Uncovering the organization of neural circuits with Generalized Phase Locking Analysis
Fig 6
GPLA of hippocampal SWRs generated by a biophysical model of [78].
(A) Hippocampal multi-compartment model. Top: Canonical circuits of CA1 and CA3. Bottom: Schematic of the whole model (blue, excitatory connections; red, inhibitory. (B) From top to bottom: Example broad band CA1 LFP trace, band-pass filtered trace of the CA1 LFP in ripple band (80–180 Hz), and population firing rate of CA1 neurons. (C) CA1 gPLVs. Triangles indicate the significance assessed based on empirical (blue triangles, p<0.05) and theoretical (red triangles) tests. (D) LFP vectors for GPLA of CA1 (blue and red curves are overlapping), superimposed to ground truth dipolar LFP profile passively generated by the two compartment models of the pyramidal cell population. The right-hand side schematic illustrates the vertical dimensions of one cell’s compartments. (E) Spike vector coefficients for CA1 in several frequency bands (left: pyramidal cells, right: interneurons). (F) Average phase lag between LFP and spike vectors across frequencies for: outcome GPLA on hippocampal SWRs, theoretical analysis of Mass2D (without and with feedforward inhibition) and MassAlpha neural mass models. Dashed green line indicate MassAlpha filtered over the frequency bands used for GPLA. (G) Difference between phases of E and I populations based on GPLA the MassAlpha neural mass model filtered in the same bands (IPSP was used as LFP proxy). (H) Spike vector resulting from GPLA jointly applied to CA1 and CA3 in the gamma band (20–40 Hz). Related Supplementary Figures: S1 Fig, Use of EPSP as LFP proxy; S2 Fig, Joint GPLA of CA3 and CA1 activities; S3 Fig, Joint GPLA of CA3 and CA1 activities.