An Analysis of Primate Inhibitory Burst Neuron Spike Trains using System
Identification Techniques: Relationship to Eye Movement Dynamics during Head-
Fixed Saccades.
Kathleen E. Cullen and Daniel Guitton.
Aerospace Medical Research Unit and the Montreal Neurological Institute,
McGill University, Montreal, Quebec H3G 1Y6, Canada.
APStracts 4:125N, 1997.
ABSTRACT
The dynamic behavior of primate (Macaca fasicularis) inhibitory burst neurons
(IBNs) during head-fixed saccades was analyzed using system identification
techniques. Neurons were categorized as IBNs on the basis of their anatomical
location, as well as by their activity during horizontal head-fixed saccadic
and smooth pursuit eye movements, and vestibular nystagmus. Each IBN’s latency
or “dynamic lead time” (td) was determined by shifting the unit discharge in
time until an optimal fit to the firing rate frequency, B(t), profile was
obtained using the simple model based on eye movement dynamics, B(t) = r +
b1E((t); where E( is eye velocity. For the population of IBNs, the dynamic
estimate of lead time provided a significantly lower value than a method which
used the onset of the first spike.
We then compared the relative abilities of different eye movement based models
to predict B(t) using objective optimization algorithms. The most important
terms for predicting B(t) were eye velocity gain (b1) and bias terms (r)
mentioned above. The contributions of higher order velocity, acceleration
and/or an eye position terms to model fits were found to be negligible. The
addition of a pole term (the time derivative of B(t)) in conjunction with an
acceleration term significantly improved model fits to IBN spike trains,
particularly when the firing rates at the beginning of each saccade (ICs) were
estimated as parameters. Such a model fit the data well (a fit comparable to a
linear regression analysis with a R2 value of 0.5, or equivalently, a
correlation coefficient of 0.74). A simplified version of this model [B(t) =
rk + b1E((t)], which did not contain a pole term, but in which the bias term
(rk) was estimated separately for each saccade, provided nearly equivalent
fits of the data. However, models, in which ICs or rks were estimated
separately for each saccade, contained too many parameters to be considered as
useful models of IBN discharges.
We discovered that estimated ICs and rks were correlated with saccade
amplitude for the majority of short-lead burst neurons (SLIBNs, 56%) and many
long lead burst neurons (LLIBNs, 42%). This observation led us to construct a
more simple model that included a term that was inversely related to the
amplitude of the saccade, in addition to eye velocity and constant bias terms.
Such a model better described neuron discharges than more complex models based
on a third order non-linear function of eye velocity. Given the small number
of parameters required by this model (only 3), and its ability to fit the
data, we suggest that it provides the most valuable description of IBN
discharges. This model emphasizes the IBN discharges are dependent on saccade
amplitude and implies further that a mechanism must exist, at the motoneuron
level, to offset the effect of the bias and amplitude-dependent terms. In
addition, we did not find a significant difference in the variance-accounted-
for (VAF) by any of the downstream models tested for SLIBNS versus LLIBNs.
Therefore, we conclude that the eye movement signals encoded dynamically by
SLIBNS and LLIBNs are similar in nature. Put another way, SLIBNS are not
closer, dynamically, to motoneurons than LLIBNs.
Received 13 August 1996; accepted in final form 2 July 1997.
APS Manuscript Number J0648-6.
Article publication pending J. Neurophysiol.
ISSN 1080-4757 Copyright 1997 The American Physiological Society.
Published in APStracts on 24 July 1997