Biology subjects

Blohm, G.

Publications and source records attributed to Blohm, G..

At least 19 recordsLinked to original sources

bioRxiv2026

Asymmetric Adaptation of Catch-up Saccades with Artificial Central Scotomas

In fully-sighted individuals, pursuit and saccadic eye movements work together to foveate moving targets; pursuit attempts to match target velocity, while catch-up saccades re-align the fovea to the target if it deviates during pursuit. Although saccade-pursuit interactions are well understood in healthy individuals, much less is known about how these mechanisms adapt in the presence of central vision loss. Here, we simulated central vision loss in healthy young adults to examine plasticity in saccade-pursuit mechanisms and investigated whether and how catch-up saccades adapted over five days of visual tracking. Twenty-five fully sighted participants performed a task in which they pursued a moving target that stepped position randomly (designed to elicit catch-up saccades) while viewing with a gaze-contingent central scotoma. The scotoma was shaped like a bitten cookie to encourage use of a specific preferred retinal locus (PRL) corresponding to the peripheral location with the highest acuity. By the end of the five days of repetition, most participants showed catch-up saccade endpoints shifted towards the PRL rather than the fovea. On average, endpoints shifted 0.5 deg towards the PRL between days 1 and 5 (range=0.3-1.5 deg), with significant shifts in 13 of the 25 participants. Adaptation was asymmetric; shifts were largest when the target moved in the direction opposite the scotoma bite and smallest when it moved towards it. In summary, we observed adaptation of saccade-pursuit interactive mechanisms through the re-referencing of catch-up saccades from the fovea to PRL. These results provide a promising avenue for rehabilitation in central vision loss aimed at improving eye movements and encouraging PRL use. Ultimately, such an approach may enhance residual visual function and quality of life.

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bioRxiv2024

MEG signals reveal arm posture coding and intrinsic movement plans in parietofrontal cortex

Movement planning processes must account for body posture to accurately convert sensory signals into movement plans. While movement plans can be computed relative to the world (extrinsic), intrinsic muscle commands tuned for current limb posture are ultimately needed to execute spatially accurate movements. The whole-brain topology and dynamics of this process are largely unknown. Here, we use high spatiotemporal resolution magnetoencephalography (MEG) in humans combined with a Pro-/Anti-wrist pointing task with 2 opposing forearm postures to investigate this question. First, we computed cortical source activity in 16 previously identified bilateral cortical areas (Alikhanian, et al., Frontiers in Neuroscience 2013). We then contrasted oscillatory activity related to opposing wrist postures to find posture coding and test when and where extrinsic and intrinsic motor codes occurred. We found a distinct pair of overlapping networks coding for posture (predominantly in {gamma} band) vs. posture-specific movement plans ( and {beta}). Some areas (e.g., pIPS) only showed extrinsic motor coding, and others (e.g., AG) only showed intrinsic coding, but the majority showed both types of codes. In the latter case, intrinsic codes appeared slightly before extrinsic codes and persisted in parallel across different cortical areas. These findings are consistent with two cortical networks for 1) direct feed-forward sensorimotor transformations to intrinsic muscle coordinates (for rapid control) and 2) computations of extrinsic spatial coordinates, possibly for use in higher-level aspects of visually-guided action, such as spatial updating and internal performance monitoring. Significance statement / author summaryIt is thought that the brain incorporates posture into extrinsic spatial codes to compute intrinsic (muscle-centered) motor commands, but the whole-brain temporal dynamics of this process is unknown. Here we employed human magneto-encephalography (MEG) to track this process across 16 bilateral cortical sites. We identified two, largely overlapping subnetworks for posture-dependent intrinsic codes, and extrinsic spatial coding. Surprisingly, the direct transformation from sensorimotor coordinates to intrinsic commands preceded the appearance of extrinsic codes, suggesting that extrinsic motor codes are derived from intrinsic codes for higher-level cognitive purposes.

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bioRxiv2024

Multisensory integration across reference frames with additive feed-forward networks

The integration of multiple sensory inputs is essential for human perception and action in uncertain environments. This process includes reference frame transformations as different sensory signals are encoded in different coordinate systems. Studies have shown multisensory integration in humans is consistent with Bayesian optimal inference. However, neural mechanisms underlying this process are still debated. Different population coding models have been proposed to implement probabilistic inference. This includes a recent suggestion that explicit divisive normalization accounts for empirical principles of multisensory integration. However, whether and how divisive operations are implemented in the brain is not well understood. Indeed, all existing models suffer from the curse of dimensionality and thus fail to scale to real-world problems. Here, we propose an alternative model for multisensory integration that approximates Bayesian inference: a multilayer-feedforward neural network of multisensory integration (MSI) across different reference frames trained on the analytical Bayesian solution. This model displays all empirical principles of multisensory integration and produces similar behavior to that reported in Ventral intraparietal (VIP) neurons in the brain. The model achieved this without a neatly organized and regular connectivity structure between contributing neurons, such as required by explicit divisive normalization. Overall, we show that simple feedforward networks of purely additive units can approximate optimal inference across different reference frames through parallel computing principles. This suggests that it is not necessary for the brain to use explicit divisive normalization to achieve multisensory integration. Significance StatementThis research presents an alternative model to divisive normalization models of multisensory integration in the brain. Our study demonstrates that a feed-forward neural network can achieve optimal multisensory integration across different reference frames without explicitly implementing divisive operations, challenging the long-held assumption that such operations are necessary for multisensory integration. The model displays all the empirical principles of multisensory integration, producing similar behavior to that reported in Ventral intraparietal (VIP) neurons in the brain. This work offers profound insights into the putative neural computations underlying multisensory processing.

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bioRxiv2024

Intra-individual variability in the effects of transcranial directcurrent stimulation on free choice saccade behaviour

Transcranial direct current stimulation (tDCS) is used as a tool to causally influence neural activity in humans non-invasively. Although most studies recruit a large number of participants in order to uncover population-level effects, growing evidence suggests that tDCS may be expected to induce different effects in different individuals, leading to large inter-individual variability and confounds in population-level testing. Additionally, variability may arise from intra-individual differences and confounds that are difficult to assess in studies with limited to no re-testing. Here, we performed 10 sessions of tDCS each on 5 human participants performing a free choice saccade task while neural activity was measured via EEG. Participants first underwent functional MRI to localize the human right frontal eye field (rFEF) homologue. An HD-tDCS montage was then used to focally target rFEF based on individual MRI localizations, alternating the polarity between anodal or cathodal current over repeated sessions during a 5 week period (twice weekly). On stimulation days, participants performed a free choice task prior to and after administration of tDCS while EEG activity was recorded. To quantify the likelihood that tDCS induced a causal effect on behaviour and neural activity across different levels of analysis, we developed a multilevel causal inference method based on permutation testing of a quasi-experiment (difference-in-differences). We then used this method to assess the likelihood of a causal effect at different levels of abstraction: group-level, participant-level, and paired-session level. At the group-level, we found evidence for an influence of tDCS on choice reaction times, which followed a reaction-time dependent change in EEG activity, and on how choices depended on previous trials. However, individuals showed heterogeneous effects. Further, analysis of paired-session variability often belied the pooled individual effect, suggesting that different sessions of tDCS may have produced markedly different effects in the same participants. In light of this, we discuss potential causes of this variability, and the counterfactuals that should be considered when making data-driven inferences about the effects of tDCS. Author SummaryDeveloping reliable interventions on human neural activity is important for establishing causal relationships in basic research and developing therapeutics for pathological brain states. Transcranial direct current stimulation is a promising technique to intervene on neural activity safely in humans, but it is poorly understood if tDCS reliably impacts brain and behaviour in the same way across sessions. We performed an extensive test-retest study on tDCS in humans, and developed statistical methods to assess variability across sessions. Our results provide strong evidence against a consistent effect of tDCS in the same individual across different sessions. This warrants caution in using tDCS as a predictable intervention on neural activity in research and clinical practices.

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bioRxiv2024

Main Sequence of Human Luminance-Evoked Pupil Dynamics

Pupil responses are commonly used to provide insight into visual perception, autonomic control, cognition, and various brain disorders. However, making inferences from pupil data can be complicated by nonlinearities in pupil dynamics and variability within and across individuals, which challenge the assumptions of linearity or group level homogeneity required for common analysis methods. In this study, we evaluated luminance evoked pupil dynamics in young healthy adults (N=10, 5:5 M:F, ages 19-25) by identifying nonlinearities, variability, and conserved relationships across individuals to improve the ability to make inferences from pupil data. We found a nonlinear relationship between final pupil diameter and luminance, linearized by considering the logarithm of luminance. Peak diameter change and peak velocity were nonlinear functions of log-luminance for constriction but not dilation responses. Across participants, curve fit parameters characterizing pupil responses as a function of luminance were highly variable, yet there was an across-participant linear correlation between overall pupil size and pupil gain (i.e. diameter change per unit log-luminance change). In terms of within-participant trial-by-trial variability, participants showed greater variability in final pupil size compared to constriction peak diameter change as a function of log-luminance. Despite the variability in stimulus-response metrics within and across participants, we found that all participants showed a highly stereotyped "main sequence" relationship between peak diameter change and peak velocity (independent of luminance). The main sequence relationship can be used to inform models of the neural control of pupil dynamics and as an empirical analysis tool to evaluate variability and abnormalities in pupil behaviour.

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bioRxiv2024

Parallel feedback processing for voluntary control: knowledge of spinal feedback in motor cortex

How hierarchical feedback pathways coordinate goal-directed motor corrections remains unknown. We show that systematic increases in spinal reflex responses to applied loads lead to a reciprocal reduction in the neural response in primary motor cortex. We use a neural network model to highlight how knowledge on lower-level feedback processing (i.e. spinal reflexes) can be embedded into a network to generate goal-directed corrections through parallel feedback pathways.

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bioRxiv2024

Timing and Amplitude of Catch-up Saccades to Accelerating Targets

To track moving targets, humans move their eyes using both saccades and smooth pursuit. If pursuit eye movements fail to accurately track the moving target, catch-up saccades are initiated to rectify the tracking error. It is well known that retinal position and velocity errors determine saccade timing and amplitude, but the extent to which retinal acceleration error influences these aspects is not well quantified. To test this, 13 adult human participants performed an experiment where they pursued accelerating / decelerating targets. During ongoing pursuit, we introduced a randomly sized target step to evoke a catch-up saccade and analyzed its timing and amplitude. We observed that retinal acceleration error was a statistically significant predictor of saccade amplitude and timing. A multiple linear regression supported our hypothesis that retinal acceleration errors influence saccade amplitude in addition to the influence of retinal position and velocity errors. We also found that saccade latencies were shorter when retinal acceleration error increased the tracking error and vice versa. In summary, our findings support a model in which retinal acceleration error is used to compute a predicted position error [~]100ms into the future to trigger saccades and determine saccade amplitude. Significance statementWhen visually tracking object motion, humans combine smooth pursuit and saccadic eye movements to maintain the target image on the fovea. Retinal position and velocity errors are known to determine catch-up saccade amplitude and timing, however it is unknown if retinal acceleration error is also used to predict future target position. This study provides evidence of a small but statistically significant contribution of retinal acceleration error in determining saccade amplitude and timing.

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bioRxiv2023

Choice anticipation as gated accumulation of sensory expectations

Predictions are combined with sensory information when making choices. Accumulator models have conceptualized predictions as trial-by-trial updates to a baseline evidence level. These models have been successful in explaining the influence of choice history across-trials, however they do not account for how sensory information is transformed into choice evidence within-trials. Here, we derive a gated accumulator that models the onset of evidence accumulation as a combination of delayed sensory information and a prediction of sensory timing. To test how the delays interact with across-trial predictions, we designed a free choice saccade task where participants directed eye movements to either of two targets that appeared with variable delays and asynchronies. Despite instructions not to anticipate, participants responded prior to target onset on some trials. We reasoned that anticipatory responses may reflect a trade-off between inhibiting and facilitating the onset of evidence accumulation via a gating mechanism as target appearance became more likely. Using a choice history analysis, we found that anticipatory responses were more likely following repeated choices, despite task randomization, suggesting that the balance between anticipatory and sensory responses was driven by a prediction of sensory timing. By fitting the gated accumulator model to the data, we found that variance in within-trial fluctuations in baseline evidence best explained the joint increase of anticipatory responses and faster sensory-guided responses with longer delays. Thus, we conclude that a prediction of sensory timing is involved in balancing the costs of anticipation with lowering the amount of accumulated evidence required to trigger saccadic choice, which could be explained by history-dependence in the baseline dynamics of a gated accumulator. New and NoteworthyEvidence accumulation models are used to study how recent history impacts the processes underlying how we make choices. Biophysical evidence suggests that the accumulation of evidence is gated, however classic accumulator models do not account for this, so little is known about how recent history may influence the gating process. In this work, computational modeling and experimental data from a free choice saccade task argue that predictions of the timing of sensory information are important in controlling how evidence accumulation is gated, and that signatures of these predictions can be detected even in randomized task environments where history effects may not be expected.

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bioRxiv2023

Visual working memory models of delayed estimation do not generalize to whole-report tasks

Whole-report working memory tasks provide a measure of recall for all stimuli in a trial, and afford single-trial analyses that are not possible with single-report delayed estimation tasks. However, most whole-report studies assume that trial stimuli are encoded and reported independently, and do not consider the relationships between stimuli presented and reported within the same trial. Here, we present the results of two independently conducted whole-report experiments. The first dataset was recorded by Adam, Vogel, and Awh, 2017, and required participants to report color and orientation stimuli using a continuous response wheel. We recorded the second dataset, which required participants to report color stimuli using a set of discrete buttons. We find that participants often group their reports by color similarity, contradicting the assumption of independence implicit in most encoding models of working memory. Next, we show that this behavior is consistent across participants and experiments when reporting color but not orientation, two circular variables often assumed to be equivalent. Finally, we implement an alternative to independent encoding where stimuli are encoded as a hierarchical Bayesian ensemble, and show that this model predicts biases that are not present in either dataset. Our results suggest that assumptions made by both independent and hierarchical ensemble encoding models--which were developed in the context of single-report delayed estimation tasks--do not hold for the whole-report task. This failure to generalize highlights the need to consider variations in task structure when inferring fundamental principles of visual working memory.

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bioRxiv2022

Differential reach vector computations in mIPS and PMd as revealed through HD-tDCS

Recent neural and behavioural findings provide support that the medial intraparietal sulcus (mIPS) and dorsal premotor (PMd) activity reflect aspects of a kinematic plan for reaching movements. However, it is unclear how these two regions differentially contribute to reach planning. Here, we used high-definition transcranial direct current stimulation (HD-tDCS; 4 x 1 electrode placement; 2 mA for 20 min; 3 cm radius) to investigate the functional roles of mIPS and PMd in the left hemisphere of humans. We examined the changes in endpoint error in reaching task with different initial hand positions and different target locations spanning both visual hemi-fields. Participants completed the task with (stimulation, post-stimulation) and without stimulation (pre-stimulation) of individually fMRI-localized cortical areas mIPS and PMd. We found a significant interaction effect between initial hand position (IHP) and target position on the difference in horizontal endpoint error after cathodal left mIPS stimulation and significant IHP and target position main effects after cathodal left PMd stimulation, suggesting that IHP and target position are not yet integrated into a movement vector at the input of the mIPS, but are integrated in the input of PMd. Hence, these findings reveal a distinction between mIPS and PMd in the stages of movement vector formation for reaching movements and indicate that HD-tDCS is a viable method for perturbing localized cortical activity to elucidate localized cortical function.

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bioRxiv2022

Parieto-frontal Oscillations Show Hand Specific Interactions with Top-Down Movement Plans

To generate a hand-specific reach plan, the brain must integrate hand-specific signals with the desired movement strategy. Although various neurophysiology / imaging studies have investigated hand-target interactions in simple reach-to-target tasks, the whole-brain timing and distribution of this process remain unclear, especially for more complex, instruction-dependent motor strategies. Previously, we showed that a pro/anti-pointing instruction influences magnetoencephalographic (MEG) signals in frontal cortex that then propagate recurrently through parietal cortex (Blohm et al., 2019). Here, we contrasted left versus right hand pointing in the same task to investigate 1) which cortical regions of interest show hand specificity, and 2) which of those areas interact with the instructed motor plan. Eight bilateral areas - the parietooccipital junction (POJ), superior parietooccipital cortex (SPOC), supramarginal gyrus (SMG), middle / anterior interparietal sulcus (mIPS/aIPS), primary somatosensory / motor cortex (S1/M1), and dorsal premotor cortex (PMd) - showed hand-specific changes in beta band power, with four of these (M1, S1, SMG, aIPS) showing robust activation before movement onset. M1, SMG, SPOC, and aIPS showed significant interactions between contralateral hand specificity and the instructed motor plan, but not with bottom-up target signals. Separate hand / motor signals emerged relatively early and lasted through execution, whereas hand-motor interactions only occurred close to movement onset. Taken together with our previous results, these findings show that instruction-dependent motor plans emerge in frontal cortex and interact recurrently with hand-specific parietofrontal signals before movement onset to produce hand-specific motor behaviors. Impact StatementThe brain must generate different motor signals, depending which hand is used. The distribution and timing of hand use / instructed motor plan integration is not understood at the whole-brain level. Using whole-brain MEG recordings we show that different sub-networks involved in action planning code for hand usage (alpha and beta frequencies) and integrating hand use information into a hand-specific motor plan (beta band). The timing of these signals indicates that frontal cortex first creates a general motor plan and then integrates hand-specific frontoparietal information to produce a hand-specific motor plan.

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bioRxiv2019

HD-tDCS over mIPS causally modulates online reach correction

Brain lesion and stimulation studies have suggested posterior parietal cortex and the medial intraparietal sulcus in particular as a crucial hub for online movement error corrections. However, causal evidence for this is still sparse. Indeed, lesion studies are potentially confounded by compensatory reorganization mechanisms while brain stimulation studies have produced heterogeneous results when employing transcranial magnetic stimulation. Here we designed a new complementary paradigm using fMRI-guided high-definition transcranial direct current stimulation (HD-tDCS) of the left medial intraparietal sulcus (mIPS) together with regression-based mediation analysis to re-examine the causal role of mIPS in online reach corrections to jumping targets. We obtained two independent measures of stimulation-induced changes in brain activity by modeling current flow in the brain and through EEG recordings before and after HD-tDCS stimulation. Third, to quantify behavioral effects of HD-tDCS we computed movement curvature as a measure of online correction. We demonstrate that both of our measurements of brain activity were consistent with a polarity-specific modulation of the online correction for targets jumping to the contralateral side of the stimulation. Importantly, using a mediation analysis of the relationship between stimulation current and movement curvature suggests that the induced current modifies brain activity, which then leads to the observed behavioral changes. This unique combination of methods and analysis thus provides complementary evidence for the crucial role of the posterior parietal cortex in online error correction, while at the same time setting a new methodological standard with respect to the causal influence of transcranial direct current stimulation. New & NoteworthyTranscranial direct current stimulation (tDCS) is an interesting and potentially useful tool for asking causal scientific questions and design clinical treatments. With our unique combination of highly accurate fMRI guided stimulation, current forward modeling, EEG recordings before and after the stimulation and behavioral changes we could unravel the causal structure of tDCS. Our approach naturally deals with the variability of tDCS results, increasing its potential usefulness as a tool for research and clinical applications.

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bioRxiv2019

Reaching around obstacles accounts for uncertainty in coordinate transformations

When reaching to a visual target, humans need to transform the spatial target representation into the coordinate system of their moving arm. It has been shown that increased uncertainty in such coordinate transformations, for instance when the head is rolled toward one shoulder, leads to higher movement variability and influence movement decisions. However, it is unknown whether the brain incorporates such added variability in planning and executing movements. We designed an obstacle avoidance task in which participants had to reach with or without visual feedback of the hand to a visual target while avoiding collisions with an obstacle. We varied coordinate transformation uncertainty by varying head roll (straight, 30{degrees} clockwise and 30{degrees} counterclockwise). In agreement with previous studies, we observed that the reaching variability increased when the head was tilted. Indeed, head roll did not influence the number of collisions during reaching compared to the head straight condition, but it did systematically change the obstacle avoidance behavior. Participants changed the preferred direction of passing the obstacle and increased the safety margins indicated by stronger movement curvature. These results suggest that the brain takes the added movement variability during head roll into account and compensates for it by adjusting the reaching trajectories.

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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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