Perceptual Estimates Research Articles

Hierarchy of User’s Need for Spatial Organisation in Public Open Spaces

The research aims to identify the hierarchy of users’ need for spatial organization in public open spaces of New Delhi by quantifying user preferences to produce a perceptual estimation in conclusion. The research will generate a better understanding of the effective utilization of spatial organization in public open spaces by incorporating the user’s perception. The study acquires a qualitative method comprising content analysis as a line of inquiry. Interviews with users from different demographic profiles were conducted in public open spaces in New Delhi. The designed interview questions are based on the hierarchy of needs in which interviewees were asked to answer which attribute of the spatial organization they prefer above others. To analyze the user preferences, 12 interviews were conducted at three distinctive sites in New Delhi. The study concludes that; ‘Accessibility and Linkages’ and ‘Security’ are the imminent attributes considered as a basic need for spatial organization in public open spaces of New Delhi, followed by ‘Facilities,’ ‘Uses and Activities,’ and ‘Microclimate.’

Psychometrics of inertial heading perception.

Inertial self-motion perception is thought to depend primarily on otolith cues. Recent evidence demonstrated that vestibular perceptual thresholds (including inertial heading) are adaptable, suggesting novel clinical approaches for treating perceptual impairments resulting from vestibular disease. Little is known about the psychometric properties of perceptual estimates of inertial heading like test-retest reliability. Here we investigate the psychometric properties of a passive inertial heading perceptual test. Forty-seven healthy subjects participated across two visits, performing in an inertial heading discrimination task. The point of subjective equality (PSE) and thresholds for heading discrimination were identified for the same day and across day tests. Paired t-tests determined if the PSE or thresholds significantly changed and a mixed interclass correlation coefficient (ICC) model examined test-retest reliability. Minimum detectable change (MDC) was calculated for PSE and threshold for heading discrimination. Within a testing session, the heading discrimination PSE score test-retest reliability was good (ICC = 0. 80) and did not change (t(1,36) = -1.23, p = 0.23). Heading discrimination thresholds were moderately reliable (ICC = 0.67) and also stable (t(1,36) = 0.10, p = 0.92). Across testing sessions, heading direction PSE scores were moderately correlated (ICC = 0.59) and stable (t(1,46) = -0.44, p = 0.66). Heading direction thresholds had poor reliability (ICC = 0.03) and were significantly smaller at the second visit (t(1,46) = 2.8, p = 0.008). MDC for heading direction PSE ranged from 6-9 degrees across tests. The current results indicate moderate reliability for heading perception PSE and provide clinical context for interpreting change in inertial vestibular self-motion perception over time or after an intervention.

The contribution of semantic distance knowledge to size constancy in perception and grasping when visual cues are limited

To achieve a stable perception of object size in spite of variations in viewing distance, our visual system needs to combine retinal image information and distance cues. Previous research has shown that, not only retinal cues, but also extraretinal sensory signals can provide reliable information about depth and that different neural networks (perception versus action) can exhibit preferences in the use of these different sources of information during size-distance computations. Semantic knowledge of distance, a purely cognitive signal, can also provide distance information. Do the perception and action systems show differences in their ability to use this information in calculating object size and distance? To address this question, we presented ‘glow-in-the-dark’ objects of different physical sizes at different real distances in a completely dark room. Participants viewed the objects monocularly through a 1-mm pinhole. They either estimated the size and distance of the objects or attempted to grasp them. Semantic knowledge was manipulated by providing an auditory cue about the actual distance of the object: “20 cm”, “30 cm”, and “40 cm”. We found that semantic knowledge of distance contributed to some extent to size constancy operations during perceptual estimation and grasping, but size constancy was never fully restored. Importantly, the contribution of knowledge about distance to size constancy was equivalent between perception and action. Overall, our study reveals similarities and differences between the perception and action systems in the use of semantic distance knowledge and suggests that this cognitive signal is useful but not a reliable depth cue for size constancy under restricted viewing conditions.

A unifying theory explains seemingly contradictory biases in perceptual estimation.

Perceptual biases are widely regarded as offering a window into the neural computations underlying perception. To understand these biases, previous work has proposed a number of conceptually different, and even seemingly contradictory, explanations, including attraction to a Bayesian prior, repulsion from the prior due to efficient coding and central tendency effects on a bounded range. We present a unifying Bayesian theory of biases in perceptual estimation derived from first principles. We demonstrate theoretically an additive decomposition of perceptual biases into attraction to a prior, repulsion away from regions with high encoding precision and regression away from the boundary. The results reveal a simple and universal rule for predicting the direction of perceptual biases. Our theory accounts for, and yields, new insights regarding biases in the perception of a variety of stimulus attributes, including orientation, color and magnitude. These results provide important constraints on the neural implementations of Bayesian computations.

Neurophysiological correlates of interpersonal discrepancy and social adjustment in an interactive decision-making task in dyads.

The pursuit of convergence and the social behavioral adjustment of conformity are fundamental cooperative behaviors that help people adjust their mental frameworks to reach a common goal. However, while social psychology has extensively studied conformity by its influence context, there is still plenty to investigate about the neural cognitive mechanisms involved in this behavior. We proposed a paradigm with two phases, a pre-activation phase to enhance cooperative tendencies and, later, a social decision-making phase in which dyads had to make a perceptual estimation in three consecutive trials and could converge in their decisions without an explicit request or reward to do so. In Study 1, 80 participants were divided in two conditions. In one condition participants did the pre-activation phase alone, while in the other condition the two participants did it with their partners and could interact freely. In Study 2, we registered the electroencephalographical (EEG) activity of 36 participants in the social decision-making phase. Study 1 showed behavioral evidence of higher spontaneous convergence in participants who interacted in the pre-activation phase. Event related Potentials (ERP) recorded in Study 2 revealed signal differences in response divergence in different time intervals. Time-frequency analysis showed theta, alpha, and beta evidence related to cognitive control, attention, and reward processing associated with social convergence. Current results support the spontaneous convergence of behavior in dyads, with increased behavioral adjustment in those participants who have previously cooperated. In addition, neurophysiological components were associated with discrepancy levels between participants, and supported the validity of the experimental paradigm to study spontaneous social behavioral adaptation in experimental settings.

The (Un)ideal Physicist: How Humans Rely on Object Interaction for Friction Estimates.

To estimate object properties such as mass or friction, our brain relies on visual information to efficiently compute approximations. The role of sensorimotor feedback, however, is not well understood. Here we tested healthy adults (N = 79) in an inclined-plane problem, that is, how much a plane can be tilted before an object starts to slide, and contrasted the interaction group with observation groups who accessed involved forces by watching objects being manipulated. We created objects of different masses and levels of friction and asked participants to estimate the critical tilt angle after pushing an object, lifting it, or both. Estimates correlated with applied forces and were biased toward object mass, with higher estimates for heavier objects. Our findings highlight that inferences about physical object properties are tightly linked to the human sensorimotor system and that humans integrate sensorimotor information even at the risk of nonveridical perceptual estimates.

Self as a prior: The malleability of Bayesian multisensory integration to social salience.

Our everyday perceptual experiences are grounded in the integration of information within and across our senses. Due to this direct behavioural relevance, cross-modal integration retains a certain degree of contextual flexibility, even to social relevance. However, how social relevance modulates cross-modal integration remains unclear. To investigate possible mechanisms, Experiment 1 tested the principles of audio-visual integration for numerosity estimation by deriving a Bayesian optimal observer model with perceptual prior from empirical data to explain perceptual biases. Such perceptual priors may shift towards locations of high salience in the stimulus space. Our results showed that the tendency to over- or underestimate numerosity, expressed in the frequency and strength of fission and fusion illusions, depended on the actual event numerosity. Experiment 2 replicated the effects of social relevance on multisensory integration from Scheller & Sui, 2022 JEP:HPP, using a lower number of events, thereby favouring the opposite illusion through enhanced influences of the prior. In line with the idea that the self acts like a prior, the more frequently observed illusion (more malleable to prior influences) was modulated by self-relevance. Our findings suggest that the self can influence perception by acting like a prior in cue integration, biasing perceptual estimates towards areas of high self-relevance.

Do striking biases in mass inference reflect a flawed mental model of physics?

To engage with the physical world, we rely on our intuitive sense of how objects will behave when we act on them or they interact with each other. Objects' latent properties such as mass and hardness determine how their physical interactions will unfold, and people have a keen ability to infer these latent properties by observing physical events. For example, we can precisely discriminate the relative masses of two objects when we see them collide. However, such inferences are sometimes subject to marked biases. When inferring mass from an observed collision, people consistently overestimate the mass of an incoming object that strikes a stationary one. Why? A number of plausible accounts have been put forward, variously arguing that the bias arises from rule-based reasoning, oversimplified stimuli, or noisy perceptual estimates of the scene dynamics. The implications of these views stand in stark contrast to one another: systematic biases may reveal a fundamental deficiency in the mental model of physical behavior, or they may be an expected consequence of reasoning over imperfect information. Here, we investigated all three accounts within a unified paradigm, presenting videos of real-world bowling ball collisions. We found that using richly detailed stimuli did not eliminate biases in mass inference. However, individual differences in the biases were task-specific and well-explained by noisy perceptual estimates rather than oversimplified physical inference mechanisms. Our findings collectively point toward an intuitive physics system that implements Newtonian principles but is subject to the quality of the information it operates on. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

A unifying theory explains seemingly contradicting biases in perceptual estimation

A unifying theory explains seemingly contradicting biases in perceptual estimation

Perceptual estimates of the physical attributes of people in photographs

Perceptual estimates of the physical attributes of people in photographs

A Machine-Learning Algorithm for the Automated Perceptual Evaluation of Dysphonia Severity

Auditory-perceptual assessments are the gold standard for assessing voice quality. This project aims to develop a machine-learning model for measuring perceptual dysphonia severity of audio samples consistent with assessments by expert raters. The Perceptual Voice Qualities Database samples were used, including sustained vowel and Consensus Auditory-Perceptual Evaluation of Voice sentences, whichwere previously expertly rated on a 0-100 scale. The OpenSMILE (audEERING GmbH, Gilching, Germany) toolkit was used to extract acoustic (Mel-Frequency Cepstral Coefficient-based, n=1428) and prosodic (n=152) features, pitch onsets, and recording duration. We utilized a support vector machineand these features (n=1582) for automated assessment of dysphonia severity. Recordings were separated into vowels (V) and sentences (S) and features were extracted separately from each. Final voice quality predictions were made by combining the features extracted from the individual components with the whole audio (WA) sample (three file sets: S, V, WA). This algorithm has a high correlation (r=0.847) with estimates of expert raters. The root mean square error was 13.36. Increasing signal complexity resulted in better estimation of dysphonia, whereby combining the features outperformed WA, S, and V sets individually. A novel machine-learning algorithm was able to perform perceptual estimates of dysphonia severity using standardized audio samples on a 100-point scale. This was highly correlated to expert raters. This suggests that ML algorithms could offer an objective method for evaluating voice samples for dysphonia severity.

Not only perception but also grasping actions can obey Weber’s law

Weber’s law, the principle that the uncertainty of perceptual estimates increases proportionally with object size, is regularly violated when considering the uncertainty of the grip aperture during grasping movements. The origins of this perception-action dissociation are debated and are attributed to various reasons, including different coding of visual size information for perception and action, biomechanical factors, the use of positional information to guide grasping, or, sensorimotor calibration. Here, we contrasted these accounts and compared perceptual and grasping uncertainties by asking people to indicate the visually perceived center of differently sized objects (Perception condition) or to grasp and lift the same objects with the requirement to achieve a balanced lift (Action condition). We found that the variability (uncertainty) of contact positions increased as a function of object size in both perception and action. The adherence of the Action condition to Weber’s law and the consequent absence of a perception-action dissociation contradict the predictions based on different coding of visual size information and sensorimotor calibration. These findings provide clear evidence that human perceptual and visuomotor systems rely on the same visual information and suggest that the previously reported violations of Weber’s law in grasping movements should be attributed to other factors.

Contrary neuronal recalibration in different multisensory cortical areas.

The adult brain demonstrates remarkable multisensory plasticity by dynamically recalibrating itself based on information from multiple sensory sources. After a systematic visual-vestibular heading offset is experienced, the unisensory perceptual estimates for subsequently presented stimuli are shifted toward each other (in opposite directions) to reduce the conflict. The neural substrate of this recalibration is unknown. Here, we recorded single-neuron activity from the dorsal medial superior temporal (MSTd), parietoinsular vestibular cortex (PIVC), and ventral intraparietal (VIP) areas in three male rhesus macaques during this visual-vestibular recalibration. Both visual and vestibular neuronal tuning curves in MSTd shifted - each according to their respective cues' perceptual shifts. Tuning of vestibular neurons in PIVC also shifted in the same direction as vestibular perceptual shifts (cells were not robustly tuned to the visual stimuli). By contrast, VIP neurons demonstrated a unique phenomenon: both vestibular and visual tuning shifted in accordance with vestibular perceptual shifts. Such that, visual tuning shifted, surprisingly, contrary to visual perceptual shifts. Therefore, while unsupervised recalibration (to reduce cue conflict) occurs in early multisensory cortices, higher-level VIP reflects only a global shift, in vestibular space.

Robotics-Based Characterization of Sensorimotor Integration in Parkinson's Disease and the Effect of Medication.

Integration of multi-modal sensory inputs and modulation of motor outputs based on perceptual estimates is called Sensorimotor Integration (SMI). Optimal functioning of SMI is essential for perceiving the environment, modulating the motor outputs, and learning or modifying motor skills to suit the demands of the environment. Growing evidence suggests that patients diagnosed with Parkinson's Disease (PD) may suffer from an impairment in SMI that contributes to perceptual deficits, leading to motor abnormalities. However, the exact nature of the SMI impairment is still unclear. This study uses a robot-assisted assessment tool to quantitatively characterize SMI impairments in PD patients and how they affect voluntary movements. A set of assessment tasks was developed using a robotic manipulandum equipped with a virtual-reality system. The sensory conditions of the virtual environment were varied to facilitate the assessment of SMI. A hundred PD patients (before and after medication) and forty-three control subjects completed the tasks under varying sensory conditions. The kinematic measures obtained from the robotic device were used to evaluate SMI. The findings reveal that across all sensory conditions, PD patients had 36% higher endpoint error, 38% higher direction error in reaching tasks, and 43% higher number of violations in tracing tasks than control subjects due to impairment in integrating sensory inputs. However, they still retained motor learning ability and the ability to modulate motor outputs. The medication worsened the SMI deficits as PD patients, after medication, performed worse than before medication when encountering dynamic sensory environments and exhibited impaired motor learning ability.

NLOS Positioning for Building Layout and Target Based on Association and Hypothesis Method

Localization of non-line-of-sight (NLOS) targets in the complex urban environment have attracted significant attention in recent years. However, the requirement for precise prior information about the environment is idealistic. It is challenging to know the environmental information in the blind area of vision in advance of practical applications. This paper proposes a joint estimation algorithm for building layout and target position in the L-shaped scene without any prior information. Specifically, a round-trip multipath propagation model is first developed for the cases of diffraction and multiple reflections. Then, the received echo signal is preprocessed with moving target identification (MTI), back-projection (BP) imaging, and image segmentation. In addition, the target points, which are screened by geometric association, are further matched and estimated by the multipath ghost’s hypothesis method, thus realizing the joint perceptual estimation of the building layout and the target position. Finally, electromagnetic (EM) simulations and experimental measurements are used to validate the effectiveness of the proposed algorithm.

Newly learned shape-color associations show signatures of reliability-weighted averaging without forced fusion or a memory color effect.

Reliability-weighted averaging of multiple perceptual estimates (or cues) can improve precision. Research suggests that newly learned statistical associations can be rapidly integrated in this way for efficient decision-making. Yet, it remains unclear if the integration of newly learned statistics into decision-making can directly influence perception, rather than taking place only at the decision stage. In two experiments, we implicitly taught observers novel associations between shape and color. Observers made color matches by adjusting the color of an oval to match a simultaneously presented reference. As the color of the oval changed across trials, so did its shape according to a novel mapping of axis ratio to color. Observers showed signatures of reliability-weighted averaging-a precision improvement in both experiments and reweighting of the newly learned shape cue with changes in uncertainty in Experiment 2. To ask whether this was accompanied by perceptual effects, Experiment 1 tested for forced fusion by measuring color discrimination thresholds with and without incongruent novel cues. Experiment 2 tested for a memory color effect, observers adjusting the color of ovals with different axis ratios until they appeared gray. There was no evidence for forced fusion and the opposite of a memory color effect. Overall, our results suggest that the ability to quickly learn novel cues and integrate them with familiar cues is not immediately (within the short duration of our experiments and in the domain of color and shape) accompanied by common perceptual effects.

Transfer of weight information depends differently on used hand and handedness for perception and action.

When lifting an object sequentially with the two hands, information about object weight can be transferred from one hand to the other. This information can be used to predictively scale fingertip forces and to form a perceptual estimation about the object's weight. This study investigated how weight information can be transferred between the two hands and how this depends on the used hand and handedness of the participant. Right- and left-handed participants lifted light and heavy objects with the right or left hand in a pseudorandomized order and estimated the object's weight. Results showed that predictive force scaling depended on the previously lifted object, with higher force rates if a previous object was heavy. This known effect of sensorimotor memory was mostly independent of the used hand and handedness, indicating that weight information could be transferred across hands for fingertip force scaling. Furthermore, a perceptual bias that depended on the previous lifted object was found, with lower weight estimations when the previous object was heavy compared to light. While this bias was found for both light and heavy objects in right-handers, it was only observed for light objects in left-handers. Notably, in contrast to the results on force scaling, this effect was not transferred across hands. These findings indicate that the transfer of weight information depends differently on the used hand and handedness for perceptual estimations and predictive force scaling.

Scene variability biases our decisions, but not our perceptual estimates.

We constantly perform tasks within complex and dynamic environments. Some of these tasks (e.g., road crossing or playing team sports) require predicting future states of the world to decide which action to unfold and when to do so. However, it remains largely unexplored how the variability in a scene influences perceptual decision-making. Here we examine how increasing the scene variability influences our ability to make perceptual judgements and decisions by using a go/no-go decision task in a dynamic scenario mimicking a road-crossing situation with different levels of stimuli variability. Parameters of psychometric functions revealed that differences in variability do not influence judgements about the objects' time-to-contact, or the difficulty in making such judgements. Nevertheless, increases in the scene variability influence the go/no-go decisions leading people to adopt more conservative criteria. How much the criterion changes across levels of variability is well accounted for by the actual amount of variance in the scene, but the overall criterion is tightly linked to the precision or reliability with which one can estimate perceptual information about the objects' arrival time. These results suggest that the reliability on our own perceptual estimates modulate our criterion when completing perceptual decision-making tasks under different scene variabilities. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Attractive and repulsive effects of sensory history concurrently shape visual perception

BackgroundSequential effects of environmental stimuli are ubiquitous in most behavioral tasks involving magnitude estimation, memory, decision making, and emotion. The human visual system exploits continuity in the visual environment, which induces two contrasting perceptual phenomena shaping visual perception. Previous work reported that perceptual estimation of a stimulus may be influenced either by attractive serial dependencies or repulsive aftereffects, with a number of experimental variables suggested as factors determining the direction and magnitude of sequential effects. Recent studies have theorized that these two effects concurrently arise in perceptual processing, but empirical evidence that directly supports this hypothesis is lacking, and it remains unclear whether and how attractive and repulsive sequential effects interact in a trial. Here we show that the two effects concurrently modulate estimation behavior in a typical sequence of perceptual tasks.ResultsWe first demonstrate that observers’ estimation error as a function of both the previous stimulus and response cannot be fully described by either attractive or repulsive bias but is instead well captured by a summation of repulsion from the previous stimulus and attraction toward the previous response. We then reveal that the repulsive bias is centered on the observer’s sensory encoding of the previous stimulus, which is again repelled away from its own preceding trial, whereas the attractive bias is centered precisely on the previous response, which is the observer’s best prediction about the incoming stimuli.ConclusionsOur findings provide strong evidence that sensory encoding is shaped by dynamic tuning of the system to the past stimuli, inducing repulsive aftereffects, and followed by inference incorporating the prediction from the past estimation, leading to attractive serial dependence.

Flexible integration of continuous sensory evidence in perceptual estimation tasks

Temporal accumulation of evidence is crucial for making accurate judgments based on noisy or ambiguous sensory input. The integration process leading to categorical decisions is thought to rely on competition between neural populations, each encoding a discrete categorical choice. How recurrent neural circuits integrate evidence for continuous perceptual judgments is unknown. Here, we show that a continuous bump attractor network can integrate a circular feature, such as stimulus direction, nearly optimally. As required by optimal integration, the population activity of the network unfolds on a two-dimensional manifold, in which the position of the network's activity bump tracks the stimulus average, and, simultaneously, the bump amplitude tracks stimulus uncertainty. Moreover, the temporal weighting of sensory evidence by the network depends on the relative strength of the stimulus compared to the internally generated bump dynamics, yielding either early (primacy), uniform, or late (recency) weighting. The model can flexibly switch between these regimes by changing a single control parameter, the global excitatory drive. We show that this mechanism can quantitatively explain individual temporal weighting profiles of human observers, and we validate the model prediction that temporal weighting impacts reaction times. Our findings point to continuous attractor dynamics as a plausible neural mechanism underlying stimulus integration in perceptual estimation tasks.