Biology subjects

Gomez-Marin, A.

Publications and source records attributed to Gomez-Marin, A..

6 recordsLinked to original sources

bioRxiv2022

Angular speed should be avoided when assessing the speed-curvature power law of movement

The speed-curvature power law is one of the most studied constraints in biological movement. In many types of movements, there is a strong relationship between instantaneous speed and local curvature. For example, in elliptical trajectories, tangential speed is proportional to curvature raised to the power -1/3, (V[~]C-1/3). This phenomenon is known as the "one-thirds power law" and is generally considered to be mathematically equivalent to the "two-thirds power law" that describes the relationship between angular speed and curvature (A[~]C2/3); the two formulations are used interchangeably. However, in this paper, analysis of empirical and synthetic data demonstrates that using angular speed instead of tangential speed to estimate the power law tends to result in much stronger correlations, impacting the interpretation of the strength of the relationship, and therefore the existence of the law. Further analysis shows that angular speed and curvature are often trivially correlated, since angular speed is not a purely kinematic variable and depends on curvature. In conclusion, two forms of the law are not equivalent, angular speed should be avoided when expressing the speed-curvature power law.

neuroscience↗

bioRxiv2022

The Motor Wisdom of the Crowd

Wisdom of the Crowd is the aggregation of many individual estimates to obtain a better collective one. This effect has an enormous potential from the social point of view, as it means that a decision may be taken more effectively by vote among a large crowd than by a small minority of experts. Wisdom of the Crowd has been demonstrated in a wide range of cognitive tasks, all of which involve rational thinking. Here we tested this effect in the context of drawing simple geometrical shapes which, while still enacting cognitive processes, mainly involved visuo-motor control. We asked more than 700 school students to trace with their finger a predefined pattern shown on a touchscreen, and analyzed whether their individual trajectories could be aggregated in a way that improved the match with the original pattern. We found that this task has all the characteristics of the strongest examples of Wisdom of the Crowd: First, the aggregate trajectory can be up to 5 times more accurate than the individual ones. Second, this great improvement requires aggregating trajectories from different individuals (rather than different trials from the same individual). Third, the aggregate trajectory outperforms >99% of the individual trajectories. Fourth, when we split our dataset between young children (<10.5 years old) and older children, we find that older individuals outperform younger ones, as naively expected. However, a crowd of young children outperforms the average older individual. In sum, we demonstrate for the first time the Wisdom of the Crowd phenomenon in the realm of motor control, opening the door to further studies of human but also animal behavioral trajectories and their mechanistic underpinnings. Significance statementWisdom of the Crowd is the aggregation of many individual estimates to obtain a better collective one. Thanks to a combination of mathematical, psychological and social factors, this collective estimate can be surprisingly accurate, even when it comes from a crowd of poorly informed individuals. Originally proposed in the context of simple tasks (such as estimating a number), a general version of this concept now pervades our society, from being a key reason behind the success of democracies to being explicitly used to generate collective high-quality knowledge, from Wikipedia to Stack Exchange. Despite this enormous practical success, academic research lags behind, with most studies focusing on simple and narrow tasks. Here we apply the concept for the first time to a sensory-motor task, testing whether the combination of many drawings traced by different subjects resembles the original template. This type of task is wildly different from previous studies of Wisdom of the Crowd, as it depends on continuous sensory-motor control, rather than explicit reasoning or discrete decision-making. We demonstrate that the effect is strong: The aggregate trajectories are more accurate than an overwhelming majority of the individual ones, and a crowd of young children outperforms the average teenager with more mature motor skills.

animal behavior and cognition↗

bioRxiv2021

Hierarchical control of visually-guided movements in a 3D-printed robot arm

The control architecture guiding simple movements such as reaching toward a visual target remains an open problem. The nervous system needs to integrate different sensory modalities and coordinate multiple degrees of freedom in the human arm to achieve that goal. The challenge increases due to noise and transport delays in neural signals, nonlinear and fatigable muscles as actuators, and unpredictable environmental disturbances. Here we examined the capabilities of a previously proposed hierarchical feedback control model (Powers 1999, 2008), so far only tested in silico. We built a robot arm system with four degrees of freedom, including a visual system for locating the planar position of the hand, joint angle proprioception, and pressure sensing in one point of contact. We subjected the robot to various human-inspired reaching and tracking tasks and found features of biological movement, such as isochrony and bell-shaped velocity profiles in straight-line movements, and the speed-curvature power law in curved movements. These behavioral properties emerge without trajectory planning or explicit optimization algorithms. We then applied static structural perturbations to the robot: we blocked the wrist joint, tilted the writing surface, extended the hand with a tool, and rotated the visual system. For all of them, we found that the arm in machina adapts its behavior without being reprogrammed. In sum, while limited in speed and precision (by the nature of the do-it-yourself inexpensive components we used to build the robot from scratch), when faced with the noise, delays, nonlinearities, and unpredictable disturbances of the real world, the embodied control architecture shown here balances biological realism with design simplicity.

neuroscience↗

bioRxiv2019

Geometric purity, kinematic scaling and dynamic optimality in drawing movements beyond ellipses

Drawing movements have been shown to comply with a power law constraining local curvature and instantaneous speed. In particular, ellipses have been extensively studied, enjoying a 2/3 exponent. While the origin of such non-trivial relationship remains debated, it has been proposed to be an outcome of the least action principle whereby mechanical work is minimized along 2/3 power law trajectories. Here we demonstrate that such claim is flawed. We then study a wider range of curves beyond ellipses that can have 2/3 power law scaling. We show that all such geometries are quasi-pure with the same spectral frequency. We then numerically estimate that their dynamics produce minimum jerk. Finally, using variational calculus and simulations, we discover that equi-affine displacement is invariant across different kinematics, power law or otherwise. In sum, we deepen and clarify the relationship between geometric purity, kinematic scaling and dynamic optimality for trajectories beyond ellipses. It is enticing to realize that we still do not fully understand why we move our pen on a piece of paper the way we do.\n\nHighlightsO_LISeveral curves beyond ellipses have power-law kinematics with 2/3 exponent.\nC_LIO_LIThe curvature spectrum of each of such geometries is quasi-pure at frequency 2.\nC_LIO_LITheir dynamics are shown to comply with minimum of jerk.\nC_LIO_LIBut the 2/3 power law is not an outcome of minimizing mechanical work.\nC_LIO_LIYet, equi-affine displacement is invariant upon different kinematics.\nC_LI\n\nGraphical abstract\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=182 SRC=\"FIGDIR/small/737460v1_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (19K):\norg.highwire.dtl.DTLVardef@1a14c5corg.highwire.dtl.DTLVardef@9c6338org.highwire.dtl.DTLVardef@1360763org.highwire.dtl.DTLVardef@1ef534_HPS_FORMAT_FIGEXP M_FIG C_FIG \"We must represent any change, any movement, as absolutely indivisible.\" -- Henri Bergson

animal behavior and cognition↗

bioRxiv2019

A context-free grammar for Caenorhabditis elegans behavior

Hierarchy is a candidate organizing principle of ethology, where actions grouped into higher order chunks combine in specific ways to generate adaptive behavior. However, demonstrations of hierarchical organization in behavior have been scarce. Moreover, it remains unclear how such underlying organization allows for behavioral flexibility. Here we uncover the hierarchical and flexible nature of Caenorhabditis elegans behavior. By describing worm locomotion as a sequence of discrete postural templates, we identified chunks containing mutually substitutable postures along the dynamics. We then elucidated the rules governing their interactions. We found that stereotypical roaming can be described by a specific sequence of postural chunks, which exhibit flexibility at the lowest postural level. The same chunks get combined differently to produce dwelling, capturing non-stereotypical actions across timescales. We show that worm foraging is organized hierarchically --a feature not explainable via Markovian dynamics--, and derive a context-free grammar governing its behavior --which is different than a regular grammar, or a hidden Markov chain. In sum, in making the analogy with human language concrete (but not literal) our work demonstrates, in line with the foundational insights of classical ethologists, that spontaneous behavior is orderly flexible. Once more, investigating the humble nematode suggests that everything human has its roots in lower animal behavior.\n\n\n\nO_FIG O_LINKSMALLFIG WIDTH=180 HEIGHT=200 SRC=\"FIGDIR/small/708891v1_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (25K):\norg.highwire.dtl.DTLVardef@168e648org.highwire.dtl.DTLVardef@1e6b2eeorg.highwire.dtl.DTLVardef@ed3ecdorg.highwire.dtl.DTLVardef@1b60741_HPS_FORMAT_FIGEXP M_FIG Graphical abstract\n\nC_FIG

animal behavior and cognition↗

bioRxiv2019

A customizable tablet app for hand movement research outside the lab

BackgroundPrecise behavioral measurements allow the discovery of movement constraints that provide insights into sensory-motor processes and their underlying neural mechanisms. For instance, when humans draw an ellipse on a piece of paper, the instantaneous speed of the pen co-varies tightly with the local curvature of the path. Known as the speed-curvature power law, this phenomenon relates to fundamental questions of motor control.\n\nNew MethodWe have developed a software app for displaying static curves or dynamic targets while recording finger or stylus movements on Android touch-screen tablets. Designed for human hand movement research, the app is free, ready-to-use, open-source and customizable.\n\nResultsWe provide a template experimental protocol, and detailed explanations to use it and flexibly modify the code for different kinds of tasks. Our validation of the app demonstrates laboratory-quality results outside the laboratory. We also provide raw data and analysis scripts.\n\nComparison with Existing MethodsCommonly used laboratory devices for recording hand movement trajectories are large, heavy and expensive. In turn, software apps are often not published, nor customizable. Our app running on tablets becomes an affordable, flexible, and portable tool suited for quantitative and robust behavioral studies with large number of participants and outside the laboratory (e.g. in a classroom, a hospital, or at home).\n\nConclusionsThe affordability, flexibility, and resolution of our tablet app provide an effective tool to study behavior quantitatively in the real world.\n\nHighlightsO_LIA free, ready-to-use, open source, and customizable app for Android tablets.\nC_LIO_LIHigh-resolution measuring of finger movement during tracing, tracking & scribbling.\nC_LIO_LIFast and easy data collection and experimental design with affordable hardware.\nC_LIO_LIAllowing for high-throughput experiments outside the lab (classroom, hospital, home).\nC_LIO_LIValidated for state-of-the-art research (speed-curvature power law, drawing accuracy).\nC_LI\n\n\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=165 SRC=\"FIGDIR/small/633305v1_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (13K):\norg.highwire.dtl.DTLVardef@1ff34corg.highwire.dtl.DTLVardef@19e151borg.highwire.dtl.DTLVardef@17bb702org.highwire.dtl.DTLVardef@12c185b_HPS_FORMAT_FIGEXP M_FIG C_FIG

animal behavior and cognition↗