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Journal articles on the topic 'Sensory expectation'

Author: Grafiati

Published: 24 June 2021

Last updated: 13 February 2022

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1

Kok, Peter, Pim Mostert, and Floris P. de Lange. "Prior expectations induce prestimulus sensory templates." Proceedings of the National Academy of Sciences 114, no. 39 (September 12, 2017): 10473–78. http://dx.doi.org/10.1073/pnas.1705652114.

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Perception can be described as a process of inference, integrating bottom-up sensory inputs and top-down expectations. However, it is unclear how this process is neurally implemented. It has been proposed that expectations lead to prestimulus baseline increases in sensory neurons tuned to the expected stimulus, which in turn, affect the processing of subsequent stimuli. Recent fMRI studies have revealed stimulus-specific patterns of activation in sensory cortex as a result of expectation, but this method lacks the temporal resolution necessary to distinguish pre- from poststimulus processes. Here, we combined human magnetoencephalography (MEG) with multivariate decoding techniques to probe the representational content of neural signals in a time-resolved manner. We observed a representation of expected stimuli in the neural signal shortly before they were presented, showing that expectations indeed induce a preactivation of stimulus templates. The strength of these prestimulus expectation templates correlated with participants’ behavioral improvement when the expected feature was task-relevant. These results suggest a mechanism for how predictive perception can be neurally implemented.

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Panichello, Matthew F., and Nicholas B. Turk-Browne. "Behavioral and Neural Fusion of Expectation with Sensation." Journal of Cognitive Neuroscience 33, no. 5 (April 1, 2021): 814–25. http://dx.doi.org/10.1162/jocn_a_01684.

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Abstract Humans perceive expected stimuli faster and more accurately. However, the mechanism behind the integration of expectations with sensory information during perception remains unclear. We investigated the hypothesis that such integration depends on “fusion”—the weighted averaging of different cues informative about stimulus identity. We first trained participants to map a range of tones onto faces spanning a male–female continuum via associative learning. These two features served as expectation and sensory cues to sex, respectively. We then tested specific predictions about the consequences of fusion by manipulating the congruence of these cues in psychophysical and fMRI experiments. Behavioral judgments and patterns of neural activity in auditory association regions revealed fusion of sensory and expectation cues, providing evidence for a precise computational account of how expectations influence perception.

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3

Kok, Peter, Michel F. Failing, and Floris P. de Lange. "Prior Expectations Evoke Stimulus Templates in the Primary Visual Cortex." Journal of Cognitive Neuroscience 26, no. 7 (July 2014): 1546–54. http://dx.doi.org/10.1162/jocn_a_00562.

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Sensory processing is strongly influenced by prior expectations. Valid expectations have been shown to lead to improvements in perception as well as in the quality of sensory representations in primary visual cortex. However, very little is known about the neural correlates of the expectations themselves. Previous studies have demonstrated increased activity in sensory cortex following the omission of an expected stimulus, yet it is unclear whether this increased activity constitutes a general surprise signal or rather has representational content. One intriguing possibility is that top–down expectation leads to the formation of a template of the expected stimulus in visual cortex, which can then be compared with subsequent bottom–up input. To test this hypothesis, we used fMRI to noninvasively measure neural activity patterns in early visual cortex of human participants during expected but omitted visual stimuli. Our results show that prior expectation of a specific visual stimulus evokes a feature-specific pattern of activity in the primary visual cortex (V1) similar to that evoked by the corresponding actual stimulus. These results are in line with the notion that prior expectation triggers the formation of specific stimulus templates to efficiently process expected sensory inputs.

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YANAGISAWA, Hideyoshi. "How does expectation affect sensory experience?" International Symposium on Affective Science and Engineering ISASE2019 (2019): 1–4. http://dx.doi.org/10.5057/isase.2019-c000014.

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Elijah, Ruth B., Mike E. Le Pelley, and Thomas J. Whitford. "Act Now, Play Later: Temporal Expectations Regarding the Onset of Self-initiated Sensations Can Be Modified with Behavioral Training." Journal of Cognitive Neuroscience 30, no. 8 (August 2018): 1145–56. http://dx.doi.org/10.1162/jocn_a_01269.

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Mechanisms of motor-sensory prediction are dependent on expectations regarding when self-generated feedback will occur. Existing behavioral and electrophysiological research suggests that we have a default expectation for immediate sensory feedback after executing an action. However, studies investigating the adaptability of this temporal expectation have been limited in their ability to differentiate modified expectations per se from effects of stimulus repetition. Here, we use a novel, within-participant procedure that allowed us to disentangle the effect of repetition from expectation and allowed us to determine whether the default assumption for immediate feedback is fixed and resistant to modification or is amenable to change with experience. While EEG was recorded, 45 participants completed a task in which they repeatedly pressed a button to produce a tone that occurred immediately after the button press (immediate training) or after a 100-msec delay (delayed training). The results revealed significant differences in the patterns of cortical change across the two training conditions. Specifically, there was a significant reduction in the cortical response to tones across delayed training blocks but no significant change across immediate training blocks. Furthermore, experience with delayed training did not result in increased cortical activity in response to immediate feedback. These findings suggest that experience with action–sensation delays broadens the window of temporal expectations, allowing for the simultaneous anticipation of both delayed and immediate motor-sensory feedback. This research provides insights into the mechanisms underlying motor-sensory prediction and may represent a novel therapeutic avenue for psychotic symptoms, which are ostensibly associated with sensory prediction abnormalities.

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Emberson, Lauren L., John E. Richards, and Richard N. Aslin. "Top-down modulation in the infant brain: Learning-induced expectations rapidly affect the sensory cortex at 6 months." Proceedings of the National Academy of Sciences 112, no. 31 (July 20, 2015): 9585–90. http://dx.doi.org/10.1073/pnas.1510343112.

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Recent theoretical work emphasizes the role of expectation in neural processing, shifting the focus from feed-forward cortical hierarchies to models that include extensive feedback (e.g., predictive coding). Empirical support for expectation-related feedback is compelling but restricted to adult humans and nonhuman animals. Given the considerable differences in neural organization, connectivity, and efficiency between infant and adult brains, it is a crucial yet open question whether expectation-related feedback is an inherent property of the cortex (i.e., operational early in development) or whether expectation-related feedback develops with extensive experience and neural maturation. To determine whether infants’ expectations about future sensory input modulate their sensory cortices without the confounds of stimulus novelty or repetition suppression, we used a cross-modal (audiovisual) omission paradigm and used functional near-infrared spectroscopy (fNIRS) to record hemodynamic responses in the infant cortex. We show that the occipital cortex of 6-month-old infants exhibits the signature of expectation-based feedback. Crucially, we found that this region does not respond to auditory stimuli if they are not predictive of a visual event. Overall, these findings suggest that the young infant’s brain is already capable of some rudimentary form of expectation-based feedback.

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YANAGISAWA, Hideyoshi. "Erratum: How does expectation affect sensory experience?" International Symposium on Affective Science and Engineering ISASE2019 (2019): 1. http://dx.doi.org/10.5057/isase.isase2019.0_1_47.

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8

Teufel, Christoph. "Sensory Neuroscience: Linking Dopamine, Expectation, and Hallucinations." Current Biology 28, no. 4 (February 2018): R158—R160. http://dx.doi.org/10.1016/j.cub.2018.01.003.

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9

Sears, David RW, Marcus T. Pearce, Jacob Spitzer, William E. Caplin, and Stephen McAdams. "Expectations for tonal cadences: Sensory and cognitive priming effects." Quarterly Journal of Experimental Psychology 72, no. 6 (November 30, 2018): 1422–38. http://dx.doi.org/10.1177/1747021818814472.

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Studies examining the formation of melodic and harmonic expectations during music listening have repeatedly demonstrated that a tonal context primes listeners to expect certain (tonally related) continuations over others. However, few such studies have (1) selected stimuli using ready examples of expectancy violation derived from real-world instances of tonal music, (2) provided a consistent account for the influence of sensory and cognitive mechanisms on tonal expectancies by comparing different computational simulations, or (3) combined melodic and harmonic representations in modelling cognitive processes of expectation. To resolve these issues, this study measures expectations for the most recurrent cadence patterns associated with tonal music and then simulates the reported findings using three sensory–cognitive models of auditory expectation. In Experiment 1, participants provided explicit retrospective expectancy ratings both before and after hearing the target melodic tone and chord of the cadential formula. In Experiment 2, participants indicated as quickly as possible whether those target events were in or out of tune relative to the preceding context. Across both experiments, cadences terminating with stable melodic tones and chords elicited the highest expectancy ratings and the fastest and most accurate responses. Moreover, the model simulations supported a cognitive interpretation of tonal processing, in which listeners with exposure to tonal music generate expectations as a consequence of the frequent (co-)occurrence of events on the musical surface.

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10

Cottereau, B., J. Ales, and A. Norcia. "Decoding the mismatch between expectation and sensory input." Journal of Vision 11, no. 11 (September 23, 2011): 267. http://dx.doi.org/10.1167/11.11.267.

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Panichello, M. F., and N. B. Turk-Browne. "Sensory and expectation cues are fused during perception." Journal of Vision 14, no. 10 (August 22, 2014): 1168. http://dx.doi.org/10.1167/14.10.1168.

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12

Rohenkohl, G., A. M. Cravo, V. Wyart, and A. C. Nobre. "Temporal Expectation Improves the Quality of Sensory Information." Journal of Neuroscience 32, no. 24 (June 13, 2012): 8424–28. http://dx.doi.org/10.1523/jneurosci.0804-12.2012.

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13

Walsh, Kevin S., and David P. McGovern. "Expectation Suppression Dampens Sensory Representations of Predicted Stimuli." Journal of Neuroscience 38, no. 50 (December 12, 2018): 10592–94. http://dx.doi.org/10.1523/jneurosci.2133-18.2018.

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14

Sheibani, Ershad, Golshan Matinfar, Sahar Jazaeri, and Abdorreza Mohammadi. "Influences of sensory and non-sensory factors on consumer perception of saffroned products." British Food Journal 121, no. 11 (October 24, 2019): 2883–900. http://dx.doi.org/10.1108/bfj-12-2018-0838.

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Purpose The purpose of this paper is to investigate the influences of the interactions of taste, colour and labelling on sensory perception, liking and identification of saffroned products. Design/methodology/approach The consumer and discrimination tests (N=120, 18, 25, 78, for Experiments 1–4, respectively) were conducted. The analyses of discrimination tests were performed using the Thurstonian model and R-index. The results from consumer studies were analysed using the Kruskal–Wallis test, penalty analysis and correlation matrix. Findings The study revealed that saffron can interact with the perception of sour and bitter taste and has no significant effects on the sweetness. The colour and labelling generated expectations for quality and sweetness of the samples. When the disparity between the expectation and actual experience was occurred resulted in contrast/assimilation effects on the hedonic ratings and negatively impacted consumer acceptability of the product. Practical implications This study showed that the visual cues can modulate the expectation for particular sensory perceptions and also affect the hedonic experiences. Saffron adulteration can be identified by the consumers and can result in a significant decrease in the acceptability of the products. Hence, the practice of substituting saffron with ingredients with a similar colour in these products can be detrimental for business. Additionally, it was revealed that saffron colour is associated with the expected and actual sweet taste perception. Therefore, it is possible to manipulate yellow colour cues to reduce sweeteners in different food products that contain saffron. Originality/value The sensory characteristics and consumer perception of saffron have been rarely studied. This study revealed that flavour perception and quality determination of saffroned foods involves the combinations of different sensory modalities and cognitive (expectancy) inputs.

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15

Rothwell, Austin, and Miriam Spering. "Cognitive expectation modulates ocular torsion." Journal of Vision 17, no. 10 (August 31, 2017): 275. http://dx.doi.org/10.1167/17.10.275.

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16

Zuanazzi, Arianna, and Uta Noppeney. "The Intricate Interplay of Spatial Attention and Expectation: a Multisensory Perspective." Multisensory Research 33, no. 4-5 (March 17, 2020): 383–416. http://dx.doi.org/10.1163/22134808-20201482.

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Abstract Attention (i.e., task relevance) and expectation (i.e., signal probability) are two critical top-down mechanisms guiding perceptual inference. Attention prioritizes processing of information that is relevant for observers’ current goals. Prior expectations encode the statistical structure of the environment. Research to date has mostly conflated spatial attention and expectation. Most notably, the Posner cueing paradigm manipulates spatial attention using probabilistic cues that indicate where the subsequent stimulus is likely to be presented. Only recently have studies attempted to dissociate the mechanisms of attention and expectation and characterized their interactive (i.e., synergistic) or additive influences on perception. In this review, we will first discuss methodological challenges that are involved in dissociating the mechanisms of attention and expectation. Second, we will review research that was designed to dissociate attention and expectation in the unisensory domain. Third, we will review the broad field of crossmodal endogenous and exogenous spatial attention that investigates the impact of attention across the senses. This raises the critical question of whether attention relies on amodal or modality-specific mechanisms. Fourth, we will discuss recent studies investigating the role of both spatial attention and expectation in multisensory perception, where the brain constructs a representation of the environment based on multiple sensory inputs. We conclude that spatial attention and expectation are closely intertwined in almost all circumstances of everyday life. Yet, despite their intimate relationship, attention and expectation rely on partly distinct neural mechanisms: while attentional resources are mainly shared across the senses, expectations can be formed in a modality-specific fashion.

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Menceloglu, Melisa, Marcia Grabowecky, and Satoru Suzuki. "Rhythm Violation Enhances Auditory-Evoked Responses to the Extent of Overriding Sensory Adaptation in Passive Listening." Journal of Cognitive Neuroscience 32, no. 9 (September 2020): 1654–71. http://dx.doi.org/10.1162/jocn_a_01578.

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Sensory systems utilize temporal structure in the environment to build expectations about the timing of forthcoming events. We investigated the effects of rhythm-based temporal expectation on auditory responses measured with EEG recorded from the frontocentral sites implicated in auditory processing. By manipulating temporal expectation and the interonset interval (IOI) of tones, we examined how neural responses adapted to auditory rhythm and reacted to stimuli that violated the rhythm. Participants passively listened to the tones while watching a silent nature video. In Experiment 1 ( n = 22), in the long-IOI block, tones were frequently presented (80%) with 1.7-sec IOI and infrequently presented (20%) with 1.2-sec IOI, generating unexpectedly early tones that violated temporal expectation. Conversely, in the short-IOI block, tones were frequently presented with 1.2-sec IOI and infrequently presented with 1.7-sec IOI, generating late tones. We analyzed the tone-evoked N1–P2 amplitude of ERPs and intertrial phase clustering in the theta–alpha band. The results provided evidence of strong delay-dependent adaptation effects (short-term, sensitive to IOI), weak cumulative adaptation effects (long-term, driven by tone repetition over time), and robust temporal-expectation violation effects over and above the adaptation effects. Experiment 2 ( n = 22) repeated Experiment 1 with shorter IOIs of 1.2 and 0.7 sec. Overall, we found evidence of strong delay-dependent adaptation effects, weak cumulative adaptation effects (which may most efficiently accumulate at the tone presentation rate of ∼1 Hz), and robust temporal-expectation violation effects that substantially boost auditory responses to the extent of overriding the delay-dependent adaptation effects likely through mechanisms involved in exogenous attention.

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Sharvit, Gil, Patrik Vuilleumier, and Corrado Corradi-Dell'Acqua. "Sensory-specific predictive models in the human anterior insula." F1000Research 8 (February 6, 2019): 164. http://dx.doi.org/10.12688/f1000research.17961.1.

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Expectations affect the subjective experience of pain by increasing sensitivity to noxious events, an effect underlain by brain regions such as the insula. However, it has been debated whether these neural processes operate on pain-specific information or on more general signals encoding expectation of unpleasant events. To dissociate these possibilities, two independent studies (Sharvit et al., 2018, Pain; Fazeli and Büchel, 2018, J. Neurosci) implemented a cross-modal expectancy paradigm, testing whether responses to pain could also be modulated by the expectation of similarly unpleasant, but painless, events. Despite their differences, the two studies report remarkably convergent (and in some cases complementary) findings. First, the middle-anterior insula response to noxious stimuli is modulated only by expectancy of pain but not of painless adverse events, suggesting coding of pain-specific information. Second, sub-portions of the middle-anterior insula mediate different aspects of pain predictive coding, related to expectancy and prediction error. Third, complementary expectancy effects are also observed for other negative experiences (i.e., disgust), suggesting that the insular cortex holds prospective models of a wide range of events concerning their sensory-specific features. Taken together, these studies have strong theoretical implications on the functional properties of the insular cortex.

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Voss, Martin, James N. Ingram, Daniel M. Wolpert, and Patrick Haggard. "Mere Expectation to Move Causes Attenuation of Sensory Signals." PLoS ONE 3, no. 8 (August 6, 2008): e2866. http://dx.doi.org/10.1371/journal.pone.0002866.

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20

Simon, Alexander J., Jessica N. Schachtner, and Courtney L. Gallen. "Disentangling expectation from selective attention during perceptual decision making." Journal of Neurophysiology 121, no. 6 (June 1, 2019): 1977–80. http://dx.doi.org/10.1152/jn.00639.2018.

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A large body of work has investigated the effects of attention and expectation on early sensory processing to support decision making. In a recent paper published in The Journal of Neuroscience, Rungratsameetaweemana et al. (Rungratsameetaweemana N, Itthipuripat S, Salazar A, Serences JT. J Neurosci 38: 5632–5648, 2018) found that expectations driven by implicitly learned task regularities do not modulate neural markers of early visual processing. Here, we discuss these findings and propose several lines of follow-up analyses and experiments that could expand on these findings in the broader perceptual decision making literature.

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Wiggins, Matthew S., and Robert J. Brustad. "Perception of Anxiety and Expectations of Performance." Perceptual and Motor Skills 83, no. 3 (December 1996): 1071–74. http://dx.doi.org/10.2466/pms.1996.83.3.1071.

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The purpose of this study was to examine expectations of performance and the directionality of anxiety. Directionality refers to the facilitative or debilitative aspects of anxiety. Subjects were 91 athletes competing in soccer, swimming, and track and field. The Competitive State Anxiety Inventory-2 with an added Facilitative/Debilitative scale and Expectation of Performance scale was employed. Analysis showed that athletes with lower scores on cognitive and somatic anxiety, and higher scores on self-confidence perceived their anxiety as more facilitative of performance. These athletes also had significantly higher scores on the Expectation of Performance scale.

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ROTH, YUVAL, and RAMESH JAIN. "SIMULATION AND EXPECTATION IN SENSOR-BASED SYSTEMS." International Journal of Pattern Recognition and Artificial Intelligence 07, no. 01 (February 1993): 145–73. http://dx.doi.org/10.1142/s0218001493000091.

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Simulations have traditionally been used as off-line tools for examining process models and experimenting with system models for which it would have been either impossible or too dangerous, expensive, or time-consuming, to perform with physical systems. We propose a novel way of regarding simulations as part of both the development and the working phases of systems. In our approach simulation is used within the processing and control loop of the system to provide sensor and state expectations. This minimizes the inverse sensory data analysis and model maintenance problems. We refer to this mode of operation as the verification mode, in contrast to the traditional discovery mode. In order to provide simulations and planning that are intertwined with the control of a physical system, temporal issues have to be considered. By limiting the focus of the system to small portions of complex models which are temporarily relevant to the system’s operation, the system is able to maintain its models and respond faster. For this we employ the Context-based Caching (CbC) mechanism within our Mobile Platform Control and Simulation Program (MOSIM). CbC is a knowledge management technique which maintains large knowledge bases by making the necessary information available at the right time.

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Puri, A., D. Whitney, and C. Ranganath. "Facilitatory effects of expectation on object discrimination." Journal of Vision 8, no. 6 (March 19, 2010): 136. http://dx.doi.org/10.1167/8.6.136.

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Esterman, M., and S. Yantis. "Category expectation modulates object-selective cortical activity." Journal of Vision 8, no. 6 (March 27, 2010): 555. http://dx.doi.org/10.1167/8.6.555.

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Chopin, A., M. Capps, and P. Mamassian. "Expectation from temporal sequences influences binocular rivalry." Journal of Vision 10, no. 7 (August 3, 2010): 347. http://dx.doi.org/10.1167/10.7.347.

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Ren, Yanna, Zhihan Xu, Fengxia Wu, Yoshimichi Ejima, Jiajia Yang, Satoshi Takahashi, Qiong Wu, and Jinglong Wu. "Does Temporal Expectation Driven by Rhythmic Cues Differ From That Driven by Symbolic Cues Across the Millisecond and Second Range?" Perception 48, no. 6 (May 2, 2019): 515–29. http://dx.doi.org/10.1177/0301006619847579.

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Temporal expectation relies on different predictive information, such as regular rhythms and symbolic cues, to direct attention to a future moment in time to optimize behaviour. However, whether differences exist between temporal expectations driven by regular rhythms and symbolic cues has not been clearly established. In this study, 20 participants performed two temporal expectation tasks in which a rhythmic cue or a symbolic cue indicated (70% expected) that the target would appear after an interval of 500 ms (short), 1,500 ms (medium), or 2,500 ms (long). We found larger cueing effects for the rhythmic cued task than for the symbolic cued task during the short interval, indicating that rhythmic cues were more effective in improving performance. Furthermore, no significant difference was found during the longer interval, reflect that the behavioural differences between the two forms of temporal expectations were likely to diminish as the time interval increased. Thus, we speculate that the temporal expectation driven by rhythmic cues differs from that driven by symbolic cues only in the limited time range; however, the mechanisms underlying the two forms of temporal expectations trend to become more similar over increasing temporal scales.

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Weis, Tina, André Brechmann, Sebastian Puschmann, and Christiane M. Thiel. "Feedback that confirms reward expectation triggers auditory cortex activity." Journal of Neurophysiology 110, no. 8 (October 15, 2013): 1860–68. http://dx.doi.org/10.1152/jn.00128.2013.

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Associative learning studies have shown that the anticipation of reward and punishment shapes the representation of sensory stimuli, which is further modulated by dopamine. Less is known about whether and how reward delivery activates sensory cortices and the role of dopamine at that time point of learning. We used an appetitive instrumental learning task in which participants had to learn that a specific class of frequency-modulated tones predicted a monetary reward following fast and correct responses in a succeeding reaction time task. These fMRI data were previously analyzed regarding the effect of reward anticipation, but here we focused on neural activity to the reward outcome relative to the reward expectation and tested whether such activation in the reward reception phase is modulated by l-DOPA. We analyzed neural responses at the time point of reward outcome under three different conditions: 1) when a reward was expected and received, 2) when a reward was expected but not received, and 3) when a reward was not expected and not received. Neural activity in auditory cortex was enhanced during feedback delivery either when an expected reward was received or when the expectation of obtaining no reward was correct. This differential neural activity in auditory cortex was only seen in subjects who learned the reward association and not under dopaminergic modulation. Our data provide evidence that auditory cortices are active at the time point of reward outcome. However, responses are not dependent on the reward itself but on whether the outcome confirmed the subject's expectations.

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Aitken, Fraser, Georgios Menelaou, Oliver Warrington, Renée S. Koolschijn, Nadège Corbin, Martina F. Callaghan, and Peter Kok. "Prior expectations evoke stimulus-specific activity in the deep layers of the primary visual cortex." PLOS Biology 18, no. 12 (December 7, 2020): e3001023. http://dx.doi.org/10.1371/journal.pbio.3001023.

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The way we perceive the world is strongly influenced by our expectations. In line with this, much recent research has revealed that prior expectations strongly modulate sensory processing. However, the neural circuitry through which the brain integrates external sensory inputs with internal expectation signals remains unknown. In order to understand the computational architecture of the cortex, we need to investigate the way these signals flow through the cortical layers. This is crucial because the different cortical layers have distinct intra- and interregional connectivity patterns, and therefore determining which layers are involved in a cortical computation can inform us on the sources and targets of these signals. Here, we used ultra-high field (7T) functional magnetic resonance imaging (fMRI) to reveal that prior expectations evoke stimulus-specific activity selectively in the deep layers of the primary visual cortex (V1). These findings are in line with predictive processing theories proposing that neurons in the deep cortical layers represent perceptual hypotheses and thereby shed light on the computational architecture of cortex.

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BRANDT, THOMAS, ANGELA DEUTSCHLÄNDER, STEFAN GLASAUER, ANNINA NOLTE, HARTMUT BRÜCKMANN, MARIANNE DIETERICH, and THOMAS STEPHAN. "Expectation of Sensory Stimulation Modulates Brain Activation during Visual Motion Stimulation." Annals of the New York Academy of Sciences 1039, no. 1 (April 2005): 325–36. http://dx.doi.org/10.1196/annals.1325.031.

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Rungratsameetaweemana, Nuttida, and John T. Serences. "Dissociating the impact of attention and expectation on early sensory processing." Current Opinion in Psychology 29 (October 2019): 181–86. http://dx.doi.org/10.1016/j.copsyc.2019.03.014.

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Ramnani, N., I. Toni, O. Josephs, J. Ashburner, and R. E. Passingham. "Learning- and Expectation-Related Changes in the Human Brain During Motor Learning." Journal of Neurophysiology 84, no. 6 (December 1, 2000): 3026–35. http://dx.doi.org/10.1152/jn.2000.84.6.3026.

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We have studied a simple form of motor learning in the human brain so as to isolate activity related to motor learning and the prediction of sensory events. Whole-brain, event-related functional magnetic resonance imaging (fMRI) was used to record activity during classical discriminative delay eyeblink conditioning. Auditory conditioned stimulus (CS+) trials were presented either with a corneal airpuff unconditioned stimulus (US, paired), or without a US (unpaired). Auditory CS− trials were never reinforced with a US. Trials were presented pseudorandomly, 66 times each. The subjects gradually produced conditioned responses to CS+ trials, while increasingly differentiating between CS+ and CS− trials. The increasing difference between hemodynamic responses for unpaired CS+ and for CS− trials evolved slowly during conditioning in the ipsilateral cerebellar cortex (Crus I/Lobule HVI), contralateral motor cortex and hippocampus. To localize changes that were related to sensory prediction, we compared trials on which the expected airpuff US failed to occur (Unpaired CS+) with trials on which it occurred as expected (Paired CS+). Error-related signals in the contralateral cerebellum and somatosensory cortex were seen to increase during learning as the sensory prediction became stronger. The changes seen in the ipsilateral cerebellar cortex may be due either to the violations of sensory predictions, or to learning-related increases in the excitability of cerebellar neurons to presentations of the CS+.

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Brayanov, Jordan B., and Maurice A. Smith. "Bayesian and “Anti-Bayesian” Biases in Sensory Integration for Action and Perception in the Size–Weight Illusion." Journal of Neurophysiology 103, no. 3 (March 2010): 1518–31. http://dx.doi.org/10.1152/jn.00814.2009.

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Which is heavier: a pound of lead or a pound of feathers? This classic trick question belies a simple but surprising truth: when lifted, the pound of lead feels heavier—a phenomenon known as the size–weight illusion. To estimate the weight of an object, our CNS combines two imperfect sources of information: a prior expectation, based on the object's appearance, and direct sensory information from lifting it. Bayes' theorem (or Bayes' law) defines the statistically optimal way to combine multiple information sources for maximally accurate estimation. Here we asked whether the mechanisms for combining these information sources produce statistically optimal weight estimates for both perceptions and actions. We first studied the ability of subjects to hold one hand steady when the other removed an object from it, under conditions in which sensory information about the object's weight sometimes conflicted with prior expectations based on its size. Since the ability to steady the supporting hand depends on the generation of a motor command that accounts for lift timing and object weight, hand motion can be used to gauge biases in weight estimation by the motor system. We found that these motor system weight estimates reflected the integration of prior expectations with real-time proprioceptive information in a Bayesian, statistically optimal fashion that discounted unexpected sensory information. This produces a motor size–weight illusion that consistently biases weight estimates toward prior expectations. In contrast, when subjects compared the weights of two objects, their perceptions defied Bayes' law, exaggerating the value of unexpected sensory information. This produces a perceptual size–weight illusion that biases weight perceptions away from prior expectations. We term this effect “anti-Bayesian” because the bias is opposite that seen in Bayesian integration. Our findings suggest that two fundamentally different strategies for the integration of prior expectations with sensory information coexist in the nervous system for weight estimation.

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Maryott, J., A. Noyce, and R. Sekuler. "Eye movements and imitation learning: Intentional disruption of expectation." Journal of Vision 11, no. 1 (January 6, 2011): 7. http://dx.doi.org/10.1167/11.1.7.

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Erol, Muge, Arien Mack, and Jason Clarke. "Expectation Blindness: Seeing a face when there is none." Journal of Vision 18, no. 10 (September 1, 2018): 1115. http://dx.doi.org/10.1167/18.10.1115.

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Ketkaew, Chavis, Peerapong Wongthahan, and Amporn Sae-Eaw. "How sauce color affects consumer emotional response and purchase intention: a structural equation modeling approach for sensory analysis." British Food Journal 123, no. 6 (January 27, 2021): 2152–69. http://dx.doi.org/10.1108/bfj-07-2020-0578.

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PurposeHere the authors investigate the effects of a visual color cue (brown color) on saltiness expectations, emotional responses and purchase intention of commercial soy sauce products.Design/methodology/approachThe study enrolled 100 participates, and three sauce colors (light brown, medium brown and dark brown) were used as treatments in this experimental design research. The data analysis was done by a structural equation modeling (SEM) approach with repeated measures.FindingsThe findings indicated that, for the medium and dark brown sauces, the final model revealed a positive effect of sauce color intensity on saltiness expectation, a positive impact of saltiness expectation on emotion and a positive impact of emotion on purchase intention with statistically indifferent factor loadings. Hence, both the medium and dark brown colors soy sauces were the preferred choices for consumers. However, for the light brown color, the test result was unsatisfactory.Originality/valueSeveral empirical studies have identified visual cues as useful for sodium reduction. However, from a marketing perspective, a causal relationship between the color intensity and a customer's purchase intention has not been explored in soy sauce products using an experimental design concept and SEM.

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Yonathan, Christianus Jodi, Yoga Pamudya Gunawan Ristam, Vania Aurellia Wijaya, and Oki Krisbianto. "FOCUS GROUP DISCUSSION AND QUANTITATIVE SENSORY ANALYSIS TO IDENTIFY SENSORY PARAMETERS OF NEW FOOD PRODUCT." JOURNAL OF TOURISM, CULINARY AND ENTREPRENEURSHIP (JTCE) 1, no. 1 (March 18, 2021): 61–78. http://dx.doi.org/10.37715/jtce.v1i1.1800.

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Focus Group Discussions (FGD) is a renowned method for new food product development. This research used FGD followed by Quantitative Descriptive Analysis (QDA) and Affective Test (AT) to identify the sensory parameters of pineapple wine. Based on FGD, five parameters were found to be crucial for panelists while testing the wine, i.e. distinctive pineapple aroma, sweetness, alcoholic flavor, alcoholic taste and appearance. These five parameters were then used in QDA and AT to understand the expectation of panelists on the sample which was served. It was found that FGD, QDA and AT were effective in identifying the sensory parameters of pineapple wine

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VÁZQUEZ, MARISA BEATRIZ, ANA CURIA, and GUILLERMO HOUGH. "SENSORY DESCRIPTIVE ANALYSIS, SENSORY ACCEPTABILITY AND EXPECTATION STUDIES ON BISCUITS WITH REDUCED ADDED SALT AND INCREASED FIBER." Journal of Sensory Studies 24, no. 4 (August 2009): 498–511. http://dx.doi.org/10.1111/j.1745-459x.2009.00223.x.

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38

Funamizu, Akihiro. "Integration of sensory evidence and reward expectation in mouse perceptual decision-making task with various sensory uncertainties." iScience 24, no. 8 (August 2021): 102826. http://dx.doi.org/10.1016/j.isci.2021.102826.

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Gisel, Erika G., and Hannah Schwob. "Relation between an Oral Form Discrimination Task and Chewing Behavior in Normal 5- to 8-Year-Old Children." Occupational Therapy Journal of Research 8, no. 4 (July 1988): 211–23. http://dx.doi.org/10.1177/153944928800800402.

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Therapists often apply oral-sensory stimulation to children with eating problems with the expectation that sensory stimulation will facilitate chewing and swallowing. Evidence from the literature to support such an expectation is inconsistent, which may be due to the difficulty of separating the sensory from the motor component when working with the eating-impaired child The present study addresses the question of whether any correlation between measures of chewing and oral sensation can be shown in healthy normal children by using normative data from a chewing assessment (Gisel, 1988a) and a sensory assessment (Gisel & Schwob, 1988). Eighty-six children between the ages of 5 and 8 participated in this study; 15 were 5 years old, 26 were 6 years old, 26 were 7 years old, and 19 were 8 years old. Significant correlations were found between the time (in seconds) for chewing viscous foods and perception of size as measured by an oral form discrimination task The data support the idea that there may be an association between oral form perception and chewing; however, the nature of this association is still unknown.

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Rungratsameetaweeman, Nuttida, Sirawaj Itthipuripat, and John T. Serences. "Dissociable effects of attention and expectation on perceptual decision making." Journal of Vision 19, no. 10 (September 6, 2019): 49b. http://dx.doi.org/10.1167/19.10.49b.

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Coffey, Kate M., Nika Adamian, Tessel Blom, Elle van Heusden, Patrick Cavanagh, and Hinze Hogendoorn. "Expecting the unexpected: Temporal expectation increases the flash-grab effect." Journal of Vision 19, no. 13 (November 12, 2019): 9. http://dx.doi.org/10.1167/19.13.9.

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van Moorselaar, Dirk, and Heleen A. Slagter. "Learning to ignore: Neural mechanisms underlying expectation-dependent distractor inhibition." Journal of Vision 19, no. 10 (September 6, 2019): 294. http://dx.doi.org/10.1167/19.10.294.

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Zuanazzi, Arianna, and Uta Noppeney. "Modality-specific and multisensory mechanisms of spatial attention and expectation." Journal of Vision 20, no. 8 (August 3, 2020): 1. http://dx.doi.org/10.1167/jov.20.8.1.

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Mazzucato, L., G. La Camera, and A. Fontanini. "Expectation-induced modulation of metastable activity underlies faster coding of sensory stimuli." Nature Neuroscience 22, no. 5 (April 1, 2019): 787–96. http://dx.doi.org/10.1038/s41593-019-0364-9.

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Menceloglu, Melisa, Marcia Grabowecky, and Satoru Suzuki. "Domain specific interactions between expectation and priming for sensory modality and timing." Journal of Vision 18, no. 10 (September 1, 2018): 329. http://dx.doi.org/10.1167/18.10.329.

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Teixeira Lopes, Maria Micheline, Maria do Carmo Passos Rodrigues, and Ana Maria Souza de Araújo. "Influence of Expectation Measure on the Sensory Acceptance of Petit Suisse Product." Journal of Food Science 83, no. 3 (February 7, 2018): 798–803. http://dx.doi.org/10.1111/1750-3841.14067.

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Bridgeman, Bruce. "Applications of predictive control in neuroscience." Behavioral and Brain Sciences 36, no. 3 (May 10, 2013): 208. http://dx.doi.org/10.1017/s0140525x12002282.

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AbstractThe sensory cortex has been interpreted as coding information rather than stimulus properties since Sokolov in 1960 showed increased response to an unexpected stimulus decrement. The motor cortex is also organized around expectation, coding the goal of an act rather than a set of muscle movements. Expectation drives not only immediate responses but also the very structure of the cortex, as demonstrated by development of receptive fields that mirror the structure of the visual world.

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Hsu, Yi-Fang, Jarmo A. Hämäläinen, and Florian Waszak. "Temporal expectation and spectral expectation operate in distinct fashion on neuronal populations." Multisensory Research 26, no. 1-2 (2013): 145. http://dx.doi.org/10.1163/22134808-000s0108.

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Stoilova, Vanya V., Beate Knauer, Stephanie Berg, Evelyn Rieber, Frank Jäkel, and Maik C. Stüttgen. "Auditory cortex reflects goal-directed movement but is not necessary for behavioral adaptation in sound-cued reward tracking." Journal of Neurophysiology 124, no. 4 (October 1, 2020): 1056–71. http://dx.doi.org/10.1152/jn.00736.2019.

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Recent evidence suggests that sensory cortex represents nonsensory variables such as reward expectation, but the relevance of these representations for behavior are not well understood. We show that rat auditory cortex (AC) is modulated during movement and reward anticipation in a sound-cued reward tracking task, whereas AC inactivation only impaired discrimination without affecting reward tracking, consistent with a predominantly sensory role of AC.

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Bergmann, Nils, Dennis Koch, and Anna Schubö. "Reward expectation facilitates context learning and attentional guidance in visual search." Journal of Vision 19, no. 3 (March 27, 2019): 10. http://dx.doi.org/10.1167/19.3.10.

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