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NROC34: Decisions and Control of Behavior (word-for-word lec notes)

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University of Toronto Scarborough
Andrew Mason

Lec 11: Decisions and Control of Behavior Slide 1: Decision and Control of Behavior Forming link btn sensory and motor systems Decision-making from the neuoroethological point of view Slide 2: Decisions Diff approaches to study decisions Psychological/cognitive science approach: o Largely involves formal models of psychophysical data (= data from experiments where you carefully control the stimulus conditions and connect what qualities of the stimulus are associated w/ a particular beh or discrimination (deciding whats the same or diff) o Low-resolution neural data (brain-imaging/EEG) = low spatial/temporal resolution o Humans & monkeys Neuroethological/behavioural approach o Emphasizes natural behavior o Focused on circuit-level description Leech paper is aiming at the possibility that there could be some unification of these 2 approaches Slide 3: A decision model Architecture that represents a set of inputs which can be thought of as sensory inputs that are sensitive to diff possibilities: o So, these could be motion-sensitive visual neurons in the brain of a monkey thats staring at cpu screen watching dots move in random ways; get reward for picking right direction o So, have set of sensory inputs that are accumulating info in favor of diff alternatives; may be watching diff axes of mvt; when one of these reaches some critical level, then its activity is integrated by these integrators o The first one of the inputs to reach a critical level makes the decision; cross cxns btn the integrators represent inhibition; competition among diff sensory inputs representing diff alternatives o This is a standard way of thinking about how decisions may be implemented in NS o This kind of approach is designed to describe response time of tasks such as the one about the monkey staring at a screen, watching random dot pattern, theres some overall direction of mvt monkey indicates which direction it thinks the dot is moving; can set this up so that theres more or less time to make the right decision and theres a tradeoff between the speed of making the choice and the accuracy of the choice o Characteristic relationship btn speed and accuracy Slide 5: Typical neuroethology approach to decisions Idea of command neurons Sensory info coming in; have pathways that are dedicated to particular behaviors The process sensory info does or does not activate some critical element of the nervous sys, often referred to as command neuron And if it does activate command neuron, then beh occurs; one of the effects of activating a command neuron could be to inhibit other command neurons Some similarities to the abstract model from above; winner takes all mechanism st where the 1 decision making element to be activated shuts off its competitors structure of processing circuit Slide 6: This kind of view: circuit-level description of the action of the NS and its relation to behavior comes from a tradition that wasnt focused on behavior at all but rather an engineering approach to NS o Ex: gastronemius prep of a frog, nerve stimulated and see muscle contract o Pieces of animals used to look at little parts of the circuits; focused on low- level properties of the NS (cell and synapse level) But Sherrington wrote book: Integrative Fxn of the NS; where he imagined how this small scale mechanism could be used to describe the NS as a whole and how it controls behavior o Based on idea of reflexes as fxnl unit; neuron when activated has hard- wired cxn to some effector (muscle), will always result in a certain beh o If many of these elaborately connected together automaton of animal; chain of deterministic reflexes o Higher mental fxns and emotions could never be addressed in this mechanistic way Earthworm: o Touch it, quickly w/draws into burrow; quick and robust w/drawal reflex o Circuit diagram of w/drawal reflex pathway; w/drawal reflex carried thru by nerve cord from segment to segment o Is this enough to describe the fxn of the NS? o Is NS capable of endogenously generated activity? Slide 8: Spontaneous/Endogenous Behavior Is NS capable of endogenously generated activity? Whether or not everything was just a stimulus-response set-up? NS is simply driven by stimuli that impinge on the animal and are processed in some way OR whether you can have activity spontaneously, independently generated by the NS itself? This lead to the idea of central pattern generators, rhythmic activity Rhythmic activity were key to demonstrating that endogenous beh is possible Slide 9: Oscillation in Neural Networks Breakthrough was that you can have self-sustained cyclical activity in NS that IS NOT driven by sensory input o Rhythmic motor activityo Sensory process (olfaction; cycles of synchronized activity as the basis of coding mechanism) o Dynamic interplay btn central and sensory processes There is nevertheless a role for sensory input for these processes Slide 11: What does it take to create a pattern generator? Simulated APs based on this circuit; 2 neurons, each w/ reciprocal inhibitory cxns, each of which has the property of inhibitory rebound (= when its membrane is hyperpolarized and that inhibition stops, it overshoots on its return to resting level and fires an AP) o Which means when you inhibit one of these neurons, when it rebounds, it has burst of APs that inhibits the other neuron; and when 2 neuron st rebounds, it has burst of APs that inhibit 1 neuron alternating bursts of activity btn these 2 neurons o Just need something to get started, then have self-sustained osciallation of activity Can be modified in diff ways: o Additional neurons may interfere; inhibits one of them, results in changes in timing reset phase of the cycle (stop and start one of them, will change phase) 2 neurons with these properties: (reciprocal inhibition, inhibitory rebound)
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