TY - JOUR
T1 - Simulation of the classically conditioned nictitating membrane response by a neuron-like adaptive element
T2 - Response topography, neuronal firing, and interstimulus intervals
AU - Moore, John W.
AU - Desmond, John E.
AU - Berthier, Neil E.
AU - Blazis, Diana E.J.
AU - Sutton, Richard S.
AU - Barto, Andrew G.
N1 - Funding Information:
This research was supported by Grants AFOSR 830215, NSF BNS 8317920, and USPHS 1 F31 MH08951.
PY - 1986/8
Y1 - 1986/8
N2 - A neuron-like adaptive element with computational features suitable for classical conditioning, the Sutton-Barto (S-B) model, was extended to simulate real-time aspects of the conditioned nictitating membrane (NM) response. The aspects of concern were response topography, CR-related neuronal firing, and interstimulus interval (ISI) effects for forward-delay and trace conditioning paradigms. The topography of the NM CR has the following features: response latency after CS onset decreases over trials; response amplitude increases gradually within the ISI and attains its maximum coincidentally with the UR. A similar pattern characterizes the firing of some (but not all) neurons in brain regions demonstrated experimentally to be important for NM conditioning. The variant of the S-B model described in this paper consists of a set of parameters and implementation rules based on 10-ms computational time steps. It differs from the original S-B model in a number of ways. The main difference is the assumption that CS inputs to the adaptive element are not instantaneous but are instead shaped by unspecified coding processes so as to produce outputs that conform with the real-time properties of NM conditioning. The model successfully simulates the aforementioned features of NM response topography. It is also capable of simulating appropriate ISI functions, i.e. with maximum conditioning strength with ISIs of 250 ms, for forward-delay and trace paradigms. The original model's successful treatment of multiple-CS phenomena, such as blocking, conditioned inhibition, and higher-order conditioning, are retained by the present model.
AB - A neuron-like adaptive element with computational features suitable for classical conditioning, the Sutton-Barto (S-B) model, was extended to simulate real-time aspects of the conditioned nictitating membrane (NM) response. The aspects of concern were response topography, CR-related neuronal firing, and interstimulus interval (ISI) effects for forward-delay and trace conditioning paradigms. The topography of the NM CR has the following features: response latency after CS onset decreases over trials; response amplitude increases gradually within the ISI and attains its maximum coincidentally with the UR. A similar pattern characterizes the firing of some (but not all) neurons in brain regions demonstrated experimentally to be important for NM conditioning. The variant of the S-B model described in this paper consists of a set of parameters and implementation rules based on 10-ms computational time steps. It differs from the original S-B model in a number of ways. The main difference is the assumption that CS inputs to the adaptive element are not instantaneous but are instead shaped by unspecified coding processes so as to produce outputs that conform with the real-time properties of NM conditioning. The model successfully simulates the aforementioned features of NM response topography. It is also capable of simulating appropriate ISI functions, i.e. with maximum conditioning strength with ISIs of 250 ms, for forward-delay and trace paradigms. The original model's successful treatment of multiple-CS phenomena, such as blocking, conditioned inhibition, and higher-order conditioning, are retained by the present model.
KW - classical conditioning
KW - computational neural model
KW - nictitating membrane response
KW - rabbit
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U2 - 10.1016/0166-4328(86)90092-6
DO - 10.1016/0166-4328(86)90092-6
M3 - Article
C2 - 3755947
AN - SCOPUS:0022486566
SN - 0166-4328
VL - 21
SP - 143
EP - 154
JO - Behavioural Brain Research
JF - Behavioural Brain Research
IS - 2
ER -