with Indira Raman's neurobiology laboratory.4 The Linköping organic neuron, coupled to a nerve cuff, stimulated the right cervical vagus nerve of anaesthetized mice, lowering heart rate by about 4.5%; its authors state explicitly that the demonstration does not amount to a new therapy.6 The earlier printed organic neuron triggered closure of a Venus flytrap, a plant.5
Out of tissue. The UMass neuron processed signals from cardiomyocytes, heart muscle cells derived from human embryonic stem cells and grown on a graphene sensor mesh. It stayed silent at the tissue's baseline beating rate and fired once noradrenaline raised it, so it distinguished two physiological states. The signals passed through an amplifier first, and the cells were heart cells rather than neurons.2
Both directions. The clearest two-way demonstration is a 2020 network in which memristive synapses linked a single cultured rat hippocampal neuron to silicon spiking neurons, with the connection strengthening or weakening according to firing rates. The three sites communicated over the internet, and the biological side was read through a patch-clamp pipette, a method that does not scale beyond the laboratory bench.8 A 2019 system took the same idea toward repair: dissociated neurons were grown as two connected modules, the link between them was cut with a laser, and a field-programmable gate array running a spiking network restored bidirectional activity between them or stood in for the missing half.9
Coverage of the April 2026 Northwestern paper ran under the headline that artificial neurons "talk" to real brain cells, "paving way to better brain implants". The same Live Science report quoted Timothée Levi, a bioelectronics researcher at the University of Bordeaux who was not involved, as saying such devices can control living neurons "for a short time but not yet for a long time", and so are not fit to be permanent additions to a human brain.10
What "communicating with brain cells" has meantNone of the studies here implanted an artificial neuron chronically in any animal, let alone a person. The brain-tissue results are acute slice and culture experiments, the in vivo result is an acute experiment in anaesthetized mice, and several "bio-integration" demonstrations used heart cells, epithelial membranes or a plant. Durability is also unmeasured at implant scale: the printed MoS2 neurons were stable for more than a million cycles, which at ten spikes a second is roughly a day of firing.
The hard problems are the ones that limit every chronic Brain–computer interface, plus some of their own. Any implant provokes a foreign-body response that encapsulates electrodes over months, as documented for the Utah array; the cited artificial-neuron papers do not report tissue responses because none was implanted for longer than an acute experiment. Filament formation is partly random, so firing varies from device to device and from cycle to cycle. And the coupling itself still runs through conventional electrodes, pipettes or cuffs, so an artificial neuron does not remove the interface problem; it changes what sits behind it.
A single neuron is also not a circuit. Hersam, the senior Northwestern author, described the "frontier problem" as integrating devices that mimic separate elements of the brain into circuits with full functionality.10 The brain-slice and nerve results each test one device driving tissue, not a network of artificial neurons maintaining a computation with a network of real ones.
Because no device has been implanted, the risks are prospective. They are the risks of any penetrating neural implant: surgical injury, infection, and the long-term consequence of stimulation that is not identical to natural input, which in Deep brain stimulation includes mood and behavioural side effects. The UMass design depends on silver filaments forming and dissolving, and none of the cited studies tests what such materials do in tissue over months. A device that adapts its firing to local chemistry is also harder to audit than a fixed stimulator, which bears on the questions raised under Mental privacy and Neurorights about who can read or alter neural activity.
Proponents argue that artificial neurons could make prostheses that speak the nervous system's own language: a Retinal implants and visual prostheses or Cochlear implant whose output is shaped like natural spikes, a Memory prosthesis that replaces a damaged circuit with a matched one, or a closed-loop stimulator for the vagus nerve that responds to the body's chemistry. Some, as Live Science reported, go further and suggest such devices could replace neurons lost in diseases like Alzheimer's disease.10 None of these has been tested.
The nearer competitors are not standing still. Conventional electrodes driven by digital electronics, refined by better Neural decoding, already restore function in small numbers of people; Optogenetics achieves cell-type specificity in animals; and wireless miniaturization of the kind pursued under Neural dust and ultrasonic implants attacks the tethering problem directly. A further line uses living neurons rather than electronic ones, as in Organoids and biohybrid circuits.
The longest-range claims connect bio-interfacing neurons to piecemeal neuron replacement as a path toward Mind uploading and Substrate independence. That argument depends on electronic neurons reproducing not just spike timing but plasticity, neuromodulation and the full repertoire of a cell's chemistry, over decades, in place. The experimental record reaches spike timing in a dish.
paperMahowald, M. and Douglas, R. "A silicon neuron." Nature, 1991. ↩
paperFu, S. et al. "Constructing artificial neurons with functional parameters comprehensively matching biological values." Nature Communications, 2025.↩ ↩2 ↩3The living cells were human embryonic stem cell-derived cardiomyocytes, and their signals were amplified before reaching the device.
paperAbu-Hassan, K. et al. "Optimal solid state neurons." Nature Communications, 2019.↩The biological recordings came from rat brain slices; the silicon neurons were compared with them, not connected to them.
paperHadke, S. S. et al. "Printed MoS2 memristive nanosheet networks for spiking neurons with multi-order complexity." Nature Nanotechnology, 2026.↩ ↩2Stimulation of Purkinje neurons in mouse cerebellar slices; no living animal or implanted device.
paperHarikesh, P. C. et al. "Organic electrochemical neurons and synapses with ion mediated spiking." Nature Communications, 2022. ↩ ↩2
paperHarikesh, P. C. et al. "Ion-tunable antiambipolarity in mixed ion–electron conducting polymers enables biorealistic organic electrochemical neurons." Nature Materials, 2023.↩ ↩2The in vivo test was acute, in anaesthetized mice, through a vagus nerve cuff; the authors say it does not establish a therapy.
paperSarkar, T. et al. "An organic artificial spiking neuron for in situ neuromorphic sensing and biointerfacing." Nature Electronics, 2022.↩The biological partner was an epithelial cell membrane, not a neuron.
paperSerb, A. et al. "Memristive synapses connect brain and silicon spiking neurons." Scientific Reports, 2020.↩One cultured rat hippocampal neuron, recorded by patch clamp, in a three-neuron network.
paperBuccelli, S. et al. "A neuromorphic prosthesis to restore communication in neuronal networks." iScience, 2019.↩Modular neuronal cultures with a laser-cut lesion, not a brain; the spiking network ran on a field-programmable gate array.
newsGuenot, M. "Scientists invent artificial neurons that 'talk' to real brain cells, paving way to better brain implants." Live Science, 23 April 2026. ↩ ↩2 ↩3