Tag Archives: neuronal activity

Transparent graphene electrode technology and complex brain imaging

Michael Berger has written a May 24, 2018 Nanowerk Spotlight article about some of the latest research on transparent graphene electrode technology and the brain (Note: A link has been removed),

In new work, scientists from the labs of Kuzum [Duygu Kuzum, an Assistant Professor of Electrical and Computer Engineering at the University of California, San Diego {UCSD}] and Anna Devor report a transparent graphene microelectrode neural implant that eliminates light-induced artifacts to enable crosstalk-free integration of 2-photon microscopy, optogenetic stimulation, and cortical recordings in the same in vivo experiment. The new class of transparent brain implant is based on monolayer graphene. It offers a practical pathway to investigate neuronal activity over multiple spatial scales extending from single neurons to large neuronal populations.

Conventional metal-based microelectrodes cannot be used for simultaneous measurements of multiple optical and electrical parameters, which are essential for comprehensive investigation of brain function across spatio-temporal scales. Since they are opaque, they block the field of view of the microscopes and generate optical shadows impeding imaging.

More importantly, they cause light induced artifacts in electrical recordings, which can significantly interfere with neural signals. Transparent graphene electrode technology presented in this paper addresses these problems and allow seamless and crosstalk-free integration of optical and electrical sensing and manipulation technologies.

In their work, the scientists demonstrate that by careful design of key steps in the fabrication process for transparent graphene electrodes, the light-induced artifact problem can be mitigated and virtually artifact-free local field potential (LFP) recordings can be achieved within operating light intensities.

“Optical transparency of graphene enables seamless integration of imaging, optogenetic stimulation and electrical recording of brain activity in the same experiment with animal models,” Kuzum explains. “Different from conventional implants based on metal electrodes, graphene-based electrodes do not generate any electrical artifacts upon interacting with light used for imaging or optogenetics. That enables crosstalk free integration of three modalities: imaging, stimulation and recording to investigate brain activity over multiple spatial scales extending from single neurons to large populations of neurons in the same experiment.”

The team’s new fabrication process avoids any crack formation in the transfer process, resulting in a 95-100% yield for the electrode arrays. This fabrication quality is important for expanding this technology to high-density large area transparent arrays to monitor brain-scale cortical activity in large animal models or humans.

“Our technology is also well-suited for neurovascular and neurometabolic studies, providing a ‘gold standard’ neuronal correlate for optical measurements of vascular, hemodynamic, and metabolic activity,” Kuzum points out. “It will find application in multiple areas, advancing our understanding of how microscopic neural activity at the cellular scale translates into macroscopic activity of large neuron populations.”

“Combining optical techniques with electrical recordings using graphene electrodes will allow to connect the large body of neuroscience knowledge obtained from animal models to human studies mainly relying on electrophysiological recordings of brain-scale activity,” she adds.

Next steps for the team involve employing this technology to investigate coupling and information transfer between different brain regions.

This work is part of the US BRAIN (Brain Research through Advancing Innovative Neurotechnologies) initiative and there’s more than one team working with transparent graphene electrodes. John Hewitt in an Oct. 21, 2014 posting on ExtremeTech describes two other teams’ work (Note: Links have been removed),

The solution [to the problems with metal electrodes], now emerging from multiple labs throughout the universe is to build flexible, transparent electrode arrays from graphene. Two studies in the latest issue of Nature Communications, one from the University of Wisconsin-Madison and the other from Penn [University of Pennsylvania], describe how to build these devices.

The University of Wisconsin researchers are either a little bit smarter or just a little bit richer, because they published their work open access. It’s a no-brainer then that we will focus on their methods first, and also in more detail. To make the arrays, these guys first deposited the parylene (polymer) substrate on a silicon wafer, metalized it with gold, and then patterned it with an electron beam to create small contact pads. The magic was to then apply four stacked single-atom-thick graphene layers using a wet transfer technique. These layers were then protected with a silicon dioxide layer, another parylene layer, and finally molded into brain signal recording goodness with reactive ion etching.

PennTransparentelectrodeThe researchers went with four graphene layers because that provided optimal mechanical integrity and conductivity while maintaining sufficient transparency. They tested the device in opto-enhanced mice whose neurons expressed proteins that react to blue light. When they hit the neurons with a laser fired in through the implant, the protein channels opened and fired the cell beneath. The masterstroke that remained was then to successfully record the electrical signals from this firing, sit back, and wait for the Nobel prize office to call.

The Penn State group [Note: Every reearcher mentioned in the paper Hewitt linked to is from the University of Pennsylvania] in the  used a similar 16-spot electrode array (pictured above right), and proceeded — we presume — in much the same fashion. Their angle was to perform high-resolution optical imaging, in particular calcium imaging, right out through the transparent electrode arrays which simultaneously recorded in high-temporal-resolution signals. They did this in slices of the hippocampus where they could bring to bear the complex and multifarious hardware needed to perform confocal and two-photon microscopy. These latter techniques provide a boost in spatial resolution by zeroing in over narrow planes inside the specimen, and limiting the background by the requirement of two photons to generate an optical signal. We should mention that there are voltage sensitive dyes available, in addition to standard calcium dyes, which can almost record the fastest single spikes, but electrical recording still reigns supreme for speed.

What a mouse looks like with an optogenetics system plugged in

What a mouse looks like with an optogenetics system plugged in

One concern of both groups in making these kinds of simultaneous electro-optic measurements was the generation of light-induced artifacts in the electrical recordings. This potential complication, called the Becqueral photovoltaic effect, has been known to exist since it was first demonstrated back in 1839. When light hits a conventional metal electrode, a photoelectrochemical (or more simply, a photovoltaic) effect occurs. If present in these recordings, the different signals could be highly disambiguatable. The Penn researchers reported that they saw no significant artifact, while the Wisconsin researchers saw some small effects with their device. In particular, when compared with platinum electrodes put into the opposite side cortical hemisphere, the Wisconsin researchers found that the artifact from graphene was similar to that obtained from platinum electrodes.

Here’s a link to and a citation for the latest research from UCSD,

Deep 2-photon imaging and artifact-free optogenetics through transparent graphene microelectrode arrays by Martin Thunemann, Yichen Lu, Xin Liu, Kıvılcım Kılıç, Michèle Desjardins, Matthieu Vandenberghe, Sanaz Sadegh, Payam A. Saisan, Qun Cheng, Kimberly L. Weldy, Hongming Lyu, Srdjan Djurovic, Ole A. Andreassen, Anders M. Dale, Anna Devor, & Duygu Kuzum. Nature Communicationsvolume 9, Article number: 2035 (2018) doi:10.1038/s41467-018-04457-5 Published: 23 May 2018

This paper is open access.

You can find out more about the US BRAIN initiative here and if you’re curious, you can find out more about the project at UCSD here. Duygu Kuzum (now at UCSD) was at  the University of Pennsylvania in 2014 and participated in the work mentioned in Hewitt’s 2014 posting.

Bidirectional prosthetic-brain communication with light?

The possibility of not only being able to make a prosthetic that allows a tetraplegic to grab a coffee but to feel that coffee  cup with their ‘hand’ is one step closer to reality according to a Feb. 22, 2017 news item on ScienceDaily,

Since the early seventies, scientists have been developing brain-machine interfaces; the main application being the use of neural prosthesis in paralyzed patients or amputees. A prosthetic limb directly controlled by brain activity can partially recover the lost motor function. This is achieved by decoding neuronal activity recorded with electrodes and translating it into robotic movements. Such systems however have limited precision due to the absence of sensory feedback from the artificial limb. Neuroscientists at the University of Geneva (UNIGE), Switzerland, asked whether it was possible to transmit this missing sensation back to the brain by stimulating neural activity in the cortex. They discovered that not only was it possible to create an artificial sensation of neuroprosthetic movements, but that the underlying learning process occurs very rapidly. These findings, published in the scientific journal Neuron, were obtained by resorting to modern imaging and optical stimulation tools, offering an innovative alternative to the classical electrode approach.

A Feb. 22, 2017 Université de Genève press release on EurekAlert, which originated the news item, provides more detail,

Motor function is at the heart of all behavior and allows us to interact with the world. Therefore, replacing a lost limb with a robotic prosthesis is the subject of much research, yet successful outcomes are rare. Why is that? Until this moment, brain-machine interfaces are operated by relying largely on visual perception: the robotic arm is controlled by looking at it. The direct flow of information between the brain and the machine remains thus unidirectional. However, movement perception is not only based on vision but mostly on proprioception, the sensation of where the limb is located in space. “We have therefore asked whether it was possible to establish a bidirectional communication in a brain-machine interface: to simultaneously read out neural activity, translate it into prosthetic movement and reinject sensory feedback of this movement back in the brain”, explains Daniel Huber, professor in the Department of Basic Neurosciences of the Faculty of Medicine at UNIGE.

Providing artificial sensations of prosthetic movements

In contrast to invasive approaches using electrodes, Daniel Huber’s team specializes in optical techniques for imaging and stimulating brain activity. Using a method called two-photon microscopy, they routinely measure the activity of hundreds of neurons with single cell resolution. “We wanted to test whether mice could learn to control a neural prosthesis by relying uniquely on an artificial sensory feedback signal”, explains Mario Prsa, researcher at UNIGE and the first author of the study. “We imaged neural activity in the motor cortex. When the mouse activated a specific neuron, the one chosen for neuroprosthetic control, we simultaneously applied stimulation proportional to this activity to the sensory cortex using blue light”. Indeed, neurons of the sensory cortex were rendered photosensitive to this light, allowing them to be activated by a series of optical flashes and thus integrate the artificial sensory feedback signal. The mouse was rewarded upon every above-threshold activation, and 20 minutes later, once the association learned, the rodent was able to more frequently generate the correct neuronal activity.

This means that the artificial sensation was not only perceived, but that it was successfully integrated as a feedback of the prosthetic movement. In this manner, the brain-machine interface functions bidirectionally. The Geneva researchers think that the reason why this fabricated sensation is so rapidly assimilated is because it most likely taps into very basic brain functions. Feeling the position of our limbs occurs automatically, without much thought and probably reflects fundamental neural circuit mechanisms. This type of bidirectional interface might allow in the future more precisely displacing robotic arms, feeling touched objects or perceiving the necessary force to grasp them.

At present, the neuroscientists at UNIGE are examining how to produce a more efficient sensory feedback. They are currently capable of doing it for a single movement, but is it also possible to provide multiple feedback channels in parallel? This research sets the groundwork for developing a new generation of more precise, bidirectional neural prostheses.

Towards better understanding the neural mechanisms of neuroprosthetic control

By resorting to modern imaging tools, hundreds of neurons in the surrounding area could also be observed as the mouse learned the neuroprosthetic task. “We know that millions of neural connections exist. However, we discovered that the animal activated only the one neuron chosen for controlling the prosthetic action, and did not recruit any of the neighbouring neurons”, adds Daniel Huber. “This is a very interesting finding since it reveals that the brain can home in on and specifically control the activity of just one single neuron”. Researchers can potentially exploit this knowledge to not only develop more stable and precise decoding techniques, but also gain a better understanding of most basic neural circuit functions. It remains to be discovered what mechanisms are involved in routing signals to the uniquely activated neuron.

Caption: A novel optical brain-machine interface allows bidirectional communication with the brain. While a robotic arm is controlled by neuronal activity recorded with optical imaging (red laser), the position of the arm is fed back to the brain via optical microstimulation (blue laser). Credit: © Daniel Huber, UNIGE

Here’s a link to and a citation for the paper,

Rapid Integration of Artificial Sensory Feedback during Operant Conditioning of Motor Cortex Neurons by Mario Prsa, Gregorio L. Galiñanes, Daniel Huber. Neuron Volume 93, Issue 4, p929–939.e6, 22 February 2017 DOI: http://dx.doi.org/10.1016/j.neuron.2017.01.023 Open access funded by European Research Council

This paper is open access.