RESUMEN
A neural field model of the brain is used to represent brain states using physiologically based parameters rather than arbitrary, discrete sleep stages. Each brain state is represented as a point in a physiologically parametrized space. Over time, changes in brain state cause these points to trace continuous trajectories, unlike the artificial discrete jumps in sleep stage that occur with traditional sleep staging. The discrete Rechtschaffen and Kales sleep stages are associated with regions in the physiological parameter space based on their electroencephalographic features, which enables interpretation of traditional sleep stages in terms of physiological trajectories. Wake states are found to be associated with strong positive corticothalamic feedback compared to sleep. The existence of physiologically valid trajectories between brain states in the model is demonstrated. Actual trajectories for an individual can be determined by fitting the model using EEG alone, and enable analysis of the physiological differences between subjects.
Asunto(s)
Nivel de Alerta/fisiología , Ondas Encefálicas/fisiología , Encéfalo/fisiología , Modelos Neurológicos , Dinámicas no Lineales , Electroencefalografía , Análisis de Fourier , Humanos , Vías Nerviosas/fisiología , Sueño/fisiologíaRESUMEN
OBJECTIVE: To investigate the properties of a sleep spindle harmonic oscillation previously predicted by a theoretical neural field model of the brain. METHODS: Spindle oscillations were extracted from EEG data from nine subjects using an automated algorithm. The power and frequency of the spindle oscillation and the harmonic oscillation were compared across subjects. The bicoherence of the EEG was calculated to identify nonlinear coupling. RESULTS: All subjects displayed a spindle harmonic at almost exactly twice the frequency of the spindle. The power of the harmonic scaled nonlinearly with that of the spindle peak, consistent with model predictions. Bicoherence was observed at the spindle frequency, confirming the nonlinear origin of the harmonic oscillation. CONCLUSIONS: The properties of the sleep spindle harmonic were consistent with the theoretical modeling of the sleep spindle harmonic as a nonlinear phenomenon. SIGNIFICANCE: Most models of sleep spindle generation are unable to produce a spindle harmonic oscillation, so the observation and theoretical explanation of the harmonic is a significant step in understanding the mechanisms of sleep spindle generation. Unlike seizures, sleep spindles produce nonlinear effects that can be observed in healthy controls, and unlike the alpha oscillation, there is no linearly generated harmonic that can obscure nonlinear effects. This makes the spindle harmonic a good candidate for future investigation of nonlinearity in the brain.
Asunto(s)
Ondas Encefálicas/fisiología , Encéfalo/fisiología , Sueño/fisiología , Adulto , Femenino , Humanos , Masculino , Modelos Neurológicos , PolisomnografíaRESUMEN
A computationally efficient, biophysically-based model of neuronal behavior is presented; it incorporates ion channel dynamics in its two fast ion channels while preserving simplicity by representing only one slow ion current. The model equations are shown to provide a wide array of physiological dynamics in terms of spiking patterns, bursting, subthreshold oscillations, and chaotic firing. Despite its simplicity, the model is capable of simulating an extensive range of spiking patterns. Several common neuronal behaviors observed in vivo are demonstrated by varying model parameters. These behaviors are classified into dynamical classes using phase diagrams whose boundaries in parameter space prove to be accurately delineated by linear stability analysis. This simple model is suitable for use in large scale simulations involving neural field theory or neuronal networks.
Asunto(s)
Potenciales de Acción/fisiología , Modelos Neurológicos , Neuronas/fisiología , Animales , Biofisica , Encéfalo/citología , Simulación por Computador , Humanos , Dinámicas no Lineales , Tiempo de ReacciónRESUMEN
This paper examines nonlinear effects in a neural field model of the corticothalamic system to predict the EEG power spectrum of sleep spindles. Nonlinearity in the thalamic relay nuclei gives rise to a spindle harmonic visible in the cortical EEG. By deriving an analytic expression for nonlinear spectrum, the power in the spindle harmonic is predicted to scale quadratically with the power in the spindle oscillation. By isolating sleep spindles from background sleep in experimental EEG data, the spindle harmonic is directly observed.
Asunto(s)
Relojes Biológicos/fisiología , Modelos Neurológicos , Sueño/fisiología , Corteza Cerebral/fisiología , Electroencefalografía/métodos , Humanos , Red Nerviosa/fisiología , Dinámicas no Lineales , Procesamiento de Señales Asistido por Computador , Tálamo/fisiologíaRESUMEN
OBJECTIVE: To investigate age trends, sex differences, and splitting of alpha peaks of the EEG spectrum in the healthy population. METHODS: An automated multi-site algorithm was used to parametrize the alpha rhythm in 1498 healthy subjects aged 6-86 years. Alpha peaks identified from multiple electrode sites were organized into clusters of similar frequencies whose sex differences and age trends were investigated. RESULTS: Significant age-related trends were observed for frequency, position, and amplitude of dominant alpha peaks. Occipital sites had alpha clusters of higher average frequency, higher power, and greater presence across the scalp. Frequency and power differences were found between the sexes. CONCLUSION: Observed increases in alpha frequency in children and decreases in the elderly were consistent with those from earlier studies. A large fraction of participants (≈ 44%) showed multiple distinct alpha rhythm thus investigations which only examine the alpha frequency with the highest peak power can produce misleading results. The strong dependence of alpha frequency on age and anterior-posterior position indicates use of a fixed alpha frequency band is insufficient to capture the full characteristics of the alpha rhythm. SIGNIFICANCE: This study establishes alpha rhythm parameter ranges (including power and frequency) in the healthy population, and quantifies the variation in alpha frequency across the scalp. The automated characterization enables objective evaluations of alpha band activities over large samples. These findings are potentially useful in testing theories of alpha generation, where splitting of the alpha rhythm has been theoretically predicted to occur in individuals with large differences in axon length between anterior and posterior corticothalamic loops.
Asunto(s)
Envejecimiento/fisiología , Ritmo alfa/fisiología , Encéfalo/fisiología , Caracteres Sexuales , Adolescente , Adulto , Anciano , Anciano de 80 o más Años , Algoritmos , Niño , Análisis por Conglomerados , Electroencefalografía/métodos , Femenino , Humanos , Masculino , Persona de Mediana Edad , Distribución Normal , Adulto JovenRESUMEN
OBJECTIVE: The physiological basis for the changes in auditory evoked potentials (AEPs) during development and aging is currently unknown. This study investigates age- and task-related changes via a mathematical model of neuronal activity, which allows a number of physiological changes to be inferred. METHODS: A quantitative, physiology-based model of activity in cortical and thalamic neurons was used to analyze oddball AEPs recorded from 1498 healthy subjects aged 6-86 years. RESULTS: Differences between standard and target responses can be largely explained by differences in connection strengths between thalamic and cortical neurons. The time it takes signals to travel between the thalamus and cortex decreases during development and increases during aging. Strong age trends are also seen in intracortical and thalamocortical neuronal connection strengths. CONCLUSIONS: Changes in AEP latency can be attributed to changes in the thalamocortical signal propagation time. Large changes in the connection strengths between neuronal populations occur during development, resulting in increased thalamocortical inhibition and decreased thalamocortical excitation. Standard and target parameters are similar in children but diverge during adolescence, due to changes in thalamocortical loop activity. SIGNIFICANCE: Model-based AEP analysis links age-related changes in brain electrophysiology to underlying changes in brain anatomy and physiology, and yields quantitative predictions of several currently unknown physiological and anatomical properties of the brain.
Asunto(s)
Envejecimiento/fisiología , Percepción Auditiva/fisiología , Encéfalo/crecimiento & desarrollo , Electroencefalografía/métodos , Modelos Neurológicos , Estimulación Acústica/métodos , Adolescente , Adulto , Anciano , Anciano de 80 o más Años , Encéfalo/anatomía & histología , Niño , Potenciales Evocados Auditivos/fisiología , Femenino , Humanos , Masculino , Persona de Mediana Edad , Adulto JovenRESUMEN
OBJECTIVE: To investigate age-associated changes in physiologically-based EEG spectral parameters in the healthy population. METHODS: Eyes-closed EEG spectra of 1498 healthy subjects aged 6-86 years were fitted to a mean-field model of thalamocortical dynamics in a cross-sectional study. Parameters were synaptodendritic rates, cortical wave decay rates, connection strengths (gains), axonal delays for thalamocortical loops, and power normalizations. Age trends were approximated using smooth asymptotically linear functions with a single turning point. We also considered sex differences and relationships between model parameters and traditional quantitative EEG measures. RESULTS: The cross-sectional data suggest that changes tend to be most rapid in childhood, generally leveling off at age 15-20 years. Most gains decrease in magnitude with age, as does power normalization. Axonal and dendritic delays decrease in childhood and then increase. Axonal delays and gains show small but significant sex differences. CONCLUSIONS: Mean-field brain modeling allows interpretation of age-associated EEG trends in terms of physiological processes, including the growth and regression of white matter, influencing axonal delays, and the establishment and pruning of synaptic connections, influencing gains. SIGNIFICANCE: This study demonstrates the feasibility of inverse modeling of EEG spectra as a noninvasive method for investigating large-scale corticothalamic dynamics, and provides a basis for future comparisons.
Asunto(s)
Envejecimiento/fisiología , Corteza Cerebral/fisiología , Electroencefalografía , Modelos Neurológicos , Tálamo/fisiología , Adolescente , Adulto , Anciano , Anciano de 80 o más Años , Axones , Niño , Estudios Transversales , Dendritas , Femenino , Humanos , Masculino , Persona de Mediana Edad , Factores Sexuales , Factores de Tiempo , Adulto JovenRESUMEN
A recent continuum model of the large scale electrical activity of the thalamocortical system is generalized to include cholinergic modulation. The model is examined analytically and numerically to determine the effect of acetylcholine (ACh) on its steady states, linear stability, spectrum, and temporal responses. Changing the ACh concentration moves the system between zones of one, three, and five steady states, showing that neuromodulation of synaptic strength is a possible mechanism by which multiple steady states emerge in the brain. The lowest firing rate steady state is always stable, and subsequent fixed points alternate between stable and unstable. Increasing ACh concentration changes the form of the spectrum. Increasing the tonic level of ACh concentration increases the magnitudes of the N100 and P200 in the evoked response potential (ERP), without changing the timing of these peaks. Driving the system with a pulse of cholinergic activity results in a transient increase in the firing rate of cortical neurons that lasts over 10s. Step-like increases in cortical ACh concentration cause increases in the firing rate of cortical neurons, with rapid responses due to fast acting nicotinic receptors and slower responses due to muscarinic receptor suppression of intracortical connections.
Asunto(s)
Acetilcolina/fisiología , Corteza Cerebral/metabolismo , Simulación por Computador , Modelos Neurológicos , Neuronas/fisiología , Tálamo/metabolismo , Animales , Electroencefalografía , Potenciales Evocados/fisiología , Humanos , Receptores Muscarínicos/metabolismo , Receptores Nicotínicos/metabolismo , Transmisión Sináptica/fisiologíaRESUMEN
Evoked potentials are the transient electrical responses caused by changes in the brain following stimuli. This work uses a physiology-based continuum model of neuronal activity in the human brain to calculate theoretical cortical auditory evoked potentials (CAEPs) from the model's linearized response. These are fitted to experimental data, allowing the fitted parameters to be related to brain physiology. This approach yields excellent fits to CAEP data, which can then be compared to fits of EEG spectra. It is shown that the differences between resting eyes-open EEG and standard CAEPs can be explained by changes in the physiology of populations of neurons in corticothalamic pathways, with notable similarities to certain aspects of slow-wave sleep. This pilot study demonstrates the ability of our model-based fitting method to provide information on the underlying physiology of the brain that is not available using standard methods.
Asunto(s)
Corteza Auditiva/fisiología , Vías Auditivas/fisiología , Potenciales Evocados Auditivos/fisiología , Modelos Neurológicos , Estimulación Acústica/métodos , Corteza Auditiva/citología , Fenómenos Biofísicos , Biofisica , Electroencefalografía/métodos , Humanos , Neuronas/fisiologíaRESUMEN
The identification of alpha rhythm in the human electroencephalogram (EEG) is generally a laborious task involving visual inspection of the spectrum. Moreover the occurrence of multiple alpha rhythms is often overlooked. This paper seeks to automate the process of identifying alpha peaks and quantifying their frequency, amplitude and width as a function of position on the scalp. Experimental EEG was fitted with parameterized spectra spanning the alpha range, with results categorized by multi-site criteria into three distinct classes: no distinguishable alpha peak, a single alpha peak, and two alpha peaks. The technique avoids visual bias, integrates spatial information, and is automated. We show that multiple alpha peaks are a common feature of many spectra.
Asunto(s)
Ritmo alfa/estadística & datos numéricos , Electroencefalografía/métodos , Electroencefalografía/estadística & datos numéricos , Adulto , Algoritmos , Procesamiento Automatizado de Datos , Femenino , Humanos , Masculino , Persona de Mediana Edad , Variaciones Dependientes del ObservadorRESUMEN
Using a standardized database of EEG data, recorded during the habituation and oddball paradigms, changes in the auditory event-related potential (ERP) are demonstrated on the time scale of seconds and minutes. Based on previous research and a mathematical model of neural activity, neural mechanisms that could account for these changes are proposed. When the stimulus tones are not relevant to a task, N100 magnitude decreases substantially for the first repetition of a stimulus pattern and increases in response to a variant tone. It is argued these short-term changes are consistent with the hypothesis that there is a refractory period in the neural elements underlying the ERP. In the oddball paradigm, when the stimulus tones are task-relevant, the magnitudes of both N100 and P200 for backgrounds decrease over the entire six-minute recording session. It is argued that these changes are mediated by a decreasing arousal level, and consistent with this, a subject's electrodermal activity (EDA) is shown to reduce over the recording session. By fitting ERPs generated by a biophysical model of neural activity, it is shown that the changes in the background ERPs over the recording session can be reproduced by changing the strength of connections between populations of cortical neurons. For ERPs elicited by infrequent stimuli, there is no corresponding trend in the magnitudes of N100 or P300 components. The effects of stimuli serial order on ERPs are also assessed, showing that the N100 for background ERPs and the N100 and P300 for target ERPs increases as the probability, and expectancy, of receiving a task relevant stimulus increases. Cortical neuromodulation by acetylcholine (ACh) is proposed as a candidate mechanism to mediate the ERP changes associated with attention and arousal.
Asunto(s)
Nivel de Alerta/fisiología , Atención/fisiología , Corteza Cerebral/fisiología , Electroencefalografía/métodos , Potenciales Evocados/fisiología , Acetilcolina/fisiología , Potenciales de Acción/fisiología , Adulto , Simulación por Computador , Potenciales Relacionados con Evento P300/fisiología , Humanos , Procesamiento de Imagen Asistido por Computador , Masculino , Red Nerviosa/fisiología , Neuronas/fisiología , Transmisión Sináptica/fisiología , Adulto JovenRESUMEN
A recent continuum model of the large scale electrical activity of the cerebral cortex is generalized to include cholinergic modulation. In this model, dynamic modulation of synaptic strength acts over the time scales of nicotinic and muscarinic receptor action. The cortical model is analyzed to determine the effect of acetylcholine (ACh) on its steady states, linear stability, spectrum, and temporal responses to changes in subcortical input. ACh increases the firing rate in steady states of the system. Changing ACh concentration does not introduce oscillatory behavior into the system, but increases the overall spectral power. Model responses to pulses in subcortical input are affected by the tonic level of ACh concentration, with higher levels of ACh increasing the magnitude firing rate response of excitatory cortical neurons to pulses of subcortical input. Numerical simulations are used to explore the temporal dynamics of the model in response to changes in ACh concentration. Evidence is seen of a transition from a state in which intracortical inputs are emphasized to a state where thalamic afferents have enhanced influence. Perturbations in ACh concentration cause changes in the firing rate of cortical neurons, with rapid responses due to fast acting facilitatory effects of nicotinic receptors on subcortical afferents, and slower responses due to muscarinic suppression of intracortical connections. Together, these numerical simulations demonstrate that the actions of ACh could be a significant factor modulating early components of evoked response potentials.
Asunto(s)
Acetilcolina/metabolismo , Corteza Cerebral/fisiología , Modelos Neurológicos , Dinámicas no Lineales , Acetilcolina/farmacología , Animales , Corteza Cerebral/efectos de los fármacos , Corteza Cerebral/efectos de la radiación , Relación Dosis-Respuesta a Droga , Estimulación Eléctrica/métodos , Electroencefalografía , Potenciales Evocados/efectos de los fármacos , Matemática , Análisis Espectral , Factores de TiempoRESUMEN
A quantitative theory is developed for the relationship between stimulus and the resulting blood oxygen level-dependent (BOLD) functional MRI signal. The relationship of stimuli to neuronal activity during evoked responses is inferred from recent physiology-based quantitative modeling of evoked response potentials (ERPs). A hemodynamic model is then used to calculate the BOLD response to neuronal activity having the form of an impulse, a sinusoid, or an ERP-like damped sinusoid. Using the resulting equations, the BOLD response is analyzed for different forms, frequencies, and amplitudes of stimuli, in contrast with previous research, which has mostly concentrated on sustained stimuli. The BOLD frequency response is found to be closely linear in the parameter ranges of interest, with the form of a low-pass filter with a weak resonance at approximately 0.07 Hz. An improved BOLD impulse response is systematically obtained which includes initial dip and post-stimulus undershoot for some parameter ranges. It is found that the BOLD response depends strongly on the precise temporal course of the evoked neuronal activity, not just its peak value or typical amplitude. Indeed, for short stimuli, the linear BOLD response is closely proportional to the time-integrated activity change evoked by the stimulus, regardless of amplitude. It is concluded that there can be widely differing proportionalities between BOLD and peak activity, that this is the likely reason for the low level of correspondence seen experimentally between ERP sources and BOLD measurements and that non-BOLD measurements, such as ERPs, can be used to correct for this effect to obtain improved activity estimates. Finally, stimulus sequences that optimize the signal-to-noise ratio in event-related BOLD fMRI (efMRI) experiments are derived using the hemodynamic transfer function.
Asunto(s)
Encéfalo/anatomía & histología , Encéfalo/fisiología , Circulación Cerebrovascular , Oxígeno/sangre , Encéfalo/diagnóstico por imagen , Potenciales Evocados , Hemodinámica , Humanos , Modelos Neurológicos , Tomografía de Emisión de PositronesRESUMEN
A central difficulty of brain modelling is to span the range of spatio-temporal scales from synapses to the whole brain. This paper overviews results from a recent model of the generation of brain electrical activity that incorporates both basic microscopic neurophysiology and large-scale brain anatomy to predict brain electrical activity at scales from a few tenths of a millimetre to the whole brain. This model incorporates synaptic and dendritic dynamics, nonlinearity of the firing response, axonal propagation and corticocortical and corticothalamic pathways. Its relatively few parameters measure quantities such as synaptic strengths, corticothalamic delays, synaptic and dendritic time constants, and axonal ranges, and are all constrained by independent physiological measurements. It reproduces quantitative forms of electroencephalograms seen in various states of arousal, evoked response potentials, coherence functions, seizure dynamics and other phenomena. Fitting model predictions to experimental data enables underlying physiological parameters to be inferred, giving a new non-invasive window into brain function that complements slower, but finer-resolution, techniques such as fMRI. Because the parameters measure physiological quantities relating to multiple scales, and probe deep structures such as the thalamus, this will permit the testing of a range of hypotheses about vigilance, cognition, drug action and brain function. In addition, referencing to a standardized database of subjects adds strength and specificity to characterizations obtained.
Asunto(s)
Mapeo Encefálico/métodos , Encéfalo/fisiología , Electroencefalografía/métodos , Imagen por Resonancia Magnética/métodos , Modelos Neurológicos , Axones/fisiología , Fenómenos Biofísicos , Biofisica , Encéfalo/anatomía & histología , Dendritas/fisiología , Potenciales Evocados/fisiología , Humanos , Vías Nerviosas/fisiología , Sinapsis/fisiología , Transmisión Sináptica/fisiologíaRESUMEN
It is shown that new model-based electroencephalographic (EEG) methods can quantify neurophysiologic parameters that underlie EEG generation in ways that are complementary to and consistent with standard physiologic techniques. This is done by isolating parameter ranges that give good matches between model predictions and a variety of experimental EEG-related phenomena simultaneously. Resulting constraints range from the submicrometer synaptic level to length scales of tens of centimeters, and from timescales of around 1 ms to 1 s or more, and are found to be consistent with independent physiologic and anatomic measures. In the process, a new method of obtaining model parameters from the data is developed, including a Monte Carlo implementation for use when not all input data are available. Overall, the approaches used are complementary to other methods, constraining allowable parameter ranges in different ways and leading to much tighter constraints overall. EEG methods often provide the most restrictive individual constraints. This approach opens a new, noninvasive window on quantitative brain analysis, with the ability to monitor temporal changes, and the potential to map spatial variations. Unlike traditional phenomenologic quantitative EEG measures, the methods proposed here are based explicitly on physiology and anatomy.
Asunto(s)
Mapeo Encefálico , Encéfalo/anatomía & histología , Encéfalo/fisiología , Electroencefalografía , Modelos Neurológicos , Neurofisiología/métodos , Adulto , Nivel de Alerta/fisiología , Mapeo Encefálico/métodos , Electroencefalografía/métodos , Femenino , Humanos , Masculino , Persona de Mediana Edad , Método de MontecarloRESUMEN
Recent theoretical work has successfully predicted electroencephalographic spectra from physiology using a model corticothalamic system with spatially uniform parameters. The present work incorporates parameter nonuniformities into this model via the coupling they induce between spatial eigenmodes. Splitting of the spectral alpha peak, an effect seen in a small percentage of the normal population, is investigated as an illustrative special case. It is confirmed that weak splitting can arise from mode structure if the peak is sufficiently sharp, even for uniform parameters. However, it is further demonstrated that greater splitting can result from nonuniformities, and it is argued that this mechanism for split alpha is better able to account quantitatively for this effect than previously suggested alternatives of pacemakers or purely cortical resonances. On introducing nonuniformities in corticothalamic loop time delays, we find that the alpha frequency also varies as one moves from the front to the back of the head, in accord with observations, and that analogous (but less distinct) variations are seen in the beta peak. Analysis shows realistic variations of around +/-10 ms relative to the mean loop delay of approximately 80 ms can account for observed splittings of about 1 Hz. It is also suggested that subjects who display clear alpha splitting form the tail of a distribution of magnitude of cortical inhomogeneity, rather than a separate population.
Asunto(s)
Electroencefalografía/métodos , Algoritmos , Animales , Fenómenos Biofísicos , Biofisica , Corteza Cerebral/patología , Simulación por Computador , Electrofisiología , Humanos , Modelos Neurológicos , Procesamiento de Señales Asistido por Computador , Estadística como Asunto , Tálamo/patología , Factores de TiempoRESUMEN
A recent neurophysical model of brain electrical activity is outlined and applied to EEG phenomena. It incorporates single-neuron physiology and the large-scale anatomy of corticocortical and corticothalamic pathways, including synaptic strengths, dendritic propagation, nonlinear firing responses, and axonal conduction. Small perturbations from steady states account for observed EEGs as functions of arousal. Evoked response potentials (ERPs), correlation, and coherence functions are also reproduced. Feedback via thalamic nuclei is critical in determining the forms of these quantities, the transition between sleep and waking, and stability against seizures. Many disorders correspond to significant changes in EEGs, which can potentially be quantified in terms of the underlying physiology using this theory. In the nonlinear regime, limit cycles are often seen, including a regime in which they have the characteristic petit mal 3 Hz spike-and-wave form.
Asunto(s)
Encéfalo/fisiología , Modelos Neurológicos , Corteza Cerebral/fisiología , Convulsiones/fisiopatología , Tálamo/fisiologíaRESUMEN
Simulation of electrocortical activity requires (a) determination of the most crucial features to be modelled, (b) specification of state equations with parameters that can be determined against independent measurements, and (c) explanation of electrical events in the brain at several scales. We report our attempts to address these problems, and show that mutually consistent explanations, and simulation of experimental data can be achieved for cortical gamma activity, synchronous oscillation, and the main features of the EEG power spectrum including the cerebral rhythms and evoked potentials. These simulations include consideration of dendritic and synaptic dynamics, AMPA, NMDA, and GABA receptors, and intracortical and cortical/subcortical interactions. We speculate on the way in which Hebbian learning and intrinsic reinforcement processes might complement the brain dynamics thus explained, to produce elementary cognitive operations.
Asunto(s)
Corteza Cerebral/fisiología , Electroencefalografía/estadística & datos numéricos , Microscopía/estadística & datos numéricos , Modelos Neurológicos , Animales , Electroencefalografía/métodos , Humanos , Microscopía/métodos , Neuronas/fisiologíaRESUMEN
Evoked potentials -- the brain's transient electrical responses to discrete stimuli -- are modeled as impulse responses using a continuum model of brain electrical activity. Previous models of ongoing brain activity are refined by adding an improved model of thalamic connectivity and modulation, and by allowing for two populations of excitatory cortical neurons distinguished by their axonal ranges. Evoked potentials are shown to be modelable as an impulse response that is a sum of component responses. The component occurring about 100 ms poststimulus is attributed to sensory activation, and this, together with positive and negative feedback pathways between the cortex and thalamus, results in subsequent peaks and troughs that semiquantitatively reproduce those of observed evoked potentials. Modulation of the strengths of positive and negative feedback, in ways consistent with psychological theories of attentional focus, results in distinct responses resembling those seen in experiments involving attentional changes. The modeled impulse responses reproduce key features of typical experimental evoked response potentials: timing, relative amplitude, and number of peaks. The same model, with further modulation of feedback, also reproduces experimental spectra. Together, these results mean that 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.
Asunto(s)
Electroencefalografía , Modelos Neurológicos , Corteza Cerebral/citología , Corteza Cerebral/fisiología , Potenciales Evocados/fisiología , Humanos , Vías Nerviosas/fisiología , Tálamo/citología , Tálamo/fisiologíaRESUMEN
Links between electroencephalograms (EEGs) and underlying aspects of neurophysiology and anatomy are poorly understood. Here a nonlinear continuum model of large-scale brain electrical activity is used to analyze arousal states and their stability and nonlinear dynamics for physiologically realistic parameters. A simple ordered arousal sequence in a reduced parameter space is inferred and found to be consistent with experimentally determined parameters of waking states. Instabilities arise at spectral peaks of the major clinically observed EEG rhythms-mainly slow wave, delta, theta, alpha, and sleep spindle-with each instability zone lying near its most common experimental precursor arousal states in the reduced space. Theta, alpha, and spindle instabilities evolve toward low-dimensional nonlinear limit cycles that correspond closely to EEGs of petit mal seizures for theta instability, and grand mal seizures for the other types. Nonlinear stimulus-induced entrainment and seizures are also seen, EEG spectra and potentials evoked by stimuli are reproduced, and numerous other points of experimental agreement are found. Inverse modeling enables physiological parameters underlying observed EEGs to be determined by a new, noninvasive route. This model thus provides a single, powerful framework for quantitative understanding of a wide variety of brain phenomena.