imaging

Adventures in Spin Labeling: Clinical Perfusion Imaging and the Path to Technical Innovation

Arterial spin labeling (ASL) MRI has become a vital tool in clinical neuroimaging, enabling noninvasive assessment of cerebral perfusion across a range of conditions including stroke, vascular malformations, and brain tumors. With broader clinical adoption, its practical strengths — as well as important limitations — have become increasingly clear.

Nikolas Karalis

We are seeking a passionate and dedicated research technician to join our team Neuronal Circuits & Brain Dynamics at the Paris Brain Institute (ICM). Our work focuses on unraveling the fascinating mysteries of how the brain generates internal states and how neuromodulators, such as dopamine and serotonin, influence neuronal activity during behavior. To achieve our goals, we employ state-of-the-art techniques, including behavioral, optogenetic, imaging, electrophysiological, and genetic approaches in mice. Main Responsibilities • As a research technician, you are at the epicenter of our research activities and you will serve as a point of reference of the lab know-how across generations of lab members. • As a hands-on research technician, your primary responsibilities will include organizing the laboratory, maintaining basic lab infrastructure, performing routine tasks, regularly updating lab databases, ensuring the lab runs efficiently, and contributing to the team's research efforts. • Collaborating closely with the team, you will contribute to ongoing research projects and you will conduct behavioral and optogenetic experiments, carry out stereotaxic surgeries, and handle histological processing, including tissue slicing, immunostaining, and fluorescent microscopy. • You will be responsible for learning, developing, and passing on Standard Operating Procedures (SOPs) for the techniques utilized in our lab. • Additionally, in coordination with the head of the animal facility, you will supervise and ensure adherence to animal welfare guidelines, as well as maintain project permits and annual reports. • This role provides the opportunity to lead and participate in research projects to the extent of your desire. We offer competitive compensation and benefits within an interactive, interdisciplinary working environment, where cutting-edge science thrives and a dynamic, international research community awaits. As part of your role, you will receive extensive training in traditional and cutting-edge neuroscience techniques related to mice. If you are eager to join our vibrant research community and contribute to groundbreaking discoveries, we warmly welcome your application. The position is available immediately, with the potential for a permanent contract based on performance. If you would like to know more, visit our website: neuronaldynamics.eu and read about our team's mission and values. Why join our team • We are a young and vibrant group of scientists, fueled by curiosity and passion for understanding the brain. • We work as a team and use or invent cutting-edge neurotechnologies to answer fundamental questions in neuroscience. • Our team is committed to the training, mentorship, and career development of the next generation of neuroscientists. To achieve that, we foster an inclusive and supportive environment, where we can learn and advance science while having fun in the process. • Our work is multi-disciplinary, and so is our team. Irrespective of your background and project, our research environment will expose you to a diverse range of experimental and computational aspects of systems and circuits neuroscience. We thus encourage everyone to apply, especially those from underrepresented minorities. • Our team is affiliated with Inserm and is located in the Paris Brain Institute (ICM), where we have access to state-of-the-art facilities and resources. • Our vibrant community at the ICM and throughout Paris promotes broad collaboration and learning opportunities. <b>How to apply</b> If you are eager to join our vibrant research community and contribute to groundbreaking discoveries, we warmly welcome your application. The position is available immediately, with the potential for a permanent contract based on performance. Please send a statement of your past work and interests, your CV, and contact information for 1-3 references to the address: contact@neuronaldynamics.eu

Nikolas Karalis

We invite applications for postdoctoral researchers to join our team Neuronal Circuits & Brain Dynamics at the Paris Brain Institute (ICM) to study the principles of neuronal circuit organization and brain dynamics. If you are an ambitious and driven researcher, interested in experimental or computational systems and circuits neuroscience, and seeking an environment that fosters intellectual and professional growth, we invite you to consider joining our team. Together, we'll make a lasting impact on science and pave the way for your successful research career. Our team values diversity and welcomes researchers from all backgrounds and profiles. If your project ideas align with our research focus, we encourage you to get in touch with us. Research Topics We are interested in how neuronal circuits are organized and how the collective action of neurons gives rise to the emergent complex brain dynamics and behavior. We focus on how neurochemicals and bodily signals influence the brain. * We study how the simultaneous release of neuromodulators influences the activity of neurons and the coordination of brain regions * We also study how bodily signals, such as breathing, serve as fundamental elements of the oscillatory circuit architecture * We employ our approach to study the brain dynamics during behavior and sleep and their involvement in the transformation of fleeting experiences into long-term memories To answer these fundamental questions about the nature and function of the brain, we combine a range of cutting-edge neurotechnologies that enable us to observe and control the activity of the brain. We aim to identify and explore the fundamental principles of neural circuit organization and apply our understanding for the improvement of the human condition. Pure experimental, as well as computational/theoretical, or hybrid projects are available, depending on your interest and skills. Opportunities As a postdoctoral researcher in our group: • You will be an integral part of shaping our research direction and team culture. You will engage in exciting and meaningful research and will have access to all the tools necessary to push the boundaries of scientific exploration, with our cutting-edge techniques and state-of-the-art facilities. • You will have the opportunity to mentor graduate and master's students. This role enhances your leadership and communication skills while you contribute to the growth of the next generation of scientists. By guiding and collaborating with these aspiring researchers, you contribute to the collective knowledge and expertise of the team. Mentoring fosters a supportive and enriching atmosphere that reduces the mental strain of working alone on a project, as you can share ideas, problem-solve together, and gain fresh perspectives. • You will have ample opportunities to develop vital skills for your future academic career, such as mentoring, grant writing, presenting your work, publishing papers, and leading projects to completion. In parallel, you will gain invaluable first-hand experience in setting up and managing a young research team. • We encourage participation in conferences and workshops, where you can present your research findings to the wider scientific community. Why join our team • We are a young and vibrant group of scientists, fueled by curiosity and passion for understanding the brain. We work as a team and use or invent cutting-edge neurotechnologies to answer fundamental questions in neuroscience. • Our team is committed to the training, mentorship, and career development of the next generation of neuroscientists. To achieve that, we foster an inclusive and supportive environment, where we can learn and advance science while having fun in the process. • Our work is multi-disciplinary, and so is our team. Irrespective of your background and project, our research environment will expose you to a diverse range of experimental and computational aspects of systems and circuits neuroscience. We thus encourage everyone to apply, especially those from underrepresented minorities. • Working in our team will provide you with invaluable experience across all stages of research and you will have the opportunity to engage in experiment design and execution, method development, software design, and data analysis, as well as publishing and communicating research results. • Our team is affiliated with Inserm and is located in the Paris Brain Institute (ICM), where we have access to state-of-the-art facilities and resources. • Our vibrant community at the ICM and throughout Paris promotes broad collaboration and learning opportunities.

Nikolas Karalis

If you are a data scientist, programmer, or engineer, with a keen interest in helping to understand the brain, consider joining our team Neuronal Circuits & Brain Dynamics at the Paris Brain Institute (ICM). We study the principles of neuronal circuit organization and brain dynamics. Our work focuses on unraveling the fascinating mysteries of how the brain generates internal states and how neuromodulators, such as dopamine and serotonin, influence neuronal activity and communication between brain regions during behavior. To achieve our goals, we perform large-scale recordings from thousands of neurons simultaneously using multimodal recordings, including electrophysiological or optical imaging approaches. We employ state-of-the-art techniques, including behavioral, optogenetic, imaging, electrophysiological, and genetic approaches in mice to record and manipulate the brain activity during behavior. Using this unprecedented data, we will be able to understand information flow in the brain in ways that would be unimaginable only a few years ago. However, the scale and complexity of this data provide major challenges and unique opportunities. We are looking for computationally-orientated researchers to join our team as temporary or permanent staff members, to help us develop methods to interact and analyze our multi-dimensional neurophysiological and behavioral data, and to develop innovative analysis approaches and efficient processing pipelines, to accelerate the progress of our research on our path to understanding the brain. As a data analyst in our group, you will interact closely with experimentalists and contribute crucially to the research. Our team values diversity and welcomes researchers from all backgrounds and profiles. If your profile aligns with our research needs, we encourage you to get in touch with us. Main responsibilities • Organize data management pipeline • Analyze neurophysiological and behavioral data • Develop analysis methods and software tools to facilitate the analysis of multi-modal and multi-dimensional neurophysiological data • Implement cutting-edge data science approaches (statistical, computational, and ML) for complex neuroscience problems • Create robust and efficient data pipelines to extract, transform, and visualize data • Develop, test, and implement scientific software (e.g., for reproducible analysis pipelines and data storage) • Interact with experimentalists to design experiments and implement analyses • Analyze current technologies, algorithms, models, and methods • As part of your role, you will have the opportunity to collaborate with other teams, attend trainings, mentor students, have independent projects, and present at major relevant conferences (Cosyne, NeurIPS). We offer competitive compensation and benefits within an interactive, interdisciplinary working environment, where cutting-edge science thrives and a dynamic, international research community awaits.

Yao Chen, PhD

Yao Chen’s laboratory at Washington University in St. Louis is seeking a passionate Postdoctoral or staff/senior scientist/engineer who is interested in building innovative optical setups and making them useful for biological discovery. The candidate should have at least 2-3 years of experience developing optical instrumentation or microscopy methods, background in fluorescence imaging, and experience developing custom imaging software. The successful applicant will design, build, and characterize innovative optical instruments for fluorescence microscopy applications. The candidate will also have opportunities to perform optical imaging experiments and quantitative data analyses for neuroscience discovery, as well as contribute to writing research papers and grant applications. The projects in the lab aim to understand how the spatial and temporal features of signals inside the cell respond to neuromodulators (chemicals in the brain), behavior state transitions, and learning. The imaging experiments are often combined with optogenetics and electrophysiology. The candidate has access to cutting-edge instrumentation within the lab, numerous core facilities within Washington University, and will be part of a vibrant and collegial neuroscience and engineering community. We are committed to mentoring and offer a creative, thoughtful, and collaborative scientific environment. We welcome individuals who value rigor, innovation, and collegiality, and will value your creativity in shaping the projects. The lab consists of a mix of kind, fearless, and dedicated students, postdocs, and staff with diverse research and cultural backgrounds. In addition to performing their own innovative work, the candidate will have opportunities to collaborate with, learn from, and mentor other lab members. Our lab is a member of the Department of Neuroscience at Washington University School of Medicine in St. Louis, a large and collegial scientific community. WashU Neuroscience is consistently ranked as one of the top 10 places worldwide for neuroscience research. Additional information on being a postdoc at Washington University in St. Louis can be found at https://neuroscience.wustl.edu/education/postdoctoral-research/ and https://postdoc.wustl.edu/prospective-postdocs/ St. Louis is a city rich in culture, green spaces, free museums, world-class restaurants, and thriving music and arts scenes. On top of it all, St. Louis is affordable and commuting to Washington University’s campuses is stress-free, whether you go by foot, bike, public transit, or car. The area combines the attractions of a major city with affordable lifestyle opportunities. Washington University is dedicated to building a diverse community of individuals who are committed to contributing to an inclusive environment – fostering respect for all and welcoming individuals from diverse backgrounds, experiences and perspectives. Individuals with a commitment to these values are encouraged to apply. Minimum education & experience The appointee will have earned a Master’s degree (for staff scientist) or Ph.D. (for postdoctoral associate or senior scientist) by the time of starting the appointment. Applicants should submit their CV, a cover letter explaining their background and interest in the position, and whether they are applying to the scientist or postdoctoral position, as well as 3 references to Dr. Yao Chen (yaochen@wustl.edu).

Prof Paul Shaw

A postdoctoral position is available immediately in the lab of Dr. Paul Shaw in the Neuroscience Department at Washington University School of Medicine in St. Louis to study the molecular and cellular bases for sleep regulation, plasticity and memory consolidation in the fruit fly Drosophila melanogaster. Successful candidates will have the opportunity to learn and apply molecular, genetic, physiological, and behavioral tools to study mechanisms by which sleep might influence plasticity. Qualified applicants are expected to hold a recent doctoral degree in the biological sciences, or in related disciplines. Prior experience in working with flies and broad understanding of genetic principles are highly preferred. Highly competitive salary and benefits are available and will commensurate with experience. Washington University School of Medicine offers a highly collaborative, top-notch training and research environment in neuroscience and the biomedical sciences. Wash U’s community is a very active and highly regarded neuroscience community, and is an excellent training environment for postdoctoral fellows. Interested candidates should email their curriculum vitae, a letter of interest outlining experience and research goals, and the names and contact information of at least three references to shawp@wustl.edu EOE Washington University is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, age, sex, sexual orientation, gender identity or expression, national origin, genetic information, disability, or protected veteran status.

Arcadia Science

Job Description: Data scientist specializing in analysis of large, high-dimensional datasets and associated methods. Apply techniques from statistics, machine learning, and computational biology to a variety of datatypes and datasets from across Arcadia's research organisms. Datasets might range from genomics, multi-omics, imaging, time course, mass spectrometry, and neural recordings. Coordinate with experimentalists from experimental design all the way to publication. Work with our publishing team to build interactive, sharable resources for the scientific community. Our ideal candidate would have a history of contributions in analysis of complex datasets, a curiosity to work on a variety of problems and data types, and a passion for open science. They would be able to share their expertise both within and outside of Arcadia, and they would be able to translate difficult concepts into runnable, sharable analysis. The Arcadia Story: We are a research and development company leveraging the biology of emerging research organisms. We were founded by Seemay Chou and Prachee Avasthi, scientists convinced there is a better way to explore the full potential of science: how discoveries can be both meaningful and profitable. We are building a team of in-house scientists to carry out active research programs and convene a broader scientific community with a visiting scholars and internship program. Visit our website at www.arcadiascience.com to learn more about our work and check out Seemay’s founding story here.

Prof Richard Smith

The Smith lab is seeking team members to conduct exciting research in human neurodevelopment and models of neuronal activity in the prenatal brain. Interested applicants can expect to work in an environment that promotes autonomy and all the resources to develop and expand the several ongoing research projects of the lab. These include, but are not limited to, questions relating to human brain development, human disease modeling (using high throughput approaches), and therapeutics. Current NIH funded projects are examining ion flux and biophysical properties of developing cell types in the prenatal brain, specifically as is relates to childhood diseases. As a trainee you will have to opportunity gain expertise in several state-of the art approaches widely used to interrogate important aspects of neurodevelopment, including human stem cell cerebral organoid models, single cell sequencing (RNA/ATAC), high-content confocal microscopy/screening, ferret model of cortex development and hiPSC derived neuronal models (excitatory, dopamine, inhibitory). Additional physiology approaches include, 2-photon imaging, high-throughput electrophysiology, patch-clamp, and calcium/voltage imaging. Please visit our website for details about our research, www.rsmithlab.com

Prof Richard Smith

The Smith lab is seeking a team members to conduct exciting research in human neurodevelopment and models of neuronal activity in the prenatal brain. Interested applicants can expect to work in an environment that promotes autonomy and all the resources to develop and expand the several ongoing research projects of the lab. These include, but are not limited to, questions relating to human brain development, human disease modeling (using high throughput approaches), and therapeutics. Current NIH funded projects are examining ion flux and biophysical properties of developing cell types in the prenatal brain, specifically as is relates to childhood diseases. As a trainee you will have to opportunity gain expertise in several state-of the art approaches widely used to interrogate important aspects of neurodevelopment, including human stem cell cerebral organoid models, single cell sequencing (RNA/ATAC), high-content confocal microscopy/screening, ferret model of cortex development and hiPSC derived neuronal models (excitatory, dopamine, inhibitory). Additional physiology approaches include, 2-photon imaging, high-throughput electrophysiology, patch-clamp, and calcium/voltage imaging. Please visit our website for details about our research, www.rsmithlab.com

Kevin Bolding

We are recruiting lab personnel. If systems neuroscience at the intersection of olfaction and memory excites you, now is an excellent time to get in touch. Our goal is to discover fundamental rules and mechanisms that govern information storage and retrieval in neural systems. Our primary focus will be establishing the changes in neural circuit and population dynamics that correspond to odor recognition memory. To bring our understanding of this process to a new level of rigor we will apply quantitative statistical approaches to relate behavioral signatures of odor recognition to activity and plasticity in olfactory circuits. We will use in vivo electrophysiology and calcium imaging to capture the activity of large neural populations during olfactory experience, and we will apply cell-type specific perturbations of activity and plasticity to piece apart how specific circuit connections contribute.

Prof. Maria de la Paz Fernandez

A NIH-funded postdoctoral position is available in the Barnard Neurobiology Lab. Our lab is in the Department of Neuroscience & Behavior at Barnard College, a liberal arts college in Manhattan affiliated with Columbia University. Imaging facilities are available at Columbia’s Zuckerman Institute which is a few blocks away. The position is fully funded for at least four years. Ideally the position would start in the summer of 2021, but the start date is flexible. We are looking for a highly motivated and accomplished scientist interested in studying circadian timekeeping and sleep in Drosophila. The research project will involve the following techniques: - Genetic manipulation of neural networks supporting timekeeping and entrainment - Behavioral analysis of clock controlled behavioral outputs - Live-imaging and immunohistochemical analysis of clock neurons Desired qualifications: The candidate should have a Ph.D. in Biology, Neuroscience, Biochemistry, or a related field. Experience with live-imaging, immunohistochemistry, or Drosophila neurobiology is desired. However, all candidates with a track record of scientific accomplishment and a strong interest in circadian biology in any species are encouraged to apply. Please submit a CV and a cover letter explaining your research and career goals. Please also include the names and contact information for three professional references. contact: mfernand@barnard.edu Application Link: https://jobs.sciencecareers.org/job/547743/postdoctoral-research-fellow/

Prof. Li Zhaoping

Experiments on Rodent behavior and neural recording motivated by computational considerations, see https://webdav.tuebingen.mpg.de/agzl/data/Postdoc_Neursoscience_July_2020.pdf position open until filled.

Jörn Diedrichsen

The Diedrichsen Lab is looking to recruit a new postdoctoral associate with interest in studying the human cerebellum. The successful candidate will join an inter-disciplinary research group that uses behavioral, neuroimaging, and computational approaches to investigate the role of the cerebellum in motor control, cognition, and language. Our approach is to use Big Data and Machine Learning to gain insight about the overall functional organization of the cerebellum, which then informs targeted imaging and behavioural experiments. The enthusiastic and supportive environment will enable the candidate to develop their own research program.

Arun Antony MD

The Neuroscience Institute at Jersey Shore University Medical Center, New Jersey, USA is seeking a postdoctoral fellow to work on basic, clinical, and translational projects in the fields of seizures, epilepsy, human intracranial EEG, signal processing, cognition and consciousness. The fellow will join a multidisciplinary team of five epileptologists, neurosurgeons, epilepsy nurses, nurse practitioners, neuropsychologists and researchers providing holistic care to patients with epilepsy. The postdoctoral fellows will have access to the large clinical, imaging, and EEG databases, and outcome measures of cutting edge treatment modalities within the system for research purposes. The successful candidate will be well versed in data collection, processing, programming and will lead an independent research project working closely with collaborators and publish high-quality research.

N/A

The Department of Neurology at Jersey Shore University Medical Center, New Jersey, USA is seeking a full time postdoctoral candidate to work on basic, clinical and translational projects in the fields of seizures, epilepsy, human intracranial EEG, signal processing, and cognition. The researcher will join a multidisciplinary team of five epileptologists, neurosurgeons, epilepsy nurses, nurse practitioners, neuropsychologists and researchers providing holistic care to patients with epilepsy. The researcher will have access to the large clinical, imaging, and EEG data bases, and outcome measures within the system for research purposes. The successful candidate will be well versed in data collection, processing, programming and will lead an independent research project working closely with the collaborators.

Consciousness at the edge of chaos

Over the last 20 years, neuroimaging and electrophysiology techniques have become central to understanding the mechanisms that accompany loss and recovery of consciousness. Much of this research is performed in the context of healthy individuals with neurotypical brain dynamics. Yet, a true understanding of how consciousness emerges from the joint action of neurons has to account for how severely pathological brains, often showing phenotypes typical of unconsciousness, can nonetheless generate a subjective viewpoint. In this presentation, I will start from the context of Disorders of Consciousness and will discuss recent work aimed at finding generalizable signatures of consciousness that are reliable across a spectrum of brain electrophysiological phenotypes focusing in particular on the notion of edge-of-chaos criticality.

Computational bio-imaging via inverse scattering

Optical imaging is a major research tool in the basic sciences, and is the only imaging modality that routinely enables non-ionized imaging with subcellular spatial resolutions and high imaging speeds. In biological imaging applications, however, optical imaging is limited by tissue scattering to short imaging depths. This prevents large-scale bio-imaging by allowing visualization of only the outer superficial layers of an organism, or specific components isolated from within the organism and prepared in-vitro.

Convergent large-scale network and local vulnerabilities underlie brain atrophy across Parkinson’s disease stages

Spike train structure of cortical transcriptomic populations in vivo

The cortex comprises many neuronal types, which can be distinguished by their transcriptomes: the sets of genes they express. Little is known about the in vivo activity of these cell types, particularly as regards the structure of their spike trains, which might provide clues to cortical circuit function. To address this question, we used Neuropixels electrodes to record layer 5 excitatory populations in mouse V1, then transcriptomically identified the recorded cell types. To do so, we performed a subsequent recording of the same cells using 2-photon (2p) calcium imaging, identifying neurons between the two recording modalities by fingerprinting their responses to a “zebra noise” stimulus and estimating the path of the electrode through the 2p stack with a probabilistic method. We then cut brain slices and performed in situ transcriptomics to localize ~300 genes using coppaFISH3d, a new open source method, and aligned the transcriptomic data to the 2p stack. Analysis of the data is ongoing, and suggests substantial differences in spike time coordination between ET and IT neurons, as well as between transcriptomic subtypes of both these excitatory types.

Scaling Up Bioimaging with Microfluidic Chips

Explore how microfluidic chips can enhance your imaging experiments by increasing control, throughput, or flexibility. In this remote, personalized workshop, participants will receive expert guidance, support and chips to run tests on their own microscopes.

The SIMple microscope: Development of a fibre-based platform for accessible SIM imaging in unconventional environments

Advancements in imaging speed, depth and resolution have made structured illumination microscopy (SIM) an increasingly powerful optical sectioning (OS) and super-resolution (SR) technique, but these developments remain inaccessible to many life science researchers due to the cost, optical complexity and delicacy of these instruments. We address these limitations by redesigning the optical path using in-line fibre components that are compact, lightweight and easily assembled in a “Plug & Play” modality, without compromising imaging performance. They can be integrated into an existing widefield microscope with a minimum of optical components and alignment, making OS-SIM more accessible to researchers with less optics experience. We also demonstrate a complete SR-SIM imaging system with dimensions 300 mm × 300 mm × 450 mm. We propose to enable accessible SIM imaging by utilising its compact, lightweight and robust design to transport it where it is needed, and image in “unconventional” environments where factors such as temperature and biosafety considerations currently limit imaging experiments.

Non-invasive human neuroimaging studies of motor plasticity have predominantly focused on the cerebral cortex due to low signal-to-noise ration of blood oxygen level-dependent (BOLD) signals in subcortical structures and the small effect sizes typically observed in plasticity paradigms. Precision functional mapping can help overcome these challenges and has revealed significant and reversible functional alterations in the cortico-subcortical motor circuit during arm immobilization

Functional Imaging of the Human Brain: A Window into the Organization of the Human Mind

Neural circuits underlying sleep structure and functions

Sleep is an active state critical for processing emotional memories encoded during waking in both humans and animals. There is a remarkable overlap between the brain structures and circuits active during sleep, particularly rapid eye-movement (REM) sleep, and the those encoding emotions. Accordingly, disruptions in sleep quality or quantity, including REM sleep, are often associated with, and precede the onset of, nearly all affective psychiatric and mood disorders. In this context, a major biomedical challenge is to better understand the underlying mechanisms of the relationship between (REM) sleep and emotion encoding to improve treatments for mental health. This lecture will summarize our investigation of the cellular and circuit mechanisms underlying sleep architecture, sleep oscillations, and local brain dynamics across sleep-wake states using electrophysiological recordings combined with single-cell calcium imaging or optogenetics. The presentation will detail the discovery of a 'somato-dendritic decoupling'in prefrontal cortex pyramidal neurons underlying REM sleep-dependent stabilization of optimal emotional memory traces. This decoupling reflects a tonic inhibition at the somas of pyramidal cells, occurring simultaneously with a selective disinhibition of their dendritic arbors selectively during REM sleep. Recent findings on REM sleep-dependent subcortical inputs and neuromodulation of this decoupling will be discussed in the context of synaptic plasticity and the optimization of emotional responses in the maintenance of mental health.

Restoring Sight to the Blind: Effects of Structural and Functional Plasticity

Visual restoration after decades of blindness is now becoming possible by means of retinal and cortical prostheses, as well as emerging stem cell and gene therapeutic approaches. After restoring visual perception, however, a key question remains. Are there optimal means and methods for retraining the visual cortex to process visual inputs, and for learning or relearning to “see”? Up to this point, it has been largely assumed that if the sensory loss is visual, then the rehabilitation focus should also be primarily visual. However, the other senses play a key role in visual rehabilitation due to the plastic repurposing of visual cortex during blindness by audition and somatosensation, and also to the reintegration of restored vision with the other senses. I will present multisensory neuroimaging results, cortical thickness changes, as well as behavioral outcomes for patients with Retinitis Pigmentosa (RP), which causes blindness by destroying photoreceptors in the retina. These patients have had their vision partially restored by the implantation of a retinal prosthesis, which electrically stimulates still viable retinal ganglion cells in the eye. Our multisensory and structural neuroimaging and behavioral results suggest a new, holistic concept of visual rehabilitation that leverages rather than neglects audition, somatosensation, and other sensory modalities.

“A Focus on 3D Printed Lenses: Rapid prototyping, low-cost microscopy and enhanced imaging for the life sciences”

High-quality glass lenses are commonplace in the design of optical instrumentation used across the biosciences. However, research-grade glass lenses are often costly, delicate and, depending on the prescription, can involve intricate and lengthy manufacturing - even more so in bioimaging applications. This seminar will outline 3D printing as a viable low-cost alternative for the manufacture of high-performance optical elements, where I will also discuss the creation of the world’s first fully 3D printed microscope and other implementations of 3D printed lenses. Our 3D printed lenses were generated using consumer-grade 3D printers and pose a 225x materials cost-saving compared to glass optics. Moreover, they can be produced in any lab or home environment and offer great potential for education and outreach. Following performance validation, our 3D printed optics were implemented in the production of a fully 3D printed microscope and demonstrated in histological imaging applications. We also applied low-cost fabrication methods to exotic lens geometries to enhance resolution and contrast across spatial scales and reveal new biological structures. Across these applications, our findings showed that 3D printed lenses are a viable substitute for commercial glass lenses, with the advantage of being relatively low-cost, accessible, and suitable for use in optical instruments. Combining 3D printed lenses with open-source 3D printed microscope chassis designs opens the doors for low-cost applications for rapid prototyping, low-resource field diagnostics, and the creation of cheap educational tools.

Functional Plasticity in the Language Network – evidence from Neuroimaging and Neurostimulation

Efficient cognition requires flexible interactions between distributed neural networks in the human brain. These networks adapt to challenges by flexibly recruiting different regions and connections. In this talk, I will discuss how we study functional network plasticity and reorganization with combined neurostimulation and neuroimaging across the adult life span. I will argue that short-term plasticity enables flexible adaptation to challenges, via functional reorganization. My key hypothesis is that disruption of higher-level cognitive functions such as language can be compensated for by the recruitment of domain-general networks in our brain. Examples from healthy young brains illustrate how neurostimulation can be used to temporarily interfere with efficient processing, probing short-term network plasticity at the systems level. Examples from people with dyslexia help to better understand network disorders in the language domain and outline the potential of facilitatory neurostimulation for treatment. I will also discuss examples from aging brains where plasticity helps to compensate for loss of function. Finally, examples from lesioned brains after stroke provide insight into the brain’s potential for long-term reorganization and recovery of function. Collectively, these results challenge the view of a modular organization of the human brain and argue for a flexible redistribution of function via systems plasticity.

Recent views on pre-registration

A discussion on some recent perspectives on pre-registration, which has become a growing trend in the past few years. This is not just limited to neuroimaging, and it applies to most scientific fields. We will start with this overview editorial by Simmons et al. (2021): https://faculty.wharton.upenn.edu/wp-content/uploads/2016/11/34-Simmons-Nelson-Simonsohn-2021a.pdf, and also talk about a more critical perspective by Pham & Oh (2021): https://www.researchgate.net/profile/Michel-Pham/publication/349545600_Preregistration_Is_Neither_Sufficient_nor_Necessary_for_Good_Science/links/60fb311e2bf3553b29096aa7/Preregistration-Is-Neither-Sufficient-nor-Necessary-for-Good-Science.pdf. I would like us to discuss the pros and cons of pre-registration, and if we have time, I may do a demonstration of how to perform a pre-registration through the Open Science Framework.

Maladaptive Neuroplasticity in Cortico-limbic Structures: Insights from Surgical Pain Relief in Chronic Neuropathic Facial Pain

Spatio-temporal Regulation of Gene Expression in Neurons: Insights from Imaging mRNAs Live in Action

Structural & Functional Neuroplasticity in Children with Hemiplegia

About 30% of children with cerebral palsy have congenital hemiplegia, resulting from periventricular white matter injury, which impairs the use of one hand and disrupts bimanual co-ordination. Congenital hemiplegia has a profound effect on each child's life and, thus, is of great importance to the public health. Changes in brain organization (neuroplasticity) often occur following periventricular white matter injury. These changes vary widely depending on the timing, location, and extent of the injury, as well as the functional system involved. Currently, we have limited knowledge of neuroplasticity in children with congenital hemiplegia. As a result, we provide rehabilitation treatment to these children almost blindly based exclusively on behavioral data. In this talk, I will present recent research evidence of my team on understanding neuroplasticity in children with congenital hemiplegia by using a multimodal neuroimaging approach that combines data from structural and functional neuroimaging methods. I will further present preliminary data regarding functional improvements of upper extremities motor and sensory functions as a result of rehabilitation with a robotic system that involves active participation of the child in a video-game setup. Our research is essential for the development of novel or improved neurological rehabilitation strategies for children with congenital hemiplegia.

Circuit Mechanisms of Remote Memory

Memories of emotionally-salient events are long-lasting, guiding behavior from minutes to years after learning. The prelimbic cortex (PL) is required for fear memory retrieval across time and is densely interconnected with many subcortical and cortical areas involved in recent and remote memory recall, including the temporal association area (TeA). While the behavioral expression of a memory may remain constant over time, the neural activity mediating memory-guided behavior is dynamic. In PL, different neurons underlie recent and remote memory retrieval and remote memory-encoding neurons have preferential functional connectivity with cortical association areas, including TeA. TeA plays a preferential role in remote compared to recent memory retrieval, yet how TeA circuits drive remote memory retrieval remains poorly understood. Here we used a combination of activity-dependent neuronal tagging, viral circuit mapping and miniscope imaging to investigate the role of the PL-TeA circuit in fear memory retrieval across time in mice. We show that PL memory ensembles recruit PL-TeA neurons across time, and that PL-TeA neurons have enhanced encoding of salient cues and behaviors at remote timepoints. This recruitment depends upon ongoing synaptic activity in the learning-activated PL ensemble. Our results reveal a novel circuit encoding remote memory and provide insight into the principles of memory circuit reorganization across time.

Analyzing Network-Level Brain Processing and Plasticity Using Molecular Neuroimaging

Behavior and cognition depend on the integrated action of neural structures and populations distributed throughout the brain. We recently developed a set of molecular imaging tools that enable multiregional processing and plasticity in neural networks to be studied at a brain-wide scale in rodents and nonhuman primates. Here we will describe how a novel genetically encoded activity reporter enables information flow in virally labeled neural circuitry to be monitored by fMRI. Using the reporter to perform functional imaging of synaptically defined neural populations in the rat somatosensory system, we show how activity is transformed within brain regions to yield characteristics specific to distinct output projections. We also show how this approach enables regional activity to be modeled in terms of inputs, in a paradigm that we are extending to address circuit-level origins of functional specialization in marmoset brains. In the second part of the talk, we will discuss how another genetic tool for MRI enables systematic studies of the relationship between anatomical and functional connectivity in the mouse brain. We show that variations in physical and functional connectivity can be dissociated both across individual subjects and over experience. We also use the tool to examine brain-wide relationships between plasticity and activity during an opioid treatment. This work demonstrates the possibility of studying diverse brain-wide processing phenomena using molecular neuroimaging.

Towards open meta-research in neuroimaging

When meta-research (research on research) makes an observation or points out a problem (such as a flaw in methodology), the project should be repeated later to determine whether the problem remains. For this we need meta-research that is reproducible and updatable, or living meta-research. In this talk, we introduce the concept of living meta-research, examine prequels to this idea, and point towards standards and technologies that could assist researchers in doing living meta-research. We introduce technologies like natural language processing, which can help with automation of meta-research, which in turn will make the research easier to reproduce/update. Further, we showcase our open-source litmining ecosystem, which includes pubget (for downloading full-text journal articles), labelbuddy (for manually extracting information), and pubextract (for automatically extracting information). With these tools, you can simplify the tedious data collection and information extraction steps in meta-research, and then focus on analyzing the text. We will then describe some living meta-research projects to illustrate the use of these tools. For example, we’ll show how we used GPT along with our tools to extract information about study participants. Essentially, this talk will introduce you to the concept of meta-research, some tools for doing meta-research, and some examples. Particularly, we want you to take away the fact that there are many interesting open questions in meta-research, and you can easily learn the tools to answer them. Check out our tools at https://litmining.github.io/

“Open Raman Microscopy (ORM): A modular Raman spectroscopy setup with an open-source controller”

Raman spectroscopy is a powerful technique for identifying chemical species by probing their vibrational energy levels, offering exceptional specificity with a relatively simple setup involving a laser source, spectrometer, and microscope/probe. However, the high cost of Raman systems lacking modularity often limits exploratory research hindering broader adoption. To address the need for an affordable, modular microscopy platform for multimodal imaging, we present a customizable confocal Raman spectroscopy setup alongside an open-source acquisition software, ORM (Open Raman Microscopy) Controller, developed in Python. This solution bridges the gap between expensive commercial systems and complex, custom-built setups used by specialist research groups. In this presentation, we will cover the components of the setup, the design rationale, assembly methods, limitations, and its modular potential for expanding functionality. Additionally, we will demonstrate ORM’s capabilities for instrument control, 2D and 3D Raman mapping, region-of-interest selection, and its adaptability to various instrument configurations. We will conclude by showcasing practical applications of this setup across different research fields.

Sometimes more is not better: The case of medical imaging

En el diagnóstico médico por imágenes muchas veces los desarrollos técnicos se han concentrado en mejorar la calidad de las imágenes en términos de resolución espacial y/o temporal, lo cual muchas veces ha incrementado considerablemente los costos de estas prestaciones. Sin embargo, mejor resolución espacial y/o temporal de las imágenes médicas, no se traducen necesariamente en mejores diagnósticos o en diagnósticos más tempranos, y en algunos casos, nuevas capacidades diagnósticas no han demostrado un impacto en reducir la mortalidad asociada a las patologías. En esta presentación discutiremos como el impacto de las nuevas tecnologías en salud debe ser medido en términos del resultado clínico del paciente o la población afectada más que en parámetros asociados a la "calidad" de las imágenes.

Decomposing motivation into value and salience

Humans and other animals approach reward and avoid punishment and pay attention to cues predicting these events. Such motivated behavior thus appears to be guided by value, which directs behavior towards or away from positively or negatively valenced outcomes. Moreover, it is facilitated by (top-down) salience, which enhances attention to behaviorally relevant learned cues predicting the occurrence of valenced outcomes. Using human neuroimaging, we recently separated value (ventral striatum, posterior ventromedial prefrontal cortex) from salience (anterior ventromedial cortex, occipital cortex) in the domain of liquid reward and punishment. Moreover, we investigated potential drivers of learned salience: the probability and uncertainty with which valenced and non-valenced outcomes occur. We find that the brain dissociates valenced from non-valenced probability and uncertainty, which indicates that reinforcement matters for the brain, in addition to information provided by probability and uncertainty alone, regardless of valence. Finally, we assessed learning signals (unsigned prediction errors) that may underpin the acquisition of salience. Particularly the insula appears to be central for this function, encoding a subjective salience prediction error, similarly at the time of positively and negatively valenced outcomes. However, it appears to employ domain-specific time constants, leading to stronger salience signals in the aversive than the appetitive domain at the time of cues. These findings explain why previous research associated the insula with both valence-independent salience processing and with preferential encoding of the aversive domain. More generally, the distinction of value and salience appears to provide a useful framework for capturing the neural basis of motivated behavior.

Localisation of Seizure Onset Zone in Epilepsy Using Time Series Analysis of Intracranial Data

There are over 30 million people with drug-resistant epilepsy worldwide. When neuroimaging and non-invasive neural recordings fail to localise seizure onset zones (SOZ), intracranial recordings become the best chance for localisation and seizure-freedom in those patients. However, intracranial neural activities remain hard to visually discriminate across recording channels, which limits the success of intracranial visual investigations. In this presentation, I present methods which quantify intracranial neural time series and combine them with explainable machine learning algorithms to localise the SOZ in the epileptic brain. I present the potentials and limitations of our methods in the localisation of SOZ in epilepsy providing insights for future research in this area.

Trackoscope: A low-cost, open, autonomous tracking microscope for long-term observations of microscale organisms

Cells and microorganisms are motile, yet the stationary nature of conventional microscopes impedes comprehensive, long-term behavioral and biomechanical analysis. The limitations are twofold: a narrow focus permits high-resolution imaging but sacrifices the broader context of organism behavior, while a wider focus compromises microscopic detail. This trade-off is especially problematic when investigating rapidly motile ciliates, which often have to be confined to small volumes between coverslips affecting their natural behavior. To address this challenge, we introduce Trackoscope, an 2-axis autonomous tracking microscope designed to follow swimming organisms ranging from 10μm to 2mm across a 325 square centimeter area for extended durations—ranging from hours to days—at high resolution. Utilizing Trackoscope, we captured a diverse array of behaviors, from the air-water swimming locomotion of Amoeba to bacterial hunting dynamics in Actinosphaerium, walking gait in Tardigrada, and binary fission in motile Blepharisma. Trackoscope is a cost-effective solution well-suited for diverse settings, from high school labs to resource-constrained research environments. Its capability to capture diverse behaviors in larger, more realistic ecosystems extends our understanding of the physics of living systems. The low-cost, open architecture democratizes scientific discovery, offering a dynamic window into the lives of previously inaccessible small aquatic organisms.

How the brain barriers ensure CNSimmune privilege”

Britta Engelhard’s research is devoted to understanding thefunction of the different brain barriers in regulating CNS immunesurveillance and how their impaired function contributes toneuroinflammatory diseases such as Multiple Sclerosis (MS) orAlzheimer’s disease (AD). Her laboratory combines expertise invascular biology, neuroimmunology and live cell imaging and hasdeveloped sophisticated in vitro and in vivo approaches to studyimmune cell interactions with the brain barriers in health andneuroinflammation.

Why age-related macular degeneration is a mathematically tractable disease

Among all prevalent diseases with a central neurodegeneration, AMD can be considered the most promising in terms of prevention and early intervention, due to several factors surrounding the neural geometry of the foveal singularity. • Steep gradients of cell density, deployed in a radially symmetric fashion, can be modeled with a difference of Gaussian curves. • These steep gradients give rise to huge, spatially aligned biologic effects, summarized as the Center of Cone Resilience, Surround of Rod Vulnerability. • Widely used clinical imaging technology provides cellular and subcellular level information. • Data are now available at all timelines: clinical, lifespan, evolutionary • Snapshots are available from tissues (histology, analytic chemistry, gene expression) • A viable biogenesis model exists for drusen, the largest population-level intraocular risk factor for progression. • The biogenesis model shares molecular commonality with atherosclerotic cardiovascular disease, for which there has been decades of public health success. • Animal and cell model systems are emerging to test these ideas.

Toward globally accessible neuroimaging: Building the OSI2ONE MRI Scanner in Paraguay

The Open Source Imaging Initiative has recently released a fully open source low field MRI scanner called the OSI2ONE. We are currently building this system at the Universidad Paraguayo Alemana in Asuncion, Paraguay for a neuroimaging project at a clinic in Bolivia. I will discuss the process of construction, important considerations before you build, and future work planned with this device.

Probing neural population dynamics with recurrent neural networks

Large-scale recordings of neural activity are providing new opportunities to study network-level dynamics with unprecedented detail. However, the sheer volume of data and its dynamical complexity are major barriers to uncovering and interpreting these dynamics. I will present latent factor analysis via dynamical systems, a sequential autoencoding approach that enables inference of dynamics from neuronal population spiking activity on single trials and millisecond timescales. I will also discuss recent adaptations of the method to uncover dynamics from neural activity recorded via 2P Calcium imaging. Finally, time permitting, I will mention recent efforts to improve the interpretability of deep-learning based dynamical systems models.

Trends in NeuroAI - Brain-like topography in transformers (Topoformer)

Dr. Nicholas Blauch will present on his work "Topoformer: Brain-like topographic organization in transformer language models through spatial querying and reweighting". Dr. Blauch is a postdoctoral fellow in the Harvard Vision Lab advised by Talia Konkle and George Alvarez. Paper link: https://openreview.net/pdf?id=3pLMzgoZSA Trends in NeuroAI is a reading group hosted by the MedARC Neuroimaging & AI lab (https://medarc.ai/fmri | https://groups.google.com/g/medarc-fmri).

Navigating semantic spaces: recycling the brain GPS for higher-level cognition

Humans share with other animals a complex neuronal machinery that evolved to support navigation in the physical space and that supports wayfinding and path integration. In my talk I will present a series of recent neuroimaging studies in humans performed in my Lab aimed at investigating the idea that this same neural navigation system (the “brain GPS”) is also used to organize and navigate concepts and memories, and that abstract and spatial representations rely on a common neural fabric. I will argue that this might represent a novel example of “cortical recycling”, where the neuronal machinery that primarily evolved, in lower level animals, to represent relationships between spatial locations and navigate space, in humans are reused to encode relationships between concepts in an internal abstract representational space of meaning.

Characterizing the causal role of large-scale network interactions in supporting complex cognition

Neuroimaging has greatly extended our capacity to study the workings of the human brain. Despite the wealth of knowledge this tool has generated however, there are still critical gaps in our understanding. While tremendous progress has been made in mapping areas of the brain that are specialized for particular stimuli, or cognitive processes, we still know very little about how large-scale interactions between different cortical networks facilitate the integration of information and the execution of complex tasks. Yet even the simplest behavioral tasks are complex, requiring integration over multiple cognitive domains. Our knowledge falls short not only in understanding how this integration takes place, but also in what drives the profound variation in behavior that can be observed on almost every task, even within the typically developing (TD) population. The search for the neural underpinnings of individual differences is important not only philosophically, but also in the service of precision medicine. We approach these questions using a three-pronged approach. First, we create a battery of behavioral tasks from which we can calculate objective measures for different aspects of the behaviors of interest, with sufficient variance across the TD population. Second, using these individual differences in behavior, we identify the neural variance which explains the behavioral variance at the network level. Finally, using covert neurofeedback, we perturb the networks hypothesized to correspond to each of these components, thus directly testing their casual contribution. I will discuss our overall approach, as well as a few of the new directions we are currently pursuing.

Combined electrophysiological and optical recording of multi-scale neural circuit dynamics

This webinar will showcase new approaches for electrophysiological recordings using our silicon neural probes and surface arrays combined with diverse optical methods such as wide-field or 2-photon imaging, fiber photometry, and optogenetic perturbations in awake, behaving mice. Multi-modal recording of single units and local field potentials across cortex, hippocampus and thalamus alongside calcium activity via GCaMP6F in cortical neurons in triple-transgenic animals or in hippocampal astrocytes via viral transduction are brought to bear to reveal hitherto inaccessible and under-appreciated aspects of coordinated dynamics in the brain.

Evolution of convulsive therapy from electroconvulsive therapy to Magnetic Seizure Therapy; Interventional Neuropsychiatry

In April, we will host Nolan Williams and Mustafa Husain. Be prepared to embark on a journey from early brain stimulation with ECT to state-of-the art TMS protocols and magnetic seizure therapy! The talks will be held on Thursday, April 25th at noon ET / 6PM CET. Nolan Williams, MD, is an associate professor of Psychiatry and Behavioral Science at Stanford University. He developed the SAINT protocol, which is the first FDA-cleared non-invasive, rapid-acting neuromodulation treatment for treatment-resistant depression. Mustafa Husain, MD, is an adjunct professor of Psychiatry and Behavioral Sciences at Duke University and a professor of Psychiatry and Neurology at UT Southwestern Medical Center, Dallas. He will tell us about “Evolution of convulsive therapy from electroconvulsive therapy to Magnetic Seizure Therapy”. As always, we will also get a glimpse at the “Person behind the science”. Please register va talks.stimulatingbrains.org to receive the (free) Zoom link, subscribe to our newsletter, or follow us on Twitter/X for further updates!

Currents of Hope: how noninvasive brain stimulation is reshaping modern psychiatric care; Adapting to diversity: Integrating variability in brain structure and function into personalized / closed-loop non-invasive brain stimulation for substance use disorders

In March we will focus on TMS and host Ghazaleh Soleimani and Colleen Hanlon. The talks will talk place on Thursday, March 28th at noon ET – please be aware that this means 5PM CET since Boston already switched to summer time! Ghazaleh Soleimani, PhD, is a postdoctoral fellow in Dr Hamed Ekhtiari’s lab at the University of Minnesota. She is also the executive director of the International Network of tES/TMS for Addiction Medicine (INTAM). She will discuss “Adapting to diversity: Integrating variability in brain structure and function into personalized / closed-loop non-invasive brain stimulation for substance use disorders”. Colleen Hanlon, PhD, currently serves as a Vice President of Medical Affairs for BrainsWay, a company specializing in medical devices for mental health, including TMS. Colleen previously worked at the Medical University of South Carolina and Wake Forest School of Medicine. She received the International Brain Stimulation Early Career Award in 2023. She will discuss “Currents of Hope: how noninvasive brain stimulation is reshaping modern psychiatric care”. As always, we will also get a glimpse at the “Person behind the science”. Please register va talks.stimulatingbrains.org to receive the (free) Zoom link, subscribe to our newsletter, or follow us on Twitter/X for further updates!

Epileptic micronetworks and their clinical relevance

A core aspect of clinical epileptology revolves around relating epileptic field potentials to underlying neural sources (e.g. an “epileptogenic focus”). Yet still, how neural population activity relates to epileptic field potentials and ultimately clinical phenomenology, remains far from being understood. After a brief overview on this topic, this seminar will focus on unpublished work, with an emphasis on seizure-related focal spreading depression. The presented results will include hippocampal and neocortical chronic in vivo two-photon population imaging and local field potential recordings of epileptic micronetworks in mice, in the context of viral encephalitis or optogenetic stimulation. The findings are corroborated by invasive depth electrode recordings (macroelectrodes and BF microwires) in epilepsy patients during pre-surgical evaluation. The presented work carries general implications for clinical epileptology, and basic epilepsy research.

Learning produces a hippocampal cognitive map in the form of an orthogonalized state machine

Cognitive maps confer animals with flexible intelligence by representing spatial, temporal, and abstract relationships that can be used to shape thought, planning, and behavior. Cognitive maps have been observed in the hippocampus, but their algorithmic form and the processes by which they are learned remain obscure. Here, we employed large-scale, longitudinal two-photon calcium imaging to record activity from thousands of neurons in the CA1 region of the hippocampus while mice learned to efficiently collect rewards from two subtly different versions of linear tracks in virtual reality. The results provide a detailed view of the formation of a cognitive map in the hippocampus. Throughout learning, both the animal behavior and hippocampal neural activity progressed through multiple intermediate stages, gradually revealing improved task representation that mirrored improved behavioral efficiency. The learning process led to progressive decorrelations in initially similar hippocampal neural activity within and across tracks, ultimately resulting in orthogonalized representations resembling a state machine capturing the inherent struture of the task. We show that a Hidden Markov Model (HMM) and a biologically plausible recurrent neural network trained using Hebbian learning can both capture core aspects of the learning dynamics and the orthogonalized representational structure in neural activity. In contrast, we show that gradient-based learning of sequence models such as Long Short-Term Memory networks (LSTMs) and Transformers do not naturally produce such orthogonalized representations. We further demonstrate that mice exhibited adaptive behavior in novel task settings, with neural activity reflecting flexible deployment of the state machine. These findings shed light on the mathematical form of cognitive maps, the learning rules that sculpt them, and the algorithms that promote adaptive behavior in animals. The work thus charts a course toward a deeper understanding of biological intelligence and offers insights toward developing more robust learning algorithms in artificial intelligence.

Novel approaches to non-invasive neuromodulation for neuropsychiatric disorders; Effects of deep brain stimulation on brain function in obsessive-compulsive disorder

On Thursday, February 29th, we will host Damiaan Denys and Andrada Neacsiu. The talks will be followed by a shared discussion. You can register via talks.stimulatingbrains.org to receive the (free) Zoom link!

Blood-brain barrier dysfunction in epilepsy: Time for translation

The neurovascular unit (NVU) consists of cerebral blood vessels, neurons, astrocytes, microglia, and pericytes. It plays a vital role in regulating blood flow and ensuring the proper functioning of neural circuits. Among other, this is made possible by the blood-brain barrier (BBB), which acts as both a physical and functional barrier. Previous studies have shown that dysfunction of the BBB is common in most neurological disorders and is associated with neural dysfunction. Our studies have demonstrated that BBB dysfunction results in the transformation of astrocytes through transforming growth factor beta (TGFβ) signaling. This leads to activation of the innate neuroinflammatory system, changes in the extracellular matrix, and pathological plasticity. These changes ultimately result in dysfunction of the cortical circuit, lower seizure threshold, and spontaneous seizures. Blocking TGFβ signaling and its associated pro-inflammatory pathway can prevent this cascade of events, reduces neuroinflammation, repairs BBB dysfunction, and prevents post-injury epilepsy, as shown in experimental rodents. To further understand and assess BBB integrity in human epilepsy, we developed a novel imaging technique that quantitatively measures BBB permeability. Our findings have confirmed that BBB dysfunction is common in patients with drug-resistant epilepsy and can assist in identifying the ictal-onset zone prior to surgery. Current clinical studies are ongoing to explore the potential of targeting BBB dysfunction as a novel treatment approach and investigate its role in drug resistance, the spread of seizures, and comorbidities associated with epilepsy.

Trends in NeuroAI - Unified Scalable Neural Decoding (POYO)

Lead author Mehdi Azabou will present on his work "POYO-1: A Unified, Scalable Framework for Neural Population Decoding" (https://poyo-brain.github.io/). Mehdi is an ML PhD student at Georgia Tech advised by Dr. Eva Dyer. Paper link: https://arxiv.org/abs/2310.16046 Trends in NeuroAI is a reading group hosted by the MedARC Neuroimaging & AI lab (https://medarc.ai/fmri | https://groups.google.com/g/medarc-fmri).

Closed-loop deep brain stimulation as a neuroprosthetic of dopaminergic circuits – Current evidence and future opportunities; Spatial filtering to enhance signal processing in invasive neurophysiology

On Thursday February 15th, we will host Victoria Peterson and Julian Neumann. Victoria will tell us about “Spatial filtering to enhance signal processing in invasive neurophysiology”. Besides his scientific presentation on “Closed-loop deep brain stimulation as a neuroprosthetic of dopaminergic circuits – Current evidence and future opportunities”, Julian will give us a glimpse at the person behind the science. The talks will be followed by a shared discussion. Note: The talks will exceptionally be held at 10 ET / 4PM CET. You can register via talks.stimulatingbrains.org to receive the (free) Zoom link!

Neurovascular Interactions: Mechanisms, Imaging, Therapeutics

Trends in NeuroAI - Meta's MEG-to-image reconstruction

Trends in NeuroAI is a reading group hosted by the MedARC Neuroimaging & AI lab (https://medarc.ai/fmri). Title: Brain-optimized inference improves reconstructions of fMRI brain activity Abstract: The release of large datasets and developments in AI have led to dramatic improvements in decoding methods that reconstruct seen images from human brain activity. We evaluate the prospect of further improving recent decoding methods by optimizing for consistency between reconstructions and brain activity during inference. We sample seed reconstructions from a base decoding method, then iteratively refine these reconstructions using a brain-optimized encoding model that maps images to brain activity. At each iteration, we sample a small library of images from an image distribution (a diffusion model) conditioned on a seed reconstruction from the previous iteration. We select those that best approximate the measured brain activity when passed through our encoding model, and use these images for structural guidance during the generation of the small library in the next iteration. We reduce the stochasticity of the image distribution at each iteration, and stop when a criterion on the "width" of the image distribution is met. We show that when this process is applied to recent decoding methods, it outperforms the base decoding method as measured by human raters, a variety of image feature metrics, and alignment to brain activity. These results demonstrate that reconstruction quality can be significantly improved by explicitly aligning decoding distributions to brain activity distributions, even when the seed reconstruction is output from a state-of-the-art decoding algorithm. Interestingly, the rate of refinement varies systematically across visual cortex, with earlier visual areas generally converging more slowly and preferring narrower image distributions, relative to higher-level brain areas. Brain-optimized inference thus offers a succinct and novel method for improving reconstructions and exploring the diversity of representations across visual brain areas. Speaker: Reese Kneeland is a Ph.D. student at the University of Minnesota working in the Naselaris lab. Paper link: https://arxiv.org/abs/2312.07705

Imaging the subcortex; Microstructural and connectivity correlates of outcome variability in functional neurosurgery for movement disorders

We are very much looking forward to host Francisca Ferreira and Birte Forstmann on December 14th, 2023, at noon ET / 6PM CET. Francisca Ferreira is a PhD student and Neurosurgery trainee at the University College of London Queen Square Institute of Neurology and a Royal College of Surgeons “Emerging Leaders” program laureate. Her presentation title will be: “Microstructural and connectivity correlates of outcome variability in functional neurosurgery for movement disorders”. Birte Forstmann, PhD, is the Director of the Amsterdam Brain and Cognition Center, a Professor of Cognitive Neuroscience at the University of Amsterdam, and a Professor by Special Appointment of Neuroscientific Testing of Psychological Models at the University of Leiden. Besides her scientific presentation (“Imaging the human subcortex”), she will give us a glimpse at the “Person behind the science”. You can register via talks.stimulatingbrains.org to receive the (free) Zoom link!

Astrocyte reprogramming / activation and brain homeostasis

Astrocytes are multifunctional glial cells, implicated in neurogenesis and synaptogenesis, supporting and fine-tuning neuronal activity and maintaining brain homeostasis by controlling blood-brain barrier permeability. During the last years a number of studies have shown that astrocytes can also be converted into neurons if they force-express neurogenic transcription factors or miRNAs. Direct astrocytic reprogramming to induced-neurons (iNs) is a powerful approach for manipulating cell fate, as it takes advantage of the intrinsic neural stem cell (NSC) potential of brain resident reactive astrocytes. To this end, astrocytic cell fate conversion to iNs has been well-established in vitro and in vivo using combinations of transcription factors (TFs) or chemical cocktails. Challenging the expression of lineage-specific TFs is accompanied by changes in the expression of miRNAs, that post-transcriptionally modulate high numbers of neurogenesis-promoting factors and have therefore been introduced, supplementary or alternatively to TFs, to instruct direct neuronal reprogramming. The neurogenic miRNA miR-124 has been employed in direct reprogramming protocols supplementary to neurogenic TFs and other miRNAs to enhance direct neurogenic conversion by suppressing multiple non-neuronal targets. In our group we aimed to investigate whether miR-124 is sufficient to drive direct reprogramming of astrocytes to induced-neurons (iNs) on its own both in vitro and in vivo and elucidate its independent mechanism of reprogramming action. Our in vitro data indicate that miR-124 is a potent driver of the reprogramming switch of astrocytes towards an immature neuronal fate. Elucidation of the molecular pathways being triggered by miR-124 by RNA-seq analysis revealed that miR-124 is sufficient to instruct reprogramming of cortical astrocytes to immature induced-neurons (iNs) in vitro by down-regulating genes with important regulatory roles in astrocytic function. Among these, the RNA binding protein Zfp36l1, implicated in ARE-mediated mRNA decay, was found to be a direct target of miR-124, that be its turn targets neuronal-specific proteins participating in cortical development, which get de-repressed in miR-124-iNs. Furthermore, miR-124 is potent to guide direct neuronal reprogramming of reactive astrocytes to iNs of cortical identity following cortical trauma, a novel finding confirming its robust reprogramming action within the cortical microenvironment under neuroinflammatory conditions. In parallel to their reprogramming properties, astrocytes also participate in the maintenance of blood-brain barrier integrity, which ensures the physiological functioning of the central nervous system and gets affected contributing to the pathology of several neurodegenerative diseases. To study in real time the dynamic physical interactions of astrocytes with brain vasculature under homeostatic and pathological conditions, we performed 2-photon brain intravital imaging in a mouse model of systemic neuroinflammation, known to trigger astrogliosis and microgliosis and to evoke changes in astrocytic contact with brain vasculature. Our in vivo findings indicate that following neuroinflammation the endfeet of activated perivascular astrocytes lose their close proximity and physiological cross-talk with vasculature, however this event is at compensated by the cross-talk of astrocytes with activated microglia, safeguarding blood vessel coverage and maintenance of blood-brain integrity.

Trends in NeuroAI - Meta's MEG-to-image reconstruction

Trends in NeuroAI is a reading group hosted by the MedARC Neuroimaging & AI lab (https://medarc.ai/fmri). This will be an informal journal club presentation, we do not have an author of the paper joining us. Title: Brain decoding: toward real-time reconstruction of visual perception Abstract: In the past five years, the use of generative and foundational AI systems has greatly improved the decoding of brain activity. Visual perception, in particular, can now be decoded from functional Magnetic Resonance Imaging (fMRI) with remarkable fidelity. This neuroimaging technique, however, suffers from a limited temporal resolution (≈0.5 Hz) and thus fundamentally constrains its real-time usage. Here, we propose an alternative approach based on magnetoencephalography (MEG), a neuroimaging device capable of measuring brain activity with high temporal resolution (≈5,000 Hz). For this, we develop an MEG decoding model trained with both contrastive and regression objectives and consisting of three modules: i) pretrained embeddings obtained from the image, ii) an MEG module trained end-to-end and iii) a pretrained image generator. Our results are threefold: Firstly, our MEG decoder shows a 7X improvement of image-retrieval over classic linear decoders. Second, late brain responses to images are best decoded with DINOv2, a recent foundational image model. Third, image retrievals and generations both suggest that MEG signals primarily contain high-level visual features, whereas the same approach applied to 7T fMRI also recovers low-level features. Overall, these results provide an important step towards the decoding - in real time - of the visual processes continuously unfolding within the human brain. Speaker: Dr. Paul Scotti (Stability AI, MedARC) Paper link: https://arxiv.org/abs/2310.19812

Current and future trends in neuroimaging

With the advent of several different fMRI analysis tools and packages outside of the established ones (i.e., SPM, AFNI, and FSL), today's researcher may wonder what the best practices are for fMRI analysis. This talk will discuss some of the recent trends in neuroimaging, including design optimization and power analysis, standardized analysis pipelines such as fMRIPrep, and an overview of current recommendations for how to present neuroimaging results. Along the way we will discuss the balance between Type I and Type II errors with different correction mechanisms (e.g., Threshold-Free Cluster Enhancement and Equitable Thresholding and Clustering), as well as considerations for working with large open-access databases.

Inducing short to medium neuroplastic effects with Transcranial Ultrasound Stimulation

Sound waves can be used to modify brain activity safely and transiently with unprecedented precision even deep in the brain - unlike traditional brain stimulation methods. In a series of studies in humans and non-human primates, I will show that Transcranial Ultrasound Stimulation (TUS) can have medium- to long-lasting effects. Multiple read-outs allow us to conclude that TUS can perturb neuronal tissues up to 2h after intervention, including changes in local and distributed brain network configurations, behavioural changes, task-related neuronal changes and chemical changes in the sonicated focal volume. Combined with multiple neuroimaging techniques (resting state functional Magnetic Resonance Imaging [rsfMRI], Spectroscopy [MRS] and task-related fMRI changes), this talk will focus on recent human TUS studies.

Neural Mechanisms of Subsecond Temporal Encoding in Primary Visual Cortex

Subsecond timing underlies nearly all sensory and motor activities across species and is critical to survival. While subsecond temporal information has been found across cortical and subcortical regions, it is unclear if it is generated locally and intrinsically or if it is a read out of a centralized clock-like mechanism. Indeed, mechanisms of subsecond timing at the circuit level are largely obscure. Primary sensory areas are well-suited to address these question as they have early access to sensory information and provide minimal processing to it: if temporal information is found in these regions, it is likely to be generated intrinsically and locally. We test this hypothesis by training mice to perform an audio-visual temporal pattern sensory discrimination task as we use 2-photon calcium imaging, a technique capable of recording population level activity at single cell resolution, to record activity in primary visual cortex (V1). We have found significant changes in network dynamics through mice’s learning of the task from naive to middle to expert levels. Changes in network dynamics and behavioral performance are well accounted for by an intrinsic model of timing in which the trajectory of q network through high dimensional state space represents temporal sensory information. Conversely, while we found evidence of other temporal encoding models, such as oscillatory activity, we did not find that they accounted for increased performance but were in fact correlated with the intrinsic model itself. These results provide insight into how subsecond temporal information is encoded mechanistically at the circuit level.

Trends in NeuroAI - SwiFT: Swin 4D fMRI Transformer

Trends in NeuroAI is a reading group hosted by the MedARC Neuroimaging & AI lab (https://medarc.ai/fmri). Title: SwiFT: Swin 4D fMRI Transformer Abstract: Modeling spatiotemporal brain dynamics from high-dimensional data, such as functional Magnetic Resonance Imaging (fMRI), is a formidable task in neuroscience. Existing approaches for fMRI analysis utilize hand-crafted features, but the process of feature extraction risks losing essential information in fMRI scans. To address this challenge, we present SwiFT (Swin 4D fMRI Transformer), a Swin Transformer architecture that can learn brain dynamics directly from fMRI volumes in a memory and computation-efficient manner. SwiFT achieves this by implementing a 4D window multi-head self-attention mechanism and absolute positional embeddings. We evaluate SwiFT using multiple large-scale resting-state fMRI datasets, including the Human Connectome Project (HCP), Adolescent Brain Cognitive Development (ABCD), and UK Biobank (UKB) datasets, to predict sex, age, and cognitive intelligence. Our experimental outcomes reveal that SwiFT consistently outperforms recent state-of-the-art models. Furthermore, by leveraging its end-to-end learning capability, we show that contrastive loss-based self-supervised pre-training of SwiFT can enhance performance on downstream tasks. Additionally, we employ an explainable AI method to identify the brain regions associated with sex classification. To our knowledge, SwiFT is the first Swin Transformer architecture to process dimensional spatiotemporal brain functional data in an end-to-end fashion. Our work holds substantial potential in facilitating scalable learning of functional brain imaging in neuroscience research by reducing the hurdles associated with applying Transformer models to high-dimensional fMRI. Speaker: Junbeom Kwon is a research associate working in Prof. Jiook Cha’s lab at Seoul National University. Paper link: https://arxiv.org/abs/2307.05916

Prefrontal mechanisms involved in learning distractor-resistant working memory in a dual task

Working memory (WM) is a cognitive function that allows the short-term maintenance and manipulation of information when no longer accessible to the senses. It relies on temporarily storing stimulus features in the activity of neuronal populations. To preserve these dynamics from distraction it has been proposed that pre and post-distraction population activity decomposes into orthogonal subspaces. If orthogonalization is necessary to avoid WM distraction, it should emerge as performance in the task improves. We sought evidence of WM orthogonalization learning and the underlying mechanisms by analyzing calcium imaging data from the prelimbic (PrL) and anterior cingulate (ACC) cortices of mice as they learned to perform an olfactory dual task. The dual task combines an outer Delayed Paired-Association task (DPA) with an inner Go-NoGo task. We examined how neuronal activity reflected the process of protecting the DPA sample information against Go/NoGo distractors. As mice learned the task, we measured the overlap between the neural activity onto the low-dimensional subspaces that encode sample or distractor odors. Early in the training, pre-distraction activity overlapped with both sample and distractor subspaces. Later in the training, pre-distraction activity was strictly confined to the sample subspace, resulting in a more robust sample code. To gain mechanistic insight into how these low-dimensional WM representations evolve with learning we built a recurrent spiking network model of excitatory and inhibitory neurons with low-rank connections. The model links learning to (1) the orthogonalization of sample and distractor WM subspaces and (2) the orthogonalization of each subspace with irrelevant inputs. We validated (1) by measuring the angular distance between the sample and distractor subspaces through learning in the data. Prediction (2) was validated in PrL through the photoinhibition of ACC to PrL inputs, which induced early-training neural dynamics in well-trained animals. In the model, learning drives the network from a double-well attractor toward a more continuous ring attractor regime. We tested signatures for this dynamical evolution in the experimental data by estimating the energy landscape of the dynamics on a one-dimensional ring. In sum, our study defines network dynamics underlying the process of learning to shield WM representations from distracting tasks.

A synergistic core for human brain evolution and cognition

Virtual Brain Twins for Brain Medicine and Epilepsy

Over the past decade we have demonstrated that the fusion of subject-specific structural information of the human brain with mathematical dynamic models allows building biologically realistic brain network models, which have a predictive value, beyond the explanatory power of each approach independently. The network nodes hold neural population models, which are derived using mean field techniques from statistical physics expressing ensemble activity via collective variables. Our hybrid approach fuses data-driven with forward-modeling-based techniques and has been successfully applied to explain healthy brain function and clinical translation including aging, stroke and epilepsy. Here we illustrate the workflow along the example of epilepsy: we reconstruct personalized connectivity matrices of human epileptic patients using Diffusion Tensor weighted Imaging (DTI). Subsets of brain regions generating seizures in patients with refractory partial epilepsy are referred to as the epileptogenic zone (EZ). During a seizure, paroxysmal activity is not restricted to the EZ, but may recruit other healthy brain regions and propagate activity through large brain networks. The identification of the EZ is crucial for the success of neurosurgery and presents one of the historically difficult questions in clinical neuroscience. The application of latest techniques in Bayesian inference and model inversion, in particular Hamiltonian Monte Carlo, allows the estimation of the EZ, including estimates of confidence and diagnostics of performance of the inference. The example of epilepsy nicely underwrites the predictive value of personalized large-scale brain network models. The workflow of end-to-end modeling is an integral part of the European neuroinformatics platform EBRAINS and enables neuroscientists worldwide to build and estimate personalized virtual brains.

The melanopsin mosaic: exploring the diversity of non-image forming retinal ganglion cells

In this talk, I will focus on recent work that has uncovered the diversity of intrinsically photosensitive retinal ganglion cells (ipRGCs). These are a unique type of retinal ganglion cell that contains the photopigment melanopsin. ipRGCs are the retinal neurons responsible for driving non-imaging forming behaviors and reflexes, such as circadian entrainment and pupil constriction, amongst many others. My lab has recently focused on uncovering the diversity of ipRGCs, their distribution throughout the mammalian retina, and their axon projections in the brain.

From primate anatomy to human neuroimaging: insights into the circuits underlying psychiatric disease and neuromodulation; Large-scale imaging of neural circuits: towards a microscopic human connectome

On Thursday, October 26th, we will host Anastasia Yendiki and Suzanne Haber. Anastasia Yendiki, PhD, is an Associate Professor in Radiology at the Harvard Medical School and an Associate Investigator at the Massachusetts General Hospital and Athinoula A. Martinos Center. Suzanne Haber, PhD, is a Professor at the University of Rochester and runs a lab at McLean hospital at Harvard Medical School in Boston. She has received numerous awards for her work on neuroanatomy. Beside her scientific presentation, she will give us a glimpse at the “Person behind the science”. The talks will be followed by a shared discussion. You can register via talks.stimulatingbrains.org to receive the (free) Zoom link!

The role of CNS microglia in health and disease

Microglia are the resident CNS macrophages of the brain parenchyma. They have many and opposing roles in health and disease, ranging from inflammatory to anti-inflammatory and protective functions, depending on the developmental stage and the disease context. In Multiple Sclerosis, microglia are involved to important hallmarks of the disease, such as inflammation, demyelination, axonal damage and remyelination, however the exact mechanisms controlling their transformation towards a protective or devastating phenotype during the disease progression remains largely unknown until now. We wish to understand how brain microglia respond to demyelinating insults and how their behaviour changes in recovery. To do so we developed a novel histopathological analysis approach in 3D and a cell-based analysis tool that when applied in the cuprizone model of demyelination revealed region- and disease- dependent changes in microglial dynamics in the brain grey matter during demyelination and remyelination. We now use similar approaches with the aim to unravel sensitive changes in microglial dynamics during neuroinflammation in the EAE model. Furthermore, we employ constitutive knockout and tamoxifen-inducible gene-targeting approaches, immunological techniques, genetics and bioinformatics and currently seek to clarify the specific role of the brain resident microglial NF-κB molecular pathway versus other tissue macrophages in EAE.

Use of brain imaging data to improve prescriptions of psychotropic drugs - Examples of ketamine in depression and antipsychotics in schizophrenia

The use of molecular imaging, particularly PET and SPECT, has significantly transformed the treatment of schizophrenia with antipsychotic drugs since the late 1980s. It has offered insights into the links between drug target engagement, clinical effects, and side effects. A therapeutic window for receptor occupancy is established for antipsychotics, yet there is a divergence of opinions regarding the importance of blood levels, with many downplaying their significance. As a result, the role of therapeutic drug monitoring (TDM) as a personalized therapy tool is often underrated. Since molecular imaging of antipsychotics has focused almost entirely on D2-like dopamine receptors and their potential to control positive symptoms, negative symptoms and cognitive deficits are hardly or not at all investigated. Alternative methods have been introduced, i.e. to investigate the correlation between approximated receptor occupancies from blood levels and cognitive measures. Within the domain of antidepressants, and specifically regarding ketamine's efficacy in depression treatment, there is limited comprehension of the association between plasma concentrations and target engagement. The measurement of AMPA receptors in the human brain has added a new level of comprehension regarding ketamine's antidepressant effects. To ensure precise prescription of psychotropic drugs, it is vital to have a nuanced understanding of how molecular and clinical effects interact. Clinician scientists are assigned with the task of integrating these indispensable pharmacological insights into practice, thereby ensuring a rational and effective approach to the treatment of mental health disorders, signaling a new era of personalized drug therapy mechanisms that promote neuronal plasticity not only under pathological conditions, but also in the healthy aging brain.

Learning with multimodal enrichment

BrainLM Journal Club

Connor Lane will lead a journal club on the recent BrainLM preprint, a foundation model for fMRI trained using self-supervised masked autoencoder training. Preprint: https://www.biorxiv.org/content/10.1101/2023.09.12.557460v1 Tweeprint: https://twitter.com/david_van_dijk/status/1702336882301112631?t=Q2-U92-BpJUBh9C35iUbUA&s=19

Quality of life after DBS; Non-motor effects of DBS and quality of life

It’s our pleasure to announce that we will host Haidar Dafsari and Günther Deuschl on September 28th at noon ET / 6PM CET. Haidar Dafsari, MD, is a researcher and lecturer at the University Hospital Cologne. Günther Deuschl, MD, PhD, is a professor at Kiel University. He was president of the International Movement Disorders Society (MDS) from 2011-2013, Editor in Chief of the journal Movement Disorders and has been awarded numerous high-class awards. Beside his scientific presentation, he will give us a glimpse at the “Person behind the science”.The talks will be followed by a shared discussion. You can register via talks.stimulatingbrains.org to receive the (free) Zoom link!

Controlled sampling of non-equilibrium brain dynamics: modeling and estimation from neuroimaging signals

Bernstein Conference 2024

Equal contribution of place cells and non-place cells to the position decoding from one-photon imaging calcium transients

Bernstein Conference 2024

A novel and highly sensitive statistical test for calcium imaging

Towards predicting Stroke Etiology from MRI and CT Imaging Data of Ischemic Stroke Patients

Bernstein Conference 2024

Automated processing of calcium imaging videos for densely labeled dendritic and somatic ROIs

COSYNE 2022

A latent model of calcium activity outperforms alternatives at removing behavioral artifacts in two-channel calcium imaging

COSYNE 2022

A latent model of calcium activity outperforms alternatives at removing behavioral artifacts in two-channel calcium imaging

COSYNE 2022

Calcium imaging-based brain-computer interface for investigating long-term neuronal code dynamics

COSYNE 2023

Improved estimation of latent variable models from calcium imaging data

COSYNE 2023

maskNMF: a denoise-sparsen-detect pipeline for demixing dense imaging data faster than real time

COSYNE 2023

On-line SEUDO for real-time cell recognition in Calcium Imaging

COSYNE 2023

Computation Within and Beyond the Brain - Uncovering Brain-Body-Wide Communication Networks through Imaging Cellular Activity of All Cells in a Vertebrate

COSYNE 2025

3D-imaging reveals conserved cerebrospinal fluid drainage via meningeal lymphatic vasculature in mice and humans

The 6-zone track: A novel spatial memory test for awake head-fixed Ca2+ imaging

Activity alterations of various brain regions in Alcohol intoxicated drivers: a systematic review and Meta analysis of functional magnetic resonance imaging studies

Ante-mortem magnetic resonance imaging grey-white matter contrast regional signatures of Alzheimer’s disease neuropathology

A Calcium Imaging Based Brain-Machine Interface for Virtual Navigation

Calcium imaging to determine the pathogenic effects of NMDAR antibodies in autoimmune encephalitis

Capturing dynamics of inhibitory synaptic connectivity underlying learning using in vivo two-photon optical imaging of hippocampal CA1

Characterisation of the neural correlates of central sensitisation induced by the high frequency stimulation (HFS) model in healthy humans using functional magnetic resonance imaging (fMRI)

Characterisation of seizure-spreading depolarisation interactions in awake-headfixed mice using multisite graphene solution-gated field effect transistor arrays combined with Ca2+ imaging

Characterization of brain networks using functional ultrasound imaging

Characterizing patterns of dendritic activity in awake behaving mice using Arboreal Scanning, a multiscale 3D imaging approach

Chronic functional ultrasound imaging combined with behavior tracking on freely moving rats performing spatial exploration

CITE-On: Cell Identification and Trace Extraction Online in functional two-photon calcium imaging

Combining high-resolution functional Ultrasound (fUS)- and fMRI-imaging in the same human subject

Comparing clearing methods and imaging procedures in light sheet microscopy

Cortical deficit in discrimination between communication sounds in a mouse lacking two-pore channels: a calcium imaging and electrophysiological study

Cost function masking artificially inflates group level differences in processing of magnetic resonance imaging data for pathological patient populations

A custom cranial window implant for long-term whole-brain functional ultrasound imaging in behaving mice

Deciphering neuronal and synaptic architecture using new methods for labeling, imaging and segmenting neuronal cells via Standard and Super Resolution Microscopy

Deep brain imaging of axon initial segment dynamics during associative fear learning

Detection of cerebral aneurysm and intracranial vertebral dissection using non-enhanced magnetic resonance imaging in emergency setting: emphasis on magnitude image of susceptibility-weighted image

Dual color imaging in freely-behaving rodents using head-mountable one photon miniscope

Elucidating the neuronal population code of sound location at the inferior colliculus of awake mice using a fast volumetric calcium imaging approach

Encoding of spatial long term memories in a neural network: understanding fear generalization with miniscope calcium imaging

Evaluation of repetitive mild traumatic brain injury by fluorescence and FDG PET imaging

Examining dendritic plasticity of the barrel cortex layer 4 neurons via in vivo high spatiotemporal-resolution imaging

Fiber photometry imaging of locus coeruleus norepinephrine activities for studying neuromodulatory spatiotemporal dynamics across sleep and wakefulness

Calcium imaging-based brain-computer interface in freely behaving mice

Bernstein Conference 2024