Mind over chatter: plastic up-regulation of the fMRI alertness network by EEG neurofeedback

EEG neurofeedback (NFB) is a brain-computer interface (BCI) approach used to shape brain oscillations by means of real-time feedback from the electroencephalogram (EEG), which is known to reflect neural activity across cortical networks. Although NFB is being evaluated as a novel tool for treating brain disorders, evidence is scarce on the mechanism of its impact on brain function. In this study with 34 healthy participants, we examined whether, during the performance of an attentional auditory oddball task, the functional connectivity strength of distinct fMRI networks would be plastically altered after a 30-min NFB session of alpha-band reduction (n=17) versus a sham-feedback condition (n=17). Our results reveal that compared to sham, NFB induced a specific increase of functional connectivity within the alertness/salience network (dorsal anterior and mid cingulate), which was detectable 30 minutes after termination of training. Crucially, these effects were significantly correlated with reduced mind-wandering 'on-task' and were coupled to NFB-mediated resting state reductions in the alpha-band (8-12 Hz). No such relationships were evident for the sham condition. Although group default-mode network (DMN) connectivity was not significantly altered following NFB, we observed a positive association between modulations of resting alpha amplitude and precuneal connectivity, both correlating positively with frequency of mind-wandering. Our findings demonstrate a temporally direct, plastic impact of NFB on large-scale brain functional networks, and provide promising neurobehavioral evidence supporting its use as a noninvasive tool to modulate brain function in health and disease

High-frequency neural oscillations and visual processing deficits in schizophrenia

Visual information is fundamental to how we understand our environment, make predictions, and interact with others. Recent research has underscored the importance of visuo-perceptual dysfunctions for cognitive deficits and pathophysiological processes in schizophrenia. In the current paper, we review evidence for the relevance of high frequency (beta/gamma) oscillations towards visuo-perceptual dysfunctions in schizophrenia. In the first part of the paper, we examine the relationship between beta/gamma band oscillations and visual processing during normal brain functioning. We then summarize EEG/MEG-studies which demonstrate reduced amplitude and synchrony of high-frequency activity during visual stimulation in schizophrenia. In the final part of the paper, we identify neurobiological correlates as well as offer perspectives for future research to stimulate further inquiry into the role of high-frequency oscillations in visual processing impairments in the disorder

Dissociating Alzheimer’s Disease from Amnestic Mild Cognitive Impairment using Time-Frequency Based EEG Neurometrics

This work explores the utility of using magnitude (ERSP), phase angle (ITPC), and cross-frequency coupling (PAC) indices derived from electroencephalogram (EEG) recording using spectral decomposition as unique biomarkers of Alzheimer’s Disease (AD) and amnestic mild cognitive impairment (aMCI), respectively. The experimental protocol was a visual oddball discrimination task conducted during a brief (approximately 20 minute) recording session. Participants were 60 older adults from an outpatient memory clinic diagnosed with either aMCI (n=29; M=73.0; SD=9.32) or AD (n=31; M=78.29; SD=8.28) according to NIA-AA criteria. Results indicate that ITPC values differ significantly between AD and MCI groups. Findings contribute to a growing body of literature seeking to document illness-related abnormalities in time-frequency EEG signatures that may serve as reliable indicators of the pathophysiological processes underlying the cognitive deficits observed in AD and aMCI-afflicted populations

Cortico-muscular coherence in sensorimotor synchronisation

This thesis sets out to investigate the neuro-muscular control mechanisms underlying the ubiquitous phenomenon of sensorimotor synchronisation (SMS). SMS is the coordination of movement to external rhythms, and is commonly observed in everyday life. A large body of research addresses the processes underlying SMS at the levels of behaviour and brain. Comparatively, little is known about the coupling between neural and behavioural processes, i.e. neuro-muscular processes. Here, the neuro-muscular processes underlying SMS were investigated in the form of cortico-muscular coherence measured based on Electroencephalography (EEG) and Electromyography (EMG) recorded in human healthy participants. These neuro-muscular processes were investigated at three levels of engagement: passive listening and observation of rhythms in the environment, imagined SMS, and executed SMS, which resulted in the testing of three hypotheses: (i) Rhythms in the environment, such as music, spontaneously modulate cortico-muscular coupling, (ii) Movement intention modulates cortico-muscular coupling, and (iii) Cortico-muscular coupling is dynamically modulated during SMS time-locked to the stimulus rhythm. These three hypotheses were tested through two studies that used Electroencephalography (EEG) and Electromyography (EMG) recordings to measure Cortico-muscular coherence (CMC). First, CMC was tested during passive music listening, to test whether temporal and spectral properties of music stimuli known to induce groove, i.e., the subjective experience of wanting to move, can spontaneously modulate the overall strength of the communication between the brain and the muscles. Second, imagined and executed movement synchronisation was used to investigate the role of movement intention and dynamics on CMC. The two studies indicate that both top-down, and somatosensory and/or proprioceptive processes modulate CMC during SMS tasks. Although CMC dynamics might be linked to movement dynamics, no direct correlation between movement performance and CMC was found. Furthermore, purely passive auditory or visual rhythmic stimulation did not affect CMC. Together, these findings thus indicate that movement intention and active engagement with rhythms in the environment might be critical in modulating CMC. Further investigations of the mechanisms and function of CMC are necessary, as they could have important implications for clinical and elderly populations, as well as athletes, where optimisation of motor control is necessary to compensate for impaired movement or to achieve elite performance

Cortical mechanisms for tinnitus in humans /

PhD ThesisThis work sought to characterise neurochemical and neurophysiological processes underlying tinnitus in humans. The first study involved invasive brain recordings from a neurosurgical patient, along with experimental manipulation of his tinnitus, to map the cortical system underlying his tinnitus. Widespread tinnitus-linked changes in low- and high-frequency oscillations were observed, along with inter-regional and cross-frequency patterns of communication. The second and third studies compared tinnitus patients to controls matched for age, sex and hearing loss, measuring auditory cortex spontaneous oscillations (with magnetoencephalography) and neurochemical concentrations (with magnetic resonance spectroscopy) respectively. Unlike in previous studies not controlled for hearing loss, there were no group differences in oscillatory activity attributable to tinnitus. However, there was a significant correlation between gamma oscillations (>30Hz) and hearing loss in the tinnitus group, and between delta oscillations (1-4Hz) and perceived tinnitus loudness. In the neurochemical study, tinnitus patients had significantly reduced GABA concentrations compared to matched controls, and within this group there was a positive correlation between choline concentration (potentially linked to acetylcholine and/or neuronal plasticity) and both hearing loss, and subjective tinnitus intensity and distress. In light of present and previous findings, tinnitus may be best explained by a predictive coding model of perception, which was tested in the final experiment. This directly controlled the three main quantities comprising predictive coding models, and found that delta/theta/alpha oscillations (1-12Hz) encoded the precision of predictions, beta oscillations (12-30Hz) encoded changes to predictions, and gamma oscillations represented surprise (unexpectedness of stimuli based on predictions). The work concludes with a predictive coding model of tinnitus that builds upon the present findings and settles unresolved paradoxes in the literature. In this, precursor processes (in varying combinations) synergise to increase the precision associated with spontaneous activity in the auditory pathway to the point where it overrides higher predictions of ‘silence’.Medical Research Council Wellcome Trust and the National Institutes of Healt

Exposing Internal Attentional Brain States using Single-Trial EEG Analysis with Combined Imaging Modalities

The goal of this dissertation is to explore the neural correlates of endogenous task-related attentional modulations. Natural fluctuations in task engagement are challenging to study, primarily because they are by nature not event related and thus cannot be controlled experimentally. Here we exploit well-accepted links between attention and various measures of neural activity while subjects perform simple target detection tasks that leave their minds free to wander. We use multimodal neuroimaging, specifically simultaneous electroencephalograpy and functional magnetic resonance imaging (EEG-fMRI) and EEG-pupillometry, with data-driven machine learning methods and study activity across the whole brain. We investigate BOLD fMRI correlates of EEG variability spanning each trial, enabling us to unravel a cascade of attention-related activations and determine their temporal ordering. We study activity during auditory and visual paradigms independently, and we also combine data to investigate supra modal attention systems. Without aiming to study known attention-related functional brain networks, we found correlates of attentional modulations in areas representative of the default mode network (DMN), ventral attention network (VAN), locus coeruleus norepinephrine (LC-NE) system, and regions implicated in generation of the extensively-studied P300 EEG response to target stimuli. Our results reveal complex interactions between known attentional systems, and do so non-invasively to study normal fluctuations of task engagement in the human brain

Distinct phase-amplitude couplings distinguish cognitive processes in human attention

Abstract Spatial attention is the cognitive function that coordinates the selection of visual stimuli with appropriate behavioral responses. Recent studies have reported that phase-amplitude coupling (PAC) of low and high frequencies covaries with spatial attention, but differ on the direction of covariation and the frequency ranges involved. We hypothesized that distinct phase-amplitude frequency pairs have differentiable contributions during tasks that manipulate spatial attention. We investigated this hypothesis with electrocorticography (ECoG) recordings from participants who engaged in a cued spatial attention task. To understand the contribution of PAC to spatial attention we classified cortical sites by their relationship to spatial variables or behavioral performance. Local neural activity in spatial sites was sensitive to spatial variables in the task, while local neural activity in behavioral sites correlated with reaction time. We found two PAC frequency clusters that covaried with different aspects of the task. During a period of cued attention, delta-phase/high-gamma (DH) PAC was sensitive to cue direction in spatial sites. In contrast, theta-alpha-phase/beta-low-gamma-amplitude (TABL) PAC robustly correlated with future reaction times in behavioral sites. Finally, we investigated the origins of TABL PAC and found it corresponded to behaviorally relevant, sharp waveforms, which were also coupled to a low frequency rhythm. We conclude that TABL and DH PAC correspond to distinct mechanisms during spatial attention tasks and that sharp waveforms are elements of a coupled dynamical process

Audiovisual sensory processing in autism spectrum condition.

Autism spectrum condition (ASC) consists of a set of pervasive developmental problems marked by measurable deficits in social interaction and communication, often coupled with specific and repetitive patterns of behavior. Featured restrictions in the capability to communicate and remain attentive can directly relate to the individual’s ability to interact with others within societal norms. Evidence has suggested that the deficits commonly demonstrated by individuals with autism may arise from a disconnect between neural processes governing sensory inputs. Comparing ASC subjects to controls, previous investigations had shown that electroencephalogram (EEG) recordings and event-related potentials (ERPs) evoked via separate auditory and visual stimuli do not display aberrations in latency or amplitude in the ASC individuals. However, the findings reported here suggest decreased latencies in early-evoked potentials. Additionally, during the combined audiovisual task, electrophysiological recordings revealed significant cortical activity differences between ASC subjects and controls. To investigate the aforementioned phenomena this study employed EEG recording technology while subjects participated in an oddball-paradigm reaction time test. This project reports on the differences behavioral reactions as well as variances in amplitude and latency in twelve autistic individuals and twelve matched controls. Subjects were evaluated using the event related potentials, N100, N200, and P300, as well as dipole source coherence and power of EEG gamma oscillations recorded at fronto-central and parietal sites in both hemispheres. Findings of this study suggest that the irregularities arise from deficits in the integration and combinatorial processing of multiple sensory inputs. Previous research investigating the neuropathology of autism has identified abnormalities in the structure, number and activity of the cortical minicolumns, which are believed to influence excitatory and inhibitory impulses of sensory processing. The minicolumns of ASC individuals appear in greater number coupled with increased neuronal density due to a reduction in the volume of peripheral neuropil space and neuronal cell bodies. Such a cortical and cellular arrangement favors the formation of short intralobular connections between neurons at the expense of longer interlobular fibers. This study proposes that aberrations in sensory processing and functional cortical binding, as evidenced by EEG recordings related to the tasks, further reflect underlying abnormalities of minicolumns in ASC individuals. Thus, the results of this project intuitively suggest that dysfunction of sensory processing by way of minicolumn irregularity may in turn lead to symptoms commonly associated with autism spectrum condition

Characterization of Neuroimage Coupling Between EEG and FMRI Using Within-Subject Joint Independent Component Analysis

The purpose of this dissertation was to apply joint independent component analysis (jICA) to electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) to characterize the neuroimage coupling between the two modalities. EEG and fMRI are complimentary imaging techniques which have been used in conjunction to investigate neural activity. Understanding how these two imaging modalities relate to each other not only enables better multimodal analysis, but also has clinical implications as well. In particular, Alzheimer’s, Parkinson’s, hypertension, and ischemic stroke are all known to impact the cerebral blood flow, and by extension alter the relationship between EEG and fMRI. By characterizing the relationship between EEG and fMRI within healthy subjects, it allows for comparison with a diseased population, and may offer ways to detect some of these conditions earlier. The correspondence between fMRI and EEG was first examined, and a methodological approach which was capable of informing to what degree the fMRI and EEG sources corresponded to each other was developed. Once it was certain that the EEG activity observed corresponded to the fMRI activity collected a methodological approach was developed to characterize the coupling between fMRI and EEG. Finally, this dissertation addresses the question of whether the use of jICA to perform this analysis increases the sensitivity to subcortical sources to determine to what degree subcortical sources should be taken into consideration for future studies. This dissertation was the first to propose a way to characterize the relationship between fMRI and EEG signals using blind source separation. Additionally, it was the first to show that jICA significantly improves the detection of subcortical activity, particularly in the case when both physiological noise and a cortical source are present. This new knowledge can be used to design studies to investigate subcortical signals, as well as to begin characterizing the relationship between fMRI and EEG across various task conditions