Course Identification

Introduction to Neuroscience: Behavioral Neuroscience

מבוא לבסיס המוחי של התנהגות

Lecturers: Prof. Nachum Ulanovsky, Prof. Tali Kimchi, Prof. Rony Paz

This course will introduce students to Behavioral Neuroscience, first by providing an in-depth introduction to behavior, and then focusing on two different approaches that are common in the field: One approach ("neuropsychological") is to study animals in artificial well-controlled tasks, the other ("neuroethological") approach utilizes the animal's natural behaviors.  We will introduce general aspects, and will contrast and compare these two approaches by focusing on several well-studied, classic example systems.

Part A:  Introduction to Brain and Behavior  (Kimchi)

1. Introduction to Behavior.
2. Hormones, genes and behaviors: Mechanisms underlying social and reproductive behaviors.
3. Neurobiology of social behaviors.

Part B:  Neural mechanisms of Behavior – the Neuroethological approach  (Ulanovsky)

1. Sensory ecology: evolutionary adaptations of animal sensory systems to their environment.
2. Example system #1: Echolocation in bats: Sensory ecology, echolocation behavior, principles of biosonar signal design, neural processing.
3. Example system #2: Multisensory integration in the brain of the barn owl. (Guest lecture by: Prof. Yoram Gutfreund, Technion)
4. Example system #3: The bird song system: behavior, neuroanatomy, physiology, models.  (Guest lecture by: Dr. Liora Las, Weizmann Institute)
5. Example system #4: Neurobiology of spatial cognition.  Introduction to spatial memory, orientation and navigation: (i) Navigational strategies in different animals. (ii) Sensory mechanisms of navigation: vision, magnetic navigation, etc.  The navigation circuits in the mammalian brain: Place cells, grid cells, head-direction cells.
6. Summary of the neuroethological approach. Choosing the right behavior and the right animal model.  Natural Neuroscience.  Comparative Neuroscience.

Part C:  Neural mechanisms of Behavior – the Neuropsychological approach  (Paz)

1. Introduction: Basic concepts, standard behavioral tasks.  Example system #5: Fear learning and its neural circuits.
2. Examples system #6: Reward-based learning and its neural basis.
3. Example system #7: Decision-making in the brain.

Upon successful completion of this course students should be be able to:

1. Describe classical model systems in behavioral neuroscience.
2. Demonstrate sufficient knowledge required to take more advanced courses in neuroscience.