Precision Functional Brain Mapping after Methamphetamine Administration
Poster No:
1727
Submission Type:
Abstract Submission
Authors:
Wililam Hoffman1,2, Robert hermosillo3,2,4,5, Laura Dennis1,2, Anita Randolph3, Holly McCready1, Daniel Smith2, Meghan Oswald6, Milky Kohno1,2, Gracie Grimsrud7, Heba Abuad3, Eric Feczko8,4, Damien Fair8,4,5
Institutions:
1Portland VA Health Care System, Portland, OR, 2Oregon Health & Science University, Portland, OR, 3Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, 4Department of Pediatrics, University of Minnesota, Minneapolis, MN, 5Institute of Child Development, University of Minnesota, Minneapolis, MN, 6Zucker School of Medicine/Northwell Health at Mather Hospital, Port Jefferson, NY, 7Masonic Institute for the Developiing Brain, University of Minnesota, Minneapolis, MN, 8Masonic Institute for the Developing Brain, University of Minnesota Medical School, Minneapolis, MN
First Author:
Wililam Hoffman, PhD, MD
Portland VA Health Care System|Oregon Health & Science University
Portland, OR|Portland, OR
Portland VA Health Care System|Oregon Health & Science University
Portland, OR|Portland, OR
Co-Author(s):
Robert hermosillo, PhD
Masonic Institute for the Developing Brain, University of Minnesota|Oregon Health & Science University|Department of Pediatrics, University of Minnesota|Institute of Child Development, University of Minnesota
Minneapolis, MN|Portland, OR|Minneapolis, MN|Minneapolis, MN
Masonic Institute for the Developing Brain, University of Minnesota|Oregon Health & Science University|Department of Pediatrics, University of Minnesota|Institute of Child Development, University of Minnesota
Minneapolis, MN|Portland, OR|Minneapolis, MN|Minneapolis, MN
Laura Dennis, BS
Portland VA Health Care System|Oregon Health & Science University
Portland, OR|Portland, OR
Portland VA Health Care System|Oregon Health & Science University
Portland, OR|Portland, OR
Milky Kohno, PhD
Portland VA Health Care System|Oregon Health & Science University
Portland, OR|Portland, OR
Portland VA Health Care System|Oregon Health & Science University
Portland, OR|Portland, OR
Gracie Grimsrud
Masonic Institute for the Developiing Brain, University of Minnesota
Minneapolis, MN
Masonic Institute for the Developiing Brain, University of Minnesota
Minneapolis, MN
Eric Feczko
Masonic Institute for the Developing Brain, University of Minnesota Medical School|Department of Pediatrics, University of Minnesota
Minneapolis, MN|Minneapolis, MN
Masonic Institute for the Developing Brain, University of Minnesota Medical School|Department of Pediatrics, University of Minnesota
Minneapolis, MN|Minneapolis, MN
Damien Fair
Masonic Institute for the Developing Brain, University of Minnesota Medical School|Department of Pediatrics, University of Minnesota|Institute of Child Development, University of Minnesota
Minneapolis, MN|Minneapolis, MN|Minneapolis, MN
Masonic Institute for the Developing Brain, University of Minnesota Medical School|Department of Pediatrics, University of Minnesota|Institute of Child Development, University of Minnesota
Minneapolis, MN|Minneapolis, MN|Minneapolis, MN
Introduction:
Precision functional mapping (Gordon et al., 2018) can reliably identify the resting state functional connectivity network structure of individual brains. The method offers important advantages for producing individual steady state functional connectivity networks will more precise borders between regions. We used this method to investigate the effect of orally administered methamphetamine (MA) or placebo (PBO) on network connectivity in healthy control subjects (CS).
Methods:
Participants were recruited through the Veterans Affairs Portland Health Care System (VAPORHCS) and Oregon Health & Science University (OHSU) (Portland, Oregon, USA). The research was approved by a joint Institutional Review Board at OHSU and VAPORHCS. Participants (n=8, age = 37.75 ± 13.06, 5 female) CS completed 2 separate sessions in a double-blind cross-over study. Either MA, 0.3 mg/kg or a matching PBO were orally administered in two sessions separated by at least 3 days to allow for drug washout. Subjective experience (euphoria) was rated hourly on the Addiction Research Center Inventory (ARCI) morphine-benazadrine group (MBG) subscale. Subjects received a baseline scan and then a scan initiated 1.5 h after receiving double blind MA or PBO (Figure 1). MA serum levels were measured from saliva collected before and after the scan.
Scanning was performed on a 3.0-T Siemens Prisma Scanner using a 32-channel head coil at OHSU. During each scan, high resolution T1w and T2w images and field maps were obtained. BOLD data (TR: 800 ms, TE: 0.03, slice thickness: 2.4mm, flip angle: 52°) for RSFC were collected in 5 minute blocks FIRMM software in real-time to collect 30 to 45 min worth of low motion (FD<0.2mm) volumes.
BOLD data for each participant was processed similarly to the ABCD-BIDS pipeline (Feczko et al. 2021). Time series data from each session were treated as separate tasks to ensure that BOLD data was registered to an identical surface mesh generated from a common T1w image. Motion censoring was performed to reduce the influence of motion artifacts (Power 2014).
Network templates were produced from 164 participants in a separate study using the template matching procedure, described in Hermosillo et al. (2022). This resulted in 14 different network templates identified in Figure 2. Precision functional maps were constructed for each participant in the present study. The spatial similarity (eta²) at each grayordinate was calculated to each of the network templates and, in each individual participant, the grayordinate was assigned to the network template that had the highest eta² value. Group connectivity matrices (Figure 2) were obtained by assigning each grayordinate to a network if it occurred in that network in at least 7 individuals.
Scanning was performed on a 3.0-T Siemens Prisma Scanner using a 32-channel head coil at OHSU. During each scan, high resolution T1w and T2w images and field maps were obtained. BOLD data (TR: 800 ms, TE: 0.03, slice thickness: 2.4mm, flip angle: 52°) for RSFC were collected in 5 minute blocks FIRMM software in real-time to collect 30 to 45 min worth of low motion (FD<0.2mm) volumes.
BOLD data for each participant was processed similarly to the ABCD-BIDS pipeline (Feczko et al. 2021). Time series data from each session were treated as separate tasks to ensure that BOLD data was registered to an identical surface mesh generated from a common T1w image. Motion censoring was performed to reduce the influence of motion artifacts (Power 2014).
Network templates were produced from 164 participants in a separate study using the template matching procedure, described in Hermosillo et al. (2022). This resulted in 14 different network templates identified in Figure 2. Precision functional maps were constructed for each participant in the present study. The spatial similarity (eta²) at each grayordinate was calculated to each of the network templates and, in each individual participant, the grayordinate was assigned to the network template that had the highest eta² value. Group connectivity matrices (Figure 2) were obtained by assigning each grayordinate to a network if it occurred in that network in at least 7 individuals.
Results:
Post scan MA levels were 389 ± 209 ng/mL (range 145 – 780). There was a consistent subjective response after MA administration (Fig 1), with subjects reporting maximum subjective effects at 12 to 15 on the MBG scale. Inspection of the individual correlation maps. pre and post drug in the MA condition, found robust, consistent decreased within network connectivity in the SMd, SMl, AUD, VIS networks and, less consistently, in the DMN (Figure 2). There were minimal changes in the PBO condition.
Conclusions:
Precision functional mapping is a feasible method for the study of acute drug administration by accounting for differences in functional topography. The method produces individual maps that approach a steady state and allow detection of precise borders between networks with increased confidence. The method can yield stable group maps in modest subject cohorts. In this study, MA administration induced widespread decreased within network connectivity in primary sensorimotor networks in healthy controls.
Disorders of the Nervous System:
Psychiatric (eg. Depression, Anxiety, Schizophrenia) 2
Modeling and Analysis Methods:
fMRI Connectivity and Network Modeling 1
Keywords:
FUNCTIONAL MRI
1|2Indicates the priority used for review
Provide references using author date format
Gordon, E et al., (2017), Precision functional mapping of individual human brains, Neuron 96(4), 791-807.
Hermosillo, RJM et al. (2022), A Precision Functional Atlas of Network Probabilities and Individual-Specific Network Topography, bioRxiv 2022.01.12.475422; doi: https://doi.org/10.1101/2022.01.12.475422.
Power, JD et al. (2014), Methods to Detect, Characterize and Remove Motion Artifact in Resting State fMRI, Neuroimage 84, 320-341.