Biology subjects

Blohm, G.

Publications and source records attributed to Blohm, G..

9 recordsLinked to original sources

bioRxiv2018

Mis-perception of motion in depth originates from an incomplete transformation of retinal signals

Depth perception requires the use of an internal model of the eye-head geometry to infer distance from binocular retinal images and extraretinal 3D eye-head information, particularly ocular vergence. Similarly for motion in depth perception, gaze angle is required to correctly interpret the spatial direction of motion from retinal images; however, it is unknown whether the brain can make adequate use of extraretinal version and vergence information to correctly interpret binocular retinal motion for spatial motion in depth perception. Here, we tested this by asking participants to reproduce the perceived spatial trajectory of an isolated point stimulus moving on different horizontal-depth paths either peri-foveally or peripherally while participants gaze was oriented at different vergence and version angles. We found large systematic errors in the perceived motion trajectory that reflected an intermediate reference frame between a purely retinal interpretation of binocular retinal motion (ignoring vergence and version) and the spatially correct motion. A simple geometric model could capture the behavior well, revealing that participants tended to underestimate their version by as much as 17%, overestimate their vergence by as much as 22%, and underestimate the overall change in retinal disparity by as much as 64%. Since such large perceptual errors are not observed in everyday viewing, we suggest that other monocular and/or contextual cues are required for accurate real-world motion in depth perception.

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bioRxiv2018

Confidence in predicted position error explains saccadic decisions during pursuit

A fundamental problem in motor control is the coordination of complementary movement types to achieve a common goal. As a common example, humans view moving objects through coordinated pursuit and saccadic eye movements. Pursuit is initiated and continuously controlled by retinal image velocity. During pursuit, eye position may lag behind the target. This can be compensated by the discrete execution of a catch-up saccade. The decision to trigger a saccade is influenced by both position and velocity errors and the timing of saccades can be highly variable. The observed distributions of saccade occurrence and trigger time remain poorly understood and this decision process remains imprecisely quantified. Here we propose a predictive, probabilistic model explaining the decision to trigger saccades during pursuit to foveate moving targets. In this model, expected position error and its associated uncertainty are predicted through Bayesian inference across noisy, delayed sensory observations (Kalman filtering). This probabilistic prediction is used to estimate the confidence that a saccade is needed (quantified through log-probability ratio), triggering a saccade upon accumulating to a fixed threshold. The model qualitatively explains behavioural observations on the probability of occurrence and trigger time distributions of saccades during pursuit over a range of target motion trajectories. Furthermore, this model makes novel predictions about the influence of sensory uncertainty and target motion parameters on saccade decisions. We suggest that this predictive, confidence-based decision making strategy represents a fundamental principle for the probabilistic neural control of coordinated movements.\n\nNew & NoteworthyThis is the first stochastic dynamical systems model of pursuit-saccade coordination accounting for noise and delays in the sensorimotor system. The model uses Bayesian inference to predictively estimate visual motion, triggering saccades when confidence in predicted position error accumulates to a threshold. This model explains saccade probability and trigger time distributions across target trajectories and makes novel predictions about the influence of sensory uncertainty in saccade decisions during pursuit.

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bioRxiv2018

Disinhibition as a canonical neural mechanism for flexible behavior

Flexibility is a hallmark of human and animal behavior, but the context-dependent neural computations that generate flexible behavior are poorly understood. Here, we use a biophysically-based cortical network model to explore the hypothesis that vasoactive intestinal polypeptide (VIP) expressing inhibitory interneurons control local circuit dynamics by targeting other classes of inhibitory interneuron, supporting context-dependent computations. Depending on the strength of this disinhibition (simulating VIP activity), network dynamics support multiple-item working memory (WM, strong disinhibition) or decision making (DM, weak disinhibition). Within these regimes, disinhibition controls WM capacity and speedaccuracy-trade-off in choice behavior. Our findings suggest that long-range trans-cortical VIP-mediated disinhibition is a canonical neural mechanism for the top-down control of flexible behavior.

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bioRxiv2018

Neuromagnetic signatures of the spatiotemporal transformation for reaching

Movement planning involves transforming the sensory goal representation into a command in motor coordinates. Surprisingly, the real-time dynamics of sensorimotor transformations at the whole brain level remain unknown, in part due to the spatiotemporal limitations of fMRI and neurophysiological recordings. Here, we used magnetoencephalography (MEG) during pro-/anti-wrist pointing to determine (1) the cortical areas involved in transforming visual signals into appropriate hand motor commands, and (2) how this transformation occurs in real time, both within and across the regions involved. We computed sensory, motor, and sensorimotor indices in 16 bilateral brain regions for direction coding based on hemispherically lateralized de/synchronization in the (7-15Hz) and {beta} (15-35Hz) bands. We found a visuomotor progression, from pure sensory codes in early occipital-parietal areas, to a temporal transition from sensory to motor coding in the majority of parietal-frontal sensorimotor areas, to a pure motor code, in both the and {beta} bands. Further, the timing of these transformations revealed a top-down pro/anti cue influence that propagated backwards from frontal through posterior cortical areas. These data directly demonstrate a progressive, real-time transformation both within and across the entire occipital-parietal-frontal network that follows specific rules of spatial distribution and temporal order.

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bioRxiv2017

Effector-dependent response deterioration by stochastic transformations reveals mixed reference frames for decisions

Recent psychophysical and modeling studies have revealed that sensorimotor reference frame transformations (RFTs) add variability to motor output by decreasing the fidelity of sensory signals. How RFT stochasticity affects the sensory input underlying perceptual decisions, if at all, is unknown. To investigate this, we asked participants to perform a simple two-alternative motion direction discrimination task under varying conditions of head roll and/or stimulus rotation while responding either with a saccade or button press, allowing us to attribute behavioral effects to eye-, head- and shoulder-centered reference frames. We observed a rotation-induced, increase in reaction time and decrease in accuracy, indicating a degradation of motion evidence commensurate with a decrease in motion strength. Inter-participant differences in performance were best explained by a continuum of eye-head-shoulder representations of accumulated decision evidence, with eye- and shoulder-centered preferences during saccades and button presses, respectively. We argue that perceptual decision making and stochastic RFTs are inseparable, consistent with electrophysiological recordings in neural areas thought to be encoding sensorimotor signals for perceptual decisions. Furthermore, transformational stochasticity appears to be a generalized phenomenon, applicable throughout the perceptual and motor systems. We show for the first time that, by simply rolling ones head, perceptual decision making is impaired in a way that is captured by stochastic RFTs.\n\nSignificance statementWhen exploring our environment, we typically maintain upright head orientations, often even despite increased energy expenditure. One possible explanation for this apparently suboptimal behavior might come from the finding that sensorimotor transformations, required for generating geometrically-correct behavior, add signal- dependent variability (stochasticity) to perception and action. Here, we explore the functional interaction of stochastic transformations and perceptual decisions by rolling the head and/or stimulus during a motion direction discrimination task. We find that, during visuomotor rotations, perceptual decisions are significantly impaired in both speed and accuracy in a way that is captured by stochastic transformations. Thus, our findings suggest that keeping ones head aligned with gravity is in fact ideal for making perceptual judgments about our environment.

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bioRxiv2017

Predictive orientation remapping maintains a stable retinal percept

Despite motion on the retina with every saccade, we perceive the world as stable. But whether this stability is a result of neurons constructing a spatial map or continually remapping a retinal representation is unclear. Previous work has focused on the perceptual consequences of shifts in the horizontal and vertical dimensions, but torsion is another key component in ocular orienting that - unlike horizontal and vertical movements - produces a natural misalignment between spatial and retinal coordinates. Here we took advantage of oblique eye orientation-induced retinal torsion to examine perisaccadic orientation perception. We found that orientation perception was largely predicted by the retinal image throughout each trial. Surprisingly however, we observed a significant presaccadic remapping of the percept consistent with maintaining a stable (but spatially inaccurate) retinotopic perception throughout the saccade. These findings strongly suggest that our seamless perceptual stability relies on retinotopic signals that are remapped with each saccade.

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bioRxiv2017

Neck muscle spindle noise biases reaches in a multi-sensory integration task

Reference frame Transformations (RFTs) are crucial components of sensorimotor transformations in the brain. Stochasticity in RFTs has been suggested to add noise to the transformed signal due to variability in transformation parameter estimates (e.g. angle) as well as the stochastic nature of computations in spiking networks of neurons. Here, we varied the RFT angle together with the associated variability and evaluated the behavioral impact in a reaching task that required variability-dependent visual-proprioceptive multi-sensory integration. Crucially, reaches were performed with the head either straight or rolled 30deg to either shoulder and we also applied neck loads of 0 or 1.8kg (left or right) in a 3x3 design, resulting in different combinations of estimated head roll angle magnitude and variance required in RFTs. A novel 3D stochastic model of multi-sensory integration across reference frames was fitted to the data and captured our main behavioral findings: (1) neck load biased head angle estimation across all head roll orientations resulting in systematic shifts in reach errors; (2) Increased neck muscle tone led to increased reach variability, due to signal-dependent noise; (3) both head roll and neck load created larger angular errors in reaches to visual targets away from the body compared to reaches toward the body. These results show that noise in muscle spindles and stochasticity in general have a tangible effect on RFTs underlying reach planning. Since RFTs are omnipresent in the brain, our results could have implication for processes as diverse as motor control, decision making, posture / balance control, and perception.\n\nNew & NoteworthyWe show that increasing neck muscle tone systematically biases reach movements. A novel 3D multisensory integration across reference frames model captures the data well and provides evidence that the brain must have online knowledge of full body geometry together with the associated variability to accurately plan reach movements.

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bioRxiv2017

Hierarchical recruitment of competition alleviates working memory overload in a fronto-parietal model

The storage limitations of visual working memory have been the subject of intense research interest for several decades, but few studies have systematically investigated the dependence of these limitations on memory load that exceeds our retention abilities. Under this real-world scenario, performance typically declines beyond a critical load among low-performing subjects, a phenomenon known as working memory overload. We used a fronto-parietal cortical model to test the hypothesis that high-performing subjects select a manageable number of items for storage, thereby avoiding overload. The model accounts for behavioural and electrophysiological data from high-performing subjects in a parameter regime where competitive encoding in its prefrontal network selects items for storage, inter-areal projections sustain their representations after stimulus offset, and weak dynamics in its parietal network limit their mutual interference. Violation of these principles accounts for these data among low-performing subjects, implying that poor visual working memory performance reflects poor control over fronto-parietal circuitry, and making testable predictions for experiments.

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bioRxiv2017

Weighted integration of short term memory and sensory signals in the oculomotor system

Oculomotor behaviors integrate sensory and prior information to overcome sensory-motor delays and noise. After much debate about this process, reliability-based integration has recently been proposed and several models of smooth pursuit now include recurrent Bayesian integration or Kalman filtering. However, there is a lack of behavioral evidence supporting these theoretical predictions.\n\nHere, we independently manipulated the reliability of visual and prior information in a smooth pursuit task. Our results show that both smooth pursuit eye velocity and catch-up saccade amplitude were modulated by visual and prior information reliability.\n\nWe interpret these findings as the continuous reliability-based integration of a short-term memory of target motion with visual information, which support modelling work. Furthermore, we suggest that saccadic and pursuit systems share this short-term memory. We propose that this short-term memory of target motion is quickly built and continuously updated, and constitutes a general building-block present in all sensorimotor systems.

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