Neuromorphic brain prosthetics

Neuromorphic implants represent a potential avenue for preserving and enhancing cognitive functions by replacing parts of the brain with artificial systems designed to mimic the behavior of biological neurons. This approach could address the intrinsic aging processes of the brain, which are hypothesized to eventually compromise its function and die even when supported by a synthetic body. Such implants must replicate the complex dynamics of biological neurons, including their electrophysiological properties, synaptic connectivity, and plasticity, to integrate seamlessly into the brain's neural networks.

One approach utilizes solid-state neurons that mimic the complex dynamics of biological neurons. Abu-Hassan et al. (2019) demonstrated neuromorphic microcircuits configured to replicate the ion channel properties of hippocampal and respiratory neurons. By estimating parameters from electrophysiological recordings, these solid-state neurons emulate intracellular currents and membrane potentials, responding nearly identically to their biological counterparts across a range of stimuli. This method provides a platform for designing implants capable of integrating with biofeedback systems, potentially enabling the repair of damaged neural circuits (Nature Communications, 2019).

Organic electrochemical neurons (c-OECNs), constructed from mixed ion–electron conducting polymers, represent another advancement. Harikesh et al. (2023) described c-OECNs that emulate critical features of biological neurons, including sodium channel activation/inactivation and delayed potassium channel activation. These neurons can spike at biologically relevant frequencies (up to 100 Hz) and respond to ion-based modulation, such as neurotransmitters or amino acids, which are essential for seamless integration with biological systems. These biocompatible materials provide significant advantages over traditional silicon-based technologies in interfacing with living tissue and have been shown to stimulate biological nerves in vivo, creating a functional link between artificial and natural neurons (Nature Materials, 2023).

Memristive devices further contribute to the development of neuromorphic systems by enabling highly efficient emulation of synaptic plasticity, a fundamental property for learning and memory. These devices use changes in resistance to encode synaptic weights and exhibit low power consumption, making them a promising candidate for dense neural networks. They provide flexibility in simulating spike-timing-dependent plasticity and other adaptive behaviors critical for neural circuit functionality.

Organic mixed ionic-electronic conductors (OMIECs) offer another approach to creating biorealistic neuromorphic systems. These materials allow real-time, bidirectional communication with biological neurons and demonstrate excellent stability and speed, with ionic modulation capabilities that mimic natural neuronal processes. OMIECs have the potential to serve as an interface for integrating neuromorphic implants with biological networks while maintaining the biocompatibility needed for long-term use.

Despite these advancements, the creation of functional neuromorphic implants remains an exceptionally challenging task. Neural systems operate as highly interconnected and dynamic networks, and replicating their behavior at a system-wide level requires significant progress in computational modeling, device miniaturization, and biocompatible fabrication. Furthermore, the question of whether artificial neurons can support or replicate consciousness remains unresolved, touching on fundamental philosophical and scientific uncertainties.