Human Purkinje cells outperform mouse Purkinje cells in dendritic complexity and computational capacity.

Purkinje cells in the cerebellum are among the largest neurons in the brain and have been extensively investigated in rodents. However, their morphological and physiological properties remain poorly understood in humans. In this study, we utilized high-resolution morphological reconstructions and unique electrophysiological recordings of human Purkinje cells ex vivo to generate computational models and estimate computational capacity. An inter-species comparison showed that human Purkinje cell had similar fractal structures but were larger than those of mouse Purkinje cells. Consequently, given a similar spine density (2/µm), human Purkinje cell hosted approximately 7.5 times more dendritic spines than those of mice. Moreover, human Purkinje cells had a higher dendritic complexity than mouse Purkinje cells and usually emitted 2-3 main dendritic trunks instead of one. Intrinsic electro-responsiveness was similar between the two species, but model simulations revealed that the dendrites could process ~6.5 times (n = 51 vs. n = 8) more input patterns in human Purkinje cells than in mouse Purkinje cells. Thus, while human Purkinje cells maintained spike discharge properties similar to those of rodents during evolution, they developed more complex dendrites, enhancing computational capacity.

Using subthreshold events to characterize the functional architecture of the electrically coupled inferior olive network.

The electrical connectivity in the inferior olive (IO) nucleus plays an important role in generating well-timed spiking activity. Here we combined electrophysiological and computational approaches to assess the functional organization of the IO nucleus in mice. Spontaneous fast and slow subthreshold events were commonly encountered during in vitro recordings. We show that whereas the fast events represent intrinsic regenerative activity, the slow events reflect the electrical connectivity between neurons ('spikelets'). Recordings from cell pairs revealed the synchronized occurrence of distinct groups of spikelets; their rate and distribution enabled an accurate estimation of the number of connected cells and is suggestive of a clustered organization. This study thus provides a new perspective on the functional and structural organization of the olivary nucleus and a novel experimental and theoretical approach to study electrically coupled networks.

Variability and directionality of inferior olive neuron dendrites revealed by detailed 3D characterization of an extensive morphological library.

The inferior olive (IO) is an evolutionarily conserved brain stem structure and its output activity plays a major role in the cerebellar computation necessary for controlling the temporal accuracy of motor behavior. The precise timing and synchronization of IO network activity has been attributed to the dendro-dendritic gap junctions mediating electrical coupling within the IO nucleus. Thus, the dendritic morphology and spatial arrangement of IO neurons governs how synchronized activity emerges in this nucleus. To date, IO neuron structural properties have been characterized in few studies and with small numbers of neurons; these investigations have described IO neurons as belonging to two morphologically distinct types, "curly" and "straight". In this work we collect a large number of individual IO neuron morphologies visualized using different labeling techniques and present a thorough examination of their morphological properties and spatial arrangement within the olivary neuropil. Our results show that the extensive heterogeneity in IO neuron dendritic morphologies occupies a continuous range between the classically described "curly" and "straight" types, and that this continuum is well represented by a relatively simple measure of "straightness". Furthermore, we find that IO neuron dendritic trees are often directionally oriented. Combined with an examination of cell body density distributions and dendritic orientation of adjacent IO neurons, our results suggest that the IO network may be organized into groups of densely coupled neurons interspersed with areas of weaker coupling.

Intensify3D: Normalizing signal intensity in large heterogenic image stacks.

Three-dimensional structures in biological systems are routinely evaluated using large image stacks acquired from fluorescence microscopy; however, analysis of such data is muddled by variability in the signal across and between samples. Here, we present Intensify3D: a user-guided normalization algorithm tailored for overcoming common heterogeneities in large image stacks. We demonstrate the use of Intensify3D for analyzing cholinergic interneurons of adult murine brains in 2-Photon and Light-Sheet fluorescence microscopy, as well as of mammary gland and heart tissues. Beyond enhancement in 3D visualization in all samples tested, in 2-Photon in vivo images, this tool corrected errors in feature extraction of cortical interneurons; and in Light-Sheet microscopy, it enabled identification of individual cortical barrel fields and quantification of somata in cleared adult brains. Furthermore, Intensify3D enhanced the ability to separate signal from noise. Overall, the universal applicability of our method can facilitate detection and quantification of 3D structures and may add value to a wide range of imaging experiments.