Abstract
As the size and complexity of network simulations accessible to computational neuroscience grows, new avenues open for research into extracellularly recorded electric signals. Biophysically detailed simulations permit the identification of the biological origins of the different components of recorded signals, the evaluation of signal sensitivity to different anatomical, physiological, and geometric factors, and selection of recording parameters to maximize the signal information content. Simultaneously, virtual extracellular signals produced by these networks may become important metrics for neuro-simulation validation. To enable efficient calculation of extracellular signals from large neural network simulations, we have developed BlueRecording, a pipeline consisting of standalone Python code, along with extensions to the Neurodamus simulation control application, the CoreNEURON computation engine, and the SONATA data format, to permit online calculation of such signals. In particular, we implement a general form of the reciprocity theorem, which is capable of handling non-dipolar current sources, such as may be found in long axons and recordings close to the current source, as well as complex tissue anatomy, dielectric heterogeneity, and electrode geometries. To our knowledge, this is the first application of this generalized (i.e., non-dipolar) reciprocity-based approach to simulate EEG recordings. We use these tools to calculate extracellular signals from an in silico model of the rat somatosensory cortex and hippocampus and to study signal contribution differences between regions and cell types.
Competing Interest Statement
The authors have declared no competing interest.
Footnotes
↵* joseph.tharayil{at}epfl.ch
We clarify that the commonly-used dipole-based approaches are a special case, under the assumption of a constant E-field, of the more general reciprocity approach used in our toolbox. We have added supplementary figure, Figure 9, demonstrating that the assumption of constant E field does not hold for ECoG recordings, necessitating the use of the general reciprocity approach. We have added subsection 3.3, in which we study of the relationship between firing rates of different cell types and the recorded EEG in response to a simulated whisker flick in the somatosensory cortex model. We have added subsection 3.4, in which we have applied the BlueRecording toolbox to a model of the hippocampus, demonstrating its versatility with respect to circuit models. Armando Romani and Elvis Boci have been added to the author list
