Correction: Energy-Optimal Electrical-Stimulation Pulses Shaped by the Least-Action Principle

Electrical stimulation (ES) devices interact with excitable neural tissue toward eliciting action potentials (AP’s) by specific current patterns. Low-energy ES prevents tissue damage and loss of specificity. Hence to identify optimal stimulation-current waveforms is a relevant problem, whose solution may have significant impact on the related medical (e.g. minimized side-effects) and engineering (e.g. maximized battery-life) efficiency. This has typically been addressed by simulation (of a given excitable-tissue model) and iterative numerical optimization with hard discontinuous constraints - e.g. AP’s are all-or-none phenomena. Such approach is computationally expensive, while the solution is uncertain - e.g. may converge to local-only energy-minima and be model-specific. We exploit the Least-Action Principle (LAP). First, we derive in closed form the general template of the membrane-potential’s temporal trajectory, which minimizes the ES energy integral over time and over any space-clamp ionic current model. From the given model we then obtain the specific energy-efficient current waveform, which is demonstrated to be globally optimal. The solution is model-independent by construction. We illustrate the approach by a broad set of example situations with some of the most popular ionic current models from the literature. The proposed approach may result in the significant improvement of solution efficiency: cumbersome and uncertain iteration is replaced by a single quadrature of a system of ordinary differential equations. The approach is further validated by enabling a general comparison to the conventional simulation and optimization results from the literature, including one of our own, based on finite-horizon optimal control. Applying the LAP also resulted in a number of general ES optimality principles. One such succinct observation is that ES with long pulse durations is much more sensitive to the pulse’s shape whereas a rectangular pulse is most frequently optimal for short pulse durations.

[1]  Manfred Morari,et al.  Energy-optimal electrical excitation of nerve fibers , 2005, IEEE Transactions on Biomedical Engineering.

[2]  Y Rudy,et al.  Ionic mechanisms of propagation in cardiac tissue. Roles of the sodium and L-type calcium currents during reduced excitability and decreased gap junction coupling. , 1997, Circulation research.

[3]  C. McIntyre,et al.  Modeling the excitability of mammalian nerve fibers: influence of afterpotentials on the recovery cycle. , 2002, Journal of neurophysiology.

[4]  F. Rattay,et al.  The basic mechanism for the electrical stimulation of the nervous system , 1999, Neuroscience.

[5]  Annette Lykknes,et al.  For Better or For Worse? Collaborative Couples in the Sciences , 2012 .

[6]  Biao Huang,et al.  System Identification , 2000, Control Theory for Physicists.

[7]  L. Lapicque Has the muscular substance a longer chronaxie than the nervous substance? 1 , 1931, The Journal of physiology.

[8]  Miguel A. L. Nicolelis,et al.  A Brain-Machine Interface Instructed by Direct Intracortical Microstimulation , 2009, Front. Integr. Neurosci..

[9]  Eugene M. Izhikevich,et al.  Which model to use for cortical spiking neurons? , 2004, IEEE Transactions on Neural Networks.

[10]  Verena Tiefenbeck,et al.  For better or for worse? Empirical evidence of moral licensing in a behavioral energy conservation campaign , 2013 .

[11]  F. Rattay,et al.  Analysis of the electrical excitation of CNS neurons , 1998, IEEE Transactions on Biomedical Engineering.

[12]  A. B. BASSET,et al.  The Principle of Least Action , 1903, Nature.

[13]  Andrew P. Sage,et al.  System Identification , 1971 .

[14]  J. B. Ranck,et al.  Which elements are excited in electrical stimulation of mammalian central nervous system: A review , 1975, Brain Research.

[15]  G. Weiss Sur la possibilite de rendre comparables entre eux les appareils servant a l'excitation electrique. , 1990 .

[16]  Leslie A. Geddes,et al.  Accuracy limitations of chronaxie values , 2004, IEEE Transactions on Biomedical Engineering.

[17]  Cameron C McIntyre,et al.  Evaluation of novel stimulus waveforms for deep brain stimulation , 2010, Journal of neural engineering.

[18]  R. FitzHugh Impulses and Physiological States in Theoretical Models of Nerve Membrane. , 1961, Biophysical journal.

[19]  Frank Rattay,et al.  Electrical Nerve Stimulation , 1990 .

[20]  F. Rattay,et al.  Strength–duration relationship for intra- versus extracellular stimulation with microelectrodes , 2012, Neuroscience.

[21]  Frank Rattay,et al.  Electrical Nerve Stimulation: "Theory, Experiments And Applications" , 2001 .

[22]  W. Rall Core Conductor Theory and Cable Properties of Neurons , 2011 .

[23]  Josef Ladenbauer,et al.  Can the human lumbar posterior columns be stimulated by transcutaneous spinal cord stimulation? A modeling study. , 2011, Artificial organs.

[24]  B. Katz Experimental Evidence for a Non-Conducted Response of Nerve to Subthreshold Stimulation , 1937 .

[25]  Warren M Grill,et al.  Efficiency Analysis of Waveform Shape for Electrical Excitation of Nerve Fibers , 2010, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[26]  Christian Hauptmann,et al.  Modified Pulse Shapes for Effective Neural Stimulation , 2011, Front. Neuroeng..

[27]  G.S. Dhillon,et al.  Direct neural sensory feedback and control of a prosthetic arm , 2005, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[28]  E. Fetz Volitional control of neural activity: implications for brain–computer interfaces , 2007, The Journal of physiology.

[29]  Warren M Grill,et al.  Energy-efficient waveform shapes for neural stimulation revealed with a genetic algorithm , 2010, Journal of neural engineering.

[30]  M. Sahin,et al.  Non-rectangular waveforms for neural stimulation with practical electrodes , 2007, Journal of neural engineering.

[31]  Eberhard E. Fetz,et al.  Myo-Cortical Crossed Feedback Reorganizes Primate Motor Cortex Output , 2013, The Journal of Neuroscience.

[32]  Liberson Wt,et al.  Functional electrotherapy: stimulation of the peroneal nerve synchronized with the swing phase of the gait of hemiplegic patients. , 1961, Archives of physical medicine and rehabilitation.

[33]  Yousheng Shu,et al.  Distinct contributions of Nav1.6 and Nav1.2 in action potential initiation and backpropagation , 2009, Nature Neuroscience.

[34]  F. Rattay,et al.  Which elements of the mammalian central nervous system are excited by low current stimulation with microelectrodes? , 2010, Neuroscience.

[35]  Louis Édouard Lapicque,et al.  L'excitabilité en fonction du temps : la chronaxie, sa signification et sa mesure , 1926 .