Introduction to class for people contemplating registering. Overview of syllabus, instructors, requirements, grading, etc... Introduction of students.

Historical ideas and the birth of the modern science of learning. Additional topics include learning/performance, innate behaviors versus adaptation (nature/nurture), critical periods, models and mechanisms, and levels of analysis.

In the following weeks we will explore a number of basic phenomena of learning. However, it is helpful to begin by casting these ideas against the backdrop of contemporary neuroscience. Today's lecture will be a basic whirl-wind tour of the neural processes thought to underly learning and memory. We'll talk about the function of neurons, the specialization of function in the brain, basic learning mechanisms (hebbian learning, LTP), and modern techniques for studying learning and memory (fMRI, EEG, etc...).

This lecture will cover non-associative forms of learning (habituation/sensitation), unsupervised learning, perceptual learning, latent learning, feature learning, stimulus-stimulus learning, statistical learning, imprinting, priming, repetition suppression.

Pavlov, basic procedure, phenomena and terms (CS/US, etc...), basic findings, blocking and overshadowing, etc..., Resorla-Wagner model, Pearce-Hall model and the role of attention/associability in classical conditioning, basic neural substrates of classical conditioning, interactions with other learning systems (e.g., role of hippocampus in trace conditioning).

modern theories including causal interpretations of classical conditioning, context-dependent learning, second-order condition (temporal-difference model and relationship to Rescorla-Wagner), neural basis of prediction errors

law of effect, role of reinforcement, stimulus control, choice behavior, matching law, melioration, concurrent schedules, self control/impulsivity, habits and planning, superstitious responding (special thanks to nathaniel daw for sharing slides and thoughts on the instrumental section)

computational reinforcement learning, model-based and model-free learning algorithms

Pearce (configural) vs. R-W (elemental), stimulus generalization, attention learning, context dependent learning

introduction, episodic memory, hippocampus and space, flexibility, interactions with striatum and cortex

consolidation, complementary learning systems hypothesis, catastrophic interference, specificity and abstraction, recognition versus recall

events, temporal context models, decay versus interference

semantic memory, models of semantic memory, episodic-semantic memory interactions

how to use science of learning and memory to be a better student?