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Analysis, Design, and Control of Movable Neuro-Probes Z. Nenadic, E. Branchaud, R. Andersen, J. Pezaris, W. Collins, and J. Burdick B. Greger, B. Pesaran.

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Presentation on theme: "Analysis, Design, and Control of Movable Neuro-Probes Z. Nenadic, E. Branchaud, R. Andersen, J. Pezaris, W. Collins, and J. Burdick B. Greger, B. Pesaran."— Presentation transcript:

1 Analysis, Design, and Control of Movable Neuro-Probes Z. Nenadic, E. Branchaud, R. Andersen, J. Pezaris, W. Collins, and J. Burdick B. Greger, B. Pesaran Engineering and Applied Science Biology California Institute of Technology (Auxiliary Program Started April 1, 2001)

2 Limitations of Current Neuro-Probe Technology Key Challenge: record high quality signals from many neurons (for months/years) Fixed positioning of implant Non-optimal (or wrong!) receptive fields. Electrode not near cell body. Low impedance (poor SNR) design required. Gliosis and encapsulation Make the probes movable to track/find neurons!

3 Movable Probe Concept: computer controlled movable probes can track moving neurons, find new neurons, break through encapsulation. Project Goals Short term: validate concept, enable more complex acute experiments Intermediate term: Develop design specs for MEMS devices Long term: develop MEMS technology for implantable devices (see talk by Y.C. Tai)

4 Current Research Program Outline Theory – develop algorithms for probe control using modeled (computational) environment Model extra-cellular neuron potentials Characterize local field potentials (LFP) Control algorithm development guided by computational model Implementation – meso-scale hardware test-beds Validate concept, evaluate algorithms Enable testing of Biomechanical issues of chronic movable probe operation

5 Single Cell Extracellular Potential Simulation 3720 compartment NEURON pyramidal cell model ( adapted from Mainen & Sejnowski ‘96 ) Synaptic inputs scattered uniformly throughout dendrites. Laplace equation: Boundary condition: Since solution nearly impossible, use line source approximation (Holt & Koch ‘99) soma

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7 Spatial Variation of Extracellular Potential

8 Peak-to-peak amplitude Tuning curve Noise variance -- determined by signal-to- noise ratio (SNR) Added noise -- independent, Gaussian, zero-mean Keep electrode in this region!

9 Movable Probe Feedback Under the conditions: the sequence converges to almost surely i.e. Q: How to find the maximum point of the tuning curve? A: Stochastic optimization gradient method basis function method splines – under development (stochastic gradient descent) step size stochastic gradient future position current position

10 Movie 1Movie 2

11 Movable Probe Test-bed Development Multiple development phases to maximize scientific gain and engineering development along the way.  Acute: probes inserted in brain tissue for a few hours  Initial validation of movable probe concept and algorithms  Enable better short-term prosthetic feedback experiments  Semi-chronic: electrodes remain, motors removed  Understand biophysical issues of chronic probe operation  Track neural populations over days for plasticity studies  Will set spec.s for future MEMS devices  Chronic: movable system permanently implanted  Ultimate goal: needs MEMS development  Key technology for future neural-prosthetics

12 Acute Test-Beds Last time: motorizing the CCMD, a pre-existing manual 4 probe device Completed, with lessons learned –(need to list some lessons here) Put diagram of Thomas system here + a few words about status

13 Semi-Chronic Test-bed Phase I(a): two motor drive that fits inside head cap Motors and electrodes stay inserted for a few days Power, control, data wires attached at start of each session Useful for studies in learning and plasticity Phase I(b): two motor drive that fits inside head cap motors detached at end of every session—electrodes stay implanted for long periods of time. enables testing of long term biophysical impact of chronic electrode operation (inflammation, gliosis, etc.) Phase II: 12-16 motor micro-drive with removable motor assembly. Will enable consistent recordings of many cells

14 Phase 1 Design Progress Pretty Picture

15 Conclusions Developed theory for control of movable probe based on peak-to- peak amplitude. Future investigations will include: other wave form features, such as phase, shape, frequency, etc. event detection algorithms to handle irregularity of spike trains the effects of multiple units (inclusion of spike sorting). effects of tissue dimpling and relaxation (easily incorporated) Movable Probe Test-Beds development program started CCMD motorization completed, with lessons learned. 5-probe acute system developed Phase I of semi-chronic system largely designed


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