scholarly journals Improvement of association between confidence and accuracy after integration of discrete evidence over time

2021 ◽  
Author(s):  
Zahra Azizi ◽  
Sajjad Zabbah ◽  
Azra Jahanitabesh ◽  
Reza Ebrahimpour
Keyword(s):  
Discrimination Task ◽  
Computational Models ◽  
Real Life ◽  
Single Pulse ◽  
Saccadic Eye Movement ◽  
Positive Relation ◽  
Time Period ◽  
Dot Motion ◽  
Predominant Direction ◽  
Random Dot Motion

When making decisions in real-life, we may receive discrete pieces of evidence during a time period. Although subjects are able to integrate information from separate cues to improve their accuracy, confidence formation is controversial. Due to a strong positive relation between accuracy and confidence, we predicted that confidence followed the same characteristics as accuracy and would improve following the integration of information collected from separate cues. We applied a Random-dot-motion discrimination task in which participants had to indicate the predominant direction of dot motions by saccadic eye movement after receiving one or two brief stimuli (i.e., pulse(s)). The interval of two pulses (up to 1s) was selected randomly. Color-coded targets facilitated indicating confidence simultaneously. Using behavioral data, computational models, pupillometry and EEG methodology we show that in double-pulse trials: (i) participants improve their confidence resolution rather than reporting higher confidence comparing with single-pulse trials, (ii) the observed confidence follow neural and pupillometry markers of confidence, unlike in weak and brief single-pulse trials. Overall, our study showed improvement of associations between confidence and accuracy in decision results from the integration of stimulus separated by different temporal gaps.

scholarly journals The basis of area and dot number effects in random dot motion perception

1982 ◽  
Vol 22 (10) ◽  
pp. 1253-1259 ◽  
Author(s):  
Curtis L. Baker ◽  
Oliver J. Braddick
Keyword(s):  
Motion Perception ◽  
Dot Motion ◽  
Random Dot Motion

scholarly journals Sensitivity of Neurons in the Middle Temporal Area of Marmoset Monkeys to Random Dot Motion

2017 ◽  
Author(s):  
Tristan A. Chaplin ◽  
Benjamin J. Allitt ◽  
Maureen A. Hagan ◽  
Nicholas S. Price ◽  
Ramesh Rajan ◽  
...  
Keyword(s):  
Primate Species ◽  
Neural Basis ◽  
Temporal Area ◽  
Middle Temporal ◽  
Mt Neurons ◽  
Wide Range ◽  
Middle Temporal Area ◽  
Dot Motion ◽  
Marmoset Monkeys ◽  
Random Dot Motion

AbstractNeurons in the Middle Temporal area (MT) of the primate cerebral cortex respond to moving visual stimuli. The sensitivity of MT neurons to motion signals can be characterized by using random-dot stimuli, in which the strength of the motion signal is manipulated by adding different levels of noise (elements that move in random directions). In macaques, this has allowed the calculation of “neurometric” thresholds. We characterized the responses of MT neurons in sufentanil/nitrous oxide anesthetized marmoset monkeys, a species which has attracted considerable recent interest as an animal model for vision research. We found that MT neurons show a wide range of neurometric thresholds, and that the responses of the most sensitive neurons could account for the behavioral performance of macaques and humans. We also investigated factors that contributed to the wide range of observed thresholds. The difference in firing rate between responses to motion in the preferred and null directions was the most effective predictor of neurometric threshold, whereas the direction tuning bandwidth had no correlation with the threshold. We also showed that it is possible to obtain reliable estimates of neurometric thresholds using stimuli that were not highly optimized for each neuron, as is often necessary when recording from large populations of neurons with different receptive field concurrently, as was the case in this study. These results demonstrate that marmoset MT shows an essential physiological similarity to macaque MT, and suggest that its neurons are capable of representing motion signals that allow for comparable motion-in-noise judgments.New and NoteworthyWe report the activity of neurons in marmoset MT in response to random-dot motion stimuli of varying coherence. The information carried by individual MT neurons was comparable to that of the macaque, and that the maximum firing rates were a strong predictor of sensitivity. Our study provides key information regarding the neural basis of motion perception in the marmoset, a small primate species that is becoming increasingly popular as an experimental model.

scholarly journals Social reinforcement learning as a predictor of real-life experiences in individuals with high and low depressive symptomatology

2019 ◽  
pp. 1-8 ◽  
Author(s):  
Anna-Lena Frey ◽  
Michael J. Frank ◽  
Ciara McCabe
Keyword(s):  
Social Learning ◽  
Computational Models ◽  
Depressive Symptomatology ◽  
Real Life ◽  
Social Experiences ◽  
Interpersonal Behavior ◽  
Model Parameters ◽  
Social Feedback ◽  
Social Situations ◽  
Learning Rates

Abstract Background Several studies have reported diminished learning from non-social outcomes in depressed individuals. However, it is not clear how depression impacts learning from social feedback. Notably, mood disorders are commonly associated with deficits in social functioning, which raises the possibility that potential impairments in social learning may negatively affect real-life social experiences in depressed subjects. Methods Ninety-two participants with high (HD; N = 40) and low (LD; N = 52) depression scores were recruited. Subjects performed a learning task, during which they received monetary outcomes or social feedback which they were told came from other people. Additionally, participants answered questions about their everyday social experiences. Computational models were fit to the data and model parameters were related to social experience measures. Results HD subjects reported a reduced quality and quantity of social experiences compared to LD controls, including an increase in the amount of time spent in negative social situations. Moreover, HD participants showed lower learning rates than LD subjects in the social condition of the task. Interestingly, across all participants, reduced social learning rates predicted higher amounts of time spent in negative social situations, even when depression scores were controlled for. Conclusion These findings indicate that deficits in social learning may affect the quality of everyday social experiences. Specifically, the impaired ability to use social feedback to appropriately update future actions, which was observed in HD subjects, may lead to suboptimal interpersonal behavior in real life. This, in turn, may evoke negative feedback from others, thus bringing about more unpleasant social encounters.

scholarly journals Modeling fMRI signals can provide insights into neural processing in the cerebral cortex

2015 ◽  
Vol 114 (2) ◽  
pp. 768-780 ◽  
Author(s):  
Simo Vanni ◽  
Fariba Sharifian ◽  
Hanna Heikkinen ◽  
Ricardo Vigário
Keyword(s):  
Computational Models ◽  
Real Life ◽  
Mass Action ◽  
System Level ◽  
Specific System ◽  
Physiological Mechanisms ◽  
Mathematical Functions ◽  
Neural Mass ◽  
Recent Developments ◽  
The Relationship

Every stimulus or task activates multiple areas in the mammalian cortex. These distributed activations can be measured with functional magnetic resonance imaging (fMRI), which has the best spatial resolution among the noninvasive brain imaging methods. Unfortunately, the relationship between the fMRI activations and distributed cortical processing has remained unclear, both because the coupling between neural and fMRI activations has remained poorly understood and because fMRI voxels are too large to directly sense the local neural events. To get an idea of the local processing given the macroscopic data, we need models to simulate the neural activity and to provide output that can be compared with fMRI data. Such models can describe neural mechanisms as mathematical functions between input and output in a specific system, with little correspondence to physiological mechanisms. Alternatively, models can be biomimetic, including biological details with straightforward correspondence to experimental data. After careful balancing between complexity, computational efficiency, and realism, a biomimetic simulation should be able to provide insight into how biological structures or functions contribute to actual data processing as well as to promote theory-driven neuroscience experiments. This review analyzes the requirements for validating system-level computational models with fMRI. In particular, we study mesoscopic biomimetic models, which include a limited set of details from real-life networks and enable system-level simulations of neural mass action. In addition, we discuss how recent developments in neurophysiology and biophysics may significantly advance the modelling of fMRI signals.

Novel Visual Illusions Related to Vasarely's ‘Nested Squares’ Show That Corner Salience Varies with Corner Angle

Perception ◽  
10.1068/p5383 ◽  
2005 ◽  
Vol 34 (4) ◽  
pp. 409-420 ◽  
Author(s):  
Xoana G Troncoso ◽  
Stephen L Macknik ◽  
Susana Martinez-Conde
Keyword(s):  
Discrimination Task ◽  
Computational Models ◽  
Visual Illusion ◽  
Human Subjects ◽  
Brightness Discrimination ◽  
Receptive Fields ◽  
Visual Illusions ◽  
Corner Angle ◽  
Brightness Discrimination Task ◽  
Sharp Corners

Vasarely's ‘nested-squares’ illusion shows that 90° corners can be more salient perceptually than straight edges. On the basis of this illusion we have developed a novel visual illusion, the ‘Alternating Brightness Star’, which shows that sharp corners are more salient than shallow corners (an effect we call ‘corner angle salience variation’) and that the same corner can be perceived as either bright or dark depending on the polarity of the angle (ie whether concave or convex: ‘corner angle brightness reversal’). Here we quantify the perception of corner angle salience variation and corner angle brightness reversal effects in twelve naive human subjects, in a two-alternative forced-choice brightness discrimination task. The results show that sharp corners generate stronger percepts than shallow corners, and that corner gradients appear bright or dark depending on whether the corner is concave or convex. Basic computational models of center – surround receptive fields predict the results to some degree, but not fully.

scholarly journals Perceptual insensitivity to higher-order statistical moments of coherent random dot motion

2018 ◽  
Vol 18 (6) ◽  
pp. 9 ◽  
Author(s):  
Michael L. Waskom ◽  
Janeen Asfour ◽  
Roozbeh Kiani
Keyword(s):  
Higher Order ◽  
Statistical Moments ◽  
Dot Motion ◽  
Random Dot Motion

scholarly journals Jalan Tasawuf dalam Naskah Layang Ijo Koleksi Kyai Mohammad Thohari Sidoarjo, Jawa Timur

2015 ◽  
Vol 13 (2) ◽  
pp. 341
Author(s):  
Nur Said
Keyword(s):  
Real Life ◽  
Community Life ◽  
The Real ◽  
Physical Conditions ◽  
Inner Sense ◽  
Time Period ◽  
Interpretative Analysis ◽  
History Of ◽  
True Knowledge ◽  
And Behavior

This research examines four things: 1) Where do the origins of the manuscript Layang Ijo obtained by the collector?, 2) What is the description of the manuscript Layang Ijo ranging from physical conditions until characteristics of teaching?, 3) What the history of the manuscript Layang Ijo was collected dan taught?, 4) What are the values of Sufism anything thatcan be drawn from the Layang Ijo for the needs of the Islamic community life today? This research uses the philological procedures followed by interpretative analysis to find the path of Sufism in the Layang Ijo teaching.The conclusion of research shows that the tradition of writing in the time period of Wali Sanga is not just an expression of inner-sense (qalb) but also as response to the humanitarian concerns in the real life such as the mission and behavior (lelaku) of Wali Sanga, the importance of true knowledge (ilmu sejati), the Sufism, the harmony between tharikat, shari'ah and hakekat, as well as the mystery of the death of Sheikh Siti Djenar also reviewed in this manuscript. In the end it also discussed the way of ma'rifatullah as a legacy of the prophets, apostles and the lover of God (Waliyyullah).

scholarly journals Neuronal correlations in MT and MST impair population decoding of opposite directions of random dot motion

2018 ◽  
Author(s):  
Tristan A. Chaplin ◽  
Maureen A. Hagan ◽  
Benjamin J. Allitt ◽  
Leo L. Lui
Keyword(s):  
Population Coding ◽  
Correlation Structure ◽  
Single Neurons ◽  
Electrode Arrays ◽  
Preferred Direction ◽  
Dot Motion ◽  
Random Dot Patterns ◽  
Stimulus Features ◽  
Random Dot Motion ◽  
Spiking Activity

AbstractThe study of neuronal responses to random-dot motion patterns has provided some of the most valuable insights into how the activity of neurons is related to perception. In the opposite directions of motion paradigm, the motion signal strength is decreased by manipulating the coherence of random dot patterns to examine how well the activity of single neurons represents the direction of motion. To extend this paradigm to populations of neurons, studies have used modelling based on data from pairs of neurons, but several important questions require further investigation with larger neuronal datasets. We recorded neuronal populations in the middle temporal (MT) and medial superior temporal (MST) areas of anaesthetized marmosets with electrode arrays, while varying the coherence of random dot patterns in two opposite directions of motion (left and right). Using the spike rates of simultaneously recorded neurons, we decoded the direction of motion at each level of coherence with linear classifiers. We found that the presence of correlations had a detrimental effect to decoding performance, but that learning the correlation structure produced better decoding performance compared to decoders that ignored the correlation structure. We also found that reducing motion coherence increased neuronal correlations, but decoders did not need to be optimized for each coherence level. Finally, we showed that decoder weights depend of left-right selectivity at 100% coherence, rather than the preferred direction. These results have implications for understanding how the information encoded by populations of neurons is affected by correlations in spiking activity.Significance StatementMany studies have examined how the spiking activity of single neurons can encode stimulus features, such the direction of motion of visual stimuli. However, majority of such studies to date have only recorded from a small number of neurons at the same time, meaning that one cannot adequately account for the trial-to-trial correlations in spiking activity between neurons. Using multi-channel recordings, we were able to measure the neuronal correlations, and their effects on population coding of stimulus features. Our results have implications on the way which neural populations must be readout in order to maximize information.

scholarly journals Dynamic expressions of confidence within an evidence accumulation framework

2020 ◽  
Author(s):  
Kobe Desender ◽  
Tobias H. Donner ◽  
Tom Verguts
Keyword(s):  
Dynamic Model ◽  
Temporal Evolution ◽  
Human Behaviour ◽  
Evidence Accumulation ◽  
Decision Confidence ◽  
Confidence Judgments ◽  
Evidence Strength ◽  
Dot Motion ◽  
Over Time ◽  
Random Dot Motion

AbstractHuman observers can reliably report their confidence in the choices they make. An influential framework conceptualizes decision confidence as the probability of a decision being correct, given the choice made and the evidence on which it was based. This framework accounts for three diagnostic signatures of human confidence reports, including an opposite dependence of confidence on evidence strength for correct and error trials. However, the framework does not account for the temporal evolution of these signatures, because it only describes the transformation of a static representation of evidence into choice and the associated confidence. Here, we combine this framework with another influential framework: dynamic accumulation of evidence over time, and build on the notion that confidence reflects the probability of being correct, given the choice and accumulated evidence up until that point. Critically, we show that such a dynamic model predicts that the diagnostic signatures of confidence depend on time; most critically, it predicts a stronger opposite dependence of confidence on evidence strength and choice correctness as a function of time. We tested, and confirmed, these predictions in human behaviour during random dot motion discrimination, in which confidence judgments were queried at different points in time. We conclude that human confidence reports reflect the dynamics of the probability of being correct given the accumulated evidence and choice.

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