Biology subjects

Donelan, J. M.

Publications and source records attributed to Donelan, J. M..

5 recordsLinked to original sources

bioRxiv2019

Spasticity reduction in children with cerebral palsy is not associated with reduced energy consumption during walking

BackgroundThe average energy consumption during walking of children with cerebral palsy (CP) is over two times of that of typically developing (TD) children and fatigue is one of the top complaints of children with CP and their families. Spasticity has been theorized to contribute to increased energy consumption during walking in CP, but its role remains unclear.\n\nMethodsWe retrospectively compared the energy consumption of walking in children with diplegic CP before and after selective dorsal rhizotomy (SDR), a surgery that reduces spasticity. A control group of participants with CP who also underwent gait analysis but did not undergo SDR was matched to the SDR group by pre-surgery age, spasticity, and energy consumption. Energy consumption and spasticity were compared at baseline and follow-up for both groups.\n\nFindingsAs expected, the SDR group has a significantly greater decrease (-44%) in spasticity compared to matched peers with CP who did not undergo SDR (-16%, P<0.001). While both groups had a reduction in energy consumption between visits (12 % SDR and 14% no-SDR), there was no difference in the change in energy consumption between groups (P=0.4).\n\nInterpretation: Reducing spasticity did not contribute to greater reductions in energy consumption, suggesting that spasticity has minimal impact on elevated energy consumption during walking for children with CP. Energy consumption and spasticity decrease with age among children with CP. Identifying matched control groups of peers with CP is critical for research involving children with CP to account for changes due to development.\n\nHighlightsO_LIEnergy consumption is not reduced after rhizotomy compared to matched peers\nC_LIO_LISpasticity has minimal contribution to elevated energy during walking\nC_LIO_LIMatched control groups are critical in cerebral palsy research\nC_LI

bioengineering↗

bioRxiv2019

Scaling of inertial delays in terrestrial mammals

As part of its response to a perturbation, an animal often needs to reposition its body. Inertia acts to oppose motion, delaying the completion of the movement--we refer to this additional elapsed time as inertial delay. As animal size increases, muscle moment arms also increase, but muscles are proportionally weaker, and limb inertia is proportionally larger. Consequently, the scaling of inertial delays is complex. Here, we quantify it using two biomechanical models representing common scenarios in animal locomotion: a distributed mass pendulum approximating swing limb repositioning (swing task), and an inverted pendulum approximating whole body posture recovery (posture task). We parameterized the anatomical, muscular, and inertial properties of these models using literature scaling relationships, then determined inertial delay for each task across a large range of movement magnitudes and the full range of terrestrial mammal sizes. We found that inertial delays scaled with an average of M0.28 in the swing task and M0.35 in the posture task across movement magnitudes--larger animals require more absolute time to perform the same movement as small animals. The time available to complete a movement also increases with animal size, but less steeply. Consequently, inertial delays comprise a greater fraction of swing duration and other characteristic movement times in larger animals. We also compared inertial delays to the other component delays within the stimulus-response pathway. As movement magnitude increased, inertial delays exceeded these sensorimotor delays, and this occurred for smaller movements in larger animals. Inertial delays appear to be a challenge for motor control, particularly for bigger movements in larger animals.

neuroscience↗

bioRxiv2018

Energy Optimization is a Major Objective in the Real-Time Control of Step Width in Human Walking

People prefer to move in energetically optimal ways during walking. We have recently found that this preference arises not just through evolution and development, but that the nervous system will continuously optimize step frequency in response to new energetic cost landscapes. Here we test whether energy optimization is also a major objective in the nervous system s real-time control of step width. To accomplish this, we use a device that can reshape the relationship between step width and energetic cost, shifting the energy optimal width wider than that initially preferred. We find that the nervous system doesn t spontaneously initiate energy optimization, but instead requires experience with a lower energetic cost step width. After initiating optimization, people converge towards their new energy optimal width within hundreds of steps and update this as their new preferred width, rapidly returning to it when perturbed away. However, energy optimization was incomplete as this new preferred width was slightly narrower than the energetically optimal width. This suggests that the nervous system may determine its preferred width by optimizing energy simultaneously with other objectives such as stability or maneuverability. Collectively, these findings indicate that the nervous systems of able-bodied people continuously optimize energetic cost to determine preferred step width.

neuroscience↗

bioRxiv2018

Taking advantage of external mechanical work to reduce metabolic cost: the mechanics and energetics of split-belt treadmill walking

In everyday tasks such as walking and running, we exploit the work performed by external sources such as gravity to reduce the work performed by muscles. There has been considerable recent effort to design devices capable of performing mechanical work to improve walking function or reduce effort. The success of these devices relies on the user adapting their natural control strategies to take advantage of assistance provided by the device. Although locomotor adaptation is central to this process, the study of adaptation is often done using approaches that on the surface, seem to have little in common with the use of external assistance. Here, we show that one of the most common approaches for studying this process, which is adaptation to walking on a split-belt treadmill, can be understood from a perspective in which people learn to take advantage of mechanical work performed by the treadmill. During adaptation, people systematically adjust their step lengths, defined as the distance between the feet at heel strike, from one step to the next. Initially, the step length on the slow belt is longer than the step length on the fast belt, measured as a negative step length asymmetry, but people naturally reduce this asymmetry with practice. Here, we demonstrate that these modifications of step length asymmetry allow people to extract positive work from the treadmill belts to reduce the positive work performed by the legs and simultaneously reduce metabolic cost. Moreover, we show that walking with a positive step length asymmetry minimizes metabolic cost, and people prefer to walk in this manner when allowed to select their walking pattern. Together, our results suggest that split-belt adaptation can be interpreted as a process by which people learn to take advantage of mechanical work performed by an external device to improve walking economy.

neuroscience↗

bioRxiv2018

A mechatronic system for studying energy optimization during walking.

A general principle of human movement is that our nervous system is able to learn optimal coordination strategies. However, how our nervous system performs this optimization is not well understood. Here we design, build, and test a mechatronic system to probe the algorithms underlying optimization of energetic cost in walking. The system applies controlled fore-aft forces to a hip-belt worn by a user, decreasing their energetic cost by pulling forward or increasing it by pulling backward. The system controls the forces, and thus energetic cost, as a function of how the user is moving. In testing, we found that the system can quickly, accurately, and precisely apply target forces within a walking step. We next controlled the forces as a function of the users step frequency and found that we could predictably reshape their energetic cost landscape. Finally, we tested whether users adapted their walking in response to the new cost landscapes created by our system, and found that users shifted their step frequency towards the new energetic minima. Our system design appears to be effective for reshaping energetic cost landscapes in human walking to study how the nervous system optimizes movement.

neuroscience↗