Neuronal physiology depends on a neuron’s ion channel composition and unique morphology. Variable ion channel compositions can produce similar neuronal physiologies across animals. Less is known regarding the morphological precision required to produce reliable neuronal physiology. Theoretical studies suggest that moraphology is tightly tuned to minimize wiring and conduction delay of synaptic events. We utilize high-resolution confocal microscopy and custom computational tools to characterize the morphologies of four neuron types in the stomatogastric ganglion (STG) of the crab Cancer borealis. Macroscopic branching patterns and fine cable properties are variable within and across neuron types. We compare these neuronal structures to synthetic minimal spanning neurite trees constrained by a wiring cost equation and find that STG neurons do not adhere to prevailing hypotheses regarding wiring optimization principles. In this highly modulated and oscillating circuit, neuronal structures appear to be governed by a space-filling mechanism that outweighs the cost of inefficient wiring.DOI: http://dx.doi.org/10.7554/eLife.22352.001

Much work has explored animal-to-animal variability and compensation in ion channel expression. Yet, little is known regarding the physiological consequences of morphological variability. We quantify animal-to-animal variability in cable lengths (CV = 0.4) and branching patterns in the Gastric Mill (GM) neuron, an identified neuron type with highly-conserved physiological properties in the crustacean stomatogastric ganglion (STG) of Cancer borealis. We examined passive GM electrotonic structure by measuring the amplitudes and apparent reversal potentials (Erevs) of inhibitory responses evoked with focal glutamate photo-uncaging in the presence of TTX. Apparent Erevs were relatively invariant across sites (mean CV ± SD = 0.04 ± 0.01; 7–20 sites in each of 10 neurons), which ranged between 100–800 µm from the somatic recording site. Thus, GM neurons are remarkably electrotonically compact (estimated λ > 1.5 mm). Electrotonically compact structures, in consort with graded transmission, provide an elegant solution to observed morphological variability in the STG.DOI: http://dx.doi.org/10.7554/eLife.23508.001

Technological advances in experimental neuroscience are generating vast quantities of data, from the dynamics of single molecules to the structure and activity patterns of large networks of neurons. How do we make sense of these voluminous, complex, disparate and often incomplete data? How do we find general principles in the morass of detail? Computational models are invaluable and necessary in this task and yield insights that cannot otherwise be obtained. However, building and interpreting good computational models is a substantial challenge, especially so in the era of large datasets. Fitting detailed models to experimental data is difficult and often requires onerous assumptions, while more loosely constrained conceptual models that explore broad hypotheses and principles can yield more useful insights.

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Deep brain stimulation (DBS) is effective in managing motor symptoms of Parkinson's disease in well-selected individuals. Recently, research has shown that DBS in the basal ganglia (BG) can alter neural circuits beyond the traditional basal ganglia-thalamus-cortical (BG-TH-CX) loop. For instance, functional imaging showed alterations in cerebellar activity with DBS in the subthalamic nucleus (STN). However, these imaging studies revealed very little about how cell-specific cerebellar activity responds to STN stimulation or if these changes contribute to its efficacy. In this study, we assess whether STN-DBS provides efficacy in managing motor symptoms in Parkinson's disease by recruiting cerebellar activity. We do this by applying STN-DBS in hemiparkinsonian rats and simultaneously recording neuronal activity from the STN, brainstem and cerebellum. We found that STN neurons decreased spiking activity by 55% during DBS (P = 0.038), which coincided with a decrease in most pedunculopontine tegmental nucleus and Purkinje neurons by 29% (P < 0.001) and 28% (P = 0.003), respectively. In contrast, spike activity in the deep cerebellar nuclei increased 45% during DBS (P < 0.001), which was likely from reduced afferent activity of Purkinje cells. Then, we applied STN-DBS at sub-therapeutic current along with stimulation of the deep cerebellar nuclei and found similar improvement in forelimb akinesia as with therapeutic STN-DBS alone. This suggests that STN-DBS can engage cerebellar activity to improve parkinsonian motor symptoms. Our study is the first to describe how STN-DBS in Parkinson's disease alters cerebellar activity using electrophysiology in vivo and reveal a potential for stimulating the cerebellum to potentiate deep brain stimulation of the subthalamic nucleus.