Neurosalience

#A conversation with 2024 Keynote Speaker Nicola Palomero-Gallagher TODO: Link to blog post Interviewers: - Naomi L. Gaggi - Beatriz Padrela

A conversation with 2024 Keynote Lecture presenter Luis Concha https://www.ohbm-com.com/blog/a-conversation-with-keynote-speaker-luis-concha Interviewers: - Eduardo A. Garza-Villarreal - Diana Giraldo

Today our guest is Dr. Vince Calhoun, who's also a longtime colleague and friend of Peter Bandettini. Vince is the founding director of the tri-institutional center for translational research in Neuroimaging and Data Science (TReNDS) which is a consortium formed by Georgia State University, Georgia Tech, and Emory University. Vince Received his BS in electrical engineering from the University of Kansas, in 1991, two masters degrees in Biomedical engineering and information systems from Johns Hopkins in 1993, and 1996, and his Ph.D. in EE from the University of Maryland Baltimore County in 2002. After four years at Yale University, he became President of the Mind Research Network and Distinguished Professor at the University of New Mexico, before he moved to Atlanta for his present position several years ago. Vince's focus over the years could be summarized as using fMRI and other neuroimaging methods while developing processing methods to extract every possible useful bit of information. He's been prodigiously engaged and productive for over 20 years advancing multi-modal brain imaging, data fusion, and machine learning. His work has inspired new ways of looking at the data. In this discussion, Peter and Vince talk about work, professional journey from the east coast to New Mexico and now to Atlanta, as well as his successful battle with cancer in about 2010. We hope you enjoy this episode. Episode producers: Xuqian Michelle Li Johanna Bayer Omer Faruk Gulban

A conversation with 2024 Keynote Lecture presenter Mac Shine https://www.ohbm-com.com/blog/a-conversation-with-dr-mac-shine-ohbm-2024-keynote-interview-series-pt3 Interviewers: - Alfie Wearn - Xuqian Michelle Li

A conversation with 2024 Talairach Lecture presenter Zarin Machanda https://www.ohbm-com.com/blog/a-conversation-with-2024-talairach-lecture-presenter-zarin-machanda Interviewers: - Elisa Guma - Lavinia Uscatescu

Today we zoom in on Vancouver British Columbia to interview Dr. Todd Woodward, who is a professor in the department of psychiatry at the University of British Columbia and director of the UBC Brain Dynamics Laboratory. He's also the Director of the Cognitive Neuroscience of Schizophrenia Laboratory at BC Mental Health and Addictions Research Institute in Vancouver. Dr. Woodward received his Ph.D. in Experimental Neuropsychology at the University of Victoria in 1999, and performed his post-doc in the department of psychology at UBC. Since 2003 he's moved up from research scientist to professor - all at the University of British Columbia.  He's been working at the interface of processing methods and well-crafted experimental designs to probe the networks that may be disrupted in schizophrenia and other disorders. He and his team developed almost two decades ago a unique and elegant method known as constrained principal component analysis ( or CPCA), which he has been applying successfully with many different tasks. He's also deeply interested in novel non-pharmaceutical interventions that help augment schizophrenia treatment - having developed a program called metacognitive training (MCT), which may allow those with schizophrenia to be able to step back and begin to assess their own beliefs. This was such a wide ranging conversation which delved into the nuts and bolts of CPCA as well as the potential future role that neuroimaging can play in better understanding and ultimately treating schizophrenia. We hope you enjoy this episode. Episode producers: Omer Faruk Gulban Xuqian Michelle Li

This episode’s guest is arguably one of the most influential scientists in the human brain mapping community. Dr. Peter Fox, director of the Research Imaging Institute at the University of Texas Health, San Antonio. Early in his career he wrote the seminal paper that showed, using positron emission tomography , that brain-activation related increases in blood flow are accompanied by only small increases in oxidative metabolic -  resulting in the blood locally increasing in oxygenation. This paper set the foundation for understanding all of Blood Oxygen Level Dependent Contrast used in fMRI today. The true purpose of activation-related flow increases is still an open question. The story of the events and details surrounding this are in his review article from the 2012 NeuroImage special issue. It's titled, simply "The coupling controversy." Dr. Fox was also among the first to promote data sharing and pooling with his brainmap database, and early on, established stereotactic coordinates and spatial normalization as a way to put data into a shareable space. He started the annual meeting that pre-dated the Organization for Human Brain Mapping, and also founded one of the major brain mapping journals today, titled: Human Brain Mapping.   Peter had his formative undergraduate education at the extremely unique St. Johns college in Annapolis. He received his MD from Georgetown University, interned at Duke University, then carried out his residency and fellowship at Washington University where he worked closely with Dr. Mark Raichle, who was at the time pioneering PET scanning.   In this discussion, we delve into his contributions in a wide range of topics, from neurovascular coupling to the challenge of spatial normalization - particularly at high resolution - to subject variability, to clinical applications and the ongoing evolution of scientific publishing. Lots of history, content, and insight here. We hope you enjoy it! Notable paper: Fox PT., The Coupling Controversy, Neuroimage. 2012 Aug 15; 62(2): 594–601.  https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4019339/ Episode producers: Omer Faruk Gulban Stephania Assimopoulos

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

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.

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. Chen’s 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