Accuracy analysis of fMRI and MEG activations determined by intraoperative mapping.

OBJECTIVE: By looking at how the accuracy of preoperative brain mapping methods vary according to differences in the distance from the activation clusters used for the analysis, the present study aimed to elucidate how preoperative functional neuroimaging may be used in such a way that maximizes the mapping accuracy. METHODS: The eloquent function of 19 patients with a brain tumor or cavernoma was mapped prior to resection with both functional MRI (fMRI) and magnetoencephalography (MEG). The mapping results were then validated using direct cortical stimulation mapping performed immediately after craniotomy and prior to resection. The subset of patients with equivalent MEG and fMRI tasks performed for motor (n = 14) and language (n = 12) were evaluated as both individual and combined predictions. Furthermore, the distance resulting in the maximum accuracy, as evaluated by the J statistic, was determined by plotting the sensitivities and specificities against a linearly increasing distance threshold. RESULTS: fMRI showed a maximum mapping accuracy at 5 mm for both motor and language mapping. MEG showed a maximum mapping accuracy at 40 mm for motor and 15 mm for language mapping. At the standard 10-mm distance used in the literature, MEG showed a greater specificity than fMRI for both motor and language mapping but a lower sensitivity for motor mapping. Combining MEG and fMRI showed a maximum accuracy at 15 mm and 5 mm-MEG and fMRI distances, respectively-for motor mapping and at a 10-mm distance for both MEG and fMRI for language mapping. For motor mapping, combining MEG and fMRI at the optimal distances resulted in a greater accuracy than the maximum accuracy of the individual predictions. CONCLUSIONS: This study demonstrates that the accuracy of language and motor mapping for both fMRI and MEG is heavily dependent on the distance threshold used in the analysis. Furthermore, combining MEG and fMRI showed the potential for increased motor mapping accuracy compared to when using the modalities separately.Clinical trial registration no.: NCT01535430 (clinicaltrials.gov).

The human functional brain network demonstrates structural and dynamical resilience to targeted attack.

In recent years, the field of network science has enabled researchers to represent the highly complex interactions in the brain in an approachable yet quantitative manner. One exciting finding since the advent of brain network research was that the brain network can withstand extensive damage, even to highly connected regions. However, these highly connected nodes may not be the most critical regions of the brain network, and it is unclear how the network dynamics are impacted by removal of these key nodes. This work seeks to further investigate the resilience of the human functional brain network. Network attack experiments were conducted on voxel-wise functional brain networks and region-of-interest (ROI) networks of 5 healthy volunteers. Networks were attacked at key nodes using several criteria for assessing node importance, and the impact on network structure and dynamics was evaluated. The findings presented here echo previous findings that the functional human brain network is highly resilient to targeted attacks, both in terms of network structure and dynamics.

Power of food moderates food craving, perceived control, and brain networks following a short-term post-absorptive state in older adults.

The Power of Food Scale (PFS) is a new measure that assesses the drive to consume highly palatable food in an obesogenic food environment. The data reported in this investigation evaluate whether the PFS moderates state cravings, control beliefs, and brain networks of older, obese adults following either a short-term post-absorptive state, in which participants were only allowed to consume water, or a short-term energy surfeit treatment condition, in which they consumed BOOST®. We found that the short-term post-absorptive condition, in which participants consumed water only, was associated with increases in state cravings for desired food, a reduction in participants' confidence related to the control of eating behavior, and shifts in brain networks that parallel what is observed with other addictive behaviors. Furthermore, individuals who scored high on the PFS were at an increased risk for experiencing these effects. Future research is needed to examine the eating behavior of persons who score high on the PFS and to develop interventions that directly target food cravings.

Gene-expression profiles predict survival of patients with lung adenocarcinoma.

Histopathology is insufficient to predict disease progression and clinical outcome in lung adenocarcinoma. Here we show that gene-expression profiles based on microarray analysis can be used to predict patient survival in early-stage lung adenocarcinomas. Genes most related to survival were identified with univariate Cox analysis. Using either two equivalent but independent training and testing sets, or 'leave-one-out' cross-validation analysis with all tumors, a risk index based on the top 50 genes identified low-risk and high-risk stage I lung adenocarcinomas, which differed significantly with respect to survival. This risk index was then validated using an independent sample of lung adenocarcinomas that predicted high- and low-risk groups. This index included genes not previously associated with survival. The identification of a set of genes that predict survival in early-stage lung adenocarcinoma allows delineation of a high-risk group that may benefit from adjuvant therapy.

Universal fractal scaling of self-organized networks.

There is an abundance of literature on complex networks describing a variety of relationships among units in social, biological, and technological systems. Such networks, consisting of interconnected nodes, are often self-organized, naturally emerging without any overarching designs on topological structure yet enabling efficient interactions among nodes. Here we show that the number of nodes and the density of connections in such self-organized networks exhibit a power law relationship. We examined the size and connection density of 47 self-organizing networks of various biological, social, and technological origins, and found that the size-density relationship follows a fractal relationship spanning over 6 orders of magnitude. This finding indicates that there is an optimal connection density in self-organized networks following fractal scaling regardless of their sizes.

Comparison of characteristics between region-and voxel-based network analyses in resting-state fMRI data.

Small-world networks are a class of networks that exhibit efficient long-distance communication and tightly interconnected local neighborhoods. In recent years, functional and structural brain networks have been examined using network theory-based methods, and consistently shown to have small-world properties. Moreover, some voxel-based brain networks exhibited properties of scale-free networks, a class of networks with mega-hubs. However, there are considerable inconsistencies across studies in the methods used and the results observed, particularly between region-based and voxel-based brain networks. We constructed functional brain networks at multiple resolutions using the same resting-state fMRI data, and compared various network metrics, degree distribution, and localization of nodes of interest. It was found that the networks with higher resolutions exhibited the properties of small-world networks more prominently. It was also found that voxel-based networks were more robust against network fragmentation compared to region-based networks. Although the degree distributions of all networks followed an exponentially truncated power law rather than true power law, the higher the resolution, the closer the distribution was to a power law. The voxel-based analyses also enhanced visualization of the results in the 3D brain space. It was found that nodes with high connectivity tended have high efficiency, a co-localization of properties that was not as consistently observed in the region-based networks. Our results demonstrate benefits of constructing the brain network at the finest scale the experiment will permit.

Applying capacity analyses to psychophysical evaluation of multisensory interactions.

Determining when, if, and how information from separate sensory channels has been combined is a fundamental goal of research on multisensory processing in the brain. This can be a particular challenge in psychophysical data, as there is no direct recording of neural output. The most common way to characterize multisensory interactions in behavioral data is to compare responses to multisensory stimulation with the race model, a model of parallel, independent processing constructed from the probability of responses to the two unisensory stimuli which make up the multisensory stimulus. If observed multisensory reaction times are faster than those predicted by the model, it is inferred that information from the two channels is being combined rather than processed independently. Recently, behavioral research has been published employing capacity analyses where comparisons between two conditions are carried out at the level of the integrated hazard function. Capacity analyses seem to be particularly appealing technique for evaluating multisensory functioning, as they describe relationships between conditions across the entire distribution curve, are relatively easy and intuitive to interpret. The current paper presents capacity analysis of a behavioral data set previously analyzed using the race model. While applications of capacity analyses are still somewhat limited due to their novelty, it is hoped that this exploration of capacity and race model analyses will encourage the use of this promising new technique both in multisensory research and other applicable fields.

Aging and the interaction of sensory cortical function and structure.

Even the healthiest older adults experience changes in cognitive and sensory function. Studies show that older adults have reduced neural responses to sensory information. However, it is well known that sensory systems do not act in isolation but function cooperatively to either enhance or suppress neural responses to individual environmental stimuli. Very little research has been dedicated to understanding how aging affects the interactions between sensory systems, especially cross-modal deactivations or the ability of one sensory system (e.g., audition) to suppress the neural responses in another sensory system cortex (e.g., vision). Such cross-modal interactions have been implicated in attentional shifts between sensory modalities and could account for increased distractibility in older adults. To assess age-related changes in cross-modal deactivations, functional MRI studies were performed in 61 adults between 18 and 80 years old during simple auditory and visual discrimination tasks. Results within visual cortex confirmed previous findings of decreased responses to visual stimuli for older adults. Age-related changes in the visual cortical response to auditory stimuli were, however, much more complex and suggested an alteration with age in the functional interactions between the senses. Ventral visual cortical regions exhibited cross-modal deactivations in younger but not older adults, whereas more dorsal aspects of visual cortex were suppressed in older but not younger adults. These differences in deactivation also remained after adjusting for age-related reductions in brain volume of sensory cortex. Thus, functional differences in cortical activity between older and younger adults cannot solely be accounted for by differences in gray matter volume.

The effect of daily caffeine use on cerebral blood flow: How much caffeine can we tolerate?

Caffeine is a commonly used neurostimulant that also produces cerebral vasoconstriction by antagonizing adenosine receptors. Chronic caffeine use results in an adaptation of the vascular adenosine receptor system presumably to compensate for the vasoconstrictive effects of caffeine. We investigated the effects of caffeine on cerebral blood flow (CBF) in increasing levels of chronic caffeine use. Low (mean = 45 mg/day), moderate (mean = 405 mg/day), and high (mean = 950 mg/day) caffeine users underwent quantitative perfusion magnetic resonance imaging on four separate occasions: twice in a caffeine abstinent state (abstained state) and twice in a caffeinated state following their normal caffeine use (native state). In each state, there were two drug conditions: participants received either caffeine (250 mg) or placebo. Gray matter CBF was tested with repeated-measures analysis of variance using caffeine use as a between-subjects factor, and correlational analyses were conducted between CBF and caffeine use. Caffeine reduced CBF by an average of 27% across both caffeine states. In the abstained placebo condition, moderate and high users had similarly greater CBF than low users; but in the native placebo condition, the high users had a trend towards less CBF than the low and moderate users. Our results suggest a limited ability of the cerebrovascular adenosine system to compensate for high amounts of daily caffeine use.

Preservation of crossmodal selective attention in healthy aging.

The goal of the present study was to determine if older adults benefited from attention to a specific sensory modality in a voluntary attention task and evidenced changes in voluntary or involuntary attention when compared to younger adults. Suppressing and enhancing effects of voluntary attention were assessed using two cued forced-choice tasks, one that asked participants to localize and one that asked them to categorize visual and auditory targets. Involuntary attention was assessed using the same tasks, but with no attentional cues. The effects of attention were evaluated using traditional comparisons of means and Cox proportional hazards models. All analyses showed that older adults benefited behaviorally from selective attention in both visual and auditory conditions, including robust suppressive effects of attention. Of note, the performance of the older adults was commensurate with that of younger adults in almost all analyses, suggesting that older adults can successfully engage crossmodal attention processes. Thus, age-related increases in distractibility across sensory modalities are likely due to mechanisms other than deficits in attentional processing.

Closing the mind's eye: deactivation of visual cortex related to auditory task difficulty.

Blood oxygen-level-dependent signal decreases relative to baseline (deactivations) can occur with stimulation of an opposing sensory modality. Here, we show the importance of the difficulty of an auditory task on the deactivation of visual cortical areas. Participants performed an auditory temporal-order judgment task in conjunction with sparse-sampling functional MRI at both moderate and high levels of difficulty (adjusted for each individual's own threshold). With moderate difficulty, small deactivations were observed not only in parietal and cingulate cortex, but occipital cortex as well. When the same task was more difficult, deactivations increased significantly to include a greater extent of functionally defined visual cortex. Together, these results suggest that cross-modal deactivations occur in compensation for task difficulty, perhaps acting as an intrinsic filter for nonrelevant information.

Oncologic efficacy of CT-guided percutaneous radiofrequency ablation of renal cell carcinomas.

OBJECTIVE: A single institution's experience with CT-guided percutaneous radiofrequency ablation of biopsy-proven renal cell carcinomas (RCCs) was studied to determine the disease-free survival and complication rate. MATERIALS AND METHODS: Data from 125 RCCs in 104 patients treated with curative intent was reviewed. Radiofrequency ablation treatments were performed using conscious sedation and local anesthesia. Patients were followed with contrast-enhanced CT or MRI. Tumor control was defined as the absence of contrast enhancement in the tumor on CT or MRI. RESULTS: Tumor size ranged from 0.6 to 8.8 cm (mean, 2.7 cm; SD, 1.5 cm). Of the 125 treated tumors, 116 (93%) were completely ablated (109 in a single ablation session, seven after a second ablation session) with a mean follow-up interval of 13.8 months. All 95 RCCs smaller than 3.7 cm were completely ablated, and 21 (70%) of 30 larger tumors were completely ablated, with nine showing evidence of residual viable tumor on follow-up scans. Tumor size smaller than 3.7 cm was significantly associated with achieving complete tumor eradication (p < 0.001). With each 1-cm increase in tumor diameter over 3.6 cm, the likelihood of tumor-free survival decreased by a factor of 2.19 (p < 0.001). There were 8 (8%) complications, none of which resulted in long-term morbidity. CONCLUSION: CT-guided percutaneous radiofrequency ablation is a safe method to treat small RCCs. This study indicates that radiofrequency ablation can reliably eradicate RCCs smaller than 3.7 cm. Treatment of larger RCCs will result in an increased risk of residual RCC.

Anti-Fragmentation of Resting-State Functional Magnetic Resonance Imaging Connectivity Networks with Node-Wise Thresholding.

Functional magnetic resonance imaging (fMRI)-based functional connectivity networks are often constructed by thresholding a correlation matrix of nodal time courses. In a typical thresholding approach known as hard thresholding, a single threshold is applied to the entire correlation matrix to identify edges representing superthreshold correlations. However, hard thresholding is known to produce a network with uneven allocation of edges, resulting in a fragmented network with a large number of disconnected nodes. It is suggested that an alternative network thresholding approach, node-wise thresholding, is able to overcome these problems. To examine this, various network characteristics were compared between networks constructed by hard thresholding and node-wise thresholding, with publicly available resting-state fMRI data from 123 healthy young subjects. It was found that networks constructed with hard thresholding included a large number of disconnected nodes, while such network fragmentation was not observed in networks formed with node-wise thresholding. Moreover, in hard thresholding networks, fragmentized modular organization was observed, characterized by a large number of small modules. On the contrary, such modular fragmentation was not observed in node-wise thresholding networks, producing modules that were robust at any threshold and highly consistent across subjects. These results indicate that node-wise thresholding may lead to less fragmented networks. Moreover, node-wise thresholding enables robust characterization of network properties without much influence by the selection of a threshold.

Enhancing tissue permeability with MRI guided preclinical focused ultrasound system in rabbit muscle: From normal tissue to VX2 tumor.

High Intensity Focused Ultrasound (HIFU) is an emerging noninvasive, nonionizing physical energy based modality to ablate solid tumors with high power, or increase local permeability in tissues/tumors in pulsed mode with relatively low power. Compared with traditional ablative HIFU, nondestructive pulsed HIFU (pHIFU) is present in the majority of novel applications recently developed for enhancing the delivery of drugs and genes. Previous studies have demonstrated the capability of pHIFU to change tissue local permeability for enhanced drug delivery in both mouse tumors and mouse muscle. Further study based on bulk tissues in large animals and clinical HIFU system revealed correlation between therapeutic effect and thermal parameters, which was absent in the previous mouse studies. In this study, we further investigated the relation between the therapeutic effect of pHIFU and thermal parameters in bulky normal muscle tissues based on a rabbit model and a preclinical HIFU system. Correlation between therapeutic effect and thermal parameters was confirmed in our study on the same bulk tissues although different HIFU systems were used. Following the study in bulky normal muscle tissues, we further created bulky tumor model with VX2 tumors implanted on both hind limbs of rabbits and investigated the feasibility to enhance tumor permeability in bulky VX2 tumors in a rabbit model using pHIFU technique. A radiolabeled peptidomimetic integrin antagonist, 111In-DOTA-IA, was used following pHIFU treatment in our study to target VX2 tumor and serve as the radiotracer for follow-up single-photon emission computed tomography (SPECT) scanning. The results have shown significantly elevated uptake of 111In-DOTA-IA in the area of VX2 tumors pretreated by pHIFU compared with the control VX2 tumors not being pretreated by pHIFU, and statistical analysis revealed averaged 34.5% enhancement 24h after systematic delivery of 111In-DOTA-IA in VX2 tumors pretreated by pHIFU compared with the control VX2 tumors.

Volumetric correlates of memory and executive function in normal elderly, mild cognitive impairment and Alzheimer's disease.

In Alzheimer's disease (AD), atrophy negatively impacts cognition while in healthy adults, inverse relationships between brain volume and cognition may occur. We investigated correlations between gray matter volume and cognition in elderly controls, AD and mild cognitive impairment (MCI) patients with memory and executive deficits. AD demonstrated substantial loss in temporal, parietal and frontal regions while MCI exhibited moderate volume loss in temporal and frontal regions. In controls, memory and executive function were negatively correlated with frontal regions, while in AD, memory was positively correlated with temporal and frontal gyri, and executive function with frontal regions. The combination of the two patterns may explain the lack of correlations in MCI. Developmental versus pathological contributions to these relationships are discussed.

Relative differences in resting-state brain connectivity associated with long term intensive lifestyle intervention.

A number of studies have reported that type 2 diabetes mellitus (T2DM) is associated with alterations in resting-state activity and connectivity in the brain. There is also evidence that interventions involving physical activity and weight loss may affect brain functional connectivity. In this study, we examined the effects of nearly 10 years of an intensive lifestyle intervention (ILI), designed to induce and sustain weight loss through lower caloric intake and increased physical activity, on resting-state networks in adults with T2DM. We performed a cross-sectional comparison of global and local characteristics from functional brain networks between individuals who had been randomly assigned to ILI or a control condition of health education and support. Upon examining brain networks from 312 participants (average age: 68.8 for ILI and 67.9 for controls), we found that ILI participants (N=160) had attenuated local efficiency at the network-level compared with controls (N=152). Although there was no group difference in the network-level global efficiency, we found that, among ILI participants, nodal global efficiency was elevated in left fusiform gyrus, right middle frontal gyrus, and pars opercularis of right inferior frontal gyrus. These effects were age-dependent, with more pronounced effects for older participants. Overall these results indicate that the individuals assigned to the ILI had brain networks with less regional and more global connectivity, particularly involving frontal lobes. Such patterns would support greater distributed information processing. Future studies are needed to determine if these differences are associated with age-related compensatory function in the ILI group or worse pathology in the control group.

Remote spatiotemporally controlled and biologically selective permeabilization of blood-brain barrier.

The blood-brain barrier (BBB), comprised of brain endothelial cells with tight junctions (TJ) between them, regulates the extravasation of molecules and cells into and out of the central nervous system (CNS). Overcoming the difficulty of delivering therapeutic agents to specific regions of the brain presents a major challenge to treatment of a broad range of brain disorders. Current strategies for BBB opening are invasive, not specific, and lack precise control over the site and timing of BBB opening, which may limit their clinical translation. In the present report, we describe a novel approach based on a combination of stem cell delivery, heat-inducible gene expression and mild heating with high-intensity focused ultrasound (HIFU) under MRI guidance to remotely permeabilize BBB. The permeabilization of the BBB will be controlled with, and limited to where selected pro-inflammatory factors will be secreted secondary to HIFU activation, which is in the vicinity of the engineered stem cells and consequently both the primary and secondary disease foci. This therapeutic platform thus represents a non-invasive way for BBB opening with unprecedented spatiotemporal precision, and if properly and specifically modified, can be clinically translated to facilitate delivery of different diagnostic and therapeutic agents which can have great impact in treatment of various disease processes in the central nervous system.

The regulation of prostate cancer cell adhesion to human bone marrow endothelial cell monolayers by androgen dihydrotestosterone and cytokines.

A previous study from our laboratory suggested that prostate cancer metastasis to bone may be mediated, in part, by preferential adhesion to human bone marrow endothelial (HBME) cells. Tumor cell adhesion to endothelial cells may be modulated by the effect of cytokines on cell adhesion molecules (CAMs). Tumor necrosis factor-alpha (TNF-alpha) regulates VCAM expression on the endothelium and this effect is enhanced by dihydrotestosterone (DHT). Transforming growth factor-beta (TGF-beta) stimulates the expression of alpha2beta1 integrin on PC-3 cells. The current study investigated the effects of the above cytokines and DHT (singularly and in various combinations) upon HBME and prostate cancer cell expression of VCAM, alpha2 integrin subunit, and beta1 integrin subunit by flow cytometry. We also monitored the effects of the above treatments on PC-3 cell adhesion to HBME monolayers. The data demonstrate that none of the treatments significantly altered the expression of selected CAMs on HBME cell and neoplastic prostate cell lines. The treatment of HBME monolayers with various combinations of cytokines and DHT prior to performing adhesion assays with PC-3 demonstrates that treatments containing TGF-beta reduced PC-3 cell adhesion to HBME monolayers by 32% or greater (P < 0.05). The reduction in PC-3 cell adhesion to TGF-beta-treated HBME monolayers was dose dependent. Interestingly, LNCaP cells but not PC-3 cells treated with TGF-beta had a reduced ability to adhere to untreated HBME monolayers. These results suggest that TGF-beta may reduce tumor cell adhesion to bone marrow microvascular endothelium, in vivo. The biological significance of this observation is discussed.

Controlling the familywise error rate in functional neuroimaging: a comparative review.

Functional neuroimaging data embodies a massive multiple testing problem, where 100,000 correlated test statistics must be assessed. The familywise error rate, the chance of any false positives is the standard measure of Type I errors in multiple testing. In this paper we review and evaluate three approaches to thresholding images of test statistics: Bonferroni, random field and the permutation test. Owing to recent developments, improved Bonferroni procedures, such as Hochberg's methods, are now applicable to dependent data. Continuous random field methods use the smoothness of the image to adapt to the severity of the multiple testing problem. Also, increased computing power has made both permutation and bootstrap methods applicable to functional neuroimaging. We evaluate these approaches on t images using simulations and a collection of real datasets. We find that Bonferroni-related tests offer little improvement over Bonferroni, while the permutation method offers substantial improvement over the random field method for low smoothness and low degrees of freedom. We also show the limitations of trying to find an equivalent number of independent tests for an image of correlated test statistics.

Functional brain networks formed using cross-sample entropy are scale free.

Over the previous decade, there has been an explosion of interest in network science, in general, and its application to the human brain, in particular. Most brain network investigations to date have used linear correlations (LinCorr) between brain areas to construct and then interpret brain networks. In this study, we applied an entropy-based method to establish functional connectivity between brain areas. This method is sensitive to both nonlinear and linear associations. The LinCorr-based and entropy-based techniques were applied to resting-state functional magnetic resonance imaging data from 10 subjects, and the resulting networks were compared. The networks derived from the entropy-based method exhibited power-law degree distributions. Moreover, the entropy-based networks had a higher clustering coefficient and a shorter path length compared with that of the LinCorr-based networks. While the LinCorr-based networks were assortative, with nodes with similar degrees preferentially connected, the entropy-based networks were disassortative, with high-degree hubs directly connected to low-degree nodes. It is likely that the differences in clustering and assortativity are due to "mega-hubs" in the entropy-based networks. These mega-hubs connect to a large majority of the nodes in the network. This is the first work clearly demonstrating differences between functional brain networks using linear and nonlinear techniques. The key finding is that the nonlinear technique produced networks with scale-free degree distributions. There remains debate among the neuroscience community as to whether human brains are scale free. These data support the argument that at least some aspects of the human brain are perhaps scale free.