Task fMRI Investigation of Pain Processing in Adolescent Cannabis Use
Poster No:
533
Submission Type:
Abstract Submission
Authors:
Tram Nguyen1, Gustavo Delgado2, Samuel Holzman2, Russell Tobe3, Vilma Gabbay4, Benjamin Ely5
Institutions:
1Albert Einstein College of Medicine, BRONX, NY, 2Albert Einstein College of Medicine, Bronx, NY, 3Nathan S. Kline Institute for Psychiatric Research, Orangeburg, NY, 4University of Miami Miller School of Medicine, Miami, FL, 5Albert Einstein College of Medicine, New York, NY
First Author:
Co-Author(s):
Introduction:
Despite growing evidence for biobehavioral relationships between pain and cannabis use (Yanes et al. 2018, Gogulski and Craft 2022), there has been sparse research on pain circuitry in adolescent cannabis use. Here, we examined pain processing among adolescent cannabis users and non-users.
Methods:
Our study is on-going and recruiting adolescents in the New York City metropolitan area. In this preliminary analysis, we included data from 25 subjects (age: 15.4 ± 2.5 years; 84% female). History of cannabis use was determined from clinician-based interviews, self-reported measures, and urine toxicology screens. MRI was performed on a 3T Siemens Skyra using protocols similar to those of the Human Connectome Project (HCP) Lifespan studies (Van Essen et al. 2012), including anatomical T1w MPRAGE and T2w SPACE (0.9mm isotropic) and fMRI (2.3mm isotropic, TR=1s, 5x multiband).
Our electric pain paradigm based on a published protocol (Ma et al. 2016) incorporated out-of-scanner and in-scanner portions (see also our related abstract detailing the task and associations with psychiatric symptoms: Ely BA et al. "Pain Response and Associations with Psychiatric Symptoms Using an Affordable Electric Shock Task"). Pre-scan, an electrode was placed on the dorsal surface of the right foot, and stimulation (100Hz, 0.5ms pulses) was calibrated (0.25V steps, max 10V) to determine when shocks were first painlessly felt (innocuous threshold), became painful (pain threshold), and were as painful as could be tolerated (maximum threshold). Thresholds were confirmed and adjusted as needed in scanner. The task comprised three 5-minute runs, each with 10 trials. For each trial (Fig. 1), the subject was first shown a cue, followed by a fixation cross, then received an electric shock. Post-shock, the subject rated pain level on a 0-10 Visual Analogue Scale. Trials were separated by jittered fixation. Preprocessing steps included motion correction, normalization to MNI space, and mild spatial smoothing (FWHM=4mm). Subject-level data were analyzed using an event-related GLM, as implemented in FSL FEAT (Woolrich et al. 2001), to model neural responses during 1) cues preceding painful vs. non-painful shocks, 2) receipt of painful vs. non-painful shocks, and 3) post-shock pain ratings. At the group level, mixed effects models with FLAME1+2 (Woolrich et al. 2004) and outlier de-weighting were performed. Neural activation across phases of pain processing was compared between cannabis users and non-users as well as correlated with cannabis use frequency across the full sample. Results were controlled for multiple comparisons using cluster-based inference at Z>2.58, p<0.05.
Our electric pain paradigm based on a published protocol (Ma et al. 2016) incorporated out-of-scanner and in-scanner portions (see also our related abstract detailing the task and associations with psychiatric symptoms: Ely BA et al. "Pain Response and Associations with Psychiatric Symptoms Using an Affordable Electric Shock Task"). Pre-scan, an electrode was placed on the dorsal surface of the right foot, and stimulation (100Hz, 0.5ms pulses) was calibrated (0.25V steps, max 10V) to determine when shocks were first painlessly felt (innocuous threshold), became painful (pain threshold), and were as painful as could be tolerated (maximum threshold). Thresholds were confirmed and adjusted as needed in scanner. The task comprised three 5-minute runs, each with 10 trials. For each trial (Fig. 1), the subject was first shown a cue, followed by a fixation cross, then received an electric shock. Post-shock, the subject rated pain level on a 0-10 Visual Analogue Scale. Trials were separated by jittered fixation. Preprocessing steps included motion correction, normalization to MNI space, and mild spatial smoothing (FWHM=4mm). Subject-level data were analyzed using an event-related GLM, as implemented in FSL FEAT (Woolrich et al. 2001), to model neural responses during 1) cues preceding painful vs. non-painful shocks, 2) receipt of painful vs. non-painful shocks, and 3) post-shock pain ratings. At the group level, mixed effects models with FLAME1+2 (Woolrich et al. 2004) and outlier de-weighting were performed. Neural activation across phases of pain processing was compared between cannabis users and non-users as well as correlated with cannabis use frequency across the full sample. Results were controlled for multiple comparisons using cluster-based inference at Z>2.58, p<0.05.
Results:
Adolescent cannabis users and non-users exhibited similar neural activation while viewing painful vs. non-painful cues. When experiencing painful vs. non-painful shocks, cannabis users showed stronger activation in the right frontal gyrus, frontal pole, insula, caudate, and bilateral paracingulate gyri (Fig. 2A). During pain rating, the bilateral precentral and postcentral gyri had stronger activation among cannabis users (Fig. 2B). Heavier cannabis use correlated with activation of the right frontal gyrus during shock (Fig. 2C) and the left precentral gyrus during pain rating (Fig. 2D).
Conclusions:
We found that experiencing and rating pain elicited stronger neural responses in adolescent cannabis users than non-users. Though preliminary, these results align with converging evidence for cannabis-associated alterations in pain processing in youth. Recruitment for this study is ongoing, with future analyses to include a larger sample and examine the role of comorbid cannabis use and depression in pain processing.
Disorders of the Nervous System:
Psychiatric (eg. Depression, Anxiety, Schizophrenia) 1
Modeling and Analysis Methods:
Activation (eg. BOLD task-fMRI)
Novel Imaging Acquisition Methods:
BOLD fMRI
Perception, Attention and Motor Behavior:
Perception: Pain and Visceral 2
Keywords:
FUNCTIONAL MRI
Pain
Psychiatric
Other - cannabis use; adolescence
1|2Indicates the priority used for review
Provide references using author date format
Ma, Y. et al. (2016). "Serotonin transporter polymorphism alters citalopram effects on human pain responses to physical pain." Neuroimage 135: 186-196.
Van Essen, D. C et al. (2012). "The Human Connectome Project: a data acquisition perspective." Neuroimage 62(4): 2222-2231.
Woolrich, M. W. et al. (2004). "Multilevel linear modelling for FMRI group analysis using Bayesian inference." Neuroimage 21(4): 1732-1747.
Woolrich, M. W. et al. (2001). "Temporal autocorrelation in univariate linear modeling of FMRI data." Neuroimage 14(6): 1370-1386.
Yanes, J. A. et al. (2018). "Neuroimaging meta-analysis of cannabis use studies reveals convergent functional alterations in brain regions supporting cognitive control and reward processing." J Psychopharmacol 32(3): 283-295.