by Anqi Zhang
figures by Yunlong Zhao

Cyborgs may sound like science fiction, but the field of brain-machine interfaces has been around for quite some time. If you paid attention to Elon Musk’s brain implant announcement, they are aiming to test the system on a human patient by the end of 2020.

In reality, electricity forms the basis of these novel cyborg-like interfaces. Brain cells called neurons use electrical currents to function and signal to one another, and reading electrical activities from neurons is the foundation of many brain-machine interface applications, such as brain mapping and neural prosthetics. Brain mapping aims to understand the brain functions by decoding the communication between neurons, while neural prosthetics have been used to translate the brain activities into control signals for prosthetic devices, such as artificial limbs to assist people with paralysis. Each neuron is like a tiny biological battery that powers its own electrical pulses. For both types of brain-machine interface applications, most of the tools used today read brain activities by picking up signals that are leaked outside of the neurons. To achieve the most accurate functional readings and finest control of neural prosthetics, electronic devices need to gain direct access to the interior of neurons for intracellular recording.

The most widely used conventional method for intracellular recording is the patch-clamp electrode, although its micrometer scale tip causes irreversible damage to the cells and it can only record a few cells at a time. To address these issues, the Lieber group at Harvard University developed a scalable way to create large arrays of ‘hairpin’-like nanowire devices and used these to read intracellular electrical activities from multiple neurons at the same time.

Fabrication of nanowire device arrays

The silicon nanowires, with very high length-to-width ratio, are as flexible as cooked noodles and 6,000 times thinner than a human hair. To incorporate them into functional tools that read intracellular electrical messages, the team first patterned a silicon wafer with U-shaped trenches, and then ‘combed’ the nanowires over the trenches (Figure 1). In addition to removing tangles from the nanowire hair, the combing process deforms the nanowires to conform to the designed U-shapes of the trenches, thus forming an array of ‘hairpin’-like U-shaped nanoscale devices. The center of each U-shaped nanowire, which points upward from the wafer surface, is modified to act as a small recorder that can be inserted into neurons and cardiac cells for intracellular recording with signals comparable to the quality of those obtained with the gold-standard patch-clamp electrodes (Figure 2). Because the nanowire tips are so small and coated with a layer of molecules that mimic the cell membrane, they can be inserted into multiple cells in parallel repetitively without causing damage.

Figure 1: Fabrication of nanowire arrays. U-shaped trenches are patterned on a silicon wafer, followed by ‘combing’ of the nanowires. The combing process deforms the nanowires into the designed U-shapes.

Nanoscale curvature effect

Prior to this work, researchers have proposed the nanoscale curvature effect, which refers to the observation that the cell membrane curvature induced by tight interfacing with smaller nanostructures can better enhance internalization of the nanostructures into the cells. During the development of the nanowire cell probes, the team compared many different curvatures of the U-shaped trenches as well as different sizes of the recorders and found a strong correlation between probes with smaller curvature/recorder sizes and easier internalization and thus better intracellular recording quality, which is consistent with the nanoscale curvature effect (Figure 2).

Taking advantage of the parallel fabrication approach, this work explored different configurations of the device arrays; for example, having multiple nanowire devices on a single probe arm such that it is possible to read from multiple locations in a single cell, as well as tens of the probes that record signals from adjacent cells simultaneously to study signal propagation between cells. These modifications have the potential to make better tools for decoding the communication within and between complex neuron networks.

Figure 2: Nanoscale curvature effect. Smaller U-shaped curvature and smaller recorder sizes enhance internalization of the recorder into cells.

Promises and challenges

The human brain contains about 86 billion neurons, and they are wired into complex circuits to process information conveyed by electrical signals. To study the large number of neurons in the brain via intracellular recording, the conventional method of patch-clamp electrode is limited by its large micrometer tip size, and it can only read from a few neurons at a time. In this work, researchers achieved for the first time a major step towards tackling the general problem of integrating nanoscale building blocks into large controllable arrays, thereby addressing the long-standing challenge of scalable intracellular electrical recording with minimal invasiveness.

One challenge that remains, however, is the stability of recording. Because the nanowires are so flexible, once they are internalized, the cell membrane will slowly nudge them out within ten minutes. In future studies, the team is planning to exploit approaches to anchor nanowire tips inside the cells by modifying their surfaces with biomolecules that are ‘sticky’ to the internal filaments, or introducing nanoscale roughness so that the nanowires grab better to the membrane. In the longer term, these probe developments could ultimately drive advanced brain-machine interfaces with better precision and perhaps eventually bringing ‘cyborgs’ to reality.

Anqi Zhang is a Ph.D. student in the Lieber group in the Department of Chemistry & Chemical Biology at Harvard University.

Yunlong Zhao is a postdoc in the Lieber group in the Department of Chemistry & Chemical Biology at Harvard University.

For more information:

  • To read the original study from the Lieber group at Harvard University, check out this article
  • For more information on these nanowire arrays,  see this piece from The Harvard Gazette.

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