Wavelet‐based regularity analysis reveals recurrent spatiotemporal behavior in resting‐state fMRI

One of the major findings from multimodal neuroimaging studies in the past decade is that the human brain is anatomically and functionally organized into large‐scale networks. In resting state fMRI (rs‐fMRI), spatial patterns emerge when temporal correlations between various brain regions are tallied, evidencing networks of ongoing intercortical cooperation. However, the dynamic structure governing the brain's spontaneous activity is far less understood due to the short and noisy nature of the rs‐fMRI signal. Here, we develop a wavelet‐based regularity analysis based on noise estimation capabilities of the wavelet transform to measure recurrent temporal pattern stability within the rs‐fMRI signal across multiple temporal scales. The method consists of performing a stationary wavelet transform to preserve signal structure, followed by construction of “lagged” subsequences to adjust for correlated features, and finally the calculation of sample entropy across wavelet scales based on an “objective” estimate of noise level at each scale. We found that the brain's default mode network (DMN) areas manifest a higher level of irregularity in rs‐fMRI time series than rest of the brain. In 25 aged subjects with mild cognitive impairment and 25 matched healthy controls, wavelet‐based regularity analysis showed improved sensitivity in detecting changes in the regularity of rs‐fMRI signals between the two groups within the DMN and executive control networks, compared with standard multiscale entropy analysis. Wavelet‐based regularity analysis based on noise estimation capabilities of the wavelet transform is a promising technique to characterize the dynamic structure of rs‐fMRI as well as other biological signals. Hum Brain Mapp 36:3603–3620, 2015. © 2015 Wiley Periodicals, Inc.     

Changes in intrinsic connectivity of the brain's reading network following intervention in children with autism

While task‐based neuroimaging studies have identified alterations in neural circuitry underlying language processing in children with autism spectrum disorders [ASD], resting state functional magnetic resonance imaging [rsfMRI] is a promising alternative to the constraints posed by task‐based fMRI. This study used rsfMRI, in a longitudinal design, to study the impact of a reading intervention on connectivity of the brain regions involved in reading comprehension in children with ASD. Functional connectivity was examined using group independent component analysis (GICA) and seed‐based correlation analysis of Broca's and Wernicke's areas, in three groups of participants: an experimental group of ASD children (ASD‐EXP), a wait list control group of ASD children (ASD‐WLC), and a group of typically developing (TD) control children. Both GICA and seed‐based analyses revealed stronger functional connectivity of Broca's and Wernicke's areas in the ASD‐EXP group postintervention. Additionally, improvement in reading comprehension in the ASD‐EXP group was correlated with greater connectivity in both Broca's and Wernicke's area in the GICA identified reading network component. In addition, increased connectivity between the Broca's area and right postcentral and right STG, and the Wernicke's area and LIFG, were also correlated with greater improvement in reading comprehension. Overall, this study revealed widespread changes in functional connectivity of the brain's reading network as a result of intervention in children with ASD. These novel findings provide valuable insights into the neuroplasticity of brain areas underlying reading and the impact of intensive intervention in modifying them in children with ASD. Hum Brain Mapp 36:2965–2979, 2015. © 2015 Wiley Periodicals, Inc.     

Age-related laterality shifts in auditory and attention networks with normal ageing: Effects on a working memory task

Our brains respond to age-related anatomical and physiological changes by reorganizing functions through increases in activity or laterality shifts, among other possibilities. In suboptimal conditions such as in a noisy environment, the impact of ageing on brain functions is likely to be most apparent. The present study examined the effects of normal ageing on the neural activity associated with working memory (WM) tasks performed in quiet (WMQ) and in noise (WMN). Participants of two different age groups (mean age of 29.9 years and 54.8 years) underwent fMRI scans while performing WMQ and WMN tasks. Behavioural findings reveal that, on average, older adults performed less accurately than younger participants across all tasks combined. Specific comparisons between WMQ and WMN tasks revealed that younger participants performed better in the WMN and older participants performed better in the WMQ. fMRI results reveal increased activity in older participants in regions of the right superior temporal gyrus (STG), right Heschl's gyrus (HG) and left thalamus in WMQ. During WMN tasks older participants demonstrate increased activity in the left STG, left middle temporal gyrus and bilateral thalamus. There was also a laterality shift with increasing age. Areas involved in this laterality shift in the WMQ task included the STG, HG and cerebellum. In the WMN task the areas demonstrating a laterality shift were the STG, HG, cerebellum and thalamus. Findings support the hypothesis that functional networks related to memory processing undergo brain reorganization during ageing. Findings also suggest that the demand on attentional resources increases to compensate for the effects of background noise in both ages studied. These findings contribute to the growing evidence that with ageing is a global reorganization in the functional neural networks associated with cognitive processing.     

Neural mechanisms of training an auditory event‐related potential task in a brain–computer interface context

Effective use of brain–computer interfaces (BCIs) typically requires training. Improved understanding of the neural mechanisms underlying BCI training will facilitate optimisation of BCIs. The current study examined the neural mechanisms related to training for electroencephalography (EEG)‐based communication with an auditory event‐related potential (ERP) BCI. Neural mechanisms of training in 10 healthy volunteers were assessed with functional magnetic resonance imaging (fMRI) during an auditory ERP‐based BCI task before (t1) and after (t5) three ERP‐BCI training sessions outside the fMRI scanner (t2, t3, and t4). Attended stimuli were contrasted with ignored stimuli in the first‐level fMRI data analysis (t1 and t5); the training effect was verified using the EEG data (t2‐t4); and brain activation was contrasted before and after training in the second‐level fMRI data analysis (t1 vs. t5). Training increased the communication speed from 2.9 bits/min (t2) to 4 bits/min (t4). Strong activation was found in the putamen, supplementary motor area (SMA), and superior temporal gyrus (STG) associated with attention to the stimuli. Training led to decreased activation in the superior frontal gyrus and stronger haemodynamic rebound in the STG and supramarginal gyrus. The neural mechanisms of ERP‐BCI training indicate improved stimulus perception and reduced mental workload. The ERP task used in the current study showed overlapping activations with a motor imagery based BCI task from a previous study on the neural mechanisms of BCI training in the SMA and putamen. This suggests commonalities between the neural mechanisms of training for both BCI paradigms.     

Altered dynamic amplitude of low-frequency fluctuation in individuals at high risk for Alzheimer's disease

The brain's dynamic spontaneous neural activity is significant in supporting cognition; however, how brain dynamics go awry in subjective cognitive decline (SCD) and mild cognitive impairment (MCI) remains unclear. Thus, the current study aimed to investigate the dynamic amplitude of low-frequency fluctuation (dALFF) alterations in patients at high risk for Alzheimer's disease and to explore its correlation with clinical cognitive assessment scales, to identify an early imaging sign for these special populations. A total of 152 participants, including 72 SCD patients, 44 MCI patients and 36 healthy controls (HCs), underwent a resting-state functional magnetic resonance imaging and were assessed with various neuropsychological tests. The dALFF was measured using sliding-window analysis. We employed canonical correlation analysis (CCA) to examine the bi-multivariate correlations between neuropsychological scales and altered dALFF among multiple regions in SCD and MCI patients. Compared to those in the HC group, both the MCI and SCD groups showed higher dALFF values in the right opercular inferior frontal gyrus (voxel P < .001, cluster P < .05, correction). Moreover, the CCA models revealed that behavioural tests relevant to inattention correlated with the dALFF of the right middle frontal gyrus and right opercular inferior frontal gyrus, which are involved in frontoparietal networks (R = .43, P = .024). In conclusion, the brain dynamics of neural activity in frontal areas provide insights into the shared neural basis underlying SCD and MCI.     

Determination of the posterior boundary of Wernicke's area based on multimodal connectivity profiles

Wernicke's area is one of the most important language regions and has been widely studied in both basic research and clinical neurology. However, its exact anatomy has been controversial. In this study, we proposed to address the anatomy of Wernicke's area by investigating different connectivity profiles. First, the posterior superior temporal gyrus (STG), traditionally called “Wernicke's area”, was parcellated into three component subregions with diffusion MRI. Then, whole‐brain anatomical connectivity, resting‐state functional connectivity (RSFC) and meta‐analytic connectivity modeling (MACM) analyses were used to establish the anatomical, resting‐state and task‐related coactivation network of each subregion to identify which subregions participated in the language network. In addition, behavioral domain analysis, meta‐analyses of semantics, execution speech, and phonology and intraoperative electrical stimulation were used to determine which subregions were involved in language processing. Anatomical connectivity, RSFC and MACM analyses consistently identified that the two anterior subregions in the posterior STG primarily participated in the language network, whereas the most posterior subregion in the temporoparietal junction area primarily participated in the default mode network. Moreover, the behavioral domain analyses, meta‐analyses of semantics, execution speech and phonology and intraoperative electrical stimulation mapping also confirmed that only the two anterior subregions were involved in language processing, whereas the most posterior subregion primarily participated in social cognition. Our findings revealed a convergent posterior anatomical border for Wernicke's area and indicated that the brain's functional subregions can be identified on the basis of its specific structural and functional connectivity patterns. Hum Brain Mapp 36:1908–1924, 2015. © 2015 Wiley Periodicals, Inc .     

Emergence of a hierarchical brain during infancy reflected by stepwise functional connectivity

The hierarchical nature of the brain's functional organization has long been recognized, but when and how this architecture emerges during development remains largely unknown. Here the development of the brain's hierarchical organization was characterized using a modified stepwise functional connectivity approach based on resting‐state fMRI in a fully longitudinal sample of infants (N = 28, with scans after birth, and at 1 and 2 years) and adults. Results obtained by placing seeds in early sensory cortices revealed novel hierarchical patterns of adult brain organization ultimately converging in limbic, paralimbic, basal ganglia, and frontoparietal brain regions. These findings are remarkably consistent with predictive coding accounts of neural processing that place these regions at the top of predictive coding hierarchies. Infants gradually developed toward this architecture in a region‐ and step‐dependent manner, and displayed many of the same regions as adults in top hierarchical positions, starting from 1 year of age. The findings further revealed patterns of inter‐sensory connectivity likely reflecting the emergence and development of multisensory processing strategies during infancy, the strengths of which were correlated with early cognitive development scores. Hum Brain Mapp 38:2666–2682, 2017. © 2017 Wiley Periodicals, Inc.     

Differential roles of right temporal cortex and broca's area in pitch processing: Evidence from music and mandarin

Superior temporal and inferior frontal cortices are involved in the processing of pitch information in the domain of language and music. Here, we used fMRI to test the particular roles of these brain regions in the neural implementation of pitch in music and in tone language (Mandarin) with a group of Mandarin speaking musicians whose pertaining experiences in pitch are similar across domains. Our findings demonstrate that the neural network for pitch processing includes the pars triangularis of Broca's area and the right superior temporal gyrus (STG) across domains. Within this network, pitch sensitive activation in Broca's area is tightly linked to the behavioral performance of pitch congruity judgment, thereby reflecting controlled processes. Activation in the right STG is independent of performance and more sensitive to pitch congruity in music than in tone language, suggesting a domain‐specific modulation of the perceptual processes. These observations provide a first glimpse at the cortical pitch processing network shared across domains. Hum Brain Mapp 34:2045–2054, 2013. © 2012 Wiley Periodicals, Inc.     

Superior temporal lobe dysfunction and frontotemporal dysconnectivity in subjects at risk of psychosis and in first‐episode psychosis

Background: Superior temporal lobe dysfunction is a robust finding in functional neuroimaging studies of schizophrenia and is thought to be related to a disruption of fronto‐temporal functional connectivity. However, the stage of the disorder at which these functional alterations occur is unclear. We addressed this issue by using functional MRI (fMRI) to study subjects in the prodromal and first episode phases of schizophrenia. Methods: Subjects with an at risk mental state (ARMS) for psychosis, a first psychotic episode (FEP), and controls were studied using fMRI while performing a working memory task. Activation in the superior temporal gyrus (STG) was assessed using statistical parametric mapping, and its relationship to frontal activation was examined using dynamic causal modeling. Results: The STG was differentially engaged across the three groups. There was deactivation of this region during the task in controls, whereas subjects with FEP showed activation and the response in subjects with ARMS was intermediately relative to the two other groups. There were corresponding differences in the effective connectivity between the STG and the middle frontal gyrus across the three groups, with a negative coupling between these areas in controls, a positive coupling in the FEP group, and an intermediate value in the ARMS group. Conclusions: A failure to deactivate the superior temporal lobe during tasks that engage prefrontal cortex is evident at the onset of schizophrenia and may reflect a disruption of fronto‐temporal connectivity. Qualitatively similar alterations are evident in people with prodromal symptoms of the disorder. Hum Brain Mapp, 2009. © 2009 Wiley‐Liss, Inc.     

Weighting of neural prediction error by rhythmic complexity: A predictive coding account using mismatch negativity

The human brain's ability to extract and encode temporal regularities and to predict the timing of upcoming events is critical for music and speech perception. This work addresses how these mechanisms deal with different levels of temporal complexity, here the number of distinct durations in rhythmic patterns. We use electroencephalography (EEG) to relate the mismatch negativity (MMN), a proxy of neural prediction error, to a measure of information content of rhythmic sequences, the Shannon entropy. Within each of three conditions, participants listened to repeatedly presented standard rhythms of five tones (four inter‐onset intervals) and of a given level of entropy: zero (isochronous), medium entropy (two distinct interval durations), or high entropy (four distinct interval durations). Occasionally, the fourth tone was moved forward in time that is it occurred 100 ms (small deviation) or 300 ms early (large deviation). According to the predictive coding framework, high‐entropy stimuli are more difficult to model for the brain, resulting in less confident predictions and yielding smaller prediction errors for deviant sounds. Our results support this hypothesis, showing a gradual decrease in MMN amplitude as a function of entropy, but only for small timing deviants. For large timing deviants, in contrast, a modulation of activity in the opposite direction was observed for the earlier N1 component, known to also be sensitive to sudden changes in directed attention. Our results suggest the existence of a fine‐grained neural mechanism that weights neural prediction error to the complexity of rhythms and that mostly manifests in the absence of directed attention.     

The effects of background noise on brain activity using speech stimuli on healthy young adults

Everyday spoken language processing does not occur in a novel acoustic environment, but rather in the presence of the interfering background noise. In the present study, brain activation associated with speech perception (SP) processing in quiet (SPQ) and SP processing in 5-dB SNR noise (SPN) was examined in 15 healthy young adults using functional MRI. The behavioral performance shows no significant difference between SPN and SPQ, suggesting that background noise does not always impair spoken language comprehension in young healthy participants. The fMRI results indicate that both the superior temporal gyrus (STG) and middle temporal gyrus (MTG) were significantly activated during both the SPQ and SPN. This is attributed to the use of verbal stimuli in this study. Further activation for both SPQ and SPN was also found in other temporal areas and the cerebellum. However interestingly, specific comparisons between SPQ and SPN revealed significant increases in brain activation in the left STG, left MTG and bilateral cerebellum during SPN compared to SPQ. We suggest that the higher processing demands due to the presence of background noise are associated with compensatory strategies to allow the cognitive system to overcome noise-related interference, particularly implicating involvement of the left STG, left MTG and bilateral cerebellum. Findings are discussed in the context of corroborating evidence of such compensation.     

Neural correlates of word production stages delineated by parametric modulation of psycholinguistic variables

Word production is a complex multistage process linking conceptual representations, lexical entries, phonological forms and articulation. Previous studies have revealed a network of predominantly left‐lateralized brain regions supporting this process, but many details regarding the precise functions of different nodes in this network remain unclear. To better delineate the functions of regions involved in word production, we used event‐related functional magnetic resonance imaging (fMRI) to identify brain areas where blood oxygen level‐dependent (BOLD) responses to overt picture naming were modulated by three psycholinguistic variables: concept familiarity, word frequency, and word length, and one behavioral variable: reaction time. Each of these variables has been suggested by prior studies to be associated with different aspects of word production. Processing of less familiar concepts was associated with greater BOLD responses in bilateral occipitotemporal regions, reflecting visual processing and conceptual preparation. Lower frequency words produced greater BOLD signal in left inferior temporal cortex and the left temporoparietal junction, suggesting involvement of these regions in lexical selection and retrieval and encoding of phonological codes. Word length was positively correlated with signal intensity in Heschl's gyrus bilaterally, extending into the mid‐superior temporal gyrus (STG) and sulcus (STS) in the left hemisphere. The left mid‐STS site was also modulated by reaction time, suggesting a role in the storage of lexical phonological codes. Hum Brain Mapp, 2009. © 2009 Wiley‐Liss, Inc.     

Grab‐AD: Generalizability and reproducibility of altered brain activity and diagnostic classification in Alzheimer's Disease

Alzheimer's disease (AD) is associated with disruptions in brain activity and networks. However, there is substantial inconsistency among studies that have investigated functional brain alterations in AD; such contradictions have hindered efforts to elucidate the core disease mechanisms. In this study, we aim to comprehensively characterize AD‐associated functional brain alterations using one of the world's largest resting‐state functional MRI (fMRI) biobank for the disorder. The biobank includes fMRI data from six neuroimaging centers, with a total of 252 AD patients, 221 mild cognitive impairment (MCI) patients and 215 healthy comparison individuals. Meta‐analytic techniques were used to unveil reliable differences in brain function among the three groups. Relative to the healthy comparison group, AD was associated with significantly reduced functional connectivity and local activity in the default‐mode network, basal ganglia and cingulate gyrus, along with increased connectivity or local activity in the prefrontal lobe and hippocampus (p < .05, Bonferroni corrected). Moreover, these functional alterations were significantly correlated with the degree of cognitive impairment (AD and MCI groups) and amyloid‐β burden. Machine learning models were trained to recognize key fMRI features to predict individual diagnostic status and clinical score. Leave‐one‐site‐out cross‐validation established that diagnostic status (mean area under the receiver operating characteristic curve: 0.85) and clinical score (mean correlation coefficient between predicted and actual Mini‐Mental State Examination scores: 0.56, p < .0001) could be predicted with high accuracy. Collectively, our findings highlight the potential for a reproducible and generalizable functional brain imaging biomarker to aid the early diagnosis of AD and track its progression.     

Working memory dysfunction in obsessive-compulsive disorder: A neuropsychological and functional MRI study

Previous neuropsychological studies indicate that OCD subtypes such as checking rituals might be associated with a working memory deficit. On the other hand, functional neuroimaging studies found functional abnormalities of the frontal cortex and subcortical structures in OCD. Combined with functional imaging method, we applied neuropsychological batteries to demonstrate a working memory deficit in OCD by comparison with normal controls. In addition, working memory and brain activation were further examined with symptom-based analysis. Forty patients with OCD and 25 normal controls were examined using neuropsychological tests including the WAIS-R, WCST, WMS-R, and R-OCFT and functional MRI (fMRI) during the N-back task including 0- and 2-back task. On fMRI, the brain regions activated during the performance and the differences in the activation between patients and controls were identified. Additional analyses of severity and subtypes were conducted by using Y-BOCS severity score, symptom-checklist and Leckman’s four-factor model, respectively. On the neuropsychological tests, the OCD patients had significantly lower scores on the delayed recall section of the WMS-R and the immediate recall section of the R-OCFT compared to the controls. On fMRI, the patients showed greater activation in the right dorsolateral prefrontal cortex (DLPFC), left superior temporal gyrus (STG), left insula, and cuneus during two-back task compared to the controls. Right orbitofrontal cortex activity showed a significant positive correlation with Y-BOCS scores in OCD. Furthermore, patients with obsessions/checking rituals (n = 10) showed severer memory deficits and decreased activity in the postcentral gyrus than patients with cleanliness/washing rituals (n = 14). In conclusion, we found neuropsychological dysfunction and brain abnormalities in OCD. Furthermore, our results suggested that symptom severity and symptom subtype such as obsessions/checking might affect neuropsychological dysfunction and related brain activities.     

Classification of autism spectrum disorder based on sample entropy of spontaneous functional near infra-red spectroscopy signal

ObjectivesTo assess the possibility of distinguishing autism spectrum disorder (ASD) based on the characteristic of spontaneous hemodynamic fluctuations and to explore the location of abnormality in the brain.MethodsUsing the sample entropy (SampEn) of functional near-infrared spectroscopy (fNIRS) from bilateral inferior frontal gyrus (IFG) and temporal cortex (TC) on 25 children with ASD and 22 typical development (TD) children, the pattern of mind-wandering was assessed. With the SampEn as feature variables, a machine learning classifier was applied to mark ASD and locate the abnormal area in the brain.ResultsThe SampEn was generally lower for ASD than TD, indicating the fNIRS series from ASD was unstable, had low fluctuation, and high self-similarity. The classification between ASD and TD could reach 97.6% in accuracy.ConclusionsThe SampEn of fNIRS could accurately distinguish ASD. The abnormality in terms of the SampEn occurs more frequently in IFG than TC, and more frequently in the left than in the right hemisphere.SignificanceThe results of this study may help to understand the cortical mechanism of ASD and provide a fNIRS-based diagnosis for ASD.     

Default‐mode network functional connectivity is closely related to metabolic activity

Over the last decade, the brain's default‐mode network (DMN) and its function has attracted a lot of attention in the field of neuroscience. However, the exact underlying mechanisms of DMN functional connectivity, or more specifically, the blood‐oxygen level‐dependent (BOLD) signal, are still incompletely understood. In the present study, we combined 2‐deoxy‐2‐[¹⁸F]fluoroglucose positron emission tomography (FDG‐PET), proton magnetic resonance spectroscopy (¹H‐MRS), and resting‐state functional magnetic resonance imaging (rs‐fMRI) to investigate more directly the association between local glucose consumption, local glutamatergic neurotransmission and DMN functional connectivity during rest. The results of the correlation analyzes using the dorsal posterior cingulate cortex (dPCC) as seed region showed spatial similarities between fluctuations in FDG‐uptake and fluctuations in BOLD signal. More specifically, in both modalities the same DMN areas in the inferior parietal lobe, angular gyrus, precuneus, middle, and medial frontal gyrus were positively correlated with the dPCC. Furthermore, we could demonstrate that local glucose consumption in the medial frontal gyrus, PCC and left angular gyrus was associated with functional connectivity within the DMN. We did not, however, find a relationship between glutamatergic neurotransmission and functional connectivity. In line with very recent findings, our results lend further support for a close association between local metabolic activity and functional connectivity and provide further insights towards a better understanding of the underlying mechanism of the BOLD signal. Hum Brain Mapp 36:2027–2038, 2015. © 2015 Wiley Periodicals, Inc.     

Predictors of treatment response to fluvoxamine in obsessive-compulsive disorder: An fMRI study

Recent neuroimaging studies suggest that the pathophysiology of obsessive-compulsive disorder (OCD) may involve more widely distributed large-scale brain systems, including the parietal, occipital, and cerebellar areas, rather than the conventional orbitofronto-striatal model. We hypothesized that not only orbitofrontal cortex and caudate nucleus activities but also posterior brain regions might be associated with subsequent treatment response to serotonin reuptake inhibitors in OCD. The participants were 17 patients with OCD. Each patient was required to undergo fluvoxamine pharmacotherapy for 12 weeks. Before treatment, fMRI images of the subjects were obtained in the context of a symptom-provocation paradigm. The percentage changes in total Yale-Brown Obsessive-Compulsive Scale (Y-BOCS) scores, from pre- to post-treatment, served as the index of treatment response. Statistical Parametric Mapping was used to identify brain loci where pre-treatment brain activation significantly correlated with the subsequent treatment response. Fifteen of 17 patients completed the 12-week treatment. During the symptom provocation task, patients showed brain activation in the left superior temporal gyrus (STG), left precuneus, left frontal cortices, right cerebellum, and right frontal cortices. We found that pre-treatment activation in the right cerebellum (Z-score = 5.10, x,y,z=22,-84,-18) and the left STG (Z-score = 4.95, x,y,z=-62,-22,0) was positively correlated with the improvement in the Y-BOCS score. Our results suggest that pre-treatment activation in the right cerebellum and in the left STG predict subsequent reduction in OCD symptom severity. There is every possibility that fMRI can be used as a tool to predict treatment response.     

Variability of structurally constrained and unconstrained functional connectivity in schizophrenia

Spatial variation in connectivity is an integral aspect of the brain's architecture. In the absence of this variability, the brain may act as a single homogenous entity without regional specialization. In this study, we investigate the variability in functional links categorized on the basis of the presence of direct structural paths (primary) or indirect paths mediated by one (secondary) or more (tertiary) brain regions ascertained by diffusion tensor imaging. We quantified the variability in functional connectivity using an unbiased estimate of unpredictability (functional connectivity entropy) in a neuropsychiatric disorder where structure‐function relationship is considered to be abnormal; 34 patients with schizophrenia and 32 healthy controls underwent DTI and resting state functional MRI scans. Less than one‐third (27.4% in patients, 27.85% in controls) of functional links between brain regions were regarded as direct primary links on the basis of DTI tractography, while the rest were secondary or tertiary. The most significant changes in the distribution of functional connectivity in schizophrenia occur in indirect tertiary paths with no direct axonal linkage in both early (P = 0.0002, d = 1.46) and late (P = 1 × 10^?17, d = 4.66) stages of schizophrenia, and are not altered by the severity of symptoms, suggesting that this is an invariant feature of this illness. Unlike those with early stage illness, patients with chronic illness show some additional reduction in the distribution of connectivity among functional links that have direct structural paths (P = 0.08, d = 0.44). Our findings address a critical gap in the literature linking structure and function in schizophrenia, and demonstrate for the first time that the abnormal state of functional connectivity preferentially affects structurally unconstrained links in schizophrenia. It also raises the question of a continuum of dysconnectivity ranging from less direct (structurally unconstrained) to more direct (structurally constrained) brain pathways underlying the progressive clinical staging and persistence of schizophrenia. Hum Brain Mapp 36:4529–4538, 2015. © 2015 The Authors. Human Brain Mapping Published by Wiley Periodicals, Inc.     

Postconcussion syndrome after minor head injury: Brain activation of working memory and attention

After minor head injury (MHI) postconcussive symptoms (PCS) such as memory and attention deficits frequently occur. It has been hypothesised that PCS are caused by microstructural damage to the brain due to shearing injury, which is not detectable with conventional imaging, and may be responsible for a functional deficit. The purpose of this study was to correlate functional magnetic resonance imaging brain activation of working memory and selective attention with PCS. 21 MHI patients and 12 healthy controls were scanned at 3T. Stimulation paradigms were the n‐back and Counting Stroop tasks to engage working memory and selective attention, respectively. Functional data analysis consisted of random effects group analyses, correlating brain activation patterns with the severity of PCS as evaluated with the Rivermead postconcussion symptoms questionnaire. At minimal working memory load, activation was seen in patients with greater severity of PCS in the working memory network. With an increase of working memory load, increase of activation was more pronounced in patients with greater severity of PCS. At high and increased working memory load, activation associated with the severity of PCS was seen in the posterior parietal area, parahippocampal gyrus, and posterior cingulate gyrus. Activation related to selective attention processing was increased with greater severity of PCS. The increased activity in relation to working memory and attention, and the recruitment of brain areas outside the working memory network at high working memory load, may be considered a reflection of the brain's compensatory response to microstructural injury in patients with PCS. Hum Brain Mapp, 2009. © 2008 Wiley‐Liss, Inc.     

Brain network alterations in Alzheimer's disease measured by Eigenvector centrality in fMRI are related to cognition and CSF biomarkers

Recent imaging studies have demonstrated functional brain network changes in patients with Alzheimer's disease (AD). Eigenvector centrality (EC) is a graph analytical measure that identifies prominent regions in the brain network hierarchy and detects localized differences between patient populations. This study used voxel‐wise EC mapping (ECM) to analyze individual whole‐brain resting‐state functional magnetic resonance imaging (MRI) scans in 39 AD patients (age 67 ± 8) and 43 healthy controls (age 69 ± 7). Between‐group differences were assessed by a permutation‐based method. Associations of EC with biomarkers for AD pathology in cerebrospinal fluid (CSF) and Mini Mental State Examination (MMSE) scores were assessed using Spearman correlation analysis. Decreased EC was found bilaterally in the occipital cortex in AD patients compared to controls. Regions of increased EC were identified in the anterior cingulate and paracingulate gyrus. Across groups, frontal and occipital EC changes were associated with pathological concentrations of CSF biomarkers and with cognition. In controls, decreased EC values in the occipital regions were related to lower MMSE scores. Our main finding is that ECM, a hypothesis‐free and computationally efficient analysis method of functional MRI (fMRI) data, identifies changes in brain network organization in AD patients that are related to cognition and underlying AD pathology. The relation between AD‐like EC changes and cognitive performance suggests that resting‐state fMRI measured EC is a potential marker of disease severity for AD. Hum Brain Mapp 35:2383–2393, 2014. © 2013 Wiley Periodicals, Inc .