scholarly journals Neural Correlates of Attitudes and Risk Perception for Food Technology Topics

2019 ◽  
Author(s):  
Tyler Davis ◽  
Mark LaCour ◽  
Erin Beyer ◽  
Jessica L. Finck ◽  
Markus F. Miller
Keyword(s):  
Prefrontal Cortex ◽  
Risk Perception ◽  
Resistance To Change ◽  
Neural Correlates ◽  
Consumer Acceptability ◽  
Technological Innovations ◽  
Food Technology ◽  
Perceptions Of Risk ◽  
Subjective Value ◽  
The Brain

AbstractFood technologies provide numerous benefits to society and are extensively vetted for safety. However, many technological innovations still face high levels of skepticism from consumers. To promote development and use of food technologies, it is critical to understand the psychological and neurobiological processes associated with consumer acceptability concerns. The current study uses a neuroscience-based approach to understand consumer attitudes and perceptions of risk associated with food technologies and investigate how such attitudes impact consumer’s processing of information related to food technologies. We used functional magnetic resonance imaging (fMRI) to measure brain activation while participants processed infographics related to food technology topics. For technology topics perceived as riskier (antibiotics and hormones), activation was higher in areas of the lateral prefrontal cortex that are associated with decisional uncertainty. In contrast, technology topics that were viewed more favorably (sustainability and animal welfare) tended to activate the ventromedial prefrontal cortex, a region that processes positive affect and subjective value. Moreover, for information about hormones, the lateral PFC activation was associated with individual differences in resistance to change in risk perception. These results reveal how attitudes and risk perception relate to how the brain processes information about food technologies and how people respond to information about such technologies.

scholarly journals Subjective value and decision entropy are jointly encoded by aligned gradients across the human brain

2020 ◽  
Author(s):  
Sebastian Bobadilla-Suarez ◽  
Olivia Guest ◽  
Bradley C. Love
Keyword(s):  
Prefrontal Cortex ◽  
Human Brain ◽  
Ventromedial Prefrontal Cortex ◽  
Neural Representation ◽  
Retrospective Evaluation ◽  
Systematic Fashion ◽  
Subjective Value ◽  
Fmri Analysis ◽  
The Relationship ◽  
The Brain

AbstractRecent work has considered the relationship between value and confidence in both behavior and neural representation. Here we evaluated whether the brain organizes value and confidence signals in a systematic fashion that reflects the overall desirability of options. If so, regions that respond to either increases or decreases in both value and confidence should be widespread. We strongly confirmed these predictions through a model-based fMRI analysis of a mixed gambles task that assessed subjective value (SV) and inverse decision entropy (iDE), which is related to confidence. Purported value areas more strongly signalled iDE than SV, underscoring how intertwined value and confidence are. A gradient tied to the desirability of actions transitioned from positive SV and iDE in ventromedial prefrontal cortex to negative SV and iDE in dorsal medial prefrontal cortex. This alignment of SV and iDE signals could support retrospective evaluation to guide learning and subsequent decisions.

scholarly journals Neuro-computational account of arbitration between imitation and emulation during human observational learning

2019 ◽  
Author(s):  
Caroline C. Charpentier ◽  
Kiyohito Iigaya ◽  
John P. O’Doherty
Keyword(s):  
Prefrontal Cortex ◽  
Observational Learning ◽  
Computational Modelling ◽  
Neural Correlates ◽  
Fundamental Question ◽  
Behavioral Task ◽  
Reliable Prediction ◽  
Ventrolateral Prefrontal Cortex ◽  
Temporoparietal Junction ◽  
The Brain

AbstractIn observational learning (OL), organisms learn from observing the behavior of others. There are at least two distinct strategies for OL. Imitation involves learning to repeat the previous actions of other agents, while in emulation, learning proceeds from inferring the goals and intentions of others. While putative neural correlates for these forms of learning have been identified, a fundamental question remains unaddressed: how does the brain decides which strategy to use in a given situation? Here we developed a novel computational model in which arbitration between the strategies is determined by the predictive reliability, such that control over behavior is adaptively weighted toward the strategy with the most reliable prediction. To test the theory, we designed a novel behavioral task in which our experimental manipulations produced dissociable effects on the reliability of the two strategies. Participants performed this task while undergoing fMRI in two independent studies (the second a pre-registered replication of the first). Behavior manifested patterns consistent with both emulation and imitation and flexibly changed between the two strategies as expected from the theory. Computational modelling revealed that behavior was best described by an arbitration model, in which the reliability of the emulation strategy determined the relative weights allocated to behavior for each strategy. Emulation reliability - the model’s arbitration signal - was encoded in the ventrolateral prefrontal cortex, temporoparietal junction and rostral cingulate cortex. Being replicated across two fMRI studies, these findings suggest a neuro-computational mechanism for allocating control between emulation and imitation during observational learning.

scholarly journals Neural Responses in Dorsal Prefrontal Cortex Reflect Proactive Interference during an Auditory Reversal Task

2018 ◽  
Author(s):  
Nikolas A. Francis ◽  
Susanne Radtke-Schuller ◽  
Jonathan B. Fritz ◽  
Shihab A. Shamma
Keyword(s):  
Prefrontal Cortex ◽  
Frontal Cortex ◽  
Proactive Interference ◽  
Cognitive Flexibility ◽  
Neural Activity ◽  
Neural Correlates ◽  
Neural Responses ◽  
Reversal Task ◽  
Neural Correlate ◽  
The Brain

AbstractTask-related plasticity in the brain is triggered by changes in the behavioral meaning of sounds. We investigated plasticity in ferret dorsolateral frontal cortex (dlFC) during an auditory reversal task to study the neural correlates of proactive interference, i.e., perseveration of previously learned behavioral meanings that are no longer task-appropriate. Although the animals learned the task, target recognition decreased after reversals, indicating proactive interference. Frontal cortex responsiveness was consistent with previous findings that dlFC encodes the behavioral meaning of sounds. However, the neural responses observed here were more complex. For example, target responses were strongly enhanced, while responses to non-target tones and noises were weakly enhanced and strongly suppressed, respectively. Moreover, dlFC responsiveness reflected the proactive interference observed in behavior: target responses decreased after reversals, most significantly during incorrect behavioral responses. These findings suggest that the weak representation of behavioral meaning in dlFC may be a neural correlate of proactive interference.Significance StatementNeural activity in prefrontal cortex (PFC) is believed to enable cognitive flexibility during sensory-guided behavior. Since PFC encodes the behavioral meaning of sensory events, we hypothesized that weak representation of behavioral meaning in PFC may limit cognitive flexibility. To test this hypothesis, we recorded neural activity in ferret PFC, while ferrets performed an auditory reversal task in which the behavioral meanings of sounds were reversed during experiments. The reversal task enabled us study PFC responses during proactive interference, i.e. perseveration of previously learned behavioral meanings that are no longer task-appropriate. We found that task performance errors increased after reversals while PFC representation of behavioral meaning diminished. Our findings suggest that proactive interference may occur when PFC forms weak sensory-cognitive associations.

scholarly journals Functional Neuroimaging Reveals Neural Processes Underlying Food Technology Attitudes and Risk Perception

2019 ◽  
Vol 3 (2) ◽  
Author(s):  
E. S. Beyer ◽  
M. LaCour ◽  
M. F. Miller ◽  
T. H. Davis ◽  
J. L. Finck
Keyword(s):  
Risk Perception ◽  
Animal Welfare ◽  
Perceived Risk ◽  
Functional Neuroimaging ◽  
Middle Temporal Gyrus ◽  
Food Technology ◽  
Process Information ◽  
Mixed Effect ◽  
Perceptions Of Risk ◽  
Positive Attitudes

ObjectivesAdvances in food technology provide numerous benefits including improvements in sustainability, quality, and food security. However, consumers often perceive such technologies as risky, even when extensively vetted for safety. Neuroimaging has the potential to reveal how the consumer brain processes information about technologies and how this processing relates to their attitudes and risk perception. The current study used functional magnetic resonance imaging (fMRI) to examine how brain activation during processing of infographics about food technologies related to subsequent ratings of risk and attitudes. Based on neuroeconomic research, we hypothesized that the ventromedial prefrontal cortex (vmPFC) would track positive attitudes for the technologies due to its role in computing subjective value and positive affect. In contrast, we predicted that the lateral PFC would track perceptions of risk associated with the technologies due to its role in processing conflict and uncertainty.Materials and MethodsParticipants (n = 53; 31 Female; Age 18- 43) completed a neuroimaging study at Texas Tech Neuroimaging Institute. Participants were scanned while viewing 6 different food technology infographics in 30s blocks: hormone implants, antibiotics, vaccines, GMOs, animal welfare technology, and sustainability technologies. Between viewing blocks, participants answered attitudes and risk perception questions for each technology. The scans were analyzed using a mixed effect implemented in FSL’s FEAT software and corrected for multiple comparisons (p < 0.05) using cluster-based thresholding with a primary threshold of z = 3.1 (p < 0.001).ResultsParticipants had lower attitudes and higher risk perception for antibiotics and hormones relative to GMOs and vaccines (risk perception: t(52) = 5.07, p < 0.001; attitudes: t(52) = 8.35, p < 0.001) and animal welfare and sustainability technologies (risk perception: t(52) = 6.60, p < 0.001; attitudes: t(52) = 7.65, p < 0.001). Consistent with our predictions, a cluster in lateral PFC (1496 voxels, p < 0.001) was positively associated with between-infographic differences in risk perception (and negatively associated with attitudes) such that it was most highly activated for the hormones and antibiotics and less so for the lower perceived risk technologies. Additionally, we observed a cluster in vmPFC (648 voxels, p < 0.001) that was positively associated with attitudes and thus was most highly activated for the lower perceived risk and higher attitude technologies. Several additional areas were associated with risk and attitudes including lateral parietal cortex, precuneus, occipital, and middle temporal gyrus (p < 0.05).ConclusionOur results present a critical step forward in understanding how consumers process information about food technologies. We found areas of the vmPFC tracked positive attitudes and lateral PFC tracked perceptions of risk and lower attitudes. These findings are important because they suggest that PFC regions may contribute to how consumers process information about food technologies, which can affect how they retain and use information to update their beliefs. Future research should examine whether fMRI may be useful prospectively for predicting consumer responses to information campaigns about food technologies.

scholarly journals The dorsomedial prefrontal cortex computes task-invariant relative subjective value for self and other

eLife ◽  
2019 ◽  
Vol 8 ◽  
Author(s):  
Matthew Piva ◽  
Kayla Velnoskey ◽  
Ruonan Jia ◽  
Amrita Nair ◽  
Ifat Levy ◽  
...  
Keyword(s):  
Prefrontal Cortex ◽  
Neural Correlates ◽  
Risky Choice ◽  
Behavioral Modeling ◽  
Self And Other ◽  
Dorsomedial Prefrontal Cortex ◽  
Subjective Value ◽  
Neural Computations ◽  
Decoding Accuracy ◽  
Independent Tasks

Few studies have addressed the neural computations underlying decisions made for others despite the importance of this ubiquitous behavior. Using participant-specific behavioral modeling with univariate and multivariate fMRI approaches, we investigated the neural correlates of decision-making for self and other in two independent tasks, including intertemporal and risky choice. Modeling subjective valuation indicated that participants distinguished between themselves and others with dissimilar preferences. Activity in the dorsomedial prefrontal cortex (dmPFC) and ventromedial prefrontal cortex (vmPFC) was consistently modulated by relative subjective value. Multi-voxel pattern analysis indicated that activity in the dmPFC uniquely encoded relative subjective value and generalized across self and other and across both tasks. Furthermore, agent cross-decoding accuracy between self and other in the dmPFC was related to self-reported social attitudes. These findings indicate that the dmPFC emerges as a medial prefrontal node that utilizes a task-invariant mechanism for computing relative subjective value for self and other.

scholarly journals Subjective value and decision entropy are jointly encoded by aligned gradients across the human brain

2020 ◽  
Vol 3 (1) ◽  
Author(s):  
Sebastian Bobadilla-Suarez ◽  
Olivia Guest ◽  
Bradley C. Love
Keyword(s):  
Prefrontal Cortex ◽  
Human Brain ◽  
Ventromedial Prefrontal Cortex ◽  
Neural Representation ◽  
Retrospective Evaluation ◽  
Systematic Fashion ◽  
Subjective Value ◽  
Fmri Analysis ◽  
The Relationship ◽  
The Brain

Abstract Recent work has considered the relationship between value and confidence in both behavioural and neural representation. Here we evaluated whether the brain organises value and confidence signals in a systematic fashion that reflects the overall desirability of options. If so, regions that respond to either increases or decreases in both value and confidence should be widespread. We strongly confirmed these predictions through a model-based fMRI analysis of a mixed gambles task that assessed subjective value (SV) and inverse decision entropy (iDE), which is related to confidence. Purported value areas more strongly signalled iDE than SV, underscoring how intertwined value and confidence are. A gradient tied to the desirability of actions transitioned from positive SV and iDE in ventromedial prefrontal cortex to negative SV and iDE in dorsal medial prefrontal cortex. This alignment of SV and iDE signals could support retrospective evaluation to guide learning and subsequent decisions.

scholarly journals Perceived Norms Influence Perceptions of Risk and Attitudes for Food Technologies

2019 ◽  
Vol 3 (2) ◽  
Author(s):  
M. LaCour ◽  
E. Beyer ◽  
J. L. Finck ◽  
M. Miller ◽  
T. Davis
Keyword(s):  
Risk Perception ◽  
Animal Welfare ◽  
Multiple Regression ◽  
Risk Perceptions ◽  
Regression Models ◽  
Critical Role ◽  
Food Technology ◽  
Psychological Variables ◽  
Perceived Norms ◽  
Perceptions Of Risk

ObjectivesUnderstanding the factors that influence consumer attitudes and risk perception is critical for effective marketing of new food technologies. Many variables impact attitudes and risk perception. However, food technology research has largely focused on demographic variables, and often only single technologies (e.g., GMOs). Our goal was to determine how psychological variables differentially influence attitudes and risk perception for a range of food technologies: antibiotics, hormones, vaccines, GMOs, sustainability, and animal welfare technologies. We examined how attitudes and risk perception for these technologies related to four social psychological variables from the Theory of Planned Behavior (TPB): perceived norms, past behavior, familiarity, and perceived control. In addition, we measured general Food Technology Neophobia (FTN), Trust in Science (TIS), chemical reasoning (CR).Materials and MethodsParticipants (n = 394) provided demographics followed by TPB, attitude, and risk perception surveys for each of the six technologies. Then they completed FTN, TIS, and a CR survey measuring dose–response beliefs (DR), beliefs in unknown risks (UR), the role of risk in society (RS), and naturalness/knowledge of chemicals (NKC). Multiple regression analyses were used to test for associations among the survey measures.ResultsThe multiple regression models were all significant (p < 0.05). Variance accounted for (R2) ranged from 0.49 to0.69 (See Table 1 for summary). Perceived norms were the strongest predictor of attitudes and risk with higher values being associated with stronger attitudes (standardized betas ranging from 0.51 to 0.71) and lower risk perception (–0.54 to –0.40). There were a number of technology-specific associations, including familiarity increasing perceptions of risk for hormones, and NKC being primarily associated with animal welfare and sustainability technologies.ConclusionThe present findings show a critical role for perceived norms– a person’s perception that people they like also approve of or use a technology– across all technologies. This suggests that social factors like norms play a major role in consumer acceptance of food technologies. Other predictors varied in strength across technologies suggesting marketing may benefit from strategies tailored to specific technologies.Table 1Standardized betas (> 0.10 in bold) from selected coefficients of regression models predicting risk perceptions and attitudes (rows) for each technology (columns)

scholarly journals Neural correlates of attitudes and risk perception for food technology topics

2020 ◽  
Vol 80 ◽  
pp. 103836
Author(s):  
Tyler Davis ◽  
Mark LaCour ◽  
Erin Beyer ◽  
Jessica L. Finck ◽  
Markus F. Miller
Keyword(s):  
Risk Perception ◽  
Neural Correlates ◽  
Food Technology

scholarly journals Base-rate neglect and neural computations for subjective weight in probabilistic inference

2019 ◽  
Author(s):  
Yun-Yen Yang ◽  
Shih-Wei Wu
Keyword(s):  
Prefrontal Cortex ◽  
Medial Prefrontal Cortex ◽  
Orbitofrontal Cortex ◽  
Base Rate ◽  
Policy Implications ◽  
Sources Of Information ◽  
Base Rate Neglect ◽  
Subjective Weight ◽  
Subjective Value ◽  
The Brain

AbstractHumans show systematic biases when estimating probability of uncertain events. Base-rate neglect is a well-known bias that describes the tendency to underweight information from the past relative to the present. In this study, we characterized base-rate neglect at the computational and neural implementation levels. At the computational level, we established that base-rate neglect arises from insufficient adjustment to weighting prior information in response to changes in prior variability. At the neural implementation level, we found that orbitofrontal cortex (OFC) and medial prefrontal cortex (mPFC) represent subjective weighting of information that reflects base-rate neglect. Critically, both subjective-weight and subjective-value signals that guide choice were found in mPFC. However, subjective-weight signals preceded subjective-value signals. These results indicate that when facing multiple sources of information, estimation bias such as base-rate neglect arises from information weighting computed in OFC and mPFC, which directly contributes to subjective-value computations that guide decisions under uncertainty.Significance StatementFacing uncertainty, estimating the probability of different potential outcomes carries significant weight in affecting how we act and decide. Decades of research show that humans are prone to giving biased estimation but it remains elusive how these biases arise in the brain. We focus on base-rate neglect, a well-known bias in probability estimation and find that it is tightly associated with activity in the medial prefrontal cortex and orbitofrontal cortex. These regions represent the degree to which human participants weigh different sources of information, suggesting that base-rate neglect arises from information-weighting computations in the brain. As technology provides us the opportunity to seek and gather information at an ever-increasing pace, understanding information-weighting and its biases also carry important policy implications.

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