The mammalian brain is the most complex organ in the body, capable of processing thousands of stimuli simultaneously to analyze patterns, predict changes and generate highly measured action.
How the brain does all this – within fractions of a second – is still largely unknown.
Implants that can probe the brain at the individual neuron level are not widely available to researchers.
Studying neuron activity while the body is in motion in an everyday setting is even more difficult, because monitoring devices typically involve wires connecting a study participant to a control station.
Researchers at the University of Arizona, George Washington University and Northwestern University have created an ultra-small, wireless, battery-free device that uses light to record individual neurons so neuroscientists can see how the brain is working.
he technology is detailed in a study in the Proceedings of the National Academy of Sciences.
“As biomedical engineers, we are working with collaborators in neuroscience to improve tools to better understand the brain, specifically how these individual neurons – the building blocks of the brain – interact with each other while we move through the world around us,” said lead study author Alex Burton, a University of Arizona biomedical engineering doctoral student and member of the Gutruf Lab.
The process first involves tinting select neurons with a dye that changes in brightness depending on activity.
Then, the device shines a light on the dye, making the neurons’ biochemical processes visible.
The device captures the changes using a probe only slightly wider than a human hair, then processes a direct readout of the neuron’s activity and transmits the information wirelessly to researchers.
“The device is smaller than a single M&M and only one-twentieth of the weight,” Burton said.
The device can be tiny, and even flexible like a sheet of paper, because it does not need a battery.
It harvests energy from external oscillating magnetic fields gathered by a miniature antenna on the device.
This allows researchers to study brain activity without the use of restrictive equipment and gives neuroscientists a platform to gain insight into the underpinning mechanisms of the brain.

Recording the activity of individual neurons is made possible by this tiny, wireless, battery-free device. Image is credited to University of Arizona Gutruf Labe.
“When creating the device, we used materials and methods that are readily available and cheap enough to enable large-scale adaptation of the tool by the scientific community,” said study senior author Philipp Gutruf, who leads the Gutruf Lab and is an assistant professor of biomedical engineering and member of the university’s BIO5 Institute.
“We hope that the technology can make a difference in fighting neurodegenerative diseases such as Alzheimer’s and Parkinson’s and cast light on the biological mechanisms, such as pain, addiction and depression.”
In the nervous system, massive numbers of neurons constantly generate and transmit electrophysiological signals to communicate between neurons and brain regions.
The electrical nature of neurophysiology was first revealed by Italian scientist Luigi Galvani more than two centuries ago using the primitive electrode technologies of his age1. In the following two centuries, several generations of neurophysiologists, including von Helmholtz2, Erlanger, Gasser3, Hodgkin and Huxley4, have made their independent contributions to the understanding of the nervous system.
By developing their own recording electrodes, these founding fathers of neurobiology all succeeded in detecting neural activity from relatively large dissected nerves and axons — for example, the 0.5–1 mm-wide giant squid axons studied by Hodgkin and Huxley4.
In 1957, Hubei took an important step forward by fabricating sharpened tungsten electrodes with sub-micron-diameter tip sizes, thereby recording from the much smaller neurons and axons in the mammalian brain, as demonstrated with the recording of extracellular action potentials from the cat brain5.
Hubei’s invention has had far-reaching impact in both neuroscience and neuroengineering. These electrodes enabled seminal contributions to visual neurophysiology with Wiesel6, and ushered in the development of newer probes, ranging from tetrodes [G]7 to microfabricated silicon Michigan-type microelectrode arrays [G]8and Utah-type microelectrode arrays [G]9 (MEAs; Fig. 1).

The broadband neural signals recorded from the extracellular space by either penetrating depth electrodes or surface electrodes can be processed to extract signals in different frequency bands, enabling the detection of at least two different types of voltage signals, the slow-varying local field potentials [G] (LFPs), which reflect collective transmembrane currents from multiple neurons, and action potentials lasting in the order of milliseconds (‘spikes’) from individual neuron or single-units10.
LFPs and single-unit action potentials are generally present in the raw recording traces in the time domain, which can be decomposed by Fourier transform [G] into component frequency bands as a spectrogram [G]10.
As LFPs and single-unit action potentials occupy distinct frequency bands in the spectrogram (typically <100 Hz for LFPs and >250 Hz for single-unit action potentials), they can be separated by applying analogue or digital filters to selectively pass signals in lower- and higher-frequency bands, respectively10.
LFPs have a critical role in coordinating the activity of different regions of the brain, and synchronizing the activity of individual neurons with that of a neural network, through phase locking to the global rhythm10.
For example, theta-frequency (4–8 Hz) oscillations and phase-locked discharge of neurons to theta waves are found in the hippocampus and some cortical areas, providing potential mechanisms to synchronize neuronal assemblies involved in complex processes and functions of the brain such as memory formation and neuroplasticity11.
Individual neurons represent the structural and functional units of the nervous system, with their spatiotemporally resolved activities holding the key to understanding the inner workings of the brain12,13.
Therefore, as the cornerstone of in vivo electrophysiology, this Review focuses on recording of single-unit spiking activity from individual neurons.
Single-unit spikes are filtered from neural signals in the high-frequency spectrum (>250 Hz). Importantly, extracellular electrodes provide information distinct from that of intracellular patch-clamp recordings from single neurons14: extracellular electrodes can record spiking from multiple nearby neurons (usually within a distance of ~140 μm)15.
When there is minimal overlap of signals from multiple neurons in the time trace, spikes recorded at the same electrode can be temporally resolved and assigned to individual neurons16; by contrast, when spiking activity from multiple neurons cannot be resolved for assignment to individual neurons, it is usually referred to as multi-unit activity (MUA)17–19.
The seemingly complicated matter of identifying each firing neuron is usually addressed by taking into account the difference between the relatively short duration of spikes and the longer interspike intervals (which reduces or eliminates signal overlap), and the distance dependence of recorded spike amplitudes20.
In addition, oversampling recording electrodes such as tetrodes21 and high-density Michigan-type silicon probes16 further facilitate spike separation and assignment to individual neurons. Thus, single-unit signals generated by different neurons can be temporally resolved and, based on the distinct amplitudes and waveforms of action potentials, the identity of each putative neuron discerned (Fig. 2a)16.

Conventional electrode technologies used since the invention of tungsten wire electrodes (Fig. 1)22–29 have made prominent contributions to neuroscience.
However, they are not fundamentally different from the primitive electrodes used by Galvani more than two centuries ago: they use a limited number of electrodes, establish a non-biological interface between rigid electrode materials and soft neural tissue and are limited in their ability to simultaneously interrogate and modulate neural activities.
Moreover, conventional neural recording electrode technologies now compete with other neurotechnologies — particularly calcium and voltage imaging using genetically encoded indicators30, and functional MRI (fMRI) of large-scale collective neural activities via neurovascular coupling31.
Calcium- and voltage-imaging techniques can record the activity of hundreds to thousands of neurons simultaneously over millimeter square areas32 and fMRI can interrogate brain activity from the same subject over long temporal spans.
These developments urge new breakthroughs in electrode technologies for neural recordings with greater spatiotemporal span, higher resolution and multiplexed functionality (Fig. 2b).
In this Review, we discuss advances in neural recording electrode technologies aimed at stable long-term recordings of single-neuron activity with high spatial integration, and multifunctional interrogation of the interfaced neural tissue.
We focus on how conventional neurotechnologies have been surpassed by many orders of magnitude in space and time, and how the latest advances point to future development of neural probes.
Other emergent neurotechnologies, such as genetically encoded calcium or voltage indicators and optogenetic control of neural activity, are reviewed elsewhere32–34 and are not discussed here.
Nonetheless, we offer insight on the potential to combine electrode technologies with optical methods for future neuroscience studies by discussing the strengths and limitations of electrode and optical techniques.
Conclusions and future directions
Only when we realize the immense disparity between the neural tissue and existing electrode technologies can we begin to develop next-generation neural probes to revolutionize neuroscientific research.
By imitating the intricate design and complex function of the brain, newly developed electrode technologies are beginning to look and behave like the neural networks we seek to probe, with an unprecedented large number of recording electrodes, neuron- and neural tissue-like designs to form a chronically stable recording interfaces at the single neuron level, and bidirectional flow of information via multifunctional electrical, optical and biochemical inputs.
We envisage that in future there will be a convergence of the greatest strengths of neurotechnologies discussed above, especially a focus on blurring their structural, mechanical and biochemical dissimilarities with the neurons and neural circuity that these probes seek to illuminate. Further technological developments in three major directions are needed to address existing limitations mentioned above to develop ‘ideal’ neural probes.
First, a large number of electrodes allowed by latest CMOS fabrication technologies should be incorporated to probe globally coordinated brain regions, whereas electrodes should be reduced in size to approach that of a single neuron soma or axon and functionalized with molecules to afford specific targeting of different cell types and neuron subtypes.
Second, electrodes should afford long-term stable recording and modulation of neural activity at the single-neuron level, with minimal-to-no perturbation of endogenous distribution of all cell types.
Third, functionalities including electrical recording, electrical or optical stimulation and pharmacological modulation should be incorporated into single probe designs, or in multiple probes for different functions (as sometimes all-in-one is less favourable than individual probes with single functions).
Such efforts will eventually afford studies of the brain in its native state and allow basic advances, such as understanding learning, memory storage and recall at the single-neuron level, and the changes that occur over the life spans of animals.
‘Ideal’ neural recording technologies will enable new neuroscientific studies of neural systems by interrogating the global coordination of multiple distant yet interconnected brain regions, tracking long-term neural circuit evolution over extended time periods and deconstructing the underlying neural circuits with multimodal modulation of brain activities140–142.