Biology subjects

Landy, M. S.

Publications and source records attributed to Landy, M. S..

14 recordsLinked to original sources

bioRxiv2026

No benefit of subsampling in ensemble coding

Our visual system compensates for its limited information processing capacity by creating summary representations of stimulus ensembles. A longstanding debate concerns whether summary statistics are computed by integrating information across the entire ensemble or by sampling only a subset of its items. Subsampling is intuitively appealing because 1) integrating over a small subset presumably reduces processing resource expenditure and 2) observer models employing this strategy can effectively reproduce ensemble coding performance. Here, we systematically evaluate both aspects. We first show that the apparent success of subsampling models depends on a problematic assumption: that the sensory encoding noise of each item remains constant as set size increases. This assumption entails that total coding resources, quantified as Fisher information, grow unconstrained with set size. Under the realistic assumption that total coding resources are limited, such that the encoding precision for each item decreases with increasing set size, we demonstrate that an ideal observer integrating the entire ensemble achieves the same accuracy with a strictly smaller total resource budget for every set size. We further show that this resource-constrained full-integration model provides a more parsimonious, yet equally good, account of ensemble coding behavior across multiple existing datasets as well as newly collected data. Our findings call into question the necessity of the subsampling hypothesis, as restricting integration to a subset of ensemble items confers neither a theoretical nor an explanatory benefit over resource-rational full integration.

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bioRxiv2026

Duration judgments with conflicting audiovisual cues

Previous work showed that observers integrate audiovisual duration cues optimally when cue-conflict is small. Does causal inference lead to a breakdown of audiovisual integration when duration conflicts are large? We addressed this by testing a wide range of duration cue-conflicts. Participants compared the auditory durations of a test and a standard stimulus. Audiovisual durations were consistent in the test stimulus, but differed by seven conflict durations (up to 250 ms) in the standard. Two levels of auditory noise were tested. Auditory duration percepts shifted systematically toward the visual duration, especially with high auditory noise. The shift was proportional to cue-conflict magnitude, inconsistent with causal inference. We compared several models. A heuristic model in which the observer probabilistically switches between the visual and auditory cues was preferred for most participants, although performance differences across models were small. Within the tested conflict range, the forced fusion, causal inference, and probabilistic cue switching models produced overlapping, near-linear shifts as a function of cue-conflict. Model simulations further revealed that given the measured sensory noise, forced fusion and causal inference can be discriminated only with unreasonably large conflicts. Together, while our results suggest that observers do not rely on causal inference when judging auditory durations under our conditions, high sensory encoding noise in auditory duration limits the discriminability of competing computational models.

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bioRxiv2026

Dissociating the behavioral and computational features of implicit motor learning and explicit perturbation detection

The human sensorimotor system is remarkably effective at automatically parsing total movement error into its constituent parts, the error component due to a perturbation, or externally-generated error (EGE), versus the error component due to motor noise, or internally-generated error (IGE). Participants robustly, and implicitly, adapt to minuscule (2{degrees}) EGEs in the form of randomized visuomotor rotations while ignoring identically-sized errors caused by IGE. This error parsing, and its associated perceptual processes, directly contrasts previous work showing that humans must observe rotations that are > 1.5x the standard deviations of their motor variability, or [≥] 4{degrees}, before explicitly reporting their presence. While the combined results suggest a dissociation between perception for action--which allows for precise and automatic error parsing--and perception for conscious detection, this must be inferred across studies using different methodologies. Here, we combined a within-subjects study design and computational modeling to shed light on the principles underlying implicit adaptation to a perturbation and explicit perturbation detection. Neuro-typical adults participated in two experiments consisting of pseudo-randomized rotations during reaches to a single target, with one session requiring explicit reports after each reach of whether a perturbation was detected. Participants demonstrated a clear dissociation between implicit responses to a perturbation and explicit detection, with robust adaptation to 1{degrees} EGEs, but an inability to reliably report the presence of an EGE until it reached [~] 4{degrees}. For the adaptation task, a model that assumes the participant compares proprioceptive and visual cues to detect a perturbation and corrects for a proportion of this error best fit the data. For signal-detection, a Bayesian causal-inference model in which sensory cues are optimally integrated with a prior on their cause best fit those data. These results indicate that implicit adaptation is dissociated from explicit perturbation detection and the sensorimotor system applies distinct computational strategies to these behaviors.

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bioRxiv2026

Normalization accounts for temporal dynamics in human somatosensory cortex

Sensory processing is fundamentally shaped by stimulation history. For example, in visual cortex, neural responses are reduced for repeated or sustained stimuli (adaptation). These phenomena are well characterized and effectively modeled by divisive normalization. We asked whether these same computational principles govern somatosensory processing. We used fMRI (6 participants) and intracranial electroencephalography (iEEG, 2 participants) to measure responses to time-varying vibrotactile stimuli in human somatosensory cortex. Stimuli consisted of single- and paired-pulses with durations and interstimulus intervals ranging from 0.05 to 1.2 s. We extracted BOLD time courses to capture neural response amplitudes, and high-frequency iEEG broadband envelopes to capture fast neural dynamics. In both experiments, we observed pronounced sub-additive temporal summation. Responses to longer or repeated stimuli were consistently lower than predicted by linear integration. Computational modeling revealed that divisive normalization models outperformed linear models in cross-validated accuracy across both datasets. These results demonstrate that somatosensory temporal dynamics closely mirror those in the visual system. Our findings suggest that the nervous system employs similar computational principles across modalities to encode sensory information across time. Significance statementHow the brain integrates sensory information over time is a fundamental question in neuroscience. While nonlinear temporal integration is well documented in visual cortex, it has not been extensively mapped in the human somatosensory system. By combining fMRI with intracranial EEG in humans, we demonstrate that somatosensory responses to tactile stimulation exhibit subadditive temporal summation. This nonlinearity is accurately captured by a divisive normalization model, matching observations in the visual system. Our results suggest that normalization is a canonical computation shared across different modalities to manage temporal dynamics, providing a unified framework for understanding how the brain encodes dynamic sensory stimuli.

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bioRxiv2026

Visual confidence accurately tracks increasing internal noise with eccentricity in peripheral vision

Sensory representations are inherently noisy, and monitoring this noise is essential for effective decision-making. This metacognitive ability of evaluating the quality of ones perceptual decision is referred to as perceptual confidence. However, whether perceptual confidence accurately tracks internal noise remains unresolved. Peripheral vision provides a natural testing ground for this question, yet previous studies report mixed results complicated by different definitions and measurements of confidence. Here, we used a normative Bayesian framework with incentivized confidence measurements to address these discrepancies. We tested the Bayesian-confidence hypothesis that confidence is derived from the posterior probability distribution of the feature being judged, given noisy sensory measurements. We tested two perceptual tasks while varying stimulus eccentricity: spatial localization and orientation estimation. We measured confidence by post-decision wagering, by which participants set a symmetrical range around the perceptual estimates. Participants earned higher reward for narrower confidence ranges but received zero reward if the range did not enclose the target. We estimated sensory noise from the perceptual responses to predict confidence, assuming that sensory noise linearly increases with eccentricity. We then compared a normative Bayesian model with three alternative models that challenged different assumptions. Across both tasks, the Bayesian ideal-observer model best predicted confidence. These results suggest that humans can accurately monitor the increased internal noise in peripheral vision and use this information to make optimal confidence judgments.

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bioRxiv2025

Implicit adaptations effect on sensorimotor and motor confidence

Sensorimotor adaptation maintains movement accuracy by counteracting perturbations or miscalibrations. It can operate explicitly, by consciously adjusting motor plans to correct errors, or implicitly, by automatically recalibrating sensorimotor mappings without altering the motor plan. While explicit adaptation is known to reduce sensorimotor confidence--the perceived likelihood of successful action--it is unclear whether implicit adaptation similarly affects confidence in sensorimotor judgments or motor awareness (knowledge of ones own limb position). To investigate this, participants made reaching movements to visual targets without seeing their hand. Cursor feedback followed an "error-clamped" trajectory: its radial position matched the hand, but its angular direction was fixed and independent of actual hand direction, a manipulation participants were told to ignore. The clamp direction varied sinusoidally over trials ({+/-}10{degrees}; 12 cycles per session). Participants reported confidence by adjusting the size of an arc centered on the target or, in another task, centered on reported reach direction; larger arcs indicated lower confidence. Points were awarded when the arc encompassed the true reach direction, with fewer points for larger arcs, encouraging accurate and meaningful confidence reports. Fourier analysis of reach and report time series revealed a strong 12-cycle component in both, demonstrating robust implicit adaptation and corresponding changes in motor awareness. These findings indicate that although implicit adaptation operates unconsciously, the resulting mismatch between motor plans and proprioceptive signals can bias judgments of reach outcomes. However, confidence judgments were not consistently affected, suggesting that sensorimotor confidence and confidence in proprioceptive awareness may rely on partially distinct mechanisms. New & NoteworthyThis work is among the first to look at how implicit adaptation influences meta-judgments regarding motor execution and internal states. It identifies a dissociation between sensorimotor confidence and motor-awareness confidence.

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bioRxiv2025

Sensorimotor confidence during explicit motor adaptation

Humans can adapt to large and sudden perturbations of sensory feedback. What multisensory and motor-execution cues are used to determine confidence in action success, and do the dynamics of confidence parallel those of ongoing sensorimotor adaptation? Participants made a slicing reach through a visual target with an unseen hand, followed by a continuous judgment of confidence in reach success. For the confidence judgment, participants adjusted the size of an arc centered on the target. Larger arcs reflected lower confidence. Points were awarded if the subsequent visual feedback was within the arc, and fewer points returned for larger arcs. This incentivized attentive reporting of confidence and minimizing feedback-target distance to maximize the score. After the confidence response, visual feedback of hand position was shown at the same distance along the reach as the target. A 20 deg rotation was applied to the feedback during the central 50 trials of a block (alternating between clockwise and counterclockwise across blocks). We used least-squares cross validation to compare four Bayesian-inference models of sensorimotor confidence using prospective cues (knowledge of motor noise and visual feedback from past performance), retrospective cues (proprioceptive measurements), or both sources of information integrated to maximize expected gain (an ideal observer) with additional parameters for learning and bias. All but one of the participants used proprioception to calculate sensorimotor confidence during motor adaptation in addition to prior information. Confidence recovered exponentially to pre-adaptation levels after the perturbation ended, but at a slower rate than motor learning. Author SummaryWe asked participants to reach to visible locations on a tablet, without being able to see their hands. We then showed them false feedback that had been rotated away from their actual hand position. This caused them to need to aim away from their intended reach direction on later trials. Confidence in their ability to have the feedback land close to the target was reduced for more trials than it took them to adapt to the rotation. To perform well, it was necessary for people to take into account their success on previous trials as well as where they sensed their hand to be positioned on the current reach.

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bioRxiv2024

Functional localization of visual motion area FST in humans

The fundus of the superior temporal sulcus (FST) in macaques is implicated in the processing of complex motion signals, yet a human homolog remains elusive. Here we considered potential localizers and evaluated their effectiveness in delineating putative FST (pFST), from hMT and MST, two nearby motion-sensitive areas in humans. Nine healthy participants underwent scanning sessions with 2D and 3D motion localizers, as well as population receptive field (pRF) mapping. We observed consistent anterior and inferior activation relative to hMT and MST in response to stimuli that contained coherent 3D, but not 2D, motion. Motion opponency and myelination measures further validated the functional and structural distinction between pFST and hMT/MST. At the same time, standard pRF mapping techniques that reveal the visual field organization of hMT/MST proved suboptimal for delineating pFST. Our findings provide a robust framework for localizing pFST in humans, and underscore its distinct functional role in motion processing.

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bioRxiv2024

Uncertainty-based causal inference modulates audiovisual temporal recalibration

Cross-modal temporal recalibration guarantees stable temporal perception across ever-changing environments. Yet, the mechanisms of cross-modal temporal recalibration remain unknown. Here, we conducted an experiment to measure how participants temporal perception was affected by exposure to audiovisual stimuli with consistent temporal delays. Consistent with previous findings, recalibration effects plateaued with increasing audiovisual asynchrony and varied by which modality led during the exposure phase. We compared six observer models that differed in how they update the audiovisual temporal bias during the exposure phase and whether they assume modality-specific or modality-independent precision of arrival latency. The causal-inference observer shifts the audiovisual temporal bias to compensate for perceived asynchrony, which is inferred by considering two causal scenarios: when the audiovisual stimuli have a common cause or separate causes. The asynchrony-contingent observer updates the bias to achieve simultaneity of auditory and visual measurements, modulating the update rate by the likelihood of the audiovisual stimuli originating from a simultaneous event. In the asynchrony-correction model, the observer first assesses whether the sensory measurement is asynchronous; if so, she adjusts the bias proportionally to the magnitude of the measured asynchrony. Each model was paired with either modality-specific or modality-independent precision of arrival latency. A Bayesian model comparison revealed that both the causal-inference process and modality-specific precision in arrival latency are required to capture the nonlinearity and asymmetry observed in audiovisual temporal recalibration. Our findings support the hypothesis that audiovisual temporal recalibration relies on the same causal-inference processes that govern cross-modal perception.

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bioRxiv2022

Feeling lucky? Prospective and retrospective cues for sensorimotor confidence

On a daily basis, humans interact with the outside world using judgments of sensorimotor confidence, constantly evaluating our actions for success. We ask, what sensory and motorexecution cues are used in making these judgements and when are they available? Two sources of temporally distinct information are prospective cues, available prior to the action (e.g., knowledge of motor noise and past performance), and retrospective cues specific to the action itself (e.g., proprioceptive measurements). We investigated the use of these two cues in two tasks, a secondary motor-awareness task and a main task in which participants reached toward a visual target with an unseen hand and then made a continuous judgment of confidence about the success of the reach. Confidence was reported by setting the size of a circle centered on the reach-target location, where a larger circle reflects lower confidence. Points were awarded if the confidence circle enclosed the true endpoint, with fewer points returned for larger circles. This incentivized accurate reaches and attentive reporting to maximize the score. We compared three Bayesian-inference models of sensorimotor confidence based on either prospective cues, retrospective cues, or both sources of information to maximize expected gain (i.e., an ideal-performance model). Our findings showed two distinct strategies: participants either performed as ideal observers, using both prospective and retrospective cues to make the confidence judgment, or relied solely on prospective information, ignoring retrospective cues. Thus, participants can make use of retrospective cues, evidenced by the behavior observed in our motorawareness task, but these cues are not always included in the computation of sensorimotor confidence. Author SummarySensorimotor confidence is a secondary judgment about how successful we feel a motor action was with relation to the goal. To make this judgment we can draw on information available before we execute an action such as our past experiences and knowledge of the environment, as well as after the action including visual feedback and proprioception, a sense of where our body is in space. In this study, we inquired as to how the information available before and after an action is weighted when considering the final feeling of sensorimotor confidence. To do so we asked participants to make reaches to visually cued targets in an unseen hand task, then report their confidence in how successful they were at hitting the target. We measured each participants reach accuracy and proprioceptive sensitivity in a separate task. Using mathematical models to fit our data we tested if a given participant depended more heavily on prior information or retrospective information when making their confidence judgment. We found that participants with high proprioceptive uncertainty were more likely to focus on prior knowledge while those with a more exact sense of proprioception incorporated information from both time points.

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bioRxiv2022

Identifying cortical areas that underlie the transformation from retinal to world motion signals

Accurate motion perception requires that the visual system integrate the retinal motion signals received by the two eyes into a single representation of 3D (i.e., world) motion. However, most experimental paradigms limit the motion stimuli to the fronto-parallel plane (i.e., 2D motion) and are thus unable to dissociate retinal and world motion signals. Here, we used stereoscopic displays to present separate motion signals to the two eyes and examined their representation in visual cortex using fMRI. Specifically, we presented random-dot motion stimuli that produced percepts of various 3D motion trajectories. We also presented control stimuli that contained the same retinal motion energy in the two eyes but were inconsistent with any 3D motion trajectory. We decoded the stimuli from BOLD activity using a probabilistic decoding algorithm. We found that 3D motion direction can be reliably decoded in three major clusters in the human visual system. In early visual cortex (V1-V3), we found no significant difference in decoding performance between the 3D motion and control stimuli, suggesting that these areas represent retinal motion rather than world motion signals. In voxels in and surrounding hMT and IPS0 however, decoding performance was consistently superior for 3D motion compared to control stimuli. Our results reveal the parts of the visual processing hierarchy that are critical for the transformation of retinal into world motion signals and suggest a role for IPS0 in the representation of 3D motion signals, in addition to its sensitivity to 3D object structure and static depth.

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bioRxiv2019

Performance Monitoring for Sensorimotor Confidence: A Visuomotor Tracking Study

To best interact with the external world, humans are often required to consider the quality of their actions. Sometimes the environment furnishes rewards or punishments to signal action efficacy. However, when such feedback is absent or only partial, we must rely on internally generated signals to evaluate our performance (i.e., metacognition). Yet, very little is known about how humans form such judgements of sensorimotor confidence. Do they monitor their performance? Or do they rely on cues to sensorimotor uncertainty to infer how likely it is they performed well? We investigated motor metacognition in two visuomotor tracking experiments, where participants followed an unpredictably moving dot cloud with a mouse cursor as it followed a random trajectory. Their goal was to infer the underlying target generating the dots, track it for several seconds, and then report their confidence in their tracking as better or worse than their average. In Experiment 1, we manipulated task difficulty with two methods: varying the size of the dot cloud and varying the stability of the targets velocity. In Experiment 2, the stimulus statistics were fixed and duration of the stimulus presentation was varied. We found similar levels of metacognitive sensitivity in all experiments, with the temporal analysis revealing a recency effect, where error later in the trial had a greater influence on the sensorimotor confidence. In sum, these results indicate humans predominantly monitor their tracking performance, albeit inefficiently, to judge sensorimotor confidence. HighlightsO_LIParticipants consciously reflected on their tracking performance with some accuracy C_LIO_LISensorimotor confidence was influenced by recent errors C_LIO_LIExpectations of task difficulty did not play a large role in sensorimotor confidence C_LIO_LIMetacognitive sensitivity of binary confidence judgements on continuous performance can be quantified with standard non-parametric techniques C_LI

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bioRxiv2019

Priors and Payoffs in Confidence Judgments

1Priors and payoffs are known to affect perceptual decision-making, but little is understood about how they influence confidence judgments. For optimal perceptual decision-making, both priors and payoffs should be considered when selecting a response. However, for confidence to reflect the probability of being correct in a perceptual decision, priors should affect confidence but payoffs should not. To experimentally test whether human observers follow this normative behavior, we conducted an orientation-discrimination task with varied priors and payoffs, probing both perceptual and metacognitive decision-making. We then examined the placement of discrimination and confidence criteria according to several plausible Signal Detection Theory models. In the normative model, observers use the optimal discrimination criterion (i.e., the criterion that maximizes expected gain) and confidence criteria that shift with the discrimination criterion that maximizes accuracy (i.e., are not affected by payoffs). No observer was consistent with this model, with the majority exhibiting non-normative confidence behavior. One subset of observers ignored both priors and payoffs for confidence, always fixing the confidence criteria around the neutral discrimination criterion. The other group of observers incorrectly incorporated payoffs into their confidence by always shifting their confidence criteria with the same gains-maximizing criterion used for discrimination. Such metacognitive mistakes could have negative consequences outside the laboratory setting, particularly when priors or payoffs are not matched for all the possible decision alternatives.

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bioRxiv2018

Human online adaptation to changes in prior probability

Optimal sensory decision-making requires the combination of uncertain sensory signals with prior expectations. The effect of prior probability is often described as a shift in the decision criterion. Can observers track sudden changes in probability? To answer this question, we used a change-point detection paradigm that is frequently used to examine behavior in changing environments. In a pair of orientation-categorization tasks, we investigated the effects of changing probabilities on decision-making. In both tasks, category probability was updated using a sample-and-hold procedure. We developed an ideal Bayesian change-point detection model in which the observer marginalizes over both the current run length (i.e., time since last change) and the current category probability. We compared this model to various alternative models that correspond to different strategies - from approximately Bayesian to simple heuristics - that the observers may have adopted to update their beliefs about probabilities. We find that probability is estimated following an exponential averaging model with a bias towards equal priors, consistent with a conservative bias. The mechanism underlying change of decision criterion is a combination of on-line estimation of prior probability and a stable, long-term equal-probability prior, thus operating at two very different timescales.\n\nAuthor summaryWe demonstrate how people learn and adapt to changes to the probability of occurrence of one of two categories on decision-making under uncertainty. The study combined psychophysical behavioral tasks with computational modeling. We used two behavioral tasks: a typical forced-choice categorization task as well as one in which the observer specified the decision criterion to use on each trial before the stimulus was displayed. We formulated an ideal Bayesian change-point detection model and compared it to several alternative models. We found that the data are best fit by a model that estimates category probability based on recently observed exemplars with a bias towards equal probability. Our results suggest that the brain takes multiple relevant time scales into account when setting category expectations.

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