Advances in functional neuroanatomy: a review of combined DTI and fMRI studies in healthy younger and older adults

Neural adaptations in short-term learning of sign language revealed by fMRI and DTI

While vocal articulation is a unique feature of spoken languages, signed languages use facial expressions and hand movements for communication. Despite this substantial difference, neuroimaging studies show that spoken and sign language rely on similar areas of the brain in the frontal and parietal regions. However, little is known about the specific roles of these areas and how early they get involved. In the present study, we investigate the impact of short-term training-related changes in learners of British sign language (BSL). Pre- and post-training functional magnetic resonance imaging (fMRI) and diffusion tensor imaging scans were taken from twenty-six right-handed healthy volunteers. During the training course, participants were taught to discriminate and sign basic sentences using BSL for three consecutive days (1 h per day). fMRI results show increasing brain activity in the right cerebellum and cerebral brain areas including bilateral middle temporal gyrus, left angular gyrus, left middle and inferior frontal gyrus. Moreover, functional connectivity increased significantly after training between these areas. Microstructural findings show significant mean diffusivity and radial diffusivity reductions in the left angular gyrus, which are significantly correlated with behavioural improvement. These results reveal a high degree of similarity in the neural activity underlying signed and spoken languages. The rapid microstructural changes, identify the left angular gyrus as a structure that rapidly adapts to newly learnt visual-semantic associations.

Individualized post-operative prediction of cochlear implantation outcomes in children with prelingual deafness using functional near-infrared spectroscopy

Objective

The goal of this study was to develop an objective measure and predictor of cochlear implantation (CI) outcomes using functional near-infrared spectroscopy (fNIRS) for young children with prelingual deafness.

Methods

Sound-evoked hemodynamic responses were recorded from auditory and language-related cortical regions of 47 child CI recipients (35.47 ± 17.24 months of age) using fNIRS shortly after CI activation (0.26 ± 0.30 months). There were four sound conditions (natural speech, instrumental music, multi-speaker babble noise, and speech-in-noise). Post-CI auditory and verbal communication performance was evaluated using clinical questionnaires with caretakers. Both classification and individualized regression models were constructed to predict post-CI behavioral improvement from fNIRS data using support vector machine (SVM) learning algorithms.

Results

Auditory cortical responses shortly after CI hearing onset yielded highly accurate prediction of behavioral development in young CI children. For classification models, optimal prediction was achieved using cortical responses to two or more sound conditions, with the highest accuracy of 98.20% (precision = 98.17%, sensitivity = 98.96%, area under the curve of the receiver operating characteristic curve = 99.61%) obtained with the combination of speech, noise, and music stimuli. Similarly, for regression models, best prediction of individual development was achieved using three (highest r = 0.919) or four (r = 0.966) sound conditions. The predictability of cortical responses far outperformed (Cohen's d: 18.56) that of the collection of audiological and demographic parameters (classification accuracy: 0.62) under the same SVM algorithms and could not benefit from the inclusion of the latter.

Conclusion

Machine learning models using auditory cortical hemodynamic responses shortly after CI activation were able to predict individualized post-CI behavioral improvement in children with prelingual deafness.

Level of Evidence

Level 5.

Brain Function and Structure Changes in the Prognosis Prediction of Prolonged Disorders of Consciousness

OBJECTIVES

To observe the functional differences in the key brain areas in patients with different levels of consciousness after severe brain injury, and provide reference for confirming the objective diagnosis indicators for prolonged disorders of consciousness (pDoCs).

METHODS

This prospective study enrolled patients with pDoCs hospitalized in the department of rehabilitation medicine of our Hospital. Levels of consciousness and clinical outcomes were assessed according to diagnostic criteria and behavioral scales. Resting-state functional magnetic resonance imaging (rs-fMRI) and diffusion tensor imaging (DTI) of 30 patients with different levels of consciousness was performed. The patients were grouped as conscious or unconscious according to whether they regained consciousness during the 12-month follow-up.

RESULTS

Thirty patients were enrolled, including eight with unresponsive wakefulness syndrome/vegetative state, eight with minimally conscious state, six with emergence from the minimally conscious state, and eight with a locked-in syndrome. There were 19 and 11 patients in the conscious and unconscious groups. Compared with the unconscious group, the left basal nucleus was activated in the conscious group, and there were significant differences in white matter fiber bundles. Correlations were observed between the regional homogeneity (ReHo) value of the cerebellum and the Glasgow coma scale score (r = 0.387, P = 0.038) and between the ReHo value of the left temporal and the coma recovery scale-revised score (r = 0.394, P = 0.035).

CONCLUSIONS

The left insula and cerebellum might be important for regaining consciousness. The brain function activity and structural remodeling of the key brain regions and the activation level of the cerebellum are correlated with clinical behaviors and have potential application value for the prognosis prediction of pDoCs patients.

Characterizing the Neurobiological Mechanisms of Action of Exercise and Cognitive-Behavioral Interventions for Rheumatoid Arthritis Fatigue: A Magnetic Resonance Imaging Brain Study

OBJECTIVE

Chronic fatigue is a major clinical unmet need among patients with rheumatoid arthritis (RA). Current therapies are limited to nonpharmacological interventions, such as personalized exercise programs (PEPs) and cognitive-behavioral approaches (CBAs); however, most patients still continue to report severe fatigue. To inform more effective therapies, we conducted a magnetic resonance imaging (MRI) brain study of PEPs and CBAs, nested within a randomized controlled trial (RCT), to identify their neurobiological mechanisms of fatigue reduction in RA.

METHODS

A subgroup of patients with RA (n = 90), participating in an RCT of PEPs and CBAs for fatigue, undertook a multimodal MRI brain scan following randomization to either usual care (UC) alone or in addition to PEPs and CBAs and again after the intervention (six months). Brain regional volumetric, functional, and structural connectivity indices were curated and then computed employing a causal analysis framework. The primary outcome was fatigue improvement (Chalder fatigue scale).

RESULTS

Several structural and functional connections were identified as mediators of fatigue improvement in both PEPs and CBAs compared to UC. PEPs had a more pronounced effect on functional connectivity than CBAs; however, structural connectivity between the left isthmus cingulate cortex (L-ICC) and left paracentral lobule (L-PCL) was shared, and the size of mediation effect ranked highly for both PEPs and CBAs (ßAverage = -0.46, SD 0.61; ßAverage = -0.32, SD 0.47, respectively).

CONCLUSION

The structural connection between the L-ICC and L-PCL appears to be a dominant mechanism for how both PEPs and CBAs reduce fatigue among patients with RA. This supports its potential as a substrate of fatigue neurobiology and a putative candidate for future targeting.

Detecting microstructural alterations of cerebral white matter associated with breast cancer and chemotherapy revealed by generalized q-sampling MRI

Objective

Previous studies have discussed the impact of chemotherapy on the brain microstructure. There is no evidence of the impact regarding cancer-related psychiatric comorbidity on cancer survivors. We aimed to evaluate the impact of both chemotherapy and mental health problem on brain microstructural alterations and consequent cognitive dysfunction in breast cancer survivors.

Methods

In this cross-sectional study conducted in a tertiary center, data from 125 female breast cancer survivors who had not received chemotherapy (BB = 65; 49.86 ± 8.23 years) and had received chemotherapy (BA = 60; 49.82 ± 7.89 years) as well as from 71 age-matched healthy controls (47.18 ± 8.08 years) was collected. Chemotherapeutic agents used were docetaxel and epirubicin. We used neuropsychological testing and questionnaire to evaluate psychiatric comorbidity, cognitive dysfunction as well as generalized sampling imaging (GQI) and graph theoretical analysis (GTA) to detect microstructural alterations in the brain.

Findings

Cross-comparison between groups revealed that neurotoxicity caused by chemotherapy and cancer-related psychiatric comorbidity may affect the corpus callosum and middle frontal gyrus. In addition, GQI indices were correlated with the testing scores of cognitive function, quality of life, anxiety, and depression. Furthermore, weaker connections between brain regions and lower segregated ability were found in the post-treatment group.

Conclusion

This study suggests that chemotherapy and cancer-related mental health problem both play an important role in the development of white matter alterations and cognitive dysfunction.

Is structural connectivity different in child and adolescent relatives of patients with bipolar disorder? A narrative review according to studies with DTI

INTRODUCTION

Bipolar disorder (BD) has been associated with a decrease in white matter integrity. Diffusion tensor imaging (DTI) studies have enabled these changes to be elucidated with higher quality. Due to BD's high heritability, some studies have been conducted in relatives of BD patients looking at white matter integrity, and have found that structural connectivity may also be affected. This alteration has been proposed as a potential BD biomarker of vulnerability. However, there are few studies in children and adolescents.

OBJECTIVE

To conduct a review of the literature on changes in white matter integrity determined by DTI in high-risk children and adolescents.

RESULTS

Brain structural connectivity in the paediatric population is described in studies using DTI. Changes in the myelination process from its evolution within normal neurodevelopment to the findings in fractional anisotropy (FA) in BD patients and their high-risk relatives are also described.

CONCLUSIONS

Studies show that both BD patients and their at-risk relatives present a decrease in FA in specific brain regions. Studies in children and adolescents with a high risk of BD, indicate a reduced FA in axonal tracts involved in emotional and cognitive functions. Decreased FA can be considered as a vulnerability biomarker for BD.

Progressive brain abnormalities in schizophrenia across different illness periods: a structural and functional MRI study

Schizophrenia is a chronic brain disorder, and neuroimaging abnormalities have been reported in different stages of the illness for decades. However, when and how these brain abnormalities occur and evolve remains undetermined. We hypothesized structural and functional brain abnormalities progress throughout the illness course at different rates in schizophrenia. A total of 115 patients with schizophrenia were recruited and stratified into three groups of different illness periods: 5-year group (illness duration: ≤5 years), 15-year group (illness duration: 12-18 years), and 25-year group (illness duration: ≥25 years); 230 healthy controls were matched by age and sex to the three groups, respectively. All participants underwent resting-state MRI scanning. Each group of patients with schizophrenia was compared with the corresponding controls in terms of voxel-based morphometry (VBM), fractional anisotropy (FA), global functional connectivity density (gFCD), and sample entropy (SampEn) abnormalities. In the 5-year group we observed only SampEn abnormalities in the putamen. In the 15-year group, we observed VBM abnormalities in the insula and cingulate gyrus and gFCD abnormalities in the temporal cortex. In the 25-year group, we observed FA abnormalities in nearly all white matter tracts, and additional VBM and gFCD abnormalities in the frontal cortex and cerebellum. By using two structural and two functional MRI analysis methods, we demonstrated that individual functional abnormalities occur in limited brain areas initially, functional connectivity and gray matter density abnormalities ensue later in wider brain areas, and structural connectivity abnormalities involving almost all white matter tracts emerge in the third decade of the course in schizophrenia.

25 years of neurocognitive aging theories: What have we learned?

The past 25 years have provided a rich discovery of at least four fundamental patterns that represent structural and functional brain aging across multiple cognitive domains. Of the many potential patterns of brain aging, few are ever examined simultaneously in a given study, leading one to question their mutual exclusivity. Moreover, more studies are emerging that note failures to replicate some brain aging patterns, thereby questioning the universality and prevalence of these patterns. Although some attempts have been made to create unifying theories incorporating many of these age-related brain patterns, we propose that the field’s understanding of the aging brain has been hindered due to a large number of influential models with little crosstalk between them. We briefly review these brain patterns, the influential domain-general theories of neurocognitive aging that attempt to explain them, and provide examples of recent challenges to these theories. Lastly, we elaborate on improvements that can be made to lead the field to more comprehensive and robust models of neurocognitive aging.

Applying multilayer analysis to morphological, structural, and functional brain networks to identify relevant dysfunction patterns

In recent years, research on network analysis applied to MRI data has advanced significantly. However, the majority of the studies are limited to single networks obtained from resting-state fMRI, diffusion MRI, or gray matter probability maps derived from T1 images. Although a limited number of previous studies have combined two of these networks, none have introduced a framework to combine morphological, structural, and functional brain connectivity networks. The aim of this study was to combine the morphological, structural, and functional information, thus defining a new multilayer network perspective. This has proved advantageous when jointly analyzing multiple types of relational data from the same objects simultaneously using graph- mining techniques. The main contribution of this research is the design, development, and validation of a framework that merges these three layers of information into one multilayer network that links and relates the integrity of white matter connections with gray matter probability maps and resting-state fMRI. To validate our framework, several metrics from graph theory are expanded and adapted to our specific domain characteristics. This proof of concept was applied to a cohort of people with multiple sclerosis, and results show that several brain regions with a synchronized connectivity deterioration could be identified.

Altered linear coupling between stimulus-evoked blood flow and oxygen metabolism in the aging human brain

Neural-vascular coupling (NVC) is the process by which oxygen and nutrients are delivered to metabolically active neurons by blood vessels. Murine models of NVC disruption have revealed its critical role in healthy neural function. We hypothesized that, in humans, aging exerts detrimental effects upon the integrity of the neural-glial-vascular system that underlies NVC. To test this hypothesis, calibrated functional magnetic resonance imaging (cfMRI) was used to characterize age-related changes in cerebral blood flow (CBF) and oxygen metabolism during visual cortex stimulation. Thirty-three younger and 27 older participants underwent cfMRI scanning during both an attention-controlled visual stimulation task and a hypercapnia paradigm used to calibrate the blood-oxygen-level-dependent signal. Measurement of stimulus-evoked blood flow and oxygen metabolism permitted calculation of the NVC ratio to assess the integrity of neural-vascular communication. Consistent with our hypothesis, we observed monotonic NVC ratio increases with increasing visual stimulation frequency in younger adults but not in older adults. Age-related changes in stimulus-evoked cerebrovascular and neurometabolic signal could not fully explain this disruption; increases in stimulus-evoked neurometabolic activity elicited corresponding increases in stimulus-evoked CBF in younger but not in older adults. These results implicate age-related, demand-dependent failures of the neural-glial-vascular structures that comprise the NVC system.

Overview of (f)MRI Studies of Cognitive Aging for Non-Experts: Looking through the Lens of Neuroimaging

This special issue concerning Brain Functional and Structural Connectivity and Cognition aims to expand our understanding of brain connectivity. Herein, I review related topics including the principle and concepts of functional MRI, brain activation, and functional/structural connectivity in aging for uninitiated readers. Visuospatial attention, one of the well-studied functions in aging, is discussed from the perspective of neuroimaging.

Brain Structural and Functional Connectivity: A Review of Combined Works of Diffusion Magnetic Resonance Imaging and Electro-Encephalography

Implications of structural connections within and between brain regions for their functional counterpart are timely points of discussion. White matter microstructural organization and functional activity can be assessed in unison. At first glance, however, the corresponding findings appear variable, both in the healthy brain and in numerous neuro-pathologies. To identify consistent associations between structural and functional connectivity and possible impacts for the clinic, we reviewed the literature of combined recordings of electro-encephalography (EEG) and diffusion-based magnetic resonance imaging (MRI). It appears that the strength of event-related EEG activity increases with increased integrity of structural connectivity, while latency drops. This agrees with a simple mechanistic perspective: the nature of microstructural white matter influences the transfer of activity. The EEG, however, is often assessed for its spectral content. Spectral power shows associations with structural connectivity that can be negative or positive often dependent on the frequencies under study. Functional connectivity shows even more variations, which are difficult to rank. This might be caused by the diversity of paradigms being investigated, from sleep and resting state to cognitive and motor tasks, from healthy participants to patients. More challenging, though, is the potential dependency of findings on the kind of analysis applied. While this does not diminish the principal capacity of EEG and diffusion-based MRI co-registration, it highlights the urgency to standardize especially EEG analysis.

The longitudinal relationship between BOLD signal variability changes and white matter maturation during early childhood

Intra-individual transient temporal fluctuations in brain signal, as measured by fMRI blood oxygenation level dependent (BOLD) variability, is increasingly considered an important signal rather than measurement noise. Evidence from computational and cognitive neuroscience suggests that signal variability is a good proxy-measure of brain functional integrity and information processing capacity. Here, we sought to explore across-participant and longitudinal relationships between BOLD variability, age, and white matter structure in early childhood. We measured standard deviation of BOLD signal, total white matter volume, global fractional anisotropy (FA) and mean diffusivity (MD) during passive movie viewing in a sample of healthy children (aged 2-8 years; N = 83). We investigated how age and white matter development related to changes in BOLD variability both across- and within-participants. Our across-participant analyses using behavioural partial least squares (bPLS) revealed that the influence of age and white matter maturation on BOLD variability was highly interrelated. BOLD variability increased in widespread frontal, temporal and parietal regions, and decreased in the hippocampus and parahippocampal gyrus with age and white matter development. Our longitudinal analyses using linear mixed effects modelling revealed significant associations between BOLD variability, age and white matter microstructure. Analyses using artificial neural networks demonstrated that BOLD variability and white matter micro and macro-structure at earlier ages were strong predictors of BOLD variability at later ages. By characterizing the across-participant and longitudinal features of the association between BOLD variability and white matter micro- and macrostructure in early childhood, our results provide a novel perspective to understand structure-function relationships in the developing brain.

Estimates of brain age for gray matter and white matter in younger and older adults: Insights into human intelligence

Aging entails a multifaceted complex of changes in macro- and micro-structural properties of human brain gray matter (GM) and white matter (WM) tissues, as well as in intellectual abilities. To better capture tissue-specific brain aging, we combined volume and distribution properties of diffusivity indices to derive subject-specific age scores for each tissue. We compared age-related variance between younger and older adults for GM and WM age scores, and tested whether tissue-specific age scores could explain different effects of aging on fluid (Gf) and crystalized (Gc) intelligence in younger and older adults. Chronological age was strongly associated with GM (R2 = 0.73) and WM (R2 = 0.57) age scores. The GM age score accounted for significantly more variance in chronological age in younger relative to older adults (p < 0.001), whereas the WM age score accounted for significantly more variance in chronological age in older compared to younger adults (p < 0.025). Consistent with existing literature, younger adults outperformed older adults in Gf while older adults outperformed younger adults in Gc. The GM age score was negatively associated with Gf in younger adults (p < 0.02), whereas the WM age score was negatively associated with Gc in older adults (p < 0.02). Our results provide evidence for differences in the effects of age on GM and WM in younger versus older adults that may contribute to age-related differences in Gf and Gc.

Age-related changes in cerebrovascular health and their effects on neural function and cognition: A comprehensive review

The process of aging includes changes in cellular biology that affect local interactions between cells and their environments and eventually propagate to systemic levels. In the brain, where neurons critically depend on an efficient and dynamic supply of oxygen and glucose, age-related changes in the complex interaction between the brain parenchyma and the cerebrovasculature have effects on health and functioning that negatively impact cognition and play a role in pathology. Thus, cerebrovascular health is considered one of the main mechanisms by which a healthy lifestyle, such as habitual cardiorespiratory exercise and a healthful diet, could lead to improved cognitive outcomes with aging. This review aims at detailing how the physiology of the cerebral vascular system changes with age and how these changes lead to differential trajectories of cognitive maintenance or decline. This provides a framework for generating specific mechanistic hypotheses about the efficacy of proposed interventions and lifestyle covariates that contribute to enhanced cognitive well-being. Finally, we discuss the methodological implications of age-related changes in the cerebral vasculature for human cognitive neuroscience research and propose directions for future experiments aimed at investigating age-related changes in the relationship between physiology and cognitive mechanisms.

Is Structural Connectivity Different in Child and Adolescent Relatives of Patients with Bipolar Disorder? A Narrative Review According to Studies with DTI

INTRODUCTION

Bipolar disorder (BD) has been associated with a decrease in white matter integrity. Diffusion tensor imaging (DTI) studies have enabled these changes to be elucidated with higher quality. Due to BD's high heritability, some studies have been conducted in relatives of BD patients looking at white matter integrity, and have found that structural connectivity may also be affected. This alteration has been proposed as a potential BD biomarker of vulnerability. However, there are few studies in children and adolescents.

OBJECTIVE

To conduct a review of the literature on changes in white matter integrity determined by DTI in high-risk children and adolescents.

RESULTS

Brain structural connectivity in the paediatric population is described in studies using DTI. Changes in the myelination process from its evolution within normal neurodevelopment to the findings in fractional anisotropy (FA) in BD patients and their high-risk relatives are also described.

CONCLUSIONS

Studies show that both BD patients and their at-risk relatives present a decrease in FA in specific brain regions. Studies in children and adolescents with a high risk of BD, indicate a reduced FA in axonal tracts involved in emotional and cognitive functions. Decreased FA can be considered as a vulnerability biomarker for BD.

Compensation of Ipsilateral Motor and Sensory Functions by Contralateral Uncrossed Pathway in a Stroke Patient With Half Brain

ABSTRACT

This study reports a case of motor and sensory function recovery after massive left cerebral infarction in a young man, along with preserved function of the injured hemisphere. He received early rehabilitation therapy in a nerval care unit within 1 wk of surgery, and the rehabilitation lasted for more than 3 yrs. When he gradually recovered from coma, his motor, sensory, and speech functions improved significantly. Two years later, he was able to live independently and returned to work. The findings of functional magnetic resonance imaging, diffusion tensor imaging, somatosensory evoked potential, and motor evoked potential confirmed that there was a strong connection between his right brain and the right limbs. Thus, early rehabilitation is a promising approach for restoring motor and sensory function after massive brain injury or extensive brain tissue damage.

Relationship between the disrupted topological efficiency of the structural brain connectome and glucose hypometabolism in normal aging

Normal aging is accompanied by structural degeneration and glucose hypometabolism in the human brain. However, the relationship between structural network disconnections and hypometabolism in normal aging remains largely unknown. In the present study, by combining MRI and PET techniques, we investigated the metabolic mechanism of the structural brain connectome and its relationship with normal aging in a cross-sectional, community-based cohort of 42 cognitively normal elderly individuals aged 57-84 years. The structural connectome was constructed based on diffusion MRI tractography, and the network efficiency metrics were quantified using graph theory analyses. FDG-PET scanning was performed to evaluate the glucose metabolic level in the cortical regions of the individuals. The results of this study demonstrated that both network efficiency and cortical metabolism decrease with age (both p < 0.05). In the subregions of the bilateral thalamus, significant correlations between nodal efficiency and cortical metabolism could be observed across subjects. Individual-level analyses indicated that brain regions with higher nodal efficiency tend to exhibit higher metabolic levels, implying a tight coupling between nodal efficiency and glucose metabolism (r = 0.56, p = 1.15 × 10^-21). Moreover, efficiency-metabolism coupling coefficient significantly increased with age (r = 0.44, p = 0.0046). Finally, the main findings were also reproducible in the ADNI dataset. Together, our results demonstrate a close coupling between structural brain connectivity and cortical metabolism in normal elderly individuals and provide new insight that improve the present understanding of the metabolic mechanisms of structural brain disconnections in normal aging.

Concordance in parent and offspring cortico-basal ganglia white matter connectivity varies by parental history of major depressive disorder and early parental care

Social behavior is transmitted cross-generationally through coordinated behavior within attachment bonds. Parental depression and poor parental care are major risks for disruptions of such coordination and are associated with offspring's psychopathology and interpersonal dysfunction. Given the key role of the cortico-basal ganglia (CBG) circuits in social communication, we examined similarities (concordance) of parent-offspring CBG white matter (WM) connections and how parental history of major depressive disorder (MDD) and early parental care moderate these similarities. We imaged 44 parent-offspring dyads and investigated WM connections between basal-ganglia seeds and selected regions in temporal cortex using diffusion tensor imaging (DTI) tractography. We found significant concordance in parent-offspring strength of CBG WM connections, moderated by parental lifetime-MDD and care. The results showed diminished neural concordance among dyads with a depressed parent and that better parental care predicted greater concordance, which also provided a protective buffer against attenuated concordance among dyads with a depressed parent. Our findings provide the first neurobiological evidence of concordance between parents-offspring in WM tracts and that concordance is diminished in families where parents have lifetime-MDD. This disruption may be a risk factor for intergenerational transmission of psychopathology. Findings emphasize the long-term role of early caregiving in shaping the neural concordance among at-risk and affected dyads.

White Matter Differences in Networks in Elders with Mild Cognitive Impairment and Alzheimer's Disease

Background: Alzheimer's disease (AD) is associated with impairment of large-scale brain networks, disruption in structural connections, and functional disconnection between distant brain regions. Although decreased functional connectivity has been thoroughly investigated and reported by existing functional neuroimaging literature, this study investigated network-based differences due to the structural changes in white matter pathways in AD patients. We hypothesize that diffusion metrics of disrupted tracts that go through cognitive networks related with intrinsic awareness, motor movement, and executive control can be utilized as biomarkers to distinguish prodromal stage from AD stage. Methods: Diffusion MRI data of a total 154 subjects, including patients with clinical AD (n = 47) and patients with mild cognitive impairment (MCI) (n = 107) was used. To study structural changes associated with white matter fiber pathways voxel-averaged diffusion metrics and fiber density metrics were calculated. Results: Study revealed that AD patients exhibit disruptions in intrahemispheric tracts and projection fiber tracts as suggested by diffusion indices. Our whole brain analysis revealed that network differences within default mode network (DMN), sensory motor network, and frontoparietal networks are associated with disruption in inferior fronto-occipital fasciculus (IFOF), corticospinal tract, and superior longitudinal fasciculus. Global function revealed by Mini Mental State Examination correlate with those fiber pathways that form reciprocal connections within networks associated with motor movement and executive control. Conclusion: Diffusion metrics appear to be more sensitive than fiber density metrics in differentiating the structural changes in the white matter. Decreased fractional anisotropy along with increased mean diffusivity and radial diffusivity in forceps minor, corticospinal tract, and IFOF as an imaging biomarker would be ideal to distinguish AD patients from MCI patients. Difference of DMN, sensory motor network, and frontal parietal network in our study reveals that AD patients may suffer from poor motor movement and degraded executive control.

Frontostriatal white matter connectivity: age differences and associations with cognition and BOLD modulation

Despite the importance of cortico-striatal circuits to cognition, investigation of age effects on the structural circuitry connecting these regions is limited. The current study examined age effects on frontostriatal white matter connectivity, and identified associations with both executive function performance and dynamic modulation of blood-oxygen-level-dependent (BOLD) activation to task difficulty in a lifespan sample of 169 healthy humans aged 20-94 years. Greater frontostriatal diffusivity was associated with poorer executive function and this negative association strengthened with increasing age. Whole-brain functional magnetic resonance imaging (fMRI) analyses additionally indicated an association between frontostriatal mean diffusivity and BOLD modulation to difficulty selectively in the striatum across 2 independent fMRI tasks. This association was moderated by age, such that younger- and middle-aged individuals showed reduced dynamic range of difficulty modulation as a function of increasing frontostriatal diffusivity. Together these results demonstrate the importance of age-related degradation of frontostriatal circuitry on executive functioning across the lifespan, and highlight the need to capture brain changes occurring in early-to middle-adulthood.

White Matter Microstructure Predicts Focal and Broad Functional Brain Dedifferentiation in Normal Aging

Ventral visual cortex exhibits highly organized and selective patterns of functional activity associated with visual processing. However, this specialization decreases in normal aging, with functional responses to different visual stimuli becoming more similar with age, a phenomenon termed "dedifferentiation." The current study tested the hypothesis that age-related degradation of the inferior longitudinal fasciculus (ILF), a white matter pathway involved in visual perception, could account for dedifferentiation of both localized and distributed brain activity in ventral visual cortex. Participants included 281 adults, ages 20-89 years, from the Dallas Lifespan Brain Study who underwent diffusion-weighted imaging to measure white matter diffusivity, as well as fMRI to measure functional selectivity to viewing photographs from different categories (e.g., faces, houses). In general, decreased ILF anisotropy significantly predicted both focal and broad functional dedifferentiation. Specifically, there was a localized effect of structure on function, such that decreased anisotropy in a smaller mid-fusiform region of ILF predicted less selective (i.e., more dedifferentiated) response to viewing faces in a proximal face-responsive region of fusiform. On the other hand, the whole ILF predicted less selective response across broader ventral visual cortex for viewing animate (e.g., human faces, animals) versus inanimate (e.g., houses, chairs) images. This structure-function relationship became weaker with age and was no longer significant after the age of 70 years. These findings indicate that decreased white matter anisotropy is associated with maladaptive differences in proximal brain function and is an important variable to consider when interpreting age differences in functional selectivity.

Contributions of White Matter Connectivity and BOLD Modulation to Cognitive Aging: A Lifespan Structure-Function Association Study

The ability to flexibly modulate brain activation to increasing cognitive challenge decreases with aging. This age-related decrease in dynamic range of function of regional gray matter may be, in part, due to age-related degradation of regional white matter tracts. Here, a lifespan sample of 171 healthy adults (aged 20-94) underwent magnetic resonance imaging (MRI) scanning including diffusion-weighted imaging (for tractography) and functional imaging (a digit n-back task). We utilized structural equation modeling to test the hypothesis that age-related decrements in white matter microstructure are associated with altered blood-oxygen-level-dependent (BOLD) modulation, and both in turn, are associated with scanner-task accuracy and executive function performance. Specified structural equation model evidenced good fit, demonstrating that increased age negatively affects n-back task accuracy and executive function performance in part due to both degraded white matter tract microstructure and reduced task-difficulty-related BOLD modulation. We further demonstrated that poorer white matter microstructure integrity was associated with weakened BOLD modulation, particularly in regions showing positive modulation effects, as opposed to negative modulation effects. This structure-function association study provides further evidence that structural connectivity influences functional activation, and the two mechanisms in tandem are predictive of cognitive performance, both during the task, and for cognition measured outside the scanner environment.

Fractional Anisotropy of Thalamic Nuclei Is Associated With Verticality Misperception After Extra-Thalamic Stroke

Verticality misperception after stroke is a frequent neurological deficit that leads to postural imbalance and a higher risk of falls. The posterior thalamic nuclei are described to be involved with verticality perception, but it is unknown if extra-thalamic lesions can have the same effect via diaschisis and degeneration of thalamic nuclei. We investigated the relationship between thalamic fractional anisotropy (FA, a proxy of structural integrity), and verticality perception, in patients after stroke with diverse encephalic extra-thalamic lesions. We included 11 first time post-stroke patients with extra-thalamic primary lesions, and compared their region-based FA to a group of 25 age-matched healthy controls. For the patient sample, correlation and regression analyses evaluated the relationship between thalamic nuclei FA and error of postural vertical (PV) and haptic vertical (HV) in the roll (PVroll/HVroll) and pitch planes (PVpitch/HVpitch). Relative to controls, patients showed decreased FA of anterior, ventral anterior, ventral posterior lateral, dorsal, and pulvinar thalamic nuclei, despite the primary lesions being extra-thalamic. We found a significant correlation between HVroll, and FA in the anterior and dorsal nuclei, and PVroll with FA in the anterior nucleus. FA in the anterior, ventral anterior, ventral posterior lateral, dorsal and pulvinar nuclei predicted PV, and FA in the ventral anterior, ventral posterior lateral and dorsal nuclei predicted HV. While prior studies indicate that primary lesions of the thalamus can result in verticality misperception, here we present evidence supporting that secondary degeneration of thalamic nuclei via diaschisis can also be associated with verticality misperception after stroke.

Intrinsic functional and structural connectivity of emotion regulation networks in obsessive-compulsive disorder

Despite emotion regulation being altered in patients with obsessive-compulsive disorder (OCD), no studies have investigated its relation to multimodal amygdala connectivity. We compared corticolimbic functional and structural connectivity between OCD patients and healthy controls (HCs), and correlated this with the dispositional use of emotion regulation strategies and with OCD severity. OCD patients (n = 73) and HCs (n = 42) were assessed for suppression and reappraisal strategies using the Emotion Regulation Questionnaire (ERQ) and for OCD severity using the Yale-Brown Obsessive-Compulsive Scale. Resting-state functional magnetic resonance imaging (rs-fMRI) connectivity maps were generated using subject-specific left amygdala (LA) and right amygdala (RA) masks. We identified between-group differences in amygdala whole-brain connectivity, and evaluated the moderating effect of ERQ strategies. Significant regions and amygdala seeds were used as targets in probabilistic tractography analysis. Patients scored higher in suppression and lower in reappraisal. We observed higher rs-fMRI RA-right postcentral gyrus (PCG) connectivity in HC, and in patients this was correlated with symptom severity. Reappraisal scores were associated with higher negative LA-left insula connectivity in HC, and suppression scores were negatively associated with LA-precuneus and angular gyri connectivity in OCD. Structurally, patients showed higher mean diffusivity in tracts connecting the amygdala with the other targets. RA-PCG connectivity is diminished in patients, while disrupted emotion regulation is related to altered amygdala connectivity with the insula and posterior brain regions. Our results are the first showing, from a multimodal perspective, the association between amygdala connectivity and specific emotional processing domains, emphasizing the importance of amygdala connectivity in OCD pathophysiology.

A Randomized Clinical Trial of a Functional Electrical Stimulation Mimic to Gait Promotes Motor Recovery and Brain Remodeling in Acute Stroke

Functional electrical stimulation can improve motor function after stroke. The mechanism may involve activity-dependent plasticity and brain remodeling. The aim of our study was to investigate the effectiveness of a patterned electrical stimulation FES mimic to gait in motor recovery among stroke survivors and to investigate possible mechanisms through brain fMRI. Forty-eight subjects were recruited and randomly assigned to a four-channel FES group (n = 18), a placebo group (n = 15), or a dual-channel FES group (n = 15). Stimulation lasted for 30 minutes in each session for 3 weeks. All of the subjects were assessed at baseline and after weeks 1, 2, and 3. The assessments included the Fugl-Meyer Assessment, the Postural Assessment Scale for Stroke Patients, Brunel's Balance Assessment, the Berg Balance Scale, and the modified Barthel Index. Brain fMRI were acquired before and after the intervention. All of the motor assessment scores significantly increased week by week in all the three groups. The four-channel group showed significantly better improvement than the dual-channel group and placebo groups. fMRI showed that fractional anisotropy was significantly increased in both the four-channel and dual-channel groups compared with the placebo group and fiber bundles had increased significantly on the ipsilateral side, but not on the contralateral side in the group given four-channel stimulation. In conclusion, when four-channel FES induces cycling movement of the lower extremities based on a gait pattern, it may be more effective in promoting motor recovery and induce more plastic changes and brain remodeling than two-channel stimulation. This trial is registered with clinical trial registration unique identifier ChiCTR-TRC-11001615.

The Relation Between White Matter Microstructure and Network Complexity: Implications for Processing Efficiency

Brain structure has been proposed to facilitate as well as constrain functional interactions within brain networks. Simulation models suggest that integrity of white matter (WM) microstructure should be positively related to the complexity of BOLD signal - a measure of network interactions. Using 121 young adults from the Human Connectome Project, we empirically tested whether greater WM integrity would be associated with greater complexity of the BOLD signal during rest via multiscale entropy. Multiscale entropy measures the lack of predictability within a given time series across varying time scales, thus being able to estimate fluctuating signal dynamics within brain networks. Using multivariate analysis techniques (Partial Least Squares), we found that greater WM integrity was associated with greater network complexity at fast time scales, but less network complexity at slower time scales. These findings implicate two separate pathways through which WM integrity affects brain function in the prefrontal cortex - an executive-prefrontal pathway and a perceptuo-occipital pathway. In two additional samples, the main patterns of WM and network complexity were replicated. These findings support simulation models of WM integrity and network complexity and provide new insights into brain structure-function relationships.

Performance Level and Cortical Atrophy Modulate the Neural Response to Increasing Working Memory Load in Younger and Older Adults

There is evidence that the neural response to increasing working memory (WM) load is modulated by age and performance level. For a valid interpretation of these effects, however, it is important to understand, whether and how they are related to gray matter atrophy. In the current work, we therefore used functional magnetic resonance imaging (fMRI) and voxel-based morphometry (VBM) to examine the association between age, performance level, spatial WM load-related brain activation and gray matter volume in 18 younger high-performers (YHP), 17 younger low-performers (YLP), 17 older high-performers (OHP), and 18 older low-performers (OLP). In multiple sub regions of the prefrontal cortex (PFC), load-related activation followed a linear trend with increasing activation at increasing load in all experimental groups. Results did not reveal differences between the sub groups. Older adults additionally showed a pattern of increasing activation from low to medium load but stable or even decreasing activation from medium to high load in other sub regions of the PFC (quadratic trend). Quadratic trend related brain activation was higher in older than in younger adults and in OLP compared to OHP. In OLP, quadratic trend related brain activation was negatively correlated with both performance accuracy and prefrontal gray matter volume. The results suggest an efficient upregulation of multiple PFC areas as response to increasing WM load in younger and older adults. Older adults and particularly OLP additionally show dysfunctional response patterns (i.e., enhanced quadratic trend related brain activation compared to younger adults and OHP, respectively) in other PFC clusters being associated with gray matter atrophy.

Compromised prefrontal structure and function are associated with slower walking in older adults

Our previous work demonstrates that reduced activation of the executive network is associated with slow walking speed in a cohort of older adults from the MOBILIZE Boston Study. However, the influence of underlying white matter integrity on the activation of this network and walking speed is unknown. Thus, we used diffusion-weighted imaging and fMRI during an n-back task to assess associations between executive network structure, function, and walking speed. Whole-brain tract-based spatial statistics (TBSS) were used to identify regions of white matter microstructural integrity that were associated with walking speed. The integrity of these regions was then entered into multiple regression models to predict task performance and executive network activation during the n-back task. Among the significant associations of FA with walking speed, we observed the anterior thalamic radiation and superior longitudinal fasciculus were further associated with both n-back response speed and executive network activation. These findings suggest that subtle damage to frontal white matter may contribute to altered executive network activation and slower walking in older adults.

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Older adult walking speed was not associated with white matter lesion burden.

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Walking speed was associated with microstructural white matter integrity.

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The integrity of prefrontal areas was associated with executive network activation.

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Low executive network activation also corresponded to slower walking.

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Interventions targeting the executive network may preserve older adult mobility.

Network specialization during adolescence: Hippocampal effective connectivity in boys and girls

Adolescence is a complex period of concurrent mental and physical development that facilitates adult functioning at multiple levels. Despite the growing number of neuroimaging studies of cognitive development in adolescence focusing on regional activation patterns, there remains a paucity of information about the functional interactions across these participating regions that are critical for cognitive functioning, including memory. The current study used structural equation modeling (SEM) to determine how interactions among brain regions critical for memory change over the course of adolescence. We obtained functional MRI in 77 individuals aged 8-16 years old, divided into younger (ages 8-10) and older (ages > 11) cohorts, using an incidental encoding memory task to activate hippocampus formation and associated brain networks, as well as behavioral data on memory function. SEM was performed on the imaging data for four groups (younger girls, younger boys, older girls, and older boys) that were subsequently compared using a stacked model approach. Significant differences were seen between the models for these groups. Younger boys had a predominantly posterior distribution of connections originating in primary visual regions and terminating on multi-modal processing regions. In older boys, there was a relatively greater anterior connection distribution, with increased effective connectivity within association and multi-modal processing regions. Connection patterns in younger girls were similar to those of older boys, with a generally anterior-posterior distributed network among sensory, multi-modal, and limbic regions. In contrast, connections in older girls were widely distributed but relatively weaker. Memory performance increased with age, without a significant difference between the sexes. These findings suggest a progressive reorganization among brain regions, with a commensurate increase in efficiency of cognitive functioning, from younger to older individuals in both girls and boys, providing insight into the age- and gender-specific processes at play during this critical transition period.

A neural network that links brain function, white-matter structure and risky behavior

The ability to evaluate the balance between risk and reward and to adjust behavior accordingly is fundamental to adaptive decision-making. Although brain-imaging studies consistently have shown involvement of the dorsolateral prefrontal cortex, anterior insula and striatum during risky decision-making, activation in a neural network formed by these regions has not been linked to structural connectivity. Therefore, in this study, white-matter connectivity was measured with diffusion-weighted imaging in 40 healthy research participants who performed the Balloon Analogue Risk Task, a test of risky decision-making, during fMRI. Fractional anisotropy within a network that includes white-matter pathways connecting four regions (the prefrontal cortex, insula and midbrain to the striatum) was positively correlated with the number of risky choices and total amount earned on the task, and with the parametric modulation of activation in regions within the network to the level of risk during choice selection. Furthermore, analysis using a mixed model demonstrated how relationships of the parametric modulation of activation in each of the four aforementioned regions are related to risk probabilities, and how previous trial outcomes and task progression influence the choice to take risk. The present findings provide the first direct evidence that white-matter integrity is linked to function within previously identified components of a network that is activated during risky decision-making, and demonstrate that the integrity of white-matter tracts is critical in consolidating and processing signals between cortical and striatal circuits during the decision-making process.

Dissociating Normal Aging from Alzheimer's Disease: A View from Cognitive Neuroscience

Both normal aging and Alzheimer's disease (AD) are associated with changes in cognition, grey and white matter volume, white matter integrity, neural activation, functional connectivity, and neurotransmission. Obviously, all of these changes are more pronounced in AD and proceed faster providing the basis for an AD diagnosis. Since these differences are quantitative, however, it was hypothesized that AD might simply reflect an accelerated aging process. The present article highlights the different neurocognitive changes associated with normal aging and AD and shows that, next to quantitative differences, there are multiple qualitative differences as well. These differences comprise different neurocognitive dissociations as different cognitive deficit profiles, different weights of grey and white matter atrophy, and different gradients of structural decline. These qualitative differences clearly indicate that AD cannot be simply described as accelerated aging process but on the contrary represents a solid entity.

Frontostriatal anatomical connections predict age- and difficulty-related differences in reinforcement learning

Reinforcement learning (RL) is supported by a network of striatal and frontal cortical structures that are connected through white-matter fiber bundles. With age, the integrity of these white-matter connections declines. The role of structural frontostriatal connectivity in individual and age-related differences in RL is unclear, although local white-matter density and diffusivity have been linked to individual differences in RL. Here we show that frontostriatal tract counts in young human adults (aged 18-28), as assessed noninvasively with diffusion-weighted magnetic resonance imaging and probabilistic tractography, positively predicted individual differences in RL when learning was difficult (70% valid feedback). In older adults (aged 63-87), in contrast, learning under both easy (90% valid feedback) and difficult conditions was predicted by tract counts in the same frontostriatal network. Furthermore, network-level analyses showed a double dissociation between the task-relevant networks in young and older adults, suggesting that older adults relied on different frontostriatal networks than young adults to obtain the same task performance. These results highlight the importance of successful information integration across striatal and frontal regions during RL, especially with variable outcomes.

The relationship between functional magnetic resonance imaging activation, diffusion tensor imaging, and training effects

While the relationship between diffusion tensor imaging (DTI) measurements and training effects is explored by Voelker et al. (this issue), a cursory discussion of functional magnetic resonance imaging (fMRI) measurements categorizes increased activation with findings of greater white matter integrity. Evidence of the relationship between fMRI activation and white matter integrity is conflicting, as is the relationship between fMRI activation and training effects. An examination of the changes in fMRI activation in response to training is helpful, but the relationship between DTI and fMRI activation, particularly in the context of white matter changes, must be examined further before general conclusions can be drawn.

The Association of Aging with White Matter Integrity and Functional Connectivity Hubs

Normal aging is associated with reduced cerebral structural integrity and altered functional brain activity, yet the association of aging with the relationship between structural and functional brain changes remains unclear. Using combined diffusion tensor imaging (DTI) and functional magnetic resonance imaging (fMRI) modalities, we hypothesized that aging-related changes in white matter integrity (i.e., fractional anisotropy) was associated with the short- or long-range functional connectivity density (FCD) in hub regions. We tested this hypothesis by using a healthy aging cohort comprised of 140 younger adults aged 20–39 years and 109 older adults aged 60–79 years. Compared with the younger group, older adults exhibited widespread reductions in white matter integrity with selective preservation in brain stem tracts and the cingulum connected to the hippocampus and cingulate cortex, whereas FCD mapping in older adults showed a reduced FCD in the visual, somatosensory, and motor functional networks and an increased FCD in the default mode network. The older adults exhibited significantly increased short- or long-range FCD in functional hubs of the precuneus, posterior, and middle cingulate, and thalamus, hippocampus, fusiform, and inferior temporal cortex. Furthermore, DTI-fMRI relationship were predominantly identified in older adults in whom short- and long-range FCD in the left precuneus was negatively correlated to structural integrity of adjacent and nonadjacent white matter tracts, respectively. We also found that long-range FCD in the left precuneus was positively correlated to cognitive function. These results support the compensatory hypothesis of neurocognitive aging theory and reveal the DTI-fMRI relationship associated with normal aging.

White matter injury in ischemic stroke

Stroke is one of the major causes of disability and mortality worldwide. It is well known that ischemic stroke can cause gray matter injury. However, stroke also elicits profound white matter injury, a risk factor for higher stroke incidence and poor neurological outcomes. The majority of damage caused by stroke is located in subcortical regions and, remarkably, white matter occupies nearly half of the average infarct volume. Indeed, white matter is exquisitely vulnerable to ischemia and is often injured more severely than gray matter. Clinical symptoms related to white matter injury include cognitive dysfunction, emotional disorders, sensorimotor impairments, as well as urinary incontinence and pain, all of which are closely associated with destruction and remodeling of white matter connectivity. White matter injury can be noninvasively detected by MRI, which provides a three-dimensional assessment of its morphology, metabolism, and function. There is an urgent need for novel white matter therapies, as currently available strategies are limited to preclinical animal studies. Optimal protection against ischemic stroke will need to encompass the fortification of both gray and white matter. In this review, we discuss white matter injury after ischemic stroke, focusing on clinical features and tools, such as imaging, manifestation, and potential treatments. We also briefly discuss the pathophysiology of WMI and future research directions.

Structural and functional connectivity in healthy aging: Associations for cognition and motor behavior

Age-related behavioral declines may be the result of deterioration of white matter tracts, affecting brain structural (SC) and functional connectivity (FC) during resting state. To date, it is not clear if the combination of SC and FC data could better predict cognitive/motor performance than each measure separately. We probed these relationships in the cingulum bundle, a major white matter pathway of the default mode network. We aimed to attain deeper knowledge about: (a) the relationship between age and the cingulum's SC and FC strength, (b) the association between SC and FC, and particularly (c) how the cingulum's SC and FC are related to cognitive/motor performance separately and combined. We examined these associations in a healthy and well-educated sample of 165 older participants (aged 64-85). SC and FC were acquired using probabilistic tractography to derive measures to capture white matter integrity within the cingulum bundle (fractional anisotropy, mean, axial and radial diffusivity) and a seed-based resting-state functional MRI correlation approach, respectively. Participants performed cognitive tests measuring processing speed, memory and executive functions, and motor tests measuring motor speed and grip force. Our data revealed that only SC but not resting state FC was significantly associated with age. Further, the cingulum's SC and FC showed no relation. Different relationships between cognitive/motor performance and SC/FC separately were found, but no additive effect of the combined analysis of cingulum's SC and FC for predicting cognitive/motor performance was apparent.

Real-time measurement and correction of both B0 changes and subject motion in diffusion tensor imaging using a double volumetric navigated (DvNav) sequence

Diffusion tensor imaging (DTI) requires a set of diffusion weighted measurements in order to acquire enough information to characterize local structure. The MRI scanner automatically performs a shimming process by acquiring a field map before the start of a DTI scan. Changes in B0, which can occur throughout the DTI acquisition due to several factors (including heating of the iron shim coils or subject motion), cause significant signal distortions that result in warped diffusion tensor (DT) parameter estimates. In this work we introduce a novel technique to simultaneously measure, report and correct in real time subject motion and changes in B0 field homogeneity, both in and through the imaging plane. This is achieved using double volumetric navigators (DvNav), i.e. a pair of 3D EPI acquisitions, interleaved with the DTI pulse sequence. Changes in the B0 field are evaluated in terms of zero-order (frequency) and first-order (linear gradients) shim. The ability of the DvNav to accurately estimate the shim parameters was first validated in a water phantom. Two healthy subjects were scanned both in the presence and absence of motion using standard, motion corrected (single navigator, vNav), and DvNav DTI sequences. The difference in performance between the proposed 3D EPI field maps and the standard 3D gradient echo field maps of the MRI scanner was also evaluated in a phantom and two healthy subjects. The DvNav sequence was shown to accurately measure and correct changes in B0 following manual adjustments of the scanner's central frequency and the linear shim gradients. Compared to other methods, the DvNav produced DTI results that showed greater spatial overlap with anatomical references, particularly in scans with subject motion. This is largely due to the ability of the DvNav system to correct shim changes and subject motion between each volume acquisition, thus reducing shear distortion.

Open Environment for Multimodal Interactive Connectivity Visualization and Analysis

Brain connectivity investigations are becoming increasingly multimodal and they present challenges for quantitatively characterizing and interactively visualizing data. In this study, we present a new set of network-based software tools for combining functional and anatomical connectivity from magnetic resonance imaging (MRI) data. The computational tools are available as part of Functional and Tractographic Connectivity Analysis Toolbox (FATCAT), a toolbox that interfaces with Analysis of Functional NeuroImages (AFNI) and SUrface MApping (SUMA) for interactive queries and visualization. This includes a novel, tractographic mini-probabilistic approach to improve streamline tracking in networks. We show how one obtains more robust tracking results for determining white matter connections by utilizing the uncertainty of the estimated diffusion tensor imaging (DTI) parameters and a few Monte Carlo iterations. This allows for thresholding based on the number of connections between target pairs to reduce the presence of tracts likely due to noise. To assist users in combining data, we describe an interface for navigating and performing queries in two-dimensional and three-dimensional data defined over voxel, surface, tract, and graph domains. These varied types of information can be visualized simultaneously and the queries performed interactively using SUMA and AFNI. The methods have been designed to increase the user's ability to visualize and combine functional MRI and DTI modalities, particularly in the context of single-subject inferences (e.g., in deep brain stimulation studies). Finally, we present a multivariate framework for statistically modeling network-based features in group analysis, which can be implemented for both functional and structural studies.

White matter microstructure between the pre-SMA and the cingulum bundle is related to response conflict in healthy subjects

INTRODUCTION

Response conflict involves selectively attending to relevant information and suppressing distracting, irrelevant information. The medial frontal cortex (MFC) is considered to be involved in response conflict. However, it remains unclear which white matter connectivity is associated with response conflict. This study aimed to delineate the neural connectivity of response conflict in healthy subjects and investigate the association between white matter microstructure and performance of a response conflict task.

METHOD

Twenty-eight healthy subjects underwent functional magnetic resonance imaging (fMRI) during the Flanker task and diffusion MRI. We identified the presupplementary motor area (pre-SMA) using fMRI. Furthermore, we delineated the white matter connectivity between the pre-SMA and the cingulum bundle (CB), which is located in the MFC, using probabilistic tractography. We calculated the mean diffusivity (MD), index of white matter microstructure, of this tract and evaluate the association between MD and performance of the Flanker task.

RESULT

The mean MD of this tract was significantly and positively associated with performance of the Flanker task.

CONCLUSION

The present study suggests the white matter connectivity between the pre-SMA and the CB is related to the response conflict in healthy subjects and finer white matter microstructure is associated with smaller response conflict.

Longitudinal alterations to brain function, structure, and cognitive performance in healthy older adults: A fMRI-DTI study

Cross-sectional research has shown that older adults tend to have different frontal cortex activation patterns, poorer brain structure, and lower task performance than younger adults. However, relationships between longitudinal changes in brain function, brain structure, and cognitive performance in older adults are less well understood. Here we present the results of a longitudinal, combined fMRI-DTI study in cognitive normal (CN) older adults. A two time-point study was conducted in which participants completed a task switching paradigm while fMRI data was collected and underwent the identical scanning protocol an average of 3.3 years later (SD=2 months). We observed longitudinal fMRI activation increases in bilateral regions of lateral frontal cortex at time point 2. These fMRI activation increases were associated with longitudinal declines in WM microstructure in a portion of the corpus callosum connecting the increasingly recruited frontal regions. In addition, the fMRI activation increase in the left VLPFC was associated with longitudinal increases in response latencies. Taken together, our results suggest that local frontal activation increases in CN older adults may in part reflect a response to reduced inter-hemispheric signaling mechanisms.

Impact of aging on frontostriatal reward processing

Healthy aging is associated with a progressive decline across a range of cognitive functions. An important factor underlying this decline may be the age-related impairment in stimulus-reward processing. Several studies have investigated age-related effects, but compared young versus old subjects. This is the first study to investigate the effect of aging on brain activation during reward processing within a continuous segment of the adult life span. We scanned 49 healthy adults aged 40-70 years, using functional MRI. We adopted a simple reward task, which allowed separate evaluation of neural responses to reward anticipation and receipt. The effect of reward on performance accuracy and speed was not related to age, indicating that all subjects could perform the task correctly. We identified a whole-brain significant age-related decline of ventral striatum activation during reward anticipation as compared to neutral anticipation. Importantly, the specificity of this finding was underscored by the observation that there was no general decline in activation during anticipation. Activation in the ventral striatum increased with age during reward receipt as compared to receiving neutral outcome. Finally, activation in the ventromedial prefrontal cortex during outcome was not affected by age. Our data demonstrate that the typical shift in striatal activation from reward receipt to reward anticipation in young adults disappears with healthy aging. These changes are consistent the well-ocumented age-related decline of striatal dopamine availability, and may provide a stepping stone for further research of age-related neurodegenerative diseases.

Cognitive reserve modulates ERPs associated with verbal working memory in healthy younger and older adults

Although many epidemiological studies suggest the beneficial effects of higher cognitive reserve (CR) in reducing age-related cognitive decline and dementia risk, the neural basis of CR is poorly understood. To our knowledge, the present study represents the first electrophysiological investigation of the relationship between CR and neural reserve (i.e., neural efficiency and capacity). Specifically, we examined whether CR modulates event-related potentials associated with performance on a verbal recognition memory task with 3 set sizes (1, 4, or 7 letters) in healthy younger and older adults. Neural data showed that as task difficulty increased, the amplitude of the parietal P3b component during the probe phase decreased and its latency increased. Notably, the degree of these neural changes was negatively correlated with CR in both age groups, such that individuals with higher CR showed smaller changes in P3b amplitude and less slowing in P3b latency (i.e., smaller changes in the speed of neural processing) with increasing task difficulty, suggesting greater neural efficiency. These CR-related differences in neural efficiency may underlie reserve against neuropathology and age-related burden.

The relevance of short-range fibers to cognitive efficiency and brain activation in aging and dementia

The integrity of structural connectivity in a functional brain network supports the efficiency of neural processing within relevant brain regions. This study aimed to quantitatively investigate the short- and long-range fibers, and their differential roles in the lower cognitive efficiency in aging and dementia. Three groups of healthy young, healthy older adults and patients with Alzheimer's disease (AD) participated in this combined functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI) study on prospective memory (PM). Short- and long-range fiber tracts within the PM task engaged brain networks were generated. The correlation between the fMRI signal change, PM performance and the DTI characters were calculated. FMRI results showed that the PM-specific frontal activations in three groups were distributed hierarchically along the rostrocaudal axis in the frontal lobe. In an overall PM condition generally activated brain network among the three groups, tractography was used to generate the short-range fibers, and they were found impaired in both healthy older adults and AD patients. However, the long-range fiber tracts were only impaired in AD. Additionally, the mean diffusivity (MD) of short-range but not long-range fibers was positively correlated with fMRI signal change and negatively correlated with the efficiency of PM performance. This study suggests that the disintegrity of short-range fibers may contribute more to the lower cognitive efficiency and higher compensatory brain activation in healthy older adults and more in AD patients.

Disconnected aging: cerebral white matter integrity and age-related differences in cognition

Cognition arises as a result of coordinated processing among distributed brain regions and disruptions to communication within these neural networks can result in cognitive dysfunction. Cortical disconnection may thus contribute to the declines in some aspects of cognitive functioning observed in healthy aging. Diffusion tensor imaging (DTI) is ideally suited for the study of cortical disconnection as it provides indices of structural integrity within interconnected neural networks. The current review summarizes results of previous DTI aging research with the aim of identifying consistent patterns of age-related differences in white matter integrity, and of relationships between measures of white matter integrity and behavioral performance as a function of adult age. We outline a number of future directions that will broaden our current understanding of these brain-behavior relationships in aging. Specifically, future research should aim to (1) investigate multiple models of age-brain-behavior relationships; (2) determine the tract-specificity versus global effect of aging on white matter integrity; (3) assess the relative contribution of normal variation in white matter integrity versus white matter lesions to age-related differences in cognition; (4) improve the definition of specific aspects of cognitive functioning related to age-related differences in white matter integrity using information processing tasks; and (5) combine multiple imaging modalities (e.g., resting-state and task-related functional magnetic resonance imaging; fMRI) with DTI to clarify the role of cerebral white matter integrity in cognitive aging.

Brain connectivity and visual attention

Emerging hypotheses suggest that efficient cognitive functioning requires the integration of separate, but interconnected cortical networks in the brain. Although task-related measures of brain activity suggest that a frontoparietal network is associated with the control of attention, little is known regarding how components within this distributed network act together or with other networks to achieve various attentional functions. This review considers both functional and structural studies of brain connectivity, as complemented by behavioral and task-related neuroimaging data. These studies show converging results: The frontal and parietal cortical regions are active together, over time, and identifiable frontoparietal networks are active in relation to specific task demands. However, the spontaneous, low-frequency fluctuations of brain activity that occur in the resting state, without specific task demands, also exhibit patterns of connectivity that closely resemble the task-related, frontoparietal attention networks. Both task-related and resting-state networks exhibit consistent relations to behavioral measures of attention. Further, anatomical structure, particularly white matter pathways as defined by diffusion tensor imaging, places constraints on intrinsic functional connectivity. Lastly, connectivity analyses applied to investigate cognitive differences across individuals in both healthy and diseased states suggest that disconnection of attentional networks is linked to deficits in cognitive functioning, and in extreme cases, to disorders of attention. Thus, comprehensive theories of visual attention and their clinical translation depend on the continued integration of behavioral, task-related neuroimaging, and brain connectivity measures.