Low-frequency oscillatory correlates of auditory predictive processing in cortical-subcortical networks: a MEG-study

Emerging evidence supports the role of neural oscillations as a mechanism for predictive information processing across large-scale networks. However, the oscillatory signatures underlying auditory mismatch detection and information flow between brain regions remain unclear. To address this issue, we examined the contribution of oscillatory activity at theta/alpha-bands (4–8/8–13 Hz) and assessed directed connectivity in magnetoencephalographic data while 17 human participants were presented with sound sequences containing predictable repetitions and order manipulations that elicited prediction-error responses. We characterized the spectro-temporal properties of neural generators using a minimum-norm approach and assessed directed connectivity using Granger Causality analysis. Mismatching sequences elicited increased theta power and phase-locking in auditory, hippocampal and prefrontal cortices, suggesting that theta-band oscillations underlie prediction-error generation in cortical-subcortical networks. Furthermore, enhanced feedforward theta/alpha-band connectivity was observed in auditory-prefrontal networks during mismatching sequences, while increased feedback connectivity in the alpha-band was observed between hippocampus and auditory regions during predictable sounds. Our findings highlight the involvement of hippocampal theta/alpha-band oscillations towards auditory prediction-error generation and suggest a spectral dissociation between inter-areal feedforward vs. feedback signalling, thus providing novel insights into the oscillatory mechanisms underlying auditory predictive processing

ERPs and their brain sources in perceptual and conceptual prospective memory tasks: commonalities and differences between the two tasks

The present study examined whether Event-Related Potential (ERP) components and their neural generators are common to perceptual and conceptual prospective memory (PM) tasks or specific to the form of PM cue involved. We used Independent Component Analysis (ICA) to study the contributions of brain source activities to scalp ERPs across the different phases of two event-based PM-tasks: (1) holding intentions during a delay (monitoring) (2) detecting the correct context to perform the delayed intention (cue detection) and (3) carrying out the action (realisation of delayed intentions). Results showed that monitoring for both perceptual and conceptual PM-tasks was characterised by an enhanced early occipital negativity (N200). In addition the conceptual PM-task showed a long-lasting effect of monitoring significant around 700 ms. Perceptual PM-task cues elicited an N300 enhancement associated with cue detection, whereas a midline N400-like response was evoked by conceptual PM-task cues. The Prospective Positivity associated with realisation of delayed intentions was observed in both conceptual and perceptual tasks. A common frontal-midline brain source contributed to the Prospective Positivity in both tasks and a strong contribution from parieto-frontal brain sources was observed only for the perceptually cued PM-task. These findings support the idea that: (1) The enhanced N200 can be understood as a neural correlate of a ‘retrieval mode’ for perceptual and conceptual PM-tasks, and additional strategic monitoring is implemented according the nature of the PM task; (2) ERPs associated with cue detection are specific to the nature of the PM cues; (3) Prospective Positivity reflects a general PM process, but the specific brain sources contributing to it depend upon the nature of the PM task

An introduction to time-resolved decoding analysis for M/EEG

The human brain is constantly processing and integrating information in order to make decisions and interact with the world, for tasks from recognizing a familiar face to playing a game of tennis. These complex cognitive processes require communication between large populations of neurons. The non-invasive neuroimaging methods of electroencephalography (EEG) and magnetoencephalography (MEG) provide population measures of neural activity with millisecond precision that allow us to study the temporal dynamics of cognitive processes. However, multi-sensor M/EEG data is inherently high dimensional, making it difficult to parse important signal from noise. Multivariate pattern analysis (MVPA) or "decoding" methods offer vast potential for understanding high-dimensional M/EEG neural data. MVPA can be used to distinguish between different conditions and map the time courses of various neural processes, from basic sensory processing to high-level cognitive processes. In this chapter, we discuss the practical aspects of performing decoding analyses on M/EEG data as well as the limitations of the method, and then we discuss some applications for understanding representational dynamics in the human brain

Age-related delay in information accrual for faces: Evidence from a parametric, single-trial EEG approach

Background: In this study, we quantified age-related changes in the time-course of face processing by means of an innovative single-trial ERP approach. Unlike analyses used in previous studies, our approach does not rely on peak measurements and can provide a more sensitive measure of processing delays. Young and old adults (mean ages 22 and 70 years) performed a non-speeded discrimination task between two faces. The phase spectrum of these faces was manipulated parametrically to create pictures that ranged between pure noise (0% phase information) and the undistorted signal (100% phase information), with five intermediate steps. Results: Behavioural 75% correct thresholds were on average lower, and maximum accuracy was higher, in younger than older observers. ERPs from each subject were entered into a single-trial general linear regression model to identify variations in neural activity statistically associated with changes in image structure. The earliest age-related ERP differences occurred in the time window of the N170. Older observers had a significantly stronger N170 in response to noise, but this age difference decreased with increasing phase information. Overall, manipulating image phase information had a greater effect on ERPs from younger observers, which was quantified using a hierarchical modelling approach. Importantly, visual activity was modulated by the same stimulus parameters in younger and older subjects. The fit of the model, indexed by R2, was computed at multiple post-stimulus time points. The time-course of the R2 function showed a significantly slower processing in older observers starting around 120 ms after stimulus onset. This age-related delay increased over time to reach a maximum around 190 ms, at which latency younger observers had around 50 ms time lead over older observers. Conclusion: Using a component-free ERP analysis that provides a precise timing of the visual system sensitivity to image structure, the current study demonstrates that older observers accumulate face information more slowly than younger subjects. Additionally, the N170 appears to be less face-sensitive in older observers

Central neuropathic pain in paraplegia alters movement related potentials

Objectives: Spinal Cord Injured (SCI) persons with and without Central Neuropathic Pain (CNP) show different oscillatory brain activities during imagination of movement. This study investigates whether they also show differences in movement related cortical potentials (MRCP). Methods: SCI paraplegic patients with no CNP (n = 8), with CNP in their lower limbs (n = 8), and healthy control subjects (n = 10) took part in the study. EEG clustering involved independent component analysis, equivalent current dipole fitting, and Measure Projection to define cortical domains that have functional modularity during the motor imagery task. Results: Three domains were identified: limbic system, sensory-motor cortex and visual cortex. The MRCP difference between the groups of SCI with and without CNP was reflected in a domain located in the limbic system, while the difference between SCI patients and control subjects was in the sensorimotor domain. Differences in MRCP morphology between patients and healthy controls were visible for both paralysed and non paralysed limbs. Conclusion: SCI but not CNP affects the movement preparation, and both SCI and CNP affect sensory processes. Significance: Rehabilitation strategies of SCI patients based on MRCP should take into account the presence of CNP

Cluster permutation analysis for EEG series based on non-parametric Wilcoxon–Mann–Whitney statistical tests

Cluster-based permutation tests are widely used in neuroscience studies for the analysis of high-dimensional electroencephalography (EEG) and event-related potential (ERP) data as it may address the multiple comparison problem without reducing the statistical power. However, classical cluster-based permutation analysis relies on parametric t-tests, whose assumptions may not be verified in case of non-normality of the data distribution and alternative options may be considered. To overcome this limitation, here we present a new software for a cluster permutation analysis for EEG series based on non-parametric Wilcoxon–Mann–Whitney tests. We tested both t-test and non-parametric Wilcoxon implementations in two independent datasets of ERPs and EEG spectral data: while t-test-based and non-parametric Wilcoxon-based cluster analyses showed similar results in case of ERP data, the t-test implementation was not able to find clustered effects in case of spectral data. We encourage the use of non-parametric statistics for a cluster permutation analysis of EEG data, and we provide a publicly available software for this computation

An optimal oscillatory phase for pattern reactivation during memory retrieval

Computational models and in vivo studies in rodents suggest that the hippocampal system oscillates between states that are optimal for encoding and states that are optimal for retrieval. Here, we show that in humans, neural signatures of memory reactivation are modulated by the phase of a theta oscillation. Electroencephalography (EEG) was recorded while participants were cued to recall previously learned word-object associations, and time-resolved pattern classifiers were trained to detect neural reactivation of the target objects. Classifier fidelity rhythmically fluctuated at 7 or 8 Hz and was modulated by theta phase across the entire recall period. The phase of optimal classification was shifted approximately 180° between encoding and retrieval. Inspired by animal work, we then computed “classifier-locked averages” to analyze how ongoing theta oscillations behaved around the time points at which the classifier indicated memory retrieval. We found strong theta (7 or 8 Hz) phase consistency approximately 300 ms before the time points of maximal neural memory reactivation. Our findings provide important evidence that the neural signatures of memory retrieval fluctuate and are time locked to the phase of an ongoing theta oscillation

A study of event-related electrocortical oscillatory dynamics associated with cued motor-response inhibition during performance of the Go/NoGo task within a sample of prenatally alcohol-exposed children and age-matched controls

Fetal alcohol spectrum disorders (FASDs) are a spectrum of disorders that occur due to prenatal alcohol exposure (PAE). Response inhibition refers to the ability to inhibit/suppress a prepotent behavioural tendency set in motion during an experimental task. Our research explored neocortical processing in heavy-exposed children from Cape Town, South Africa, performing the Go/NoGo response inhibition task. We utilised event-related electroencephalographic methodologies to examine event-related potentials (ERP) and eventrelated changes in induced oscillatory power - event-related desynchronisation (ERD)/eventrelated synchronisation (ERS). Across visual and auditory Go/NoGo tasks, we observed equivalent levels of inhibitory control between heavy-exposed (HE) participants and normally-developing controls; however, HEs demonstrated significantly slower reaction times relative to the control group. In an auditory ERP study, we observed a number of alcohol-related changes in ERP waveform morphology, such as decreased P2 amplitude, reduced P3 amplitude, and longer P3 peak latency. In addition, within the HE group, late in the trials, a slow-wave component was observed in both experimental conditions. A significant difference in N2 amplitude across conditions that has consistently been observed in normally-developing samples was not observed in the HE group. We extended previous research findings in the visual domain by analysing induced oscillatory responses. We observed within the normally-developing sample: (1) in both experimental conditions, a frontal induced beta-band ERS related to decision-making; and (2) in the NoGo-condition, a frontal gamma-band ERS related to cognitive-control. Within the HE group, the beta-ERS was not observed in either of the experimental conditions, neither was the gamma-ERS observed in the NoGo-condition. Frontal induced beta-power was predictive of performance accuracy in the HE group, but not in the control group. The observed alcohol-related effects were not explained and/or mediated by IQ (WISC-IQ), socio-economic circumstances, comorbid ADHD, or teratogenic effects related to postnatal lead exposure and prenatal cigarette-smoke exposure. Our results point to alterations in scalp-measured event-related neocortical oscillatory dynamics and slower processing of task demands due to heavy PAE. These alcohol-related effects are observable on ERP component measures, primarily related to conflict-monitoring and attention-based processing. PAE also affects induced classes of neocortical oscillatory dynamics related to decision-making and cognitive-control processes required to inhibit a prepotent motor-response

Integration of EEG-FMRI in an Auditory Oddball Paradigm Using Joint Independent Component Analysis

The integration of event-related potential (ERP) and functional magnetic resonance imaging (fMRI) can contribute to characterizing neural networks with high temporal and spatial resolution. The overall objective of this dissertation is to determine the sensitivity and limitations of joint independent component analysis (jICA) within-subject for integration of ERP and fMRI data collected simultaneously in a parametric auditory oddball paradigm. The main experimental finding in this work is that jICA revealed significantly stronger and more extensive activity in brain regions associated with the auditory P300 ERP than a P300 linear regression analysis, both at the group level and within-subject. The results suggest that, with the incorporation of spatial and temporal information from both imaging modalities, jICA is more sensitive to neural sources commonly observed with ERP and fMRI compared to a linear regression analysis. Furthermore, computational simulations suggest that jICA can extract linear and nonlinear relationships between ERP and fMRI signals, as well as uncoupled sources (i.e., sources with a signal in only one imaging modality). These features of jICA can be important for assessing disease states in which the relationship between the ERP and fMRI signals is unknown, as well as pathological conditions causing neurovascular uncoupling, such as stroke