Experiment protocols for brain-body imaging of locomotion: A systematic review

Frontiers in Neuroscience, Год журнала: 2023, Номер 17

Опубликована: Март 1, 2023

Human locomotion is affected by several factors, such as growth and aging, health conditions, physical activity levels for maintaining overall well-being. Notably, impaired a prevalent cause of disability, significantly impacting the quality life individuals. The uniqueness high prevalence human have led to surge research develop experimental protocols studying brain substrates, muscle responses, motion signatures associated with locomotion. However, from technical perspective, reproducing experiments has been challenging due lack standardized benchmarking tools, which impairs evaluation validation previous findings.This paper addresses challenges conducting systematic review existing neuroimaging studies on locomotion, focusing settings protocols, intensity, duration, distance, adopted imaging technologies, corresponding activation patterns. Also, this study provides practical recommendations future experiment protocols.The findings indicate that EEG preferred sensor detecting patterns, compared fMRI, fNIRS, PET. Walking most studied task, likely its fundamental nature status reference task. In contrast, running received little attention in research. Additionally, cycling an ergometer at speed 60 rpm using fNIRS provided some basis. Dual-task walking tasks are typically used observe changes cognitive function. Moreover, primarily focused healthy individuals, scenario closely resembling free-living real-world environments.Finally, outlines standards setting up based findings. It discusses impact neurological musculoskeletal well locomotive demands, design. also considers limitations imposed sensing techniques used, including acceptable level artifacts brain-body effects spatial temporal resolutions performance. various protocol constraints need be addressed analyzed explained.

Язык: Английский

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Dopamine-sensitive neurons in the mesencephalic locomotor region control locomotion initiation, stop, and turns

Cell Reports, Год журнала: 2024, Номер 43(5), С. 114187 - 114187

Опубликована: Май 1, 2024

The locomotor role of dopaminergic neurons is traditionally attributed to their ascending projections the basal ganglia, which project mesencephalic region (MLR). In addition, descending MLR are present from vertebrates mammals. However, targeted in and behavioral unknown Here, we identify genetically defined cells that express D

Язык: Английский

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Acquiring musculoskeletal skills with curriculum-based reinforcement learning

Neuron, Год журнала: 2024, Номер unknown

Опубликована: Окт. 1, 2024

Язык: Английский

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Parallel locomotor control strategies in mice and flies

Current Opinion in Neurobiology, Год журнала: 2022, Номер 73, С. 102516 - 102516

Опубликована: Фев. 11, 2022

Our understanding of the neural basis locomotor behavior can be informed by careful quantification animal movement. Classical descriptions legged locomotion have defined discrete gaits, characterized distinct patterns limb Recent technical advances enabled increasingly detailed characterization kinematics across many species, imposing tighter constraints on control. Here, we highlight striking similarities between coordination observed in two genetic model organisms: laboratory mouse and Drosophila. Both species exhibit continuously-variable with similar low-dimensional structure, suggesting shared principles for descending

Язык: Английский

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Estimation performance of the novel hybrid estimator based on machine learning and extended Kalman filter proposed for speed-sensorless direct torque control of brushless direct current motor

Engineering Applications of Artificial Intelligence, Год журнала: 2023, Номер 126, С. 107083 - 107083

Опубликована: Сен. 11, 2023

Язык: Английский

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

bioRxiv (Cold Spring Harbor Laboratory), Год журнала: 2023, Номер unknown

Опубликована: Янв. 20, 2023

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

Язык: Английский

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The Role of the Medial Septum—Associated Networks in Controlling Locomotion and Motivation to Move

Frontiers in Neural Circuits, Год журнала: 2021, Номер 15

Опубликована: Июль 22, 2021

The Medial Septum and diagonal Band of Broca (MSDB) was initially studied for its role in locomotion. However, the last several decades were focussed on intriguing function theta rhythm generation. Early studies relied electrical stimulation, lesions pharmacological manipulation, reported an inconclusive picture regarding MSDB circuits. Recent using more specific methodologies have started to elucidate differential MSDB’s cell populations controlling both behaviour. In particular, a novel theory is emerging showing that different project brain regions control distinct aspects While majority these behaviours involve movement, increasing evidence suggests MSDB-related networks govern motivational aspect actions, rather than locomotion per se . Here, we review literature links MSDB, activity, propose open questions, future directions, methods could be employed diverse roles MSDB-associated networks.

Язык: Английский

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Using deep learning to study emotional behavior in rodent models

Frontiers in Behavioral Neuroscience, Год журнала: 2022, Номер 16

Опубликована: Ноя. 22, 2022

Quantifying emotional aspects of animal behavior (e.g., anxiety, social interactions, reward, and stress responses) is a major focus neuroscience research. Because manual scoring emotion-related behaviors time-consuming subjective, classical methods rely on easily quantified measures such as lever pressing or time spent in different zones an apparatus open vs. closed arms elevated plus maze). Recent advancements have made it easier to extract pose information from videos, multiple approaches for extracting nuanced about behavioral states estimation data been proposed. These include supervised, unsupervised, self-supervised approaches, employing variety model types. Representations derived these can be correlated with recordings neural activity increase the scope connections that drawn between brain behavior. In this mini review, we will discuss how deep learning techniques used experiments architectures training paradigms influence type representation obtained.

Язык: Английский

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A rubric for human-like agents and NeuroAI

Philosophical Transactions of the Royal Society B Biological Sciences, Год журнала: 2022, Номер 378(1869)

Опубликована: Дек. 13, 2022

Researchers across cognitive, neuro- and computer sciences increasingly reference 'human-like' artificial intelligence 'neuroAI'. However, the scope use of terms are often inconsistent. Contributed research ranges widely from mimicking

Язык: Английский

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Acquiring musculoskeletal skills with curriculum-based reinforcement learning

bioRxiv (Cold Spring Harbor Laboratory), Год журнала: 2024, Номер unknown

Опубликована: Янв. 25, 2024

Efficient musculoskeletal simulators and powerful learning algorithms provide computational tools to tackle the grand challenge of understanding biological motor control. Our winning solution for inaugural NeurIPS MyoChallenge leverages an approach mirroring human skill learning. Using a novel curriculum approach, we trained recurrent neural network control realistic model hand with 39 muscles rotate two Baoding balls in palm hand. In agreement data from subjects, policy uncovers small number kinematic synergies even though it is not explicitly biased towards low-dimensional solutions. However, by selectively inactivating parts signal, found that more dimensions contribute task performance than suggested traditional synergy analysis. Overall, our work illustrates emerging possibilities at interface physics engines, reinforcement neuroscience advance

Язык: Английский

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