Coupled Electromagnetic-Electrophysiological Modeling of Neural Circuits
Much of our knowledge about the brain is derived from extracellular recordings of the electric
fields produced by neural activity. However, interpretation of these signals is nontrivial. In par-
ticular, it is difficult to link macro-scale observations of electric fields with micro-scale neural
activity. In silico models of neural tissue may help to bridge these scales, shedding light onto
the biophysical basis of voltage signals from extracellular recordings. Simulating extracellular
fields produced by neural activity is nevertheless a computationally difficult problem. In this
thesis, we use a reciprocity-based approach to efficiently simulate neural recordings. To do so,
we have developed a state-of-the-art software package, called BlueRecording, to rapidly and
flexibly calculate voltage signals from large-scale simulations of neural circuits. BlueRecording
is extensively tested, and is shown to outperform previously available software in both speed
and accuracy.
We then use BlueRecording, in conjunction with the Blue Brain Project model of the rat
somatosensory cortex, to investigate the mechanisms underlying the somatosensory evoked
response to a whisker flick stimulation. We find that the initial positive deflection in the signal
is the result of direct thalamic input onto pyramidal cells, primarily in cortical Layer 2/3 and
5, while the initial negative deflection is driven largely by cortico-cortical inhibition, though
thalamic inputs to Layer 6 also play a role. We also use BlueRecording and the Blue Brain
Project somatosensory cortex model to study the inverse current source density technique
to estimate the distribution of neural currents on the basis of voltage signals recorded from
penetrating electrodes. We find that as the density of the recording array increases, the
estimated current source density diverges from the expected distribution. We suggest two
possible explanations for this phenomenon, both related to the violation, in the simulated
neural circuit, of the assumptions underlying the inverse current source density technique.
Finally, we apply the reciprocity-based approach to calculating neural signals to develop a
simplified model of the evoked compound action potential signal generated by vagus nerve
stimulation. We determine that in multifascicular nerves, incomplete activation of the fiber
population in a fascicle has a strong impact on the recorded signal. We find that the signal
is sensitive to the orientation of both the stimulus and recording electrodes relative to the
fascicles, and that, contrary to popular belief, the amplitude of the recorded signal is not
monotonic with respect to fiber activation.
Our approach of simulating extracellular recordings of neural circuit models is therefore able
to generate insights into the relationship between micro-scale activity and macro-scale signals.
In addition to explaining the biophysical basis of observed phenomena, which may lead to clinically relevant insights, this approach may also be useful in designing more effective recording
techniques, and inform the development of closed-loop neuronstimulation applications.
Prof. Henning Paul-Julius Stahlberg (président) ; Prof. Henry Markram, Dr Esra Neufeld (directeurs) ; Dr Wolfger von der Behrens, Prof. Gaute Einevoll, Prof. Viktor Jirsa (rapporteurs)
2024
Lausanne
2024-12-16
11176
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