EEG/EP: new techniques

Neurophysiological measures of covert semantic processing in neurotypical adolescents actively ignoring spoken sentence inputs: A high-density event-related potential (ERP) study

Language comprehension requires semantic processing of individual words and their context within a sentence. Well-characterized event-related potential (ERP) components (the N400 and late positivity component (LPC/P600)) provide neuromarkers of semantic processing, and are robustly evoked when semantic errors are introduced into sentences. These measures are useful for evaluating semantic processing in clinical populations, but it is not known whether they can be evoked in more severe neurodevelopmental disorders where explicit attention to the sentence inputs cannot be objectively assessed (i.e., when sentences are passively listened to). We evaluated whether N400 and LPC/P600 could be detected in adolescents who were explicitly ignoring sentence inputs. Specifically, it was asked whether explicit attention to spoken inputs was required for semantic processing, or if a degree of automatic processing occurs when the focus of attention is directed elsewhere? High-density ERPs were acquired from twenty-two adolescents (12-17 years), under two experimental conditions: 1. individuals actively determined whether the final word in a sentence was congruent or incongruent with sentence context, or 2. passively listened to background sentences while watching a video. When sentences were ignored, N400 and LPC/P600 were robustly evoked to semantic errors, albeit with reduced amplitudes and protracted/delayed latencies. Statistically distinct topographic distributions during passive versus active paradigms pointed to distinct generator configurations for semantic processing as a function of attention. Covert semantic processing continues in neurotypical adolescents when explicit attention is withdrawn from sentence inputs. As such, this approach could be used to objectively investigate semantic processing in populations with communication deficits.

Neuroimaging Modalities in Alzheimer's Disease: Diagnosis and Clinical Features

Alzheimer's disease (AD) is a neurodegenerative disease causing progressive cognitive decline until eventual death. AD affects millions of individuals worldwide in the absence of effective treatment options, and its clinical causes are still uncertain. The onset of dementia symptoms indicates severe neurodegeneration has already taken place. Therefore, AD diagnosis at an early stage is essential as it results in more effective therapy to slow its progression. The current clinical diagnosis of AD relies on mental examinations and brain imaging to determine whether patients meet diagnostic criteria, and biomedical research focuses on finding associated biomarkers by using neuroimaging techniques. Multiple clinical brain imaging modalities emerged as potential techniques to study AD, showing a range of capacity in their preciseness to identify the disease. This review presents the advantages and limitations of brain imaging modalities for AD diagnosis and discusses their clinical value.

Developmental Changes in the EEG Rhythms of Children and Young Adults

This study analyzed the developmental trends of brain rhythms in a group of children and a group of young adults. Principal component analysis (PCA), ANOVA, as well as correlational and topographical analyses were applied to the power spectral density of spontaneous electroencephalography (EEG). Absolute and relative power data were analyzed. The PCA analysis allowed to define three sources of variability related to the classical EEG rhythms. The absolute power results showed that children have higher spectral power than young adults in all frequency bands. Relative power demonstrated that children have more spectral power in the lower frequency bands (delta and theta) while young adults have more spectral power in the higher frequency bands (alpha and beta). Scalp topography analysis showed similar distributions for the four EEG bands in both groups, although delta and theta differed slightly between age groups. Correlational and PCA analysis showed an inverse relationship between delta and alpha power during development. Posterior regions and lower frequency rhythms seem to mature earlier than other regions and frequencies.

Abnormal brain processing in hepatic encephalopathy: evidence of cerebral reorganization?

BACKGROUND AND AIM

Hepatic encephalopathy (HE) is a severe and frequent complication of liver cirrhosis characterized by abnormal cerebral function. Little is known about the underlying neural mechanisms in HE and human data are sparse. Electrophysiological methods such as evoked brain potentials after somatic stimuli can be combined with inverse modeling of the underlying brain activity. Thereby, information on neuronal dynamics and brain activity can be studied in vivo. The aim of this study was to investigate the sensory brain processing in patients with HE.

PATIENTS AND METHODS

Twelve patients with minimal or overt HE and 26 healthy volunteers were included in the study. Cerebral sensory processing was investigated as (i) an auditory reaction time task; (ii) visual and somatosensory evoked brain potentials, and (iii) reconstruction of the underlying brain activity.

RESULTS

Somatosensory evoked potentials were reproducible (all P>0.05), whereas flash evoked potentials were not reproducible (all P<0.05). Compared with healthy volunteers, the patient group had a prolonged reaction time index (P=0.03) along with increasing prolongation of latencies of median nerve evoked potentials (P<0.03). Reconstruction of the underlying brain sources showed a lateral shift in source localization of the P45 (P<0.001) and N60 components (P=0.02). A correlation between the psychometric hepatic encephalopathy score and the dipole shift corresponding to the N60 (P=0.003) component was seen.

CONCLUSION

HE patients have evidence of prolonged intracerebral nerve conduction, along with lateralization of brain activity following median nerve stimulation. This possibly represents cortical reorganization and may be important in our understanding of this condition.

Gastrointestinal symptoms in type-1 diabetes: is it all about brain plasticity?

BACKGROUND AND AIMS

Autonomic neuropathy seems to play a central role in the development of gastrointestinal symptoms in diabetes. In order to explore the neuronal mechanisms behind the symptoms we evaluated the brain processing of painful visceral stimuli.

METHODS

Evoked brain potentials were recorded to assess the response to painful oesophageal electrical stimuli in 15 healthy volunteers and 14 type-1 diabetes patients with autonomic neuropathy and related gastrointestinal symptoms. Source reconstruction analysis (fixed Multiple Signal Classification (MUSIC) algorithm) was applied to estimate the location of the evoked electrical activity in the brain.

RESULTS

The patients had increased oesophageal sensory thresholds compared to the controls (P=0.004). The latencies of the evoked brain potentials at vertex (Cz) were increased (P=0.007) and amplitudes reduced (P=0.011) in diabetics. Compared with controls the patients had a posterior shift of the electrical sources in the anterior cingulate cortex at 54 ms, and additional sources close to the posterior insula at 95 ms and in medial frontal gyrus at 184 ms.

CONCLUSIONS

There is evidence of altered central processing to visceral stimulation, and both peripheral and central mechanisms seem involved. Central neuronal reorganisation may contribute to our understanding of the gastrointestinal symptoms in patients with diabetic autonomic neuropathy and this may guide development and evaluation of new treatment modalities.

Topographic ERP analyses: a step-by-step tutorial review

In this tutorial review, we detail both the rationale for as well as the implementation of a set of analyses of surface-recorded event-related potentials (ERPs) that uses the reference-free spatial (i.e. topographic) information available from high-density electrode montages to render statistical information concerning modulations in response strength, latency, and topography both between and within experimental conditions. In these and other ways these topographic analysis methods allow the experimenter to glean additional information and neurophysiologic interpretability beyond what is available from canonical waveform analyses. In this tutorial we present the example of somatosensory evoked potentials (SEPs) in response to stimulation of each hand to illustrate these points. For each step of these analyses, we provide the reader with both a conceptual and mathematical description of how the analysis is carried out, what it yields, and how to interpret its statistical outcome. We show that these topographic analysis methods are intuitive and easy-to-use approaches that can remove much of the guesswork often confronting ERP researchers and also assist in identifying the information contained within high-density ERP datasets.

Generating controlled image sets in cognitive neuroscience research

The investigation of perceptual and cognitive functions with non-invasive brain imaging methods critically depends on the careful selection of stimuli for use in experiments. For example, it must be verified that any observed effects follow from the parameter of interest (e.g. semantic category) rather than other low-level physical features (e.g. luminance, or spectral properties). Otherwise, interpretation of results is confounded. Often, researchers circumvent this issue by including additional control conditions or tasks, both of which are flawed and also prolong experiments. Here, we present some new approaches for controlling classes of stimuli intended for use in cognitive neuroscience, however these methods can be readily extrapolated to other applications and stimulus modalities. Our approach is comprised of two levels. The first level aims at equalizing individual stimuli in terms of their mean luminance. Each data point in the stimulus is adjusted to a standardized value based on a standard value across the stimulus battery. The second level analyzes two populations of stimuli along their spectral properties (i.e. spatial frequency) using a dissimilarity metric that equals the root mean square of the distance between two populations of objects as a function of spatial frequency along x- and y-dimensions of the image. Randomized permutations are used to obtain a minimal value between the populations to minimize, in a completely data-driven manner, the spectral differences between image sets. While another paper in this issue applies these methods in the case of acoustic stimuli (Aeschlimann et al., Brain Topogr 2008), we illustrate this approach here in detail for complex visual stimuli.

Double dissociation of N1 and P3 abnormalities in deficit and nondeficit schizophrenia

It has been proposed that the presence of enduring, idiopathic negative symptoms define a group of patients with a disease (deficit schizophrenia, DS) that is separate from other forms of schizophrenia (nondeficit schizophrenia, NDS). Although several findings support this hypothesis, the possibility that DS represents the severe end of a single schizophrenia continuum cannot be excluded yet. We tested the hypothesis that DS and NDS differ relative to event-related potentials (ERPs). Amplitude, scalp topography and cortical sources of the ERP components were assessed in clinically stable DS and NDS outpatients and in matched healthy subjects (HCS). Twenty subjects per group were recruited. Among the subjects who completed the target detection task, there were no group difference in accuracy. For N1, only patients with DS, as compared with HCS, showed an amplitude reduction over the scalp central leads and a reduced current source density in cingulate and parahippocampal gyrus. For P3, only patients with NDS, as compared with HCS, showed a lateralized amplitude reduction over the left posterior regions and reduced current source density in left temporal and bilateral frontal, cingulate and parietal areas. The DS and NDS groups differed significantly from each other with regard to N1 amplitude and topography, as well as P3 amplitude and cortical sources. The N1 was affected in DS but not in NDS patients, whereas P3 was affected in NDS only. This double dissociation is consistent with the hypothesis that DS represents a separate disease entity within schizophrenia.

Response inhibition deficits in externalizing child psychiatric disorders: an ERP-study with the Stop-task

Background

Evidence from behavioural studies suggests that impaired motor response inhibition may be common to several externalizing child psychiatric disorders, although it has been proposed to be the core-deficit in AD/HD. Since similar overt behaviour may be accompanied by different covert brain activity, the aim of this study was to investigate both brain-electric-activity and performance measures in three groups of children with externalizing child psychiatric disorders and a group of normal controls.

Methods

A Stop-task was used to measure specific aspects of response inhibition in 10 children with attention-deficit hyperactivity disorder (AD/HD), 8 children with oppositional defiant disorder/conduct disorder (ODD/CD), 11 children with comorbid AD/HD+ODD/CD and 11 normal controls. All children were between 8 and 14 years old. Event-related potentials and behavioural responses were recorded. An initial go-signal related microstate, a subsequent Stop-signal related N200, and performance measures were analyzed using ANCOVA with age as covariate.

Results

Groups did not differ in accuracy or reaction time to the Go-stimuli. However, all clinical groups displayed reduced map strength in a microstate related to initial processing of the Go-stimulus compared to normal controls, whereas topography did not differ. Concerning motor response inhibition, the AD/HD-only and the ODD/CD-only groups displayed slower Stop-signal reaction times (SSRT) and Stop-failure reaction time compared to normal controls. In children with comorbid AD/HD+ODD/CD, Stop-failure reaction-time was longer than in controls, but their SSRT was not slowed. Moreover, SSRT in AD/HD+ODD/CD was faster than in AD/HD-only or ODD/CD-only. The AD/HD-only and ODD/CD-only groups displayed reduced Stop-N200 mean amplitude over right-frontal electrodes. This effect reached only a trend for comorbid AD/HD+ODD/CD.

Conclusion

Following similar attenuations in initial processing of the Go-signal in all clinical groups compared to controls, distinct Stop-signal related deficits became evident in the clinical groups. Both children with AD/HD and ODD/CD showed deficits in behavioural response-inhibition accompanied by decreased central conflict signalling or inhibition processes. Neither behavioural nor neural markers of inhibitory deficits as found in AD/HD-only and ODD/CD-only were additive. Instead, children with comorbid AD/HD+ODD/CD showed similar or even less prominent inhibition deficits than the other clinical groups. Hence, the AD/HD+ODD/CD-group may represent a separate clinical entity.

Cortical activation related to arm-movement combinations

Recent studies support the long-standing hypothesis that continuous arm movements consist of overlapping, discrete submovements. However, the cortical activation associated with these submovements is unclear. We tested the hypothesis that electroencephalography (EEG) activity would more strongly correspond to the particular combinations of muscle electrical activity, the independent components (ICs) of surface electromyography (EMG), than the surface EMG from individual muscles alone. We examined data recorded from two normal subjects performing sustained submaximal contractions or continual, unpaced repetitive movements of the arm. Independent component analysis (ICA) was used to determine the ICs of the multichannel EMG recordings (EMGICs). ICA was also used to calculate the coupling between the simultaneously recorded EEG and the EMG from a single muscle (Subject 1) or the EMGICs (Subject 2). The EMGICs were either tonic or phasic. The significant couplings between the EEG and the EMGICs were different for each EMGIC. The distribution on the scalp of the coupling between the EEG and tonic EMGICs and those of the single-muscle EMG were similar and followed topographic patterns in sensorimotor regions. Couplings between the EEG and phasic EMGICs were bifrontal, lateral, and bioccipital and were significantly stronger than the coupling between a single muscle's EMG and the EEG (p < 2 x 10(-5)) or another EMG combination derived from principal component analysis. These preliminary results support the notion that electrophysiological cortical activations are more significantly related to the ICs of muscle activations than to the activations of individual muscles alone.

Phasic and tonic coupling between EEG and EMG demonstrated with independent component analysis

The authors describe a method for demonstrating the tonic and phasic couplings between suitably time-aligned surface eletromyographs (sEMGs) and the simultaneously recorded EEGs. The method, based on independent component analysis, was applied to data recorded from two normal subjects performing sustained submaximal contractions or continual repetitive movements of the arm. Augmented datasets, consisting of the EEG and either the sEMG from a single muscle (subject 1) or a combination of sEMGs from several muscles (subject 2), were analyzed with independent component analysis to determine the EEG/sEMG coupling. Each derived coupling consisted of a spatial distribution on the scalp and a waveform representing an EEG channel combination coactivating with the sEMG. The combinations of sEMGs, derived by applying independent component analysis to the simultaneous sEMG recordings from several muscles to create sEMG independent components (ICs), were either tonic or phasic with differing periods of activation. The topographic distributions on the scalp of the couplings between the EEG and sEMG ICs were different for each sEMG IC. The spatial distributions of the couplings between tonic sEMG ICs or single-muscle sEMGs and the EEG followed topographic patterns in sensorimotor regions. Phasic couplings were bifrontal, lateral, and bioccipital. Calculation of coherence between the sEMG ICs and calculated EEG combinations agreed well with the frequency spectra of the independent component analysis-derived coupling waveforms. These preliminary results demonstrate that detection of both the tonic and phasic coupling between the sEMG and the EEG is possible when monitoring unpaced proximal arm movement. This may thus be a practical means of exploring the dynamic cortical/muscle relationships in subjects unable to perform fine finger movements, such as patients recovering from stroke.

Asymmetries in brain maturation and behavioral disturbances: multivariate electroencephalogram and P300 studies

If behavior results from brain function, some evidence of dysfunction could be expected in children with major behavioral problems. Yet, neurophysiologic studies in these children are frequently normal. We hypothesized a relationship between maturational asymmetry and behavior, given the role of hemispheric imbalance in adult psychopathology. The purpose of this study was to investigate whether age-sensitive neurophysiologic measures could identify behaviorally relevant maturational asymmetries in otherwise healthy children. Ninety-five children were studied; reasons for testing were behavioral (19), academic (12), medical nonneurologic (16), and mixed (28), along with 20 control subjects. Academic, behavioral (Child Behavioral Checklist), and psychometric (Wechsler Intelligence Scale for Children-Revised; WISC-R) measures were analyzed in relation to four neurophysiologic parameters: P300 Latency, P300 Latency Asymmetry, Maturational Z-score, and Maturational Z-score Asymmetry, within a canonical design. The highest correlation was behavior with Maturational Z-score Asymmetry. Academic scores were predicted by the three-variable interaction of P300 Latency,Maturational Z-score, and Maturational Z-score Asymmetry. We concluded that behavior was strongly influenced by maturational asymmetry, while academic performance depended on both global maturation and maturational asymmetry. Our results suggest that behavioral disturbances can have a neural substrate despite apparently normal electroencephalograms (EEGs) and event-related potentials (ERPs). They open the possibility for specific therapeutic interventions to improve behavior and performance, and, perhaps, prevent major psychopathology in later life.