Webinar Recording

posted Jun 17, 2020, 12:24 PM by Bionic Lab   [ updated Jun 17, 2020, 12:24 PM ]

New Research Opportunities at the Brain-Computer Interface: BRAIN Technology Physiology and Non-neuronal Neurocomputation

Using electrophysiology and engineered neurotechnologies, we track and interrogate neural circuit functions. By utilizing multi-channel electrophysiological arrays and electrochemical assays together with computational signal processing, we map out how neural signals are processed. We combine this method with in vivo multiphoton imaging to tease apart the spatiotemporal dynamics of neurons (quiescent and silenced), microglia, astrocytes, oligodendrocytes, oligodendrocyte progenitor cells, and pericytes. This enables unprecedented ability to understand the electrical activity of neurons in the context of simultaneous non-neuronal cell activity visualization, which cannot be monitored with electrophysiological technologies.

 More recently, we have pivoted to exploring gaps in knowledge regarding electrical stimulation-based activation or inactivation of neural elements over time, which have limited the field’s ability to adequately interpret evoked downstream responses or fine‐tune stimulation parameters to focus on desired effects. Here, we show frequency–dependent differences in spatial and temporal somatic responses during continuous stimulation. In addition, we use genetically encoded activity-dependent fluorescent proteins to track molecular-level activity in specific cell types, such as genetically encoded calcium indicators and glutamate sensors. Our results elucidate conflicting results from prior studies reporting either dense spherical activation of somas biased toward those near the electrode, or sparse activation of somas at a distance via axons near the electrode; our findings indicate that the neural element specific temporal response local to the stimulating electrode changes as a function of applied charge density and frequency.

Combined, these results reveal a complex environment around the device-tissue interface, and highlight the need for more comprehensive basic science research at the neuroelectronic interface. By developing a better fundamental science understanding at this brain-computer interface, we show that it is possible to intelligently design novel BRAIN Initiative technologies that further enable new modalities for interfacing with the nervous system.

Fall Presentations (BMES and SfN)

posted Oct 13, 2019, 5:53 PM by Bionic Lab   [ updated Oct 13, 2019, 5:54 PM ]

Poster at BMES:
Saturday, October 19, 2019
9:30 AM - 1:00 PM Exhibit Hall DE

P-SAT-641Inhibition of Na+/H+ Exchanger Modulates Microglia Activation Following Microelectrode Implantation   M. Dubaniewicz, J. Eles, S. Wellman, F. Cambi, D. Sun, T. Kozai.  

We’ve got 1 talk and 4 posters at SfN this year!

October 21, 2019, 8:00 AM 
314.03. Oligodendrocyte and myelin loss impairs recording performance of neural interfaces in cuprizone-induced model of demyelination 
*S. M. WELLMAN et al
Session: Poster: 314 - Motor Cortex and Motor Learning 

October 21, 2019, 1:00 PM 
358.03. Modulating the amplitude of intracortical microstimulation reveals distinct recruitment mechanisms of local and distant neurons as seen by in vivo two-photon microscopy 
Session: Nanosymposium: 358 - Tactile Coding in the Cortex 

October 22, 2019, 8:00 AM 
468.18. In vivo spatiotemporal dynamics of astrocytes activity following neural electrode implantation 
*S. P. SAVYA et al 
Session: Poster: 468 - Role of Astrocyte Dysfunction in Disease States 

October 22, 2019, 8:00 AM 
479.14. In vivo spatiotemporal patterns of oligodendrocyte and myelin damage at the neural electrode interface 
*K. CHEN et al
Session: Poster: 479 - Traumatic Brain Injury: Mechanisms, Biomarkers, and Recovery 

October 23, 2019, 1:00 PM 
797.08. Electrical stimulation waveform modulates spatial and temporal activation of cortical neurons in vivo 
*K. C. STIEGER et al
Session: Poster: 797 - Electrical Methods to Modulate Neural Activity II 

BRAIN Initiative 2.0 RFI due May 15th

posted Apr 30, 2019, 2:26 PM by Bionic Lab   [ updated May 2, 2019, 6:13 AM ]

What you need to know about Phase 2 BRAIN RFI (Request for Information).

The BRAIN Initiative was a 2013 White House initiative to support better understanding the brain. The Budget for the BRAIN Initiative has also expanded with recent bipartisan legislation securing funding to at least 2026 with an operational budget greater than NIBIB. There were some politics involved, but ultimately a decision was made to use the money in phase 1 to largely support brain related proposals that struggled in traditional mechanisms and traditional review panels. These ended up being grants that were engineering based (design driven proposals) as opposed to classical neuroscience hypothesis driven proposals that are funded through traditional mechanisms under NIBIB, NINDS, NIMH, NIA, NIE, etc (eg. parent R01s)

BRAIN Initiative Phase 1 is closing to an end, they the committee/working group is trying to pick a direction for Phase 2. There is considerable internal pushback against technology development and a push for funding “circuit function” research (ie research that is already funded through traditional mechanisms). However, thanks to your feedback during the first RFI, the ACD has recommended continued funding for neurotechnologies summarized here:

That said, there remains a major gap between where we stand and supporting "Technology Development", which is not addressed under current BRAIN Initiative Mechanisms and not acknowledged in the current update. For example, there is very little "Basic Science of Interface Biology" research to help guide/inform technology development.


1)      Neural Interface research is not represented on the working group panel nor the leadership of the BRAIN Initiative. The major representation is made up of neuroscientists despite “The overarching vision of the BRAIN Initiative is best captured by Goal #7 (New Technology)”

2)      Effective increases to pay lines: by removing support for grants that struggle in normal review/study sections (ie technology development), it frees up money. Then, by supporting BRAIN grants that already have standard mechanisms (circuit function parent R01s) through the BRAIN Initiative, it frees up money in the traditional mechanisms (ie parent R01s). This effectively raises the pay line for standard circuit function grants.

Lessons from 2017 GSI

The NIH announced the “Grant Support Index (GSI)” on May 2, 2017 to support new investigators (average age of 1st R01 has shifted from 35 (1980) to 47 (2017)). While I’ve been fortunate to receive my R01 at 32, this is a huge issue. The GSI was designed to help decrease that first R01 age, by capping funding to each investigator at a maximum of 3 R01s. However, the NIH received overwhelming feedback that led to abandoning the GSI on June 17, 2017. This is because graduate students, postdocs, and assistant professors that would benefit from it never responded to RFI/request for feedback, where as STRONG and overwhelming feedback was provided by a few directors and PIs with 5+ R01 equivalents.

Lesson: This is your opportunity to have your voices heard. You don’t have to be a PI or a faculty. You can be a postdoc, student, industry, an artist, or not in the USA. You just need to submit your opinions by MAY 15.

Here are some talking points that I think are important and within the scope of the BRAIN 2025 roadmap and new priorities from the ACD, but are overlooked missing in current RFAs and funding opportunities:

Acknowledge and Agree with the ACD

·       The importance of continued neurotechnology development

·       Power of integrated technologies

·       Support of neuronal and non-neuronal research on neural activity and neurotechnologies

Research Priorities

  • What is still lacking is the “basic science” research for neurotechnology. The use of technology causes very unique biological changes (whether reactive tissue response or plastic changes). While neurological diseases and brain injuries have robust basic science physiology research that guide treatments, there are very few mechanisms supporting the basic science physiology and neurobiology research at the neurotechnology-nervous system interface. An equal emphasis is necessary to research neural interface material science at the level of neurodegenerative diseases. Understanding these problems will be critical in strategically guiding next-generation technology development in a data driven manner. This is particularly the most important “Next step” of advancing “integrative efforts in BRAIN 2.0”
“We cannot solve our problems with the same thinking we used when we created them.” – Albert Einstein
“It isn’t that they cannot find the solution. It is that they cannot see the problem.” – G.K Chesterton
“If you are unable to understand the cause of a problem, it is impossible to solve it.” – Naoto Kan
“We fail more often because we solve the wrong problem than because we get the wrong solution to the right problem.” – Russell L. Ackoff
“We cannot solve our problems with the same thinking we used when we created them.” – Albert Einstein
“It isn’t that they cannot find the solution. It is that they cannot see the problem.” – G.K Chesterton
“If you are unable to understand the cause of a problem, it is impossible to solve it.” – Naoto Kan
“We fail more often because we solve the wrong problem than because we get the wrong solution to the right problem.” – Russell L. Ackoff
  • Supporting Technology Failure Analysis. In industry, the first step to technology development is to comprehensively and robustly study the modes and distribution of failures that can occur with the technology. While normally, these are risks that industrial partners take on, much of the technology is immature or have too long of a R&D cycle for commercial investment into these analyses. Therefore, there is a need for government support to facilitate failure analysis (biological and technological) to better inform and guide the development of future technologies.
  • Packaging: Failure analysis will likely reveal that packaging and usability are key aspects of device failure (failure to adopt and failure to perform) in technology development. Again, traditionally, these are R&D that commercial partners typically shoulder, but the R&D cycle for these technologies are too long for commercial investment. Their development needs to be supported by institutional partnership. This includes support at review panel and study section level to fund "un-sexy" packaging development which is critical to the technology dissemination pathway (and getting away from the standard R01 review and funding model)
  • Non-traditional RFA structure and Study Section/Review Panels: Much of the current inefficiencies in Brain technology in the US is due to the structure of review and funding. Even when RFAs are specifically written to support projects such as neuropixel and Grégoire Courtine's work, it is the review panels that tear into these as unfundable projects. For the US to take back the leadership in technology development, perhaps it is important to rethink the NIH funding pipeline for technology R&D (not just the RFA but also the review process). Not just treating these RFAs as standard R01s.
  • Along these lines, there are notable deficiencies in some BRAIN Initiative review panels or committees with respect to individuals that have both expertise at the interface of Technology and Neurobiology.
  • Biology and Biophysics of…[neurotechnology] are currently being reviewed by study sections that predominantly include people who are “non-biologists” and “non-biophysicist” which negatively impact these RFA mechanisms.
  • The above analysis are necessary in order to truly understand and apply these technologies for circuit function research and eliminate artifacts and false assumptions from contaminating the interpretation of the data collected using new technologies.
  • Neurobiology of Neurotechnology (Neural Interface Cybernetics: ie the science of communications and automatic control systems in both machines and living things): So much focus is on building “new” technology, there is very little effort to focus on the “science that governs functional communication between biology and interface”. This goes beyond biocompatibility and tissue scarring. How does biology govern communication with the technology and how does technology influence neural activity?
  • Too much emphasis on channel count and not enough on intelligent design: there are no RFAs currently available to study what makes a good interface and what makes a bad interface. Instead, current focus is on “increasing channel count”. But maximizing channel count likely means a greater “observer principle” alteration of the natural circuit. A better approach would be evaluate the science of the technology interface to inform better design and optimization of different design parameters. See
  • Technology will always be obsolete, but the knowledge generated to guide technology development will be immortal. Therefore, there should be emphasis on understanding the biology of neural interfaces. see
  • Cross-training: The importance of understanding both the language of neuroscience and neural engineering is emphasized elsewhere. It also explains why you can’t “just collaborate, you do the engineering and I’ll do the science” (closed-loop engineering):
  • Observer Principle: Despite all the tools that are being developed, we still have very little idea how using these tools alter natural circuitry function. How can you use these tools to study circuit function if you don't understand the "side effects" on native neural circuits from using these tools? (eg, electrodes cause silencing of nearby neuron (alive but not firing properly) because oxygen and nutrient delivery is damaged. This means that instead of increasing channel count for next generation electrodes, but we should be focusing on technology that helps repair the neurovascular unit around implants. See
  • Assumptions: Many neurotechnologies are based on assumption. There is immerging research that suggests or proves that some of these assumptions are wrong (eg NeuN labeled neurons around electrodes are not silenced.). Instead, there should be RFAs that are designed to tease apart and test these assumptions.
  • Standard Technology: There is no emphasis on studying how standard technology influences neural circuit function. How can we evaluate if “new” technology from BRAIN is better or not if there are no efforts to evaluate these impacts on neural circuits with standard technologies?
  • Utilizing technology to understand neurodegeneration and regeneration/wound healing is not widely explored, especially their influence on neural (and gliovascular) circuit function.
  • Disease/Degeneration: Many degenerative diseases and brain injuries share activation of similar pathways. The key differences are where and what triggers onset. What makes these degenerative disease hard to study is that their onset is difficult to identify and the focal point of activation is hard to pinpoint (some have multiple focal initiation points). With technologies, the time and location is precisely known and you get a bonus of having a sensor or effector at the epicenter of the trigger injury. This not only informs technology development, but also understanding disease progression and potential platform for treatments.
  • Without underlying basic science to understand how to regulate “non-neuronal cells” and how “non-neuronal cells” regulate neural circuits, how can we create gliotechnologies and neurovasculartechnologies?


Dissemination and Training

  • Cross-training: The importance of understanding both the language of neuroscience and neural engineering is emphasized elsewhere. It also explains why you can’t “just collaborate, you do the engineering and I’ll do the science” (closed-loop engineering):
  • While ACD has shown appreciation for integrated approach, technology, and training. There is considerable personal risk and inherently limited financial opportunity for trainees to pursue integrated training in neuroscience and neurotechnology. NIH should carefully consider what these challenges are and how NIH can support and de-risk integrated training for the individual. Otherwise, it will remain a pipe dream that would be "nice to have someday".



  • Representation: No advocates for technology interface nor are there any individuals that appreciate the neural interface challenge serve on the working group. One technologist on the working group has, on multiple occasions, stated in talks, “I’m not really sure what happens to the brain [when this is implanted]. I’m not a biologist, it’s not important to me.”

Topics that do not do well in traditional NIH mechanisms

1)    1. Technology development

2)    2. Neural Interface Science/Neural Interface Biology: exploring the biological mechanisms that govern Neural Technology Interfaces at a level equivalent to neurodegenerative diseases, Stroke or TBI.

3)    3. Regulatory Neurotechnology science

a.     What makes technology safe

b.     What makes technology effective

c.     We don’t even know which experiments to carry out to evaluate the above questions. We need research to determine what experiments and metric standards inform safety and effectiveness at both pre-clinical and clinical trial levels

See you at SfN

posted Nov 2, 2018, 10:11 AM by Bionic Lab   [ updated Nov 2, 2018, 10:12 AM ]

November 5, 2018, 8:00 AM
271.09. Calcium activation of frequency dependent, phasic, localized, and dense population of cortical neurons by continuous electrical stimulation
1Bioengineering, 2Biomed. Engin., 3Radiology, Univ. of Pittsburgh, Pittsburgh, PA; 4Neurologic Surgery, Mayo Clin., Rochester, MN
Session: Nanosymposium: 271 - Brain-Machine Interface

November 7, 2018, 8:00 AM

658.12. A time course study of melatonin's effect on microglia responses to neural implants as revealed by two-photon imaging

Univ. of Pittsburgh, Oakland, PA
Session: Poster: 658 - Neurotoxicity, Inflammation, and Neuroprotection: Neuroinflammation: Microglia
November 7, 2018, 1:00 PM
769.01. Microelectrode implantation induces pericyte reactivity and vascular bed reorganization as revealed by two-photon microscopy
Dept. of Bioengineering, Univ. of Pittsburgh, Pittsburgh, PA
Session: Poster: 769 - Histologic Responses to Electrode Insertion

November 7, 2018, 1:00 PM
736.23. Effect of APOE lipoproteins on microglial response to intracranial infusion of Aβ - in vivo two-photon imaging and transcriptomic analysis
1Envrn. & Occup. Hlth., 2Bioengineering, Univ. of Pittsburgh, Pittsburgh, PA
Session: Poster: 736 - Alzheimer's Disease and Other Dementias: Neuroinflammation

Upcoming Gordon Conference on Neuroelectronic Interface

posted Feb 8, 2018, 9:47 AM by Bionic Lab   [ updated Feb 8, 2018, 9:47 AM ]

PITTSBURGH (February 6, 2018) ... Takashi Kozai, assistant professor of bioengineering at the University of Pittsburgh Swanson School of Engineering, will act as co-vice chair at the inaugural Gordon Research Conference on Neuroelectronic Interfaces. The meeting will take place March 25-30, 2018 in Galveston, Texas.

Neuroelectronic interfaces -commonly known as brain-machine (or brain-computer) interfaces- create a direct communication line from the central nervous system to the outside world. This connection allows scientists to research ways to rehabilitate those with paralysis, other forms of motor dysfunction, or limb loss.

“One major limitation for practical clinical translation, despite nearly 60 years of chronic neural interface research, is that there remains a poor understanding of the complex biological and material failure modes across all classes of microelectrode arrays,” Kozai explains. “Among several classes of multi-modal problems encountered, the strong foreign body response, scar tissue formation, and implant material breakdown over time are critical obstacles. These issues ultimately lead to an electrical decoupling of implanted devices from the brain and a loss of signal.” 

“Our inaugural Gordon Research Conference (GRC) on Neuroelectronic Interfaces will challenge the international field to turn back to the drawing board of basic materials research armed with emerging basic neurosciences knowledge,” Kozai says.

The event will bring together a multi-disciplinary team of leading experts in cellular neuroscience, brain pathology, neuro-technology and materials science to discuss and eventually solve these challenges in order to achieve a chronically useful and reliable neural interface.

Kozai leads the Bio-Integrating Optoelectric Neural Interface & Cybernetics Lab (B.I.O.N.I.C. Lab) in the Swanson School of Engineering. The lab takes a multidisciplinary approach to better understand interactions at micro-scale neural interfaces and develop next-generation neural technologies that reduce or reverse negative tissue interactions.

“As both scientific knowledge and technological advances progress, we’re finding that many of the assumptions that were made in the field are limited in scope, or incomplete,” Kozai says. “As a result, we see more and more of these dogmas fall apart as we push the limits of engineering.”

As part of the five-day event, Kozai will lead a discussion on “Biomechanics of the Device-Tissue Interface.” The program also includes Xinyan Tracy Cui, William Kepler Whiteford Professor of Bioengineering at Pitt, who will present a talk titled “Biomimetic Strategy for Seamless Neural Electrode-Tissue Integration.”

“The Gordon Research Conference is unlike most other conferences in that you get to spend a week sitting shoulder to shoulder with the leaders in the field to discuss new ideas and emerging research and development,” Kozai says. “We’ve been fortunate enough to bring together an all-star list of the world’s expert scientists and engineers.”

Applications for this meeting must be submitted by February 25, 2018.


See the research being done at Pitt’s Human Neural Prosthetics Program:


Contact: Leah Russell

re:posted from:

Nature BME Highlights

posted Feb 8, 2018, 9:45 AM by Bionic Lab   [ updated Feb 8, 2018, 9:45 AM ]

PITTSBURGH (January 8, 2018) … Implanted devices send targeted electrical stimulation to the nervous system to interfere with abnormal brain activity, and it is commonly assumed that neurons are the only important brain cells that need to be stimulated by these devices. However, research published in Nature Biomedical Engineering reveals that it may also be important to target the supportive glial cells surrounding the neurons.
The collaboration was led by Erin Purcell, assistant professor of biomedical engineering at Michigan State University; Joseph W. Salatino, Purcell’s graduate student researcher; Kip A. Ludwig, associate director of technology at Mayo Clinic; and Takashi Kozai, assistant professor of bioengineering at the University of Pittsburgh’s Swanson School of Engineering.
“Glial cells are the most abundant in the central nervous system and critical to the function of the neuronal network,” Kozai says. “The most obvious function of glial cells has been related to their role in forming scar tissue to prevent the spread of injury and neuronal degeneration, but so much about their role in the brain is unknown.”
The study, “Glial responses to implanted electrodes in the brain” (doi:10.1038/s41551-017-0154-1)  suggests that these glial cells are more functional than previously thought. “From providing growth factor support and ensuring proper oxygen and nutrient delivery to the brain to trimming of obsolete synapses and recycling waste products, recent findings show that glial cells do much more to ensure brain activity is optimized,” Kozai says.
The slow, dim signals of glial cells are much more difficult to detect than the vibrant electrical activity of neurons. New advancements in technology allows researchers like Kozai to detect the subtleties of glial cell activity, and these observations are shedding new light on current issues plaguing implant devices and the treatment of neurological disease.
Kozai explains, “Dysfunction in glial cells has been implicated as a cause and/or major contributor to an increasing number of neurological and developmental diseases. Therefore, it stands to reason that targeting these glial cells (in lieu of or in combination with neurons) may dramatically improve current treatments.”
Kozai leads the Bionic Lab at Pitt, where researchers are investigating the biological tissue response to implantable technologies. Although there have been many advancements in neural implant technology in recent years, their underlying effects and reasons for their failure still puzzle scientists. By using advanced microscopy techniques, researchers can create more detailed neurological maps and imaging.
“By combining in vivo multiphoton microscopy and in vivo electrophysiology, our lab is better able to visualize how cells move and change over time in the living brain and explain how changes in these glial cells alter the visually evoked neural network activity,” says Kozai. “Using this approach to better understand these cells can help guide implant design and success.”
Kozai’s lab is currently working with Franca Cambi, professor of neurology at Pitt, on a project to understand the role of another type of glial cell on brain injury and neuronal activity. “Oligodendrocyte Progenitor Cells,” or OPCs, are progenitor cells—similar to stem cells—that have the capacity to differentiate during tissue repair.
“Although OPCs have been understudied in brain-computer interface, they form direct synapses with neurons and are critical to their repair,” explains Kozai. “As progenitor cells, they have the capacity to differentiate into a variety of cells, including neurons. The technology is advancing to the point in which we can have a much better understanding of how the brain works comprehensively, rather than just focusing on neurons because their electrical signals make them appear brighter when imaging the brain.”

re-posted from:

Society for Neuroscience

posted Nov 9, 2017, 6:32 PM by Bionic Lab   [ updated Nov 9, 2017, 6:33 PM ]

Come see our posters (including a dynamic poster) Tuesday November 14, 2017, 1:00 - 5:00 PM

595.14 / DP10/KK17 - Multi-scale, multi-modal analysis of the brain tissue-implant interface reveals new depths of the biological research field at the neuroelectronic interface [LINK]

595.03 / KK6 - In vivo 2-photon microscopy mapping of acute mechanical damage due to neural electrode array implantation [LINK]

595.07 / KK10 - CLARITY based 3D histology assessment of neural electrodes with antifouling coating implanted in mouse cortex [LINK]

Multimodal Microelectrode Failure Analysis Reveals Complex Relationship at the Neural Interface @ ECS

posted Oct 2, 2017, 2:58 AM by Bionic Lab   [ updated Oct 2, 2017, 2:59 AM ]

   Penetrating microelectrode arrays that can record extracellular action potentials from small, targeted groups of neurons are critical for basic neuroscience research and emerging clinical applications. However, these electrode devices suffer from reliability and variability issues which impact their performance on the order of months to years. The failure mechanisms of these electrodes are understood to be a complex combination of the biotic and abiotic failure modes.

The breaching of the blood–brain barrier (BBB) to insert devices triggers a cascade of biochemical pathways resulting in complex molecular and cellular responses to implanted devices. Molecular and cellular changes in the microenvironment surrounding an implant include the introduction of mechanical strain, BBB leakage, activation of glial cells, loss of perfusion, secondary metabolic injury, and neuronal degeneration. The resulting inflammation is a key hypothesized cause of neural recording failure. However, previous attempt so directly correlate recording performance, to impedance, and to histological outcomes have led counter-intuitive and sometimes conflicting outcomes.

One reason is that many neurons remain quiescent during anesthetized or resting-state conditions. We previously demonstrated this by visually evoked stimulation paradigms of the contralateral eye in order to evaluate chronic recording performance of linear silicon electrode in the primary visual cortex. Additional, multiphoton analysis using GCaMP6 transgenic animals further confirmed these results. More recently, there has been a growing interesting recording during awake free-roaming conditions in the primary motor cortex in order to avoid resting-state related quiescent activity. However, this in turn leads to increases in Lenz’s Law related artefacts that have the same time constants and waveform shapes as action potentials in rodents, but not NHP. While behaviorally training animals to remain immobile could improve outcomes, it also introduces the potential for Experimenter Expectancy Effect bias on the outcomes.

The visual stimulation paradigm enable the use of current source density analysis to electrophysiologically identify Layer II/III, IV, and V in the cortex. This, in turn, allowed correlation of electrophysiological layers to the histological layers based on section depth and the differences in neural morphology and density. Our findings from electrophysiology, impedance spectroscopy, and post-mortem histology demonstrate a very poor relationship between histology and impedance to electrophysiology. For example, tissue with low-levels of glial encapsulation, healthy neuronal proximity, and low impedance can still have poor recording performance, even with neural activity is behaviorally driven.

Even when histology confirms a perfect tissue interface, cracking or delamination of insulation on the microelectrode has been linked to a drop in impedance and a loss of recording failure. In contrast, cracking of the electrical trace and delamination of the recording site has been linked to recording failure through a jump in electrical impedance. As such, several modes of mechanical failure of chronically implanted planar silicon electrodes were found that result in degradation and/or loss of recording. Our findings highlight the importance of strains and material properties of various subcomponents within an electrode array and the poor reliability of determining electrode viability through electrochemical impedance spectroscopy.

Interestingly, we discovered in a number of situations that even with good neural density, uncompromised electrode material, and good impedances, recording performance can sometimes completely degrade. New multimodal analysis demonstrates the importance of capturing dynamic information, such as with in vivo multiphoton study, and that the presence of neurons does not guarantee functional neural activity over time. We further demonstrate that the foundation of assumptions and simplification made in the field for neural interface research are not true or incomplete. To solve the longstanding chronic neural interface problem, we need to first understand the complexity of the problem.

  • © 2017 ECS - The Electrochemical Society

ACS Chemical Neuroscience: Most Cited Papers from 2015

posted Aug 22, 2017, 11:57 AM by Bionic Lab   [ updated Aug 22, 2017, 11:58 AM ]

"The most cited paper from 2015 thus far, is a review article from Kozai and co-workers at the University of Pittsburgh and the McGowan Center for Regenerative Medicine entitled “Brain tissue responses to neural implants impact signal sensitivity and intervention strategies” (DOI: 10.1021/cn500256e).(2) This review was in the biannual special issue on Monitoring Molecules, edited by Prof. Anne Andrews. The review focused on the complex molecular and cellular changes that occur when a device breaches the blood-brain barrier and is implanted. The review does a fantastic job summarizing the magnitude, variability, and time course (of acute, seconds to minutes, and chronic, week to months) of injuries and responses to the introduction of foreign bodies into the brain. The review ends with reflections on how and deeper understanding of these complex issues might lead to devices with improved sensitivity and longevity.(2) This is truly a must read."

Save the Date: GRC on Neuroelectronic Interfaces

posted Apr 19, 2017, 1:50 PM by Bionic Lab   [ updated Apr 19, 2017, 1:51 PM ]

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