About

Teresa R Franklin, Ph.D., is an Adjunct Associate Professor of Psychiatry at the University of Pennsylvania, affiliated with the David J. Mahoney Institute of Neurological Sciences, the Center for Functional Neuroimaging, and the Penn Medicine Neuroscience Center at the Perelman School of Medicine. Her research focuses on characterizing pharmaco-responsive endophenotypes in smokers to aid in smoking cessation. She investigates the factors contributing to relapse, including withdrawal-induced craving and cue-induced craving, using neuroimaging techniques such as continuous arterial spin labeled (CASL) perfusion fMRI and single photon emission computed tomography (SPECT). Franklin's work explores the neural and genetic mechanisms underlying smoking behavior, with particular attention to individual variability, sex and hormonal influences, and co-morbidities such as obesity, ADHD, anxiety, and marijuana addiction. Her research aims to establish brain, behavioral, and genetic endophenotypes of medication response to develop tailored treatment strategies for addiction.

Research topics

• Psychology
• Neuroscience
• Medicine
• Internal medicine
• Anesthesia

Selected publications

• “ARRESTED DEVELOPMENT”? COCAINE PATIENTS WITH GENETICS LINKED TO OVER-RESPONSE OF THE STRESS (CORTISOL) SYSTEM SHOW AN “IMMATURE” PATTERN OF POSITIVE, RATHER THAN INVERSE, AMYGDALA RESTING FUNCTIONAL CONNECTIVITY WITH THE VMPFC

  Drug and Alcohol Dependence · 2024-07-01

  article
  PublisherDOI

• Impact of the natural hormonal milieu on ventral striatal responses to appetitive cigarette smoking cues: A prospective longitudinal study

  Drug and Alcohol Dependence Reports · 2022-11-13 · 6 citations

  articleOpen access1st authorCorresponding

  Background: The female sex hormones estradiol (E) and progesterone (P) galvanize the ventral striatal reward pathway. E elevates ventral striatal dopamine and accelerates drug-cued reinstatement, while P has opposing 'protective' effects on drug-related behavior. We hypothesize that women may exhibit greater ventral striatal responses to smoking cues (SCs) during the late follicular phase of the menstrual cycle (MC) when E is high and unimpeded by P, and reduced responses during the late luteal phase when P is high. Methods: To test our hypothesis, 24 naturally cycling cigarette-dependent women completed functional magnetic resonance (fMRI) sessions over the course of 3 MCs at select time points to reflect the early follicular (low E and P; LEP, control condition), late follicular (high E, low P; HE) and mid-luteal (high E, high P; HEP) MC phases. During fMRI sessions (counterbalanced by phase), women were exposed to a SC versus nonSC audio-visual clip. Ovulation was verified for each MC, and hormone levels were acquired prior to sessions. Results: Contrasts within conditions showed that ventral striatal brain responses to SCs versus nonSCs were negligible during LEP and greater during HE (p=0.009) and HP (p=0.016). Contrasts across conditions showed that HE and HEP had greater responses than LEP (p=0.005), and HE had greater responses than HEP (p=0.049). Conclusions: Results support and extend our retrospective cross-sectional study of the influence of the hormonal milieu on SC reactivity. Results are clinically relevant as they may guide novel, hormonally-informed and immediately translatable treatment strategies that can potentially reduce relapse in naturally cycling women.

  PublisherDOI

• Trauma exposure among cannabis use disorder individuals was associated with a craving-correlated non-habituating amygdala response to aversive cues.

  Drug and Alcohol Dependence Reports · 2022-09-29 · 2 citations

  articleOpen access

  The relationship of cannabis-use disorder and trauma exposure at the level of the brain is not well-understood. Cue-reactivity paradigms have largely focused on characterizing aberrant subcortical function by averaging across the entire task. However, changes across the task, including a non-habituating amygdala response (NHAR), may be a useful biomarker for relapse vulnerability and other pathology. This secondary analysis utilized existing fMRI data from a CUD population with (TR-Y, n = 18) or without trauma (TR-N, n = 15). Amygdala reactivity to novel and repeated aversive cues was examined between TR-Y vs. TR-N groups, using a repeated measures ANOVA. Analysis revealed a significant interaction between TR-Y vs. TR-N and amygdala response to novel vs. repeated cues in the amygdala (right: F (1,31) = 5.31, p = 0.028; left: F (1,31) = 7.42, p = 0.011). In the TR-Y group, a NHAR was evident, while the TR-N group exhibited amygdala habituation, resulting in a significant difference between groups of amygdala reactivity to repeated cues (right: p = 0.002; left: p < 0.001). The NHAR in the TR-Y (but not TR-N) group was significantly correlated with higher cannabis craving scores, yielding a significant group difference (z = 2.1, p = 0.018). Results suggest trauma interacts with the brain's sensitivity to aversive cues, offering a neural explanation for the relationship between trauma and CUD vulnerability. These findings suggest the importance of considering the temporal dynamics of cue reactivity and trauma history in future studies and treatment planning, as this distinction may help decrease relapse vulnerability.

  PublisherDOI

• Effects of topiramate on neural responses to alcohol cues in treatment-seeking individuals with alcohol use disorder: preliminary findings from a randomized, placebo-controlled trial

  Neuropsychopharmacology · 2021-02-08 · 29 citations

  articleOpen access

  Topiramate, a GABA/glutamate modulator, is efficacious in reducing alcohol consumption, though the mechanisms underlying this effect are not well characterized. This study analyzed functional magnetic resonance imaging (fMRI) data from 22 heavy drinkers enrolled in a 12-week placebo-controlled, randomized clinical trial of topiramate to examine the effects of topiramate on alcohol cue-elicited brain responses, craving, and heavy drinking in individuals with DSM-5 alcohol use disorder. Patients were randomized to receive either topiramate (maximal daily dosage of 200 mg/day) or placebo and were administered an fMRI alcohol cue-reactivity task at baseline (before starting medication) and after 6 weeks of double-blind treatment. Analyses compared the topiramate (n = 12) and placebo (n = 8) groups on (1) the change in brain responses during alcohol cue exposure (vs non-alcohol cues) within five a priori regions of interest related to reward-the bilateral and medial orbitofrontal cortex (OFC) and bilateral ventral striatum (VS) and (2) change in craving and heavy drinking days (HDDs) from baseline and scan 2. Topiramate, relative to placebo, reduced alcohol cue-elicited activation of the left VS, bilateral OFC, and medial OFC, alcohol cue-elicited craving, and HDDs between baseline and 6 weeks of treatment. The reduction in alcohol cue-elicited activation in the medial OFC correlated with reductions in craving, and reduced activation in the right VS, right OFC, and medial OFC correlated with the reduction in HDD. This preliminary study provides evidence that topiramate's attenuation of alcohol cue-elicited brain activation and craving are key elements of the drug's neurobiological mechanism of action in reducing heavy drinking.

  PublisherOA PDFDOI

• Editorial

  Drug and Alcohol Dependence Reports · 2021-12-01

  editorialOpen access1st authorCorresponding
  PublisherDOI

• Smoking-induced craving relief relates to increased DLPFC-striatal coupling in nicotine-dependent women

  Drug and Alcohol Dependence · 2021-02-15 · 8 citations

  articleOpen access1st authorCorresponding
  PublisherOA PDFDOI

• An exploration of associations between smoking motives and behavior as a function of body mass index

  Drug and Alcohol Dependence Reports · 2021-11-27 · 3 citations

  articleOpen access

  Cigarette smoking and obesity are the leading causes of premature morbidity and mortality and increase the risk of all-cause mortality four-fold when comorbid. Although research suggests that smoking motives may differ based on body mass index (BMI), it is unclear how these differences translate to smoking behavior. Three groups of adults who smoke cigarettes (N = 79; obese n = 25, overweight n = 30, and lean n = 24) completed measures of smoking and the Smoking Motivations Questionnaire. Groups did not differ on age, education, cigarettes per day (CPD), pack-years, or nicotine dependence, as measured by the Fagerström Test for Cigarette Dependence (FTCD). Analyses revealed different associations between reasons for smoking and smoking behavior depending on lean, overweight, or obesity status. Participants (N = 37 female, average age 39.8 years) self-reported smoking was positively associated with Addictive, and Automatic subscale scores among lean participants, with only the Addictive subscale score among those with overweight, and only the Automatic subscale score among those with obesity. Post hoc MANCOVA analysis revealed a significant interaction effect of Group x Automatic Smoking on Pack-years (F(2, 79)=3.34, p = 0.04). Findings suggest smoking motives are differentially associated with smoking behavior in adults who smoke depending on weight status. The daily smoking rate of participants with obesity may be less related to the addictive quality of smoking, and automaticity may be less associated with smoking history in those with overweight. Additional research on the influence of BMI on cigarette smoking is necessary to fully elucidate how obesity may impact treatment outcomes to optimize smoking cessation treatment among those with excess body weight.

  PublisherDOI

• Influence of the natural hormonal milieu on brain and behavior in women who smoke cigarettes: Rationale and methodology

  Contemporary Clinical Trials Communications · 2021-02-21 · 3 citations

  articleOpen accessSenior authorCorresponding

  Women experience more severe health consequences from smoking, have greater difficulty quitting, and respond less favorably to nicotine replacement therapy than men. The influence of fluctuating ovarian hormones, specifically estradiol (E) and progesterone (P), on brain and behavioral responses during exposure to smoking reminders (i.e., cues) may be a contributing factor. Results from our laboratory suggest that women in the late follicular phase of their menstrual cycle (MC) have enhanced smoking cue (SC) vulnerabilities and reduced functional connectivity in neurocircuitry underlying cognitive control, potentially placing them at greater risk for continued smoking and relapse. The primary aim of this study is to examine and link hormonal status with brain and behavioral responses to SCs over the course of three monthly MCs in naturally cycling women who are chronic cigarette smokers. This longitudinal, counterbalanced study collects brain and behavioral responses to SCs at three time points during a woman's MC. Participants complete psychological and physical examinations, biochemical hormonal verification visits, and at least three laboratory/neuroimaging scan visits. The scan visits include a 10-min SC task during blood oxygen level-dependent (BOLD) data acquisition and are timed to occur during the early follicular phase (low E and P), late follicular phase (high E, unopposed by P), and mid-luteal phase (high P, high E). The primary outcomes include brain responses to SCs (compared to non-SCs), subjective craving, E and P hormone levels, and behavioral responses to SCs. This study addresses a critical gap in our knowledge: namely, the impact of the natural hormonal milieu on brain and behavioral responses to SCs, a powerful relapse trigger. Additionally, this study will provide a roadmap for human sex differences researchers who are obliged to consider the often confounding cyclic hormonal fluctuations of women.

  PublisherDOI

• Sustained brain response to repeated drug cues is associated with poor drug‐use outcomes

  Addiction Biology · 2021-02-26 · 32 citations

  articleOpen access

  A threefold increase in fatal cocaine overdoses during the past decade highlights the critical lack of medications for cocaine use disorders. The brain response to drug cues can predict future drug use; however, results have been mixed. We present preliminary evidence that a sustained response to repeated cocaine cues within a single task is a significant predictor of drug-use outcomes. Seventy-three cocaine inpatients were administered a passive-viewing fMRI task, featuring 500 ms novel evocative (cocaine, sexual, aversive) and neutral comparator cues in the first half (Half1), which were then repeated in the second half (Half2). After the baseline scan, patients received eight outpatient treatment weeks with twice-weekly drug screens. Drug-use outcome groups were empirically defined based on cocaine-positive or missing urines averaged across the outpatient phase: GOOD (<40%), POOR (>85%), and Intermediate (INT, between 40% and 85%) outcomes. Differences of response to initial (Half1) and repeated (Half2) cues in a priori (cue-reactive) regions were tested between outcome groups (3 [Group] × 2 [Halves] ANOVA). An interaction was found in the brain response to drug (but not sex or aversive) cues, with a significant difference between the GOOD and POOR outcome groups in Half2, driven by a significant decrease in brain response by the GOOD outcome group and a sustained brain response by the POOR outcome group, to repeated cocaine cues. The brain response to repeated drug cues may be a useful predictor of future drug use, encouraging future intervention studies to restore a "healthy" (decreasing) response to the repeated presentation of drug cues.

  PublisherOA PDFDOI

• Exploration of the influence of body mass index on intra-network resting-state connectivity in chronic cigarette smokers

  Drug and Alcohol Dependence · 2021-07-21 · 8 citations

  articleOpen access

  BACKGROUND: Obesity and cigarette smoking are two leading preventable causes of death. Previous research suggests that comorbid smoking and obesity likely share neurobehavioral underpinnings; however, the influence of body mass index (BMI) on resting-state functional connectivity (rsFC) in smokers remains unknown. In this study, we explore how BMI affects rsFC and associations between rsFC and smoking-related behavior. METHODS: Treatment-seeking cigarette smokers (N = 87; 54 % men) completed a BOLD resting-state fMRI scan session. We grouped smokers into BMI groups (N = 23 with obesity, N = 33 with overweight, N = 31 lean) and used independent components analysis (ICA) to identify the resting state networks commonly associated with cigarette smoking: salience network (SN), right and left executive control networks (ECN) and default mode network (DMN). Average rsFC values were extracted (p < 0.001, k = 100) to determine group differences in rsFC and relationship to self-reported smoking and dependence. RESULTS: Analyses revealed a significant relationship between BMI and connectivity in the SN and a significant quadratic effect of BMI on DMN connectivity. Heavier smoking was related to greater rsFC in the SN among lean and obese groups but reduced rsFC in the overweight group. CONCLUSIONS: Findings build on research suggesting an influence of BMI on the neurobiology of smokers. In particular, dysfunction of SN-DMN-ECN circuitry in smokers with overweight may lead to a failure to modulate attention and behavior and subsequent difficulty quitting smoking. Future research is needed to elucidate the mechanism underlying the interaction of BMI and smoking and its impact on treatment.

  PublisherDOI

Recent grants

• NIH Grant R21DA025882

  NIH · $345k · 2012

• NIH Grant K01DA015426

  NIH · $336k · 2007

• Influence of the natural hormonal milieu on perfusion fMRI smoking cue responses

  NIH · $2.4M · 2016–2022

• NIH Grant F31DA005878

  NIH · $19k

• NIH Grant R01DA029845

  NIH · $1.2M · 2016

Frequent coauthors

• Anna Rose Childress

  California University of Pennsylvania

  75 shared

• Charles P. O’Brien

  61 shared

• Reagan R. Wetherill

  University of Pennsylvania

  53 shared

• Jesse J. Suh

  52 shared

• Kanchana Jagannathan

  48 shared

• Ronald N. Ehrman

  Philadelphia VA Medical Center

  35 shared

• Nathan Hager

  Old Dominion University

  21 shared

• Michael J. Gawrysiak

  West Chester University

  21 shared

Labs

• Brain and Behavioral Vulnerabilities LaboratoryPI