Biology subjects

Ramadan, R.

Publications and source records attributed to Ramadan, R..

5 recordsLinked to original sources

bioRxiv2022

High-level motor planning allows flexible walking at different gait patterns in a neuromechanical model

Humans are able to adopt almost any desired gait pattern on the fly when walking. We postulate that this flexibility in humans is partially due to the ability to control the whole body during walking as a volitional, goal-directed movement that can be planned and changed, rather than having to rely on habitual, reflexive control that is adapted over long time-scales. Here we present a neuromechanical model that accounts for this flexibility by combining movement goals and motor plans on a kinematic task level with low-level spinal feedback loops. We show that the model is able to walk at a wide range of different gait patterns by choosing a small number of high-level control parameters representing a movement goal. A larger number of parameters governing the low-level reflex loops in the spinal cord, on the other hand, remains fixed. We also show that the model is able to generalize the learned behavior by re-combining the high-level control parameters and walk with gait patterns it had not encountered before. Furthermore, the model can transition between different gaits without loss of balance by switching to a new set of control parameters in real time.

neuroscience↗

bioRxiv2022

Estimating the time structure of descending activation that generates movements at different speeds

In targeted movements of the hand, descending activation patterns must not only generate muscle activation, but must also adjust spinal reflexes from stabilizing the initial to stabilizing the final postural state. We estimate descending activation patterns that change minimally while generating a targeted movement within a given movement time based on a model of the biomechanics, muscle dynamics, and the stretch reflex. The estimated descending activation patterns predict human movement trajectories quite well. Their temporal structure varies across workspace and with movement speed, from monotonic profiles for slow movements to non-monotonic profiles for fast movements. Descending activation patterns at different speeds thus do not result from a not mere rescaling of invariant templates, but reflect varying needs to compensate for interaction torques and muscle dynamics. The virtual attractor trajectories, on which active muscle torques are zero, lie within reachable workspace and are largely invariant movements when represented in end-effector coordinates. Their temporal structure along movement direction changes from linear ramps to "N-shaped" profiles with increasing movement speed. Author summaryWhat descending patterns of activation drive targeted movements? Based on a model that includes biomechanics, muscles dynamics and the stretch reflex we estimate the descending activation patterns by minimizing their change using optimal control, given a movement target and movement time. The resulting activation patterns predict experimentally observed human movements reasonably well. The temporal structure of the estimated descending activation patterns depends on the speed of the movement, varying from monotonic for slow to non-monotonic for fast movements. This structure reflects the need to compensate for interaction torques and muscle properties. From the model we are able to estimate the virtual attractor trajectories on which all active muscle torques are zero. These lie within reachable workspace, and are relatively uniform across workspace. Their time structure varies from linear ramps for slow movements to N-shaped temporal profiles for fast movements.

neuroscience↗

bioRxiv2021

A Neuromuscular Model of Human Locomotion Combines Spinal Reflex Circuits with Voluntary Movements

Existing models of human walking use low-level reflexes or neural oscillators to generate movement. While appropriate to generate the stable, rhythmic movement patterns of steady-state walking, these models lack the ability to change their movement patterns or spontaneously generate new movements in the specific, goal-directed way characteristic of voluntary movements. Here we present a neuromuscular model of human locomotion that bridges this gap and combines the ability to execute goal directed movements with the generation of stable, rhythmic movement patterns that are required for robust locomotion. The model represents goals for voluntary movements of the swing leg on the task level of swing leg joint kinematics. Smooth movements plans towards the goal configuration are generated on the task level and transformed into descending motor commands that execute the planned movements, using internal models. The movement goals and plans are updated in real time based on sensory feedback and task constraints. On the spinal level, the descending commands during the swing phase are integrated with a generic stretch reflex for each muscle. Stance leg control solely relies on dedicated spinal reflex pathways. Spinal reflexes stimulate Hill-type muscles that actuate a biomechanical model with eight internal joints and six free-body degrees of freedom. The model is able to generate voluntary, goal-directed reaching movements with the swing leg and combine multiple movements in a rhythmic sequence. During walking, the swing leg is moved in a goal-directed manner to a target that is updated in real-time based on sensory feedback to maintain upright balance, while the stance leg is stabilized by low-level reflexes and a behavioral organization switching between swing and stance control for each leg. With this combination of reflex-based stance leg and voluntary, goal-directed control of the swing leg, the model controller generates rhythmic, stable walking patterns in which the swing leg movement can be flexibly updated in real-time to step over or around obstacles.

neuroscience↗

bioRxiv2021

The extracellular matrix controls stem cell specification and tissue morphology in the developing and adult gut

The rapid renewal of the epithelial gut lining is fuelled by stem cells that reside at the base of intestinal crypts. In recent years, the signal transduction pathways and morphogens that regulate intestinal stem cell self-renewal and differentiation have been extensively characterised. In contrast, although extracellular matrix (ECM) components form an integral part of the intestinal stem cell niche, their direct influence on the cellular composition is less well understood. Here, we set out to systematically compare the effect of two major ECM classes, fibrillar collagen type I and the basement membrane, on the intestinal epithelium. We found that both collagen I and laminin-containing cultures allow growth of small intestinal epithelial cells with all differentiated and undifferentiated cell types present in both cultures, albeit at different ratios. Specific to the collagen culture was a subset of cells with a fetal-like gene expression program. In contrast, laminin, but not collagen IV, increased Lgr5+ stem cells and Paneth cells, and induced crypt-like morphology changes. The transition from a collagen culture to a laminin culture, resembles the gut development in vivo. Here, the ECM is dramatically remodelled by mesenchymal cells, which is accompanied by a specific and local expression of the laminin receptor ITGA6 in the crypt-forming epithelium. This laminin:ITGA6 signalling is essential for the stem cell induction and crypt formation in vitro. Importantly, deletion of laminin in the adult mouse results in a fetal-like epithelium with a marked reduction of adult intestinal stem cells. Overall, our data support the hypothesis that the formation of intestinal crypts is induced by an increased laminin concentration in the ECM.

cell biology↗

bioRxiv2020

Statistical Pitfalls in Brain Age Analyses

Over the past decade, there has been an abundance of research on the difference between age and age predicted using brain features, which is commonly referred to as the "brain age gap". Researchers have identified that the brain age gap, as a linear transformation of an out-of-sample residual, is dependent on age. As such, any group differences on the brain age gap could simply be due to group differences on age. To mitigate the brain age gaps dependence on age, it has been proposed that age be regressed out of the brain age gap. If this modified brain age gap (MBAG) is treated as a corrected deviation from age, model accuracy statistics such as R2 will be artificially inflated. Given the limitations of proposed brain age analyses, further theoretical work is warranted to determine the best way to quantify deviation from normality. HighlightsO_LIThe brain age gap is an out-of-sample residual, and as such varies as a function of age. C_LIO_LIA recently proposed modification of the brain age gap, designed to mitigate the dependence on age, results in inflated model accuracy statistics if used incorrectly. C_LIO_LIGiven these limitations, we suggest that new methods should be developed to quantify deviation from normal developmental and aging trajectories. C_LI

neuroscience↗