Encoding movement direction with theta sequences
Zutshi, I., Leutgeb, J.K. & Leutgeb, S. Theta sequences of grid cell populations can provide a movement-direction signal. Curr Opin Behav Sci 17, 147-154 (2017).
Research on theta phase precession to date has focused on its roles in improving the accuracy of spatial coding in place cells and grid cells, and in encoding trajectories through overlapping spatial fields as theta sequences, supporting memory consolidation and path planning. However, a recent paper by Zutshi, Leutgeb & Leutgeb proposes a novel function for phase precession in grid cells, suggesting that it may be key to encoding the movement direction information essential for an animal to keep track of its position via path integration.
Theta phase precession (PP) was first discovered in hippocampal place cells in a pioneering study by O’Keefe and Recce1, who observed that the phases of place cell spikes relative to the hippocampal theta oscillation become earlier on successive theta cycles, directly proportional to the animal’s movement through space. More than two decades on from that initial discovery, phase precession has been observed in the firing patterns of neurons from several other brain regions, including medial entorhinal cortex (MEC), ventral striatum, and prefrontal cortex2. Furthermore, experimental studies have indicated that it is grid cells in MEC, rather than hippocampal place cells, which are responsible for generating PP3, 4, with the other regions “inheriting” PP from MEC2.
In place cells, PP has been found to underlie the formation of theta sequences5, 6, which compress trajectories through overlapping place cell fields into individual theta cycles, supporting memory consolidation and path planning at a behaviourally and physiologically relevant timescale7, 8. In contrast, the spatially repetitive, tessellating fields of grid cells mean that theta sequences formed by these cells are not suitable for unambiguously encoding arbitrary trajectories through space in the same way as those formed by place cells. Therefore, despite the fact that grid cells appear to generate the PP inherited by other brain regions, proposals regarding the function of PP in grid cells to date have focused almost exclusively on its role in improving the precision of spatial position coding by supplementing the firing rate code with a phase code3, 9.
A recent paper by Zutshi, Leutgeb & Leutgeb10 expands on this view by putting forward the novel proposal that PP in grid cells has the additional function of coding for movement direction, which can be combined with speed information to update an animal’s internal estimates of its position in space, a process termed path integration11. Grid cells have long been implicated in path integration due to their strikingly regularly spaced fields12, and recent behavioural evidence from animals with grid cell activity specifically disrupted has provided strong confirmatory evidence to support this assertion13. Models of grid cell function to date have assumed that the precise spatial tuning of grid cell fields necessary for path integration can be maintained as the animal moves through an environment by integrating speed and head direction signals which converge on MEC12, 14, 15.
Recent modelling and experimental work by Raudies et al.16, however, has shown that using head direction information would quickly accumulate path integration error, since the animal’s head direction is frequently misaligned with its movement direction. Furthermore, they found that the neuronal population in MEC represents head direction information more strongly than movement direction, which is only weakly represented. So where, then, is the primary source of the movement direction information necessary for path integration?
In their paper, Zutshi, Leutgeb and Leutgeb propose a possible mechanism to resolve this question, suggesting that discrete sets of grid cell theta sequences code for different movement directions. Given the known anatomical clustering of grid cells with identical spatial scale and orientation but differing spatial offset into modules within MEC17, they argue that the number of possible theta sequence codes for each movement direction is finite. Based on these codes, cells downstream of the grid cells, which can also be local given the recurrent connectivity within MEC18, could then “read out” the movement direction. Their work therefore ascribes the novel function of signalling movement direction to grid cell theta sequences, which would allow for accurate path integration in MEC networks.
However, it is not yet clear whether such a coding scheme would provide a biologically plausible and efficient mechanism for computing path integration in MEC. Downstream cells would need to learn the different grid cell theta sequences corresponding to specific movement directions and be robust to reading these codes in the face of noise in spike timing19. Given that path integration is such an essential part of many animals’ natural behaviour11, 20, relying on such a mechanism could be unduly error-prone. An alternative and perhaps more robust signal for movement direction might involve the modulation of subcortical head direction signals arriving in MEC by proprioceptive and optic flow information21, 22.
Regardless of the precise origin of the movement direction signal, current models of grid cell firing which rely on the incorrect assumption that speed and head direction signals alone are sufficient for accurate path integration should be revised12, 14, 15. Despite much research in the past decades, a comprehensive description of the neural mechanisms underlying path integration in mammals remains elusive12, 20. Future experimental work should help to clarify whether theta sequences in MEC grid cells do indeed play a role in coding movement direction, or whether modulation of head direction inputs or an as yet undiscovered extra-entorhinal movement direction signal might provide the information necessary for accurate path integration in MEC grid cells.
References
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