Modeling brain activity
To model brain activity successfully, we incorporate the main features of
structures ranging from the submicron scale of synapses to the whole-brain, and from
millisecond timespans (action potentials) to many seconds (adaptation, habituation)
and longer (learning).
Our main approach is to use the sheer numbers of neurons in even a small piece
of brain tissue to work with average properties, rather than those of individual
cells. This enables us to link stimuli to activity via physiologically realistic
approximations to neural responses and interactions. The outcomes are then related
to measurements by computing activity-related quantities that correspond to what is
measured in experiments and diagnostics.
Our approach has succeeded in modeling a range of electroencephalographic (EEG) data,
including time dependences, spectra, spatial structure, impulse responses (evoked
response potentials), and differences depending on age, sex, and disorder (see
Applications link). The physiological parameters that are inferred by matching model
predictions to data are consistent with
independent measures and thus open a new noninvasive window on brain function.
Currently, we are extending our model to understand finer scale structure in
visual processing, and to incorporate additional aspects of physiology and
anatomy. We are also continuing to explore its existing predictions, including
those in the nonlinear regime, and using new analysis techniques (see Nonlinear
projects).
Key Publications
Robinson, P. A., Rennie, C. J., and Wright, J. J. (1997).
Propagation and Stability of Waves of Electrical Activity in
the Cerebral
Cortex, Physical Review
E, 56, 826-840.
Rennie, C. J., Robinson, P. A., and Wright, J. J. (2002). Unified
Neurophysical Model of EEG Spectra and Evoked Potentials, Biol.
Cybernetics, 86, 457-471.
Robinson, P. A., Rennie, C. J., and Rowe, D. L. (2002). Dynamics
of Large-Scale Brain Activity in Normal Arousal States and
Epileptic Seizures, Physical Review E, 65, 041924, 1-9.
Robinson, P. A., Rennie, C. J., Rowe, D. L., and O'Connor, S.
C. (2004). Estimation of Multiscale Neurophysiological Parameters
by EEG Means: Consistency and Complementarity vs. Independent
Measures, Human
Brain Mapping, 23, 53-72.
Rowe, D. L., Robinson, P. A., and Rennie, C. J. (2004). Estimation
of Neurophysiological Parameters from the Waking EEG Using a
Biophysical Model of Brain Dynamics, Journal of Theoretical
Biology, 231, 413-433.
Robinson, P. A., Drysdale, P. M., Van der Merwe,
H., Kyriakou, E., Rigozzi, M.,
Germanoska, B., and Rennie, C. J. (2005). New Aspects of
the Stimulus-Activity-BOLD
Relationship and Optimal ER-BOLD Pulse Sequences, Neuroimage,
submitted.
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