Steady states and global dynamics of electrical activity in the cerebral cortex

Robinson, P. A.; Rennie, Chris; Wright, J. J.; Bourke, Paul

doi:10.1103/physreve.58.3557

Cited by 101 publications

(112 citation statements)

References 14 publications

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“…Unless otherwise noted, we use the parameter values as listed in Appendix for numerical simulations. These values result from physiological experiments, and can be found in previous studies (Breakspear et al 2006;Chen et al 2014;Robinson et al 1998Robinson et al , 2001Robinson et al , 2003. At the same time, some parameter values are slightly adjusted to generate stable SWDs oscillation in corticothalamic circuit.…”

Section: Model Descriptionmentioning

confidence: 91%

Control of absence seizures induced by the pathways connected to SRN in corticothalamic system

Guo

Wang

2014

Cogn Neurodyn

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The cerebral cortex, thalamus and basal ganglia together form an important network in the brain, which is closely related to several nerve diseases, such as parkinson disease, epilepsy seizure and so on. Absence seizure can be characterized by 2-4 Hz oscillatory activity, and it can be induced by abnormal interactions between the cerebral cortex and thalamus. Many experimental results have also shown that basal ganglia are a key neural structure, which closely links the corticothalamic system in the brain. Presently, we use a corticothalamic-basal ganglia model to study which pathways in corticothalamic system can induce absence seizures and how these oscillatory activities can be controlled by projections from the substantia nigra pars reticulata (SNr) to the thalamic reticular nucleus (TRN) or the specific relay nuclei (SRN) of the thalamus. By tuning the projection strength of the pathway ''Excitatory pyramidal cortex-SRN'', ''SRN-Excitatory pyramidal cortex'' and ''SRN-TRN'' respectively, different firing states including absence seizures can appear. This indicates that absence seizures can be induced by tuning the connection strength of the considered pathway. In addition, typical absence epilepsy seizure state ''spike-and-slow wave discharges'' can be controlled by adjusting the activation level of the SNr as the pathways SNr-SRN and SNr-TRN open independently or together. Our results emphasize the importance of basal ganglia in controlling absence seizures in the corticothalamic system, and can provide a potential idea for the clinical treatment.

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Section: Model Descriptionmentioning

confidence: 91%

Control of absence seizures induced by the pathways connected to SRN in corticothalamic system

Guo

Wang

2014

Cogn Neurodyn

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“…They showed that the frequency content, wave velocities, frequency spectra, and responses to cortical activation of the ECoG can be reproduced by a "lumped" simulation treating small cortical areas as a single function unit. Describing the overall activity, Robinson et al (1997Robinson et al ( , 1998Robinson et al ( , 2002 developed a model based on the model of Wright and Liley. They argued that the isolated cortex is relatively stable, leading to strongly damped waves and minimal influence of boundary conditions.…”

Section: J Neurophysiolmentioning

confidence: 99%

EEG Generator—A Model of Potentials in a Volume Conductor

Avitan

Teicher

Abeles

2009

Journal of Neurophysiology

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Avitan L, Teicher M, Abeles M. EEG generator-a model of potentials in a volume conductor. J Neurophysiol 102: 3046 -3059, 2009. First published August 26, 2009 doi:10.1152/jn.91143.2008. EEG generator-a model of potentials in a volume conductor. The potential recorded over the cortex electro-corticogram (ECoG) or over the scalp [electroencephalograph (EEG)] derives from the activity of many sources known as "EEG generators." The recorded amplitude is basically a function of the unitary potential of a generator and the statistical relationship between different EEG generators in the recorded population. In this study, we first suggest a new definition of the EEG generator. We use the theory of potentials in a volume conductor and model the contribution of a single synapse activated to the surface potential. We then model the contribution of the generator to the surface potential. Once the generator and its contribution are well defined, we can quantitatively assess the degree of synchronization among generators. The measures obtained by the model for a real life scenario of a group of generators organized in a specific statistical way were consistent with the expected values that were reported experimentally. The study sheds new light on macroscopic modeling approaches which make use of mean soma membrane potential. We showed major contribution of activity of superficial apical synapses to the ECoG signal recorded relative to lower somatic or basal synapses activity. I N T R O D U C T I O N Existing models of EEG generationSince the early days of clinical electroencephalography (EEG), it has generally been accepted that rhythmic electrical activity recorded from the human scalp originates within the cerebral cortex. The critical experimental evidence was reported in 1929 by Berger in his first three reports on human EEG. He noted on numerous occasions that the amplitude of the electrical potentials was considerably greater when electrodes were placed directly on the exposed cortex or on the scalp overlying bone defects. By recording simultaneously from a pair of electrodes located subcortically in the white matter, he determined that typical EEG activity was obtained only from the cortex and not from the white matter.Many researchers have tried since that time to account for the mechanism of EEG generation. Early researchers favored the idea that the EEG represents summated action potentials of cortical neurons (Adrian and Yamsgiva 1935; Bishop 1936). In addition, an early description of a strong correlation of rhythmical single-unit activity in the pyramidal tract with rhythmical EEG waves suggested that cortical neurons are involved in EEG activity (Adrian and Moruzzi 1939). Further experiments corroborated the fact that extracellularly recorded action potentials of cortical cells often show a statistically significant relationship with EEG waves (Ajmone Marsan 1965;Creutzfeldt et al. 1957; Creuzfeldt and Meisch 1963). These relationships vary according to the type of EEG wave. Some wave types such as spindle ...

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“…, and threshold J i ; they fit the static nonlinearity of real neurons for p i in roughly the range 0.5 … 3.0 (Anderson et al 2001;Heeger 1992) but may also be seen as a polynomial approximation of sigmoid rate-functions employed by others in the most relevant regime of low and intermediate activity (Amari 1977;Haken 1996, 1997;Rennie et al 1999;Robinson et al 1997Robinson et al , 1998Taylor 1999;Cowan 1972, 1973). Note that all potentials are measured against a resting potential of zero without loss of generality: Any non-zero resting potential would appear in (1) as a constant offset on the right hand side, say, þ/ bg i : A linear transformation / i ðx; tÞ ¼ / i ðx; tÞ À / bg i would move these offsets into the arguments of the rate-functions where they could be integrated into the firing thresholds leaving us with the form (1) again, this time for the transformed potentials (the ''firing thresholds'', so-to-speak, measure the relative distance between the ''true'' resting potential and the ''true'' threshold).…”

Section: Neural Field Modelmentioning

confidence: 95%

“…These models take the form of partial differential equations comprising diffusively coupled local nonlinear oscillators. They are useful to explain properties of experimental EEG data like its frequency spectrum, wave propagation, and selforganising excitation patterns (Ingber 1994;Haken 1996, 1997;Rennie et al 1999;Robinson et al 1997Robinson et al , 1998Hutt et al 2003;Wright et al 2003;Robinson and Rennie 2006;Coombes et al 2007). …”

Section: Introductionmentioning

confidence: 99%

“…In contrast, maps are well observable in optical recordings, e.g., Tsodyks et al (1999); Kenet et al (2003); Tucker and Katz (2003). Thereby, complementary information about functional cortical processes is reflected on different scales, such that it is of interest to study how these resolution scales relate to each other, and how cortical microcircuits for feature specificity give rise to more globally observable activation patterns like the EEG, MEG, or fMRI (Friston 2005;Rennie et al 1999;Robinson et al 1998;Wright et al 2003;Robinson and Rennie 2006).…”

Section: Introductionmentioning

confidence: 99%

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Tuned solutions in dynamic neural fields as building blocks for extended EEG models

Wennekers

2008

Cognitive Neurodynamics

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The most prominent functional property of cortical neurons in sensory areas are their tuned receptive fields which provide specific responses of the neurons to external stimuli. Tuned neural firing indeed reflects the most basic and best worked out level of cognitive representations. Tuning properties can be dynamic on a short time-scale of fractions of a second. Such dynamic effects have been modeled by localised solutions (also called ''bumps'' or ''peaks'') in dynamic neural fields. In the present work we develop an approximation method to reduce the dynamics of localised activation peaks in systems of n coupled nonlinear d-dimensional neural fields with transmission delays to a small set of delay differential equations for the peak amplitudes and widths only. The method considerably simplifies the analysis of peaked solutions as demonstrated for a two-dimensional example model of neural feature selectivity in the brain. The reduced equations describe the effective interaction between pools of local neurons of several (n) classes that participate in shaping the dynamic receptive field responses. To lowest order they resemble neural mass models as they often form the base of EEG-models. Thereby they provide a link between functional small-scale receptive field models and more coarse-grained EEG-models. More specifically, they connect the dynamics in feature-selective cortical microcircuits to the more abstract local elements used in coarse-grained models. However, beside amplitudes the reduced equations also reflect the sharpness of tuning of the activity in a d-dimensional feature space in response to localised stimuli.

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Steady states and global dynamics of electrical activity in the cerebral cortex

Cited by 101 publications

References 14 publications

Control of absence seizures induced by the pathways connected to SRN in corticothalamic system

Control of absence seizures induced by the pathways connected to SRN in corticothalamic system

EEG Generator—A Model of Potentials in a Volume Conductor

Tuned solutions in dynamic neural fields as building blocks for extended EEG models

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