Correlation dimension changes accompanying the occurrence of the mismatch negativity and the P3 event-related potential component

Effect of oxytocin nasal spray on auditory automatic discrimination measured by mismatch negativity

RATIONALE

As a treatment for cognitive dysfunction in schizophrenia, oxytocin nasal sprays potentially improve social cognition, facial expression recognition, and sense of smell. Mismatch negativity (MMN) is an event-related potential (ERP) reflecting auditory discrimination while MMN deficits reflect cognitive function decline in schizophrenia.

OBJECTIVES

To determine whether oxytocin nasal spray affects auditory MMN METHODS: We measured ERPs in healthy subjects during an auditory oddball task, both before and after oxytocin nasal spray administration. Forty healthy subjects were randomly assigned to either the oxytocin or placebo group. ERPs were recorded during the oddball task for all subjects before and after a 24 international unit (IU) intranasal administration, and MMN was compared between the two groups.

RESULTS

Participants who received oxytocin had significantly shorter MMN latencies than those who received a placebo. Oxytocin had no significant effect on the Change in MMN amplitude.

CONCLUSIONS

The shortened MMN latencies that were observed after oxytocin nasal spray administration suggest that oxytocin may promote the comparison-decision stage.

Relationship of auditory electrophysiological responses to magnetic resonance spectroscopy metabolites in Early Phase Psychosis

Both auditory evoked responses and metabolites measured by magnetic resonance spectroscopy (MRS) are altered in schizophrenia and other psychotic disorders, but the relationship between electrophysiological and metabolic changes are not well characterized. We examined the relation of MRS metabolites to cognitive and electrophysiological measures in individuals during the early phase of psychosis (EPP) and in healthy control subjects. The mismatch negativity (MMN) of the auditory event-related potential to duration deviant tones and the auditory steady response (ASSR) to 40 Hz stimulation were assessed. MRS was used to quantify glutamate+glutamine (Glx), N-Acetylasparate (NAA), creatine (Cre), myo-inositol (Ins) and choline (Cho) at a voxel placed medially in the frontal cortex. MMN amplitude and ASSR power did not differ between groups. The MRS metabolites Glx, Cre and Cho were elevated in the psychosis group. Partial least squares analysis in the patient group indicated that elevated levels of MRS metabolites were associated with reduced MMN amplitude and increased 40 Hz ASSR power. There were no correlations between the neurobiological measures and clinical measures. These data suggest that elevated neurometabolites early in psychosis are accompanied by altered auditory neurotransmission, possibly indicative of a neuroinflammatory or excitotoxic disturbance which disrupts a wide range of metabolic processes in the cortex.

Deception Decreases Brain Complexity

Extensive evidence suggests the feasibility of lie detection using electroencephalograms (EEGs). However, it is largely unknown whether there are any differences in the nonlinear features of EEGs between guilty and innocent subjects. In this study, we proposed a complexity-based method to distinguish lying from truth telling. A total of 35 participants were randomly divided into two groups, and their EEG signals were recorded with 14 electrodes. Averages for sequential sets of five trials were first calculated for the probe responses within each subject. Next, a common wavelet entropy (WE) measure and an improved one were used to quantify complexity from each five-trial average. The results show that for both measures, the WE values in the guilty subjects are statistically lower than those in the innocent subjects for most of the 14 electrodes. More importantly, using the improved measure, the difference in WE between the two groups of subjects significantly increases for 11 brain regions compared with the values from the common measure. Finally, the highest balanced classification accuracy, 89.64%, is achieved when using the combined WE feature vector in five brain regions from the sites of Pz, P3, C4, Cz, and C3. Our findings indicate that the lying task elicits a more ordered brain activity in some specific brain regions than the task of telling the truth. This study not only demonstrates that improved WE measurements could be a powerful quantitative index for detecting lying but also sheds light on the brain mechanisms underlying deceptive behaviors.

Changes in Dimensionality and Fractal Scaling Suggest Soft-Assembled Dynamics in Human EEG

Humans are high-dimensional, complex systems consisting of many components that must coordinate in order to perform even the simplest of activities. Many behavioral studies, especially in the movement sciences, have advanced the notion of soft-assembly to describe how systems with many components coordinate to perform specific functions while also exhibiting the potential to re-structure and then perform other functions as task demands change. Consistent with this notion, within cognitive neuroscience it is increasingly accepted that the brain flexibly coordinates the networks needed to cope with changing task demands. However, evaluation of various indices of soft-assembly has so far been absent from neurophysiological research. To begin addressing this gap, we investigated task-related changes in two distinct indices of soft-assembly using the established phenomenon of EEG repetition suppression. In a repetition priming task, we assessed evidence for changes in the correlation dimension and fractal scaling exponents during stimulus-locked event-related potentials, as a function of stimulus onset and familiarity, and relative to spontaneous non-task-related activity. Consistent with predictions derived from soft-assembly, results indicated decreases in dimensionality and increases in fractal scaling exponents from resting to pre-stimulus states and following stimulus onset. However, contrary to predictions, familiarity tended to increase dimensionality estimates. Overall, the findings support the view from soft-assembly that neural dynamics should become increasingly ordered as external task demands increase, and support the broader application of soft-assembly logic in understanding human behavior and electrophysiology.

The relationship between ERP components and EEG spatial complexity in a visual Go/Nogo task

The ERP components and variations of spatial complexity or functional connectivity are two distinct dimensions of neurophysiological events in the visual Go/Nogo task. Extensive studies have been conducted on these two distinct dimensions; however, no study has investigated whether these two neurophysiological events are linked to each other in the visual Go/Nogo task. The relationship between spatial complexity of electroencephalographic (EEG) data, quantified by the measure omega complexity, and event-related potential (ERP) components in a visual Go/Nogo task was studied. We found that with the increase of spatial complexity level, the latencies of N1 and N2 component were shortened and the amplitudes of N1, N2, and P3 components were decreased. The anterior Go/Nogo N2 effect and the Go/Nogo P3 effect were also found to be decreased with the increase of EEG spatial complexity. In addition, the reaction times in high spatial complexity trials were significantly shorter than those of medium and low spatial complexity trials when the time interval used to estimate the EEG spatial complexity was extended to 0∼1,000 ms after stimulus onset. These results suggest that high spatial complexity may be associated with faster cognitive processing and smaller postsynaptic potentials that occur simultaneously in large numbers of cortical pyramidal cells of certain brain regions. The EEG spatial complexity is closely related with demands of certain cognitive processes and the neural processing efficiency of human brain.

NEW & NOTEWORTHY

The reaction times, the latencies/amplitudes of event-related potential (ERP) components, the Go/Nogo N2 effect, and the Go/Nogo P3 effect are linked to the electroencephalographic (EEG) spatial complexity level. The EEG spatial complexity is closely related to demands of certain cognitive processes and could reflect the neural processing efficiency of human brain. Obtaining the single-trial ERP features through single-trial spatial complexity may be a more efficient approach than traditional methods.

Lifespan differences in nonlinear dynamics during rest and auditory oddball performance

Electroencephalographic recordings (EEG) were used to assess age-associated differences in nonlinear brain dynamics during both rest and auditory oddball performance in children aged 9.0-12.8 years, younger adults, and older adults. We computed nonlinear coupling dynamics and dimensional complexity, and also determined spectral alpha power as an indicator of cortical reactivity. During rest, both nonlinear coupling and spectral alpha power decreased with age, whereas dimensional complexity increased. In contrast, when attending to the deviant stimulus, nonlinear coupling increased with age, and complexity decreased. Correlational analyses showed that nonlinear measures assessed during auditory oddball performance were reliably related to an independently assessed measure of perceptual speed. We conclude that cortical dynamics during rest and stimulus processing undergo substantial reorganization from childhood to old age, and propose that lifespan age differences in nonlinear dynamics during stimulus processing reflect lifespan changes in the functional organization of neuronal cell assemblies.

Investigation of changes in EEG complexity during memory retrieval: the effect of midazolam

The aim of this study is applying nonlinear methods to assess changes in brain dynamics in a placebo-controlled study of midazolam-induced amnesia. Subjects injected with saline and midazolam during study, performed old/new recognition memory tests with EEG recording. Based on previous studies, as midazolam causes anterograde amnesia, we expected that midazolam would affect the EEG's degree of complexity. Recurrence quantification analysis, and approximate entropy were used in this assessment. These methods compare with other nonlinear techniques such as computation of the correlation dimension, are suitable for non-stationary EEG signals. Our findings suggest that EEG's complexity decreases during memory retrieval. Although this trend is observed in nonlinear curves related to the midazolam condition, the overall complexity were greater than in the saline condition. This result implies that impaired memory function caused by midazolam is associated with greater EEG's complexity compared to normal memory retrieval in saline injection.

Chaos in induced rhythms of the brain – the value of ERP studies

Event-related potentials (ERPs) – neglected almost entirely by Wright & Liley – allow objective investigation of information processing in the brain. The application of chaos theory to such an analysis broadens this possibility. Through the use of the point correlation dimension (PD2) accurate dimensional analysis of different Event-Related Potential components such as the P3 wave is possible.

Why does the human brain need to be a nonlinear system?

We focus on one aspect of Wright & Liley's target article: the linearity of the EEG. According to the authors, some nonlinear models of the cortex can be reduced (approximated) to the linear case at the millimetric scale. We argue here that the statement about the linear character of EEG is too strong and that EEG exhibits nonlinear features which cannot be ignored.

Nonlinear nonequilibrium nonquantum nonchaotic statistical mechanics of neocortical interactions

The work in progress reported by Wright & Liley shows great promise, primarily because of their experimental and simulation paradigms. However, their tentative conclusion that macroscopic neocortex may be considered (approximately) a linear near-equilibrium system is premature and does not correspond to tentative conclusions drawn from other studies of neocortex.

Levels, models, and brain activities: Neurodynamics is pluralistic

Some dichotomies related to modeling electrocortical activities are analyzed. Attractor neural networks versus biologically motivated models, near-equilibrium versus nonequilibrium processes, linear and nonlinear dynamics, stochastic and chaotic patterns, local and global scale simulation of cortical activities are discussed.

The form of chaos in the noisy brain can manifest function

I would like to emphasize the significance of chaotic dynamics at both local and macroscopic levels in the cortex. The basic notions dealt with in this commentary will be noise-induced order, chaotic “itinerancy” and dissipative structure. Wright & Laley's theory would be partially misleading, since emergent nonlinearity rather than the linearity at even a macroscopic level can actually subserve cortical functions.

Dynamics of the brain at global and microscopic scales: Neural networks and the EEG

There is some complementarity of models for the origin of the electroencephalogram (EEG) and neural network models for information storage in brainlike systems. From the EEG models of Freeman, of Nunez, and of the authors' group we argue that the wavelike processes revealed in the EEG exhibit linear and near-equilibrium dynamics at macroscopic scale, despite extremely nonlinear – probably chaotic – dynamics at microscopic scale. Simulations of cortical neuronal interactions at global and microscopic scales are then presented. The simulations depend on anatomical and physiological estimates of synaptic densities, coupling symmetries, synaptic gain, dendritic time constants, and axonal delays. It is shown that the frequency content, wave velocities, frequency/wavenumber spectra and response to cortical activation of the electrocorticogram (ECoG) can be reproduced by a “lumped” simulation treating small cortical areas as single-function units. The corresponding cellular neural network simulation has properties that include those of attractor neural networks proposed by Amit and by Parisi. Within the simulations at both scales, sharp transitions occur between low and high cell firing rates. These transitions may form a basis for neural interactions across scale. To maintain overall cortical dynamics in the normal low firing-rate range, interactions between the cortex and the subcortical systems are required to prevent runaway global excitation. Thus, the interaction of cortex and subcortex via corticostriatal and related pathways may partly regulate global dynamics by a principle analogous to adiabatic control of artificial neural networks.

Comparative reduction of theories — or over-simplification?

To model the organization of levels' of cortical dynamics, at least some general scheme for hierarchy, functional diversity, and proper intrinsic control must be provided. Rhythmic control forces the system to iterate its state by short trajectories, which makes it much more stable and predictable without discarding the desirable ability of chaotic systems to make rapid phase transitions. Rhythmic control provides a fundamentally different systems dynamics, one not provided by models that allow the emergence of continuous trajectories in the systems state space.

Is there chaos in the brain?

For some years there has been a controversy about whether brain state variables such as EEG or neuronal spike trains exhibit chaotic behaviour. Wright & Liley claim that the local dynamics measured by spike trains or local field potentials exhibit chaotic behaviour, but global measures like EEG should be governed by linear dynamics. We propose a different scheme. Based on simulation studies and various experiments, we suggest that the pointwise dimension of EEG time series may provide some valuable information about underlying neuronal generators.

The application of graph theoretical analysis to complex networks in the brain

Considering the brain as a complex network of interacting dynamical systems offers new insights into higher level brain processes such as memory, planning, and abstract reasoning as well as various types of brain pathophysiology. This viewpoint provides the opportunity to apply new insights in network sciences, such as the discovery of small world and scale free networks, to data on anatomical and functional connectivity in the brain. In this review we start with some background knowledge on the history and recent advances in network theories in general. We emphasize the correlation between the structural properties of networks and the dynamics of these networks. We subsequently demonstrate through evidence from computational studies, in vivo experiments, and functional MRI, EEG and MEG studies in humans, that both the functional and anatomical connectivity of the healthy brain have many features of a small world network, but only to a limited extent of a scale free network. The small world structure of neural networks is hypothesized to reflect an optimal configuration associated with rapid synchronization and information transfer, minimal wiring costs, resilience to certain types of damage, as well as a balance between local processing and global integration. Eventually, we review the current knowledge on the effects of focal and diffuse brain disease on neural network characteristics, and demonstrate increasing evidence that both cognitive and psychiatric disturbances, as well as risk of epileptic seizures, are correlated with (changes in) functional network architectural features.

Plastic Phase-Locking and Magnetic Mismatch Response to Auditory Deviants in Temporal Lobe Epilepsy

The magnetic equivalent (MMNm) of mismatch negativity may reflect auditory discrimination and sensory memory. To study whether temporal lobe epilepsy (TLE) affects automatic central auditory-change processing, we recorded magnetoencephalographic (MEG) responses to standard and duration-deviant sounds in 12 TLE patients and 12 age-matched controls, and repeated MEG measurement in 8 patients 6-30 months following epilepsy surgery and in 6 controls 3-8 months after their first measurement. We compared the MMNm between patients and controls, and also evaluated intertrial phase coherences as indexed by phase-locking factors (PLF) using wavelet-based analyses. We observed longer MMNm latencies for patients than for controls. Dipole modeling and minimum-current estimates together showed bi-frontotemporal sources for MMNm. The phase locking across trials was dominant at the 4- to 14-Hz band, and the main difference in PLF between deviant- and standard-evoked responses occurred in the time frame of 150-250 ms after stimulus onset. Notably, in the 5 patients who became seizure free after removal of right temporal epileptic focus, the phase-locking phenomena resulting from deviant stimuli were enhanced, and even more distributed in the frontotemporal regions. We conclude that mesial TLE might affect auditory-change detection, and a successful surgery causes a possible plastic change in phase locking of deviant-evoked signals.

Genetic influences on dynamic complexity of brain oscillations

Human electroencephalogram (EEG) consists of complex aperiodic oscillations that are assumed to indicate underlying neural dynamics such as the number and degree of independence of oscillating neuronal networks. EEG complexity can be estimated using measures derived from nonlinear dynamic systems theory. Variations in such measures have been shown to be associated with normal individual differences in cognition and some neuropsychiatric disorders. Despite the increasing use of EEG complexity measures for the study of normal and abnormal brain functioning, little is known about genetic and environmental influences on these measures. Using the pointwise dimension (PD2) algorithm, this study assessed heritability of EEG complexity at rest in a sample of 214 young female twins consisting of 51 monozygotic (MZ) and 56 dizygotic (DZ) pairs. In MZ twins, intrapair correlations were high and statistically significant; in DZ twins, correlations were substantially smaller. Genetic analyses using linear structural equation modeling revealed high and significant heritability of EEG complexity: 62-68% in the eyes-closed condition, and 46-60% in the eyes-open condition. Results suggest that individual differences in the complexity of resting electrocortical dynamics are largely determined by genetic factors. Neurophysiological mechanisms mediating genetic variation in EEG complexity may include the degree of structural connectivity and functional differentiation among cortical neuronal assemblies.

Nonlinear dynamical analysis of EEG and MEG: review of an emerging field

Many complex and interesting phenomena in nature are due to nonlinear phenomena. The theory of nonlinear dynamical systems, also called 'chaos theory', has now progressed to a stage, where it becomes possible to study self-organization and pattern formation in the complex neuronal networks of the brain. One approach to nonlinear time series analysis consists of reconstructing, from time series of EEG or MEG, an attractor of the underlying dynamical system, and characterizing it in terms of its dimension (an estimate of the degrees of freedom of the system), or its Lyapunov exponents and entropy (reflecting unpredictability of the dynamics due to the sensitive dependence on initial conditions). More recently developed nonlinear measures characterize other features of local brain dynamics (forecasting, time asymmetry, determinism) or the nonlinear synchronization between recordings from different brain regions. Nonlinear time series has been applied to EEG and MEG of healthy subjects during no-task resting states, perceptual processing, performance of cognitive tasks and different sleep stages. Many pathologic states have been examined as well, ranging from toxic states, seizures, and psychiatric disorders to Alzheimer's, Parkinson's and Cre1utzfeldt-Jakob's disease. Interpretation of these results in terms of 'functional sources' and 'functional networks' allows the identification of three basic patterns of brain dynamics: (i) normal, ongoing dynamics during a no-task, resting state in healthy subjects; this state is characterized by a high dimensional complexity and a relatively low and fluctuating level of synchronization of the neuronal networks; (ii) hypersynchronous, highly nonlinear dynamics of epileptic seizures; (iii) dynamics of degenerative encephalopathies with an abnormally low level of between area synchronization. Only intermediate levels of rapidly fluctuating synchronization, possibly due to critical dynamics near a phase transition, are associated with normal information processing, whereas both hyper-as well as hyposynchronous states result in impaired information processing and disturbed consciousness.

Memory-based or afferent processes in mismatch negativity (MMN): a review of the evidence

The mismatch negativity (MMN) is an electromagnetic response to any discriminable change in regular auditory input. This response is usually interpreted as being generated by an automatic cortical change-detection process in which a difference is found between the current input and the representation of the regular aspects of the preceding auditory input. Recently, this interpretation was questioned by Jääskeläinen et al. (2004) who proposed that the MMN is a product of an N1 (N1a) difference wave emerging in the subtraction procedure used to visualize and quantify the MMN. We now evaluate this "adaptation hypothesis" of the MMN in the light of the available data. It is shown that the MMN cannot be accounted for by differential activation of the afferent N1 transient detectors by repetitive ("standard") stimuli and deviant ("novel") stimuli and that the presence of a memory representation of the standard is required for the elicitation of MMN.

Permanent or transitory effects on neurocognitive components of the CNV complex induced by brain dysfunctions, lesions and ablations in humans

Since the mid-1960s, essentially using electrophysiological methods, our research group has examined the effects of different brain diseases in humans, both on first- and second-order conditioned responses and on some types of neurocognitive potentials of the CNV complex. This didactic lecture will focus on our various attempts to identify and understand the neuroanatomical and neurophysiological substrates involved in cognitive information processing followed by the conception and execution of sensory-motor and behavioural responses evoked by significant acoustic stimuli, in both pathological situations and normal control subjects. Great interest was, e.g. aroused in the early 1970s by the rare, fortunately unrepeatable, opportunity of examining the CNV patterns in various psychiatric patients treated with psychosurgical Freeman-Watts bilateral prefrontal 'radical' lobotomy, also with repeated recordings (The Responsive Brain (1976) 158; Multidisciplinary Perspectives in Event-Related Brain-Potentials Research (1978) 376) or bimedial bifrontal cingulotomy (Multidisciplinary Perspectives in Event-Related Brain Potential Research (1978) 383). In the same period, investigations into CNV activity recorded in patients submitted to complete callosotomy ('split brain': Attention and Performance, vol. IV (1972) 221; Electroenceph. Clin. Neurophysiol. Suppl. 33 (1973) 161) were also begun and were continued into the 1980s, also with regard to other types of ERP (Brain 111 (1988) 553; J. Cog. Neurosci. 2 (1990) 258). All these data furnished unique information about the sub-second dynamics of unilateral or bihemispheric cortico-cortical and cortico-subcortical interconnections in humans. In recent years, with a classic method of analysis based on sequential scalp-topographic bidimensional neuroelectric mapping and 21/19 electrodes connected to three different references, and binaural/monaural clicks as warning signals (S1), we have repeatedly examined the CNV activity of 11 selected patients submitted to complete ablation of the damaged cortical areas, with uni- or bilateral lesions restricted to the prefrontal or associative parieto-temporal areas. We have always used the standard CNV paradigm (S1-S2 motor-response) which evokes a complex of neurocognitive potentials, including the P300 from S1, which are well-known, since they are certainly among the most studied ERPs in the various ages and races of normal subjects, psychiatric patients and subjects with different brain diseases. The most important results have been, (1) In normal subjects the MRI and the latency differences of CNV component measurements along the bidirectional pathways functionally interconnecting ipsilateral distant associative cortical areas (e.g. the arcuate-superior longitudinal complex bundle) were accounted for by the transcortical conduction time, which varies in our scalp recordings from 1 cm/0.74 to 1.28 ms ( approximately 9.8 m/s). (2) Constantly, no true auditory S1-elicited N1a, b, c, P2, N2, P300 components or CNV slow waves (O- and E-wave) were recordable over the whole of the ablated cortical areas, but only clearly identifiable volume-conducted EP/ERPs generated in other hemispheric structures. (3) The post-S1 ERP/CNV complexes on the intact hemisphere were found to be within the normal limits. (4) Effects of severe disruption on the S1 ERP/CNV complexes evocable on the site and on remote ipsilateral apparently normal anatomo-functionally interconnected brain regions were observed in 5 patients, 4 of whom had extensive frontocortical ablations. In two of the latter the distant disruptive action on the CNV components over the neuroradiologically normal ipsilateral two-way connected post-rolandic sensory and association areas was seen to be partially reversible, showing aspects of a probable slowly evolving diaschisis-like effect. Similar deactivation of some ERP components was observed in reverse on the ipsilateral dorsolateral frontocortical region in the fifth patient with a large parieto-temporal cortex ablation. These data require confirmahese data require confirmation, and when this phenomenon is observable, it must be appropriately monitored with different methods of functional neuroimaging. This will serve not only for medical and neuropsychophysiological diagnosis purposes, but also particularly for a correct and really useful planning of neuro-rehabilitation activities in selected cases.

Electrophysiological evidence of abnormal activation of the cerebral network of involuntary attention in alcoholism

OBJECTIVE

Increased distractibility is a common impairment in alcoholism, but objective evidence has remained elusive. Here, a task designed to investigate with event-related brain potentials (ERPs) the neural mechanism underlying distraction was used to show abnormal involuntary orienting of attention in chronic alcoholism.

METHODS

Fifteen alcoholics and 17 matched healthy controls were instructed to ignore auditory stimuli while concentrating in the discrimination of immediately following visual stimuli. The auditory sequences contained repetitive standard tones occasionally replaced by deviant tones of slightly higher frequency, or by complex novel sounds.

RESULTS

Deviant tones and novel sounds distracted visual performance, i.e. increased reaction time to visual stimuli, similarly in patients and controls. Compared to controls, however, alcoholics showed ERP abnormalities, i.e. enhanced P3a amplitudes over the left frontal region, and a positive posterior deflection instead of the frontally distributed reorienting negativity (RON).

CONCLUSIONS

The enhanced P3a to novelty and subsequent positive wave instead of RON in alcoholics suggests encoding into working memory of task-irrelevant auditory events and provides neurophysiological markers of impaired involuntary attention mechanisms in chronic alcoholism.

The difference in Mismatch negativity between the acute and post-acute phase of schizophrenia

In order to investigate the trait and state aspects of Mismatch negativity (MMN) amplitude reduction in schizophrenia, auditory MMNs were measured from 13 schizophrenic patients on two occasions, initially when they showed acute exacerbation and later when their symptoms improved. Patients exhibited reduced mean amplitude of the MMN recorded at Fz. There were no significant changes in the amplitude of MMN at Fz between the acute patients and the post-acute patients, despite significant improvement in symptomatology. However, the acute patients showed a significant attenuation of MMN recorded at both mastoids as compared with the post-acute patients. Although the findings of the MMN at Fz support the overall longitudinal stability of MMN deficits in schizophrenia, the acute phase patients showed a modestly altered MMN activity compared with the post-acute phase patients, suggesting that there is some state-dependent modulation of these deficits.

Dynamic sensory updating in the auditory system

Typically, in everyday situations, auditory input is constantly changing. Change is an important cue for the auditory system, which can signal the start of new sources of information or that some action may be required. Using an event-related brain potential that can be elicited whether or not attention is focused on the sounds (the mismatch negativity, MMN) we measured the time course of the effects of contextual changes on the brain's response to the same stimulus event. The onset or cessation of a sound in a stimulus block brought about context changes. The effect of the context was observed through changes in the MMN response to a deviant event that was present throughout the sound sequence. These results suggest the existence of a dynamic system of change detection, which updates its model of the sensory input on-line as the changes occur.

The initial orienting response during human REM sleep as revealed by the N1 component of auditory event-related potentials

The large N1 wave of the auditory event-related potentials (ERPs) typically occurring to the first stimulus after a long silent interval seems to be associated with the involuntary initial-orienting response. Since the mechanisms involved in the generation of this brain response are assumed to be activated automatically, the present study aims at determining whether this electrophysiological response can also be elicited during human REM sleep, the sleep stage considered most sensitive to external stimuli. To achieve this goal, the auditory N1 wave was analyzed in wakefulness and REM sleep for frequency deviant tones delivered in several positions (1, 2, 4 and 6) within homogenous stimulus trains separated by different intervals of silence (3, 6 and 9 s), the intra-train stimulus interval being 600 ms. A significant increment in the amplitude of the N1 component for the first deviant tone, as compared with deviants delivered in remaining positions, was observed in both brain states, independently of the inter-train interval length. This result cannot be explained by a release-from-refractoriness effect, since only one deviant was presented in each train and the inter-deviant interval hardly changed from one train to another. The increase in N1 to the first stimulus of the train, probably due to the contribution of the neuronal elements responsible for the supratemporal and non-specific components, may be explained by changes in the silent interval, rather than by variations in the stimulus frequency. The enhanced N1 could be reflecting a general increase in sensory sensitivity associated with the arousal factor of the orienting response. These findings suggest that the brain maintains the potential ability to trigger the brain events responsible for the OR elicitation, even during REM sleep.

Brain electrical microstates in subjects with panic disorder

Brain electrical microstates represent spatial configurations of scalp recorded brain electrical activity and are considered to be the basic elements of stepwise processing of information in the brain. In the present study, the hypothesis of a temporo-limbic dysfunction in panic disorder (PD) was tested by investigating the topographic descriptors of brain microstates, in particular the one corresponding to the Late Positive Complex (LPC), an event-related potential (ERP) component with generators in these regions. ERPs were recorded in PD patients and matched healthy subjects during a target detection task, in a central (CC) and a lateral condition (LC). In the CC, a leftward shift of the LPC microstate positive centroid was observed in the patients with PD versus the healthy control subjects. In the LC, the topographic descriptor of the first microstate showed a rightward shift, while those of both the second and the fourth microstate, corresponding to the LPC, revealed a leftward shift in the PD patients versus the healthy control subjects. These findings indicate an overactivation of the right hemisphere networks involved in early visual processing and a hypoactivation of the right hemisphere circuits involved in LPC generators in PD. In line with this interpretation, the abnormal topography of the LPC microstate, observed in the CC, was associated with a worse performance on a test exploring right temporo-hippocampal functioning. Topographical abnormalities found for the LPC microstate in the LC were associated with a higher number of panic attacks, suggesting a pathogenetic role of the right temporo-hippocampal dysfunction in PD.

Symbolic dynamics of event-related brain potentials

We apply symbolic dynamics techniques such as word statistics and measures of complexity to nonstationary and noisy multivariate time series of electroencephalograms (EEG) in order to estimate event-related brain potentials (ERP). Their significance against surrogate data as well as between different experimental conditions is tested. These methods are validated by simulations using stochastic dynamical systems with time-dependent control parameters and compared with traditional ERP-analysis techniques. Continuous EEG data are cut into epochs according to stimuli events presented to the subjects. These ensembles of time series can be considered as ensembles of trajectories given by some dynamical systems. We employ a statistical mechanics approach motivated by the Frobenius-Perron equation and apply it to coarse-grained symbolic descriptions of the dynamics. We develop time-dependent measures of complexity founded on running cylinder sets and show that these quantities are able to distinguish simulated data obtained by different control parameters as well as experimental data between different experimental conditions. As a first finding, our approach restores the well-known ERP components and it reveals additionally qualitative changes in the EEG that cannot be detected by means of the traditional techniques. We criticize the prerequisites of the traditional approach to ERP analysis and propose to consider ERP instead in terms of dynamical system theory and information theory.

Brain hemispheric organization, anxiety, and psychoses

Abnormalities of brain hemispheric organization have been found in a variety of psychiatric disorders. Despite the great amount of data collected and the number of theoretical models elaborated, the role of these abnormalities in the pathogenesis of these disorders remains controversial. This article briefly reviews current concepts of hemispheric functioning, discusses the role of abnormalities of brain hemispheric organization in schizophrenia and in two anxiety disorders (panic disorder and obsessive-compulsive disorder), and outlines a developmental perspective that accounts for the observed abnormalities.

Low sampling rate induces high correlation dimension on electroencephalograms from healthy subjects

The aim of this paper was to elucidate the influence of sampling parameters in the non-linear analysis of a resting electroencephalogram (EEG) in healthy subjects. Electroencephalograms in 12 healthy volunteers were recorded and the signal digitized at 128, 256, 512 and 1024 Hz, respectively, with the resolution of 8 bits, 12 bits and 16 bits for each sampling rate. Correlation dimension was calculated on each data set. Results were demonstrated on brain maps and examined by analysis of variance (ANOVA). Correlation integral functions demonstrated four parts separated by critical points. The data showed that sampling rate significantly affected the estimation, while resolution did not influence the results. The correlation dimensions calculated with the sampling rate at or below 256 Hz were apparently higher than the results obtained at 1024 Hz. The values at 512 Hz and 1024 Hz did not differ. The data revealed that low sampling rate can severely distort the estimation of correlation dimension. The optimal sampling rate for analyzing resting EEG on normal subjects is 512 Hz. Limitation and aliasing phenomenon are discussed in the paper.

Comparison of human ictal, interictal and normal non-linear component analyses

OBJECTIVES

The non-linear properties of EEG and filtered rhythms obtained from healthy subjects and epileptic patients with complex partial seizures were analyzed to investigate whether EEG in different neurological states can be generated by the mechanism that integrates several non-linear dynamic systems.

METHODS

The control EEG (from 26 healthy subjects), interictal EEG and ictal EEG (from 25 patients) were digitally filtered into delta (0.5-4 Hz), theta (4-8 Hz), alpha (8-13 Hz), beta (13-30 Hz) and gamma (30-40 Hz) components. The correlation dimension was calculated on each original signal and corresponding surrogate data. A new method was developed to accelerate the calculation of the correlation integral. Function P(m,r) was defined to visualize the meaning of the correlation dimension. The point critical to the estimation was determined by the P(m,r) function.

RESULTS

The EEG in the control subjects and patients showed significantly lower correlation dimensions than the surrogate data. The delta, alpha, beta and gamma components from the control EEG exhibited similar complexity to the surrogate data, while only the alpha component from the interictal EEG presented the same dimension as the surrogate data. The correlation dimensions of the theta and alpha components remained the same when the neurological state changed from interictal EEG to ictal EEG. The complexity of the beta component was higher than the complexity of other components in both control subjects and patients. The correlation dimension of EEG was significantly correlated to the complexity of delta, theta, beta and gamma components.

CONCLUSIONS

Our results suggest that EEG and filtered components in different neurological states demonstrate varied dynamic properties. The characteristics of neuronal networks can be differentiated by the dynamics of filtered components. Separating EEG into different dynamic systems may facilitate understanding of the mechanisms involved in the human EEG.

Event-related dimensional reductions in the primary auditory cortex of the conscious cat are revealed by new techniques for enhancing the non-linear dimensional algorithms

The analytic algorithms derived from non-linear deterministic models may be more sensitive to differences in physiological data than those based on linear stochastic models. Among the non-linear algorithms the time-dependent dimensional ones appear to be the most sensitive discriminators. In the present study dimensional responses were examined in both electronically and mathematically generated data and in high-resolution physiological data. The latter were event-related potentials (ERPs) recorded from the primary auditory cortex of cats during classical conditioning. Two techniques were found to lengthen and stabilize the linear scaling region in the correlation integral of the dimensional algorithms: (1) linking trials to increase data length; and (2) gain reduction to lower integer-values of noise, combined with algorithmic setting of slopes < 0.5 to zero. Of the three dimensional algorithms examined, only the time-dependent Point Correlation Dimension (PD2i) showed low error rates when tracking the dimensional shifts in non-stationary generated data. This algorithm also uniquely distinguished between the conditioned and unconditioned physiological responses. The ERPs had corresponding PD2i's that were significantly different from each other as well as from their own randomized-phase surrogates. The brief dimensional reduction that follows a conditioned stimulus is interpreted to be related to 'cooperativity' among the underlying cortical neurons that contribute to its electrogenesis.

Working memory load and EEG-dynamics as revealed by point correlation dimension analysis

The results of the present study showed a decreased dimensional complexity during working-memory load, which was induced by the Corsi-Bock-Tapping task as compared to a baseline task. This baseline task was similar to the Corsi-Block-Tapping with respect to both the required processes of perception and the motor performance. A load-specific change of brain dynamics was observed, which was most pronounced over frontal cortical areas. This finding is in agreement with the literature and encourages further research on the ongoing EEG, especially with clinical tests, where little is known about their psychophysiological correlates. From a methodological point of view, the point correlation dimension, which deals with non-stationary data, was applied to EEG-time series that were a concatenation of several EEG-subepochs of the same experimental conditions. From the results it is proposed that this procedure might offer an approach for EEG analysis, where the EEG-epochs are of short duration and non-stationary data are to be expected.

Scalp distribution of the dimensional complexity of the EEG and the P3 ERP component in stroke patients

The use of recently developed techniques allows the quantitative investigation of the non-linear properties of the electrical activity of the brain not only in basic but also in applied research. The point correlation dimension (PD2) was used in this study for the analysis of the electroencephalogram (EEG) recorded in patients with unilateral stroke caused by middle cerebral artery occlusion. The scalp distribution of the PD2 and that of the P3 event-related potential component was mapped and frequency spectra were calculated. Compared to normal controls, asymmetrical PD2 distribution was observed with low values on the side of the stroke, the extension of which depended on recording conditions (level of vigilance) and only partially corresponded to the region characterized by slow frequencies. In one case, ipsilateral reduction of the P3 wave was caused by a small subcortical stroke. The efficacy of the linear and non-linear methods in localizing brain pathology are evaluated and compared.

Focal enhancement of chaotic strange attractor dimension in the left semantic (Wernicke) human cortex during reading without concomitant change in vigilance level

Non-averaged scalp-recorded brain potentials were analyzed in four right-handed humans while they were either silently reading a book, or in idle alert conditions. The dimensionality of chaotic strange attractors was estimated from the EEG at each of 14 scalp electrodes, using the point correlation dimension PD2 algorithm. When the subject was fully alert but not engaged in any specific task, PD2 was between 5.2 and 5.9. When the subject was silently reading a book, PD2 bifurcated to significantly higher values (6.6-6.9) in the left lateral anterior extrasylvian temporal cortex, but did not change in the adjacent left perisylvian cortex nor over the right side of the brain. The PD2 increases occurred without any significant change in vigilance level as assessed from the unchanged mean voltage of concomitant gamma (40 Hz) EEG oscillations. A small barely significant PD2 increase was only noticed in the left lateral precentral region. The increase of chaotic dimensionality in the left lateral extrasylvian temporal cortex during reading reflects enhanced processing operations in the semantic (Wernicke) areas and is in line with recent PET imaging data. These results provide for the first time evidence of a focal chaotic fractal dimension increase that is related to specific cognitive brain processing operations.

The dimensional complexity of the P3 event-related potential: area-specific and task-dependent features

Appropriate methods are needed for the study of the non-linear properties of the nervous system. The correlation dimension, as expressed by the effective point correlation dimension (PD2eff), was used in this study for the analysis of the dimensional complexity of event-related potentials. The ERPs were recorded at Fz, Cz and Pz in an auditory oddball paradigm in which 'easy' and 'difficult' sensory discrimination tasks were applied. The PD2eff was calculated from each EEG epoch used in the process of ERP averaging. The PD2eff significantly decreased during the ERPs in which the P3-component appeared, and this reduction showed area-specific and task-specific patterns. The area-specific PD2eff changes indicated distinctive functional features of the frontal areas in this task. The magnitude of the PD2eff change was found to depend on the degree of task difficulty. Implications of the findings related to theories on the functional significance of the P3-wave in information processing are discussed.

Neural mechanisms of involuntary attention to acoustic novelty and change

Behavioral and event-related brain potential (ERP) measures were used to elucidate the neural mechanisms of involuntary engagement of attention by novelty and change in the acoustic environment. The behavioral measures consisted of the reaction time (RT) and performance accuracy (hit rate) in a forced-choice visual RT task where subjects were to discriminate between odd and even numbers. Each visual stimulus was preceded by an irrelevant auditory stimulus, which was randomly either a "standard" tone (80%), a slightly higher "deviant" tone (10%), or a natural, "novel" sound (10%). Novel sounds prolonged the RT to successive visual stimuli by 17 msec as compared with the RT to visual stimuli that followed standard tones. Deviant tones, in turn, decreased the hit rate but did not significantly affect the RT. In the ERPs to deviant tones, the mismatch negativity (MMN), peaking at 150 msec, and a second negativity, peaking at 400 msec, could be observed. Novel sounds elicited an enhanced N1, with a probable overlap by the MMN, and a large positive P3a response with two different subcomponents: an early centrally dominant P3a, peaking at 230 msec, and a late P3a, peaking at 315 msec with a right-frontal scalp maximum. The present results suggest the involvement of two different neural mechanisms in triggering involuntary attention to acoustic novelty and change: a transient-detector mechanism activated by novel sounds and reflected in the N1 and a stimulus-change detector mechanism activated by deviant tones and novel sounds and reflected in the MMN. The observed differential distracting effects by slightly deviant tones and widely deviant novel sounds support the notion of two separate mechanisms of involuntary attention.

Combined mapping of human auditory EEG and MEG responses

Auditory electric and magnetic P50(m), N1(m) and MMN(m) responses to standard, deviant and novel sounds were studied by recording brain electrical activity with 25 EEG electrodes simultaneously with the corresponding magnetic signals measured with 122 MEG gradiometer coils. The sources of these responses were located on the basis of the MEG responses; all were found to be in the supratemporal plane. The goal of the present paper was to investigate to what degree the source locations and orientations determined from the magnetic data account for the measured EEG signals. It was found that the electric P50, N1 and MMN responses can to a considerable degree be explained by the sources of the corresponding magnetic responses. In addition, source-current components not detectable by MEG were shown to contribute to the measured EEG signals.

Non-linear dynamic complexity of the human EEG during evoked emotions

The present study examined EEG dimensional complexity (estimated correlation dimension) in 76 healthy volunteers in response to emotionally valenced (i.e. neutral, positive and negative) film clip stimulation. EEG was recorded from 18 sites (10-20 system). We estimated the dimensional complexity by the Grassberger and Procaccia and Skinner's point-wise dimension (PD2i) methods. The results were compared to spectral measures of the EEG. Only the PD2i algorithm (i.e. the one that did not require data stationarity) discriminated among all the three film categories. The main results showed that both negative and positive emotions occurred with higher values (at some posterior locations) of EEG DCx estimates compared to the neutral viewing condition. The topographical differences (frontal vs. posterior temporal) between positive and negative evoked emotions were obtained. There were also some significant direct relationships between dynamic complexity estimates and intensities of subjective emotional feelings. It is concluded that dimensional complexity estimates turned out to be sensitive to subtle aspects of emotional processing not accessible by linear EEG analyses.

Dimensional complexity of the EEG in subcortical stroke--a case study

The conventional electrophysiological methods used for the analysis of the functional characteristics of the nervous system are not able to grasp its non-linear and random features. Of the methods based on the application of chaos-theory the correlation dimension analysis can be used to quantify the complexity of the analyzed signal, such as the electroencephalogram (EEG). The new version (point-correlation dimension, PD2) was used in this study, which is more accurate than the other, currently used algorithms. The purpose of the present investigation was to compare the sensitivity of the methods based on chaos-theory with the traditional electrophysiological ones in a case when no apparent abnormality was present as judged on the basis of this latter methodology. The PD2 was calculated from the EEG recorded in 13 healthy control subjects and in a patient who suffered a small subcortical stroke 2 years prior to the investigation and who was free of neurological symptoms at the time of recording. Compared to that seen in the control group, in the Z-score maps of the scalp distribution of the PD2, a marked asymmetry was seen and the absolute PD2 values showed a low-dimensional area in the parietal region, ipsilateral to the stroke. A relative decrease of the gamma band was found in the frequency power spectra in the same area. It is suggested that the additional information extracted from the EEG by non-linear analysis may increase the sensitivity of electrophysiological methods for detecting brain pathology.

Adaptive modeling of the unattended acoustic environment reflected in the mismatch negativity event-related potential

The mismatch negativity (MMN) event-related potential is elicited by changes in repetitive auditory stimuli. The present paper suggests that: (1) an acoustic model of the auditory environment is maintained even in the absence of attention focussed on auditory stimuli, preattentively detecting repetitive features of the acoustic stimulation; and (2) the MMN reflects modifications to existing parts of this model during incorporation of a new stimulus into the model. MMN responses were investigated during the period when a repetitive stimulus (standard) was replaced by a new standard sound. It was found that whereas the new standard stimulus stopped eliciting an MMN after its third presentation with respect to the old standard, a probe stimulus, differing from both standards, elicited an MMN with respect to the old standard, even when following four presentations of the new standard. The probe stimulus also elicited an MMN with respect to the new standard after four or more presentations of this new standard stimulus, thus eliciting two consecutive MMNs. The comparison (conducted on the basis of the present and some previous findings) of the present hypothesis with alternative explanations of MMN based on the presence and strength of auditory transient memory traces supported the model adjustment hypothesis.

Working-memory load and dimensional complexity of the EEG

This investigation shows that a working-memory load induced by a memory scanning task has an effect on nonlinear descriptors of the EEG dynamics. The effect was locally specific above the fronto-temporal (right) cortex and it may be described as a reduction in the dimensional complexity of cortical brain activity. The meaning of the effects seems to differ from that of EEG spectral power, which varied with time during the experiment and not with changes in the working-memory load conditions. Behaviorally controlled over- and underload led to increased variance of the dimensional complexity, thus indicating that dimensional complexity correlates more closely with actual performance than with more general descriptions of brain states. Habitual response speed had an effect at the parietal lead, thus indicating that fast responders reduced their dimensional complexity as the task demand increased. In contrast, the slower responders showed no such definite trend.

Neuromodulation can significantly change the dynamical state of cortical networks

We present simulation results of an olfactory cortex model complementing the results presented in Wright & Liley's target article. We show how the cortical dynamics as expressed in EEG can be regulated by neuromodulation and discuss how the system can attain global stability without cortical-subcortical interaction, as presumed necessary by Wright & Liley. Network structure is shown to be crucial.

Multiscale modeling of the brain should be validated in more detail against the biological data

Wright & Liley provide an advance in addressing the interaction of multiple scales of processing in the brain. It should address in more detail the biological evidence that underlies the models it proposes to replace.

Dynamics of the brain — from the statistical properties of neural signals to the development of representations

The unification of microscopic and macroscopic models of brain behaviour is of paramount importance and Wright & Liley's target article provides some important groundwork. In this commentary, I propose that a useful approach for the future is to incorporate a developmental perspective into such models. This may be an important constraint, providing a key to understanding the nature of macroscopic measures of brain function such as functional measures like ERP.

Empirical data base for simulation: Firing rates and axonal conduction velocity for cortical neurones

Simulation of brain dynamics requires the use of accurate empirical data. This commentary points out major errors in some of the empirical data used in Wright & Laley's simulation. The simulation is quantitatively very different from the real cortex, and may also have important qualitative differences.

Multiscale modeling of brain dynamics depends upon approximations at each scale

We outline fresh findings that show that our macroscopic electrocorticographic (ECoG) simulations can account for synchronous multiunit pulse oscillations at separate, simultaneously activated cortical sites and the associated gamma-band ECoG activity. We clarify our views on the approximations of dynamic class applicable to neural events at macroscopic and microscopic scales, and the analogies drawn to classes of ANN behaviour. We accept the need to introduce memory processes and detailed anatomical and physiological information into any future developments of our simulations. On the issue of intrinsic cortical stability and the role of extrinsic fibre systems in maintaining stability, we argue that this position is not in extreme contradiction to those of our commentators, and that the mechanisms implicit in our simulations' properties imply rich computational possibilities. We discuss some of the reasons for and against the existence of significant global resonances in the brain and explain why such behaviour appears absent in our simulations. Last, we discuss other phenomena, such as rhythmic driving of the cortex, which have not yet been introduced into our models, and indicate lines for future development of the simulations.

Rhythmicity in the EEG and global stabilization of the average level of excitation in the cerebral cortex

The network model of EEG formation has revealed a unified mechanism for disparate EEG phenomena: for various reactions as well as for ontogenetic and phylogenetic differences. EEG rhythmicity was shown to be an external manifestation of the functioning of the intracortical stabilizing system which provides normal informational operations in the cerebral cortex.

Multiscale neocortical dynamics, experimental EEG measures, and global facilitation of local cell assemblies

Multiscale dynamics, linear approximations, global boundary conditions, experimental verification, and global influences on local cell assemblies are considered in the context of Wright & Liley's work. W&L provide a nice introduction to these issues and a reasonable simulation of intermediate scale dynamics, but the model does not adequately simulate combined local and global processes.