for Interface Stability over Time (HIST) effort identifies leading mechanisms
of interface degradation and failure. HIST teams are also developing new
invasive and non-invasive histology methods to assess
neural-recording-interface status and performance, accurate predictive models
of interface performance, and methods to reduce the time required to assess and
develop robust interfaces.
Technical Area #1: Quantitatively identify
dominant failure mechanisms of neural-recording interfaces, with objectivity
and strong statistical confidence. Performers in the HIST effort uncovered
serious problems with electrode degradation, interconnect failure,
blood-brain-barrier breach and microglia degeneration.
#2: Develop new quantitative in-vitro and in-vivo techniques for assessing
neural-recording-interface degradation and failure. For this purpose, the
Farsight tool was refined and applied to quantitatively assess biological
response to cortical implants.
Technical Area #3: Predict the failure
of neural-recording interfaces by creating new statistically validated models
and early-precursor-signal-based techniques. Researchers identified measures of
electrode impedance that were indicative of electrode failure.
Technical Area #4: Accelerate the failure of neural-recording interfaces by
creating new statistically validated models and stressor-signal-based
techniques. In this final TA, researchers developed new lines of transgenic
animals and microfluidic platforms to accelerate the biological tissue response
associated with interface failure; and developed “artificial brain” preps to
bench-test electrode degradation.
HIST is one of three complementary efforts within DARPA’s Reliable Neural-Interface Technology (RE-NET) program aimed at understanding why the performance of neural interfaces degrades over time and developing new high-performance neural interfaces that last the life of the patient.
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