• Schiff, Steven (PI)
  • Schiff, Steven J. (PI)
  • Schiff, Steven J. (PI)

Project: Research project

Project Details


The well-known extreme variability of spinal cord reflex output has
defied analysis suing classical statistics. This variability renders the
interpretation of electrophysiologic monitoring during spasticity surgery
extremely difficult. Preliminary studies have re-evaluated reflex output
data using new techniques developed for the analysis of complex
phenomena. In the normal human, it appears that reflexes fluctuate on
many different time scales: seconds, minutes, and perhaps hours.
Physical systems which fluctuate on many time scales are "self-similar",
and this is the hallmark of a "fractal" process. The results generate
the following working hypothesis: time-series of spinal cord reflex
output fluctuate with a fractal pattern. this idea will be rigorously
tested using data collected from the spinal cord of the decerebrate cat
including: 1) neuronal population response, 2) individual neuron firing
frequency and 3) the tendon force generated. Data will be obtained while
varying the frequency of stimulation and with the reflex feedback loop
opened and closed. to characterize fractal behavior, non-linear
analytical methods will be extensively used. By employing simulated data
sets as mathematical controls, these methods should help determine
whether the observed fractal patterns originate from deterministic or
stochastic processes. The results of this work are important from both
clinical and basic science perspectives. Clinically, proving that spinal
cord reflexes fluctuate on time scales far longer than the measuring
period permitted in the operating room would lead to a radical shortening
of operative time and risk. On a basic level, the results will provide
information leading to a deeper understanding of the origin of apparently
random fluctuations in a simple input-output neural circuit in the
mammalian nervous system. It is expected that the results of this study
will be applicable to more complex neural circuits in the central nervous
Effective start/end date1/1/937/31/09