Biology subjects

Tsay, J.

Publications and source records attributed to Tsay, J..

8 recordsLinked to original sources

bioRxiv2026

A rapid, sensitive, and quantitative high plex biomarker digital detection platform enabled by Hypercoding

Low-cost, multiplexed, and automated assays are needed to make omic technologies more broadly accessible in clinical, research, and commercial settings. We present Hypercoding, a scalable technology for detection and quantitation of multi-omic targets. Drawing from data reliability methods in the telecommunications field, Hypercoding uses fluorescent signals from hybridization with an error-correcting code to enable detection of high-plexity targets from biological samples, such as human DNA. In the presence of the target, a linear DNA construct is circularized, immobilized, and amplified to enable single-molecule detection of a target via rapid readout cycles within a 96-well plate. We demonstrate capability for >10,000 code plexity and accurate (98.7%) genotyping of 209 pharmacogenomic variants. Furthermore, we show computation of copy number variation with whole chromosome and sub-gene resolution, as well as quantitation of target abundance down to 10 fM sensitivity with a dynamic range of up to 10 logs.

genomics↗

bioRxiv2023

Predictors of sensorimotor adaption: insights from over 100,000 reaches

Sensorimotor adaptation is essential for keeping our movements well-calibrated in response to changes in the body and environment. For over a century, we have studied sensorimotor adaptation in highly controlled laboratory settings that typically involve small sample sizes. While this approach has proven useful to characterize different learning processes, laboratory studies are typically very underpowered to generate data suited for exploring the myriad of factors that may modulate motor performance. Here, using a citizen science website (testmybrain.org), we collected over 2000 sessions on a visuomotor rotation task. This unique dataset has allowed us to replicate classic motor findings, reconcile controversial findings in the learning and memory literature, and discover novel constraints underlying dissociable implicit and explicit learning processes supporting sensorimotor adaptation. Taken together, this study suggests that large-scale motor learning studies hold enormous potential to advance sensorimotor neuroscience.

neuroscience↗

bioRxiv2022

A Unitary Mechanism Underlies Adaptation to Both Local and Global Environmental Statistics in Time Perception

Our sense of the passage of time flexibly adapts to the statistical properties of the temporal context. Humans and non-human species exhibit a perceptual bias towards the mean of durations previously observed as well as serial dependence, a perceptual bias towards the duration of recently processed events. Here we asked whether those two phenomena arise from a unitary mechanism or reflect the operation of two distinct systems that adapt separately to the global and local statistics of the environment. We employed a set of duration reproduction tasks in which the target duration was sampled from distributions with different variances and means. The central tendency and serial dependence biases were jointly modulated by the range and the variance of the prior. These effects were well-captured by a unitary mechanism model in which temporal expectancies are updated after each trial based on perceptual observations. Alternative models that assume separate mechanisms for global and local contextual effects failed to capture the empirical results. TeaserTime perception of humans is shaped by a common mechanism that is sensitive to short-term and long-term environmental changes.

neuroscience↗

bioRxiv2022

Advanced Feedback Enhances Sensorimotor Adaptation

It is widely recognized that sensorimotor learning is enhanced when the feedback is provided throughout the movement compared to when it is provided at the end of the movement. However, the source of this advantage is unclear: Continuous feedback is more ecological, dynamic, and available earlier than endpoint feedback. Here we assess the relative merits of these factors using a method that allows us to manipulate feedback timing independent of actual hand position. By manipulating the onset time of endpoint feedback, we found that adaptation was modulated in a non-monotonic manner, with the peak of the function occurring in advance of the hand reaching the target. Moreover, at this optimal time, learning was of similar magnitude as that observed with continuous feedback. By varying movement duration, we demonstrate that this optimal time occurs at a relatively fixed time after movement onset, an interval we hypothesize corresponds to when the comparison of the sensory prediction and feedback generates the strongest error signal.

neuroscience↗

bioRxiv2022

The Effect of Perturbation Variability on Sensorimotor Adaptation Does Not Require an Implicit Memory of Errors

In a recent paper1 entitled, "An implicit memory of errors limits human sensorimotor adaptation" Albert and colleagues presented a model in which the adaptive response of the sensorimotor system is flexibly modulated by recent experience, or what they refer to as a "memory of errors". This hypothesis stands in contrast to prevailing models in which automatic and implicit responses to movement errors are relatively insensitive to the statistical properties of the environment2-6. A prime example of this rigidity is that the adaptation system exhibits a saturated response to large errors, resulting in a non-linear motor correction function, a feature that is independent of experience4,5,7. Here we show that the key results reported in Albert et al. are fully explained by presupposing this rigid "motor correction" function without reference to memory-dependent changes in error sensitivity. As such, the evidence presented in Albert et. al. does not support the claim that the history of errors modulates implicit adaptation.

neuroscience↗

bioRxiv2021

Long-term Motor Learning in the Wild with High Volume Video Game Data

Motor learning occurs over long periods of practice during which motor acuity - the ability to execute actions more accurately, precisely, and within a shorter amount of time - improves. Laboratory-based motor learning studies are typically limited to a small number of participants and a time frame of minutes to several hours per participant. Thus, there is a need to assess the generalizability of theories and findings from lab-based motor learning studies on much larger samples across longer time scales. In addition, laboratory-based studies of motor learning use relatively simple motor tasks which participants are unlikely to be intrinsically motivated to learn, limiting the interpretation of their findings in more ecologically valid settings. We studied the acquisition and longitudinal refinement of a complex sensorimotor skill embodied in a first-person shooter video game scenario, with a large sample size (N = 7174 participants, 682,564 repeats of the 60 sec game) over a period of months. Participants voluntarily practiced the gaming scenario for as much as several hours per day up to 100 days. We found improvement in performance accuracy (quantified as hit rate) was modest over time but motor acuity (quantified as hits per second) improved considerably, with 40-60% retention from one day to the next. We observed steady improvements in motor acuity across multiple days of video game practice, unlike most motor learning tasks studied in the lab that hit a performance ceiling rather quickly. Learning rate was a nonlinear function of baseline performance level, amount of daily practice, and to a lesser extent, number of days between practice sessions. In addition, we found that the benefit of additional practice on any given day was non-monotonic; the greatest improvements in motor acuity were evident with about an hour of practice and 90% of the learning benefit was achieved by practicing 30 minutes per day. Taken together, these results provide a proof-of-concept in studying motor skill acquisition outside the confines of the traditional laboratory and provide new insights into how a complex motor skill is acquired in an ecologically valid setting and refined across much longer time scales than typically explored.

neuroscience↗

bioRxiv2021

Distinct Processing of Sensory Prediction Error and Task Error during Motor Learning

Implicit motor recalibration allows us to flexibly move in novel and changing environments. Conventionally, implicit recalibration is thought to be driven by errors in predicting the sensory outcome of movement (i.e., sensory prediction errors). However, recent studies have shown that implicit recalibration is also influenced by errors in achieving the movement goal (i.e., task errors). Exactly how sensory prediction errors and task errors interact to drive implicit recalibration and, in particular, whether task errors alone might be sufficient to drive implicit recalibration remain unknown. To test this, we induced task errors in the absence of sensory prediction errors by displacing the target mid-movement. We found that task errors alone failed to induce implicit recalibration. In additional experiments, we simultaneously varied the size of sensory prediction errors and task errors. We found that implicit recalibration driven by sensory prediction errors could be continuously modulated by task errors, revealing an unappreciated dependency between these two sources of error. Moreover, implicit recalibration was attenuated when the target was simply flickered in its original location, even though this manipulation did not affect task error - an effect likely attributed to attention being directed away from the feedback cursor. Taken as a whole, the results were accounted for by a computational model in which sensory prediction errors and task errors, modulated by attention, interact to determine the extent of implicit recalibration. Authors summaryWhat information does the brain use to maintain precise calibration of the sensorimotor system? Using a reaching task paired with computational modeling, we find that movements are implicitly recalibrated by errors in predicting both the sensory outcome of movement (i.e., sensory prediction errors) as well as errors in achieving the movement goal (i.e., task errors). Even though task errors alone do not elicit implicit recalibration, they nonetheless modulate implicit recalibration when sensory prediction error is present. The results elucidate an unappreciated interaction between these two sources of error in driving implicit recalibration.

neuroscience↗

bioRxiv2020

Cerebellar degeneration selectively disrupts continuous mental operations in visual cognition

Here we test the hypothesis that the cerebellum aids in the dynamic transformation of mental representations. We report a series of neuropsychological experiments comparing the performance of individuals with cerebellar degeneration (CD) on cognitive tasks that either entail continuous, movement-like mental operations or more discrete mental operations. In visual cognition, individuals with CD exhibited an impaired rate of mental rotation, an operation hypothesized to require the continuous manipulation of a visual representation. In contrast, individuals with CD showed a normal processing rate when scanning items in visual working memory, an operation hypothesized to require the maintenance and retrieval of representations. In mathematical cognition, individuals with CD were impaired at single-digit addition, an operation hypothesized to require iterative manipulations along a mental number-line; this group was not impaired on arithmetic tasks requiring memory retrieval (e.g., single-digit multiplication). These results, obtained in tasks from two disparate domains, suggest one potential constraint on the contribution of the cerebellum to cognitive tasks. This constraint may parallel the cerebellums role in motor control, involving coordinated dynamic transformations in a mental workspace.

neuroscience↗