REP-2009-473 - TASK-BASED SPIKETRAIN DISCRIMINATION AND AN...

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Unformatted text preview: TASK-BASED SPIKETRAIN DISCRIMINATION AND AN APPLICATION TO NEURAL REINFORCEMENT By NATHAN D. VANDERKRAATS A PROPOSAL PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY UNIVERSITY OF FLORIDA 2008 1 c circlecopyrt 2008 Nathan D. VanderKraats 2 TABLE OF CONTENTS page LIST OF TABLES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 LIST OF FIGURES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 ABSTRACT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 CHAPTER 1 BACKGROUND MATERIAL . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 1.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 1.2 Neuroscience Concepts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 1.2.1 Basic neural dynamics . . . . . . . . . . . . . . . . . . . . . . . . . 9 1.2.2 Functional Brain Regions . . . . . . . . . . . . . . . . . . . . . . . . 12 1.2.3 Neural Modeling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 1.2.4 Spike Timing Dependent Plasticity . . . . . . . . . . . . . . . . . . 15 1.3 Auditory System Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . 16 1.4 Meddis Inner-Hair Cell Model . . . . . . . . . . . . . . . . . . . . . . . . . 18 1.5 Machine Learning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 1.5.1 Support Vector Machines . . . . . . . . . . . . . . . . . . . . . . . . 20 1.5.2 Perceptron . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21 2 ON THE MUTUAL INFORMATION BETWEEN TASK-BASED STIMULI AND SPIKETRAIN RESPONSES FOR LARGE NEURAL POPULATIONS . . 22 2.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22 2.1.1 Informational Tasks . . . . . . . . . . . . . . . . . . . . . . . . . . . 22 2.1.2 Task-Based Reconstruction . . . . . . . . . . . . . . . . . . . . . . . 23 2.1.3 A Tighter Information-Theoretic Bound . . . . . . . . . . . . . . . . 25 2.1.4 Previous Information-Theoretic Results . . . . . . . . . . . . . . . . 26 2.2 Description of Method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 2.2.1 Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 2.2.2 Auditory input . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 2.2.3 Spiking Neuron Model . . . . . . . . . . . . . . . . . . . . . . . . . 30 2.2.4 Decoder Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30 2.2.5 Feature Space Candidates . . . . . . . . . . . . . . . . . . . . . . . 31 2.2.6 Statistical Classifier . . . . . . . . . . . . . . . . . . . . . . . . . . . 32 2.3 A Lower Bound on MI . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32 3 DECODING METHOD RESULTS . . . . . . . . . . . . . . . . . . . . . . . . . 34 3.1 Experimental Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ....
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REP-2009-473 - TASK-BASED SPIKETRAIN DISCRIMINATION AND AN...

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