Early changes in alpha band power and DMN BOLD activity in Alzheimer's disease: a simultaneous resting state EEG-fMRI study

Simultaneous resting state functional magnetic resonance imaging (rsfMRI)-resting state electroencephalography (rsEEG) studies in healthy adults showed robust positive associations of signal power in the alpha band with BOLD signal in the thalamus, and more heterogeneous associations in cortical default mode network (DMN) regions. Negative associations were found in occipital regions. In Alzheimer's disease (AD), rsfMRI studies revealed a disruption of the DMN, while rsEEG studies consistently reported a reduced power within the alpha band. The present study is the first to employ simultaneous rsfMRI-rsEEG in an AD sample, investigating the association of alpha band power and BOLD signal, compared to healthy controls (HC). We hypothesized to find reduced positive associations in DMN regions and reduced negative associations in occipital regions in the AD group. Simultaneous resting state fMRI-EEG was recorded in 14 patients with mild AD and 14 HC, matched for age and gender. Power within the EEG alpha band (8-12 Hz, 8-10 Hz, and 10-12 Hz) was computed from occipital electrodes and served as regressor in voxel-wise linear regression analyses, to assess the association with the BOLD signal. Compared to HC, the AD group showed significantly decreased positive associations between BOLD signal and occipital alpha band power in clusters in the superior, middle and inferior frontal cortex, inferior temporal lobe and thalamus (p < 0.01, uncorr., cluster size ≥ 50 voxels). This group effect was more pronounced in the upper alpha sub-band, compared to the lower alpha sub-band. Notably, we observed a high inter-individual heterogeneity. Negative associations were only reduced in the lower alpha range in the hippocampus, putamen and cerebellum. The present study gives first insights into the relationship of resting-state EEG and fMRI characteristics in an AD sample. The results suggest that positive associations between alpha band power and BOLD signal in numerous regions, including DMN regions, are diminished in AD

Integration of Simultaneous Resting-State EEG, fMRI, and Eye Tracker Methods to Determine and Verify EEG Vigilance Measure

Resting-state functional magnetic resonance imaging (rsfMRI) has been widely used for studying the (presumably) awake and alert human brain. Although rsfMRI scans are typically collected while individuals are instructed to focus their eyes on a fixation cross, objective and verified experimental measures to quantify degree of alertness (e.g., vigilance) are not readily available. Concurrent electroencephalography and fMRI (EEG-fMRI) measurements are also widely used to study human brain with high spatial/temporal resolution. EEG is the modality extensively used for estimating vigilance during eyes-closed resting state. On the other hand, pupil size measured using an eye-tracker device could provide an indirect index of vigilance. In this study, we investigated whether simultaneous multimodal EEG-fMRI combined with eye-tracker measurements can be used to determine EEG signal feature associated with pupil size changes (e.g., vigilance measure) in healthy human subjects (n=10) during brain rest with eyes open. We found that EEG frontal and occipital beta power (FOBP) correlates with pupil size changes, an indirect index for locus coeruleus activity implicated in vigilance regulation (r=0.306, p<0.001). Moreover, FOBP also correlated with heart rate (r=0.255, p<0.001), as well as several brain regions in the anti-correlated network, including the bilateral insula and inferior parietal lobule. These results support the conclusion that FOBP is an objective measure of vigilance in healthy human subjects

Validation of non-REM sleep stage decoding from resting state fMRI using linear support vector machines

A growing body of literature suggests that changes in consciousness are reflected in specific connectivity patterns of the brain as obtained from resting state fMRI (rs-fMRI). As simultaneous electroencephalography (EEG) is often unavailable, decoding of potentially confounding sleep patterns from rs-fMRI itself might be useful and improve data interpretation. Linear support vector machine classifiers were trained on combined rs-fMRI/EEG recordings from 25 subjects to separate wakefulness (S0) from non-rapid eye movement (NREM) sleep stages 1 (S1), 2 (S2), slow wave sleep (SW) and all three sleep stages combined (SX). Classifier performance was quantified by a leave-one-subject-out cross-validation (LOSO-CV) and on an independent validation dataset comprising 19 subjects. Results demonstrated excellent performance with areas under the receiver operating characteristics curve (AUCs) close to 1.0 for the discrimination of sleep from wakefulness (S0|SX), S0|S1, S0|S2 and S0|SW, and good to excellent performance for the classification between sleep stages (S1|S2:~0.9; S1|SW:~1.0; S2|SW:~0.8). Application windows of fMRI data from about 70 s were found as minimum to provide reliable classifications. Discrimination patterns pointed to subcortical-cortical connectivity and within-occipital lobe reorganization of connectivity as strongest carriers of discriminative information. In conclusion, we report that functional connectivity analysis allows valid classification of NREM sleep stages

Simultaneous pupillometry and functional Magnetic Resonance Imaging (fMRI) for the detection of stress-related endophenotypes

Mental diseases constitute a core health challenge of the 21st century. To date, diagnostics in psychiatry have been primarily based on subjective self-reports, largely bypassing the biological underpinnings and phenotypic heterogeneity of psychiatric disorders. As an effort to implement a more biologically valid classification of mental disorders, recent initiatives like the Research Domain Criteria (RDoC) project aim to identify endophenotypes that reflect transdiagnostic core mechanisms of psychiatric disorders. Stress is known to play a fundamental role in the development of mood and anxiety disorders. One key system involved in the physiological response to stress is the brainstem?s noradrenergic (NA) arousal center located in the locus coeruleus (LC), and previous studies indicate that pupil size provides an indirect index for activity of the LC-NA system. In order to investigate the relationship between spontaneous drifts in autonomic arousal and global brain activity in healthy human subjects, we first determined the fMRI correlates of spontaneous pupil fluctuations during the resting state. We found that pupil dilations are strongly coupled to activation of the dorsal anterior cingulate cortex (dACC) and bilateral insula (salience network [SN]). To assess whether this link between the pupil and the SN would also extend to emotional arousal, we next investigated the neural correlates of reward anticipation-induced pupil dilations in healthy subjects. Here, we could show that a cue signaling the possibility to receive a monetary reward evoked strong pupil dilations, the magnitude of which predicted response time to a target cue. Again, pupil dilations were strongly linked to SN activation. Furthermore, our results suggest that pupillometry is helpful to dissect different phases of reward anticipation and associated brain activity, disentangling reward prediction, arousal modulation and attentionrelated processes. These observations led us to the conclusion that the SN modulates arousal levels to optimize task performance, that is, to counteract drowsiness/ transitions to sleep during the resting state and to facilitate reward-directed behaviors in the reward anticipation task. Taken together, pupillometry appears to provide a reliable index for activity of the SN, a core network related to psychiatric disorders, making it a promising tool for the detection of stress-related endophenotypes

Advancing Multimodal Approaches to Study Human Brain: Improvements in Simultaneous EEG-fMRI Acquisition

The primary aim of the study detailed in this dissertation was improving the quality of simultaneous electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) experiments. Two common challenges to use concurrent EEG-fMRI tests are addressed herein. The first is the presence of EEG artifacts during simultaneous EEG-fMRI, which require more consideration than EEG data recorded outside the scanner. To mitigate this issue, a fully automated artifact correction pipeline was developed. In the proposed pipeline, magnetic resonance (MR) environmental (i.e., gradient and ballistocardiogram [BCG]) artifacts were reduced using optimal basis sets (OBS) and average artifact subtraction (AAS). Subsequently, independent component analysis (ICA) was leveraged for reducing physiological artifacts (e.g., eye blinks, saccade and muscle artifacts), in addition to residual BCG artifacts. To validate pipeline performance, both resting-state (time/frequency and frequency analysis) and task-based (event related potential [ERP]) EEG data from eight healthy participants were tested. This data was compared with the time/frequency and frequency results achieved by matching meticulously, manually corrected EEG data to the automatically corrected EEG data. No significant difference was found between results. A comparison between ERP results (e.g., amplitude measures and SNR) also showed no differences between manually corrected and fully automated EEG corrected data. The second challenge addressed in this work is the low experimental control over the subject's actual behavior during the eyes-open resting-state fMRI (rsfMRI). This technique has been widely used for studying the (presumably) awake and alert human brain using multimodal EEG-fMRI; however, objective and verified experimental measures to quantify the degree of alertness (e.g., vigilance) are not readily available. To this end, the study reported in this dissertation investigated whether simultaneous multimodal EEG, rsfMRI and eye-tracker experiments could be used to extract objective and robust biomarkers of vigilance in healthy human subjects (n = 10) during cross fixation. Frontal and occipital beta power (FOBP) were found to correlate (r = 0.306, p<0.001) with pupil size fluctuation, which is an indirect index for locus coeruleus activity implicated in vigilance regulation. Moreover, FOBP was also correlated with heart rate (r = 0.255, p<0.001) and several brain regions in an anti-correlated network, including the bilateral insula and inferior parietal lobule. Results support the conclusion that FOBP is an objective and robust biomarker of vigilance in healthy human subjects

Drug and disease effects on the human brain studied by functional MRI

Background: With the advent of magnetic resonance imaging (MRI) technology, various functional MRI (fMRI) techniques have become available for non-invasive neuroscientific studies and clinical diagnostics, which have led to a better understanding of the human brain function in normal and diseased subjects. In order to interpret the fMRI results correctly and design optimal research studies it is important to understand both the potentials and limitations associated with each fMRI technique. In this thesis we used two fMRI techniques: arterial spin labeling (ASL) and resting-sate BOLD (blood-oxygen-level dependent) fMRI to study the effects of a CNS-active (central nervous system) drug and neurologic disorder on the human brain function. Purpose: The main research purposes of this thesis are the following: 1) We assess the reproducibility and reliability of rCBF (regional cerebral blood flow) measurements conducted at 3T with pCASL (pseudo continuous ASL) technique; 2) We study the pharmacokinetics of a CNS active drug in normal volunteers by conducting rCBF measurements as a function of time after intake of a single dose of 20 mg d-amphetamine with the pCASL technique; 3) We investigate the possible neurological abnormalities of mild traumatic brain injury (mTBI) patients with chronic fatigue by performing rCBF and resting-sate functional connectivity measurements before, during and after a 20 minute continuous psychomotor vigilance task (PVT). Conclusion: The results from these studies show that the pCASL technique is a relatively robust method for quantitative measurements of rCBF in both normal volunteers and patient subjects. Repeated rCBF measurements with the pCASL method is a non-invasive and sufficiently sensitive approach to assess pharmacokinetic response to CNS active chemicals and should be useful for studying the neurophysiological characteristics in vivo of potential CNS drugs. The results from the mTBI subjects demonstrate that the repeated measurements of rCBF and functional connectivity metrics before, during and after a PVT provide sensitive diagnostic imaging methods to assess neurological abnormality of mTBI patients without apparent neuroanatomical damage. In addition to the clinical diagnostic value, these studies also contribute to important knowledge for the design and analysis of brain functional imaging studies of drugs and neurological diseases

Connectivity dynamics from wakefulness to sleep

Interest in time-resolved connectivity in fMRI has grown rapidly in recent years. The most widely used technique for studying connectivity changes over time utilizes a sliding windows approach. There has been some debate about the utility of shorter versus longer windows, the use of fixed versus adaptive windows, as well as whether observed resting state dynamics during wakefulness may be predominantly due to changes in sleep state and subject head motion. In this work we use an independent component analysis (ICA)-based pipeline applied to concurrent EEG/fMRI data collected during wakefulness and various sleep stages and show: 1) connectivity states obtained from clustering sliding windowed correlations of resting state functional network time courses well classify the sleep states obtained from EEG data, 2) using shorter sliding windows instead of longer non-overlapping windows improves the ability to capture transition dynamics even at windows as short as 30 ​s, 3) motion appears to be mostly associated with one of the states rather than spread across all of them 4) a fixed tapered sliding window approach outperforms an adaptive dynamic conditional correlation approach, and 5) consistent with prior EEG/fMRI work, we identify evidence of multiple states within the wakeful condition which are able to be classified with high accuracy. Classification of wakeful only states suggest the presence of time-varying changes in connectivity in fMRI data beyond sleep state or motion. Results also inform about advantageous technical choices, and the identification of different clusters within wakefulness that are separable suggest further studies in this direction.Fil: Damaraju, Eswar. Instituto Tecnológico de Georgia; Estados UnidosFil: Tagliazucchi, Enzo Rodolfo. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Física de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Física de Buenos Aires; ArgentinaFil: Laufs, Helmut. Goethe Universitat Frankfurt; AlemaniaFil: Calhoun, Vince D.. Instituto Tecnológico de Georgia; Estados Unido

Neural mechanisms of visual awareness and their modulation by social threat

The human brain can extract an enormous wealth of visual information from our surroundings. However, only a fraction of this immense data set ever becomes available to the observer’s awareness. How and why certain information is selected for awareness are questions under active investigation. Following two introductory chapters, this thesis contains six inter-related experimental chapters, through which I will explore two key outstanding questions in this field, using bistable perceptual paradigms to study conscious and non-conscious visual processing in healthy human volunteers. The first major theme focuses on adding new insight into the brain regions and networks that facilitate transfer between non-conscious and conscious modes of visual processing. In Chapters 3 and 4 I will use fMRI, both in task-related and resting-state conditions, to delineate areas, and their interactions (in terms of effective connectivity), which are relevant for transition between different conscious perceptual experiences. In Chapter 5 I will focus on one specific region in the proposed perceptual transition-related network (the frontal eye field) and explore its causal role in access to awareness using repetitive TMS. The second key question explored in this thesis is how social cues in the visual environment influence non-conscious visual processing as well as transition to conscious vision. In Chapter 6 I will study behavioural effects of non-conscious social cues from faces, and the relationship of these effects to focal brain anatomy. Based on finding slower perceptuomotor performance when non-conscious faces contain threatening cues in Chapter 6, I hypothesise that a defensive freezing response is engaged in such situations. The final two experimental chapters will explore the correlates of putative human freezing in the context of non-conscious social threat: using fMRI and psychophysiological measurements to study effects on perceptual transition in Chapter 7, and relating TMS-induced motor-evoked potentials and concurrent psychophysiological measurements to non-conscious perceptuomotor performance in Chapter 8. Taken together, the presented findings shed new light on the network of brain regions involved in transition between non-conscious and conscious modes of visual processing. In addition, they uncover novel mechanisms through which socially relevant visual cues shape our awareness of the visual world, with particular emphasis on the engagement of defensive responses by socially threatening stimuli. The concluding chapter discusses the implications of these findings and explores relevant avenues for future work

Cognitive Flexibility: A Default Mode Perspective

The intra/extradimensional set-shifting task (IED) provides a reliable assessment of cognitive flexibility, the shifting of attention to select behaviorally relevant stimuli in a given context. Impairments in this domain were previously reported in patients with altered neurotransmitter systems such as schizophrenia and Parkinson's disease. Consequently, corticostriatal connections were implicated in the mediation of this function. In addition, parts of the default mode network (DMN), namely the medial prefrontal and posterior cingulate/precuneus cortices, are also being progressively described in association with set-shifting paradigms. Nevertheless, a definitive link between cognitive flexibility and DMN connectivity remains to be established. To this end, we related resting state functional magnetic resonance imaging (fMRI)-based functional connectivity of DMN with IED task performance in a healthy population, measured outside the scanner. The results demonstrated that greater posterior cingulate cortex/precuneus (DMN) connectivity with the ventromedial striatopallidum at rest correlated with fewer total adjusted errors on the IED task. This finding points to a relationship between DMN and basal ganglia connectivity for cognitive flexibility, further highlighting this network's potential role in adaptive human cognition.The Evelyn Trust (RUAG/018) supported this research. Additionally, DV received funding from the Yousef Jameel Academic Program; DKM is funded by the NIHR Cambridge Biomedical Centre (RCZB/004), and an NIHR Senior Investigator Award (RCZB/014), and EAS is supported by the Stephen Erskine Fellowship Queens’ College, Cambridge. We would also like to thank Dr. Guy Williams and Victoria Lupson and the rest of the staff in the Wolfson Brain Imaging Centre (WBIC) at Addenbrooke’s Hospital for their assistance in scanning. Finally, we thank all the participants for their contribution to this studyThis is the author accepted manuscript. The final version is available from Mary Ann Liebert via http://dx.doi.org/10.1089/brain.2015.038