Julie Onton

Frontal midline EEG dynamics during working memory

We show that during visual working memory, the electroencephalographic (EEG) process producing 5-7 Hz frontal midline theta (fmtheta) activity exhibits multiple spectral modes involving at least three frequency bands and a wide range of amplitudes. The process accounting for the fmtheta increase during working memory was separated from 71-channel data by clustering on time/frequency transforms of components returned by independent component analysis (ICA). Dipole models of fmtheta component scalp maps were consistent with their generation in or near dorsal anterior cingulate cortex. From trial to trial, theta power of fmtheta components varied widely but correlated moderately with theta power in other frontal and left temporal processes. The weak mean increase in frontal midline theta power with increasing memory load, produced entirely by the fmtheta components, largely reflected progressively stronger theta activity in a relatively small proportion of trials. During presentations of letter series to be memorized or ignored, fmtheta components also exhibited 12-15 Hz low-beta activity that was stronger during memorized than during ignored letter trials, independent of letter duration. The same components produced a brief 3-Hz burst 500 ms after onset of the Probe letter following each letter sequence. A new decomposition method, log spectral ICA, applied to normalized log time/frequency transforms of fmtheta component Memorize-letter trials, showed that their low-beta activity reflected harmonic energy in continuous, sharp-peaked theta wave trains as well as independent low-beta bursts. Possibly, the observed fmtheta process variability may index dynamic adjustments in medial frontal cortex to trial-specific behavioral context and task demands.

Imaging human EEG dynamics using independent component analysis.

This review discusses the theory and practical application of independent component analysis (ICA) to multi-channel EEG data. We use examples from an audiovisual attention-shifting task performed by young and old subjects to illustrate the power of ICA to resolve subtle differences between evoked responses in the two age groups. Preliminary analysis of these data using ICA suggests a loss of task specificity in independent component (IC) processes in frontal and somatomotor cortex during post-response periods in older as compared to younger subjects, trends not detected during examination of scalp-channel event-related potential (ERP) averages. We discuss possible approaches to component clustering across subjects and new ways to visualize mean and trial-by-trial variations in the data, including ERP-image plots of dynamics within and across trials as well as plots of event-related spectral perturbations in component power, phase locking, and coherence. We believe that widespread application of these and related analysis methods should bring EEG once again to the forefront of brain imaging, merging its high time and frequency resolution with enhanced cm-scale spatial resolution of its cortical sources.

Independent EEG sources are dipolar

Independent component analysis (ICA) and blind source separation (BSS) methods are increasingly used to separate individual brain and non-brain source signals mixed by volume conduction in electroencephalographic (EEG) and other electrophysiological recordings. We compared results of decomposing thirteen 71-channel human scalp EEG datasets by 22 ICA and BSS algorithms, assessing the pairwise mutual information (PMI) in scalp channel pairs, the remaining PMI in component pairs, the overall mutual information reduction (MIR) effected by each decomposition, and decomposition ‘dipolarity’ defined as the number of component scalp maps matching the projection of a single equivalent dipole with less than a given residual variance. The least well-performing algorithm was principal component analysis (PCA); best performing were AMICA and other likelihood/mutual information based ICA methods. Though these and other commonly-used decomposition methods returned many similar components, across 18 ICA/BSS algorithms mean dipolarity varied linearly with both MIR and with PMI remaining between the resulting component time courses, a result compatible with an interpretation of many maximally independent EEG components as being volume-conducted projections of partially-synchronous local cortical field activity within single compact cortical domains. To encourage further method comparisons, the data and software used to prepare the results have been made available (http://sccn.ucsd.edu/wiki/BSSComparison).

High-frequency Broadband Modulations of Electroencephalographic Spectra.

High-frequency cortical potentials in electroencephalographic (EEG) scalp recordings have low amplitudes and may be confounded with scalp muscle activities. EEG data from an eyes-closed emotion imagination task were linearly decomposed using independent component analysis (ICA) into maximally independent component (IC) processes. Joint decomposition of IC log spectrograms into source- and frequency-independent modulator (IM) processes revealed three distinct classes of IMs that separately modulated broadband high-frequency (∼15–200 Hz) power of brain, scalp muscle, and likely ocular motor IC processes. Multi-dimensional scaling revealed significant but spatially complex relationships between mean broadband brain IM effects and the valence of the imagined emotions. Thus, contrary to prevalent assumption, unitary modes of spectral modulation of frequencies encompassing the beta, gamma, and high gamma frequency ranges can be isolated from scalp-recorded EEG data and may be differentially associated with brain sources and cognitive activities.

Human brain dynamics accompanying use of egocentric and allocentric reference frames during navigation

Maintaining spatial orientation while travelling requires integrating spatial information encountered from an egocentric viewpoint with accumulated information represented within egocentric and/or allocentric reference frames. Here, we report changes in high-density EEG activity during a virtual tunnel passage task in which subjects respond to a postnavigation homing challenge in distinctly different ways—either compatible with a continued experience of the virtual environment from a solely egocentric perspective or as if also maintaining their original entrance orientation, indicating use of a parallel allocentric reference frame. By spatially filtering the EEG data using independent component analysis, we found that these two equal subject subgroups exhibited differences in EEG power spectral modulation during tunnel passages in only a few cortical areas. During tunnel turns, stronger alpha blocking occurred only in or near right primary visual cortex of subjects whose homing responses were compatible with continued use of an egocentric reference frame. In contrast, approaching and during tunnel turns, subjects who responded in a way compatible with use of an allocentric reference frame exhibited stronger alpha blocking of occipito-temporal, bilateral inferior parietal, and retrosplenial cortical areas, all areas implicated by hemodynamic imaging and neuropsychological observation in construction and maintenance of an allocentric reference frame. We conclude that in these subjects, stronger activation of retrosplenial and related cortical areas during turns support a continuous translation of egocentrically experienced visual flow into an allocentric model of their virtual position and movement.

Emotion Recognition from EEG during Self-Paced Emotional Imagery

Here we present an analysis of a 12-subject electroencephalographic (EEG) data set in which participants were asked to engage in prolonged, self-paced episodes of guided emotion imagination with eyes closed. Our goal is to correctly predict, given a short EEG segment, whether the participant was imagining a positive respectively negative-valence emotional scenario during the given segment using a predictive model learned via machine learning. The challenge lies in generalizing to novel (i.e., previously unseen) emotion episodes from a wide variety of scenarios including love, awe, frustration, anger, etc. based purely on spontaneous oscillatory EEG activity without stimulus event-locked responses. Using a variant of the Filter-Bank Common Spatial Pattern algorithm, we achieve an average accuracy of 71.3% correct classification of binary valence rating across 12 different emotional imagery scenarios under rigorous block-wise cross-validation.

Mapping single-trial EEG records on the cortical surface through a spatiotemporal modality

Event-related potentials (ERPs) induced by visual perception and cognitive tasks have been extensively studied in neuropsychological experiments. ERP activities time-locked to stimulus presentation and task performance are often observed separately at individual scalp channels based on averaged time series across epochs and experimental subjects. An analysis using averaged EEG dynamics could discount information regarding interdependency between ongoing EEG and salient ERP features. Advanced tools such as independent component analysis (ICA) have been developed for decomposing collections of single-trial EEG records into separate features. Those features (or independent components) can then be mapped onto the cortical surface using source localization algorithms to visualize brain activation maps and to study between-subject consistency. In this study, we propose a statistical framework for estimating the time course of spatiotemporally independent EEG components simultaneously with their cortical distributions. Within this framework, we implemented Bayesian spatiotemporal analysis for imaging the sources of EEG features on the cortical surface. The framework allows researchers to include prior knowledge regarding spatial locations as well as spatiotemporal independence of different EEG sources. The use of the Electromagnetic Spatiotemporal ICA (EMSICA) method is illustrated by mapping event-related EEG dynamics induced by events in a visual two-back continuous performance task. The proposed method successfully identified several interesting components with plausible corresponding cortical activation topographies, including processes contributing to the late positive complex (LPC) located in central parietal, frontal midline, and anterior cingulate cortex, to atypical mu rhythms associated with the precentral gyrus, and to the central posterior alpha activity in the precuneus.

Reduced Gi and Go protein function in the rat nucleus accumbens attenuates sensorimotor gating deficits

Prepulse inhibition of the acoustic startle response (PPI) is a cross-species measure of sensorimotor gating, which is severely disrupted in patients with schizophrenia. PPI deficits can be produced in experimental animals by administration of selective D(2)-like dopamine receptor agonists in the nucleus accumbens (NAc). G proteins coupled to these receptors reportedly are altered in the NAc of patients with schizophrenia. Therefore, we sought to determine whether experimental inactivation of intracellular G proteins in the NAc alters PPI. In adult male Sprague-Dawley rats, baseline PPI was determined by presenting acoustic pulse stimuli (120 dB) alone or preceded 100 ms earlier by prepulse stimuli (3, 6 or 12 dB above 70 dB ambient noise). PPI disruption was assessed in the presence of quinpirole (0.0, 0.05, 0.1, 0.5 mg/kg, sc), and pertussis toxin (PTX; 0.05 microg/side) was then infused into the NAc bilaterally. Ten days later, quinpirole-mediated disruption of PPI was significantly reduced; neither PTX alone, nor heat-inactivated PTX had any effect on quinpirole-induced PPI reductions. PPI was significantly higher after PTX infusion upon moderate quinpirole challenge, suggesting that D(2)-like receptors were less effective. PTX treatment significantly reduced basal and dopamine-stimulated [35S]GTPgammaS binding in the NAc core and shell, and reduced G(i)(alpha) protein immunoreactivity in the NAc. The results suggest that PPI disruption mediated by D(2)-like receptor activation in the NAc depends on coupling to G(i) and G(o) proteins, alteration of which could cause sensorimotor gating deficits in schizophrenia.

Inhibition of nitric oxide synthase in the ventral tegmental area attenuates cocaine sensitization in rats

1. Male Sprague-Dawley rats were pretreated via bilateral infusion of the VTA with the selective neuronal nitric oxide synthase inhibitor, 7-nitroindazole (0, 8, or 40 ng/hemisphere), prior to each of 7 daily systemic cocaine (30 mg/kg, i.p.) or saline (1 ml/kg) treatments. 2. After a 7-day treatment withdrawal period, rats received a final systemic challenge with either cocaine (30 mg/kg, i.p.) or saline (1 ml/kg). 3. Locomotor and stereotypic activity were measured following the first and last treatments. 4. Daily cocaine treatment led to the development of sensitization to its stereotypic effects as revealed upon drug challenge. 5. The development of sensitization of cocaine-induced stereotypy was completely blocked by daily intra-VTA pretreatment with 7-nitroindazole. 6. In addition, attenuation of the locomotor effects of cocaine challenge was also observed in animals that received daily intra-VTA 7-nitroindazole (40 ng/hemisphere) infusions. 7. The results indicate that VTA nitric oxide is necessary for the development of sensitization of cocaine-induced stereotypic behavior, and that its repeated inhibition may produce lasting effects on the locomotor response to the drug.

Combat veterans with PTSD after mild TBI exhibit greater ERPs from posterior–medial cortical areas while appraising facial features

Posttraumatic stress disorder (PTSD) worsens prognosis following mild traumatic brain injury (mTBI). Combat personnel with histories of mTBI exhibit abnormal activation of distributed brain networks-including emotion processing and default mode networks. How developing PTSD further affects these abnormalities has not been directly examined. We recorded electroencephalography in combat veterans with histories of mTBI, but without active PTSD (mTBI only, n=16) and combat veterans who developed PTSD after mTBI (mTBI+PTSD, n=16)-during the Reading the Mind in the Eyes Test (RMET), a validated test of empathy requiring emotional appraisal of facial features. Task-related event related potentials (ERPs) were identified, decomposed using independent component analysis (ICA) and localized anatomically using dipole modeling. We observed larger emotional face processing ERPs in veterans with mTBI+PTSD, including greater N300 negativity. Furthermore, greater N300 negativity correlated with greater PTSD severity, especially avoidance/numbing and hyperarousal symptom clusters. This correlation was dependent on contributions from the precuneus and posterior cingulate cortex (PCC). Our results support a model where, in combat veterans with histories of mTBI, larger ERPs from over-active posterior-medial cortical areas may be specific to PTSD, and is likely related to negative self-referential activity.