The capabilities and limitations of conductance-based compartmental neuron models with reduced branched or unbranched morphologies and active dendrites

Conductance-based neuron models are frequently employed to study the dynamics of biological neural networks. For speed and ease of use, these models are often reduced in morphological complexity. Simplified dendritic branching structures may process inputs differently than full branching structures, however, and could thereby fail to reproduce important aspects of biological neural processing. It is not yet well understood which processing capabilities require detailed branching structures. Therefore, we analyzed the processing capabilities of full or partially branched reduced models. These models were created by collapsing the dendritic tree of a full morphological model of a globus pallidus (GP) neuron while preserving its total surface area and electrotonic length, as well as its passive and active parameters. Dendritic trees were either collapsed into single cables (unbranched models) or the full complement of branch points was preserved (branched models). Both reduction strategies allowed us to compare dynamics between all models using the same channel density settings. Full model responses to somatic inputs were generally preserved by both types of reduced model while dendritic input responses could be more closely preserved by branched than unbranched reduced models. However, features strongly influenced by local dendritic input resistance, such as active dendritic sodium spike generation and propagation, could not be accurately reproduced by any reduced model. Based on our analyses, we suggest that there are intrinsic differences in processing capabilities between unbranched and branched models. We also indicate suitable applications for different levels of reduction, including fast searches of full model parameter space

Distinct contributions of small and large conductance Ca2+-activated K+ channels to rat Purkinje neuron function

The cerebellum is important for many aspects of behaviour, from posture maintenance and goal-oriented reaching movements to timing tasks and certain forms of learning. In every case, information flowing through the cerebellum passes through Purkinje neurons, which receive input from the two primary cerebellar afferents and generate continuous streams of action potentials that constitute the sole output from the cerebellar cortex to the deep nuclei. The tonic firing behaviour observed in Purkinje neurons in vivo is maintained in brain slices even when synaptic inputs are blocked, suggesting that Purkinje neuron activity relies to a significant extent on intrinsic conductances. Previous research has suggested that the interplay between Ca2+ currents and Ca2+-activated K+ channels (KCa channels) is important for Purkinje cell activity, but how many different KCa channel types are present and what each channel type contributes to cell behaviour remains unclear. In order to better understand the ionic mechanisms that control the behaviour of these neurons, we investigated the effects of different Ca2+ channel and KCa channel antagonists on Purkinje neurons in acute slices of rat cerebellum. Our data show that Ca2+ entering through P-type voltage-gated Ca2+ channels activates both small-conductance (SK) and large-conductance (BK) KCa channels. SK channels play a role in setting the intrinsic firing frequency, while BK channels regulate action potential shape and may contribute to the unique climbing fibre response

A robotic device for studying rodent locomotion after spinal cord injury

We have developed a robotic device (the "rat stepper") for evaluating and training locomotor function of spinal cord injured rodents. This paper provides a detailed description of the device design and a characterization of its robotic performance capabilities