A system for quantitative analysis of associative learning. Part 1. Hardware interfaces with cross-species applications

J Neurosci Methods. 1994 Sep;54(1):109-17. doi: 10.1016/0165-0270(94)90165-1.

Abstract

This paper describes a reliable, durable, and readily calibrated hardware interface system designed to present sensory stimuli at precise time intervals and to transduce and digitize behavioral data in classical conditioning experiments. It has been extensively tested in a 'model'-associative learning task, conditioning of eyeblink or nictitating membrane responses, but is readily adapted to other behavioral paradigms. Each system can run a pair of conditioned experimental or pseudoconditioned control subjects simultaneously, or collect data from a single subject carrying out two tasks simultaneously. The requirements of the system are defined, based around an inexpensive AT-class MS-DOS microcomputer. The interface hardware needed to present auditory tone conditioned stimuli and corneal airpuff-unconditioned stimuli to training subjects are detailed, with timing signals provided by TTL pulses generated at the digital output ports of an analog-to-digital (A/D) converter. An electronic circuit is described that provides stable inputs to the A/D converter, transducing eyeblink responses to voltage signals opto-electronically, without requiring any invasive attachment of the subject to the subject to the measuring device. The 1-piece eyeblink sensor used (selected for ease of alignment and maintenance) is also discussed. Examples of applications for classical conditioning of rabbits, rats, and human subjects are described. A companion paper describes data-acquisition and control software written as a user-friendly interface for this hardware system.

Publication types

  • Research Support, U.S. Gov't, P.H.S.

MeSH terms

  • Animals
  • Association Learning*
  • Behavior
  • Blinking
  • Computers*
  • Conditioning, Classical
  • Electric Wiring
  • Equipment Design
  • Humans
  • Nictitating Membrane / physiology
  • Signal Processing, Computer-Assisted