Functional MRI Speaker Series

Most years our laboratory provides opportunities for our users and researchers to learn about advances in fields related to Functional MRI.

No RSVP is required. To be added to the Speaker Series email group and receive notifications about the speaker series talks, please contact the Administrator.

Video of past presentations can be accessed here.

Academic Year 2019-2020 Speaker Series

October 29, 2019

Dr. Scott A. Langenecker, University of Utah

Topic: Contemplating Rumination: Assessing and Measuring Change in Relation to Risk for Depression Recurrence

Rumination is a feature of major depressive disorder, that is considered a passive, negative, and recurrent thought patterns and habits. Like negative cognitive biases, rumination reflects the thought content (negative, potentially distorted) typical of depression. Unlike negative cognitive biases, rumination also includes habitual tendencies in responding to stressors (avoidance, passivity) which are not clearly or necessarily ascribed to negative thought patterns. As depressive rumination includes both content and habit it has been difficult to measure well. The fact that it may reflect a disengaged state from active cognitive processing means that it is often ascertained through the absence of certain mental states and behaviors, which also makes measurement challenging. The talk will focus on fMRI paradigms that are thought to capture the ruminative state and habit, behavioral correlates of increased rumination, and the relations of rumination to depression risk, poor treatment response, and frequent recurrence of depression. Moreover, it will cover strategies to intervene to change rumination, and resulting changes in resting state connectivity and task-based brain activation.

December 3, 2019

Dr. Nathan Rose, University of Notre Dame

Topic: A Dynamic Processing Model of Working Memory: Evidence from Behavior, Neuroimaging, and Neurostimulation

Recent shifts in the understanding of how the mind and brain retain information in working memory (WM) call for revision to canonical theory. Evidence for the existence of dynamic, “activity-silent” short- term retention processes in the brain diverge from traditional models that have argued that items in WM are retained by sustained representation in buffers or activated states. Such evidence comes from the use of machine-learning analytic approaches to decode patterns of brain activity and the simultaneous administration of transcranial magnetic stimulation (TMS) to causally manipulate brain activity in specific areas and time-points. TMS has been used to 'ping' brain areas and reactivate latent representations retained in WM and affect memory performance, but only when the information is still relevant for the current trial. These findings argue for a supplement to the sustained retention mechanisms associated with attending to information in WM. Brain decoding methods reveal dynamic, hierarchical levels of representation in WM that vary according to task context, from perceptual/sensory codes in posterior areas to more conceptual/abstract codes distributed across frontal-parietal regions. A Dynamic Processing Model of WM is advanced to account for the overall pattern of results.

January 21, 2020

Dr. Martin Lindquist, Johns Hopkins University

Topic: High-dimensional Multivariate Mediation with Application to Neuroimaging Data

Mediation analysis is an important tool in the behavioral sciences for investigating the role of intermediate variables that lie in the path between a randomized treatment/exposure and an outcome variable. The influence of the intermediate variable on the outcome is often explored using structural equation models (SEMs), with model coefficients interpreted as possible effects. While there has been significant research on the topic in recent years, little work has been done on mediation analysis when the intermediate variable (mediator) is a high-dimensional vector. In this work we introduce a novel method for mediation analysis in this setting called the directions of mediation (DMs). The DMs represent an orthogonal transformation of the space spanned by the set of mediators, chosen so that the transformed mediators are ranked based upon the proportion of the likelihood of the full SEM that they explain. We provide an estimation algorithm and establish the asymptotic properties of the obtained estimators. We demonstrate the method using a functional magnetic resonance imaging (fMRI) study of thermal pain where we are interested in determining which brain locations mediate the relationship between the application of a thermal stimulus and self-reported pain.




POSTPONED TO FALL 2020 DUE TO COVID-19

Date: TBD

Dr. Kawin Setsompop, Harvard University

Topic: Efficient Acquisition Approaches for Brain MRI

This talk will focus on a number of innovative MRI acquisition methods aim at improving in vivo brain imaging in Healthcare and Health science. The study of subtle changes in brain structure and function with MRI are typically limited by slow image encoding and limited sensitivity. Here a number of rapid and efficient acquisition methods will be described. These techniques are specifically designed to make full use of highly sensitive cutting-edge hardware, such as massively parallel receiver array, ultra-high field MRI and the “Connectome” system with ultra-high gradient strength. Such acquisition technologies have enabled an unprecedented order of magnitude gain in speed and sensitivity of brain MRI. This talk will describe a few brain imaging areas that such technologies have already had a big impact, including diffusion imaging, fMRI, and structural and quantitative imaging.

Date: TBD

Dr. Sabine Kastner, Princeton University

Topic: Neural Dynamics of the Primate Attention Network

The selection of information from our cluttered sensory environments is one of the most fundamental cognitive operations performed by the primate brain. In the visual domain, the selection process is thought to be mediated by a static spatial mechanism – a ‘spotlight’ that can be flexibly shifted around the visual scene. This spatial search mechanism has been associated with a large-scale network that consists of multiple nodes distributed across all major cortical lobes and also includes subcortical regions. To identify the specific functions of each network node and their functional interactions is a major goal for the field of cognitive neuroscience. In my lecture, I will give an overview on the neural basis of this fundamental cognitive function and discuss recently discovered rhythmic properties that set up alternating attention states.

Date: TBD

Dr. Alberto L. Vazquez, University of Pittsburgh

Topic: TBA