Stephen D. Mayhew

Brainstem functional magnetic resonance imaging: Disentangling signal from physiological noise

To estimate the importance of respiratory and cardiac effects on signal variability found in functional magnetic resonance imaging data recorded from the brainstem.

Determination of the human brainstem respiratory control network and its cortical connections in vivo using functional and structural imaging

This study combined functional and structural magnetic resonance imaging techniques, optimized for the human brainstem, to investigate activity in brainstem respiratory control centres in a group of 12 healthy human volunteers. We stimulated respiration with carbon dioxide (CO(2)), and utilized novel methodology to separate its vascular from its neuronal effects upon the blood oxygen level dependent (BOLD) signal. In the brainstem we observed activity in the dorsal rostral pons (representing the Kölliker-Fuse/parabrachial (KF/PB) nuclei and locus coeruleus), the inferior ventral pons and the dorsal and lateral medulla. These areas of activation correspond to respiratory nuclei identified in recent rodent studies. Our results also reveal functional participation of the anteroventral (AV), ventral posterolateral (VPL) ventrolateral thalamic nuclei, and the posterior putamen in the response to CO(2) stimulation, suggesting that these centres may play a role in gating respiratory information to the cortex. As the functional imaging plane was limited to the brainstem and adjacent subcortical areas, we employed diffusion tractography to further investigate cortical connectivity of the thalamic activations. This revealed distinct connectivity profiles of these thalamic activations suggesting subdivision of the thalamus with regards to respiratory control. From these results we speculate that the thalamus plays an important role in integrating respiratory signals to and from the brainstem respiratory centres.

The structural and functional connectivity of the posterior cingulate cortex: comparison between deterministic and probabilistic tractography for the investigation of structure-function relationships.

The default mode network (DMN) is one of the most studied resting-state networks, and is thought to be involved in the maintenance of consciousness within the alert human brain. Although many studies have examined the functional connectivity (FC) of the DMN, few have investigated its underlying structural connectivity (SC), or the relationship between the two. We investigated this question in fifteen healthy subjects, concentrating on connections to the precuneus/posterior cingulate cortex (PCC), commonly considered as the central node of the DMN. We used group independent component analysis (GICA) and seed-based correlation analysis of fMRI data to quantify FC, and streamline and probabilistic tractography to identify structural tracts from diffusion tensor imaging (DTI) data. We first assessed the presence of structural connections between the DMN regions identified with GICA. Of the 15 subjects, when using the probabilistic approach 15 (15) demonstrated connections between the PCC and mesial prefrontal cortex (mPFC), 11 (15) showed connections from the PCC to the right inferior parietal cortex (rIPC) and 8 (15) to the left IPC. Next, we assessed the strength of FC (magnitude of temporal correlation) and SC (mean fractional anisotropy of reconstructed tracts (streamline), number of super-threshold voxels within the mask region (probabilistic)). The lIPC had significantly reduced FC to the PCC compared to the mPFC and rIPC. No difference in SC strength between connections was found using the streamline approach. For the probabilistic approach, mPFC had significantly lower SC than both IPCs. The two measures of SC strength were significantly correlated, but not for all paired connections. Finally, we observed a significant correlation between SC and FC for both tractography approaches when data were pooled across PCC-lIPL, PCC-rIPL and PCC-mPFC connections, and for some individual paired connections. Our results suggest that the streamline approach is advantageous for characterising the connectivity of long white matter tracts (PCC-mPFC), whilst the probabilistic approach was more reliable at identifying PCC-IPC connections. The direct comparison of FC and SC indicated that pairs of nodes with stronger structural connections also had stronger functional connectivity, and that this was maintained with both tractography approaches. Whilst the definition of SC strength remains controversial, our results could be considered to provide some degree of validation for the measures of SC strength that we have used. Direct comparisons of SC and FC are necessary in order to understand the structural basis of functional connectivity, and to characterise and quantify the changes in the brains functional architecture that occur as a result of normal physiology or pathology.

EEG signatures of auditory activity correlate with simultaneously recorded fMRI responses in humans

We recorded auditory-evoked potentials (AEPs) during simultaneous, continuous fMRI and identified trial-to-trial correlations between the amplitude of electrophysiological responses, characterised in the time domain and the time-frequency domain, and the hemodynamic BOLD response. Cortical AEPs were recorded from 30 EEG channels within the 3 T MRI scanner with and without the collection of simultaneous BOLD fMRI. Focussing on the Cz (vertex) EEG response, single-trial AEP responses were measured from time-domain waveforms. Furthermore, a novel method was used to characterise the single-trial AEP response within three regions of interest in the time-frequency domain (TF-ROIs). The latency and amplitude values of the N1 and P2 AEP peaks during fMRI scanning were not significantly different from the Control session (p>0.16). BOLD fMRI responses to the auditory stimulation were observed in bilateral secondary auditory cortices as well as in the right precentral and postcentral gyri, anterior cingulate cortex (ACC) and supplementary motor cortex (SMC). Significant single-trial correlations were observed with a voxel-wise analysis, between (1) the magnitude of the EEG TF-ROI1 (70-800 ms post-stimulus, 1-5 Hz) and the BOLD response in right primary (Heschls gyrus) and secondary (STG, planum temporale) auditory cortex; and (2) the amplitude of the P2 peak and the BOLD response in left pre- and postcentral gyri, the ACC and SMC. No correlation was observed with single-trial N1 amplitude on a voxel-wise basis. An fMRI-ROI analysis of functionally-identified auditory responsive regions identified further single-trial correlations of BOLD and EEG responses. The TF amplitudes in TF-ROI1 and TF-ROI2 (20-400 ms post-stimulus, 5-15 Hz) were significantly correlated with the BOLD response in all bilateral auditory areas investigated (planum temporale, superior temporal gyrus and Heschls gyrus). However the N1 and P2 peak amplitudes, occurring at similar latencies did not show a correlation in these regions. N1 and P2 peak amplitude did correlate with the BOLD response in bilateral precentral and postcentral gyri and the SMC. Additionally P2 and TF-ROI1 both correlated with the ACC. TF-ROI3 (400-900 ms post-stimulus, 4-10 Hz) correlations were only observed in the ACC and SMC. Across the group, the subject-mean N1 peak amplitude correlated with the BOLD response amplitude in the primary and secondary auditory cortices bilaterally, as well as the right precentral gyrus and SMC. We confirm that auditory-evoked EEG responses can be recorded during continuous and simultaneous fMRI. We have presented further evidence of an empirical single-trial coupling between the EEG and BOLD fMRI responses, and show that a time-frequency decomposition of EEG signals can yield additional BOLD fMRI correlates, predominantly in auditory cortices, beyond those found using the evoked response amplitude alone.

Poststimulus undershoots in cerebral blood flow and BOLD fMRI responses are modulated by poststimulus neuronal activity

fMRI is the foremost technique for noninvasive measurement of human brain function. However, its utility is limited by an incomplete understanding of the relationship between neuronal activity and the hemodynamic response. Though the primary peak of the hemodynamic response is modulated by neuronal activity, the origin of the typically negative poststimulus signal is poorly understood and its amplitude assumed to covary with the primary response. We use simultaneous recordings of EEG with blood oxygenation level-dependent (BOLD) and cerebral blood flow (CBF) fMRI during unilateral median nerve stimulation to show that the poststimulus fMRI signal is neuronally modulated. We observe high spatial agreement between concurrent BOLD and CBF responses to median nerve stimulation, with primary signal increases in contralateral sensorimotor cortex and primary signal decreases in ipsilateral sensorimotor cortex. During the poststimulus period, the amplitude and directionality (positive/negative) of the BOLD signal in both contralateral and ipsilateral sensorimotor cortex depends on the poststimulus synchrony of 8–13 Hz EEG neuronal activity, which is often considered to reflect cortical inhibition, along with concordant changes in CBF and metabolism. Therefore we present conclusive evidence that the fMRI time course represents a hemodynamic signature of at least two distinct temporal phases of neuronal activity, substantially improving understanding of the origin of the BOLD response and increasing the potential measurements of brain function provided by fMRI. We suggest that the poststimulus EEG and fMRI responses may be required for the resetting of the entire sensory network to enable a return to resting-state activity levels.

Automated single-trial measurement of amplitude and latency of laser-evoked potentials (LEPs) using multiple linear regression

OBJECTIVE Laser stimulation of Adelta-fibre nociceptors in the skin evokes nociceptive-specific brain responses (laser-evoked potentials, LEPs). The largest vertex complex (N2-P2) is widely used to assess nociceptive pathways in physiological and clinical studies. The aim of this study was to develop an automated method to measure amplitudes and latencies of the N2 and P2 peaks on a single-trial basis. METHODS LEPs were recorded after Nd:YAP laser stimulation of the left hand dorsum in 7 normal volunteers. For each subject, a basis set of 4 regressors (the N2 and P2 waveforms and their respective temporal derivatives) was derived from the time-averaged data and regressed against every single-trial LEP response. This provided a separate quantitative estimate of amplitude and latency for the N2 and P2 components of each trial. RESULTS All estimates of LEP parameters correlated significantly with the corresponding measurements performed by a human expert (N2 amplitude: R2=0.70; P2 amplitude: R2=0.70; N2 latency: R2=0.81; P2 latency: R2=0.59. All P<0.0001). Furthermore, regression analysis was able to extract an LEP response from a subset of the trials that had been classified by the human expert as without response. CONCLUSIONS This method provides a simple, fast and unbiased measurement of different components of single-trial LEP responses. SIGNIFICANCE This method is particularly desirable in several experimental conditions (e.g. drug studies, correlations with experimental variables, simultaneous EEG/fMRI and low signal-to-noise ratio data) and in clinical practice. The described multiple linear regression approach can be easily implemented for measuring evoked potentials in other sensory modalities.

Influence of epoch length on measurement of dynamic functional connectivity in wakefulness and behavioural validation in sleep

Conventional functional connectivity (FC) analysis of fMRI data derives a single measurement from the entire scan, generally several minutes in duration, which neglects the brains dynamic behaviour and potentially loses important temporal information. Short-interval dynamic FC is an attractive proposition if methodological issues can be resolved and the approach validated. This was addressed in two ways; firstly we assessed FC of the posterior cingulate cortex (PCC) node of the default mode network (DMN) using differing temporal intervals (8s to 5min) in the waking-resting state. We found that 30-second intervals and longer produce spatially similar correlation topography compared to 15-minute static FC measurements, while providing increased temporal information about changes in FC that were consistent across interval lengths. Secondly, we used NREM sleep as a behavioural validation for the use of 30-second temporal intervals due to the known fMRI FC changes with sleep stage that have been observed in previous studies using intervals of several minutes. We found significant decreases in DMN FC with sleep depth which were most pronounced during stage N2 and N3. Additionally, both the proportion of time with strong PCC-DMN connectivity and the variability in dynamic FC decreased with sleep. We therefore show that dynamic FC with epochs as short as tens of seconds is a viable method for characterising intrinsic brain activity.

Learning Shapes Spatiotemporal Brain Patterns for Flexible Categorical Decisions

Learning is thought to facilitate our ability to perform complex perceptual tasks and optimize brain circuits involved in decision making. However, little is known about the experience-dependent mechanisms in the human brain that support our ability to make fine categorical judgments. Previous work has focused on identifying spatial brain patterns (i.e., areas) that change with learning. Here, we take advantage of the complementary high spatial and temporal resolution of simultaneous electroencephalography-functional magnetic resonance imaging (EEG-fMRI) to identify the spatiotemporal dynamics between cortical networks involved in flexible category learning. Observers were trained to use different decision criteria (i.e., category boundaries) when making fine categorical judgments on morphed stimuli (i.e., radial vs. concentric patterns). Our findings demonstrate that learning acts on a feedback-based circuit that supports fine categorical judgments. Experience-dependent changes in the behavioral decision criterion were associated with changes in later perceptual processes engaging higher occipitotemporal and frontoparietal circuits. In contrast, category learning did not modulate early processes in a medial frontotemporal network that are thought to support the coarse interpretation of visual scenes. These findings provide evidence that learning flexible criteria for fine categorical judgments acts on distinct spatiotemporal brain circuits and shapes the readout of sensory signals that provide evidence for categorical decisions.

Coupling of simultaneously acquired electrophysiological and haemodynamic responses during visual stimulation

We investigate the relationship between the temporal variation in the magnitude of occipital visual evoked potentials (VEPs) and of haemodynamic measures of brain activity obtained using both blood oxygenation level dependent (BOLD) and perfusion sensitive (ASL) functional magnetic resonance imaging (fMRI). Volunteers underwent a continuous BOLD fMRI scan and/or a continuous perfusion-sensitive (gradient and spin echo readout) ASL scan, during which 30 second blocks of contrast reversing visual stimuli (at 4 Hz) were interleaved with 30 second blocks of rest (visual fixation). Electroencephalography (EEG) and fMRI were simultaneously recorded and following EEG artefact cleaning, VEPs were averaged across the whole stimulation block (120 reversals, VEP(120)) and at a finer timescale (15 reversals, VEP(15)). Both BOLD and ASL time-series were linearly modelled to establish: (1) the mean response to visual stimulation, (2) transient responses at the start and end of each stimulation block, (3) the linear decrease between blocks, (4) the nonlinear between-block variation (covariation with VEP(120)), (5) the linear decrease within block and (6) the nonlinear variation within block (covariation with VEP(15)). VEPs demonstrated a significant linear time-dependent reduction in amplitude, both within and between blocks of stimulation. Consistent with the VEPs finding, both BOLD and perfusion measures showed significant linear time-dependent reductions in response amplitude between blocks. In addition, there were significant linear time-dependent within-block reductions in BOLD response as well as between-block variations positively correlating with VEP(120) (medial occipital and frontal) and within-block variations positively correlating with VEP(15) (occipital and thalamus). Both electrophysiological and haemodynamic (BOLD and ASL) measures of visual activity showed steady habituation through the experiment. Beyond this, the VEP measures were predictive of shorter timescale (3-30 second) localised variations in BOLD response engaging both occipital cortex and other regions such as anterior cingulate and parietal regions, implicating attentional processes in the modulation of the VEP signal.

Variability in Cumulative Habitual Sleep Duration Predicts Waking Functional Connectivity.

STUDY OBJECTIVES We examined whether interindividual differences in habitual sleep patterns, quantified as the cumulative habitual total sleep time (cTST) over a 2-w period, were reflected in waking measurements of intranetwork and internetwork functional connectivity (FC) between major nodes of three intrinsically connected networks (ICNs): default mode network (DMN), salience network (SN), and central executive network (CEN). METHODS Resting state functional magnetic resonance imaging (fMRI) study using seed-based FC analysis combined with 14-d wrist actigraphy, sleep diaries, and subjective questionnaires (N = 33 healthy adults, mean age 34.3, standard deviation ± 11.6 y). Data were statistically analyzed using multiple linear regression. Fourteen consecutive days of wrist actigraphy in participants home environment and fMRI scanning on day 14 at the Birmingham University Imaging Centre. Seed-based FC analysis on ICNs from resting-state fMRI data and multiple linear regression analysis performed for each ICN seed and target. cTST was used to predict FC (controlling for age). RESULTS cTST was specific predictor of intranetwork FC when the mesial prefrontal cortex (MPFC) region of the DMN was used as a seed for FC, with a positive correlation between FC and cTST observed. No significant relationship between FC and cTST was seen for any pair of nodes not including the MPFC. Internetwork FC between the DMN (MPFC) and SN (right anterior insula) was also predicted by cTST, with a negative correlation observed between FC and cTST. CONCLUSIONS This study improves understanding of the relationship between intranetwork and internetwork functional connectivity of intrinsically connected networks (ICNs) in relation to habitual sleep quality and duration. The cumulative amount of sleep that participants achieved over a 14-d period was significantly predictive of intranetwork and inter-network functional connectivity of ICNs, an observation that may underlie the link between sleep status and cognitive performance.