scholarly journals The rhythms of predictive coding: pre-stimulus phase modulates the influence of shape perception on luminance judgments

2016 ◽  
Author(s):  
Biao Han ◽  
Rufin VanRullen

AbstractPredictive coding is an influential model emphasizing interactions between feedforward and feedback signals. Here, we investigated its temporal dynamics. Two gray disks with different versions of the same stimulus, one enabling predictive feedback (a 3D-shape) and one impeding it (random-lines), were simultaneously presented on the left and right of fixation. Human subjects judged the luminance of the two disks while EEG was recorded. Independently of the spatial response (left/right), we found that the choice of 3D-shape or random-lines as the brighter disk (our measure of post-stimulus predictive coding efficiency on each trial) fluctuated along with the pre-stimulus phase of two spontaneous oscillations: a ~5Hz oscillation in contralateral frontal electrodes and a ~16Hz oscillation in contralateral occipital electrodes. This pattern of results demonstrates that predictive coding is a rhythmic process, and suggests that it could take advantage of faster oscillations in low-level areas and slower oscillations in high-level areas.

2018 ◽  
Author(s):  
Paolo Papale ◽  
Monica Betta ◽  
Giacomo Handjaras ◽  
Giulia Malfatti ◽  
Luca Cecchetti ◽  
...  

AbstractBiological vision relies on representations of the physical world at different levels of complexity. Relevant features span from simple low-level properties, as contrast and spatial frequencies, to object-based attributes, as shape and category. However, how these features are integrated into coherent percepts is still debated. Moreover, these dimensions often share common biases: for instance, stimuli from the same category (e.g., tools) may have similar shapes. Here, using magnetoencephalography, we revealed the temporal dynamics of feature processing in human subjects attending to pictures of items pertaining to different semantic categories. By employing Relative Weights Analysis, we mitigated collinearity between model-based descriptions of stimuli and showed that low-level properties (contrast and spatial frequencies), shape (medial-axis) and category are represented within the same spatial locations early in time: 100-150ms after stimulus onset. This fast and overlapping processing may result from independent parallel computations, with categorical representation emerging later than the onset of low-level feature processing, yet before shape coding. Categorical information is represented both before and after shape also suggesting a role for this feature in the refinement of categorical matching.


2018 ◽  
Author(s):  
Jesse Breedlove ◽  
Ghislain St-Yves ◽  
Cheryl Olman ◽  
Thomas Naselaris

Humans have long wondered about the function of mental imagery and its relationship to vision. Although visual representations are utilized during imagery, the computations they subserve are unclear. Building on a theory that treats vision as inference about the causes of sensory stimulation in an internal generative model, we propose that mental imagery is inference about the sensory consequences of predicted or remembered causes. The relation between these complementary inferences yields a relation between the brain activity patterns associated with imagery and vision. We show that this relation has the formal structure of an echo that makes encoding of imagined stimuli in low-level visual areas resemble the encoding of seen stimuli in higher areas. To test for evidence of this echo effect we developed imagery encoding models—a new tool for revealing how imagined stimuli are encoded in brain activity. We estimated imagery encoding models from brain activity measured with fMRI while human subjects imagined complex visual stimuli, and then compared these to visual encoding models estimated from a matched viewing experiment. Consistent with an echo effect, imagery encoding models in low-level visual areas exhibited decreased spatial frequency preference and larger, more foveal receptive fields, thus resembling visual encoding models in high-level visual areas where imagery and vision appeared to be almost interchangeable. Our findings support an interpretation of mental imagery as a predictive inference that is conditioned on activity in high-level visual cortex, and is related to vision through shared dependence on an internal model of the visual world.


2018 ◽  
Author(s):  
Anaïs Louzolo ◽  
Rita Almeida ◽  
Marc Guitart-Masip ◽  
Malin Björnsdotter ◽  
Martin Ingvar ◽  
...  

AbstractPsychosis is characterized by distorted perceptions and deficient low-level learning, including reward learning and fear conditioning. This has been interpreted as reflecting imprecise priors in a predictive coding system. However, this idea is not compatible with formation of overly strong beliefs and delusions in psychosis-associated states. A reconciliation of these paradoxical observations is that these individuals actively develop and use higher-order beliefs in order to interpret a chaotic environment. In the present behavioural and fMRI study, we compared delusion-prone individuals (n=20), a trait related to psychotic disorders, with controls (n=23; n=20 in fMRI-part) to study the effect of beliefs on fear learning. We show that instructed fear learning, involving explicit change of beliefs and an associated activation of lateral orbitofrontal cortex, is expressed to a higher degree in delusion-prone subjects. Our results suggest that strong high-level top-down learning co-exists with previously reported weak low-level bottom-up learning in psychosis-associated states.


2019 ◽  
Author(s):  
Lilla Hodossy ◽  
Manos Tsakiris

The experience of one’s embodied sense of self is dependent on the integration of signals originating both from within and outwith one’s body. During the processing and integration of these signals, the bodily self must maintain a fine balance between stability and malleability. Here we investigate the potential role of autonomic responses in interoceptive processing and their contribution to the stability of the bodily self. Using a biofeedback paradigm, we manipulated the congruency of cardiac signals across two hierarchical levels: (i) the low-level congruency between a visual feedback and participant’s own cardiac signal and (ii) the high-level congruency between the participants’ beliefs about the identity of the cardiac feedback and its true identity. We measured the effects of these manipulations on high-frequency heart rate variability (HF-HRV), a selective index of phasic vagal cardiac control. In Experiment 1, HF-HRV was sensitive to low-level congruency, independently of whether participants attempted to regulate or simply attend to the biofeedback. Experiment 2 revealed a higher-level congruency effect, as participants’ prior veridical beliefs increased HF-HRV while when false they decreased HF-HRV. Our results demonstrate that autonomic changes in HF-HRV are sensitive to congruencies across multiple hierarchical levels. Our findings have important theoretical implications for predictive coding models of the self as they pave the way for a more direct way to track the subtle changes in the co-processing of the internal and external milieus.


2018 ◽  
Author(s):  
Mehran Spitmaan ◽  
Oihane Horno ◽  
Emily Chu ◽  
Alireza Soltani

AbstractContext effects have been explained by either high-level cognitive processes or low-level neural adjustments but not their combination. It is currently unclear how these processes interact to shape individuals’ responses to context. Here, we used a large cohort of human subjects in experiments involving choice between two or three gambles in order to study the dependence of context effects on neural adaptation and individuals’ risk attitudes. We found no evidence that neural adaptation on long timescales (~100 trials) contributes to context effects. However, we identified two groups of subjects with distinct patterns of responses to decoys, both of which depended on individuals’ risk aversion. Subjects in the first group exhibited strong, consistent decoy effects and became more risk averse due to decoy presentation. In contrast, subjects in the second group did not show consistent decoy effects and became more risk seeking. The degree of change in risk aversion due to decoy presentation was positively correlated with the initial degrees of risk aversion. To explain these results and reveal underlying neural mechanisms, we developed a new model that incorporates both low- and high-level processes to fit individuals’ choice behavior. We found that observed decoy effects can be explained by a combination of adjustments in neural representations and competitive weighting of reward attributes, both of which depend on risk aversion but in opposite directions. Altogether, our results demonstrate how a combination of low- and high-level processes shapes multi-attribute choice, modulates overall risk preference, and explains distinct behavioral phenotypes.Significance statementA large body of experimental work has illustrated that the introduction of a new, and often irrelevant, option can influence preference among the existing options, a phenomenon referred to as context or decoy effects. Although context effects have been explained by high-level cognitive processes—such as comparisons and competitions between attributes—or low-level adjustments of neural representations, it is unclear how these processes interact to shape individuals’ responses to context. Here, we show that both high-level cognitive processes and low-level neural adjustments shift risk preference during choice between multiple options but in opposite directions. Moreover, we demonstrate that a combination of these processes can account for distinct patterns of context effects in human subjects.


2017 ◽  
Vol 372 (1714) ◽  
pp. 20160102 ◽  
Author(s):  
Iris I. A. Groen ◽  
Edward H. Silson ◽  
Chris I. Baker

Visual scene analysis in humans has been characterized by the presence of regions in extrastriate cortex that are selectively responsive to scenes compared with objects or faces. While these regions have often been interpreted as representing high-level properties of scenes (e.g. category), they also exhibit substantial sensitivity to low-level (e.g. spatial frequency) and mid-level (e.g. spatial layout) properties, and it is unclear how these disparate findings can be united in a single framework. In this opinion piece, we suggest that this problem can be resolved by questioning the utility of the classical low- to high-level framework of visual perception for scene processing, and discuss why low- and mid-level properties may be particularly diagnostic for the behavioural goals specific to scene perception as compared to object recognition. In particular, we highlight the contributions of low-level vision to scene representation by reviewing (i) retinotopic biases and receptive field properties of scene-selective regions and (ii) the temporal dynamics of scene perception that demonstrate overlap of low- and mid-level feature representations with those of scene category. We discuss the relevance of these findings for scene perception and suggest a more expansive framework for visual scene analysis. This article is part of the themed issue ‘Auditory and visual scene analysis’.


2019 ◽  
Vol 1 (1) ◽  
pp. 31-39
Author(s):  
Ilham Safitra Damanik ◽  
Sundari Retno Andani ◽  
Dedi Sehendro

Milk is an important intake to meet nutritional needs. Both consumed by children, and adults. Indonesia has many producers of fresh milk, but it is not sufficient for national milk needs. Data mining is a science in the field of computers that is widely used in research. one of the data mining techniques is Clustering. Clustering is a method by grouping data. The Clustering method will be more optimal if you use a lot of data. Data to be used are provincial data in Indonesia from 2000 to 2017 obtained from the Central Statistics Agency. The results of this study are in Clusters based on 2 milk-producing groups, namely high-dairy producers and low-milk producing regions. From 27 data on fresh milk production in Indonesia, two high-level provinces can be obtained, namely: West Java and East Java. And 25 others were added in 7 provinces which did not follow the calculation of the K-Means Clustering Algorithm, including in the low level cluster.


Author(s):  
Margarita Khomyakova

The author analyzes definitions of the concepts of determinants of crime given by various scientists and offers her definition. In this study, determinants of crime are understood as a set of its causes, the circumstances that contribute committing them, as well as the dynamics of crime. It is noted that the Russian legislator in Article 244 of the Criminal Code defines the object of this criminal assault as public morality. Despite the use of evaluative concepts both in the disposition of this norm and in determining the specific object of a given crime, the position of criminologists is unequivocal: crimes of this kind are immoral and are in irreconcilable conflict with generally accepted moral and legal norms. In the paper, some views are considered with regard to making value judgments which could hardly apply to legal norms. According to the author, the reasons for abuse of the bodies of the dead include economic problems of the subject of a crime, a low level of culture and legal awareness; this list is not exhaustive. The main circumstances that contribute committing abuse of the bodies of the dead and their burial places are the following: low income and unemployment, low level of criminological prevention, poor maintenance and protection of medical institutions and cemeteries due to underperformance of state and municipal bodies. The list of circumstances is also open-ended. Due to some factors, including a high level of latency, it is not possible to reflect the dynamics of such crimes objectively. At the same time, identification of the determinants of abuse of the bodies of the dead will reduce the number of such crimes.


2021 ◽  
pp. 002224372199837
Author(s):  
Walter Herzog ◽  
Johannes D. Hattula ◽  
Darren W. Dahl

This research explores how marketing managers can avoid the so-called false consensus effect—the egocentric tendency to project personal preferences onto consumers. Two pilot studies were conducted to provide evidence for the managerial importance of this research question and to explore how marketing managers attempt to avoid false consensus effects in practice. The results suggest that the debiasing tactic most frequently used by marketers is to suppress their personal preferences when predicting consumer preferences. Four subsequent studies show that, ironically, this debiasing tactic can backfire and increase managers’ susceptibility to the false consensus effect. Specifically, the results suggest that these backfire effects are most likely to occur for managers with a low level of preference certainty. In contrast, the results imply that preference suppression does not backfire but instead decreases false consensus effects for managers with a high level of preference certainty. Finally, the studies explore the mechanism behind these results and show how managers can ultimately avoid false consensus effects—regardless of their level of preference certainty and without risking backfire effects.


Author(s):  
Richard Stone ◽  
Minglu Wang ◽  
Thomas Schnieders ◽  
Esraa Abdelall

Human-robotic interaction system are increasingly becoming integrated into industrial, commercial and emergency service agencies. It is critical that human operators understand and trust automation when these systems support and even make important decisions. The following study focused on human-in-loop telerobotic system performing a reconnaissance operation. Twenty-four subjects were divided into groups based on level of automation (Low-Level Automation (LLA), and High-Level Automation (HLA)). Results indicated a significant difference between low and high word level of control in hit rate when permanent error occurred. In the LLA group, the type of error had a significant effect on the hit rate. In general, the high level of automation was better than the low level of automation, especially if it was more reliable, suggesting that subjects in the HLA group could rely on the automatic implementation to perform the task more effectively and more accurately.


Sign in / Sign up

Export Citation Format

Share Document