[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-128164-en":3,"doc-seo-128164-105":31,"detail-sidebar-cat-0-en-105":92},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":20,"is_deleted":4,"is_public":21,"is_downloadable":21,"audit_status":21,"page_count":22,"language":23,"language_code":24,"site_id":25,"html_lang":24,"table_of_contents":26,"faqs":27,"seo_title":28,"seo_description":14,"update_tm":29,"read_time":30},128164,549768072016,"River Wang","https://ap-avatar.wpscdn.com/davatar_155a257f0dc6eb9ab79c44ca47cae57d",8,"Research & Report","Efficient Neural Representations in Spatial Navigation and Pharmacokinetic Imaging - Information-Theoretic and Machine Learning Approaches","Mammalian spatial navigation relies on specialized neurons, such as place and grid cells, to encode position from self-motion and environmental cues. Existing approaches to spatial information often evaluate single-neuron encoding, leaving efficiency and population-level representation less understood. This dissertation introduces information-theoretic measures for multi-neuron encoding efficiency, including joint stimulus information for neuron pairs and spectral-stimulus information for arbitrary populations. Spectral-stimulus information is maximized with localized, non-overlapping firing fields and is used to train recurrent neural networks via self-supervised learning to yield place and head direction cells. It further applies functional ultrasound imaging with machine learning models to analyze drug pharmacokinetics. ","University of Tennessee, Knoxville  \nTRACE: Tennessee Research and Creative Exchange  \n\n| Doctoral Dissertations | Graduate School |\n| --- | --- |\n| 5-2025\u003Cbr>Efficient Neural Representations in Spatial Navigation and Pharmacokinetic Imaging: Information-Theoretic and Machine Learning Approaches\u003Cbr>Jared Deighton\u003Cbr>The University of Tennessee, [jdeighto@vols.utk.edu](jdeighto@vols.utk.edu)\u003Cbr>Follow this and additional works at: [https://trace.tennessee.edu/utk_graddiss](https://trace.tennessee.edu/utk_graddiss)\u003Cbr> Part of the Artificial Intelligence and Robotics Commons, Other Applied Mathematics Commons, and the Theory and Algorithms Commons |  |\n\nRecommended Citation  \nDeighton, Jared, \"Efficient Neural Representations in Spatial Navigation and Pharmacokinetic Imaging: Information-Theoretic and Machine Learning Approaches. \" PhD diss., University of Tennessee, 2025. [https://trace.tennessee.edu/utk_graddiss/12347](https://trace.tennessee.edu/utk_graddiss/12347)  \nThis Dissertation is brought to you for free and open access by the Graduate School at TRACE: Tennessee Research and Creative Exchange. It has been accepted for inclusion in Doctoral Dissertations by an authorized administrator of TRACE: Tennessee Research and Creative Exchange. For more information, please contact [trace@utk.edu](trace@utk.edu).  \nTo the Graduate Council:  \nI am submitting herewith a dissertation written by Jared Deighton entitled \"Efficient Neural Representations in Spatial Navigation and Pharmacokinetic Imaging: Information-Theoretic and Machine Learning Approaches.\" I have examined the final electronic copy of this dissertation for form and content and recommend that it be accepted in partial fulfillment of the requirements for the degree of Doctor of Philosophy, with a major in Mathematics.  \nVasileios Maroulas, Major Professor  \nWe have read this dissertation and recommend its acceptance: Catherine Schuman, Ioannis Sgouralis, Piotr J. Franaszczuk  \nAccepted for the Council: Dr. Amy Cathey  \nVice Provost and Dean of the Graduate School  \n(Original signatures are on file with official student records.)  \nEfficient Neural Representations in Spatial Navigation and Pharmacokinetic Imaging:  \nInformation-Theoretic and Machine Learning Approaches  \nA Dissertation Presented for the Doctor of Philosophy  \nDegree  \nThe University of Tennessee, Knoxville  \nJared Deighton  \nMay 2025  \n© by Jared Deighton, 2025 All Rights Reserved.  \nii  \n“I will not say: do not weep; for not all tears are an evil.” - Gandalf, The Return of the  \nKing by J.R.R Tolkien  \nAcknowledgments  \nI want to thank my parents, Jeremy and Heather, for everything, including their endless reminders to “stay safe, get smart, and love others.” Thank you, Alison, my sister, for believing in me, showing me how to succeed, and always seeing the bright side.  \nI also want to thank my advisor, Dr. Vasileios Maroulas, for guiding my studies and growth as a researcher, as well as Dr. Piotr Franaszczuk, Dr. Catherine Schuman, and Dr. Ioannis Sgouralis for serving on my dissertation committee. Furthermore, I would like to thank my elementary school teachers, high school teachers, professors, and anyone else who invested their time and energy in my learning.  \nTo my friends, both new and old, whose fellowship kept me going through twenty years of learning, I thank you. This includes Camren Turner, Isaiah Keeler, Tucker Besch, Kyle Harkema, Matthew Blanker, Chris Ralph, Zach Reitsma, Kevin Sisco, Brett O’Brien, Peter Simala, Jonathan Kalman, Jacob Nguyen, Chiara Mattamira, Patrick Gillespie, Brittany Story, Wyatt Mackey, and Hayden Everett.  \nFinally, I want to thank my fianc´ee, Samantha, for her unwavering love and support, without which I would falter.  \nThis work has been partially supported by the U.S. Army Research Laboratory Cooperative Agreement No. W911NF-21-2-0186 .  \nAbstract  \nMammalian spatial navigation relies on specialized neurons, such as place and grid cells, which encode positio","cbCaip4Tju17fcMe","https://ap.wps.com/l/cbCaip4Tju17fcMe","pdf",30557789,2,1,104,"English","en",105,"# Abstract\n## Information-theoretic measures for neural populations\n## Self-supervised training of recurrent neural networks\n## Functional ultrasound imaging and pharmacokinetic analysis","[{\"question\":\"What is the main goal of the dissertation's neural coding contribution?\",\"answer\":\"To quantify how efficiently populations of neurons encode stimuli using new information-theoretic measures that go beyond single-neuron analyses.\"},{\"question\":\"How does the spectral-stimulus information relate to firing-field organization?\",\"answer\":\"It is maximized when neurons develop localized, non-overlapping firing fields, matching key behaviors of biological place and head direction cells.\"},{\"question\":\"How are these measures used in machine learning models?\",\"answer\":\"They enable self-supervised training of recurrent neural networks, which then exhibit emergent place-cell and head-direction-cell-like activity.\"}]","Efficient Neural Representations in Spatial Navigation and Pharmacokinetic Imaging - Information-Theoretic and Machine Learning Approaches | PDF",1785945210,262,{"code":4,"msg":32,"data":33},"ok",{"site_id":25,"language":24,"slug":34,"title":13,"keywords":35,"description":14,"schema_data":36,"social_meta":87,"head_meta":89,"extra_data":91,"updated_unix":29},"efficient-neural-representations-in-spatial-navigation-and-pharmacokinetic-imaging-information-theoretic-and-machine-learning-approaches","",{"@graph":37,"@context":86},[38,54,69],{"@type":39,"itemListElement":40},"BreadcrumbList",[41,45,48,51],{"item":42,"name":43,"@type":44,"position":21},"https://docshare.wps.com","Home","ListItem",{"item":46,"name":47,"@type":44,"position":20},"https://docshare.wps.com/document/","Document",{"item":49,"name":12,"@type":44,"position":50},"https://docshare.wps.com/document/research-report/",3,{"item":52,"name":13,"@type":44,"position":53},"https://docshare.wps.com/document/efficient-neural-representations-in-spatial-navigation-and-pharmacokinetic-imaging-information-theoretic-and-machine-learning-approaches/128164/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":24,"description":14,"dateModified":62,"datePublished":63,"encodingFormat":61,"isAccessibleForFree":64,"interactionStatistic":65},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":42,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-28","2026-08-05",true,{"@type":66,"interactionType":67,"userInteractionCount":20},"InteractionCounter",{"@type":68},"ViewAction",{"@type":70,"mainEntity":71},"FAQPage",[72,78,82],{"name":73,"@type":74,"acceptedAnswer":75},"What is the main goal of the dissertation's neural coding contribution?","Question",{"text":76,"@type":77},"To quantify how efficiently populations of neurons encode stimuli using new information-theoretic measures that go beyond single-neuron analyses.","Answer",{"name":79,"@type":74,"acceptedAnswer":80},"How does the spectral-stimulus information relate to firing-field organization?",{"text":81,"@type":77},"It is maximized when neurons develop localized, non-overlapping firing fields, matching key behaviors of biological place and head direction cells.",{"name":83,"@type":74,"acceptedAnswer":84},"How are these measures used in machine learning models?",{"text":85,"@type":77},"They enable self-supervised training of recurrent neural networks, which then exhibit emergent place-cell and head-direction-cell-like activity.","https://schema.org",{"og:url":52,"og:type":88,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":90,"canonical":52},"index,follow",{"doc_id":7,"site_id":25},{"code":4,"msg":5,"data":93},[94,98,102,106,111,116,121,124,129,132,136],{"id":21,"doc_module":4,"doc_module_name":47,"category_name":95,"show_sort_weight":96,"slug":97},"Story & Novel",90,"story-novel",{"id":20,"doc_module":4,"doc_module_name":47,"category_name":99,"show_sort_weight":100,"slug":101},"Literature",80,"literature",{"id":53,"doc_module":4,"doc_module_name":47,"category_name":103,"show_sort_weight":104,"slug":105},"Exam",70,"exam",{"id":107,"doc_module":4,"doc_module_name":47,"category_name":108,"show_sort_weight":109,"slug":110},5,"Comic",60,"comic",{"id":112,"doc_module":4,"doc_module_name":47,"category_name":113,"show_sort_weight":114,"slug":115},6,"Technology",50,"technology",{"id":117,"doc_module":4,"doc_module_name":47,"category_name":118,"show_sort_weight":119,"slug":120},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":47,"category_name":12,"show_sort_weight":122,"slug":123},30,"research-report",{"id":125,"doc_module":4,"doc_module_name":47,"category_name":126,"show_sort_weight":127,"slug":128},9,"Religion & Spirituality",20,"religion-spirituality",{"id":127,"doc_module":4,"doc_module_name":47,"category_name":130,"show_sort_weight":127,"slug":131},"World Cup","world-cup",{"id":133,"doc_module":4,"doc_module_name":47,"category_name":134,"show_sort_weight":133,"slug":135},10,"Lifestyle","lifestyle",{"id":137,"doc_module":4,"doc_module_name":47,"category_name":138,"show_sort_weight":107,"slug":139},19,"General","general"]