PubMed · 14976773
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Yoshio Sakurai. 2004. [Neuronal coding by cell assemblies: to detect in experiments].. https://pubmed.ncbi.nlm.nih.gov/14976773/
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The extent of external and internal factors contributing to location-specific firing of hippocampal place cells is currently unclear. We investigated the role of active movement in location-specific firing by comparing spatial firing patterns of hippocampal neurons, while rats either ran freely or rode a motorized cart on the same circular track. Most neurons changed their spatial firing patterns across the two navigation conditions ("remapping"), and they were stably maintained across repeated active or passive navigation sessions. These results show that active movement is a critical factor in determining place-specific firing of hippocampal neurons. This could explain why passive displacement is not an effective way of acquiring spatial knowledge for subsequent active navigation in an unfamiliar environment.
The importance of space-specific single-unit activity for hippocampal formation (HF)-mediated learning and memory in rodents has been extensively studied, yet little is known about how the unit findings in rodents generalize to other vertebrate species. We report a first assessment of the space-specific single-unit activity recorded from the HF of homing pigeons as they moved through a plus maze for food reward. Rate maps of pigeon HF single-unit activity typically revealed multiple regions (2-5 per cell) of increased activity (on average, 2.5 times higher than other regions of the maze) that in 27% of slow-firing cells was reliably space-specific over time. The qualitative appearance of rate maps and the degree of spatial-specificity observed for most all pigeon HF cells suggests more modest space-specific activity than typically reported for rat hippocampal cells. The nature of space-specific activity in the pigeon HF includes (1) often transiently reliable regions of increased activity for many cells, (2) multiple patches of activity that were sometimes observed in analogous maze areas, and (3) cells displaying substantial decreases in firing rate between baseline and maze-run conditions that could not be explained by a simple relationship between firing rate and a pigeon's speed. These observations suggest that pigeon HF cells may be coding for an unspecified behavioral/motivational/environmental factors in addition to a pigeon's momentary location. The data further suggest that the spatial ecology and evolutionary history of different species may be a critical feature shaping how HF neurons capture properties of space.
To investigate conjoint stimulus control over place cells, Fenton et al. (J Gen Physiol 116:191-209, 2000a) recorded while rats foraged in a cylinder with 45 degrees black and white cue cards on the wall. Card centers were 135 degrees apart. In probe trials, the cards were rotated together or apart by 25 degrees . Firing field centers shifted during these trials, stretching and shrinking the cognitive map. Fenton et al. (2000b) described this deformation with an ad hoc vector field equation. We consider what sorts of neural network mechanisms might be capable of accounting for their observations. In an abstract, maximum likelihood formulation, the rat's location is estimated by a conjoint probability density function of landmark positions. In an attractor neural network model, recurrent connections produce a bump of activity over a two-dimensional array of cells; the bump's position is influenced by landmark features such as distances or bearings. If features are chosen with appropriate care, the attractor network and maximum likelihood models yield similar results, in accord with previous demonstrations that recurrent neural networks can efficiently implement maximum likelihood computations (Pouget et al. Neural Comput 10:373-401, 1998; Deneve et al. Nat Neurosci 4:826-831, 2001).