Welcome message from the organizers

General anesthesia is a drug-induced, reversible condition comprised of five behavioral states: unconsciousness, amnesia (loss of memory), antinociception (loss of pain sensation), akinesia (immobility), and hemodynamic stability with control of the stress response. Our work shows that a primary mechanism through which anesthetics create these altered states of arousal is by initiating and maintaining highly structured oscillations. These oscillations impair communication among brain regions. We illustrate this effect by presenting findings from our human and non-human primate studies using high-density EEG recordings and intracranial recordings. These studies have allowed us to give a detailed characterization of the neurophysiology of loss and recovery of consciousness due to propofol, and more recently ketamine. We show how these dynamics change systematically with different anesthetic classes and with age. As a consequence, we have developed a principled, neuroscience-based paradigm for using the EEG to monitor the brain states of patients receiving general anesthesia. We demonstrate that the state of general anesthesia can be rapidly reversed by activating specific brain circuits. Finally, we demonstrate that the state of general anesthesia can be controlled using closed-loop feedback control systems. The success of our research has depended critically on tight coupling of experiments, signal processing research and mathematical modeling. Biography of the speaker: Emery N. Brown, M.D., Ph.D. is the Edward Hood Taplin Professor of Medical Engineering and Computational Neuroscience at MIT; the Warren M. Zapol Professor of Anaesthesia at Harvard Medical School; and an anesthesiologist at Massachusetts General Hospital (MGH). He received his B.A. in Applied Mathematics (magna cum laude) from Harvard College, his M.A. and Ph.D. in statistics from Harvard University and his M.D. (magna cum laude) from Harvard Medical School. Professor Brown completed his internship in internal medicine at the Brigham and Women’s Hospital and his anesthesiology residency at MGH. Professor Brown is an anesthesiologist-statistician whose research is defining the neuroscience of how anesthetics produce the states of general anesthesia. He also develops statistical methods for neuroscience data analysis. Professor Brown is a fellow of the IEEE, the American Association for the Advancement of Science, the American Academy of Arts Sciences, and the National Academy of Inventors. He is a member of the National Academy of Medicine, National Academy of Sciences, and the National Academy of Engineering.


Welcome Message from the Organizers
Dear Friends and Colleagues, Welcome to the 2023 International Conference on Brain Informatics (BI'23). It is our great pleasure and privilege to welcome you to Hoboken, New Jersey, USA! The conference program reflects the intellectual richness that the area can offer in the interdisciplinary and multidisciplinary fields of brain informatics. On behalf of the BI'23 Conference Committees, we would like to appreciate your participation and do hope that you will enjoy the conference technical and social programs.
Brain informatics (BI) started the exploration as a research field with the vision of studying the brain from the perspective of informatics. Firstly, BI combines the efforts of neuroscience, cognitive science, medicine and life sciences, data science, artificial intelligence (AI), neuroimaging technologies, and information and communication technologies (ICT) to study the brain as a general information processing system. Secondly, new informatics equipment, techniques and platforms are causing a revolution to understand the brain. Thirdly, starting from its proposal as a field, BI is with the goal of inspiring future AI, especially Web Intelligence (WI, i.e. AI in the connected world). The BI conference provides a premier international forum to bring together researchers and practitioners from diverse fields for presentation of original research results, as well as exchange and dissemination of innovative and practical development experiences on BI. The main theme of BI'23 is Brain Science meets Artificial Intelligence with respect to the five tracks: Cognitive and Computational Foundations of Brain Science; Human Information Processing Systems; Brain Big Data Analytics, Curation and Management; Informatics Paradigms for Brain and Mental Health Research; and Brain-Machine Intelligence and Brain-Inspired Computing.
The series of BI conferences started with the WICI International Workshop on Web Intelligence Meets Brain Informatics, held in Beijing, China in 2006. The 2nd, 3rd, 4th and 5th BI conferences were held in Beijing China (2009), Toronto Canada (2010), Lanzhou China (2011), and Macau China (2012, respectively. Since 2013, health was added to the conference title as Brain Informatics and Health (BIH) with an emphasis on real-world applications of brain research in human health and well-being. The BIH13, BIH14, BIH15, and BIH16 were held at Maebashi Japan, Warsaw Poland, London UK, and Omaha USA, respectively. In 2017, the conference went back to its original design and vision to investigate the brain from informatics perspective and to promote brain-inspired information technology revolution. Thus, the conference name was changed back to Brain Informatics at Beijing, China in 2017. In 2018, the conference was held in Arlington, Texas, USA. In 2019, this grand event was held in Haikou, Hainan, China. In 2020 and 2021, the conference was held online. In 2022, the conference resumed offline and was held in Padova-Italy & Brisbane-Australia in a hybrid way. In 2023, this world-class event is held in Hoboken, New Jersey, USA during August 1st-3rd. The BI'23 conference is hosted by Stevens Institute of Technology. The BI'23 solicited high-quality papers and keynote talks with world-class speakers, workshops, and special sessions. The BI'23 involves several world leaders in brain research as keynote speakers, including Drs. Emery N. Brown, Bin He, John Ngai, Helen Mayberg, Vinod Goel, Amy Kuceyeski, Grace M. Hwang, Paul Sajda. The BI'23 conference promotes transformative research to inspire novel conceptual paradigms and innovative technologies and designs that will benefit society. In particular, big data analytics, machine learning and AI technologies are transforming the BI research and facilitating their real-world BI applications. New data fusion and AI methodologies are developed to enhance human interpretive powers when dealing with big neuroimaging data sets, including fMRI, PET, MEG, EEG and fNIRS, as well as data from other sources like eye-tracking and wearable, portable, micro and nano devices. BI research creates and implements various tools to analyze all the data and establish a more comprehensive understanding of human thought, memory, learning, decision-making, emotion, consciousness and social behaviors. These methods and related studies will also assist in building brain-inspired intelligence, brain-inspired computing, human-level wisdom-computing paradigms and technologies, improving the treatment efficacy of mental health and brain disorders.
On behalf of the BI'23 Conference Committees, we would like to thank all authors, presenters, keynote speakers, panelists, workshop/special session organizers, and all members of the International Program Committee for their substantive contributions towards the high quality of the BI'23 conference. We would like to thank the sponsors for their valuable support. Organizing such a major event would not be possible without a solid organization, and without the efforts of many people. We are extraordinarily appreciative for the tremendous and most effective administrative and secretarial support from the local host and local organizing team. We would like to thank all who contributed to the success of this great meeting. We thank you for your participation and support of BI'23! We encourage you to explore many excellent technical programs and network events during the BI'23 conference. Hope you enjoy the conference and will have fond memories in Hoboken, New Jersey! July 19, 2023 The organizing committee 3

Facilities at the Presentation Room
Each presentation room is equipped with a video projector (without PC). It is suggested that attendees bring their own laptops and USB disks to the presentation rooms.

Presentation Time
The time allocated to each presentation is: • 20 minutes for Type I full paper (15 to 17 minutes for the presentation plus 3 to 5 minutes for discussions) • 15 minutes for Type II abstract (10 to 12 minutes for the presentation plus 3 to 5 minutes for discussions) • For presentations in Workshops / Special Sessions, the time is flexible (please confirm the time with Workshops / Special Sessions Organizers)

Tips for Presenters
• Please check the time and location for your presentation in advance, and get to the venue a little earlier.
• Please leave time for discussions (questions and answers) after your oral presentation.  Abstract: General anesthesia is a drug-induced, reversible condition comprised of five behavioral states: unconsciousness, amnesia (loss of memory), antinociception (loss of pain sensation), akinesia (immobility), and hemodynamic stability with control of the stress response. Our work shows that a primary mechanism through which anesthetics create these altered states of arousal is by initiating and maintaining highly structured oscillations. These oscillations impair communication among brain regions. We illustrate this effect by presenting findings from our human and non-human primate studies using high-density EEG recordings and intracranial recordings. These studies have allowed us to give a detailed characterization of the neurophysiology of loss and recovery of consciousness due to propofol, and more recently ketamine. We show how these dynamics change systematically with different anesthetic classes and with age. As a consequence, we have developed a principled, neuroscience-based paradigm for using the EEG to monitor the brain states of patients receiving general anesthesia. We demonstrate that the state of general anesthesia can be rapidly reversed by activating specific brain circuits. Finally, we demonstrate that the state of general anesthesia can be Professor Brown is an anesthesiologist-statistician whose research is defining the neuroscience of how anesthetics produce the states of general anesthesia. He also develops statistical methods for neuroscience data analysis.
Professor Brown is a fellow of the IEEE, the American Association for the Advancement of Science, the American Academy of Arts Sciences, and the National Academy of Inventors. He is a member of the National Academy of Medicine, National Academy of Sciences, and the National Academy of Engineering. Abstract: Brain activity is distributed over the 3-dimensional volume and evolves in time. Mapping spatio-temporal distribution of brain activation with high spatial resolution and high temporal resolution is of great importance for understanding the brain and aiding in the clinical diagnosis and management of brain disorders. Electrophysiological source imaging from noninvasively recorded electroencephalogram (EEG) has played a significant role in advancing our ability to image brain function and dysfunction. We will discuss how AI/ML can greatly facilitate addressing technical challenges in electrophysiological source imaging, and applications to mapping brain activation from EEG in drug-resistant epilepsy patients. We will introduce and discuss clinical implications of our recently developed AI-based source imaging technology in which deep neural networks are integrated with neural mass models to achieve high-resolution spatio-temporal source imaging of epileptogenic networks, from scalp recorded EEG (and MEG).

Biography of the speaker: Bin He is a Trustee Professor of Biomedical Engineering at Carnegie
Mellon University. He's major research interests include electrophysiological neuroimaging, braincomputer interface, and neuromodulation. He's pioneering and sustained contributions has helped establish electroencephalography (EEG) as a modern 3-dimensional functional neuroimaging modality for source localization and imaging of spatio-temporal brain activity and functional connectivity. He's lab has also made significant contributions to noninvasive brain-computer interface and focused ultrasound neuromodulation. He is a Fellow of the National Academy of Inventors (NAI), Innovative Neurotechnologies® (BRAIN) Initiative is an ambitious program whose mission is to develop and apply new technologies to answer fundamental questions about the brain and to find new treatments for human brain disorders. Launched in 2013, the BRAIN Initiative supports research on understanding neural circuit function by developing novel tools and applying innovate techniques to precisely map and observe brain circuits. Building on initial successes, the BRAIN Initiative is investing in large-scale projects that will transform the landscape and potential for neuroscience research. These programs will (1) generate a comprehensive atlas detailing the cell type composition of the human brain; (2) develop scalable technologies for generating whole mammalian brain connectivity maps at different scales and resolution; and (3) develop, validate, and disseminate new tools for precision access to brain cell types across species. Together these projects promise to deliver new resources and tools for interrogating and modulating neural circuit activity and will support established programs focused on understanding the circuit basis of behavior in a diversity of model This alternative approach has ignited interest in non-von Neuman architectures and new types of brainlike learning algorithms and systems. I will highlight recent innovations that illustrate a potential convergence among neuromorphic hardware design, brain-like learning algorithms, and engineered organoids, which I refer to as convergence intelligence. I will present relevant federal funding opportunities and strategies along with my personal outlook for how advances in convergence intelligence could translate to many domains, including improvements in brain-body interfaces, neural recording and neuromodulation technologies. The basic idea I advocate is that, while we have a reasoning mind that sets us apart from bats and baboons, this reasoning mind does not float above the biology. It is not powered by angel dust. It evolved on top of, and is integrated into, the neurobiology we inherited from our common ancestors with bats and baboons. That is, our reasoning mind is tethered to evolutionary older systems such as the autonomic, instinctive, and associative systems.

Biography of the speaker:
Taking this idea seriously leads to a model of tethered rationality whereby the autonomic, the instinctive, associative, and reasoning systems all have an input into behavior. The response generated by each system is in the common currency of feelings, with valence, arousal, and duration components.
This allows for communication across systems and the generation of a blended response. The control structure is set up to maximize pleasure and minimize pain or displeasure. There is no central executive in charge. The reasoning system has an input into the response, but so do the other systems. Individual differences in behavior are explained not just in terms of individual differences at the level of beliefs and desires, but also individual differences at the level of the autonomic, instinctive, and associative systems.
Such an account drives human behavior back into the biology, where it belongs, and provides a richer set of tools to understand how we pursue food, sex, and politics.  Neural Networks (ANNs). These networks, originally inspired by biological neural networksspecifically, how the human brain processes visual information -have proved remarkably useful for classification or regression problems of many types. Meanwhile, in the field of neuroscience, researchers have incorporated ANNs into "encoding models" that predict neural responses to visual stimuli and, furthermore, have been shown to reflect structure and function of the visual processing pathway. This observation has led to speculation that primate ventral visual stream may have evolved to be an optimal system for object recognition/detection in the same way that ANNs are identifying optimal computational architectures. Here, we introduce NeuroGen, a novel encoding/generative model architecture designed to synthesize realistic images predicted to maximize or minimize activation in pre-selected regions of the human visual cortex. We then apply this framework as a discovery architecture to amplify differences in regional and individual brain response patterns to visual stimuli, and, furthermore, use it to generate synthetic images predicted to modulate brain regions' responses in a controlled way. Finally, we present some recent work showing that synthetic images produced by NeuroGen can actually produce desired target brain activation responses, thus performing macro-scale, non-invasive neuromodulation in humans.

Biography of the speaker: Amy Kuceyeski is an Associate Professor of Mathematics and
Neuroscience in Radiology at Weill Cornell Medicine and the Computational Biology Department at Cornell University. She is the director of the Computational Connectomics (CoCo) Laboratory and the Machine Learning in Medicine group at Cornell. Over the past 14 years, she has been working to understand the human brain using quantitative modeling approaches, including machine learning, to map anatomical and physiological characteristics to behavior. Specifically, she is interested in understanding how brains recover from injury so we can devise strategies, possibly via non-invasive neuromodulation, to support natural recovery processes. She also performs research at the intersection of biological and artificial neural networks that aims to understand how human brains process incoming visual information.

Volunteers
You may ask Volunteers for help. They will be happy to help you.

About Hoboken Location
Hoboken is a New Jersey city on the Hudson River. Its former industrial port now features parks such as Pier A Park, with Manhattan skyline views. The Hudson River Waterfront Walkway links several green spaces. Global eateries, bistros and bars cluster on Washington Street and riverside Frank Sinatra Drive, named after the locally born singer.

Time
Hoboken is using the Eastern Time of United States. Greenwich Mean Time is 4 hours ahead of Hoboken.

Hotel Reservation
✓ Lodging Stay at the UCC dorm room of Stevens Institute of Technology: Guest rooms are available. All guest rooms have their own bathroom (the suites with four guests have two bathrooms) and a kitchenette with a stovetop and convection oven. New dorms at Stevens Institute of Technology offer breathtaking views of NYC skyline.
To book, please send email to the local chair Dr. Feng Liu (fliu22@stevens.edu) ✓ Hotels Near Stevens with a discounted rate.
• Sheraton Lincoln Harbor Hotel (500 Harbor Blvd, Weehawken, NJ 07086): Admire the views of New York City from the banks of the Hudson River at Sheraton Lincoln Harbor Hotel.
• Here is a Booking link with discount pricing.
This hotel is within a walkable distance along the Hudson river (around 7 mins).
• Here is a Booking link with discount pricing.

Stevens Institute of Technology
The conference events will be held at the University Complex Center at Stevens Institute of Technology.