This paper demonstrates the feasibility of real-time mapping of the visual field for clinical applications. Specifically, three aspects of this problem were considered: (1) experimental design, (2) statistical analysis, and (3) display of results.
Proper experimental design is essential to achieving a successful outcome, particularly for real-time applications. A random-block experimental design was shown to have less sensitivity to measurement noise, as well as greater robustness to error in modeling of the hemodynamic impulse response function (IRF) and greater flexibility than common alternatives. In addition, random encoding of the visual field allows for the detection of voxels that are responsive to multiple, not necessarily contiguous, regions of the visual field.
Due to its recursive nature, the Kalman filter is ideally suited for real-time statistical analysis of visual field mapping data. An important feature of the Kalman filter is that it can be used for nonstationary time series analysis. The capability of the Kalman filter to adapt, in real time, to abrupt changes in the baseline arising from subject motion inside the scanner and other external system disturbances is important for the success of clinical applications.
The clinician needs real-time information to evaluate the success or failure of the imaging run and to decide whether to extend, modify, or terminate the run. Accordingly, the analytical software provides real-time displays of (1) brain activation maps for each stimulus segment, (2) voxel-wise spatial tuning profiles, (3) time plots of the variability of response parameters, and (4) time plots of activated volume.
Kalman filtering; Nonstationary time series; Real-time imaging; fMRI; Retinotopy; Visual cortex; Human
In the present study, we sought to examine whether the fronto-striatal
learning system, which has been implicated in bulimia nervosa, would demonstrate
altered BOLD activity during probabilistic category learning in women who met
subthreshold criteria for bulimia nervosa (Sub-BN). Sub-BN, which falls within
the clinical category of Eating Disorder Not Otherwise Specified (EDNOS), is
comprised of individuals who demonstrate recurrent binge eating, efforts to
minimize their caloric intake and caloric retention, and elevated levels of
concern about shape, weight, and/or eating, but just fail to meet the diagnostic
threshold for bulimia nervosa (BN). fMRI data were collected from eighteen women
with subthreshold-BN (Sub-BN) and nineteen healthy control women group-matched
for age, education and body mass index (MC) during the weather prediction task.
Sub-BN participants demonstrated increased caudate nucleus and dorsolateral
prefrontal cortex (DLPFC) activation during the learning of probabilistic
categories. Though the two subject groups did not differ in behavioral
performance, over the course of learning, Sub-BN participants showed a dynamic
pattern of brain activity differences when compared to matched control
participants. Regions implicated in episodic memory, including the medial
temporal lobe (MTL), retrosplenial cortex, middle frontal gyrus, and anterior
and posterior cingulate cortex showed decreased activity in the Sub-BN
participants compared to MCs during early learning which was followed by
increased involvement of the DLPFC during later learning. These findings
demonstrate that women with Sub-BN demonstrate differences in fronto-striatal
learning system activity, as well as a distinct functional pattern between
fronto-striatal and MTL learning systems during the course of implicit
probabilistic category learning.
Eating disorders; fMRI; Fronto-striatal system; Weather prediction task; Bulimia nervosa; Memory system interactions
Contradictory results from the efforts for detecting evoked neuronal currents have left the feasibility of neuronal current MRI (ncMRI) an open question. Most of the previous ncMRI studies in human subjects are suspect due to their inability to separate or eliminate the hemodynamic effects. In this study, we used a bloodless turtle brain that eliminates hemodynamic effects, to explore the feasibility of detecting visual-evoked ncMRI signals at 9.4T. The turtle brain, with its eyes attached, was dissected from the cranium and placed in artificial cerebral spinal fluid. Light flashes were delivered to the eyes, which produced visual-evoked neuronal activity in the brain. Local field potential (LFP) and MRI signals in the turtle brain were measured in an interleave fashion. Although robust neuronal responses to the visual stimulation were observed in the LFP signals, no significant signal changes synchronized with neuronal currents were found in the MRI images. Analysis of the temporal stability of the MRI time courses indicated that the detectable effect sizes are 0.11% and 0.09° for the magnitude and phase, respectively, and the visual-evoked ncMRI signals in the turtle brain are below these levels.
Previous studies have suggested atypically enhanced activity of visual cortex during language processing in autism spectrum disorder (ASD). However, it remains unclear whether visual cortical participation reflects isolated processing within posterior regions or functional cooperation with distal brain regions, such as left inferior frontal gyrus (LIFG). We addressed this question using functional connectivity MRI (fcMRI) and structural equation modeling in 14 adolescents and adults with ASD and 14 matched typically developing (TD) participants. Data were analyzed to isolate low-frequency intrinsic fluctuations, by regressing out effects of a semantic decision task. For a right extrastriate seed derived from the strongest cluster of atypical activation in the ASD group, widespread effects of increased connectivity in prefrontal and medial frontal lobes bilaterally were observed for the ASD group, compared to the TD group. A second analysis for a seed in LIFG, derived from pooled activation effects in both groups, also yielded widespread effects of overconnectivity in the ASD group, especially in temporal lobes. Structural equation modeling showed that whereas right extrastriate cortex did not impact function of language regions (left and right IFG, left middle temporal gyrus) in the TD model, it was an integral part of a language circuit in the ASD group. These results suggest that atypical extrastriate activation during language processing in ASD reflects integrative (not isolated) processing. Furthermore, our findings are inconsistent with previous reports of functional underconnectivity in ASD, probably related to removal of task effects required to isolate intrinsic low-frequency fluctuations.
Lexical; semantic; visual; functional connectivity; structural equation modeling; autism
White matter (WM) lesions are the classic pathological hallmarks of multiple sclerosis (MS). However, MRI-based WM lesion load shows relatively poor correlation with functional outcome, resulting in the “clinico-radiological paradox” of MS. Unlike lesion based measures, volumetric MRI assessment of brain atrophy shows a strong correlation with functional outcome, and the presence of early atrophy predicts a worse disease course. While extensive literature exists describing MRI characteristics of atrophy in MS, the exact pathogenesis and the substrate of atrophy - gray vs WM loss, axonal/neuronal damage vs demyelination, or a combination of the above – remain unclear. Animal models of atrophy would allow for detailed investigations of the pathomechanism, and would contribute to an enhanced understanding of structural-functional connections in this complex disease. We now report that in the Theiler’s Murine Encephalitis Virus (TMEV) model of MS in SJL/J mice, significant brain atrophy accompanies the development of the progressive MS-like disease. We conducted volumetric MRI studies in 8 cases and 4 age, gender and strain matched control mice. While in controls we did not detect any brain atrophy, significant atrophy developed as early as 3 months into the disease course, and reached its peak by 6 months, resulting in ventricular enlargement by 118% (p= 0.00003). A strong correlation (r=−0.88) between atrophy and disability, as assessed by rotarod assay, was also demonstrated. We earlier reported another neurodegenerative feature in this model, the presence of deep gray matter T2 hypointensity in thalamic nuclei. Future studies utilizing this model will allow us to investigate key components of MRI detectable neurodegenerative feature development, their tissue correlations and associations with functional outcome measures. These studies are expected to pave the way to a better understanding of the substrate of disability in MS models.
brain atrophy; multiple sclerosis; mouse model of multiple sclerosis; Theiler’s Murine Encephalitis Virus; TMEV; volumetric MRI
Normal aging is associated with a gradual decline in executive functions such as set-shifting, inhibition, and updating, along with a progressive decline of neurotransmitter systems including the dopamine system. Modulation from the dopamine system is thought to be critical for the gating of information during working memory. Given the known relationships between executive aging, cognition, and dopamine, this study aims to explore the neurobiology underlying age-related changes in working memory updating using fMRI with healthy subjects from across the adult age spectrum. Our results indicate that older age is associated with poorer performance, reduced meso-cortico-striatal activation, and reduced functional coupling between the caudate and the VLPFC during the updating task. Additionally, caudate activation is associated with improved accuracy and VLPFC activation with faster reaction times in the full sample. Thus, older subjects’ under-recruitment of and reduced functional coupling between these regions may specifically underlie age-related changes in working memory updating. These results are consistent with computational models of executive cognition and dopamine-mediated age-related cognitive decline.
working memory; aging; fMRI; functional connectivity; caudate; prefrontal cortex
Harsh corporal punishment (HCP) was defined as frequent parental administration of corporal punishment (CP) for discipline, with occasional use of objects such as straps, or paddles. CP is linked to increased risk for depression and substance abuse. We examine whether long-term exposure to HCP acts as sub-traumatic stressor that contributes to brain alterations, particularly in dopaminergic pathways, which may mediate their increased vulnerability to drug and alcohol abuse. Nineteen young adults who experienced early HCP but no other forms of maltreatment and twenty-three comparable controls were studied. T2 relaxation time (T2-RT) measurements were performed with an echo planar imaging TE stepping technique and T2 maps were calculated and analyzed voxel-by-voxel to locate regional T2-RT differences between groups. Previous studies indicated that T2-RT provides an indirect index of resting cerebral blood volume. Region of interest (ROI) analyses were also conducted in caudate, putamen, nucleus accumbens, anterior cingulate cortex, dorsolateral prefrontal cortex, thalamus, globus pallidus and cerebellar hemispheres. Voxel-based relaxometry showed that HCP was associated with increased T2-RT in right caudate and putamen. ROI analyses also revealed increased T2-RT in dorsolateral prefrontal cortex, substantia nigra, thalamus and accumbens but not globus pallidus or cerebellum. There were significant associations between T2-RT measures in dopamine target regions and use of drugs and alcohol, and memory performance. Alteration in the paramagnetic or hemodynamic properties of dopaminergic cell body and projection regions were observed in subjects with HCP, and these findings may relate to their increased risk for drug and alcohol abuse.
Mental simulations are often focused on a goal in the future or a problem to be solved. Recent neuroimaging studies have associated mental simulations of the future with default network activity, but the simulations in these studies were not typically directed toward achieving a particular goal. Goal-directed simulation requires cognitive control to maintain information, make decisions, and coordinate abstract action sequences. Therefore, it should recruit not only the default network, but also executive regions. To investigate whether default network and executive regions can be coactive in the context of goal-directed simulation, we designed a problem-solving task in which participants simulated solving several specific problems in imaginary scenarios while in the MRI scanner. We analyzed brain activity during simulation relative to a semantic elaboration task and found that goal-directed simulation engaged core regions of the default network and executive dorsolateral prefrontal cortex. A functional connectivity analysis with posterior cingulate and dorsolateral prefrontal cortex seeds revealed that activity in these regions was coupled throughout the goal-directed simulation period and associated with a distributed network of other default and executive regions, including medial prefrontal cortex, medial temporal, and parietal regions.
Default mode; cognitive control; fMRI
Logan graphical analysis with cerebellum as reference region has been widely used for the estimation of the distribution volume ratio (DVR) of [18F]FDDNP as a measure of amyloid burden and tau deposition in human brain because of its simplicity and computational ease. However, spurious parametric DVR images may be produced with shorter scanning times and when the noise level is high. In this work, we have characterized a relative-equilibrium-based (RE) graphical method against the Logan analysis for parametric imaging and region-of-interest (ROI) analysis.
Dynamic [18F]FDDNP PET scans were performed on 9 control subjects and 12 patients diagnosed with Alzheimer’s disease. Using the cerebellum as reference input, regional DVR estimates were derived using both the Logan analysis and the RE plot approach. Effects on DVR estimates obtained at voxel and ROI levels by both graphical approaches using data in different time windows were investigated and compared with the standard values derived using the Logan analysis on a voxel-by-voxel basis for the time window of 35–125 min used in previous studies.
Larger bias and variability were observed for DVR estimates obtained by the Logan graphical analysis at the voxel level when short time windows (85–125 and 45–65 min) were used, because of high noise levels in voxel-wise parametric imaging. However, when the Logan graphical analysis was applied at the ROI level over those short time windows, the DVR estimates did not differ significantly from the standard values derived using the Logan analysis on the voxel level for the time window of 35–125 min, and their bias and variability were remarkably lower. Conversely, the RE plot approach was more robust in providing DVR estimates with less bias and variability even when short time windows were used. The DVR estimates obtained at voxel and ROI levels were consistent. No significant differences were observed in DVR estimates obtained by the RE plot approach for all paired comparisons with the standard values.
The RE plot approach provides less noisy parametric images and gives consistent and reliable regional DVR estimates at both voxel and ROI levels, indicating that it is preferred over the Logan graphical analysis for analyzing [18F]FDDNP PET data.
Alzheimer’s disease (AD); Distribution volume ratio (DVR); [18F]FDDNP; Graphical methods; Positron emission tomography (PET)
Changes in regional brain activity can be observed following global normalization procedures to reduce variability in the data. In particular, spurious regional differences may appear when scans from patients with low global activity are compared to those from healthy subjects. It has thus been suggested that the consistent increases in subcortical activity that characterize the abnormal Parkinson’s disease-related metabolic covariance pattern (PDRP) are artifacts of global normalization, and that similar topographies can be identified in scans from healthy subjects with varying global activity. To address this issue, we examined the effects of experimental reductions in global metabolic activity on PDRP expression. Ten healthy subjects underwent 18F-fluorodeoxyglucose PET in wakefulness and following sleep induction. In all subjects, the global metabolic rate (GMR) declined with sleep (mean −34%, range: −17 to −56%), exceeding the test-retest differences of the measure (p<0.001). By contrast, sleep-wake differences in PDRP expression did not differ from test-retest differences, and did not correlate (R2=0.04) with concurrent declines in global metabolic activity. Indeed, despite significant GMR reductions in sleep, PDRP values remained within the normal range. Likewise, voxel weights on the principal component patterns resulting from combined analysis of the sleep and wake scans did not correlate (R2<0.07) with the corresponding regional loadings on the PDRP topography. In aggregate, the data demonstrate that abnormal PDRP expression is not induced by reductions in global activity. Moreover, significant declines in GMR are not associated with the appearance of PDRP-like spatial topographies.
Parkinson’s disease; PET; Sleep
An Alzheimer’s fMRI study has motivated us to evaluate inter-regional correlations during rest between groups. We apply generalized estimating equation (GEE) models to test for differences in regional correlations across groups. Both the GEE marginal model and GEE transition model are evaluated and compared to the standard pooling Fisher-z approach using simulation studies. Standard errors of all methods are estimated both theoretically (model-based) and empirically (bootstrap). Of all the methods, we find that the transition models have the best statistical properties. Overall, the model-based standard errors and bootstrap standard errors perform about the same. We also demonstrate the methods with a functional connectivity study in a healthy cognitively normal population of ApoE4+ participants and ApoE4− participants who are recruited from the Adult Children’s Study conducted at the Washington University Knight Alzheimer’s Disease Research Center.
resting-state fMRI; time-series; temporal dependence; brain regional correlations; functional connectivity
Adaptive false discovery rate (FDR) procedures, which offer greater power than the original FDR procedure of Benjamini and Hochberg, are often applied to statistical maps of the brain. When a large proportion of the null hypotheses are false, as in the case of widespread effects such as cortical thinning throughout much of the brain, adaptive FDR methods can surprisingly reject more null hypotheses than not accounting for multiple testing at all— i.e., using uncorrected p-values. A straightforward mathematical argument is presented to explain why this can occur with the q-value method of Storey and colleagues, and a simulation study shows that it can also occur, to a lesser extent, with a two-stage FDR procedure due to Benjamini and colleagues. We demonstrate the phenomenon with reference to a published data set documenting cortical thinning in attention deficit/hyperactivity disorder. The paper concludes with recommendations for how to proceed when adaptive FDR results of this kind are encountered in practice.
adjusted p-values; attention deficit/hyperactivity disorder; cortical thickness; false discovery rate; multiple testing; q-values
Measuring iron content in the brain has important implications for a number of neurodegenerative diseases. Quantitative susceptibility mapping (QSM), derived from magnetic resonance images, has been used to measure total iron content in vivo and in post mortem brain. In this paper, we show how magnetic susceptibility from QSM correlates with total iron content measured by X-ray fluorescence (XRF) imaging and by inductively coupled plasma mass spectrometry (ICPMS). The relationship between susceptibility and ferritin iron was estimated at 1.10 ± 0.08 ppb susceptibility per μg iron/g wet tissue, similar to that of iron in fixed (frozen/thawed) cadaveric brain and previously published data from unfixed brains. We conclude that magnetic susceptibility can provide a direct and reliable quantitative measurement of iron content and that it can be used clinically at least in regions with high iron content.
PMID: 23591072 CAMSID: cams3678
Brain iron; Ferritin; Quantitative susceptibility mapping (QSM); X-ray fluorescence imaging (XRF)
The mirror neuron system (MNS) has been proposed to play an important role in social cognition by providing a neural mechanism by which others’ actions, intentions, and emotions can be understood. Here functional magnetic resonance imaging was used to directly examine the relationship between MNS activity and two distinct indicators of social functioning in typically-developing children (aged 10.1 years±7 months): empathy and interpersonal competence. Reliable activity in pars opercularis, the frontal component of the MNS, was elicited by observation and imitation of emotional expressions. Importantly, activity in this region (as well as in the anterior insula and amygdala) was significantly and positively correlated with established behavioral measures indexing children’s empathic behavior (during both imitation and observation) and interpersonal skills (during imitation only). These findings suggest that simulation mechanisms and the MNS may indeed be relevant to social functioning in everyday life during typical human development.
The investigation of brain activity using naturalistic, ecologically-valid stimuli is becoming an important challenge for neuroscience research. Several approaches have been proposed, primarily relying on data-driven methods (e.g. independent component analysis, ICA). However, data-driven methods often require some post-hoc interpretation of the imaging results to draw inferences about the underlying sensory, motor or cognitive functions. Here, we propose using a biologically-plausible computational model to extract (multi-)sensory stimulus statistics that can be used for standard hypothesis-driven analyses (general linear model, GLM). We ran two separate fMRI experiments, which both involved subjects watching an episode of a TV-series. In Exp 1, we manipulated the presentation by switching on-and-off color, motion and/or sound at variable intervals, whereas in Exp 2, the video was played in the original version, with all the consequent continuous changes of the different sensory features intact. Both for vision and audition, we extracted stimulus statistics corresponding to spatial and temporal discontinuities of low-level features, as well as a combined measure related to the overall stimulus saliency. Results showed that activity in occipital visual cortex and the superior temporal auditory cortex co-varied with changes of low-level features. Visual saliency was found to further boost activity in extra-striate visual cortex plus posterior parietal cortex, while auditory saliency was found to enhance activity in the superior temporal cortex. Data-driven ICA analyses of the same datasets also identified “sensory” networks comprising visual and auditory areas, but without providing specific information about the possible underlying processes, e.g., these processes could relate to modality, stimulus features and/or saliency. We conclude that the combination of computational modeling and GLM enables the tracking of the impact of bottom–up signals on brain activity during viewing of complex and dynamic multisensory stimuli, beyond the capability of purely data-driven approaches.
Data-driven; Saliency; Multi-sensory; Cinematographic material; Biologically-inspired vision and audition
Multisensory signals can enhance the spatial perception of objects and events in the environment. Changes of visual size and auditory intensity provide us with the main cues about motion direction in depth. However, frequency changes in audition and binocular disparity in vision also contribute to the perception of motion in depth. Here, we presented subjects with several combinations of auditory and visual depth-cues to investigate multisensory interactions during processing of motion in depth. The task was to discriminate the direction of auditory motion in depth according to increasing or decreasing intensity. Rising or falling auditory frequency provided an additional within-audition cue that matched or did not match the intensity change (i.e. intensity-frequency (IF) “matched vs. unmatched” conditions). In two-thirds of the trials, a task-irrelevant visual stimulus moved either in the same or opposite direction of the auditory target, leading to audio–visual “congruent vs. incongruent” between-modalities depth-cues. Furthermore, these conditions were presented either with or without binocular disparity. Behavioral data showed that the best performance was observed in the audio–visual congruent condition with IF matched. Brain imaging results revealed maximal response in visual area V3A when all cues provided congruent and reliable depth information (i.e. audio–visual congruent, IF-matched condition including disparity cues). Analyses of effective connectivity revealed increased coupling from auditory cortex to V3A specifically in audio–visual congruent trials. We conclude that within- and between-modalities cues jointly contribute to the processing of motion direction in depth, and that they do so via dynamic changes of connectivity between visual and auditory cortices.
Audio–visual interaction; fMRI; Motion discrimination; Binocular disparity; V3A; Effective connectivity
A cross-sectional study to establish whether a subject’s cognitive state can be predicted based on regional values obtained from brain cortical maps of FDDNP Distribution Volume Ratio (DVR), which shows the pattern of beta amyloid and neurofibrillary binding, along with those of early summed FDDNP PET images (reflecting the pattern of perfusion) was performed.
Dynamic FDDNP PET studies were performed in a group of 23 subjects (8 control (NL), 8 Mild Cognitive Impairment (MCI) and 7 Alzheimer’s Disease (AD) subjects). FDDNP DVR images were mapped to the MR derived hemispheric cortical surface map warped into a common space. A set of Regions of Interest (ROI) values of FDDNP DVR and early summed FDDNP PET (0-6 min post tracer injection), were thus calculated for each subject which along with the MMSE score were used to construct a linear mathematical model relating ROI values to MMSE. After the MMSE prediction models were developed, the models’ predictive ability was tested in a non-overlapping set of 8 additional individuals, whose cognitive status was unknown to the investigators who constructed the predictive models.
Among all possible subsets of ROIs, we found that the standard deviation of the predicted MMSE was 1.8 by using only DVR values from medial and lateral temporal and prefrontal regions plus the early summed FDDNP value in the posterior cingulate gyrus. The root mean square prediction error for the eight new subjects was 1.6.
FDDNP scans reflect progressive neuropathology accumulation and can potentially be used to predict the cognitive state of an individual.
cortical surface maps; MR; FDDNP PET; MMSE
Recent FMRI studies suggest that cortical face processing extends well beyond the fusiform face area (FFA), including unspecified portions of the anterior temporal lobe. However, the exact location of such anterior temporal region(s), and their role during active face recognition, remain unclear. Here we demonstrate that (in addition to FFA) a small bilateral site in the anterior tip of the collateral sulcus (‘AT’; the anterior temporal face patch) is selectively activated during recognition of faces but not houses (a non-face object). In contrast to the psychophysical prediction that inverted and contrast reversed faces are processed like other non-face objects, both FFA and AT (but not other visual areas) were also activated during recognition of inverted and contrast reversed faces. However, response accuracy was better correlated to recognition-driven activity in AT, compared to FFA. These data support a segregated, hierarchical model of face recognition processing, extending to the anterior temporal cortex.
fMRI; Face Recognition; Face Inversion; Contrast Reversal; FFA; Anterior Temporal Face Patch
Quantitative PET studies of neuroreceptor tracers typically require that arterial input function be measured. The aim of this study was to explore the use of a population-based input function (PBIF) and an image-derived input function (IDIF) for [11C](R)-rolipram kinetic analysis, with the goal of reducing—and possibly eliminating—the number of arterial blood samples needed to measure parent radioligand concentrations.
A PBIF was first generated using [11C](R)-rolipram parent time-activity curves from 12 healthy volunteers (Group 1). Both invasive (blood samples) and non-invasive (body weight, body surface area, and lean body mass) scaling methods for PBIF were tested. The scaling method that gave the best estimate of the Logan-VT values was then used to determine the test-retest variability of PBIF in Group 1 and then prospectively applied to another population of 25 healthy subjects (Group 2), as well as to a population of 28 patients with major depressive disorder (Group 3). Results were also compared to those obtained with an image-derived input function (IDIF) from the internal carotid artery. In some subjects, we measured arteriovenous differences in [11C](R)-rolipram concentration to see whether venous samples could be used instead of arterial samples. Finally, we assessed the ability of IDIF and PBIF to discriminate depressed patients (MDD) and healthy subjects.
Arterial blood-scaled PBIF gave better results than any non-invasive scaling technique. Excellent results were obtained when the blood-scaled PBIF was prospectively applied to the subjects in Group 2 (VT ratio 1.02 ± 0.05; mean ± SD) and Group 3 (VT ratio 1.03 ± 0.04). Equally accurate results were obtained for two subpopulations of subjects drawn from Groups 2 and 3 who had very differently shaped (i.e. “flatter” or “steeper”) input functions compared to PBIF (VT ratio 1.07 ± 0.04 and 0.99 ± 0.04, respectively).
Results obtained via PBIF were equivalent to those obtained via IDIF (VT ratio 0.99 ± 0.05 and 1.00 ± 0.04 for healthy subjects and MDD patients, respectively). Retest variability of PBIF was equivalent to that obtained with full input function and IDIF (14.5%, 15.2%, and 14.1%, respectively). Due to [11C](R)-rolipram arteriovenous differences, venous samples could not be substituted for arterial samples.
With both IDIF and PBIF, depressed patients had a 20% reduction in [11C](R)-rolipram binding as compared to control (two-way ANOVA: p=0.008 and 0.005, respectively). These results were almost equivalent to those obtained using 23 arterial samples.
Although some arterial samples are still necessary, both PBIF and IDIF are accurate and precise alternatives to full arterial input function for [11C](R)-rolipram PET studies. Both techniques give accurate results with low variability, even for clinically different groups of subjects and those with very differently shaped input functions.
Population-based input function; image-derived input function; [11C](R)-rolipram; major depressive disorder
Ultra high fields (UHF) permit unprecedented explorations of functional organizations and insight into basic neuronal processes. Increases in the signal and contrast to noise ratios have allowed increases in the spatial resolution of T *2 weighted gradient echo (GE) echo planar imaging (EPI). Furthermore, while the use of T2 weighted imaging methods at UHF (e.g. spin echo (SE) EPI, gradient and spin echo (GRASE) EPI) can also permit higher resolution images, they in addition allow for increased spatial specificity of functional responses, permitting the in-vivo study of functional organizations down to the columnar level of the cortex.
The study of the visual cortex has, thus far, benefitted the most from higher resolution T2 weighted studies as achieving the required transmit B1 magnitude at 7T is more challenging in other brain regions, such as the auditory cortex. As such, auditory fMRI studies at UHF have been limited to T2* weighted GE sequences.
Recent advances in multi-channel RF transmission (e.g. B1 shimming) have enabled procedures to efficiently address deficiencies in transmit B1 profiles. However, these techniques, shown to be advantageous in anatomical imaging at UHF, are not generally utilized to facilitate T2 weighted fMRI studies.
Here we investigate the feasibility of applying B1 shimming to achieve efficient RF transmission in human auditory cortex. We demonstrate that, with B1 shimming, functional responses to simple tones and to complex sounds (i.e. voices, speech, animal cries, tools and nature) can be efficiently measured with T2 weighted SE-EPI in bilateral human auditory cortex at 7T without exceeding specific absorption rate (SAR) limits.
7T; BOLD; fMRI; spin echo; B1 shimming; auditory cortex
The lateral frontal cortex (LFC) is thought to represent contextual and rule-based information that allows adaptive behavior according to circumstance. Recent progress has suggested that the representations of the LFC vary along its rostral-caudal axis with more abstract, higher level representations associated with rostral areas of the LFC and more concrete, lower level representations associated with caudal areas of the LFC. Here, we investigated this proposal. Subjects responded to stimuli based upon a nested series of contextual cues stored in working memory (WM) while being scanned with fMRI. Higher level context cues denoted an abstract rule set while lower level context cues provided more concrete information. Using multi-variate pattern analysis (MVPA), we found varying forms of representation along the rostral-caudal axis of the LFC depending on the type of information stored in WM. Rostral areas of frontal cortex in the lateral orbitofrontal cortex (OFC) represented the higher level context, but not more concrete information, and only when more concrete information was unavailable. Mid-level areas in the mid-dorsolateral prefrontal cortex (DLPFC) and inferior frontal junction (IFJ) represented more concrete rules, but only when the forthcoming response could not be anticipated. By contrast, the dorsal premotor cortex (PMd) and primary motor cortex (M1) represented contextual and response information when the forthcoming response could be anticipated on the basis of context. Collectively, these data indicate that representations dedicated to higher levels of abstraction become less discriminating when more concrete information becomes available. These patterns are consistent with rostral-caudal abstraction proposals of the LFC.
prefrontal cortex; PFC; frontal lobe; cognitive control; executive function; hierarchical
We have investigated the amplitude and phase of spontaneous low-frequency oscillations (LFOs) of the cerebral deoxy- and oxy-hemoglobin concentrations ([Hb] and [HbO]) in a human sleep study using near-infrared spectroscopy (NIRS). Amplitude and phase analysis was based on the analytic signal method, and phasor algebra was used to decompose measured [Hb] and [HbO] oscillations into cerebral blood volume (CBV) and flow velocity (CBFV) oscillations. We have found a greater phase lead of [Hb] vs. [HbO] LFOs during non-REM sleep with respect to the awake and REM sleep states (maximum increase in [Hb] phase lead: ~π/2). Furthermore, during non-REM sleep, the amplitudes of [Hb] and [HbO] LFOs are suppressed with respect to the awake and REM sleep states (maximum amplitude decrease: 87%). The associated cerebral blood volume and flow velocity oscillations are found to maintain their relative phase difference during sleep, whereas their amplitudes are attenuated during non-REM sleep. These results show the potential of phase-amplitude analysis of [Hb] and [HbO] oscillations measured by NIRS in the investigation of hemodynamics associated with cerebral physiology, activation, and pathological conditions.
cerebral hemodynamics; low-frequency oscillations; near-infrared spectroscopy; diffuse optical imaging; instantaneous phase; phasor analysis; sleep
Oscillatory electrical brain activity in the alpha (8–13Hz) band is a prominent feature of human electroencephalography (EEG) during alert wakefulness, and is commonly thought to arise primarily from the occipital and parietal parts of the cortex. While the thalamus is considered to play a supportive role in the generation and modulation of cortical alpha rhythms, its precise function remains controversial and incompletely understood. To address this, we evaluated the correlation between the blood oxygenation level dependent (BOLD) functional magnetic resonance imaging (fMRI) signals in the thalamus and the spontaneous modulation of posterior alpha rhythms based on EEG-fMRI data acquired concurrently during an eyes-closed task-free condition. We observed both negative and positive correlations in the thalamus. The negative correlations were mostly seen within the visual thalamus, with a preference for the pulvinar over lateral geniculate nuclei. The positive correlations were found at the anterior and medial dorsal nuclei. Through functional connectivity analysis of the fMRI data, the pulvinar was found to be functionally associated with the same widespread cortical visual areas where the fMRI signals were negatively correlated with the posterior alpha modulation. In contrast, the dorsal nuclei were part of a distinct functional network that included brain stem, cingulate cortex and cerebellum. These observations are consistent with previous animal electrophysiology studies and the notion that the visual thalamus, and the pulvinar in particular, is intimately involved in the generation and spontaneous modulation of posterior alpha rhythms, facilitated by its reciprocal and widespread interaction with the cortical visual areas. We further postulate that the anterior and medial dorsal nuclei, being part of the ascending neuromodulatory system, may indirectly modulate cortical alpha rhythms by affecting vigilance and arousal level.
EEG-fMRI; Alpha; Thalamus; Pulvinar; Lateral Geniculate Nucleus
Inferences about functional correspondences between functional networks of human and non-human primates largely rely on proximity and anatomical expansion models. However, it has been demonstrated that topologically correspondent areas in two species can have different functional properties, suggesting that anatomy-based approaches should be complemented with alternative methods to perform functional comparisons. We have recently shown that comparative analyses based on temporal correlations of sensory-driven fMRI responses can reveal functional correspondent areas in monkeys and humans without relying on spatial assumptions. Inter-species activity correlation (ISAC) analyses require the definition of seed areas in one species to reveal functional correspondences across the cortex of the same and other species. Here we propose an extension of the ISAC method that does not rely on any seed definition, hence a method void of any spatial assumption. Specifically, we apply independent component analysis (ICA) separately to monkey and human data to define species-specific networks of areas with coherent stimulus-related activity. Then, we use a hierarchical cluster analysis to identify ICA-based ISAC clusters of monkey and human networks with similar timecourses. We implemented this approach on fMRI data collected in monkeys and humans during movie watching, a condition that evokes widespread sensory-driven activity throughout large portions of the cortex. Using ICA-based ISAC, we detected seven monkey-human clusters. The timecourses of several clusters showed significant correspondences with either the motion energy in the movie or with eye-movement parameters. Five of the clusters spanned putative homologous functional networks in either primary or extrastriate visual regions, whereas two clusters included higher-level visual areas at topological locations that are not predicted by cortical surface expansion models. Overall, our ICA-based ISAC analysis complemented the findings of our previous seed-based investigations, and suggested that functional processes can be executed by brain networks in different species that are functionally but not necessarily anatomically correspondent. Overall, our method provides a novel approach to reveal evolution-driven functional changes in the primate brain with no spatial assumptions.
cluster analysis; independent component analysis; functional magnetic resonance imaging; primate brain; evolution; functional correspondence