Advances in research on brain processing of food odors using different neuroimaging techniques

From Traditional to Intelligent, A Review of Application and Progress of Sensory Analysis in Alcoholic Beverage Industry

Sensory analysis is an interdisciplinary field that combines multiple disciplines to analyze food qualitatively and quantitatively. At present, this analysis method has been widely used in product development, quality control, marketing, flavor analysis, safety supervision and inspection of alcoholic beverages. Due to the changing needs of analysis, new and more optimized methods are still emerging. Thereinto, intelligent and biometric technologies with growing attention have also been applied to sensory analysis. This work summarized the sensory analysis methods from three aspects, including traditional artificial sensory analysis, intelligent sensory technology, and innovative technologies. Meanwhile, the application sensory analysis in alcoholic beverages and its industrial production was scientifically emphasized. Moreover, the future tendency of sensory analysis in the alcoholic beverage industry is also highlights.

Enhancing classification accuracy of HRF signals in fNIRS using semi-supervised learning and filtering

This paper introduces a novel approach to enhance the classification accuracy of hemodynamic response function (HRF) signals acquired through functional near-infrared spectroscopy (fNIRS). Leveraging a semi-supervised learning (SSL) framework alongside a filtering technique, the study preprocesses HRF data effectively before applying the SSL algorithm. Collected from the prefrontal cortex, HRF signals capture variations in oxyhemoglobin (oxyHb) and deoxyhemoglobin (deoxyHb) levels in response to odor stimuli and air state. Training the classification model on a dataset containing filtered and feature-extracted HRF signals led to significant improvements in classification accuracy. By comparing the algorithm's performance before and after employing the proposed filtering technique, the study provides compelling evidence of its effectiveness. These findings hold promise for advancing functional brain imaging research and cognitive studies, facilitating a deeper understanding of brain responses across various experimental contexts.

An advance in novel intelligent sensory technologies: From an implicit-tracking perspective of food perception

Food sensory evaluation mainly includes explicit and implicit measurement methods. Implicit measures of consumer perception are gaining significant attention in food sensory and consumer science as they provide effective, subconscious, objective analysis. A wide range of advanced technologies are now available for analyzing physiological and psychological responses, including facial analysis technology, neuroimaging technology, autonomic nervous system technology, and behavioral pattern measurement. However, researchers in the food field often lack systematic knowledge of these multidisciplinary technologies and struggle with interpreting their results. In order to bridge this gap, this review systematically describes the principles and highlights the applications in food sensory and consumer science of facial analysis technologies such as eye tracking, facial electromyography, and automatic facial expression analysis, as well as neuroimaging technologies like electroencephalography, magnetoencephalography, functional magnetic resonance imaging, and functional near-infrared spectroscopy. Furthermore, we critically compare and discuss these advanced implicit techniques in the context of food sensory research and then accordingly propose prospects. Ultimately, we conclude that implicit measures should be complemented by traditional explicit measures to capture responses beyond preference. Facial analysis technologies offer a more objective reflection of sensory perception and attitudes toward food, whereas neuroimaging techniques provide valuable insight into the implicit physiological responses during food consumption. To enhance the interpretability and generalizability of implicit measurement results, further sensory studies are needed. Looking ahead, the combination of different methodological techniques in real-life situations holds promise for consumer sensory science in the field of food research.

Enhancement effect of odor and multi-sensory superposition on sweetness

The impact of sugary foods on public health has contributed to the development of low-sugar and sugar-substituted products, and sugar reduction has become a major challenge for the food industry. There is growing empirical evidence that odor can enhance the perception of sweetness without increasing the caloric load. This current review summarizes the researches on odor-induced sweetness enhancement published in recent years and discusses the mechanisms and influencing factors of odor-sweetness interactions. In addition, by combing existing studies, this paper also summarizes the research methods and strategies to investigate odor-induced sweetness enhancement. Finally, the feasibility of synergistic enhancement of sweetness through the superposition of odor with other senses (texture, visual, etc.) is also discussed and analyzed. In conclusion, odor-induced sweetness enhancement may present an alternative or complementary approach for developing foods with less sugar.

Insights into brain perceptions of the different taste qualities and hedonic valence of food via scalp electroencephalogram

Investigating brain activity is essential for exploring taste-experience related cues. The paper aimed to explore implicit (unconscious) emotional or physiological responses related to taste experiences using scalp electroencephalogram (EEG). We performed implicit measures of tastants of differing perceptual types (bitter, salty, sour and sweet) and intensities (low, medium, and high). The results showed that subjects were partially sensitive to different sensory intensities, i.e., for high intensities, taste stimuli could induce activation of different rhythm signals in the brain, with α and θ bands possibly being more sensitive to different taste types. Furthermore, the neural representations and corresponding sensory qualities (e.g., "sweet: pleasant" or "bitter: unpleasant") of different tastes could be discriminated at 250-1,500 ms after stimulus onset, and different tastes exhibited distinct temporal dynamic differences. Source localization indicated that different taste types activate brain areas associated with emotional eating, reward processing, and motivated tendencies, etc. Overall, our findings reveal a larger sophisticated taste map that accounted for the diversity of taste types in the human brain and assesses the emotion, reward, and motivated behavior represented by different tastes. This study provided basic insights and a perceptual foundation for the relationship between taste experience-related decisions and the prediction of brain activity.

Integrative Hedonic and Homeostatic Food Intake Regulation by the Central Nervous System: Insights from Neuroimaging

Food intake regulation in humans is a complex process controlled by the dynamic interaction of homeostatic and hedonic systems. Homeostatic regulation is controlled by appetitive signals from the gut, adipose tissue, and the vagus nerve, while conscious and unconscious reward processes orchestrate hedonic regulation. On the one hand, sight, smell, taste, and texture perception deliver potent food-related feedback to the central nervous system (CNS) and influence brain areas related to food reward. On the other hand, macronutrient composition stimulates the release of appetite signals from the gut, which are translated in the CNS into unconscious reward processes. This multi-level regulation process of food intake shapes and regulates human ingestive behavior. Identifying the interface between hormones, neurotransmitters, and brain areas is critical to advance our understanding of conditions like obesity and develop better therapeutical interventions. Neuroimaging studies allow us to take a glance into the central nervous system (CNS) while these processes take place. This review focuses on the available neuroimaging evidence to describe this interaction between the homeostatic and hedonic components in human food intake regulation.

Brain Responses to High-Calorie Visual Food Cues in Individuals with Normal-Weight or Obesity: An Activation Likelihood Estimation Meta-Analysis

Overconsumption of high-calorie or unhealthy foods commonly leads to weight gain. Understanding people’s neural responses to high-calorie food cues might help to develop better interventions for preventing or reducing overeating and weight gain. In this review, we conducted a coordinate-based meta-analysis of functional magnetic resonance imaging studies of viewing high-calorie food cues in both normal-weight people and people with obesity. Electronic databases were searched for relevant articles, retrieving 59 eligible studies containing 2410 unique participants. The results of an activation likelihood estimation indicate large clusters in a range of structures, including the orbitofrontal cortex (OFC), amygdala, insula/frontal operculum, culmen, as well as the middle occipital gyrus, lingual gyrus, and fusiform gyrus. Conjunction analysis suggested that both normal-weight people and people with obesity activated OFC, supporting that the two groups share common neural substrates of reward processing when viewing high-calorie food cues. The contrast analyses did not show significant activations when comparing obesity with normal-weight. Together, these results provide new important evidence for the neural mechanism underlying high-calorie food cues processing, and new insights into common and distinct brain activations of viewing high-calorie food cues between people with obesity and normal-weight people.