1 Dissecting neural circuits for vision in non-human primates using fMRI-guided electrophysiology and optogenetics Thesis by Shay Ohayon In Partial Fulfillment of the Requirements for the degree of Doctor of Philosophy CALIFORNIA INSTITUTE OF TECHNOLOGY Pasadena, California 2014 (Defended 15th May 2014) ii 2014 Shay Ohayon All Rights Reserved iii This work is dedicated to my parents The distance between your dreams and reality is called action. - Unknown iv v Acknowledgements There are many people without whom this thesis would not exist. First and foremost, I would like to acknowledge my PhD advisor, Doris Tsao, for giving me the opportunity to perform research in her lab and the freedom to pursue my own research ideas. She provided continuous guidance and support throughout the years and trusted me in leading experiments and procedures from day one (“OK, now you drill…” will forever be remembered as the ultimate show of confidence to a young graduate student with zero surgical experience). Nicole Schweers, our lab manager, for always lending an ear and taking care of my animals as if they were her own children. I would like to thank Prof. Pietro Perona for a joyful collaboration throughout my years at Caltech. Many thanks also go to all the past members of the Tsao lab. Winrich Freiwald who was a close collaborator throughout the years and provided many important advices on electrophysiology. Sebastian Moeller, for many fruitful discussions and teaching me how to perform electrical microstimulation and fMRI data analysis. Piercesare Grimaldi, who I owe everything I know about histology and immunohistochemistry. I was extremely lucky to spend three weeks in Stanford where I was trained in the Karl Deisseroth lab by Ilka Diester, who provided continuing support and help to my ongoing optogenetics experiments. Last and not least, I would like to thank my wife, who left much behind in order to join me in my adventure of pursuing a PhD. vi vii Abstract The visual system is a remarkable platform that evolved to solve difficult computational problems such as detection, recognition, and classification of objects. Of great interest is the face-processing network, a sub-system buried deep in the temporal lobe, dedicated for analyzing specific type of objects (faces). In this thesis, I focus on the problem of face detection by the face-processing network. Insights obtained from years of developing computer-vision algorithms to solve this task have suggested that it may be efficiently and effectively solved by detection and integration of local contrast features. Does the brain use a similar strategy? To answer this question, I embark on a journey that takes me through the development and optimization of dedicated tools for targeting and perturbing deep brain structures. Data collected using MR-guided electrophysiology in early face-processing regions was found to have strong selectivity for contrast features, similar to ones used by artificial systems. While individual cells were tuned for only a small subset of features, the population as a whole encoded the full spectrum of features that are predictive to the presence of a face in an image. Together with additional evidence, my results suggest a possible computational mechanism for face detection in early face processing regions. To move from correlation to causation, I focus on adopting an emergent technology for perturbing brain activity using light: optogenetics. While this technique has the potential to overcome problems associated with the de-facto way of brain stimulation (electrical micro- stimulation), many open questions remain about its applicability and effectiveness for perturbing the non-human primate (NHP) brain. In a set of experiments, I use viral vectors to deliver genetically encoded optogenetic constructs to the frontal eye field and face- selective regions in NHP and examine their effects side-by-side with electrical micro- stimulation to assess their effectiveness in perturbing neural activity as well as behavior. Results suggest that cells are robustly and strongly modulated upon light delivery and that such perturbation can modulate and even initiate motor behavior, thus, paving the way for future explorations that may apply these tools to study connectivity and information flow in the face processing network. viii TABLE OF CONTENTS Table of Contents Acknowledgements ............................................................................................. v Abstract .............................................................................................................. vii Preface ................................................................................................................ 12 Introduction ........................................................................................................ 14 Inferotemporal Cortex and Face Processing ............................................... 17 Why IT? ...................................................................................................................... 17 Overall Structure of IT ............................................................................................... 18 Micro-structure in IT .................................................................................................. 19 Imaging methods shed more light on the global structure of IT ............................... 21 Face processing in IT ................................................................................................. 23 Perturbation of IT activity .......................................................................................... 27 Optogenetics ................................................................................................ 28 Origins ........................................................................................................................ 29 Optimizations and expansion of the optogenetic toolbox ......................................... 30 Expression and Delivery ............................................................................................ 31 Chapter 1: MR-Guided Electrophysiology ....................................................... 34 Introduction .................................................................................................. 35 Methods ....................................................................................................... 38 Animals and Surgery .................................................................................................. 38 MR Scans .................................................................................................................... 40 Results .......................................................................................................... 40 Framework overview ................................................................................................. 40 Experimental validation ............................................................................................. 45 Correction for surgical placement errors ................................................................... 49 Blood vessel avoidance .............................................................................................. 49 Discussion .................................................................................................... 51 Appendices .................................................................................................. 54 Appendix 1: Solving the absolute orientation problem............................................. 54 Appendix 2: Solving the inverse kinematics problem using iterative manipulator Jacobian ...................................................................................................................... 55 Appendix 3: DH Representation for Kopf 1460 manipulator ................................... 56 Figures.......................................................................................................... 58 Tables ........................................................................................................... 64 Chapter 2: Local contrast features and their importance for face detection .... 65 Introduction .................................................................................................. 66 Methods ....................................................................................................... 69 Experimental Procedures ........................................................................................... 69 Face Patch Localization ............................................................................................. 69 Visual Stimuli and Behavioral Task .......................................................................... 69 Parameterized face stimuli generation ....................................................................... 70 Neural Recording ....................................................................................................... 70 Data analysis ............................................................................................................... 71 Polarity consistency index ......................................................................................... 72 Determining geometrical feature significance........................................................... 72 Results .......................................................................................................... 73 Face-selective cells respond