Classical conditioning in a simple withdrawal reflex in Aplysia californica

By T. J. Carew, E. Walters, E. Kandel. 1981

The ability of Aplysia and other gastropod molluscs to exhibit complex behaviors that can be modified by associative learning has encouraged us to search for an elementary behavior controlled by a simple and well analyzed neural circuit that also can be modified by this type of learning. Toward that end, we have now produced classical conditioning in the defensive siphon and gill withdrawal reflex of Aplysia. We used as a conditioned stimulus (CS) a light tactile stimulus to the siphon, which produces weak siphon and gill withdrawal. As the unconditioned stimulus (US), we used a strong electric shock to the tail, which produces a massive withdrawal reflex. Specific temporal pairing of the CS and US endowed the CS with the ability of triggering enhanced withdrawal of both the siphon and the gill. Random or unpaired presentations of the CS and US, as well as presentations of the CS or US alone, produced either no enhancement or significantly less enhancement than paired presentations of the CS and US. The conditioning is acquired rapidly (within 15 trials) and is retained for several days. The conditioned response is abolished completely by removal of the abdominal ganglion and many of the neurons involved in the conditioning have been identified in this ganglion previously. These include the sensory neurons and several interneurons in the CS pathway and the siphon and gill motor neurons of the conditioned and unconditioned response pathways. Moreover, the sensory neurons of the US pathway have been identified in the pleural ganglia. As a result of its simplicity, it should be possible in this reflex to specify neurons that are causally related to the conditioned response. Since this reflex also exhibits nonassociative learning, it also may be possible to compare associative and nonassociative learning on a mechanistic level.

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Citations in the corpus

Born to Learn: the Inspiration, Progress, and Future of Evolved Plastic Artificial Neural Networks (2017, background): “Walters and Byrne (1983) showed that a single neuron can perform associative learning such as classical conditioning, a class of learning that is observed in simple neural systems such as by the Aplysia (Carew et al., 1981).”
A unified approach to evolving plasticity and neural geometry (2012, background): “This property seems to play a critical role in regulating learning behavior in animals [5] and neuromodulated networks have a clear advantage in more complex dynamic, reward-based scenarios: Soltoggio et al. [25] showed that networks with neuromodulated plasticity and the same evolved Hebbian rule…”
Overcoming deception in evolution of cognitive behaviors (2014, methodology): “In particular, in the learning task described later, ANNs are augmented with neuromodulated plasticity, a biologicallyplausible [3] method for behavioral plasticity applied in similar previous learning experiments [17, 21].”
Evolving plastic neural networks with novelty search (2010, background): “Interestingly, Chalmers (1990) evolved a global learning rule (i.”
Evolutionary and Computational Advantages of Neuromodulated Plasticity (2008, background): “Studies on molluscs like the Aplysia californica (Kandel and Tauc, 1965; Clark and Kandel, 1984; Roberts and Glanzman, 2003) have shown modulatory cellular mechanisms to regulate classical conditioning (Carew et al., 1981; Sun and Schacher, 1998), operant conditioning (Brembs et al.”
Evolutionary Advantages of Neuromodulated Plasticity in Dynamic, Reward-based Scenarios (2008, background): “Studies on mollusks like the Aplysia californica (Roberts and Glanzman, 2003) have shown neuromodulation to regulate classical conditioning (Carew et al., 1981; Sun and Schacher, 1998), operant conditioning (Brembs et al., 2002) and wiring in developmental processes (Marcus and Carew, 1998).”
How novelty search escapes the deceptive trap of learning to learn (2009, background): “This property seems to play a critical role in regulating learning behavior in animals [3] and neuromodulated networks have a clear advantage in more complex dynamic, reward-based scenarios: Soltoggio et al.”
Rare Neural Correlations Implement Robotic Conditioning with Delayed Rewards and Disturbances (2013, background): “Even organisms with relatively simple neural systems, like the marine mollusk Aplysia, are capable of associating neutral stimuli with following noxious stimuli in classical (Kandel and Tauc, 1965; Carew et al., 1981) and operant conditioning (Brembs et al.”
From modulated Hebbian plasticity to simple behavior learning through noise and weight saturation (2012, background): “Early studies on the mollusk Aplysia proved that behavioral changes were precisely linked to the growth of particular pathways from sensory to motor systems (Kandel and Tauc, 1965; Carew et al., 1981).”