Topological analysis of hippocampal CA1 co-firing graphs

Gava GP
McHugh SB
Lefèvre L
Lopes-Dos-Santos V
Trouche S
El-Gaby M
Schultz SR
Dupret D

Each matrix contains the hippocampal CA1 co-firing graphs computed using the spike trains of pyramidal cells recorded from mice during active exploratory behaviour (i.e., excluding immobility epochs and sharp-wave/ripples) in four different tasks: (i) conditioned place preference (CPP), (ii) exploration of a novel context (without reward), (iii) spontaneous place preference (SPP) for a novel context and (iv) rewarded exploration of an otherwise familiar context (without CPP).

In these co firing graphs, each node represents one cell; the edge linking any two nodes represents the coactivity of that cell pair, with a weight computed as the Pearson correlation coefficient between their spike trains.

Each co-firing graph is defined by its adjacency matrix, whose elements are the edges of the graph / co-firing relationships between pairs of neurons indexed by the rows and columns of the matrix.

For each matrix, the code provided (python 3.6) analyses the co-firing relationships among pyramidal cells for the 6 sessions recorded on that task day. Graph-theoretical measures are obtained for each co-firing graph (one graph per task session) and their dynamics across the 6 task sessions are analysed. See the paper 'Integrating new memories into the hippocampal network activity space' for description of the task and detailed methods. Notably, these example co-firing graphs and codes relate to figures 1, 2 and extended data figure 2.

Example co-firing graph. Each node represents one cell. Each edge represents the co-firing association of one cell pair, color-coded according to their correlation’s sign and width proportional to the edge’s absolute value.
Year Published
Funders & Grant Numbers
BBSRC, UKRI (BB/N002547/1)
MRC, UKRI (MC_UU_12024/3)
MRC, UKRI (MC_UU_00003/4)
University of Oxford
First Published In
Gava GP, McHugh SB, Lefèvre L, Lopes-Dos-Santos V, Trouche S, El-Gaby M, Schultz SR, Dupret D
2021. Nat. Neurosci., 24:326–330.
Dupret Group

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