Biology subjects

Sander, D.

Publications and source records attributed to Sander, D..

6 recordsLinked to original sources

bioRxiv2026

Mapping the brain basis of appraisals and discrete emotions

The Component Process Model of Emotion conceptualizes any emotional episode (e.g., the discrete emotions of sadness, anger, fear, or interest) as being driven by the multiple appraisal components. However, both the specificity of the neural mechanisms underlying appraisal processes and the way these appraisal networks relate to the neural circuits underlying discrete emotions remain unclear. Here we investigated the neural correlates of appraisal processes and compared them with those of discrete emotions. Participants (n = 97) were scanned with functional magnetic resonance imaging (fMRI) while watching short movie clips with varying emotional contents. Intensity for 12 appraisals and 12 basic and epistemic emotions evoked by the movie clips were rated by independent participants (n = 444). The neural responses were modelled with convolved ratings of appraisals and discrete emotions. The results indicated that appraisals and discrete emotions are supported by a shared set of distributed brain regions that extend beyond typically reported emotion-related areas, encompassing perceptual, action-related, and higher-order cognitive systems. Activations were more consistent for and better explained by appraisals versus discrete emotions. Within this network, epistemic emotions elicited less consistent activations than basic emotions, particularly in limbic regions. Our results highlight the functional organization of appraisals and discrete emotions under dynamic and complex conditions and indicate that appraisal theories better explain neural responses than discrete emotion models.

neuroscience↗

bioRxiv2025

GPT-4 accurately predicts human emotions and their neural correlates

Emotions are evoked by both internal and external events related to survival challenges. Recent advances in multimodal large language models ((M)LLMs), such as GPT-4, enable them to accurately analyze and describe complex visual scenes, raising the question whether LLMs can also predict human emotional experiences evoked by similar scenes. Here we asked GPT-4 and humans (N = 519) to provide self-reports of 48 unipolar emotions and aFective dimensions for emotionally evocative videos and images. We evaluated GPT-4s emotion ratings using three natural socio-emotional stimulus datasets: two video datasets (234 and 120 videos) and one image dataset (300 images). We found that GPT-4 can predict emotions of human observers with high accuracy. The multivariate emotion structure (correlation matrices of emotions ratings) converged between GPT-4 and humans and across datasets indicating that GPT-4 ratings for diFerent emotions follow similar structural representations as the human evaluations. Finally, we modeled the brains hemodynamic responses for emotions elicited by videos or images in two fMRI datasets (N = 97) with GPT-4 or human-based emotional evaluations to highlight the usefulness of GPT-4 in neuroscientific research. The results showed that the brains emotion circuits can be mapped with high accuracy using GPT-4 emotion ratings as the stimulation model. In conclusion, GPT-4 can predict human emotion ratings to the extent that GPT-4 ratings can also model the associated neural responses. Our results indicate that LLMs provide novel and scalable tools that have broad potential in emotion research, cognitive and aFective neuroscience, and that it can also have practical applications.

neuroscience↗

bioRxiv2025

Neural correlates of approach and avoidance tendencies toward physical activity and sedentary stimuli: An fMRI study

Automatic tendencies toward physical activity and sedentary stimuli are involved in the regulation of physical activity behavior. However, the brain regions underlying these automatic tendencies remain largely unknown. Here, we used an approach-avoidance task and magnetic resonance imaging (MRI) in 42 healthy young adults to investigate whether cortical and subcortical brain regions underpinning reward processing and executive function are associated with these tendencies. At the behavioral level, results showed more errors in avoidance behavior following sedentary stimuli than physical activity stimuli. At the brain level, avoidance behavior following sedentary stimuli was associated with more activation of the motor control network (dorsolateral-prefrontal cortex, primary and secondary motor cortices, somatosensory cortex). In addition, increased activation of the bilateral parahippocampal gyrus -- and structural deformation of the right hippocampus - were associated with a tendency toward approaching sedentary stimuli. Together, these results suggest that avoiding sedentary stimuli requires higher levels of behavioral control than avoiding physical activity stimuli.

neuroscience↗

bioRxiv2021

3D printed pacifier-shaped mouthpiece for fMRI-compatible gustometers

Gustometers have allowed the delivery of liquids in fMRI settings for decades and mouthpieces are a critical part of those taste delivery systems. Here we propose an innovative 3D printed mouthpiece inspired by childrens pacifiers that allow participants to swallow while lying down in an MRI scanner. Our results validate the effectiveness of our method by showing significant clusters of activation in the insular and piriform cortex which are regions that have been consistently identified to compute taste processing. We used a large sample (n=85) to validate our method. Our mouthpiece fulfills several criteria guarantying a gustatory stimulus of quality, making the delivery more precise and reliable. Moreover, this new pacifier-shaped design is: simple and cheap to manufacture, hygienic, comfortable to keep in mouth, and flexible to diverse use cases.We hope that this new method will promote and facilitate the study of taste and flavor perception in the context of reward processing in affective neuroscience and thus help provide an integrative approach to the study of the emotional nature of rewards.

neuroscience↗

bioRxiv2021

Differential contributions of ventral striatum subregions to the motivational and hedonic components of the affective processing of the reward

The ventral striatum is implicated in the affective processing of the reward, which can be divided into a motivational and a hedonic component. Here, we examined whether these two components rely on distinct neural substrates within the ventral striatum in humans. We used a high-resolution fMRI protocol targeting the ventral striatum combined with a Pavlovian-instrumental task and a hedonic reactivity task. Both tasks involved an olfactory reward, thereby allowing us to measure Pavlovian-triggered motivation and sensory pleasure for the same reward within the same participants. Our findings show that different subregions of the ventral striatum are dissociable in their contributions to the motivational and the hedonic component of the affective processing of the reward. Parsing the neural mechanisms and the interplay between Pavlovian incentive processes and hedonic processes might have important implications for understanding compulsive reward-seeking behaviors such as addiction, binge eating, or gambling.

neuroscience↗

bioRxiv2017

Reward and automatic processes in exercise behavior: A new approach and a systematic review

BackgroundIn a time of physical inactivity pandemic, attempts to better understand the factors underlying the regulation of exercise behavior is important. The dominant neuropsychological approach to exercise behavior explains physical activity as a reward. However, the opposite of physical exertion -- behaviors minimizing energy cost -- may also be a reward, which activates automatic reactions favoring the engagement in behaviors associated with lower energetic costs.\n\nObjectiveOur objective was to systematically review studies testing the automatic reactions triggered by stimuli associated with different types of exercise behavior (e.g., physical activity, sedentary behaviors) and energetic cost variations (e.g., behaviors minimizing energetic cost).\n\nMethodsTwo authors systematically searched, screened, extracted, and analyzed data from articles in the MEDLINE database.\n\nResultsWe included 26 studies. Three types of automatic processes were tested: Affective reactions, attentional capture, and approach tendencies. Results show that automatic reactions toward stimuli depicting exercise behaviors explained individuals level of physical activity. Brain imaging results show that stimuli associated with exercise behavior activate regions associated with reward, but these studies were scarce.\n\nConclusionReward is an important factor of exercise behavior. There is strong evidence showing that physical activity is a reward. While brain imaging results suggest that sedentary behaviors are also a reward, behaviors minimizing energetic cost have not been investigated so far. Additional studies are required to establish a strong and complete framework of reward in exercise behavior.\n\nKey points- Behavioral and brain imaging studies using different types of automatic behavior show that physical activity is a reward\n- Behaviors minimizing energetic cost have been essential to evolutionary survival and are likely to be a reward. However, experimental evidence remains scarce\n- The dominant neuropsychological approaches to exercise behavior may be incomplete, which may partly explain our current inability to counteract the pandemic of physical inactivity

neuroscience↗