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Linden, H.

Publications and source records attributed to Linden, H..

2 recordsLinked to original sources

Movement is governed by rotational population dynamics in spinal motor networks

Although the generation of movements is a fundamental function of the nervous system, the underlying neural principles remain unclear. Since flexor- and extensor-muscles alternate during rhythmic movements like walking, it is often assumed that the responsible neural circuitry is similarly displaying alternating activity. Here, we present ensemble-recordings of neurons in the lumbar spinal cord that indicate that, rather than alternating, the population is performing a low-dimensional "rotation" in neural space, in which the neural activity is cycling through all phases continuously during the rhythmic behavior. The radius of rotation correlates with the intended muscle force and a perturbation of the low-dimensional trajectory can modify the motor behavior. Since existing models of spinal motor control offer an inadequate explanation of rotation, we propose a new theory of neural generation of movements from which this and other unresolved issues, such as speed regulation, force control, and multi-functionalism, are readily explained.

neuroscience↗

Decoupling of timescales reveals sparse convergent CPG network in the adult spinal cord

During the generation of rhythmic movements, most spinal neurons receive an oscillatory synaptic drive. The neuronal architecture underlying this drive is unknown, and the corresponding network size and sparseness have not yet been addressed. If the input originates from a small central pattern generator (CPG) with dense divergent connectivity, it will induce correlated input to all receiving neurons, while sparse convergent wiring will induce a weak correlation, if any. Here, we use pairwise recordings of spinal neurons to measure synaptic correlations and thus infer the wiring architecture qualitatively. A strong correlation on a slow timescale implies functional relatedness and a common source, which will also cause correlation on fast timescale due to shared synaptic connections. However, we consistently find marginal coupling between slow and fast correlations regardless of neuronal identity. This suggests either sparse convergent connectivity or a CPG network with recurrent inhibition that actively decorrelates common input.

neuroscience↗