TY - JOUR
T1 - Sign- vs. goal-tracking is associated with greater adiposity and altered functional connectivity in response to a naturalistic food paradigm
AU - Papantoni, Afroditi
AU - Shearrer, Grace E.
AU - Taillie, Lindsey Smith
AU - Shaikh, Saame Raza
AU - Meyer, Katie A.
AU - Paninos, Elianna
AU - Kravitz, Alexxai V.
AU - Burger, Kyle S.
N1 - Publisher Copyright:
© 2025 The Author(s)
PY - 2025/11/1
Y1 - 2025/11/1
N2 - Our modern food environment is full of highly palatable, ultra-processed foods that influence our eating behaviors. The reinforcement learning framework posits that some individuals readily assign motivational value to environmental cues (e.g., food ads) that predict reward, biasing their attention and making them more susceptible to seek that reward. These individuals are characterized as sign-trackers and differ from goal-trackers who do not tend to assign any motivational value to those reward-predicting environmental cues. Here, we tested whether this well-characterized phenotype in animals that is commonly associated with increased impulsivity and substance use disorders, could be translated to humans and adapted to study differences in adiposity and eating behaviors. A total of 47 adults completed a food-adapted Pavlovian conditioning task with cues predicting the delivery of candy with simultaneous eye-tracking to determine the sign-tracking vs. goal-tracking phenotype. Participants also completed a naturalistic fMRI scan where they passively viewed videos of sweet and savory dishes to examine functional connectivity associated with those phenotypes. We found that sign-tracking behavior was associated with a greater waist-to-hip ratio but not BMI. During the viewing of the sweet video only, we identified a brain network comprising high-degree nodes in the fusiform gyrus, occipital lobe, prefrontal cortex and posterior cingulate cortex that predicted higher sign-tracking behavior. These findings suggest that the sign- and goal-tracking phenotype model translates to humans using a food-based eye-tracking methodology. Further, supported by animal research, sign-tracking is associated with greater central adiposity and greater functional connectivity between visual, sensorimotor, and subcortical networks.
AB - Our modern food environment is full of highly palatable, ultra-processed foods that influence our eating behaviors. The reinforcement learning framework posits that some individuals readily assign motivational value to environmental cues (e.g., food ads) that predict reward, biasing their attention and making them more susceptible to seek that reward. These individuals are characterized as sign-trackers and differ from goal-trackers who do not tend to assign any motivational value to those reward-predicting environmental cues. Here, we tested whether this well-characterized phenotype in animals that is commonly associated with increased impulsivity and substance use disorders, could be translated to humans and adapted to study differences in adiposity and eating behaviors. A total of 47 adults completed a food-adapted Pavlovian conditioning task with cues predicting the delivery of candy with simultaneous eye-tracking to determine the sign-tracking vs. goal-tracking phenotype. Participants also completed a naturalistic fMRI scan where they passively viewed videos of sweet and savory dishes to examine functional connectivity associated with those phenotypes. We found that sign-tracking behavior was associated with a greater waist-to-hip ratio but not BMI. During the viewing of the sweet video only, we identified a brain network comprising high-degree nodes in the fusiform gyrus, occipital lobe, prefrontal cortex and posterior cingulate cortex that predicted higher sign-tracking behavior. These findings suggest that the sign- and goal-tracking phenotype model translates to humans using a food-based eye-tracking methodology. Further, supported by animal research, sign-tracking is associated with greater central adiposity and greater functional connectivity between visual, sensorimotor, and subcortical networks.
KW - Functional connectivity
KW - Goal-tracking
KW - Naturalistic fMRI paradigm
KW - Pavlovian conditioning
KW - Sign-tracking
UR - https://www.scopus.com/pages/publications/105014101634
U2 - 10.1016/j.physbeh.2025.115075
DO - 10.1016/j.physbeh.2025.115075
M3 - Article
C2 - 40845935
AN - SCOPUS:105014101634
SN - 0031-9384
VL - 301
JO - Physiology and Behavior
JF - Physiology and Behavior
M1 - 115075
ER -