Episodit
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In this episode, our guest is Rotem Botvinik-Nezer, a postdoc at Dartmouth University, working with Dr. Tor Wager in his Cognitive and Affective Neuroscience Lab. In 2020, Dr. Botvinik-Nezer was first author of an influential paper published in Nature, titled Variability in the analysis of a single neuroimaging dataset by many teams, where the results were compared from 70 independent teams analyzing a single data set having 9 hypotheses. This paper made it clear that there are many points of variability in data analysis pipelines, and provided further incentives for sharing data and code to grow consensus and replicability. While the popular press suggested that this paper was yet another hit to fMRI, we discuss how even papers that critique the results of this seminal paper ultimately converge in agreement with the overall message of systematic transparency. Dr. Botvinik-Nezer also has a strong interest in how our brains influence our perception of pain, having just published a recent paper showing evidence that regions associated with painful stimuli remain active even when subjects experience less pain while having the belief that a placebo is effective.
In this conversation, Peter and Rotem delve into all these topics and more, but spend the bulk of the discussion on the interplay between choices in analyses, such as determining a statistical threshold, and variability in results. We also discuss incentives for users to share data and code and possible ways to create a more solid scaffolding for best practices.
Episode producers:
Omer Faruk Gulban
Xuqian Michelle Li
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Dr. Daniele Marinazzo is a full professor in the department of data analysis at the University of Ghent, in Belgium. For over a decade he has been showing us what further information and insight we may extract from brain imaging data - from EEG and MEG to fMRI. He is technically a statistical physicist, but in reality, he is a network neuroscientist and data modeler who is constantly pushing the envelope.
In this podcast he discusses some recent papers that go into how we might be able to improve the impact and relevance of new findings and models through careful benchmarking and well considered experimental design.
He talks about his desire to move from correlation to causation in functional connectivity studies, he discusses granger causality, as well as moving from pairwise correlation to multivariate correlation.
Furthermore, he delves into the limits of hemodynamics - limits that may be pushed back to a degree, as suggested by his compelling work showing that hemodynamic response function, which varies over space, may be estimated on a voxel-wise basis using resting state data alone.
His work in estimating and mapping the Excitation/Inhibition ratio in the brain by using gamma frequency coherence as a signature was also discussed. This has potentially profound clinical and research applications.
Lastly, his collaborative work with the European Human Brain Project towards the creation of the useful website, called ebrains (https://www.ebrains.eu), was discussed, which serves as a repository and tool for exploring shared data and code, as well as providing a user-friendly encapsulation of the project's collective effort.
It is an all-around fun, eye-opening discussion featuring an outstanding scientist who is not only deep in the trenches of network modelling, but also a strong proponent of open science and constant engagement across disciplines.
Episode producers:
Omer Faruk Gulban
Alfie Wearn
Stephania Assimopoulos
Referenced Papers:
Mika Rubinov. Circular and unified analysis in network neuroscience. eLife. 2023; 12:e79559. Doi: 10.7554/eLife.79559
Reid AT, et al. Advancing functional connectivity research from association to causation. Nat Neurosci. 2019 Nov;22(11):1751-1760. Doi: 10.1038/s41593-019-0510-4.
Valdes-Sosa PA et al. Effective connectivity: Influence, causality and biophysical modelling. Neuroimage. 2009; 58(2): 339-361. Doi: 10.1016/j.neuroimage.2011.03.058.
Wu GR, et al. A blind deconvolution approach to recover effective connectivity brain networks from resting state fMRI data. Medical Image Analysis. 2013; 17(3):365-374. Doi:
10.1016/j.media.2013.01.003.
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Today, we are excited to have Dr. Gang Chen on the podcast. Dr. Chen is the go-to statistics guru for the fMRI community at the NIH and a well-respected scientist worldwide. He is a staff scientist in the group that developed the AFNI software package. As an applied mathematician, Dr. Chen has written a series of insightful papers in the past seven years, bucking the status quo in fMRI processing - essentially saying that we are throwing away too much valuable information by thresholding our data, relying on overly simple and rigid models of the hemodynamic response, not mapping effect sizes, and using center of mass measures to describe clusters of activation. He backs it all up with a rigorous approach characterized by all good statisticians. He is a master in the art of casting a wide net to capture useful data without taking in artifact and noise, finding that sweet spot in data reduction to balance utility with sensitivity.
In this episode, we hear all about Dr. Chenâs perspectives through these papers, which are so important yet not widely known or embraced by the field. We hope you enjoy it!
Episode producers:
Omer Faruk Gulban
Xuqian Michelle Li
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In this episode, it's our pleasure to host Jack Wells who is a Wellcome Trust Career Development Fellow at the University College London Center for Advanced Biomedical Engineering. Dr. Wells received his Ph.D. in MRI in the Department of Medical Physics and Bioengineering at at University College London in 2010, and since he began his scientific career, he's been working at the interface of MRI methodology and neurophysiology - focusing on understanding the Cerebral Spinal Fluid dynamics and how they may relate to the Glymphatic system. He and his colleagues have been among the leaders in using MRI to image and characterize the glymphatic system as well as the brain - cerebrospinal fluid barrier. The glymphatic system is hypothesized to be the paravascular mechanism by which CSF is washed through brain tissue - typically during sleep - clearing out metabolic waste. It is an incompletely understood yet potentially profoundly important system where its dysfunction may be at the root of disorders that include Alzheimer's disease.
In this wonderful conversation we hear all about Jack's and others' work imaging and understanding the hydrodynamics and spatial organization of neurofluids in the brain.
We hope you enjoy this conversation as much as we did!
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If you are interested in working with Nathan, he is currently recruiting for a postdoc! Send your CV to [email protected]
Today our guest is Nathan Spreng. Dr. Spreng is the James McGill Professor of Neurology and Neurosurgery and Director of the Laboratory of Brain and Cognition at the Montreal Neurological Institute and Hospital at McGill University.
As an undergraduate, Dr. Spreng was initially interested in pursuing a major in poetry until he took a psychology class that sparked his interest in the brain. He received Ph.D. in 2008 from the University of Toronto in Brian Levine's lab, and post docs with Cheryl Grady at the University of Toronto and Dan Schacter at Harvard. After about 5 years as an assistant professor at Cornell University, he moved to McGill University.
Throughout his career Dr. Spreng has been using fMRI to reveal subtle yet repeatable large-scale brain networks as they relate attention, memory, cognitive control, and social cognition. He has also helped to elucidate the central role that the default network plays in self-generated thought, and in how it dynamically interacts with multiple systems in the brain.
In this episode Peter and Nathan have a far reaching conversation about his work and what it implies, covering his study of age dependence of resting state hippocampal-linked network ensembles, how to move from mapping networks to modeling and understanding mechanisms, the many possible clinical implications of his work, current understanding of Alzheimer's disease, our mutual appreciation for multi-echo EPI, his data release paper of a large multi-echo EPI and structural MRI data set, and much more.
Enjoy listening!
Episode producers:
Alfie Wearn
Omer Faruk Gulban
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It is our great pleasure and deep honor to host Dr. Marsel Mesulam who is a giant in the field of Neurology and one of founders of OHBM. Dr. Mesulam is Chief of Behavioral Neurology and the Ruth Dunbar Davee Professor of Neuroscience at Northwestern University Feinberg School of Medicine, and Professor of Behavioral Neurology at the Weinberg College of Arts and Sciences.
Dr. Mesulam received his MD from Harvard Medical School in 1972, and in 1976 completed residencies at Boston City Hospital and Beth Israel Deaconess Medical Center in Boston. After a 1 year postdoc at Harvard University he began his tenure in Chicago at Northwestern. Dr. Mesulam's work has been both prodigious and impactful over the years, as his almost 1000 papers have been cited over 140 thousand times. He has written the seminal book, Principles of Behavioral and Cognitive Neurology, and has produced many landmark papers - a few of which we'll discuss in the podcast. One paper that we consider a masterpiece was published in Brain in 1998 and titled From Sensation to Cognition. This can be considered as a required reading for everyone in the field of brain mapping as it lays out so concisely and eloquently, a breathtaking perspective of the structure and functional organization of the human brain.
Dr. Mesulam's research is extremely broad and diverse, having impacted such areas as neural networks and functional imaging, Dementia, Alzheimer's Disease, Primary Progressive Aphasia (PPA), Cholinergic Pathways, Acetylcholinesterase Studies, Cognitive Psychology, Neurology, and Neuropsychiatry. He also developed, early in his career, a neuronal marker, Tetramethyl benzidine, that profoundly impacted research in this area.
In this inspiring conversation, Peter and Marsel discuss his early career and what was important for his success, delve into research culture and the value of opportunistic research, and the value of having the freedom and resources to try many things and rapidly change directions that follow interesting leads. They also discuss some of the exciting early days of Neuroimaging and OHBM. Lastly, we go into some of his current research on Primary Progressive Aphasia (PPA) and the study of temporal pole disease as a window to temporal pole functional significance.
We hope that you enjoy this conversation.
Episode producers:
Alfie Wearn
Omer Faruk Gulban -
Dr. Rosenberg received her Ph.D. from the department of Psychology at Yale University, where she also carried out her post doc. In 2019, she started as an assistant professor in the Department of Psychology at the University of Chicago and is a member of the Chicago Neuroscience Institute. She has been pioneering the use of connectome-based predictive modeling to capture individual differences in the ability to sustain attention. Attention is fundamental to just about everything that we experience and do and how we navigate the world. It varies over time and each person has different abilities to maintain it. Monica has developed and used extensively a task known as gradCPT, an easy at first but hard to sustain, continuous attention task that allows moment to moment assessment of sustained attention. She has found two networks that characterize high attention vs lower attention, and these have been powerful for characterizing individuals ability to sustain attention. It's also been useful for characterizing differences in such attention-related skills such as reading comprehension. She's been delving further into both fMRI methodology and the nuances of attention ever since.
In this conversation we talk about her career development, the great environment at Yale, the development of her exciting and impactful fMRI-based human attention research. We hope you enjoy the conversation!
Episode producers:
Omer Faruk Gulban
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Today, we are excited to have Dr. Evan Gordon on the podcast. Evan is an assistant professor in the Neuroimaging Labs Research Center, based in the Mallinckrodt Institute of Radiology at the Washington University School of Medicine in St. Louis. Since joining the group and joining forces with what is known as the "midnight scan club," he has gone on a scientific tear, publishing several highly influential papers that make use of the unique high-fidelity data sets, containing up to 11 hours of resting state or task-activated fMRI data for each subject. This powerful approach in fMRI is known as "deep sampling." His findings include insights into unique individual connectivity patterns, the whole brain use of a novel parcellation approach using boundary maps, and most recently, discovery of effector-specific regions in motor cortex - a finding which is likely to replace in textbooks the classic Penfield maps of the homunculus.
This was a wonderful conversation where we explored the implementation, benefits, and potential of deep sampling of fMRI data! Evan is not only a creative and productive scientist, but a great conversationalist. We hope you enjoy it!
Episode producers:
Omer Faruk Gulban
Alfie Wearn
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Today, our guest is Shella Keilholz. Dr. Keilholz received her Bachelor's in Physics from Missouri University of Science and Technology in 1997, and her PhD in Engineering Physics from the University of Virginia in 2004. She went on to a do a post-doc at NIH in Dr. Alan Koretsky's lab and in 2004 joined the department of Biomedical Engineering at Emory University as a faculty member. She is now a full professor at Emory University and also closely affiliated with Georgia Tech.
Since around 2008 she has been uncovering new spatial and temporal patterns in resting state fMRI. She was the first to identify spatial propagation of wave-like behavior in the resting state time series and in 2011 coined the term quasi-periodic patterns (QPP) to describe whole brain networks that dominate much of the resting state signal. Recently, she and others have described three such patterns that account for most of the variance. Here we not only talk about her career but also delve into how these quasi-periodic patterns mesh with the current landscape of diverse features of resting state fMRI that continue to be found. She has shown that these patterns may have a central driver and may relate to such things as vasomotion, global signal, arousal state, and attention. In general, there is much more information from basic neurophysiology to cognition that remains to be derived from resting state fMRI, and Shella is among those leading the effort.
This was an incredibly stimulating and fun discission. We hope you enjoy it!
Episode producers:Omer Faruk Gulban
Jeff Mentch
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Today, we’re excited to have Alex Huth on the podcast. Alex is one of the more creative and insightful people in the field of brain imaging today as he has been forging new ground using naturalistic stimuli and voxelwise models to create intricate maps of semantic features across large swaths of the brain. His seminal 2016 paper in Nature brought his approach to prominence: https://www.nature.com/articles/nature17637
Here, Alex shares insights on the value of naturalistic stimuli on fMRI research and updates us on our current capabilities to decode brain activity. During this conversation Alex highlights an amazing tool to view semantic maps in the brain, which can be found here: https://gallantlab.org/viewer-huth-2016/
Alex received his bachelor’s in engineering and applied science from Cal Tec, where he was also working as an undergraduate researcher in Christoff Koch's lab. He continued on, receiving his Ph.D. in 2013 from University of California Berkeley, Helen Wills Neuroscience Institute, under the guidance of Dr.'s Christof Koch and Jack Gallant. He went on to do his post doc in the Gallant lab and finally moved to the University of Austin in 2017, where he is an assistant professor in computer science and neuroscience: https://www.cs.utexas.edu/~huth/ -
Today, our guest is Dr. Andrew Jahn.
Those of you learning MRI and fMRI analysis - which realistically, should be pretty much all of us - may already know about the amazing resources that he is prodigiously producing online. Starting with "Andy's Brain Blog" in 2012, expanding to videos (over 300 of them), and now his current project, "Andy's Brain Book", Dr. Jahn has been steadily creating a standard and a go-to resource for all of us to learn the nuts and bolts as well as concepts and nuances of processing our data.
Dr. Jahn received his Bachelors in Psychology in 2008 from Carleton College, and his Ph.D. in Cognitive Neuroscience at Indiana University in 2015. He did a postdoc at the Haskins Laboratories at Yale University, and is now a professor at the University of Michigan, in Ann Arbor. There he has been given the freedom to expand his extremely valuable teaching resources.
In this podcast we discuss how he got started in this, how perhaps failing to get a post-undergraduate position at the NIH started him down this path. We discuss the educational resources that he has been producing, and how he draws upon luminaries from Jaque Barzun to Dave Berry for inspiration. We also discuss the wider issue of education in neuroimaging - what can be taught and what cannot and have an open-ended conversation on the future of neuroimaging as well as some of his own planned future projects.
This was a truly fun and enlightening discussion! We hope you enjoy it!
Episode producers:
Alfie Wearn Omer Faruk GulbanBrain Art
Artist: Laura Bundesen Title: Colors of hope -
In this episode our guest is Dr. Russ Poldrack who has been so influential to the fields of fMRI, cognitive neuroscience, and brain imaging in general for the past 30+ years. Russ is the Albert Ray Lang Professor of Psychology at Stanford University and Director of the Center for Open and Reproducible Science. Over the years, he has helped elevate how we do fMRI by creating resources and standards for sharing data and code. He is also working to advance the precision with which we think about task design and data interpretation through his Cognitive Atlas project, which is a knowledge base for cognitive neuroscience.
Russ Poldrack received his Bachelors in Psychology from Baylor University in 1989, and his Ph.D. from the University of Illinois, Urbana/Champaign in 1995. After a postdoc at Stanford, he started, in 1999, as an assistant professor at Harvard University and Mass General Hospital, in 2002 he moved to UCLA, then in 2009, he became the director of the imaging research center at the University of Texas at Austin. Finally, in 2014 he was recruited to Stanford, where he has been ever since.
In this discussion, Peter and Russ look back into some of the paradigm shifts in fMRI best practices that Russ helped foster, as well as some of the big picture challenges that we face when using brain imaging, modeling, and precision task design to derive new insights into brain organization and mechanisms of computation. Here, Russ also weighs in on the prospects of fMRI for biomarker derivation and the exciting potential for single subject deep imaging.
Peter mentioned to Russ that this was one of the fastest hours he has experienced in quite some time as it was an engrossing discussion.
Enjoy listening!
Episode producers
Jeff Mentch
Omer Faruk Gulban
Brain Art
Artist: Mia Coutinho
Title: Represent, Connect, Empower
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Organization for Human Brain Mapping (OHBM) 2023 live podcast session hosted by Alfie Wearn on site during the conference.
In this episode, our guests Ana LuĂsa Pinho, Enrico Amico, Tim Laumann, and Emily Finn discuss mapping individual differences in the human brain.
Enjoy listening!
Episode producers:
Alfie Wearn
Omer Faruk Gulban
Jeff Mentch
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A brand new season of Neurosalience! This year production of podcast will be in the safe hands of Ămer Faruk GĂŒlban.
Here, Faruk turns the microphone around onto our trusty host, PeterBandettini, to talk about all Peterâs favorite moments of last season, some interesting updates about the âDIANAâ paper (discussed in Season 3 Episode 4), and future plans for your favorite brain mapping podcast.
Enjoy Season 4!
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In the final episode of Season 3 of Neurosalience, Peter chats with Michele Thiebaut de Shotten. Michele is a full professor at the French National Center for Scientific Research in Paris where he heads the Brain Connectivity and Behavior Lab and the Neurofunctional Imaging Group. On top of all this he is Editor in Chief of the journal Brain Structure and Function and, this year, has been the President of the Organization for Human Brain Mapping.
Having over 15 years of experience in neuropsychology and brain connectivity neuroimaging, he has established himself as a leader in the field with work that spans everything including development, evolution, methodology, and theory. He has been a pioneer in probing brain connectivity and disconnectivity, starting in 2005 with a paper published in science showing that spatial neglect is a consequence of the disruption of communication between the frontal and the parietal lobes, and thus should be considered as a disconnection syndrome. Since then, he has been a highly prolific producer of creative, insightful, and high impact work exploring and characterizing structural and functional brain connectivity.
Here we talk about the development of his career and his ideas as well as the importance of thinking of the brain from a connectivity perspective. We delve into some of his recent papers, including one that highlights differences in various MRI methods to measure myelin, and finally, we discuss how OHBM has evolved along with the role of the president of OHBM, as well as a few things that the meeting has in store for this year.
Episode producers:
Omer Faruk Gulban
Alfie Wearn
Please send any feedback, guest suggestions, or ideas to [email protected]
Thank you for listening to this season of Neurosalience! We'll be back in a few months time with Season 4!
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The 2023 OHBM Annual Meeting is fast approaching! In addition to the fantastic scientific content organized by the Program Committee, many other committees and special interest groups (SIGs) host their own programs. At last yearâs Annual Meeting in Glasgow, committees and SIGs hosted events on inclusivity, mentorship, art, and much more.
In this podcast, Peter and Alfie highlight upcoming committee and SIG events at OHBM 2023.
Further information on all these events, including exact times and places, can be found in this accompanying blog post: <LINK TBC>
Other useful links:
SIGs
1. BrainArt:
https://ohbm-brainart.github.io/
2. Open Science:
https://ossig.netlify.app/
3. Student and Postdoc:
https://www.ohbmtrainees.com/
4. Sustainability and Environmental Action:
https://ohbm-environment.org/
5. Women in OHBM:
https://www.ohbmbrainmappingblog.com/blog/announcing-the-launch-of-the-women-in-ohbm-special-interest-group recentblog post
COMMITTEES
1. Diversity and Inclusion:
Kid's live review: https://ohbm-dic.github.io/kidsreview/2023/
2. Education:
https://www.humanbrainmapping.org/i4a/pages/index.cfm?pageid=4204
3. Communications (ComCom):
https://www.ohbmbrainmappingblog.com/
Episode producers:
Alfie Wearn
Stephania Assimopoulos
Please send any feedback, guest suggestions, or ideas [email protected]
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In this episode, Peter talks with Mallar Chakravarty about the imminent relaunch of the journal Aperture Neuro, which, a few years ago, was created and supported through OHBM.
Here we learn what happened with the first version of Aperture Neuro, what lessons were learned, and what the relaunched version of Aperture offers that is truly unique and valuable to the field. It is non-profit and open access with an APC of 800 dollars for members. It provides an avenue for many different kinds of papers, from typical original research to editorials, tutorials, conference summaries, book reviews, registered reports, and more. It will be heavily weighing the assessment of submitted papers based on their utility and transparency rather than just their novelty. In the future, Aperture Neuro aims to seamlessly support other objects such as code, data, notebooks, and videos, and is currently looking into mechanisms for handling these without compromising on quality or efficiency.
For more information about the journal, go to apertureneuro.org
Episode producers:
Alfie Wearn
Stephania Assimopoulos
Please send any feedback, guest suggestions, or ideas [email protected]
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Dr. Aviv Mezer is an Associate Professor at the Edmond and Lily Safra Center for Brain Sciences (ELSC) at the Hebrew University of Jerusalem, Israel.
Research in Dr. Mezerâs lab is focused on mapping human brain structures during normal development and aging. In addition, it is focused on developing new approaches to characterize the structural changes associated with neurological disorders. Mezerâs main research tool is in-vivo quantitative magnetic resonance imaging â qMRI. The Mezer lab is developing tools to biophysically explain the brainâs MRI signals at different levels and resolutions: from molecular local sources through cellular organization to the mapping of networks across the entire brain.
In this interview, we discuss the field of qMRI more broadly, touching upon the present and future interpretations âin vivo histologyâ. We also discuss Dr Mezerâs approach to mentorship, as well as the skills that would benefit future researchers in this field.
At OHBM 2023, Dr. Mezer will show us how combining multiple quantitative MRI measures can provide additional biological information about tissue composition and brain health.
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Dr Horn is a medical scientist with training in neuroimaging, movement disorders, software development and both invasive and noninvasive brain stimulation and the group leader of the Network Stimulation Laboratory at Brigham & Womenâs Hospital, Massachusetts General Hospital Boston and CharitĂ© â University Medicine Berlin. His main interest and research focus lies in the development and improvement of methods to analyze brain stimulation sites to study network interactions of neuromodulation in the human brain. He is also the host of a podcast focusing on brain stimulation.
In the interview with Dr Horn we explore how the impact of deep brain stimulation on the connectome can be studied, and how it can be used to improve patients lives. âIn contrast to many other neuroimaging domains, there is a more or less direct translation [..] to clinical practiceâ, says Dr Horn, and explains how for example networks that have been identified via DBS can later be targeted with noninvasive stimulation methods such as multifocal transcranial direct current stimulation (tDCS), for example to improve patientsâ conditions in movement disorders such as Parkinson's disease. Among many other things, Dr Horn also lets us in on an informally ongoing challenge at Harvard University whether structural or functional measures provide better predictions for DBS outcomes. He explains why his lab has gradually shifted away from using patient specific connectivity data to precise normative connectomes for studying which brain networks should optimally be modulated for maximal effects.
In his keynote at OHBM 2023, Dr Horn will give us a tour through his findings from years of work studying the effects of deep brain stimulation on the connectome across different disorders, ranging across neurological, neuropsychiatric and psychiatric diseases. He will illustrate how his findings can be transferred across disorders to inform one another and how they can be further used to inform neurocognitive effects and behaviors such as risk-taking and impulsivity.
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Dr. Emma Robinson is a Senior Lecturer (Assoc. Professor) at Kingâs College London. Her development of the Multimodal Surface Matching (MSM) software for cortical surface registration has been instrumental to the development of the Human Connectome Projectâs multimodal parcellation of the human cortex. She is currently developing interpretable machine learning models to aid in the personalized prediction of disease progression. In this interview, Dr.Robinson describes the advantages of interpretable machine learning models, and the methodological challenges she faced during the development of this framework.
Her approach to identifying disease-related changes in individual brain scans attempts to circumvent two of the limitations of traditional approaches: (1) the over-reliance on population averages, and (2) the opacity of âblack-boxâ machine learning algorithms such as deep neural networks. In addition, Dr. Robinson shared that, following her extensive experience working on the Human Connectome Project, she realized that traditional image registration methods may not be sufficient for individualized predictions.
Finally, Dr. Robinson shared how her relationship with her mentors shaped the trajectory of her current career. Her mentors not only guided her on the application of computational methods to neuroscience, but also encouraged her to develop her own methods.
At OHBM 2023, Dr. Robinson will present how her work contributes to improved personalized predictions of cortical features in patient populations and how interpretable machine learning approaches can enhance precision.
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