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Central nervous system (CNS) sequelae continue to be common in HIV-infected individuals despite combination antiretroviral therapy (cART). These sequelae include HIV-associated neurocognitive disorder (HAND) and virologic persistence in the CNS. Resting state functional magnetic resonance imaging (rsfMRI) is a widely used tool to examine the integrity of brain function and pathology. In this study, we examined 16 HIV-positive (HIV+) subjects and 12 age, sex, and race matched HIV seronegative controls (HIV-) whole-brain high-resolution rsfMRI along with a battery of neurocognitive tests. A comprehensive data-driven analysis of rsfMRI revealed impaired functional connectivity, with very large effect sizes in executive function, language, and multisensory processing networks in HIV+ subjects. These results indicate the potential of high-resolution rsfMRI in combination with advanced data analysis techniques to yield biomarkers of neural impairment in HIV.

Quantifying accurate functional magnetic resonance imaging (fMRI) activation maps can be dampened by spatio-temporally varying task-correlated motion (TCM) artifacts in certain task paradigms (e.g., overt speech). Such real-world tasks are relevant to characterize longitudinal brain reorganization poststroke, and removal of TCM artifacts is vital for improved clinical interpretation and translation. In this study, we developed a novel independent component analysis (ICA)-based approach to denoise spatio-temporally varying TCM artifacts in 14 persons with aphasia who participated in an overt language fMRI paradigm. We compared the new methodology with other existing approaches such as "standard" volume registration, nonselective motion correction ICA packages (i.e., AROMA), and combining the novel approach with AROMA. Results show that the proposed methodology outperforms other approaches in removing TCM-related false positive activity (i.e., improved detectability power) with high spatial specificity. The proposed method was also effective in maintaining a balance between removal of TCM-related trial-by-trial variability and signal retention. Finally, we show that the TCM artifact is related to clinical metrics, such as speech fluency and aphasia severity, and the implication of TCM denoising on such relationship is also discussed. Overall, our work suggests that routine bulkhead motion based denoising packages cannot effectively account for spatio-temporally varying TCM. Further, the proposed TCM denoising approach requires a one-time front-end effort to hand label and train the classifiers that can be cost-effectively utilized to denoise large clinical data sets., (© 2020 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.)

Recently, dense connections have attracted substantial attention in computer vision because they facilitate gradient flow and implicit deep supervision during training. Particularly, DenseNet that connects each layer to every other layer in a feed-forward fashion and has shown impressive performances in natural image classification tasks. We propose HyperDenseNet, a 3-D fully convolutional neural network that extends the definition of dense connectivity to multi-modal segmentation problems. Each imaging modality has a path, and dense connections occur not only between the pairs of layers within the same path but also between those across different paths. This contrasts with the existing multi-modal CNN approaches, in which modeling several modalities relies entirely on a single joint layer (or level of abstraction) for fusion, typically either at the input or at the output of the network. Therefore, the proposed network has total freedom to learn more complex combinations between the modalities, within and in-between all the levels of abstraction, which increases significantly the learning representation. We report extensive evaluations over two different and highly competitive multi-modal brain tissue segmentation challenges, iSEG 2017 and MRBrainS 2013, with the former focusing on six month infant data and the latter on adult images. HyperDenseNet yielded significant improvements over many state-of-the-art segmentation networks, ranking at the top on both benchmarks. We further provide a comprehensive experimental analysis of features re-use, which confirms the importance of hyper-dense connections in multi-modal representation learning. Our code is publicly available.

Functional connectivity using task-residual data capitalizes on remaining variance after mean task-related signal is removed from a time series. The degree of network specificity in language and attention domains featured by task-residual and resting-state data types were compared. Functional connectivity based on task-residual data evidenced stronger laterality of the language and attention connections and thus greater network specificity compared to resting-state functional connectivity of the same connections. Covariance between network nodes of task-residuals may thus reflect the degree to which two regions are coordinated in their specific activity, rather than a general shared co-activation. Task-residual functional connectivity provides complementary data to that of resting-state, emphasizing network relationships during task engagement., (Copyright © 2018 Elsevier Inc. All rights reserved.)

Rationale: There is a significant interest in the NMDA-receptor antagonist ketamine due to its efficacy in treating depressive disorders and its induction of psychotic-like symptoms that make it a useful tool for modeling psychosis. Pharmacological MRI in awake nonhuman primates provides a highly translational model for studying the brain network dynamics involved in producing these drug effects., Objective: The present study evaluated ketamine-induced changes in functional connectivity (FC) in awake rhesus monkeys. The effects of ketamine after pretreatment with the antipsychotic drug risperidone were also examined., Methods: Functional MRI scans were conducted in four awake adult female rhesus monkeys during sub-anesthetic i.v. infusions of ketamine (0.345 mg/kg bolus followed by 0.256 mg kg -1  h -1 constant infusion) with and without risperidone pretreatment (0.06 mg/kg). A 10-min window of stable BOLD signal was used to compare FC between baseline and drug conditions. FC was assessed in specific regions of interest using seed-based cross-correlation analysis., Results: Ketamine infusion induced extensive changes in FC. In particular, FC to the dorsolateral prefrontal cortex (dlPFC) was increased in several cortical and subcortical regions. Pretreatment with risperidone largely attenuated ketamine-induced changes in FC., Conclusions: The results are highly consistent with similar human imaging studies showing ketamine-induced changes in FC, as well as a significant attenuation of these changes when ketamine infusion is preceded by pretreatment with risperidone. The extensive increases shown in FC to the dlPFC are consistent with the idea that disinhibition of the dlPFC may be a key driver of the antidepressant and psychotomimetic effects of ketamine.

Rationale: There is significant interest in the NMDA receptor antagonist ketamine due to its efficacy in treating depressive disorders and its induction of psychotic-like symptoms that make it a useful tool for modeling psychosis., Objective: The present study extends the successful development of an apparatus and methodology to conduct pharmacological MRI studies in awake rhesus monkeys in order to evaluate the CNS effects of ketamine., Methods: Functional MRI scans were conducted in four awake adult female rhesus monkeys during sub-anesthetic intravenous (i.v.) infusions of ketamine (0.345 mg/kg bolus followed by 0.256 mg/kg/h constant infusion) with and without risperidone pretreatment (0.06 mg/kg). Statistical parametric maps of ketamine-induced blood oxygenation level-dependent (BOLD) activation were obtained with appropriate general linear regression models (GLMs) incorporating motion and hemodynamics of ketamine infusion., Results: Ketamine infusion induced and sustained robust BOLD activation in a number of cortical and subcortical regions, including the thalamus, cingulate gyrus, and supplementary motor area. Pretreatment with the antipsychotic drug risperidone markedly blunted ketamine-induced activation in many brain areas., Conclusions: The results are remarkably similar to human imaging studies showing ketamine-induced BOLD activation in many of the same brain areas, and pretreatment with risperidone or another antipsychotic blunting the ketamine response to a similar extent. The strong concordance of the functional imaging data in humans with these results from nonhuman primates highlights the translational value of the model and provides an excellent avenue for future research examining the CNS effects of ketamine. This model may also be a useful tool for evaluating the efficacy of novel antipsychotic drugs.

A number of studies have established that transcranial direct current stimulation (tDCS) modulates cortical excitability. We previously demonstrated polarity dependent changes in parietal lobe blood oxygen level dependent (BOLD) fMRI in a group of young adults during a spatial navigation task [15]. Here we used resting state functional connectivity (rsFC) to examine whether analogous changes were also evident during the resting state. Participants were randomized to either a parietal-anodal, frontal-cathodal (P+F-) or the opposite montage (P-F+) and received 20min of tDCS (2mA) before undergoing resting-state fMRI. rsFC was evaluated between the groups by placing a seed in the medial superior parietal lobule (mSPL), which was under the target electrode. rsFC between the mSPL and a number of other areas involved in spatial navigation, scene processing, and sensorimotor processing was significantly higher in the P+F- than the P-F+ group. Thus, the modulatory effects of tDCS were evident during rest and suggest that stimulation primes not just the underlying neocortex but an extended network that can be recruited as necessary during active task performance., (Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.)

Approximately one quarter of 1991 Persian Gulf War Veterans experience cognitive and physiological sequelae that continue to be unexplained by known medical or psychological conditions. Difficulty coming up with words and names, familiar before the war, is a hallmark of the illness. Three Gulf War Syndrome subtypes have been identified and linked to specific war-time chemical exposures. The most functionally impaired veterans belong to the Gulf War Syndrome 2 (Syndrome 2) group, for which subcortical damage due to toxic nerve gas exposure is the suspected cause. Subcortical damage is often associated with specific complex language impairments, and Syndrome 2 veterans have demonstrated poorer vocabulary relative to controls. 11 Syndrome 1, 16 Syndrome 2, 9 Syndrome 3, and 14 age-matched veteran controls from the Seabees Naval Construction Battalion were compared across three measures of complex language. Additionally, functional magnetic resonance imaging (fMRI) was collected during a covert category generation task, and whole-brain functional activity was compared between groups. Results demonstrated that Syndrome 2 veterans performed significantly worse on letter and category fluency relative to Syndrome 1 veterans and controls. They also exhibited reduced activity in the thalamus, putamen, and amygdala, and increased activity in the right hippocampus relative to controls. Syndrome 1 and Syndrome 3 groups tended to show similar, although smaller, differences than the Syndrome 2 group. Hence, these results further demonstrate specific impairments in complex language as well as subcortical and hippocampal involvement in Syndrome 2 veterans. Further research is required to determine the extent of language impairments in this population and the significance of altered neurologic activity in the aforementioned brain regions with the purpose of better characterizing the Gulf War Syndromes., (Copyright © 2015 Elsevier Inc. All rights reserved.)

Ruminative thoughts about a stressful event can seem subjectively real, as if the imagined event were happening in the moment. One possibility is that this subjective realism results from simulating the self as engaged in the stressful event (immersion). If so, then the process of decentering--disengaging the self from the event--should reduce the subjective realism associated with immersion, and therefore perceived stressfulness. To assess this account of decentering, we taught non-meditators a strategy for disengaging from imagined events, simply viewing these events as transient mental states (mindful attention). In a subsequent neuroimaging session, participants imagined stressful and non-stressful events, while either immersing themselves or adopting mindful attention. In conjunction analyses, mindful attention down-regulated the processing of stressful events relative to baseline, whereas immersion up-regulated their processing. In direct contrasts between mindful attention and immersion, mindful attention showed greater activity in brain areas associated with perspective shifting and effortful attention, whereas immersion showed greater activity in areas associated with self-processing and visceral states. These results suggest that mindful attention produces decentering by disengaging embodied senses of self from imagined situations so that affect does not develop., (Copyright © 2015 Elsevier Ltd. All rights reserved.)

A major focus of brain research recently has been to map the resting-state functional connectivity (rsFC) network architecture of the normal brain and pathology through functional magnetic resonance imaging. However, the phenomenon of anticorrelations in resting-state signals between different brain regions has not been adequately examined. The preponderance of studies on resting-state fMRI (rsFMRI) have either ignored anticorrelations in rsFC networks or adopted methods in data analysis, which have rendered anticorrelations in rsFC networks uninterpretable. The few studies that have examined anticorrelations in rsFC networks using conventional methods have found anticorrelations to be weak in strength and not very reproducible across subjects. Anticorrelations in rsFC network architecture could reflect mechanisms that subserve a number of important brain processes. In this preliminary study, we examined the properties of anticorrelated rsFC networks by systematically focusing on negative cross-correlation coefficients (CCs) among rsFMRI voxel time series across the brain with graph theory-based network analysis. A number of methods were implemented to enhance the neuronal specificity of resting-state functional connections that yield negative CCs, although at the cost of decreased sensitivity. Hubs of anticorrelation were seen in a number of cortical and subcortical brain regions. Examination of the anticorrelation maps of these hubs indicated that negative CCs in rsFC network architecture highlight a number of regulatory interactions between brain networks and regions, including reciprocal modulations, suppression, inhibition, and neurofeedback.

Foreign accent syndrome (FAS) is a rare disorder characterized by the emergence of a perceived foreign accent following brain damage. Despite decades of study, little is known about the neural substrates involved in this disorder. In this case study, MRI images of the brain were obtained during a speech task for an American English-speaking monolingual female who presented with FAS of unknown etiology and was thought to sound 'Swedish' or 'Eastern European'. On the basis of MR structural imaging, the patient was noted to have frontal lobe atrophy. An fMRI picture-naming task designed to broadly engage the speech motor network revealed predominantly left-hemisphere involvement, including activation of the (1) left superior temporal and medial frontal structures, (2) bilateral subcortical structures and thalamus, and (3) left cerebellum. The results suggest an instance of substantial brain reorganization for speech motor control.

Many veterans chronically ill from the 1991 Gulf War exhibit symptoms of altered sensation, including chronic pain. In this study of 55 veterans of a Construction Battalion previously examined in 1995-1996 and 1997-1998, brain activation to innocuous and noxious heat stimuli was assessed in 2008-2009 with a quantitative sensory testing fMRI protocol in control veterans and groups representing three syndrome variants. Testing outside the scanner revealed no significant differences in warm detection or heat pain threshold among the four groups. In the fMRI study, Syndrome 1 and Syndrome 2, but not Syndrome 3, exhibited hypo-activation to innocuous heat and hyper-activation to noxious heat stimuli compared to controls. The results indicate abnormal central processing of sensory and painful stimuli in 2 of 3 variants of Gulf War illness and call for a more comprehensive study with a larger, representative sample of veterans., (Copyright © 2012 Elsevier Inc. All rights reserved.)

Resting state fluctuations in blood oxygenation level dependent functional connectivity magnetic resonance imaging (BOLD fcMRI) time-series have been increasingly employed to study functional connectivity networks in healthy and diseased brain. FcMRI studies have been conducted under a number of different conditions, including resting eyes open, visual fixation and finger tapping. BOLD fcMRI networks are believed to reflect both anatomically constrained spontaneous fluctuations and state-dependent activity. In this study, state-dependence of functional connectivity to dorsal and ventral striatum was assessed with fcMRI during an eyes open resting state condition (REST) and during continuous 3 Hz transcutaneous electrical nerve stimulation (TENS), with the a priori hypotheses: (1) dorsal striatum connectivity with sensorimotor/attention networks will be stronger during TENS compared to REST, (2) ventral striatum connectivity with limbic system emotion-processing network will be weaker during TENS compared to REST and (3) ventral striatum connectivity with sensorimotor/attention networks will be stronger during TENS compared to REST. These hypotheses were confirmed by the results obtained, indicating that resting state BOLD fMRI networks reflect, in substantial measure, state-dependent activity., (Copyright © 2010 Elsevier Inc. All rights reserved.)

Task-correlated motion artifacts that occur during functional magnetic resonance imaging can be mistaken for brain activity. In this work, a new selective detrending method for reduction of artifacts associated with task-correlated motion (TCM) during speech in event-related functional magnetic resonance imaging is introduced and demonstrated in an overt word generation paradigm. The performance of this new method is compared with that of three existing methods for reducing artifacts because of TCM: (1) motion parameter regression, (2) ignoring images during speech, and (3) detrending time course datasets of signal components related to TCM (deduced from artifact corrupted voxels). The selective detrending method outperforms the other three methods in reducing TCM artifacts and in retaining blood oxygenation level dependent signal., (2008 Wiley-Liss, Inc.)

Recent findings suggest that neural representations of semantic knowledge contain information about category, modality, and attributes. Although an object's category is defined according to shared attributes that uniquely distinguish it from other category members, a clear dissociation between visual attribute and category representation has not yet been reported. We investigated the contribution of category (living and nonliving) and visual attribute (global form and local details) to semantic representation in the fusiform gyrus. During functional magnetic resonance imaging (fMRI), 40 adults named pictures of animals, tools, and vehicles. In a preliminary study, identification of objects in these categories was differentially dependent on global versus local visual feature processing. fMRI findings indicate that activation in the lateral and medial regions of the fusiform gyrus distinguished stimuli according to category, that is, living versus nonliving, respectively. In contrast, visual attributes of global form (animals) were associated with higher activity in the right fusiform gyrus, while local details (tools) were associated with higher activity in the left fusiform gyrus. When both global and local attributes were relevant to processing (vehicles), cortex in both left and right medial fusiform gyri was more active than for other categories. Taken together, results support distinctions in the role of visual attributes and category in semantic representation.

Accurate segmentation of different brain tissues is of much importance in magnetic resonance imaging. This paper presents a comparison of the existing segmentation algorithms that are deployed in the neuroimaging community as part of two widely used software packages. The results obtained in this comparison can be used to select the appropriate segmentation algorithm for the neuroimaging application of interest. In addition to the entire brain area, a comparison is carried out for the subcortical region of the brain in terms of its gray matter composition.

Functional localization is a concept which involves the application of a sequence of geometrical and statistical image processing operations in order to define the location of brain activity or to produce functional/parametric maps with respect to the brain structure or anatomy. Considering that functional brain images do not normally convey detailed structural information and, thus, do not present an anatomically specific localization of functional activity, various image registration techniques are introduced in the literature for the purpose of mapping functional activity into an anatomical image or a brain atlas. The problems addressed by these techniques differ depending on the application and the type of analysis, i.e., single-subject versus group analysis. Functional to anatomical brain image registration is the core part of functional localization in most applications and is accompanied by intersubject and subject-to-atlas registration for group analysis studies. Cortical surface registration and automatic brain labeling are some of the other tools towards establishing a fully automatic functional localization procedure. While several previous survey papers have reviewed and classified general-purpose medical image registration techniques, this paper provides an overview of brain functional localization along with a survey and classification of the image registration techniques related to this problem.

Functional magnetic resonance imaging (fMRI) in humans has revealed increases in brain activity associated with various mental activities that are task-dependent. However, changes in brain activity have been dependent on baseline as well as experimental tasks. In the present study, fMRI was applied to investigate the most appropriate baseline task, picture naming or passive viewing of nonsense objects, to isolate syntactic processes related to 14.7-s blocks of silent sentence generation in 10 neurologically normal adults. The aim of this comparison was to determine the most suitable baseline task for the purpose of elucidating changes in the neural substrates of sentence generation following therapy for syntax production problems. Use of naming but not passive object viewing as a baseline task obscured activity in Broca's area, a region previously shown to be involved in syntactic processing. These results suggest that passive viewing of nonsense objects serves as a more appropriate baseline comparison than object naming for investigating sentence processing.

The localization of brain functional activity with respect to brain anatomy requires registration between a functional image and a reference high-resolution anatomical image. The fast functional magnetic resonance brain images acquired via echo planar imaging (EPI) in functional magnetic resonance imaging (fMRI) suffer from local geometric distortions. After performing standard rigid or affine registration, local nonlinear distortions of up to 10 mm still appear in prefrontal and orbitofrontal cortex, as well as in temporal and cerebellar regions. To reduce such distortions, an enhanced version of a previously developed deformable registration technique is introduced in this paper. The enhanced deformable registration technique involves a multistage mutual information-based free-form deformable framework guided by a field map template. This template is utilized as prior knowledge for performing an initial warp as well as a guiding mechanism to constrain the initial stage of the deformable registration. The enhanced technique is cross-validated with the high-resolution field map distortion correction technique using real datasets. The results from consistency tests using a normalized mutual information similarity measure as well as the statistics of quantitative cross-validation show the degree of enhancement achieved and the impact of the developed deformable registration in applications requiring accurate local registration. [ABSTRACT FROM PUBLISHER]