Alexander M. Puckett

The spatiotemporal hemodynamic response function for depth-dependent functional imaging of human cortex.

The gray matter of human cortex is characterized by depth-dependent differences in neuronal activity and connections (Shipp, 2007) as well as in the associated vasculature (Duvernoy et al., 1981). The resolution limit of functional magnetic resonance imaging (fMRI) measurements is now below a millimeter, promising the non-invasive measurement of these properties in awake and behaving humans (Muckli et al., 2015; Olman et al., 2012; Ress et al., 2007). To advance this endeavor, we present a detailed spatiotemporal hemodynamic response function (HRF) reconstructed through the use of high-resolution, submillimeter fMRI. We decomposed the HRF into directions tangential and perpendicular to the cortical surface and found that key spatial properties of the HRF change significantly with depth from the cortical surface. Notably, we found that the spatial spread of the HRF increases linearly from 4.8mm at the gray/white matter boundary to 6.6mm near the cortical surface. Using a hemodynamic model, we posit that this effect can be explained by the depth profile of the cortical vasculature, and as such, must be taken into account to properly estimate the underlying neuronal responses at different cortical depths.

An investigation of positive and inverted hemodynamic response functions across multiple visual areas

Recent studies have demonstrated significant regional variability in the hemodynamic response function (HRF), highlighting the difficulty of correctly interpreting functional MRI (fMRI) data without proper modeling of the HRF. The focus of this study was to investigate the HRF variability within visual cortex. The HRF was estimated for a number of cortical visual areas by deconvolution of fMRI blood oxygenation level dependent (BOLD) responses to brief, large‐field visual stimulation. Significant HRF variation was found across visual areas V1, V2, V3, V4, VO‐1,2, V3AB, IPS‐0,1,2,3, LO‐1,2, and TO‐1,2. Additionally, a subpopulation of voxels was identified that exhibited an impulse response waveform that was similar, but not identical, to an inverted version of the commonly described and modeled positive HRF. These voxels were found within the retinotopic confines of the stimulus and were intermixed with those showing positive responses. The spatial distribution and variability of these HRFs suggest a vascular origin for the inverted waveforms. We suggest that the polarity of the HRF is a separate factor that is independent of the suppressive or activating nature of the underlying neuronal activity. Correctly modeling the polarity of the HRF allows one to recover an estimate of the underlying neuronal activity rather than discard the responses from these voxels on the assumption that they are artifactual. We demonstrate this approach on phase‐encoded retinotopic mapping data as an example of the benefits of accurately modeling the HRF during the analysis of fMRI data. Hum Brain Mapp 35:5550–5564, 2014.

Serial correlations in single-subject fMRI with sub-second TR

&NA; When performing statistical analysis of single‐subject fMRI data, serial correlations need to be taken into account to allow for valid inference. Otherwise, the variability in the parameter estimates might be under‐estimated resulting in increased false‐positive rates. Serial correlations in fMRI data are commonly characterized in terms of a first‐order autoregressive (AR) process and then removed via pre‐whitening. The required noise model for the pre‐whitening depends on a number of parameters, particularly the repetition time (TR). Here we investigate how the sub‐second temporal resolution provided by simultaneous multislice (SMS) imaging changes the noise structure in fMRI time series. We fit a higher‐order AR model and then estimate the optimal AR model order for a sequence with a TR of less than 600 ms providing whole brain coverage. We show that physiological noise modelling successfully reduces the required AR model order, but remaining serial correlations necessitate an advanced noise model. We conclude that commonly used noise models, such as the AR(1) model, are inadequate for modelling serial correlations in fMRI using sub‐second TRs. Rather, physiological noise modelling in combination with advanced pre‐whitening schemes enable valid inference in single‐subject analysis using fast fMRI sequences. HighlightsSerial correlations affect statistical inference on fMRI data.Optimal AR model orders were estimated using Variational Bayesian inference.Sub‐second TR achieved by SMS EPI requires higher‐order autoregressive (AR) modelling.Physiological noise modelling is crucial for analysis of fMRI data with sub‐second TR.Remaining serial correlations necessitate advanced pre‐whitening schemes.

Measuring the effects of attention to individual fingertips in somatosensory cortex using ultra-high field (7T) fMRI

Abstract Attention to sensory information has been shown to modulate the neuronal processing of that information. For example, visuospatial attention acts by modulating responses at retinotopically appropriate regions of visual cortex (Puckett and DeYoe, 2015; Tootell et al. 1998). Much less, however, is known about the neuronal processing associated with attending to other modalities of sensory information. One reason for this is that visual cortex is relatively large, and therefore easier to access non‐invasively in humans using tools such as functional magnetic resonance imaging (fMRI). With high‐resolution fMRI, however, it is now possible to access smaller cortical areas such as primary somatosensory cortex (Martuzzi et al., 2014; Sanchez‐Panchuelo et al., 2010; Schweisfurth et al. 2014; Schweizer et al. 2008). Here, we combined a novel experimental design and high‐resolution fMRI at ultra‐high field (7T) to measure the effects of attention to tactile stimulation in primary somatosensory cortex, S1. We find that attention modulates somatotopically appropriate regions of S1, and importantly, that this modulation can be measured at the level of the cortical representation of individual fingertips. HighlightsAttending to tactile stimulation modulates primary somatosensory cortex, S1.High‐resolution fMRI at 7T can measure fingertip specific attentional modulation.This modulation is somatotopically appropriate and directly linked to task‐relevance.Such measurements are critical for examining neural mechanisms of somatosensation.

Using multi-echo simultaneous multi-slice (SMS) EPI to improve functional MRI of the subcortical nuclei of the basal ganglia at ultra-high field (7T)

&NA; The nuclei of the basal ganglia pose a special problem for functional MRI, especially at ultra‐high field, because T2* variations between different regions result in suboptimal BOLD sensitivity when using gradient‐echo echo‐planar imaging (EPI). Specifically, the iron‐rich lentiform nucleus of the basal ganglia, including the putamen and globus pallidus, suffers from substantial signal loss when imaging is performed using conventional single‐echo EPI with echo times optimized for the cortex. Multi‐echo EPI acquires several echoes at different echo times for every imaging slice, allowing images to be reconstructed with a weighting of echo times that is optimized individually for each voxel according to the underlying tissue or T2* properties. Here we show that multi‐echo simultaneous multi‐slice (SMS) EPI can improve functional activation of iron‐rich subcortical regions while maintaining sensitivity within cortical areas. Functional imaging during a motor task known to elicit strong activations in the cortex and the subcortex (basal ganglia) was performed to compare the performance of multi‐echo SMS EPI to single‐echo SMS EPI. Notably within both the caudate nucleus and putamen of the basal ganglia, multi‐echo SMS EPI yielded higher tSNR (an average 84% increase) and CNR (an average 58% increase), an approximate 3‐fold increase in supra‐threshold voxels, and higher t‐values (an average 39% increase). The degree of improvement in the group level t‐statistics was negatively correlated to the underlying T2* of the voxels, such that the shorter the T2*, as in the iron‐rich nuclei of the basal ganglia, the higher the improvement of t‐values in the activated region. HighlightsRegional T2* variations result in suboptimal BOLD sensitivity using single‐echo EPI.Multi‐echo EPI permits voxel‐wise sensitivity optimization depending on the underlying T2*.This can be used to improve functional imaging of the basal ganglia at 7T.This improvement can be achieved while maintaining BOLD sensitivity in the cortex.Sub‐second, whole‐brain imaging is possible with simultaneous multislice multi‐echo EPI.

Vascular effects on the BOLD response and the retinotopic mapping of hV4

Despite general acceptance that the retinotopic organisation of human V4 (hV4) takes the form of a single, uninterrupted ventral hemifield, measured retinotopic maps of this visual area are often incomplete. Here, we test hypotheses that artefact from draining veins close to hV4 cause inverted BOLD responses that may serve to obscure a portion of the lower visual quarterfield — including the lower vertical meridian — in some hemispheres. We further test whether correcting such responses can restore the ‘missing’ retinotopic coverage in hV4. Subjects (N=11) viewed bowtie, ring, drifting bar and full field flash stimuli. Functional EPIs were acquired over approximately 1.5h and analysed to reveal retinotopic maps of early visual cortex, including hV4. Normalised mean maps (which show the average EPI signal amplitude) were constructed by voxel-wise averaging of the EPI time course and used to locate venous eclipses, which can be identified by a decrease in the EPI signal caused by deoxygenated blood. Inverted responses are shown to cluster in these regions, and correcting these responses improves maps of hV4 in some hemispheres, including restoring a complete hemifield map in one. A leftwards bias was found in which 11/11 hV4 maps in the left hemisphere were classified as incomplete, while this was the case in only 3/11 right hemisphere maps. Incomplete hV4 maps did not correspond with venous artefact in many instances, with incomplete maps being present in the absence of a venous eclipse and complete maps coexisting with a proximate venous eclipse. We also show that mean maps of upper surfaces (near the boundary between cortical grey matter and CSF) provide highly detailed maps of veins on the cortical surface. Results suggest that venous eclipses and inverted voxels can explain some incomplete hV4 maps, but cannot explain the remainder nor the leftwards bias in hV4 coverage reported here.