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•From rest to task, GSCORR reduces in sensory but increases in associative areas.•Reallocation of functional resources from sensory to associative regions at task.•Two distinct clusters of areas are recruited during GO and STOP trials.•GSCORR correlates with deactivation rather than activation.•GSCORR, activation and deactivation reflect distinct neurofunctional processes. The dynamics of global, state-dependent reconfigurations in brain connectivity are yet unclear. We aimed at assessing reconfigurations of the global signal correlation coefficient (GSCORR), a measure of the connectivity between each voxel timeseries and the global signal, from resting-state to a stop-signal task. The secondary aim was to assess the relationship between GSCORR and blood-oxygen-level-dependent (BOLD) activations or deactivation across three different trial-conditions (GO, STOP-correct, and STOP-incorrect). As primary analysis we computed whole-brain, voxel-wise GSCORR during resting-state (GSCORR-rest) and stop-signal task (GSCORR-task) in 107 healthy subjects aged 21–50, deriving GSCORR-shift as GSCORR-task minus GSCORR-rest. GSCORR-tr and trGSCORR-shift were also computed on the task residual time series to quantify the impact of the task-related activity during the trials. To test the secondary aim, brain regions were firstly divided in one cluster showing significant task-related activation and one showing significant deactivation across the three trial conditions. Then, correlations between GSCORR-rest/task/shift and activation/deactivation in the two clusters were computed. As sensitivity analysis, GSCORR-shift was computed on the same sample after performing a global signal regression and GSCORR-rest/task/shift were correlated with the task performance. Sensory and temporo-parietal regions exhibited a negative GSCORR-shift. Conversely, associative regions (ie. left lingual gyrus, bilateral dorsal posterior cingulate gyrus, cerebellum areas, thalamus, posterolateral parietal cortex) displayed a positive GSCORR-shift (FDR-corrected p < 0.05). GSCORR-shift showed similar patterns to trGSCORR-shift (magnitude increased) and after global signal regression (magnitude decreased). Concerning BOLD changes, Brodmann area 6 and inferior parietal lobule showed activation, while posterior parietal lobule, cuneus, precuneus, middle frontal gyrus showed deactivation (FDR-corrected p < 0.05). No correlations were found between GSCORR-rest/task/shift and beta-coefficients in the activation cluster, although negative correlations were observed between GSCORR-task and GO/STOP-correct deactivation (Pearson rho=-0.299/-0.273; Bonferroni-p < 0.05). Weak associations between GSCORR and task performance were observed (uncorrected p < 0.05). GSCORR state-dependent reconfiguration indicates a reallocation of functional resources to associative areas during stop-signal task. GSCORR, activation and deactivation may represent distinct proxies of brain states with specific neurofunctional relevance.

The relationship between Blood-Oxygen-Level-Dependent (BOLD) responses in functional magnetic resonance imaging (fMRI) and increases or decreases in neural firing rate across human brain regions, especially the association cortex, remains largely unknown. Here, we contrast direct measures of neuronal activity in two adjacent brain regions of the fusiform gyrus (FG) associated with fMRI increases (lateral FG portion) or decreases (medial FG portion) of the same category-selective neural activity. In both individual brains tested across multiple recording sessions, a frequency-tagging stimulation objectively identified a substantial proportion (about 70%) of face-selective neurons. While single units recorded in the lateral FG showed a selective increase to faces, neurons localized in the medial FG decreased spiking activity selectively to faces. Beyond a relative reduction to faces compared to non-face objects, about a third of the single neurons found in the medial FG showed genuine suppression of baseline spiking activity upon presentation of a face. These observations clarify the nature of face-selective neural activity in the human brain, which can be expressed both as increases and active suppressions of spiking activity and, more generally, shed light on the physiological basis of the fMRI signal.

Beta-amyloid (Aβ) positive individuals hyper-activate brain regions compared to those not at-risk; however, hyperactivation is then thought to diminish as Alzheimer's disease symptomatology begins, evidencing eventual hypoactivation. It remains unclear when in the disease staging this transition occurs. We hypothesized that differential levels of amyloid burden would be associated with both increased and decreased activation (i.e., a quadratic trajectory) in cognitively-normal adults. Participants (N = 62; aged 51–94) underwent an fMRI spatial distance-judgment task and Amyvid-PET scanning. Voxelwise regression modeled age, linear-Aβ, and quadratic-Aβ as predictors of BOLD activation to difficult spatial distance-judgments. A significant quadratic-Aβ effect on BOLD response explained differential activation in bilateral angular/temporal and medial prefrontal cortices, such that individuals with slightly elevated Aβ burden exhibited hyperactivation whereas even higher Aβ burden was then associated with hypoactivation. Importantly, in high-Aβ individuals, Aβ load moderated the effect of BOLD activation on behavioral task performance, where in lower-elevation, greater deactivation was associated with better accuracy, but in higher-elevation, greater deactivation was associated with poorer accuracy during the task. This study reveals a dose-response, quadratic relationship between increasing Aβ burden and alterations in BOLD activation to cognitive challenge in cognitively-normal individuals that suggests 1) the shift from hyper-to hypo-activation may begin early in disease staging, 2) depends, in part, on degree of Aβ burden, and 3) tracks cognitive performance. •Alzheimer's stages are associated with both hyper- and hypoactivation during fMRI.•When in the disease process hyper- to hypoactivation transition occurs is unclear.•Currently thought to transition in later stages after significant symptomatology.•fMRI and amyloid-PET scanning results indicated nonlinear staging association of Aβ.•Hypoactivation transition begins in preclinical adults and tracks task performance.

Recent evidence indicates that the relationship between increased beta-amyloid (Aβ) deposition and functional task-activation can be characterized by a non-linear trajectory of change in functional activation (Foster et al., 2017), explaining mixed results in prior literature showing both increases and decreases in activation as a function of beta-amyloid burden in cognitively normal adults. Here we sought to replicate this nonlinear effect in the same sample using a different functional paradigm to test the generalizability of this phenomenon. Participants (N = 68 healthy adults aged 49–94) underwent fMRI (0-, 2-, 3-, 4-back working memory task; WM) and 18F-Florbetapir PET scanning. A parametric WM load contrast was used as the dependent variable in a model with age, mean cortical Aβ, and Aβ2 as predictors. Results revealed that nonlinear amyloid (Aβ2) was a significant negative predictor of modulation of activation to WM load in two large inferior clusters: bilateral subcortical nuclei and bilateral lateral cerebellum. Individuals with slightly elevated Aβ burden evidenced greater modulation as compared to individuals with little or no Aβ burden, whereas individuals with the greatest Aβ burden evidenced lesser modulation as compared to individuals with slightly elevated Aβ. Increased modulation to WM load predicted better task accuracy and executive function measured outside the scanner. The current study provides further evidence for a dose-response, nonlinear relationship between increasing Aβ burden and alteration in brain activation in cognitively healthy adults, extending the existing evidence to dynamic range of activation to task difficulty, and reconciling seemingly discrepant effects of amyloid on brain function.

This manuscript examines the origins and nature of the function-derived activation detected by magnetic resonance imaging at ultrahigh fields using different encoding methods. A series of preclinical high field (7T) and ultra-high field (17.2T) fMRI experiments were performed using gradient echo EPI, spin echo EPI and spatio-temporally encoded (SPEN) strategies. The dependencies of the fMRI signal change on the strength of the magnetic field and on different acquisition and sequence parameters were investigated. Artifact-free rat brain images with good resolution in all areas, as well as significant localized activation maps upon forepaw stimulation, were obtained in a single scan using fully refocused SPEN sequences devoid of T2* effects. Our results showed that, besides the normal T2-weighted BOLD contribution that arises in spin-echo sequences, fMRI SPEN signals contain a strong component caused by apparent T1-related effects, demonstrating the potential of such technique for exploring functional activation in rodents and on humans at ultrahigh fields. [Display omitted] •Functional rodent brain images were collected at high and ultrahigh magnetic fields by EPI and SPEN methods•Although devoid from T2* effects, fully-refocused SPEN produces ultrahigh field functional activation maps with good contrast•Besides T2 and BOLD contributions, contrast in ultrahigh field SPEN fMRI arises from a T1 related component

After staring at a blank region surrounded by a dynamic background for a few seconds, observers report a twinkle aftereffect in the unstimulated blank region. The significance of this twinkle aftereffect is that it occurs at a location that received no stimulation, and therefore reflects a rebound from lateral inhibition within the dynamic processing system. To study this inhibitory rebound effect, the blood oxygenation level dependent (BOLD) activation in the visual cortex was measured while the observers were viewing a flickering pin-wheel pattern alternating with a blank test. Retinotopic regions corresponding to the inter-wedge regions in the pin-wheel pattern showed activation negatively correlated with the test sequence. While the BOLD activation in the visual cortex is generally considered to be retinotopically driven by the visual stimuli, we were able to show a sustained negative activation in the unstimulated regions, with properties that correspond to those of the inhibitory rebound of the perceived aftereffect.

Resting state functional magnetic resonance (rs-fMRI) imaging offers insights into how different brain regions are connected into functional networks. It was recently shown that networks that are almost identical to the ones created from conventional correlation analysis can be obtained from a subset of high-amplitude data, suggesting that the functional networks may be driven by instantaneous co-activations of multiple brain regions rather than ongoing oscillatory processes. The rs-fMRI studies, however, rely on the blood oxygen level dependent (BOLD) signal, which is only indirectly sensitive to neural activity through neurovascular coupling. To provide more direct evidence that the neuronal co-activation events produce the time-varying network patterns seen in rs-fMRI studies, we examined the simultaneous rs-fMRI and local field potential (LFP) recordings in rats performed in our lab over the past several years. We developed complementary analysis methods that focus on either the temporal or spatial domain, and found evidence that the interaction between LFP and BOLD may be driven by instantaneous co-activation events as well. BOLD maps triggered on high-amplitude LFP events resemble co-activation patterns created from rs-fMRI data alone, though the co-activation time points are defined differently in the two cases. Moreover, only LFP events that fall into the highest or lowest thirds of the amplitude distribution result in a BOLD signal that can be distinguished from noise. These findings provide evidence of an electrophysiological basis for the time-varying co-activation patterns observed in previous studies. •The relationship between LFP and BOLD is dominated by the high-amplitude events.•FMRI frames that co-occur with high LFP events can resemble LFP-BOLD correlation map.•Such fMRI frames can be divided into a few groups showing distinct spatial patterns.•Multimodal methods might provide insights into dynamic functional connectivity.

The goal of this review is to describe, from a personal perspective, the development and emergence of the resting state fMRI. In particular, various concepts derived from the resting state data are discussed in detail, including connectivity, amplitude of the fluctuations, analysis techniques, and use in clinical populations. We also briefly summarize our efforts in creating an open data sharing platform as well as both a journal and a conference dedicated to brain connectivity. All three projects are aimed at significantly increasing the impact of resting state fMRI developments and enabling large, collaborative science projects. ► The development and emergence of the resting state fMRI is presented. ► Various concepts derived from resting state fMRI are discussed. ► We summarize our efforts in creating an open data sharing platform. ► Formation of a journal and a conference dedicated to brain connectivity is discussed.

Interactions between top-down and bottom-up information streams are integral to brain function but challenging to measure noninvasively. Laminar resolution, functional MRI (lfMRI) is sensitive to depth-dependent properties of the blood oxygen level-dependent (BOLD) response, which can be potentially related to top-down and bottom-up signal contributions. In this work, we used lfMRI to dissociate the top-down and bottom-up signal contributions to the left occipitotemporal sulcus (LOTS) during word reading. We further demonstrate that laminar resolution measurements could be used to identify condition-specific distributed networks on the basis of whole-brain connectivity patterns specific to the depth-dependent BOLD signal. The networks corresponded to top-down and bottom-up signal pathways targeting the LOTS during word reading. We show that reading increased the top-down BOLD signal observed in the deep layers of the LOTS and that this signal uniquely related to the BOLD response in other language-critical regions. These results demonstrate that lfMRI can reveal important patterns of activation that are obscured at standard resolution. In addition to differences in activation strength as a function of depth, we also show meaningful differences in the interaction between signals originating from different depths both within a region and with the rest of the brain. We thus show that lfMRI allows the noninvasive measurement of directed interaction between brain regions and is capable of resolving different connectivity patterns at submillimeter resolution, something previously considered to be exclusively in the domain of invasive recordings.

Functional magnetic resonance imaging (fMRI) depicts neural activity in the brain indirectly by measuring blood oxygenation level dependent (BOLD) signals. The majority of fMRI studies have focused on detecting cortical activity in gray matter (GM), but whether functional BOLD signal changes also arise in white matter (WM), and whether neural activities trigger hemodynamic changes in WM similarly to GM, remain controversial, particularly in light of the much lower vascular density in WM. However, BOLD effects in WM are readily detected under hypercapnic challenges, and the number of reports supporting reliable detections of stimulus-induced activations in WM continues to grow. Rather than assume a particular hemodynamic response function, we used a voxel-by-voxel analysis of frequency spectra in WM to detect WM activations under visual stimulation, whose locations were validated with fiber tractography using diffusion tensor imaging (DTI). We demonstrate that specific WM regions are robustly activated in response to visual stimulation, and that regional distributions of WM activation are consistent with fiber pathways reconstructed using DTI. We further examined the variation in the concordance between WM activation and fiber density in groups of different sample sizes, and compared the signal profiles of BOLD time series between resting state and visual stimulation conditions in activated GM as well as activated and non-activated WM regions. Our findings confirm that BOLD signal variations in WM are modulated by neural activity and are detectable with conventional fMRI using appropriate methods, thus offering the potential of expanding functional connectivity measurements throughout the brain. •White matter activation under visual stimulation is detected voxel-wise with fMRI.•Detected activation in white matter is validated by DTI tractography.•Sensitivity in detecting white matter activation is quantitatively analyzed.•BOLD signals in white and gray matter are statistically characterized.