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Introduction: Neuromarketing is an interdisciplinary field that is rapidly emerging in the world of consumer cognition research. Furthermore, it is an innovative field of marketing research which challenges the classic marketing model to improve our understanding of the processes associated with purchasing behavior. Neuromarketing is investigating the manner that consumers make the decision to purchase. Based on the neuromarketing concept of decision processing, consumer buying decisions rely on bi-systemic approaches. System 1 is based on fast automatic operations in contrast, decisions driven by System 2 are deliberate, conscious reasoning, and slow. In cognition of the consumer behavior, these processes guide everyday purchasing decisions. Furthermore, neuromarketing is built on the top of at least three basic science fields, including neuroscience, behavioral economics, and social psychology. The aim of this review was to investigate the different aspects of neuroscience involved in neuromarketing. The signals from the human body and brain are important for understanding the origins and operations of neuromarketing measures. Body measures are contained the facial expressions, eye movements, eye blink, startle reflex, behavioral responses, electrodermal activity, heart rate, blood pressure, pupil dilation, and respiration. The human brain signals are captured by the blood oxygenation, positron emissions, electrical fields, and magnetic fields. Conclusion: Understanding the basic functions of human brain is crucial in investigation of consumers’ purchasing behaviors.

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Introduction: Decision process is an accumulation-to-bound mechanism, in which momentary sensory evidence is accumulated over time toward a criterion level. This bounded evidence accumulation is represented in the activity of neurons in the lateral intraparietal (LIP) cortex. Whether the firing rate of LIP neuron contains post decision information (PDI) or returns to baseline level as soon as decision made needs to be clarified. Materials and Methods: To investigate this issue, we conducted behavioral experiments based on the two forced-choice discrimination of motion direction. Human subjects reported the net direction of stochastic random dot motion by pressing a key of specified keys associated with the two possible directions of motion. Trials were separated by different time gaps. Results: Results showed that there is a preference in subjects to make a same decision as their pervious decision, especially in weak stimuli. Conclusion: Our findings suggest that the value of decision variable (DV) after crossing the bound (named PDI) may accumulate with DV for the next decisions.

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Introduction: Most decisions are based on the accumulation of discrete pieces of evidence. This evidence has usually been separated with the various intervals. Indeed, how the brain gathers and combines distinct pieces of information received at different times is need to be clarified. In order to investigate the kinship between brain function and human behavior, the behavioral experimental studies could be designed. Previous studies demonstrated that subjects gather and effectively combine discrete evidence to improve their accuracy. In addition, it has been shown that the latest information has a larger influence on decisions. However, it remains unclear that why this larger influence of the later pulses occurs and what can affect this influence. Materials and Methods: Dealing with these questions a perceptual decision-making task has been implemented by the psychophysics’ toolbox in MATLAB. Subjects, during the task, were instructed to report the direction of motion in a noisy random dot stimulus with certain keys. Stimuli were presented in continuous (one pulse) or discrete (two continuousness pulses separated with different intervals) form. Each of these two forms of stimuli was presented randomly during each session. Each session has been included 300 trials. Each subject has done 3600 trials. Data have been analyzed by regression models. Results: We observed that in double-pulse trials, the strength of the second pulse was more crucial in the accuracy of responses compared to the first pulse. In addition, this accuracy was dependent on the differences between the strength of the first and the last pulses. Conclusion: These findings suggest that a key factor which affects the importance of pulses is the strength of the previous pulse. As the difference between the motion strength increases, the effect of the second pulse on choice accuracy enhanced.

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Introduction: The increasing prevalence of smoking, despite the awareness of its potential damages, may be due to various causes. Impairments of the neurocognitive functions have been identified in a variety of addictive behaviors. Accordingly, the aim of the present study was to investigate neurocognitive performance relative defects in smoking people compared to the non-smoking subjects. Materials and Methods: This investigation is a causal-comparative study. The sample of 50 subjects (aged 21-32 years), 25 male smoker student and 25 non-smokers were chosen through convenience sampling from the University of Guilan. These subjects answered researcher-made cigarette checklist and worked with software tests of Cambridge Gambling, Stroop’s Color-Word, and Tower of London, for evaluation risky decision making, response inhibition, and planning and problem solving. Results: The results of multivariate analysis of variance showed that two groups of smoker and non-smoker people have shown different results of software tests of Cambridge Gambling, Stroop’s Color-Word, and Tower of London. Conclusion: The findings of this study indicate that smokers have a poor relative performance in risky decision-making, response inhibition, and planning and problem-solving. These neurocognitive performance relative defects may explain their smoking behavior despite the awareness of potential damages of smoking.

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Introduction: Others’ decision could constantly affect our decisions. There are numerous studies which revealed this effect properly. The social influence could affect most of the decision parameters, especially the confidence.  Recently, an interesting study showed that participants tend to match their confidence to each other while they preserve their decision accuracy in a group decision making task. Since the decision accuracy is not able to explain this effect, the main question is which decision parameter is changing in a way which could be resulted in changing in the confidence and ultimately the confidence matching. Materials and Methods: In order to answer this question, ten subjects attended into a Psycho-Physic study with two separate sessions; Isolated and Social. In both situations, the participants were required to determine the direction of the presented motion dots and report their decision and confidence simultaneously. In the social situation, subjects were paired with four computer-generated partners, which had been created based on the data from the isolated session. The joint decisions were determined by the decision of either partner which had higher confidence. In this session, confidence and decision of the partner were represented to the participant. Results: The results indicated the subjects not only try to match their confidence to their partners, but also reported higher confidence in comparison with the isolated situation. We observed although the confidence matching did not affect the decision accuracy, however, the reaction time varied significantly in both sessions. Conclusion: This study reveals the role of reaction time in changing the confidence and consequently the confidence matching. This study once again emphasis on the reverse correlation of the reaction time and confidence even in a group decision making task.

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Introduction: We encounter different information or stimuli. However, the combination of these stimuli and the quality of their presentation can influence our perception and decision. Despite the importance of these combined stimuli to our judgments and decisions, it is not yet clear how the characteristics of these stimuli affect the decision- making processes. For example, it is not clear whether the time interval between the information we receive can affect the accuracy and speed of decision- making. This study aimed to investigate the effect of the time interval between two different visual stimuli on perceptual decision- making. Materials and Methods: According to psychophysical experiments, it was possible to measure the response to perceptual stimuli and compare perceptual choices. In a Random Dot Motion (RDM), the task was displayed to the participants as the primary visual stimulus and a graphic cue as the second visual stimulus, at different intervals, and then the participant's decision accuracy and reaction time to each of these two stimuli were recorded and analyzed. Results: We found that in RDM (primary stimulus), the accuracy of participants' decisions is not affected by the time interval between the presentation of two stimuli. Instead, the accuracy of the response to the Cue (second visual stimulus) decreases in long time intervals between two stimuli. Interestingly, if two stimuli are presented simultaneously, the decision about each of these stimuli is reasonably accurate; yet, the speed of the decision- making process is slower than when a person encounters two stimuli separated by a time interval. Conclusion: The human visual system can distinguish visual stimuli that are presented with a short time interval in between; however, in exchange for correctly identifying these stimuli, the speed of decision- making may be slowed down.

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Introduction: The decision- making process in the human brain is controlled by two mechanisms: Pavlovian and instrumental learning systems. The Pavlovian system learns the stimulus- outcome association independent of action; a process that manifests itself in the tendency to approach reward- associated stimuli. The instrumental controller, on the other hand, learns the action- outcome association. Instrumental learning is not limited to the current action's outcome and may evaluate a sequence of future actions in the form of forward planning. Nonetheless, forward planning may not be the only planning process used by instrumental learning. Humans may also use backward planning to evaluate actions sequences. However, backward planning has received less attention so far. Previous research has shown that despite the independence of Pavlovian and instrumental learning, they interact with each other such that the Pavlovian approach tendency biases forward planning, causing it to make decisions that may not be optimal actions from the instrumental learning perspective. Nevertheless, the effect of Pavlovian learning on backward planning has not yet been studied. Materials and Methods: This paper designs a navigation experiment that allows investigating forward, backward, and bidirectional planning. Moreover, we embed Pavlovian approach cues into the maps to investigate how they bias the three forms of planning. Results: Statistical analysis of the collected data indicates the existence of backward planning and shows that the Pavlovian- approach cues bias the planning. This bias is stronger in forward planning compared to backward planning and is even stronger in bidirectional planning. In the context of reinforcement learning, we developed a bidirectional planning algorithm under the Pavlovian approach tendency. Conclusion: The simulation results are consistent with the experimental results and indicate that the effect of Pavlovian bias can be modeled as pruning of decision trees.

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Introduction: Certainty is one of the parameters of hierarchical decisions. In hierarchical decisions, decisions at different levels are generally accompanied by uncertainty. After decision-making, the response can be positive or negative feedback. The reason for the negative feedback is unclear. Humans try to resolve this ambiguity by evaluating their certainty, so calculations of hierarchical decisions based on certainty are debatable. The complexity of computation for these types of decisions has made it more important to use other types of information in addition to behavioral data. Since decision processes are mapped to eye responses, this study analyzes the pupil diameter, in addition to behavioral data in the context of hierarchical decisions. In this research, pupil diameter size has been used as a valuable source for predicting hierarchical decision certainty. Materials and Methods: In a hierarchical experiment, the subjects were asked to repeat the direction of the displayed moving points (left or right) at the top or bottom of the screen (top/bottom of the environment), as well as their certainty relative to the selected points, simultaneously. Subjects received auditory positive feedback when they reported both the direction of moving points and the environment correctly. During the experiment, the subjects' eye data were recorded by an eye-tracker device. Results: In hierarchical decisions, high-level decisions depend on the subject's degree of certainty in low-level decisions, and changes in pupil diameter are significantly associated with certainty. Conclusion: This study revealed that in high-level decisions, the average size of the pupil diameter predicts the certainty of decisions and reflects the subject's strategy in complex conditions.

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Introduction: The primary purpose of this study is to identify a network model to attract actual customers through neuromarketing and compare the insurance and mushroom industries. Materials and Methods: The method of study is a descriptive survey. the statistical sample was 9 experts in neuroscience, marketing, insurance, and the mushroom industry selected by Judgmental sampling. The method of analysis is Multiple Attribute Decision Making. Data were collected by the library-questionnaire method. fuzzy Delphi was used to screen, FUZZY DEMATEL to determine the effect of factors, fuzzy network analysis to prioritize dimensions in Excel, and super decision. Results: Dimensions of neuromarketing were identified in 3 dimensions (physiological, personality, and social dimension) and 8 sub-criteria. In the insurance industry, the social dimension of the product (weight: 0.319) with the fulfillment of commitments (weight: 0.074), and in the mushroom industry, the physiological dimension of the product (weight: 0.346) with visual and auditory stimuli (weight: 0.0658) are the most effective dimension of neuromarketing in attracting actual customers. Conclusion: In the insurance industry attention to intangible dimensions, like trust, has a greater role in attracting actual customers. In the mushroom industry, the physiological dimension and visual-auditory senses, which have a tangible nature, have an important role in attracting actual customers. This may be due to brain processes in dealing with tangible and intangible stimuli taken from senses that need to be monitored in specific brain areas using MRI and fMRI.

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Introduction: Obliging to make decisions with only limited and sometimes insufficient evidence is one of the challenges that we face. Previous studies have examined the effect of evidence on performance, confidence, and response time. The question of what leads to a decision with insufficient evidence is still shrouded in ambiguity. This research tries to find an answer by experimenting with random dot motion tasks and using behavioral modeling. Materials and Methods: A random dot motion psychophysics experiment was designed and 10 participants were asked to indicate the direction of dots and the degree of their confidence after observing the movement of the dots. In this experiment, the duration of stimulus display was variable and, in each trial, randomly had one of the six specified durations (80 to 720 milliseconds). As the stimulus display time varied, participants were exposed to sufficient and insufficient evidence to make a decision. The results of the participants' behavioral data were analyzed by psychometric functions and the participants' behavior was modeled using the drift-diffusion model. Results: Our behavioral data indicate that the duration of stimulus display has a significant impact on increasing accuracy and confidence as well as on reducing response time. Behavioral modeling results also showed that the decision components (i.e., threshold separation, drift rate, and none-decision time) are affected by changes in stimulus duration, and threshold separation is significantly affected. The threshold separation increases significantly as the stimulus shows increases. Conclusion: Our investigation supports the hypothesis that the brain changes the decision threshold and adapts to the situation when making decisions based on insufficient evidence.