The project has resulted in several major research developments. They have all advanced our understanding of how information is encoded in large neural populations during experience. Our windows into these computations have been the dynamics of grid cells and other entorhinal neurons during navigation as well as with minimal sensory stimulation during rest and sleep. We have made observations that significantly impact how we think computation is enabled in networks of interconnected cortical neurons. We shall highlight the most important published findings.
Our most recent breakthrough is the discovery of a new form of dynamics in grid cells and other cells of the entorhinal-hippocampal spatial coding system, reported in Nature in February (Vollan et al., 2025). We show that populations of grid cells and place cells encode a position signal that within a 125-ms theta cycle sweeps linearly outwards from the animal’s location into the ambient environment, alternating stereotypically between left and right directions. The decoded sweeps are time-locked to the local theta rhythm. Each theta cycle has one sweep. The sweeps alternate their direction between left and right on successive theta cycles. A striking observation was that the sweeps can extend into never-visited space inaccessible to the animal, and that they persist during REM sleep, all pointing to an intrinsic “hardwired” network mechanism for the phenomenon rather than one determined by specific sensory inputs. The sweeps were accompanied by, and aligned with, a similarly alternating directional signal in a discrete population of direction-tuned cells with putative connections to the grid cells. Sweeps in hippocampal place cells were delayed compared to sweeps in grid cells, pointing to an entorhinal origin. Using simulations in a simple computational model, we show that sweeps represent an efficient mechanism for scanning locations in the ambient environment during navigation. We show that sweep direction can be explained by an algorithm that maximizes cumulative coverage of surrounding space. These findings collectively point to an entirely new form of dynamics, hardwired into the circuit, by which activity systematically scans the surrounding state space, irrespective of whether animals move in a physical environment or not. The Nature paper mostly reports the experimental findings, but we are exploring at this moment whether and how they can be followed up in computational modelling to determine the underlying mechanisms.
In a second paper published during the reporting period, also in Nature (Gonzalo Cogno et al., 2024), we showed that entorhinal cells can self-organize into minute-long periodic sequences that may serve as a scaffold for on-the-fly formation of new sequences. Using both Neuropixels and two-photon calcium imaging, we found that during running in head-fixed mice, neural activity in the medial entorhinal cortex self-organized into oscillations at periods often longer than a minute that involved nearly the entire cell population. During each oscillatory cycle, the neural activity progressed in a stereotyped sequence. Sequences were periodic, with no interruption between oscillatory cycles. The sequences sometimes advanced uninterruptedly for tens of minutes, transcending epochs of locomotion and immobility. The ultraslow oscillatory sequences may have the potential to couple neurons and circuits across extended time scales and may serve as a template for new sequence formation downstream in hippocampus and other regions during navigation and episodic memory formation. Since the publication of this paper in 2024, we have been working on identifying the similar sequences during more natural behaviors, and we are seeking to understand what types of cells participate in the oscillations and sequences.
