19 papers · ranked by Valyu relevance
Chenhui Zuo, Guo‐Hao Lin, Chen Zhang, Shao-Peng Zhuang + 1 more
Coordinated human movement depends on the integration of multisensory inputs, sensorimotor transformation, and motor execution, as well as sensory feedback resulting from body-environment interaction. Building dynamic models of the sensory-musculoskeletal system is essential for understanding movement control and…
Muhammad Noman Almani, John Lazzari, Shreya Saxena
How does the motor cortex (MC) produce purposeful and generalizable movements with the complex musculoskeletal system in a dynamic environment? To elucidate the underlying neural dynamics, we use a goal-driven approach to model MC by considering its goal as a controller driving the musculoskeletal system through…
Tonio Weidler, Rainer Goebel, Mario Senden
Goal-driven deep learning increasingly supplements classical modeling approaches in computational neuroscience. The strength of deep neural networks as models of the brain lies in their ability to autonomously learn the connectivity required to solve complex and ecologically valid tasks, obviating the need for…
Adriana Perez Rotondo, Alessandro Marin Vargas, Michael Dimitriou, Alexander Mathis
Proprioception is essential for planning and executing precise movements. Muscle spindles, the key mechanoreceptors for proprioception, are the principle sensory neurons enabling this process. Emerging evidence suggests spindles act as adaptable processors, modulated by gamma motor neurons to meet task demands. Yet…
Tonio Weidler, Rainer Goebel, Mario Senden
Goal-driven deep learning is increasingly used to supplement classical modeling approaches in computational neuroscience. The strength of deep neural networks lies in their ability to autonomously learn the connectivity required to solve complex and ecologically valid tasks, obviating the need for hand-engineered or…
Omar Zahra, David Navarro‐Alarcon
> Abstract. In this work, we present the development of a neuro-inspired approach for characterizing sensorimotor relations in robotic systems. The proposed method has self-organizing and associative properties that enable it to autonomously obtain these relations without any prior knowledge of either the motor (e.g.…
Muhammad Noman Almani, John Lazzari, Jeff Walker, Shreya Saxena
We review how sensorimotor control is dictated by interacting neural populations, optimal feedback mechanisms, and the biomechanics of bodies. First, we outline the distributed anatomical loops that shuttle sensorimotor signals between cortex, subcortical regions, and spinal cord. We then summarize evidence that neural…
Muhammad Noman Almani, John Lazzari, Jeff Walker, Shreya Saxena
We review how sensorimotor control is dictated by interacting neural populations, optimal feedback mechanisms, and the biomechanics of bodies. First, we outline the distributed anatomical loops that shuttle sensorimotor signals between cortex, subcortical regions, and spinal cord. We then summarize evidence that neural…
Ning Lan, Vincent C. K. Cheung, Simon C. Gandevia
Our knowledge of the neural mechanisms of movement generation is mostly derived from experimental data obtained in animals and humans. For a more comprehensive and holistic understanding of motor control, the ever-mounting experimental information must be integrated to allow general principles of sensorimotor control…
Travis DeWolf, Steffen Schneider, Paul Soubiran, Adrian Roggenbach + 1 more
The neural activity of the brain is intimately coupled to the dynamics of the body. Yet how our hierarchical sensorimotor system dynamically orchestrates the generation of movement while adapting to incoming sensory information remains unclear (1–4). In mice, the extent of encoding from posture to muscle-level features…
Gerald E. Loeb, George A. Tsianos
Experimental descriptions of the anatomy and physiology of individual components of sensorimotor systems have revealed substantial complexity, making it difficult to intuit how complete systems might work. This has led to increasing efforts to develop and employ mathematical models to study the emergent properties of…
Pablo Filipe Santana Chacon, Isabell Wochner, Maria Hammer, Jochen Martin Eppler + 2 more
'Jochen Martin Eppler' 'Susanne Kunkel' 'Syn Schmitt'] The development of new studies that consider different structures of the hierarchical sensorimotor control system is essential to enable a more holistic understanding about movement. The incorporation of more biological proprioceptive and neuronal circuit models to…
Tixian Wang, Udit Halder, Ekaterina Gribkova, Rhanor Gillette + 2 more
'Mattia Gazzola' 'Prashant G. Mehta'] In this article, a biophysically realistic model of a soft octopus arm with internal musculature is presented. The modeling is motivated by experimental observznations of sensorimotor control where an arm localizes and reaches a target. Major contributions of this article are: (i)…
Leonardo Gizzi, Ivan Vujaklija, Massimo Sartori, Oliver Röhrle + 1 more
Computational models of the composite neuro-musculo-skeletal system, allow investigating the neuro-mechanical interplay underlying movement in the controlled and predictive environment of simulation (Klotz et al., ). This provides new tools to determine the relative weight of the different components in the…
Alessandro Marin Vargas, Axel Bisi, Alberto Chiappa, Chris Versteeg + 2 more
Proprioception tells the brain the state of the body based on distributed sensors in the body. However, the principles that govern proprioceptive processing from those distributed sensors are poorly understood. Here, we employ a task-driven neural network modeling approach to investigate the neural code of…
Mohamed Irfan Mohamed Refai, Huawei Wang, Antonio Gogeascoechea, Rafael Ornelas-Kobayashi + 6 more
A primer Authors: ['Mohamed Irfan Mohamed Refai' 'Huawei Wang' 'Antonio Gogeascoechea' 'Rafael Ornelas-Kobayashi' 'Lucas Avanci Gaudio' 'Federica Damonte' 'Guillaume Durandau' 'Herman van der Kooij' 'Utku Ş. Yavuz' 'Massimo Sartori'] Wearable assistive robots (WR) for the lower extremity are extensively documented in…
Raghu Sesha Iyengar, Kapardi Mallampalli, Mohan Raghavan
Mechanisms behind neural control of movement have been an active area of research. Goal-directed movement is a common experimental setup used to understand these mechanisms and relevant neural pathways. On the one hand, optimal feedback control theory is used to model and make quantitative predictions of the…
Authors not listed
Machine olfaction—the artificial replication of the sense of smell—faces significant challenges due to the absence of large, standardized training datasets. Unlike vision, language, and audio models, which benefit from extensive corpora such as ImageNet, GLUE, and AudioSet, olfaction lacks scaled equivalents and…
Authors not listed
Digital twins are virtual companions for the design, scale-up, and control of chemical processes. Equipping digital twins with mechanistic models of their mirrored unit operation expands their range of applicability compared to pure data-driven models. As constructing mechanistic models requires time, effort, and…