Biology subjects

Ota, K.

Publications and source records attributed to Ota, K..

17 recordsLinked to original sources

bioRxiv2026

Amide I kurtosis maps cardiac amyloid in human tissue by ultrabroadband multiplex coherent anti-Stokes Raman scattering (CARS) microscopy

Cardiac amyloidosis is caused by deposits of misfolded proteins in the heart and can lead to heart failure. Histological confirmation typically involves staining tissue sections with Congo red and examining them under polarized light for apple-green birefringence; however, achieving an interpretable, label-free, and observer-independent assessment remains challenging. Here we show that Pearson kurtosis of channel intensities within the amide I window provides an interpretable, fitting-free contrast for cardiac amyloid in unstained human cardiac tissue sections from ten participants imaged by ultrabroadband multiplex coherent anti-Stokes Raman scattering (CARS). In a discovery participant, high-kurtosis regions corresponded with Congo red-positive tissue in two CARS-histology pairs of adjacent sections (descriptive spatial AUCs, 0.79 and 0.73). Across 15 fields from nine additional participants, field-level kurtosis values did not overlap between severe-deposition and Congo red-negative tissue fields. Among the descriptors examined, kurtosis showed the largest standardized participant-level separation. Exploratory multivariate curve resolution yielded a deposit-associated component with aromatic-residue features shared with reagent transthyretin. In one field from the discovery participant, the second harmonic generation (SHG) signal, acquired simultaneously with CARS, showed a broadly inverse spatial pattern relative to the amide I kurtosis map, revealing distinct tissue-architectural contrast. Together, these findings support a potential label-free approach to detecting cardiac amyloid deposits that combines amide I kurtosis derived from broadband CARS with SHG-derived architectural contrast.

biophysics↗

bioRxiv2026

The Lateral Protein Cluster as a Key Component of Plant Cell Polarity

Cell polarity is an ancient organizing principle across kingdoms. As in animal epithelial cells, plant cells asymmetrically distribute proteins to establish functionally distinct membrane domains. In roots, radial polarity distinguishes inner and outer cell surfaces and supports directional nutrient transport, yet its molecular basis remains poorly understood. Here, we show that the leucine-rich repeat receptor-like kinases CaMRLK and IRK occupy complementary lateral plasma membrane domains in Arabidopsis thaliana roots. Polarity-guided proximity labeling identified previously uncharacterized proteins associated with inner- and outer-lateral domains. Clade VII LRR-RLKs, protein S-acyltransferases, SICK, IRKI1, and a distinct group of NPH3/RPT2-LIKEs assemble into the Lateral Protein Cluster (LPC) through multivalent interactions. LPC components are conserved across land plants, and disruption of NRL function impairs morphogenesis in Arabidopsis and Marchantia polymorpha. Together, these findings establish the LPC as an evolutionarily conserved molecular machinery linking radial cell polarity to plant morphogenesis.

plant biology↗

bioRxiv2026

Proton FLASH preserves neurocognition across delivery techniques: implications for clinical translation in pediatric brain tumors

BackgroundRadiation therapy is integral to the curative treatment of childhood brain tumors but contributes to late neurocognitive impairment in survivors. FLASH (ultra-high dose rate, >40Gy/s) reduces normal-tissue toxicity in preclinical models, and proton-FLASH is currently the only modality capable of delivering ultra-high dose rates to the deep targets, such as pediatric brain tumors. However, two questions remain unresolved before clinical translation: (1) whether the FLASH effect can be achieved on synchrotron-based proton systems, which deliver protons in discrete spills that may be insufficient to cover a clinical target within a single delivery, and (2) which dose-rate metric, among the multiple definitions currently used in the field, best predicts the biological FLASH effect. MethodsC57BL/6 mice (7-8 weeks) received 10 Gy whole-brain RT via a clinical Hitachi ProBEAT synchrotron with CBCT-guided delivery, using three transmission-beam techniques: single-spill pencil beam scanning (SS PBS), multi-spill PBS with [~]2-second inter-spot delay (MS PBS), and passive scatter (PS), compared to conventional (CONV) delivery and unirradiated controls (n=24-28/group, equal sex distribution). Dose rate was quantified using three frameworks: field dose rate (FDR), PBS dose rate (PBSDR), and dose-averaged dose rate (DADR). Recognition memory was assessed by novel object recognition (NOR) at 6 weeks post-RT, and cognitive flexibility was assessed via touchscreen visual discrimination and reversal learning at 14 weeks. Hippocampal neuroinflammation was evaluated by immunofluorescence and immunohistochemistry for Iba1, NeuN, and GFAP. ResultsFLASH conditions were met by SS PBS and PS under all three dose-rate definitions, but MS PBS qualified as FLASH only by DADR. Despite this, neuroprotection was preserved across all three FLASH techniques: discrimination index was significantly higher for SS PBS (P=0.021), MS PBS (P=0.008), and PS (P<0.001) versus CONV, with no significant difference between FLASH techniques. On touchscreen testing, FLASH-treated females demonstrated preserved cognitive flexibility (P=0.047 vs. CONV on reversal learning correct trials). Iba1+ microglia were reduced in FLASH compared to CONV mice, with morphology suggestive of preserved homeostatic state. ConclusionsSynchrotron-based proton FLASH preserves neurocognitive function across all delivery techniques, including under multi-spill delivery essential for treating clinical-scale pediatric brain tumors. Critically, this neuroprotection was observed even for deliveries that qualified as FLASH only by DADR, identifying DADR as the dose-rate metric most relevant to the biological FLASH effect with direct implications for clinical trial design and dose-rate reporting standards.

cancer biology↗

bioRxiv2026

Dose-dependent modeling of combinatorial drug responses stratifies patient survival and reveals therapeutic vulnerabilities in precision oncology

A substantial proportion of cancer patients fail to benefit from their prescribed combination regimens, yet identifying superior alternatives from the vast pharmacological space prior to treatment failure remains an unsolved clinical challenge. Existing computational approaches either rely on multi-omics profiles unavailable in standard oncological practice or reduce drug efficacy to scalar metrics that discard the dose-dependent resolution essential for therapeutic optimization. Here, we present XACT, a hierarchical deep learning framework that reconstructs full dose-dependent drug responses for both monotherapy and drug combinations using only clinically accessible transcriptomic profiles. By leveraging an asymmetric X-Linear Attention mechanism that models second-order interactions between molecular drug substructures and intracellular signaling pathway activities, XACT captures concentration-dependent pharmacodynamics with state-of-the-art accuracy and generalizability to unseen transcriptomic landscapes. When applied to the TCGA pan-cancer cohort, XACT-derived resistance scores were significantly associated with clinical treatment outcomes and stratified overall survival as the strongest independent prognostic factor after multivariate adjustment for tumor stage and cancer type. Systematic virtual screening revealed therapeutic vulnerabilities and nominated alternative regimens for treatment-refractory sarcoma and pancreatic adenocarcinoma. These results establish XACT as a scalable, interpretable, and clinically translatable framework that advances precision oncology from computational prediction toward data-driven therapeutic prescription.

cancer biology↗

bioRxiv2026

Synaptic mitochondrial oxidative stress drives individual variability in age-related cognitive decline in mice

Aging leads to cognitive decline with considerable individual variability, yet the biological mechanisms remain unclear. Here we performed ultrastructural and proteomic analyses of the medial prefrontal cortex (mPFC) alongside behavioral assessments of attentional set shifting in mice across age groups. Although reduced synaptic density did not consistently lead to cognitive decline, proteomic analyses of synaptosomes and whole tissue revealed that the molecular signatures associated with individual variability in cognitive decline were distinct from those associated with chronological aging, and that synaptic mitochondria and their proteins were more abundant in aged mice with greater cognitive decline. Moreover, treatment with the mitochondria-targeted antioxidant MitoQ reduced the abundance of synaptic mitochondrial proteins, including pro-apoptotic proteins, and mitigated age-related cognitive decline. These findings demonstrate that synaptic mitochondrial oxidative stress in the mPFC, distinct from chronological age-related processes, contributes to individual variability in age-related cognitive decline and offers a potential target for prevention and intervention.

animal behavior and cognition↗

bioRxiv2025

Given the birds, where is the flock? Visual estimation of the location of collections of points

Many visual tasks resemble statistical judgments, estimating the center of a cloud of identical items for example. In statistical form, the observer sees a sample drawn from an invisible probability density function (PDF) : the observer attempts to estimate the location of the PDF. He receives larger rewards for lower variance. Optimal minimum variance estimators are different for different distributions. We evaluated performance for three location families (Gaussian, Laplacian, and Uniform). How does human perceptual organization stack up against optimal perceptual estimation? We found that observers adopted distinct estimators for distinct distribution families, each approximately minimizing variance for its family. To explain observers ability to adapt to different distributional families, we propose that observers adopt a single estimator based on clusters in the sample. This Visual Cluster Model accounted for performance across distributions, suggesting that perceptual grouping first aggregates parts into clusters and only then into a whole. Significance statementImagine a flock of birds. We can predict where additional birds might appear by estimating the probability density function (PDF) of the birds. We compared performance in estimating the location of PDFs drawn from Gaussian, Laplacian or Uniform location families, rewarding lower variance. The optimal estimators for the three families are different. Observers approximately minimized variance for each condition and used different estimators for different families. How could they do so? We propose that observers use a single estimator based on sample clusters: perceptual grouping first aggregates parts into clusters and only then into a whole.

neuroscience↗

bioRxiv2025

A Functional Atlas of the Tardigrade Resistome Reveals a Diverse Molecular Toolkit for Extremotolerance

How organisms survive environmental extremes that push life to its physical limits is a fundamental question in biology. Tardigrades are a paradigm for this resilience, entering a state of suspended animation called cryptobiosis to withstand near-complete desiccation and intense radiation. While a few key effectors, including the DNA-shielding protein Dsup and various tardigrade-specific intrinsically disordered proteins (TDPs) have been identified, they constitute only a fraction of a vast, uncharacterized proteome, fundamentally limiting a systems-level understanding of this remarkable biology. Here we overcome this limitation by developing AEGIS, an AI-driven engine that systematically discovers and prioritizes novel guardian proteins constituting the tardigrade molecular shield. Applying AEGIS to the tardigrade proteome, we construct the first functional atlas of the tardigrade resistome, revealing hundreds of novel protein families organized into a diverse and compartmentalized molecular toolkit. This atlas pinpoints new Dsup-like nuclear proteins, suggesting multi-layered genome protection, and a rich cohort of cytoplasmic proteins poised to form protective biological glasses. Our work provides a foundational resource for understanding the evolution of extremotolerance and serves as a blueprint for engineering novel biomolecules with transformative biotechnological potential.

bioinformatics↗

bioRxiv2025

Integrating explicit reliability for optimal choices: effect of trustworthiness on decisions and metadecisions

A key challenge in todays fast-paced digital world is to integrate information from various sources, which differ in their reliability. Yet, little is known about how explicit probabilistic information about the likelihood that a source provides correct information is used in decision-making. Here, we investigated how such explicit reliability markers are integrated and the extent to which individuals have metacognitive insight into this process. We developed a novel paradigm where participants viewed opinions from sources of varying reliability to make a choice between two options. After each decision, they rated how much they felt a given source influenced their choice. Using computational modelling, we estimated the effective reliability that participants assigned to each source and how leaky their decision process was. Overall, we found that participants acted as if sources were more informative than they actually were, inflating the reliability they were communicated. Interestingly, we show that even though sources were explicitly labelled as unreliable, these sources biased choices, as if these were treated as moderately reliable. Additionally, the presence of sources known to be lying, reliably voting for the incorrect answer, impaired performance by increasing decision leakiness. Despite these biases, participants showed some metacognitive awareness of what influenced their choices: they were generally accurate in reporting the degree to which a source influenced them and were aware of the impact unreliable sources had on their decisions. These results suggest that people make suboptimal use of explicit source reliability, but have some awareness of their suboptimal choices. Author summaryIn everyday life, we constantly draw on information from multiple sources that differ in how much they can be trusted. When scrolling through social media or online platforms, for instance, we know some sources are reliable, others dubious, and some clearly misleading. In this study, we created a simple task mirroring this everyday challenge to examine how people form beliefs using information from sources of known, varying reliability. Using a computational model, we uncovered two systematic ways in which decisions fell short of optimal. First, sources that were clearly identified as unreliable still influenced the opinions and final choice of individuals. Second, peoples choices were often swayed by the last piece of information they saw, especially in a context where misleading sources were present. Surprisingly, participants were aware of some of these biases and could report which sources had shaped their choices, suggesting that awareness of bias is not necessarily sufficient to overcome it.

neuroscience↗

bioRxiv2024

Evolutionary Insights into Muscle Fiber Distribution in the Twin Tails of Ornamental Goldfish

Twin-tail ornamental goldfish have a bifurcated caudal fin with a morphology that is extremely diverged from the conventional body plan of the vertebrates. Here, we investigate the muscu-loskeletal histology of this bifurcated caudal fin. From some of the investigated twin-tail goldfish, we found a twin-tail goldfish specific muscle (hereafter referred to as the "medial caudal muscle") between left and right bifurcated caudal fin skeletons. Our immunohistochemical analyses revealed that the medial caudal muscle showed laterally biased distribution patterns of the slow and fast muscle fibers. Similar distribution patterns were also commonly observed in several deep muscles of wild-type goldfish as well as zebrafish, suggesting that these muscle fiber distribution patterns are formed by the same molecular developmental mechanisms even though their morphologies are highly diverged. These findings provide empirical evidence to consider how the histological features of a newly emerged morphology are influenced by selective pressures and pre-existing developmental mechanisms.

developmental biology↗

bioRxiv2023

Using influence measures to test normative use of probability density information derived from a sample

Bayesian decision theory (BDT) is frequently used to model normative performance in perceptual, motor, and cognitive decision tasks where the outcome of each trial is a reward or penalty that depends on the subjects actions. The resulting normative models specify how decision makers should encode and use information about uncertainty and value - step by step - in order to maximize their expected reward. When prior, likelihood, and posterior are probabilities, the Bayesian computation requires only simple arithmetic operations: addition, etc. We focus on visual cognitive tasks where Bayesian computations are carried out not on probabilities but on (1) probability density functions and (2) these probability density functions are derived from samples. We break the BDT model into a serries of computations and test human ability to carry out each of these computations in isolation. We test three necessary properties of normative use of pdf information derived from a sample - accuracy, additivity and influence. Influence measures allows us to assess how much weight each point in the sample is assigned in making decisions and allows us to compare normative use (weighting) of samples to actual, point by point. We find that human decision makers violate accuracy and additivity systematically but that the cost of failure in accuracy or additivity would be minor in common decision tasks. However, a comparison of measured influence for each sample point with normative influence measures demonstrates that the individuals use of sample information is markedly different from the predictions of BDT. We demonstrate that the normative BDT model takes into account the geometric symmetries of the pdf while the human decision maker does not. A heuristic model basing decisions on a single extreme sample point provided a better account for participants data than the normative BDT model. Author SummaryBayesian decision theory (BDT) is used to model human performance in tasks where the decision maker must compensate for uncertainty in order to to gain rewards and avoid losses. BDT prescribes how the decision maker can combine available data, prior knowledge, and value to reach a decision maximizing expected winnings. Do human decision makers actually use BDT in making decisions? Researchers typically compare overall human performance (total winnings) to the predictions of BDT but we cannot conclude that BDT is an adequate model for human performance based on just overall performance. We break BDT down into elementary operations and test human ability to execute such operations. In two of the tests human performance deviated only slightly (but systematically) from the predictions of BDT. In the third test we use a novel method to measure the influence of each sample point provided to the human decision maker and compare it to the influence predicted by BDT. When we look at what human decision makers do - in detail - we find that they use sensory information very differently from what the normative BDT observer does. We advance an alternative non-Bayesian model that better predicts human performance.

animal behavior and cognition↗

bioRxiv2023

Interleg coordination is not strictly controlled during walking

In human walking, the left and right legs move alternately, half a stride out of phase with each other. Although various parameters, such as stride frequency, stride length, and duty factor, vary with walking speed, the antiphase relationship of the leg motion remains unchanged. This is the case even during running. However, during walking in left-right asymmetric situations, such as walking with unilateral leg loading, walking along a curved path, and walking on a split-belt treadmill, the relative phase between left and right leg motion shifts from the antiphase condition to compensate for the asymmetry. In addition, the phase relationship fluctuates significantly during walking of elderly people and patients with neurological disabilities, such as those caused by stroke or Parkinsons disease. These observations suggest that appropriate interleg coordination is important for adaptive walking and that interleg coordination is strictly controlled during walking of healthy young people. However, the control mechanism of interleg coordination remains unclear. In the present study, we derive a quantity that models the control of interleg coordination during walking of healthy young people by taking advantage of a state-of-the-art method that combines big data science with nonlinear dynamics. This is done by modeling this control as the interaction between two coupled oscillators through the phase reduction theory and Bayesian inference method. However, the results were not what we expected. Specifically, we found that the relative phase between the motion of the legs is not actively controlled until the deviation from the antiphase condition exceeds a certain threshold. In other words, the control of interleg coordination has a dead zone like that in the case of the steering wheel of an automobile. Such forgoing of control presumably enhances energy efficiency and maneuverability during walking. Furthermore, the forgoing of control in specific situations, where we expect strict control, also appears in quiet standing. This suggests that interleg coordination in walking and quiet standing have a common characteristic strategy. Our discovery of the dead zone in the control of interleg coordination not only provides useful insight for understanding gait control in humans, but also should lead to the elucidation of the mechanisms involved in gait adaptation and disorders through further investigation of the dead zone.

bioengineering↗

bioRxiv2022

Freedom from habits: the capacity for autonomous behaviour

Humans and some other animals can autonomously generate action choices that contribute to solving complex problems. However, experimental investigations of the cognitive bases of human autonomy are challenging, because experimental paradigms typically constrain behaviour using controlled contexts, and elicit behaviour by external triggers. In contrast, autonomy and freedom imply unconstrained behaviour initiated by endogenous triggers. Here we propose a new theoretical construct of adaptive autonomy, meaning the capacity to make behavioural choices that are free from constraints of both immediate external triggers and of routine response patterns, but nevertheless show appropriate coordination with the environment. Participants (N = 152) played a competitive game in which they had to choose the right time to act, in the face of an opponent who punished (in separate blocks) either choice biases (such as always responding early), sequential patterns of action timing across trials (such as early, late, early, late...), or predictable action-outcome dependence (such as win-stay, lose-shift). Adaptive autonomy was quantified as the ability to maintain performance when each of these influences on action selection was punished. We found that participants could become free from habitual choices regarding when to act and could also become free from sequential action patterns. However, they were not able to free themselves from influences of action-outcome dependence, even when these resulted in poor performance. These results point to a new concept of autonomous behaviour as flexible adaptation of voluntary action choices in a way that avoids stereotypy. In a sequential analysis, we also demonstrated that participants increased their reliance on belief learning in which they attempt to understand the competitors beliefs and intentions, when transition bias and reinforcement bias were punished. Taken together, our study points to a cognitive mechanism of adaptive autonomy in which competitive interactions with other agents could promote both social cognition and volition in the form of non-stereotyped action choices.

neuroscience↗

bioRxiv2022

Inhibition of the BMP pathway suppresses tumor growth via downregulation of EGFR in MEK/ERK-dependent colorectal cancer

The bone morphogenetic protein (BMP) pathway promotes differentiation and induces apoptosis in normal colorectal epithelial cells. However, the effect of the BMP pathway in colorectal cancer (CRC) is controversial; it can either be tumor promoting or tumor suppressing, depending on the study. In this study, we found that CRC cells reside in a BMP-rich environment based on RNA-sequencing database analysis. Suppression of BMP using a specific BMP inhibitor, LDN193189, suppresses the growth of organoids in some CRC cases. CRC organoids treated with LDN193189 exhibited a decrease in epidermal growth factor receptor, which was, at least in part, mediated by protein degradation induced by leucine-rich repeats and immunoglobulin-like domains protein 1 (LRIG1). Among CRC organoid panels from 18 different patients, suppression of organoid growth by BMP inhibition correlated with the induction of LRIG1 gene expression. Notably, knockdown of LRIG1 in organoids diminished the growth-suppressive effect of LDN193189. Furthermore, simultaneous treatment with LDN192189 and trametinib, an FDA-approved MEK inhibitor, resulted in a combination effect in both in vivo and in vitro xenograft tumor treatment in CRC organoids, which are susceptible to growth suppression by LDN193189. Taken together, the simultaneous inhibition of BMP and MEK can be a novel treatment option in CRC cases, and evaluating in vitro growth suppression and LRIG1 induction by BMP inhibition using patient-derived organoids could offer functional biomarkers for predicting potential responders.

cancer biology↗

bioRxiv2021

Biomechanical characteristics of scapula and glenohumeral movements during pitching motion in injury-prone college baseball pitchers

Coordination of glenohumeral and scapular movements plays an important role in the injury prevention of baseball pitchers. However, there is no objective data establishing the direct relationship between pitching injuries and associated glenohumeral and scapular movements. Therefore, the objectives of the present study were to demonstrate biomechanical differences in scapular and glenohumeral movements during pitching between injury-prone pitchers and healthy college baseball pitchers. Thirty collegiate baseball pitchers were classified into two groups according to their injury status: injury-prone group (N=15, 20.7{+/-}1.4 years, 180.1{+/-}6.5 cm, 78.9{+/-}5.4 kg) and control group (N=15, 20.9{+/-}1.1 years, 177.1{+/-}6.6 cm, 72.3{+/-}6.7 kg). We obtained the pitching motion data using the three-dimensional motion analysis technique with four high-speed cameras. The horizontal abduction angles of the glenohumeral joint during cocking and acceleration phases were significantly greater in injury-prone pitchers [19.0{degrees} (95% CI: 14.4-23.6) at foot contact, -4.0{degrees} (95% CI: -7.7 to -0.2) at maximum external rotation (MER), and -0.3{degrees} (95% CI: -4.8 to -4.2) at ball release] than in healthy controls [11.7 {degrees}(95%CI:7.1 to 16.3) at foot contact, -10.0{degrees}(95%CI: -13.7 to -6.3) at MER, and -6.9{degrees}(95%CI: -11.4 to -2.4)](p<0.01). In addition, the external rotation angle (ER) of the scapula at MER was significantly greater in the injury-prone group [-0.1{degrees} (95% CI: -5.0 to 4.8)] than in the control group [-12.3{degrees} (95% CI: -17.2 to -7.4)] (p<0.01), but there was no difference in the scapular ER during foot contact between the two groups. These results suggests that injury-prone pitchers have less internal rotation of the scapula and more horizontal abduction of the glenohumeral joint during cocking and acceleration phases. Therefore, sports medicine practitioners may need to pay more attention to coordination of scapular and glenohumeral movements during the cocking and acceleration phases of pitching for prevention of shoulder injuries.

physiology↗

bioRxiv2020

Fast scanning high optical invariant two-photon microscopy for monitoring a large neural network activity with cellular resolution

Fast and wide imaging with single-cell resolution, high signal-to-noise ratio and no optical aberration has the potential to open up new avenues of investigation in biology. However, this imaging is challenging because of the inevitable tradeoffs among those parameters. Here, we overcome the tradeoffs by combining a resonant scanning system, a large objective with low magnification and high numerical aperture, and highly sensitive large-aperture photodetectors. The result is a practically aberration-free, fast scanning high optical invariant two-photon microscopy (FASHIO-2PM) that enables calcium imaging from a large network composed of [~]16k neurons at 7.5 Hz in a 9 mm2 contiguous image plane including more than 10 sensory-motor and higher-order regions of the cerebral cortex in awake mice. Through a network analysis based on single-cell activities, we discover that the brain exhibits small-world-ness rather than scale-freeness. FASHIO-2PM will enable revealing biological dynamics by simultaneous monitoring of macroscopic activity and its composing elements.

neuroscience↗

bioRxiv2018

Low Computational-cost Cell Detection Method for Calcium Imaging Data

The rapid progress of calcium imaging has reached a point where the activity of tens of thousands of cells can be recorded simultaneously. However, the huge amount of data in such records makes it difficult to carry out cell detection manually. Consequently, because the cell detection is the first step of multicellular data analysis, there is a pressing need for automatic cell detection methods for large-scale image data. Automatic cell detection algorithms have been pioneered by a handful of research groups. Such algorithms, however, assume a conventional field of view (FOV) (i.e. 512 x 512 pixels) and need a significantly higher computational power for a wider FOV to work within a practical period of time. To overcome this issue, we propose a method called low computational-cost cell detection (LCCD), which can complete its processing even on the latest ultra-large FOV data within a practical period of time. We compared it with two previously proposed methods, constrained non-negative matrix factorization (CNMF) and Suite2P. We found that LCCD makes it possible to detect cells from a huge-amount of high-density imaging data within a shorter period of time and with an accuracy comparable to or better than those of CNMF and Suite2P.

neuroscience↗

bioRxiv2018

Optimal motor decision-making through competition with opponents

Although optimal decision-making is essential for sports performance and fine motor control, it has been repeatedly confirmed that humans show a strong risk-seeking bias, selecting a risky strategy over an optimal solution. Despite such evidence, the ideal method to promote optimal decision-making remains unclear. Here, we propose that interactions with other people can influence motor decision-making and improve risk-seeking bias. We developed a competitive reaching game (a variant of the "chicken game") in which aiming for greater rewards increased the risk of no reward and subjects competed for the total reward with their opponent. The game resembles situations in sports, such as a penalty kick in soccer, service in tennis, the strike zone in baseball, or take-off in ski jumping. In five different experiments, we demonstrated that, at the beginning of the competitive game, the subjects robustly switched their risk-seeking strategy to a risk-averse strategy. Following the reversal of the strategy, the subjects achieved optimal decision-making when competing with risk-averse opponents. This optimality was achieved by a non-linear influence of an opponents decisions on a subjects decisions. These results suggest that interactions with others can alter human motor decision strategies and that competition with a risk-averse opponent is key for optimizing motor decision-making.

neuroscience↗