Modelling event-related responses in the brain

@article{David2005ModellingER,
  title={Modelling event-related responses in the brain},
  author={Olivier David and Lee M. Harrison and Karl J. Friston},
  journal={NeuroImage},
  year={2005},
  volume={25},
  pages={756-770}
}
The aim of this work was to investigate the mechanisms that shape evoked electroencephalographic (EEG) and magneto-encephalographic (MEG) responses. We used a neuronally plausible model to characterise the dependency of response components on the models parameters. This generative model was a neural mass model of hierarchically arranged areas using three kinds of inter-area connections (forward, backward and lateral). We investigated how responses, at each level of a cortical hierarchy… Expand
CHAPTER 33 – Neuronal models of EEG and MEG
TLDR
This chapter uses neural-mass models to emulate common M/EEG phenomena and addresses their underlying mechanisms, and it is shown how the parameters of these models can be estimated from real data. Expand
Dynamic causal modelling of evoked potentials: A reproducibility study
TLDR
The validity of DCM is established by assessing its reproducibility across subjects by using an oddball paradigm to elicit mismatch responses and evaluating three different connectivity models, which showed that a more complex model is not necessarily the most likely model. Expand
Dynamic causal modeling of evoked responses in EEG and MEG
TLDR
A Bayesian procedure to estimate the parameters of this extended forward model is described, characterizing the role of changes in cortico-cortical coupling, in the genesis of ERPs, and showing that category- or context-specific coupling among cortical regions can be assessed explicitly, within a mechanistic, biologically motivated inference framework. Expand
Causal modelling of evoked brain responses.
The aim of this thesis was to test predictive coding as a model of cortical organization and function using a specific brain response, the mismatch negativity (MMN), and a novel tool for connectivityExpand
Dynamic causal modelling of evoked responses: The role of intrinsic connections
TLDR
The modulation of intrinsic connectivity to the DCM framework is introduced, useful for testing hypotheses about adaptation of neuronal responses to local influences, in relation to influences that are mediated by long-range extrinsic connections from other sources. Expand
Dynamic causal models for EEG
TLDR
This chapter describes the dynamic causal modelling (DCM) of event-related responses measured withEEG or magnetoencephalography, which uses a biologically informed causal model to make inferences about the underlying neuronal networks generating responses. Expand
A Dynamic Causal Model of the Coupling Between Pulse Stimulation and Neural Activity
TLDR
A dynamic causal model that can explain context-dependent changes in neural responses, in the rat barrel cortex, to an electrical whisker stimulation at different frequencies is presented and can be used to invert the hemodynamic measurements of changes in blood flow to estimate the underlying neural activity. Expand
Modelling Theta-Band Connectivity Between Occipital and Frontal Lobes: A Methodological MEG Study
TLDR
A mathematical model of wave propagation is presented, motivated by current neuroscience literature, and the utility of the method is demonstrated in a clinical sample of schizophrenia patients, to investigate event related cortico-cortical brain dynamics in individuals and groups in the task positive state. Expand
Repetition suppression and plasticity in the human brain
TLDR
This study shows that auditory perceptual learning is associated with repetition-dependent plasticity in the human brain, and it is remarkable that distinct changes in intrinsic and extrinsic connections could be quantified so reliably and non-invasively using EEG. Expand
A neural mass model of spectral responses in electrophysiology
TLDR
This work establishes a forward or generative model of electrophysiological recordings for psychopharmacological studies and shows how neuromodulatory effects can be modelled by adding adaptation currents to a simple phenomenological model of EEG. Expand
...
1
2
3
4
5
...

References

SHOWING 1-10 OF 82 REFERENCES
Electroencephalogram and visual evoked potential generation in a mathematical model of coupled cortical columns
TLDR
It was found that the previously developed lumped-parameter model of a single cortical column could produce a large variety of EEG-like waveforms and rhythms and suggest that the scalp-recorded EP is at least partially due to a phase reordering of the ongoing activity. Expand
Evaluation of different measures of functional connectivity using a neural mass model
TLDR
A neural mass model is exploited by evaluating different measures of statistical dependencies among MEG or EEG signals that are mediated by neuronal coupling to suggest that methods based on the concept of generalised synchronisation are the most sensitive when interactions encompass different frequencies. Expand
Neural dynamics and the fundamental mechanisms of event-related brain potentials.
TLDR
These findings support a predominant role for stimulus-evoked activity in sensory ERP generation, and outline both logic and methodology necessary for differentiating evoked and phase resetting contributions to cognitive and motor ERPs in future studies. Expand
Computational model of thalamo-cortical networks: dynamical control of alpha rhythms in relation to focal attention.
TLDR
The hypothesis that this basic neurophysiological mechanism can account for the general observation that enhanced attention given to a certain stimulus (the focus) is coupled to inhibition of attention to other stimuli (the surround) is formed. Expand
Relating Macroscopic Measures of Brain Activity to Fast, Dynamic Neuronal Interactions
In this article we used biologically plausible simulations of coupled neuronal populations to address the relationship between phasic and fast coherent neuronal interactions and macroscopic measuresExpand
A neural mass model for MEG/EEG: coupling and neuronal dynamics
TLDR
This work extended the classical nonlinear lumped-parameter model of alpha rhythms, initially developed by Lopes da Silva and colleagues, to generate more complex dynamics and shows that the whole spectrum of MEG/EEG signals can be reproduced within the oscillatory regime of this model by simply changing the population kinetics. Expand
Model of brain rhythmic activity
TLDR
A family of spectral curves could be obtained which simulated the development of the EEG as function of age from a predominantly low frequency to a clearly rhythmic type of signal, which was shown to depend mainly on the feedback coupling parameters. Expand
The brain wave equation: a model for the EEG
Abstract Both spontaneous and evoked potentials measured on the surface of the head are believed due to postsynaptic potentials in vertically oriented neurons in the cortex. Potential differencesExpand
A model of the spatial-temporal characteristics of the alpha rhythm.
Unified neurophysical model of EEG spectra and evoked potentials
TLDR
A broad range of ongoing and transient electrocortical activity can be understood within a common framework, which is parameterized by values that are directly related to physiological and anatomical quantities. Expand
...
1
2
3
4
5
...