Axonal self-sorting without target guidance in Drosophila visual map formation.

The idea of guidance toward a target is central to axon pathfinding and brain wiring in general. In this work, we show how several thousand axonal growth cones self-pattern without target-dependent guidance during neural superposition wiring in Drosophila. Ablation of all target lamina neurons or loss of target adhesion prevents the stabilization but not the development of the pattern. Intravital imaging at the spatiotemporal resolution of growth cone dynamics in intact pupae and data-driven dynamics simulations reveal a mechanism by which >30,000 filopodia do not explore potential targets, but instead simultaneously generate and navigate a dynamic filopodial meshwork that steers growth directions. Hence, a guidance mechanism can emerge from the interactions of the axons being guided, suggesting self-organization as a more general feature of brain wiring.

A neural code for egocentric spatial maps in the human medial temporal lobe.

Spatial navigation and memory rely on neural systems that encode places, distances, and directions in relation to the external world or relative to the navigating organism. Place, grid, and head-direction cells form key units of world-referenced, allocentric cognitive maps, but the neural basis of self-centered, egocentric representations remains poorly understood. Here, we used human single-neuron recordings during virtual spatial navigation tasks to identify neurons providing a neural code for egocentric spatial maps in the human brain. Consistent with previous observations in rodents, these neurons represented egocentric bearings toward reference points positioned throughout the environment. Egocentric bearing cells were abundant in the parahippocampal cortex and supported vectorial representations of egocentric space by also encoding distances toward reference points. Beyond navigation, the observed neurons showed activity increases during spatial and episodic memory recall, suggesting that egocentric bearing cells are not only relevant for navigation but also play a role in human memory.

Cell-Type Specific Phase Precession in Layer II of the Medial Entorhinal Cortex.

The identity of phase-precessing cells in the entorhinal cortex is unknown. Here, we used a classifier derived from cell-attached recordings to separate putative pyramidal cells and putative stellate cells recorded extracellularly in layer II of the medial entorhinal cortex in rats. Using a novel method to identify single runs as temporal periods of elevated spiking activity, we find that both cell types show phase precession but putative stellate cells show steeper slopes of phase precession and larger phase ranges. As the two classes of cells have different projection patterns, phase precession is differentially passed on to different subregions of the hippocampal formation. SIGNIFICANCE STATEMENT: It is a great challenge for neuroscience to reveal the cellular basis of cognitive functions. One such function is the ability to learn and recollect temporal sequences of events. The representation of sequences in the brain is thought to require temporally structured activity of nerve cells. How different types of neurons generate temporally structured activity is currently unknown. In the present study, we use a computational classification procedure to separate different cell types and find that a subpopulation of cells, so-called stellate neurons, exhibits clear temporal coding. Contrary to the stellate cells, pyramidal cells show weaker temporal coding. This discovery sheds light on the cellular basis of temporal coding in the brain.

Grid cells in rat entorhinal cortex encode physical space with independent firing fields and phase precession at the single-trial level.

When a rat moves, grid cells in its entorhinal cortex become active in multiple regions of the external world that form a hexagonal lattice. As the animal traverses one such "firing field," spikes tend to occur at successively earlier theta phases of the local field potential. This phenomenon is called phase precession. Here, we show that spike phases provide 80% more spatial information than spike counts and that they improve position estimates from single neurons down to a few centimeters. To understand what limits the resolution and how variable spike phases are across different field traversals, we analyze spike trains run by run. We find that the multiple firing fields of a grid cell operate as independent elements for encoding physical space. In addition, phase precession is significantly stronger than the pooled-run data suggest. Despite the inherent stochasticity of grid-cell firing, phase precession is therefore a robust phenomenon at the single-trial level, making a theta-phase code for spatial navigation feasible.