Biology subjects

Medendorp, W. P.

Publications and source records attributed to Medendorp, W. P..

At least 19 recordsLinked to original sources

bioRxiv2026

Stretch-induced muscle responses under threat vs safety

When in a stressful situation, making fast and accurate decisions is crucial. Previous work has shown that sensorimotor decisions can improve under threat. However, it is unclear if these improvements are achieved by improvements in perceptual or motor performance. Here, we present two hypotheses for how threat might influence motor preparation and use muscular stretch reflexes to test both. The task-unspecific hypothesis predicts that threat promotes motor preparation irrespective of the reach target, through tonic upregulation of the short latency stretch reflex. In contrast, the task-specific hypothesis predicts that threat increases sensory processing for a specific reach target, leading to direction-selective up- and down-regulation of the long latency stretch reflex. Participants were asked to reach to one of two targets that appeared shortly before a perturbation eliciting a stretch reflex, they performed this task either under threat of an electric shock or under safe circumstances. Skin conductance and heart rate results show that the threat manipulation significantly increased sympathetic activation, but not parasympathetic activation. Supporting the task-specific hypothesis, the EMG findings demonstrate a direction-selective modulation of the long-latency response of stretch reflexes, starting ~100 ms after perturbation onset. Our results suggest that stress affects action preparation through upregulation of cortical visuomotor circuits.

physiology↗

bioRxiv2026

Task-Dependent Modulation of Feedback Control in Human Steering

We examined whether human steering behavior conforms to optimal feedback control (OFC) principles when driving a vehicle through sequences of upcoming gates varying in width (narrow/wide) relative to the vehicles size, while occasional lateral velocity perturbations elicited corrective steering responses. In 24 participants, three predictions of OFC were tested: (1) greater positional variability when passing wide gates; (2) reduced corrective steering (lower feedback gains) to perturbations for wide compared to narrow gates (minimum intervention); and (3) modulation of feedback gains according to the relative spatial configuration of upcoming gates. Steering data were analyzed in terms of vehicle position and control velocity, the latter representative of feedback gain modulations. Results supported all predictions. When no perturbations occurred, participants showed wider distributions of passing locations through wide gates, consistent with allowing more task-relevant variability. During perturbed trials, feedback gains were lower for wide gates, confirming context-dependent control. When both gate types were center aligned, feedback responses were symmetric, whereas alignment of inner posts produced asymmetric feedback gains, being stronger for outward perturbations in narrow gates. Overall, these findings indicate that participants adapt their feedback control strategies to task-specific spatial constraints, demonstrating flexible optimization of steering control behavior.

neuroscience↗

bioRxiv2025

Distinct prior expectations shape tactile and proprioceptive localization

When a mosquito lands on your finger, swatting it away requires your brain to calculate its location in the external space, which depends on the bodys 3D posture. Two competing hypotheses explain how the brain solves this challenge: the integration hypothesis, where tactile signals are transformed into spatial coordinates by integrating touch and posture information; and the cueing hypothesis, where touch merely cues a location on the body whose position is specified via proprioception. Adjudicating between these hypotheses is nearly impossible without modeling the latent factors underlying somatosensory spatial perception. We fill this gap in the present study. We first formalized each hypothesis from a Bayesian perspective: If touch merely triggers proprioceptive localization (cueing hypothesis), tactile and proprioceptive localization should rely on the same Bayesian computations, with identical prior expectations about the mosquitos spatial location; If they involve distinct Bayesian computational processes (integration hypothesis), distinct prior expectations may shape tactile and proprioceptive localization. To test these predictions, we had nineteen participants localize either proprioceptive or tactile targets on their fingertips. We then fit their data with several Bayesian models of each hypothesis. Models allowing different prior distributions between modalities provided the best fit for most participants, with 17 out of 19 participants showing significantly different prior distributions across modalities. These provide strong computational evidence that tactile and proprioceptive localization rely on distinct computational mechanisms, a conclusion that has important implications for how we understand these everyday behaviors and their neural mechanisms. Author SummaryWhen a mosquito lands on your finger and you swat it away, your brain must solve a challenging problem: determining where the mosquito is in space based on where it touched your skin and where your finger is positioned. Scientists have debated how the brain accomplishes this. One hypothesis proposes that the brain transforms touch signals by combining them with information about body posture--an integration process. An alternative hypothesis suggests that touch simply signals which body part was contacted, and the brain then locates that body part with only proprioception--essentially treating touch as only a cue. While these hypotheses make different predictions, distinguishing between them using behavior alone has proven difficult because the underlying computations remain hidden. We addressed this by having participants locate either touches on their fingertips or the fingertips themselves, then used Bayesian computational modeling to reveal the spatial expectations guiding these judgments. Our models showed that tactile and proprioceptive localization rely on distinct spatial expectations, with 17 of 19 participants showing significantly different patterns. These findings provide computational evidence that localizing touch involves transformations beyond simply locating the body, supporting the integration hypothesis and challenging the idea that touch merely cues body location.

neuroscience↗

bioRxiv2025

A dynamic causal inference framework for perception-action loops

Causal inference, the process of inferring the causes of our sensory input, is central to multisensory perception. While most computational models of causal inference focus on static perceptual tasks with no temporal or motor components, real-world behavior unfolds dynamically and often involves closed-loop control. Here, we introduce and validate a general modeling framework that unifies multisensory causal inference with optimal feedback control by casting the problem as inference and action in a switching linear dynamical system (SLDS). Our framework combines approximate inference over latent causal structures with a mixture-of-controllers approach, in which each controller is optimized for a specific causal model and weighted by the current belief in that model. We show that classical static models of multisensory perception are special cases of our framework, and extend them to dynamic, action-oriented settings where inference and control evolve over time. Using simulations of previously published behavioral tasks, including visuo-vestibular heading discrimination and path integration with interception, we show that the model reproduces key empirical findings, such as S-shaped biases in heading estimation and motor strategies based on inferred object motion. We also demonstrate the versatility of our approach in novel task extensions, including motion in depth, latent switching dynamics, and multi-objective motor control. Together, our results provide a principled, general-purpose computational account of how causal inference and motor behavior interact in dynamic, uncertain environments, offering a bridge between theories of perception and action. Author summaryWhen we interact with the world, our brain constantly combines information from different senses -- like visual and vestibular sensory input - to determine what is happening and guide an appropriate response. However, these signals do not always originate from the same source in the world. For example, a moving object might not match the background movement we feel during self-motion. In such situations, the brain faces the challenge of "causal inference": do these signal arise from a common source or from separate events. Most previous research has studied this problem in simplified, perceptual settings. But in everyday life, we move through the world and make decisions in real time based on noisy and often conflicting sensory input. In this work, we develop and validate a new computational framework that combines causal inference with models of movement control. This approach allows us to simulate more realistic situations where perception and action interact continuously. We show that our model not only reproduces results from earlier experiments but also makes predictions about how people behave in more complex tasks, like intercepting moving targets or navigating uncertain environments. Our framework offers a new way to study how the brain integrates sensory information to guide behavior in the real world.

neuroscience↗

bioRxiv2025

Movement Effort does not alter the Planning Horizon of Sequential Reaching Movements

Everyday tasks often involve multiple reaching movements in a sequence, where the choices made for one movement also affect the conditions for subsequent movements. Previous research indicates that humans are capable of planning ahead to optimize such sequences. Here, we ask whether increasing the resistance to movement prompts participants to plan even further ahead to reduce overall movement effort. Participants (n=28) were shown 14 targets that varied in size, value and location, and were instructed to accumulate as many points as possible. To collect each target, they reached while holding the handle of a robotic manipandulum that applied a resistive force. We analyzed their target choices using a planning model that takes into account the size, value and distance of several future targets. We expected that, as resistance - and therefore the effort required to move between two targets - increased, participants would plan further ahead to minimize total movement distance. Results show that participants typically planned 2-4 targets ahead. However, increasing resistance did not significantly affect the planning horizon. We conclude that movement effort is not a primary constraint on the planning horizon in sequential reaching movements. NEW AND NOTEWORTHYHumans are capable of planning ahead in sequential reaching movements, but whether they adjust their planning horizon according to task demands is unknown. To manipulate task demands, we increased movement effort during a free target collection task. This makes planning more beneficial. However, we found no adjustment in planning horizon, suggesting that movement effort might not be a critical factor for planning in sequential reaching movements.

neuroscience↗

bioRxiv2025

Explaining attractive and repulsive biases in the subjective visual vertical

Perception of gravity can be assessed by measuring the subjective visual vertical (SVV), the visually indicated spatial direction that appears earth-vertical to an observer. When the SVV is measured in darkness while the observer is roll-tilted, it shows substantial biases. At tilts larger than 45{degrees}, the bias is attractive, that is, the visual indicator appears vertical when rotated toward the observer. At smaller tilts, however, a repulsive bias is observed. The attractive bias has been explained within the Bayesian framework as the effect of a prior for upright posture. The repulsive bias has so far been considered anti-Bayesian, suboptimal, or as the result of uncompensated ocular counterroll. Here we show that both biases can be explained within a purely Bayesian model. More specifically, the repulsive bias at small roll-tilts is a consequence of the known tilt-dependent variability of the SVV, which is hypothesized to reflect different levels of sensory noise of the otolith organs. We thus provide a solution to a century-old question of why there is a repulsive bias in vertical perception.

neuroscience↗

bioRxiv2025

Does stimulus order affect central tendency and serial dependence in vestibular path integration?

The reproduction of a perceived stimulus, such as a distance or a duration, is often influenced by two biases. Central tendency indicates that reproductions are biased toward the mean of the stimulus distribution. Serial dependence reflects that the reproduction of the current stimulus is influenced by the previous stimulus. Although these biases are well-documented, their origins remain to be determined. Studies on duration reproduction suggest that autocorrelation within a stimulus sequence may play a role. In this study, we explored whether the level of autocorrelation in a stimulus sequence affects central tendency and serial dependence in vestibular path integration. Participants (n = 24) performed a vestibular distance reproduction task in total darkness by actively replicating a passively moved stimulus distance with a linear motion platform. We compared two conditions: a high-autocorrelation condition, where stimulus distances followed a random walk, and a no-autocorrelation condition, where the same distances were presented in a randomly shuffled order. We quantified both biases using two approaches: separate simple linear regressions and a joint multiple linear regression model that accounts for the autocorrelation in the stimulus sequence. Simple linear regressions revealed that central tendency was weaker and serial dependence reversed in the high-autocorrelation condition compared to the no-autocorrelation condition. However, these differences were no longer observed in the multiple linear regression analysis, indicating that these biases were independent of the specific stimulus sequence protocol. We conclude that these perceptual biases in vestibular path integration persist regardless of stimulus autocorrelation, suggesting that they reflect robust strategies of the brain to process vestibular information in self-motion perception. Author summaryHow are we able to successfully navigate our surroundings? An essential part of navigation is distance estimation based on self-motion signals. We previously found that distance reproductions based on vestibular self-motion signals were affected by stimulus history. Reproductions showed a central tendency toward the mean of the stimulus distribution and an attractive serial dependence toward the immediately preceding stimulus distance. The stimulus distances were presented in a low-autocorrelation, randomized order. Here we ask whether reproductions show the same central tendency and serial dependence when consecutive stimulus distances are similar (i.e., in a high-autocorrelation, random-walk order). Participants performed a distance reproduction task in the dark: a linear motion platform first passively moved the participant over a stimulus distance, after which they actively reproduced this distance by steering the platform back to the estimated start position. We found that the reproductions showed similar central tendency and attractive serial dependence in both a no- and high-autocorrelation condition, but only if the analysis accounted for the covariation of the two effects in the high-autocorrelation condition. In conclusion, our findings indicate that central tendency and serial dependence of vestibular distance reproductions are not a result of the stimulus sequence protocol, but have neurocognitive origins.

neuroscience↗

bioRxiv2025

The spatial coding of touch is defined in intrinsic, limb-specific coordinates: an EEG study

The brain localizes touch in space by integrating tactile and proprioceptive signals, a process known as tactile remapping. While it is often assumed that the remapped touch is encoded in an extrinsic, limb-independent reference frame, an alternative view proposes that touch may instead be represented within an intrinsic, limb-specific coordinate system. To test these hypotheses, we used electroencephalography (EEG) and a novel tactile stimulation paradigm in which participants received touch on their hands positioned at various locations relative to the body. Previous findings suggest that neural activity in primate sensorimotor and parietal regions monotonically encodes limb position. We therefore analyzed amplitude gradients in somatosensory evoked potentials (SEPs) to test predictions from each coding scheme. If touch is coded extrinsically, neural gradients should reflect changes of the external stimulus location, regardless of the limb. If coded intrinsically, gradients should be tied to the position of each limb and mirror each other between hands. Both univariate and multivariate EEG analyses found no evidence for extrinsic coding. Instead, we observed neural signatures of limb-specific, intrinsic spatial codes, the earliest emerging about 160 ms after touch in centro-parietal regions, later shifting to fronto-temporal and parieto-occipital areas. Furthermore, a population-based neural network model of tactile remapping successfully reproduced the observed gradient patterns. These results show that the human brain localizes touch using an intrinsic, limb-specific spatial code, challenging the dominant assumption of extrinsic encoding in tactile remapping.

neuroscience↗

bioRxiv2025

Gaze-centered spatial coding of touch on a hand-held tool

Humans possess the remarkable ability to project tactile sensations outside their body and onto a hand-held tool that they are using. Despite nearly a century of research, the computations underlying this projection have not been adequately addressed. In the present study, we employed model-driven psychophysics to fill this gap. We hypothesized that tool-based sensory projection involves the remapping of touch from sensory feedback in the hand into an egocentric coordinate system. We first formalized the computational steps underlying tactile remapping. We designed a novel tool-sensing experiment that allowed us to rigorously test this model. In this task, participants contacted an object with a hand-held rod and then judged whether the object was above or below where they were currently looking. This comparison would only be possible if touch on the tool was projected outside the hand. Crucially, both object location and gaze position varied independently, allowing us to characterize the hand-to-space-to-gaze remapping process. Model-based curve fitting provided strong evidence that all participants in our task projected touch outside their body and into gazecentered coordinates. Crucially, the resolution of this projection was similar to what has been found for touch on the body. These findings provide the first step towards characterizing the computations underlying the spatial projection of touch on external objects, highlighting the incredible versatility of the sensorimotor system.

neuroscience↗

bioRxiv2025

Rapid modulation of choice behavior by ultrasound on the human frontal eye fields

A fundamental challenge in neuroscience is establishing causal brain-function relationships with spatial and temporal precision. Transcranial ultrasonic stimulation (TUS) offers a unique opportunity to modulate deep brain structures non-invasively with high spatial resolution, but temporally precise effects and their neurophysiological foundations have yet to be demonstrated in humans. Here, we develop a temporally precise TUS protocol targeting the frontal eye fields (FEFs) -- a well-characterized circuit critical for saccadic eye movements. We demonstrate that TUS induces robust excitatory behavioral effects. Importantly, individual differences in baseline GABAergic inhibitory tone predict response magnitude. These findings establish TUS as a reliable tool for chronometric circuit interrogation and highlight the importance of neurophysiological state in neuromodulation. This work bridges human and animal research, advancing targeted TUS applications in neuroscience and clinical settings. HighlightsO_LIFocused ultrasound modulates saccades with high spatial and temporal precision C_LIO_LIInhibitory circuits in the frontal eye fields shape choice computations C_LIO_LIGABA levels predict individual variability in ultrasound-induced behavioral changes C_LIO_LIUltrasound can be used to probe fast neural dynamics and individual differences C_LI

neuroscience↗

bioRxiv2024

Online interference of declarative memory on fast and slow adaptive processes in force field motor learning

Error-based motor adaptation is currently understood as a dual-rate process involving a fast adaptive process that learns quickly but also decays rapidly and a slow process that learns slowly but has good retention. While the fast process is typically categorized as procedural learning, recent evidence suggests that it relies on the declarative memory system. To test this hypothesis, we investigated in what manner a declarative memory task interferes with two processes that supposedly underly force field adaptation in reaching. This declarative memory task, which involved learning of a list of words, was assessed through either recognition or recall, and was compared to a non-declarative, vowel counting task, using a within-subject design (n=32). We employed a Bayesian hierarchical dual-rate process model to capture the observed force compensation across trials, expecting that the parameters of the fast process would be affected by the declarative memory task. We examined the 95% highest density interval of the posterior distribution of the difference between the experimental and control condition for each parameter. While most parameters remained unaffected by the declarative memory task, the retention rate of the fast process showed a hint of reduction, suggesting a complex interplay between declarative memory and ongoing motor adaptation processes.

neuroscience↗

bioRxiv2024

Visuoinertial and visual feedback in online steering control

Multisensory integration has primarily been studied in static environments, where optimal integration relies on the precision of the respective sensory modalities. However, in numerous situations, sensory information is dynamic and changes over time, due to changes in our bodily state and the surrounding environment. Given that different sensory modalities have different delays, this suggests that optimal integration may not solely depend on sensory precision but may also be affected by the delays associated with each sensory system. To investigate this hypothesis, participants (n = 22, 16 female) engaged in a continuous steering task. Participants sat on a motion platform facing a screen that displayed a cartoonish traffic scene, featuring a car traveling along a road. In the visuoinertial condition, where vestibular and somatosensory feedback were available, they were tasked with counteracting an external multi-frequency perturbation signal, which laterally perturbed the platform and the car, such that the car was kept within the center of the road. In the visual condition, the visual car was perturbed, while the motion platform remained stationary. We show that participants compensate better for the perturbation in the visuoinertial than the visual condition, particularly in the high frequency range of the perturbation. Using computational modelling, we demonstrate that this enhanced performance is partially due to the shorter delay of the vestibular modality. In this condition, participants rely more on the vestibular information, which is less delayed than the more precise but longer delayed, visual information. Author summaryNavigating the world effectively requires the continuous integration of sensory information related to our self-motion, forming a cohesive representation of our current location and direction. Although studies on multisensory integration indicate that sensory inputs are combined optimally based on their precision, these findings have largely been derived from static experimental settings. In real-life situations, the sensory environment changes continuously, as does the state of our body. In such scenarios, how are sensory inputs combined? We developed an experimental paradigm where participants were tasked with controlling a simple vehicle while counteracting a time-varying perturbation signal. To assess the role of different sensory inputs we manipulated whether visual and inertial (primarily vestibular) cues were available or solely visual cues. Our results show that the presence of both visual and inertial cues significantly improved task performance. Modeling suggests this improvement is likely due to the shorter delay associated with the vestibular system compared to the visual system. Collectively, our results suggest that sensory precision alone is insufficient for effective state estimation and control in naturalistic scenarios, where accounting for the different delays of the sensory systems is critical for optimal task performance.

neuroscience↗

bioRxiv2024

Bayesian inference in arm posture perception

To configure our limbs in space the brain must compute their position based on sensory information provided by mechanoreceptors in the skin, muscles, and joints. Because this information is corrupted by noise, the brain is thought to process it probabilistically, and integrate it with prior belief about arm posture, following Bayes rule. Here, we combined computational modeling with behavioral experimentation to test this hypothesis. The model conceives the perception of arm posture as the combination of a probabilistic kinematic chain composed by the shoulder, elbow, and wrist angles, compromised with additive Gaussian noise, with a Gaussian prior about these joint angles. We tested whether the model explains errors in a VR-based posture-matching task better than a model that assumes a uniform prior. Human participants (N=20) were required to align their unseen right arm to a target posture, presented as a visual configuration of the arm in the horizontal plane. Results show idiosyncratic biases in how participants matched their unseen arm to the target posture. We used maximum likelihood estimation to fit the Bayesian model to these observations and retrieve key parameters including the prior means and its variance-covariance structure. The Bayesian model including a Gaussian prior explained the response biases and variance much better than a model with a uniform prior. The prior varied across participants, consistent with the idiosyncrasies in arm posture perception, and in alignment with previous behavioral research. Our work clarifies the biases in arm posture perception within a new perspective on the nature of proprioceptive computations. New & NoteworthyWe modeled the perception of arm posture as a Bayesian computation. A VR posture-matching task was used to empirically test this Bayesian model. The Bayesian model including a non-uniform postural prior well explained individual participants biases in arm posture perception.

neuroscience↗

bioRxiv2024

Central tendency and serial dependence in vestibular path integration

Path integration, the process of updating ones position using successive self-motion signals, has previously been studied using visual distance reproduction tasks in which optic flow patterns provide information about traveled distance. These studies have reported that reproduced distances show two types of systematic biases: central tendency and serial dependence. In the present study, we investigated whether these biases are also present in vestibular path integration. Participants were seated on a linear motion platform and performed a distance reproduction task in total darkness. The platform first passively moved the participant a pre-defined stimulus distance which they then actively reproduced by steering the platform back the same distance. Stimulus distances were sampled from short- and long-distance probability distributions and presented in either a randomized order or in separate blocks to study the effect of presentation context. Similar to the effects observed in visual path integration, we found that reproduced distances showed an overall positive central tendency effect as well as a positive, attractive serial dependence effect. Furthermore, reproduction behavior was affected by presentation context. These results were mostly consistent with predictions of a Bayesian Kalman-filter model, originally proposed for visual path integration. New & NoteworthyDistance reproduction tasks based on visual information about the traveled distance have shown that reproductions are biased by central tendency and serial dependence effects. Here, we show that distance reproductions based on vestibular signals show similar biases and that the reproductions are affected by the presentation order of the stimulus distances.

neuroscience↗

bioRxiv2024

Vestibular-derived internal models in active self-motion estimation

Self-motion estimation is thought to depend on sensory information as well as on sensory predictions derived from motor feedback. In driving, the vestibular afference can in principle be predicted based on the steering motor commands if an accurate internal model of the steering dynamics is available. Here, we used a closed-loop steering experiment to examine whether participants can build such an internal model of the steering dynamics. Participants steered a motion platform on which they were seated to align their body with a memorized visual target. We varied the gain between the steering wheel angle and the velocity of the motion platform across trials in three different ways: unpredictable (white noise), moderately predictable (random walk), or highly predictable (constant gain). We examined whether participants took the across-trial predictability of the gain into account to control their steering (internal model hypothesis), or whether they simply integrated the vestibular feedback over time to estimate their travelled distance (path integration hypothesis). Results from a trial series regression analysis show that participants took the gain of the previous trial into account more when it followed a random walk across trials than when it varied unpredictably across trials. Furthermore, on interleaved trials with a large jump in the gain, participants made fast corrective responses, irrespective of gain predictability, suggesting they also rely on vestibular feedback. These findings suggest that the brain can construct an internal model of the steering dynamics to predict the vestibular reafference in driving and self-motion estimation.

neuroscience↗

bioRxiv2024

Does early-stage Alzheimer's disease affect the dynamics of motor adaptation?

Alzheimers disease (AD) is characterized by an initial decline in declarative memory, while non-declarative memory processing remains relatively intact. Error-based motor adaptation is traditionally seen as a form of non-declarative memory, but recent findings suggest that it involves both fast, declarative and slow, non-declarative adaptive processes. If the declarative memory system shares resources with the fast process in motor adaptation, it can be hypothesized that the fast, but not the slow, process is disturbed in AD patients. To test this, we studied 20 early-stage AD patients and 21 age-matched controls of both sexes using a reach adaptation paradigm that relies on spontaneous recovery after sequential exposure to opposing force fields. Adaptation was measured using error clamps and expressed as an adaptation index (AI). Although patients with AD showed slightly lower adaptation to the force field than the controls, both groups demonstrated effects of spontaneous recovery. The time course of the AI was fitted by a hierarchical Bayesian two-state model in which each dynamic state is characterized by a retention and learning rate. Compared to controls, the retention rate of the fast process was the only parameter that was significantly different (lower) in the AD patients, confirming that the memory of the declarative, fast process is disturbed by AD. The slow adaptive process was virtually unaffected. Since the slow process learns only weakly from error, our results provide neurocomputational evidence for the clinical practice of errorless learning of everyday tasks in people with dementia.

neuroscience↗

bioRxiv2023

Biases in hand perception are driven by somatosensory computations, not a distorted hand model

To sense and interact with objects in the environment, we effortlessly configure our fingertips at desired locations. It is therefore reasonable to assume the underlying control mechanisms rely on accurate knowledge about the structure and spatial dimensions of our hand and fingers. This intuition, however, is challenged by years of research showing drastic biases in the perception of finger geometry.1-5 This perceptual bias has been taken as evidence that the brains internal representation of the bodys geometry is distorted,6 leading to an apparent paradox with the skillfulness of our actions.7 Here, we propose an alternative explanation of the biases in hand perception--They are the result of the Bayesian integration of noisy, but unbiased somatosensory signals about finger geometry and posture. To address this hypothesis, we combined Bayesian reverse-engineering with behavioral experimentation on joint and fingertip localization of the index finger. We modelled the Bayesian integration either in sensory or in space-based coordinates, showing that the latter model variant led to biases in finger perception despite accurate representation of finger length. Behavioral measures of joint and fingertip localization responses showed similar biases, which were well-fitted by the space-based but not the sensory-based model variant. The space-based model variant also outperformed a distorted-hand model with built-in geometric biases. In total, our results suggest that perceptual distortions of finger geometry do not reflect a distorted hand model but originate from near-optimal Bayesian inference on somatosensory signals.

neuroscience↗

bioRxiv2022

Dynamic spatial coding in parietal cortex mediates hand movement planning towards touch

Movements towards touch on the body require integrating tactile location and body posture information. Tactile processing and movement planning both rely on posterior parietal cortex (PPC) but their interplay is not understood. Here, human participants received tactile stimuli on their crossed and uncrossed feet, dissociating stimulus location relative to anatomy versus external space. Participants pointed to the touch or the equivalent location on the other foot, which dissociates sensory and motor locations. Multi-voxel pattern analysis of concurrently recorded fMRI signals revealed that tactile location was coded anatomically in anterior PPC but spatially in posterior PPC during sensory processing. After movement instructions were specified, PPC exclusively represented the movement goal in space, in regions associated with visuo-motor planning and with regional overlap for sensory, rule-related, and movement coding. Thus, PPC flexibly updates its spatial codes to accommodate rule-based transformation of sensory input to generate movement to environment and own body alike.

neuroscience↗