Functional analysis of information rates conveyed by rat whisker-related trigeminal nuclei neurons.

The rat whisker system connects the tactile environment with the somatosensory thalamocortical system using only two synaptic stages. Encoding properties of the first stage, the primary afferents with somas in the trigeminal ganglion (TG), has been well studied, whereas much less is known from the second stage, the brainstem trigeminal nuclei (TN). The TN are a computational hub giving rise to parallel ascending tactile pathways and receiving feedback from many brain sites. We asked the question, whether encoding properties of TG neurons are kept by two trigeminal nuclei, the principalis (Pr5) and the spinalis interpolaris (Sp5i), respectively giving rise to two "lemniscal" and two "nonlemniscal" pathways. Single units were recorded in anesthetized rats while a single whisker was deflected on a band-limited white noise trajectory. Using information theoretic methods and spike-triggered mixture models (STM), we found that both nuclei encode the stimulus locally in time, i.e., stimulus features more than 10 ms in the past do not significantly influence spike generation. They further encode stimulus kinematics in multiple, distinct response fields, indicating encoding characteristics beyond previously described directional responses. Compared with TG, Pr5 and Sp5i gave rise to lower spike and information rates, but information rate per spike was on par with TG. Importantly, both brainstem nuclei were found to largely keep encoding properties of primary afferents, i.e. local encoding and kinematic response fields. The preservation of encoding properties in channels assumed to serve different functions seems surprising. We discuss the possibility that it might reflect specific constraints of frictional whisker contact with object surfaces.NEW & NOTEWORTHY We studied two trigeminal nuclei containing the second neuron on the tactile pathway of whisker-related tactile information in rats. We found that the subnuclei, traditionally assumed to give rise to functional tactile channels, nevertheless transfer primary afferent information with quite similar properties in terms of integration time and kinematic profile. We discuss whether such commonality may be due the requirement to adapt to physical constraints of frictional whisker contact.

Phenotypic variation of transcriptomic cell types in mouse motor cortex.

Cortical neurons exhibit extreme diversity in gene expression as well as in morphological and electrophysiological properties1,2. Most existing neural taxonomies are based on either transcriptomic3,4 or morpho-electric5,6 criteria, as it has been technically challenging to study both aspects of neuronal diversity in the same set of cells7. Here we used Patch-seq8 to combine patch-clamp recording, biocytin staining, and single-cell RNA sequencing of more than 1,300 neurons in adult mouse primary motor cortex, providing a morpho-electric annotation of almost all transcriptomically defined neural cell types. We found that, although broad families of transcriptomic types (those expressing Vip, Pvalb, Sst and so on) had distinct and essentially non-overlapping morpho-electric phenotypes, individual transcriptomic types within the same family were not well separated in the morpho-electric space. Instead, there was a continuum of variability in morphology and electrophysiology, with neighbouring transcriptomic cell types showing similar morpho-electric features, often without clear boundaries between them. Our results suggest that neuronal types in the neocortex do not always form discrete entities. Instead, neurons form a hierarchy that consists of distinct non-overlapping branches at the level of families, but can form continuous and correlated transcriptomic and morpho-electrical landscapes within families.

A Systematic Evaluation of Interneuron Morphology Representations for Cell Type Discrimination.

Quantitative analysis of neuronal morphologies usually begins with choosing a particular feature representation in order to make individual morphologies amenable to standard statistics tools and machine learning algorithms. Many different feature representations have been suggested in the literature, ranging from density maps to intersection profiles, but they have never been compared side by side. Here we performed a systematic comparison of various representations, measuring how well they were able to capture the difference between known morphological cell types. For our benchmarking effort, we used several curated data sets consisting of mouse retinal bipolar cells and cortical inhibitory neurons. We found that the best performing feature representations were two-dimensional density maps, two-dimensional persistence images and morphometric statistics, which continued to perform well even when neurons were only partially traced. Combining these feature representations together led to further performance increases suggesting that they captured non-redundant information. The same representations performed well in an unsupervised setting, implying that they can be suitable for dimensionality reduction or clustering.

Author Correction: Layer 4 of mouse neocortex differs in cell types and circuit organization between sensory areas.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Layer 4 of mouse neocortex differs in cell types and circuit organization between sensory areas.

Layer 4 (L4) of mammalian neocortex plays a crucial role in cortical information processing, yet a complete census of its cell types and connectivity remains elusive. Using whole-cell recordings with morphological recovery, we identified one major excitatory and seven inhibitory types of neurons in L4 of adult mouse visual cortex (V1). Nearly all excitatory neurons were pyramidal and all somatostatin-positive (SOM+) non-fast-spiking interneurons were Martinotti cells. In contrast, in somatosensory cortex (S1), excitatory neurons were mostly stellate and SOM+ interneurons were non-Martinotti. These morphologically distinct SOM+ interneurons corresponded to different transcriptomic cell types and were differentially integrated into the local circuit with only S1 neurons receiving local excitatory input. We propose that cell type specific circuit motifs, such as the Martinotti/pyramidal and non-Martinotti/stellate pairs, are used across the cortex as building blocks to assemble cortical circuits.

Manipulating Hippocampal Place Cell Activity by Single-Cell Stimulation in Freely Moving Mice.

Learning critically depends on the ability to rapidly form and store non-overlapping representations of the external world. In line with their postulated role in episodic memory, hippocampal place cells can undergo a rapid reorganization of their firing fields upon contextual manipulations. To explore the mechanisms underlying such global remapping, we juxtacellularly stimulated 42 hippocampal neurons in freely moving mice during spatial exploration. We found that evoking spike trains in silent neurons was sufficient for creating place fields, while in place cells, juxtacellular stimulation induced a rapid remapping of their place fields to the stimulus location. The occurrence of complex spikes was most predictive of place field plasticity. Our data thus indicate that plasticity-inducing stimuli are able to rapidly bias place cell activity, simultaneously suppressing existing place fields. We propose that such competitive place field dynamics could support the orthogonalization of the hippocampal map during global remapping.