Assessment of reliability in functional imaging studies

Measuring the relationship between museum attributes and visitors: An application of topic model on museum online reviews

In recent years, cultural tourism has increasingly embraced museum visits. Museums serve as both cultural heritage guardians and integral parts of tourist destinations, significantly impacting visitor satisfaction and experience. Moreover, online museum reviews have become a crucial indicator of museum service quality, visitor experience, and public feedback in the digital age. An analysis of online reviews on major tourism websites and social media platforms can assist museums in developing appropriate management strategies. This study employed the structural topic model (STM) to analyze online museum reviews, identifying three primary attributes of museums and visitors' personal experiences, as well as 19 sub-attributes. The study confirmed that core offerings have a positive impact on visitor experience and satisfaction, while peripheral services and overall ambiance are also positively related to visitor experience and satisfaction. Furthermore, the results of structural equation modeling demonstrated that visitors' personal experiences have a positive impact on satisfaction. The results of structural equation modeling analysis support all seven hypothesized relationships. These findings will assist museum managers in developing effective management strategies and future plans.

Evaluation of a Simple Clinical Language Paradigm With Respect to Sensory Independency, Functional Asymmetry, and Effective Connectivity

The present study replicates a known visual language paradigm, and extends it to a paradigm that is independent from the sensory modality of the stimuli and, hence, could be administered either visually or aurally, such that both patients with limited sight or hearing could be examined. The stimuli were simple sentences, but required the subject not only to understand the content of the sentence but also to formulate a response that had a semantic relation to the content of the presented sentence. Thereby, this paradigm does not only test perception of the stimuli, but also to some extend sentence and semantic processing, and covert speech production within one task. When the sensory base-line condition was subtracted, both the auditory and visual version of the paradigm demonstrated a broadly overlapping and asymmetric network, comprising distinct areas of the left posterior temporal lobe, left inferior frontal areas, left precentral gyrus, and supplementary motor area. The consistency of activations and their asymmetry was evaluated with a conjunction analysis, probability maps, and intraclass correlation coefficients (ICC). This underlying network was further analyzed with dynamic causal modeling (DCM) to explore whether not only the same brain areas were involved, but also the network structure and information flow were the same between the sensory modalities. In conclusion, the paradigm reliably activated the most central parts of the speech and language network with a great consistency across subjects, and independently of whether the stimuli were administered aurally or visually. However, there was individual variability in the degree of functional asymmetry between the two sensory conditions.

Identity-mapping cascaded network for fMRI registration

Neuroscience researches based on functional magnetic resonance imaging (fMRI) rely on accurate inter-subject image registration of functional regions. The intersubject alignment of fMRI can improve the statistical power of group analyses. Recent studies have shown the deep learning-based registration methods can be used for registration. In our work, we proposed a 30-Identity-Mapping Cascaded network (30-IMCNet) for rs-fMRI registration. It is a cascaded network that can warp the moving image progressively and finally align to the fixed image. A Combination unit with an identity-mapping path is added to the inputs of each IMCNet to guide the network training. We implemented 30-IMCNet on an rs-fMRI dataset (1000 Functional Connectomes Project dataset) and a task-related fMRI dataset (Eyes Open Eyes Closed fMRI dataset). To evaluate our method, a group-level analysis was implemented in the testing dataset. For rs-fMRI, the criterions such as peakt-value of group-level t-maps, cluster-level evaluation, and intersubject functional network correlation were used to evaluate the quality of the registrations. For task-related fMRI, peakt-value in ALFF paired-t map and peakt-value in ReHo paired-t maps were used. Compared with traditional algorithm FSL, SPM, and deep learning algorithm Kimet al, Zhaoet alour method has improvements of 48.90%, 30.73%, 36.38%, and 16.73% in the peaktvalue of t-maps. Our proposed method can achieve superior functional registration performance and thus gain a significant improvement in functional consistency.

Functional organisation for verb generation in children with developmental language disorder

Developmental language disorder (DLD) is characterised by difficulties in learning one's native language for no apparent reason. These language difficulties occur in 7% of children and are known to limit future academic and social achievement. Our understanding of the brain abnormalities associated with DLD is limited. Here, we used a simple four-minute verb generation task (children saw a picture of an object and were instructed to say an action that goes with that object) to test children between the ages of 10-15 years (DLD N = 50, typically developing N = 67). We also tested 26 children with poor language ability who did not meet our criteria for DLD. Contrary to our registered predictions, we found that children with DLD did not have (i) reduced activity in language relevant regions such as the left inferior frontal cortex; (ii) dysfunctional striatal activity during overt production; or (iii) a reduction in left-lateralised activity in frontal cortex. Indeed, performance of this simple language task evoked activity in children with DLD in the same regions and to a similar level as in typically developing children. Consistent with previous reports, we found sub-threshold group differences in the left inferior frontal gyrus and caudate nuclei, but only when analysis was limited to a subsample of the DLD group (N = 14) who had the poorest performance on the task. Additionally, we used a two-factor model to capture variation in all children studied (N = 143) on a range of neuropsychological tests and found that these language and verbal memory factors correlated with activity in different brain regions. Our findings indicate a lack of support for some neurological models of atypical language learning, such as the procedural deficit hypothesis or the atypical lateralization hypothesis, at least when using simple language tasks that children can perform. These results also emphasise the importance of controlling for and monitoring task performance.

Current Challenges in Translational and Clinical fMRI and Future Directions

Translational neuroscience is an important field that brings together clinical praxis with neuroscience methods. In this review article, the focus will be on functional neuroimaging (fMRI) and its applicability in clinical fMRI studies. In the light of the "replication crisis," three aspects will be critically discussed: First, the fMRI signal itself, second, current fMRI praxis, and, third, the next generation of analysis strategies. Current attempts such as resting-state fMRI, meta-analyses, and machine learning will be discussed with their advantages and potential pitfalls and disadvantages. One major concern is that the fMRI signal shows substantial within- and between-subject variability, which affects the reliability of both task-related, but in particularly resting-state fMRI studies. Furthermore, the lack of standardized acquisition and analysis methods hinders the further development of clinical relevant approaches. However, meta-analyses and machine-learning approaches may help to overcome current shortcomings in the methods by identifying new, and yet hidden relationships, and may help to build new models on disorder mechanisms. Furthermore, better control of parameters that may have an influence on the fMRI signal and that can easily be controlled for, like blood pressure, heart rate, diet, time of day, might improve reliability substantially.

Test-retest reliability of brain responses to risk-taking during the balloon analogue risk task

The Balloon Analogue Risk Task (BART) provides a reliable and ecologically valid model for the assessment of individual risk-taking propensity and is frequently used in neuroimaging and developmental research. Although the test-retest reliability of risk-taking behavior during the BART is well established, the reliability of brain activation patterns in response to risk-taking during the BART remains elusive. In this study, we used functional magnetic resonance imaging (fMRI) and evaluated the test-retest reliability of brain responses in 34 healthy adults during a modified BART by calculating the intraclass correlation coefficients (ICC) and Dice’s similarity coefficients (DSC). Analyses revealed that risk-induced brain activation patterns showed good test-retest reliability (median ICC = 0.62) and moderate to high spatial consistency, while brain activation patterns associated with win or loss outcomes only had poor to fair reliability (median ICC = 0.33 for win and 0.42 for loss). These findings have important implications for future utility of the BART in fMRI to examine brain responses to risk-taking and decision-making.

Test-retest reliability in an fMRI study of naming in dementia

fMRI has been used as an outcome measure in dementia treatment studies, with many previous studies comparing only single pre- and post-treatment fMRI scans to determine treatment-induced neural changes, while utilizing single subject experimental designs. The purpose of the current study was to evaluate fMRI test-retest reliability in dementia patients and typical older adults using noun and verb confrontation naming to evaluate the validity of using a single pre/post-treatment scan comparison. Seven individuals with dementia and 9 control participants were tested three times over two months using the same fMRI procedures. Differences in individual and group level activation patterns were observed that varied across time. Additionally, the extent of variability fluctuated across individuals, groups, and the grammatical category of target words. Our findings suggested that one time fMRI scanning may inadequately represent an individual's typical brain activation pattern, particularly an individual with dementia. Thus, multiple imaging baselines are recommended.

Prevalence and function of Heschl's gyrus morphotypes in musicians

Morphological variations of the first transverse Heschl's gyrus (HG) in the human auditory cortex (AC) are common, yet little is known about their functional implication. We investigated individual morphology and function of HG variations in the AC of 41 musicians, using structural and functional magnetic resonance imaging (fMRI) as well as magnetoencephalography (MEG). Four main morphotypes of HG were (i) single HG, (ii) common stem duplication (CSD), (iii) complete posterior duplication (CPD), and (iv) multiple duplications (MD). The vast majority of musicians (90%) exhibited HG multiplications (type ii-iv) in either one (39%) or both (51%) hemispheres. In 27% of musicians, MD with up to four gyri were found. To probe the functional contribution of HG multiplications to auditory processing we performed fMRI and MEG with auditory stimulation using analogous instrumental tone paradigms. Both methods pointed to the recruitment of all parts of HG during auditory stimulation, including multiplications if present. FMRI activations extended with the degree of HG gyrification. MEG source waveform patterns were distinct for the different types of HG: (i) hemispheres with single HG and (ii) CSD exhibited dominant N1 responses, whereas hemispheres with (iii) CPD and (iv) MD exhibited dominant P1 responses. N1 dipole amplitudes correlated with the localization of the first complete Heschl's sulcus (cHS), designating the most posterior anatomical border of HG. P2 amplitudes were significantly higher in professional as compared to amateur musicians. The results suggest that HG multiplications occur much more frequently in musicians than in the general population and constitute a functional unit with HG.

Test-retest reliability of functional connectivity networks during naturalistic fMRI paradigms

Functional connectivity analysis has become a powerful tool for probing the human brain function and its breakdown in neuropsychiatry disorders. So far, most studies adopted resting-state paradigm to examine functional connectivity networks in the brain, thanks to its low demand and high tolerance that are essential for clinical studies. However, the test-retest reliability of resting-state connectivity measures is moderate, potentially due to its low behavioral constraint. On the other hand, naturalistic neuroimaging paradigms, an emerging approach for cognitive neuroscience with high ecological validity, could potentially improve the reliability of functional connectivity measures. To test this hypothesis, we characterized the test-retest reliability of functional connectivity measures during a natural viewing condition, and benchmarked it against resting-state connectivity measures acquired within the same functional magnetic resonance imaging (fMRI) session. We found that the reliability of connectivity and graph theoretical measures of brain networks is significantly improved during natural viewing conditions over resting-state conditions, with an average increase of almost 50% across various connectivity measures. Not only sensory networks for audio-visual processing become more reliable, higher order brain networks, such as default mode and attention networks, but also appear to show higher reliability during natural viewing. Our results support the use of natural viewing paradigms in estimating functional connectivity of brain networks, and have important implications for clinical application of fMRI. Hum Brain Mapp 38:2226-2241, 2017. © 2017 Wiley Periodicals, Inc.

Characterizing and differentiating task-based and resting state fMRI signals via two-stage sparse representations

A relatively underexplored question in fMRI is whether there are intrinsic differences in terms of signal composition patterns that can effectively characterize and differentiate task-based or resting state fMRI (tfMRI or rsfMRI) signals. In this paper, we propose a novel two-stage sparse representation framework to examine the fundamental difference between tfMRI and rsfMRI signals. Specifically, in the first stage, the whole-brain tfMRI or rsfMRI signals of each subject were composed into a big data matrix, which was then factorized into a subject-specific dictionary matrix and a weight coefficient matrix for sparse representation. In the second stage, all of the dictionary matrices from both tfMRI/rsfMRI data across multiple subjects were composed into another big data-matrix, which was further sparsely represented by a cross-subjects common dictionary and a weight matrix. This framework has been applied on the recently publicly released Human Connectome Project (HCP) fMRI data and experimental results revealed that there are distinctive and descriptive atoms in the cross-subjects common dictionary that can effectively characterize and differentiate tfMRI and rsfMRI signals, achieving 100% classification accuracy. Moreover, our methods and results can be meaningfully interpreted, e.g., the well-known default mode network (DMN) activities can be recovered from the very noisy and heterogeneous aggregated big-data of tfMRI and rsfMRI signals across all subjects in HCP Q1 release.

Variance decomposition for single-subject task-based fMRI activity estimates across many sessions

Here we report an exploratory within-subject variance decomposition analysis conducted on a task-based fMRI dataset with an unusually large number of repeated measures (i.e., 500 trials in each of three different subjects) distributed across 100 functional scans and 9 to 10 different sessions. Within-subject variance was segregated into four primary components: variance across-sessions, variance across-runs within a session, variance across-blocks within a run, and residual measurement/modeling error. Our results reveal inhomogeneous and distinct spatial distributions of these variance components across significantly active voxels in grey matter. Measurement error is dominant across the whole brain. Detailed evaluation of the remaining three components shows that across-session variance is the second largest contributor to total variance in occipital cortex, while across-runs variance is the second dominant source for the rest of the brain. Network-specific analysis revealed that across-block variance contributes more to total variance in higher-order cognitive networks than in somatosensory cortex. Moreover, in some higher-order cognitive networks across-block variance can exceed across-session variance. These results help us better understand the temporal (i.e., across blocks, runs and sessions) and spatial distributions (i.e., across different networks) of within-subject natural variability in estimates of task responses in fMRI. They also suggest that different brain regions will show different natural levels of test-retest reliability even in the absence of residual artifacts and sufficiently high contrast-to-noise measurements. Further confirmation with a larger sample of subjects and other tasks is necessary to ensure generality of these results.

Visualising inter-subject variability in fMRI using threshold-weighted overlap maps

Functional neuroimaging studies are revealing the neural systems sustaining many sensory, motor and cognitive abilities. A proper understanding of these systems requires an appreciation of the degree to which they vary across subjects. Some sources of inter-subject variability might be easy to measure (demographics, behavioural scores, or experimental factors), while others are more difficult (cognitive strategies, learning effects, and other hidden sources). Here, we introduce a simple way of visualising whole-brain consistency and variability in brain responses across subjects using threshold-weighted voxel-based overlap maps. The output quantifies the proportion of subjects activating a particular voxel or region over a wide range of statistical thresholds. The sensitivity of our approach was assessed in 30 healthy adults performing a matching task with their dominant hand. We show how overlap maps revealed many effects that were only present in a subsample of our group; we discuss how overlap maps can provide information that may be missed or misrepresented by standard group analysis, and how this information can help users to understand their data. In particular, we emphasize that functional overlap maps can be particularly useful when it comes to explaining typical (or atypical) compensatory mechanisms used by patients following brain damage.

Post-Surgical Language Reorganization Occurs in Tumors of the Dominant and Non-Dominant Hemisphere

PURPOSE

Surgical resection of brain tumors may shift the location of cortical language areas. Studies of language reorganization primarily investigated left-hemispheric tumors irrespective of hemispheric language dominance. We used functional magnetic resonance imaging (fMRI) to investigate how tumors influence post-surgical language reorganization in relation to the dominant language areas.

METHODS

A total of, 17 patients with brain tumors (16 gliomas, one metastasis) in the frontotemporal and lower parietal lobes planned for awake surgery underwent pre-surgical and post-surgical language fMRI. Language activation post-to-pre surgery was evaluated visually and quantitatively on the statistically thresholded images on patient-by-patient basis. Results were qualitatively compared between three patient groups: temporal, with tumors in the dominant temporal lobe, frontal, with tumors in the dominant frontal lobe and remote, with tumors in the non-dominant hemisphere.

RESULTS

Post-to-pre-surgical distributions of activated voxels changed in all except the one patient with metastasis. Changes were more pronounced in the dominant hemisphere for all three groups, showing increased number of activated voxels and also new activation areas. Tumor resection in the dominant hemisphere (frontal and temporal) shifted the activation from frontal towards temporal, whereas tumor resection in the non-dominant hemisphere shifted the activation from temporal towards frontal dominant areas.

CONCLUSION

Resection of gliomas in the dominant and in the non-dominant hemisphere induces postsurgical shifts and increase in language activation, indicating that infiltrating gliomas have a widespread influence on the language network. The dominant hemisphere gained most of the language activation irrespective of tumor localization, possibly reflecting recovery of pre-surgical tumor-induced suppression of these activations.

Test-retest reliability of effective connectivity in the face perception network

Computational approaches have great potential for moving neuroscience toward mechanistic models of the functional integration among brain regions. Dynamic causal modeling (DCM) offers a promising framework for inferring the effective connectivity among brain regions and thus unraveling the neural mechanisms of both normal cognitive function and psychiatric disorders. While the benefit of such approaches depends heavily on their reliability, systematic analyses of the within-subject stability are rare. Here, we present a thorough investigation of the test-retest reliability of an fMRI paradigm for DCM analysis dedicated to unraveling intra- and interhemispheric integration among the core regions of the face perception network. First, we examined the reliability of face-specific BOLD activity in 25 healthy volunteers, who performed a face perception paradigm in two separate sessions. We found good to excellent reliability of BOLD activity within the DCM-relevant regions. Second, we assessed the stability of effective connectivity among these regions by analyzing the reliability of Bayesian model selection and model parameter estimation in DCM. Reliability was excellent for the negative free energy and good for model parameter estimation, when restricting the analysis to parameters with substantial effect sizes. Third, even when the experiment was shortened, reliability of BOLD activity and DCM results dropped only slightly as a function of the length of the experiment. This suggests that the face perception paradigm presented here provides reliable estimates for both conventional activation and effective connectivity measures. We conclude this paper with an outlook on potential clinical applications of the paradigm for studying psychiatric disorders. Hum Brain Mapp 37:730-744, 2016. © 2015 Wiley Periodicals, Inc.

The reliability of continuous brain responses during naturalistic listening to music

Low-level (timbral) and high-level (tonal and rhythmical) musical features during continuous listening to music, studied by functional magnetic resonance imaging (fMRI), have been shown to elicit large-scale responses in cognitive, motor, and limbic brain networks. Using a similar methodological approach and a similar group of participants, we aimed to study the replicability of previous findings. Participants' fMRI responses during continuous listening of a tango Nuevo piece were correlated voxelwise against the time series of a set of perceptually validated musical features computationally extracted from the music. The replicability of previous results and the present study was assessed by two approaches: (a) correlating the respective activation maps, and (b) computing the overlap of active voxels between datasets at variable levels of ranked significance. Activity elicited by timbral features was better replicable than activity elicited by tonal and rhythmical ones. These results indicate more reliable processing mechanisms for low-level musical features as compared to more high-level features. The processing of such high-level features is probably more sensitive to the state and traits of the listeners, as well as of their background in music.

Quantitative assessment of visual cortex function with fMRI at 7 Tesla-test-retest variability

fMRI-based retinotopic mapping was used to assess systematic variations in activated cortical surface area, amplitude, and coherence across sessions. Seven healthy subjects were scanned at 7 T in three separate sessions with intervals of 51.4 ± 5.4 days (Sessions 1 and 2) and 167.9 ± 24.4 days (Sessions 2 and 3). We found a reduction between Sessions 1 and 2 for activated cortical surface area, between Sessions 1 and 3 for amplitude, and between Sessions 1 and 2/3 for coherence. The results do not support head motion as a major cause of the observed effect seen in Session 1, suggesting that cognitive effects were the underlying cause of change. The phase correlations for both eccentricity and polar angle mapping were highly correlated between sessions, demonstrating the stability of the maps. Furthermore, the sensitivity in determining inter-session changes of cortical surface area, response amplitude, and coherence were, at a 5% significance level, estimated to be 1.5, 6, and 5%, respectively. Any future longitudinal fMRI study should carefully evaluate activation across sessions to determine the eligibility of inclusion of all time points. This experimental design provides guidance in methodological issues of clinical longitudinal fMRI-studies, specifically regarding effects of subject experience.

The relationship between the neural computations for speech and music perception is context-dependent: an activation likelihood estimate study

The relationship between the neurobiology of speech and music has been investigated for more than a century. There remains no widespread agreement regarding how (or to what extent) music perception utilizes the neural circuitry that is engaged in speech processing, particularly at the cortical level. Prominent models such as Patel's Shared Syntactic Integration Resource Hypothesis (SSIRH) and Koelsch's neurocognitive model of music perception suggest a high degree of overlap, particularly in the frontal lobe, but also perhaps more distinct representations in the temporal lobe with hemispheric asymmetries. The present meta-analysis study used activation likelihood estimate analyses to identify the brain regions consistently activated for music as compared to speech across the functional neuroimaging (fMRI and PET) literature. Eighty music and 91 speech neuroimaging studies of healthy adult control subjects were analyzed. Peak activations reported in the music and speech studies were divided into four paradigm categories: passive listening, discrimination tasks, error/anomaly detection tasks and memory-related tasks. We then compared activation likelihood estimates within each category for music vs. speech, and each music condition with passive listening. We found that listening to music and to speech preferentially activate distinct temporo-parietal bilateral cortical networks. We also found music and speech to have shared resources in the left pars opercularis but speech-specific resources in the left pars triangularis. The extent to which music recruited speech-activated frontal resources was modulated by task. While there are certainly limitations to meta-analysis techniques particularly regarding sensitivity, this work suggests that the extent of shared resources between speech and music may be task-dependent and highlights the need to consider how task effects may be affecting conclusions regarding the neurobiology of speech and music.

An Automated, Adaptive Framework for Optimizing Preprocessing Pipelines in Task-Based Functional MRI

BOLD fMRI is sensitive to blood-oxygenation changes correlated with brain function; however, it is limited by relatively weak signal and significant noise confounds. Many preprocessing algorithms have been developed to control noise and improve signal detection in fMRI. Although the chosen set of preprocessing and analysis steps (the “pipeline”) significantly affects signal detection, pipelines are rarely quantitatively validated in the neuroimaging literature, due to complex preprocessing interactions. This paper outlines and validates an adaptive resampling framework for evaluating and optimizing preprocessing choices by optimizing data-driven metrics of task prediction and spatial reproducibility. Compared to standard “fixed” preprocessing pipelines, this optimization approach significantly improves independent validation measures of within-subject test-retest, and between-subject activation overlap, and behavioural prediction accuracy. We demonstrate that preprocessing choices function as implicit model regularizers, and that improvements due to pipeline optimization generalize across a range of simple to complex experimental tasks and analysis models. Results are shown for brief scanning sessions (<3 minutes each), demonstrating that with pipeline optimization, it is possible to obtain reliable results and brain-behaviour correlations in relatively small datasets.

Accounting for Dynamic Fluctuations across Time when Examining fMRI Test-Retest Reliability: Analysis of a Reward Paradigm in the EMBARC Study

Longitudinal investigation of the neural correlates of reward processing in depression may represent an important step in defining effective biomarkers for antidepressant treatment outcome prediction, but the reliability of reward-related activation is not well understood. Thirty-seven healthy control participants were scanned using fMRI while performing a reward-related guessing task on two occasions, approximately one week apart. Two main contrasts were examined: right ventral striatum (VS) activation fMRI BOLD signal related to signed prediction errors (PE) and reward expectancy (RE). We also examined bilateral visual cortex activation coupled to outcome anticipation. Significant VS PE-related activity was observed at the first testing session, but at the second testing session, VS PE-related activation was significantly reduced. Conversely, significant VS RE-related activity was observed at time 2 but not time 1. Increases in VS RE-related activity from time 1 to time 2 were significantly associated with decreases in VS PE-related activity from time 1 to time 2 across participants. Intraclass correlations (ICCs) in VS were very low. By contrast, visual cortex activation had much larger ICCs, particularly in individuals with high quality data. Dynamic changes in brain activation are widely predicted, and failure to account for these changes could lead to inaccurate evaluations of the reliability of functional MRI signals. Conventional measures of reliability cannot distinguish between changes specified by algorithmic models of neural function and noisy signal. Here, we provide evidence for the former possibility: reward-related VS activations follow the pattern predicted by temporal difference models of reward learning but have low ICCs.

A Study of Long-Term fMRI Reproducibility Using Data-Driven Analysis Methods

The reproducibility of functional magnetic resonance imaging (fMRI) is important for fMRI-based neuroscience research and clinical applications. Previous studies show considerable variation in amplitude and spatial extent of fMRI activation across repeated sessions on individual subjects even using identical experimental paradigms and imaging conditions. Most existing fMRI reproducibility studies were typically limited by time duration and data analysis techniques. Particularly, the assessment of reproducibility is complicated by a fact that fMRI results may depend on data analysis techniques used in reproducibility studies. In this work, the long-term fMRI reproducibility was investigated with a focus on the data analysis methods. Two spatial smoothing techniques, including a wavelet-domain Bayesian method and the Gaussian smoothing, were evaluated in terms of their effects on the long-term reproducibility. A multivariate support vector machine (SVM)-based method was used to identify active voxels, and compared to a widely used general linear model (GLM)-based method at the group level. The reproducibility study was performed using multisession fMRI data acquired from eight healthy adults over 1.5 years' period of time. Three regions-of-interest (ROI) related to a motor task were defined based upon which the long-term reproducibility were examined. Experimental results indicate that different spatial smoothing techniques may lead to different reproducibility measures, and the wavelet-based spatial smoothing and SVM-based activation detection is a good combination for reproducibility studies. On the basis of the ROIs and multiple numerical criteria, we observed a moderate to substantial within-subject long-term reproducibility. A reasonable long-term reproducibility was also observed from the inter-subject study. It was found that the short-term reproducibility is usually higher than the long-term reproducibility. Furthermore, the results indicate that brain regions with high contrast-to-noise ratio do not necessarily exhibit high reproducibility. These findings may provide supportive information for optimal design/implementation of fMRI studies and data interpretation.

Resting states are resting traits--an FMRI study of sex differences and menstrual cycle effects in resting state cognitive control networks

To what degree resting state fMRI is stable or susceptible to internal mind states of the individual is currently an issue of debate. To address this issue, the present study focuses on sex differences and investigates whether resting state fMRI is stable in men and women or changes within relative short-term periods (i.e., across the menstrual cycle). Due to the fact that we recently reported menstrual cycle effects on cognitive control based on data collected during the same sessions, the current study is particularly interested in fronto-parietal resting state networks. Resting state fMRI was measured in sixteen women during three different cycle phases (menstrual, follicular, and luteal). Fifteen men underwent three sessions in corresponding time intervals. We used independent component analysis to identify four fronto-parietal networks. The results showed sex differences in two of these networks with women exhibiting higher functional connectivity in general, including the prefrontal cortex. Menstrual cycle effects on resting states were non-existent. It is concluded that sex differences in resting state fMRI might reflect sexual dimorphisms in the brain rather than transitory activating effects of sex hormones on the functional connectivity in the resting brain.

The timing and directional connectivity of human frontoparietal and ventral visual attention networks in emotional scene perception

Electrocortical and hemodynamic measures reliably identify enhanced activity in the ventral and dorsal visual cortices during the perception of emotionally arousing versus neutral images, an effect that may reflect directive feedback from the subcortical amygdala. However, other brain regions strongly modulate visual attention, such as frontal eye fields (FEF) and intraparietal sulcus (IPS). Here we employ rapid sampling of BOLD signal (4 Hz) in the amygdala, fusiform gyrus (FG), FEF and IPS in 42 human participants as they viewed a series of emotional and neutral natural scene photographs balanced for luminosity and complexity, to test whether emotional discrimination is evident in dorsal structures prior to such discrimination in the amygdala and FG. Granger causality analyses were used to assess directional connectivity within dorsal and ventral networks. Results demonstrate emotionally-enhanced peak BOLD signal in the amygdala, FG, FEF, and IPS, with the onset of BOLD signal discrimination occurring between 2 and 3s after stimulus onset in ventral structures, and between 4 and 5s in FEF and IPS. Granger causality estimates yield stronger directional connectivity from IPS to FEF than the reverse in this emotional picture paradigm. Consistent with a reentrant perspective of emotional scene perception, greater directional connectivity was found from the amygdala to FG compared to the reverse. These data support a perspective in which the registration of emotional scene content is orchestrated by the amygdala and rostral inferotemporal visual cortex.

Task-modulated coactivation of vergence neural substrates

While functional magnetic resonance imaging (fMRI) has identified which regions of interests (ROIs) are functionally active during a vergence movement (inward or outward eye rotation), task-modulated coactivation between ROIs is less understood. This study tested the following hypotheses: (1) significant task-modulated coactivation would be observed between the frontal eye fields (FEFs), the posterior parietal cortex (PPC), and the cerebellar vermis (CV); (2) significantly more functional activity and task-modulated coactivation would be observed in binocularly normal controls (BNCs) compared with convergence insufficiency (CI) subjects; and (3) after vergence training, the functional activity and task-modulated coactivation would increase in CIs compared with their baseline measurements. A block design of sustained fixation versus vergence eye movements stimulated activity in the FEFs, PPC, and CV. fMRI data from four CI subjects before and after vergence training were compared with seven BNCs. Functional activity was assessed using the blood oxygenation level dependent (BOLD) percent signal change. Task-modulated coactivation was assessed using an ROI-based task-modulated coactivation analysis that revealed significant correlation between the FEF, PPC, and CV ROIs. Prior to vergence training, the CIs had a reduced BOLD percent signal change compared with BNCs for the CV (p<0.05), FEFs, and PPC (p<0.01). The BOLD percent signal change increased within the CV, FEF, and PPC ROIs (p<0.001) as did the task-modulated coactivation between the FEFs and CV as well as the PPC and CV (p<0.05) when comparing the CI pre- and post-training datasets. Results from the Convergence Insufficiency Symptom Survey were correlated to the percent BOLD signal change from the FEFs and CV (p<0.05).

Reliability measures of functional magnetic resonance imaging in a longitudinal evaluation of mild cognitive impairment

As the aging population grows, it has become increasingly important to carefully characterize amnestic mild cognitive impairment (aMCI), a preclinical stage of Alzheimer's disease (AD). Functional magnetic resonance imaging (fMRI) is a valuable tool for monitoring disease progression in selectively vulnerable brain regions associated with AD neuropathology. However, the reliability of fMRI data in longitudinal studies of older adults with aMCI is largely unexplored. To address this, aMCI participants completed two visual working tasks, a Delayed-Recognition task and a One-Back task, on three separate scanning sessions over a three-month period. Test-retest reliability of the fMRI blood oxygen level dependent (BOLD) activity was assessed using an intraclass correlation (ICC) analysis approach. Results indicated that brain regions engaged during the task displayed greater reliability across sessions compared to regions that were not utilized by the task. During task-engagement, differential reliability scores were observed across the brain such that the frontal lobe, medial temporal lobe, and subcortical structures exhibited fair to moderate reliability (ICC=0.3-0.6), while temporal, parietal, and occipital regions exhibited moderate to good reliability (ICC=0.4-0.7). Additionally, reliability across brain regions was more stable when three fMRI sessions were used in the ICC calculation relative to two fMRI sessions. In conclusion, the fMRI BOLD signal is reliable across scanning sessions in this population and thus a useful tool for tracking longitudinal change in observational and interventional studies in aMCI.

Affective traits link to reliable neural markers of incentive anticipation

While theorists have speculated that different affective traits are linked to reliable brain activity during anticipation of gains and losses, few have directly tested this prediction. We examined these associations in a community sample of healthy human adults (n=52) as they played a Monetary Incentive Delay task while undergoing functional magnetic resonance imaging (FMRI). Factor analysis of personality measures revealed that subjects independently varied in trait Positive Arousal and trait Negative Arousal. In a subsample (n=14) retested over 2.5years later, left nucleus accumbens (NAcc) activity during anticipation of large gains (+$5.00) and right anterior insula activity during anticipation of large losses (-$5.00) showed significant test-retest reliability (intraclass correlations>0.50, p's<0.01). In the full sample (n=52), trait Positive Arousal correlated with individual differences in left NAcc activity during anticipation of large gains, while trait Negative Arousal correlated with individual differences in right anterior insula activity during anticipation of large losses. Associations of affective traits with neural activity were not attributable to the influence of other potential confounds (including sex, age, wealth, and motion). Together, these results demonstrate selective links between distinct affective traits and reliably-elicited activity in neural circuits associated with anticipation of gain versus loss. The findings thus reveal neural markers for affective dimensions of healthy personality, and potentially for related psychiatric symptoms.

Mapping a lateralization gradient within the ventral stream for auditory speech perception

Recent models on speech perception propose a dual-stream processing network, with a dorsal stream, extending from the posterior temporal lobe of the left hemisphere through inferior parietal areas into the left inferior frontal gyrus, and a ventral stream that is assumed to originate in the primary auditory cortex in the upper posterior part of the temporal lobe and to extend toward the anterior part of the temporal lobe, where it may connect to the ventral part of the inferior frontal gyrus. This article describes and reviews the results from a series of complementary functional magnetic resonance imaging studies that aimed to trace the hierarchical processing network for speech comprehension within the left and right hemisphere with a particular focus on the temporal lobe and the ventral stream. As hypothesized, the results demonstrate a bilateral involvement of the temporal lobes in the processing of speech signals. However, an increasing leftward asymmetry was detected from auditory-phonetic to lexico-semantic processing and along the posterior-anterior axis, thus forming a "lateralization" gradient. This increasing leftward lateralization was particularly evident for the left superior temporal sulcus and more anterior parts of the temporal lobe.

Enhanced sympathetic arousal in response to FMRI scanning correlates with task induced activations and deactivations

It has been repeatedly shown that functional magnetic resonance imaging (fMRI) triggers distress and neuroendocrine response systems. Prior studies have revealed that sympathetic arousal increases, particularly at the beginning of the examination. Against this background it appears likely that those stress reactions during the scanning procedure may influence task performance and neural correlates. However, the question how sympathetic arousal elicited by the scanning procedure itself may act as a potential confounder of fMRI data remains unresolved today. Thirty-seven scanner naive healthy subjects performed a simple cued target detection task. Levels of salivary alpha amylase (sAA), as a biomarker for sympathetic activity, were assessed in samples obtained at several time points during the lab visit. SAA increased two times, immediately prior to scanning and at the end of the scanning procedure. Neural activation related to motor preparation and timing as well as task performance was positively correlated with the first increase. Furthermore, the first sAA increase was associated with task induced deactivation (TID) in frontal and parietal regions. However, these effects were restricted to the first part of the experiment. Consequently, this bias of scanner related sympathetic activation should be considered in future fMRI investigations. It is of particular importance for pharmacological investigations studying adrenergic agents and the comparison of groups with different stress vulnerabilities like patients and controls or adolescents and adults.

Characterization of task-free and task-performance brain states via functional connectome patterns

Both resting state fMRI (R-fMRI) and task-based fMRI (T-fMRI) have been widely used to study the functional activities of the human brain during task-free and task-performance periods, respectively. However, due to the difficulty in strictly controlling the participating subject's mental status and their cognitive behaviors during R-fMRI/T-fMRI scans, it has been challenging to ascertain whether or not an R-fMRI/T-fMRI scan truly reflects the participant's functional brain states during task-free/task-performance periods. This paper presents a novel computational approach to characterizing and differentiating the brain's functional status into task-free or task-performance states, by which the functional brain activities can be effectively understood and differentiated. Briefly, the brain's functional state is represented by a whole-brain quasi-stable connectome pattern (WQCP) of R-fMRI or T-fMRI data based on 358 consistent cortical landmarks across individuals, and then an effective sparse representation method was applied to learn the atomic connectome patterns (ACPs) of both task-free and task-performance states. Experimental results demonstrated that the learned ACPs for R-fMRI and T-fMRI datasets are substantially different, as expected. A certain portion of ACPs from R-fMRI and T-fMRI data were overlapped, suggesting some subjects with overlapping ACPs were not in the expected task-free/task-performance brain states. Besides, potential outliers in the T-fMRI dataset were further investigated via functional activation detections in different groups, and our results revealed unexpected task-performances of some subjects. This work offers novel insights into the functional architectures of the brain.

Neural correlates of adaptation in freely-moving normal hearing subjects under cochlear implant acoustic simulations

Neurobiological correlates of adaptation to spectrally degraded speech were investigated with fMRI before and after exposure to a portable real-time speech processor that implements an acoustic simulation model of a cochlear implant (CI). The speech processor, in conjunction with isolating insert earphones and a microphone to capture environment sounds, was worn by participants over a two week chronic exposure period. fMRI and behavioral speech comprehension testing were conducted before and after this two week period. After using the simulator each day for 2h, participants significantly improved in word and sentence recognition scores. fMRI shows that these improvements came accompanied by changes in patterns of neuronal activation. In particular, we found additional recruitment of visual, motor, and working memory areas after the perceptual training period. These findings suggest that the human brain is able to adapt in a short period of time to a degraded auditory signal under a natural learning environment, and gives insight on how a CI might interact with the central nervous system. This paradigm can be furthered to investigate neural correlates of new rehabilitation, training, and signal processing strategies non-invasively in normal hearing listeners to improve CI patient outcomes.

False positive control of activated voxels in single fMRI analysis using bootstrap resampling in comparison to spatial smoothing

Functional magnetic resonance imaging (fMRI) is an effective tool for the measurement of brain neuronal activities. To date, several statistical methods have been proposed for analyzing fMRI datasets to select true active voxels among all the voxels appear to be positively activated. Finding a reliable and valid activation map is very important and becomes more crucial in clinical and neurosurgical investigations of single fMRI data, especially when pre-surgical planning requires accurate lateralization index as well as a precise localization of activation map. Defining a proper threshold to determine true activated regions, using common statistical processes, is a challenging task. This is due to a number of variation sources such as noise, artifacts, and physiological fluctuations in time series of fMRI data which affect spatial distribution of noise in an expected uniform activated region. Spatial smoothing methods are frequently used as a preprocessing step to reduce the effect of noise and artifacts. The smoothing may lead to a shift and enlargement of activation regions, and in some extend, unification of distinct regions. In this article, we propose a bootstrap resampling technique for analyzing single fMRI dataset with the aim of finding more accurate and reliable activated regions. This method can remove false positive voxels and present high localization accuracy in activation map without any spatial smoothing and statistical threshold setting.

Quantifying the test-retest reliability of cerebral blood flow measurements in a clinical model of on-going post-surgical pain: A study using pseudo-continuous arterial spin labelling

Arterial spin labelling (ASL) is increasingly being applied to study the cerebral response to pain in both experimental human models and patients with persistent pain. Despite its advantages, scanning time and reliability remain important issues in the clinical applicability of ASL. Here we present the test–retest analysis of concurrent pseudo-continuous ASL (pCASL) and visual analogue scale (VAS), in a clinical model of on-going pain following third molar extraction (TME). Using ICC performance measures, we were able to quantify the reliability of the post-surgical pain state and ΔCBF (change in CBF), both at the group and individual case level. Within-subject, the inter- and intra-session reliability of the post-surgical pain state was ranked good-to-excellent (ICC > 0.6) across both pCASL and VAS modalities. The parameter ΔCBF (change in CBF between pre- and post-surgical states) performed reliably (ICC > 0.4), provided that a single baseline condition (or the mean of more than one baseline) was used for subtraction. Between-subjects, the pCASL measurements in the post-surgical pain state and ΔCBF were both characterised as reliable (ICC > 0.4). However, the subjective VAS pain ratings demonstrated a significant contribution of pain state variability, which suggests diminished utility for interindividual comparisons. These analyses indicate that the pCASL imaging technique has considerable potential for the comparison of within- and between-subjects differences associated with pain-induced state changes and baseline differences in regional CBF. They also suggest that differences in baseline perfusion and functional lateralisation characteristics may play an important role in the overall reliability of the estimated changes in CBF. Repeated measures designs have the important advantage that they provide good reliability for comparing condition effects because all sources of variability between subjects are excluded from the experimental error. The ability to elicit reliable neural correlates of on-going pain using quantitative perfusion imaging may help support the conclusions derived from subjective self-report.

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Test-retest reliability of pCASL is considered in a post-surgical pain model.

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Pain-state and ∆CBF measurements were reliable at the group and individual level.

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Single or average baseline measurements improve reliability of ∆CBF.

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pCASL is a reliable technique for detecting cerebral responses to on-going pain.

Task and task-free FMRI reproducibility comparison for motor network identification

Test-retest reliability of individual functional magnetic resonance imaging (fMRI) results is of importance in clinical practice and longitudinal experiments. While several studies have investigated reliability of task-induced motor network activation, less is known about the reliability of the task-free motor network. Here, we investigate the reproducibility of task-free fMRI, and compare it to motor task activity. Sixteen healthy subjects participated in this study with a test-retest interval of seven weeks. The task-free motor network was assessed with a univariate, seed-voxel-based correlation analysis. Reproducibility was tested by means of intraclass correlation (ICC) values and ratio of overlap. Higher ICC values and a better overlap were found for task fMRI as compared to task-free fMRI. Furthermore, ratio of overlap improved for task fMRI at higher thresholds, while it decreased for task-free fMRI, suggesting a less focal spatial pattern of the motor network during resting state. However, for both techniques the most active voxels were located in the primary motor cortex. This indicates that, just like task fMRI, task-free fMRI can properly identify critical brain areas for motor task performance. Although both fMRI techniques are able to detect the motor network, resting-state fMRI is less reliable than task fMRI.

Functional neuroimaging of treatment effects in psychiatry: methodological challenges and recommendations

Functional magnetic resonance imaging (fMRI) has helped to elucidate the neurobiological bases of psychiatric and neurodevelopmental disorders by localizing etiologically-relevant aberrations in brain function. Functional MRI also has shown great promise to help understand potential mechanisms of action of effective treatments for a range of psychiatric and neurodevelopmental disorders, including mood and anxiety disorders, schizophrenia, and autism. However, the use of fMRI to probe intervention effects in psychiatry is associated with unique methodological considerations, including the psychometric properties of repeated fMRI scans, how to assess potential relations between the effects of an intervention on symptoms and on specific brain activation patterns, and how to best make causal inferences about intervention effects on brain function. Additionally, the study of treatment effects in neurodevelopmental disorders presents additional unique challenges related to brain maturation, analysis methods, and the potential for motion artifacts. We review these methodological considerations and provide recommendations for best practices for each of these topics.

An iterative jackknife approach for assessing reliability and power of FMRI group analyses

For functional magnetic resonance imaging (fMRI) group activation maps, so-called second-level random effect approaches are commonly used, which are intended to be generalizable to the population as a whole. However, reliability of a certain activation focus as a function of group composition or group size cannot directly be deduced from such maps. This question is of particular relevance when examining smaller groups (<20–27 subjects). The approach presented here tries to address this issue by iteratively excluding each subject from a group study and presenting the overlap of the resulting (reduced) second-level maps in a group percent overlap map. This allows to judge where activation is reliable even upon excluding one, two, or three (or more) subjects, thereby also demonstrating the inherent variability that is still present in second-level analyses. Moreover, when progressively decreasing group size, foci of activation will become smaller and/or disappear; hence, the group size at which a given activation disappears can be considered to reflect the power necessary to detect this particular activation. Systematically exploiting this effect allows to rank clusters according to their observable effect size. The approach is tested using different scenarios from a recent fMRI study (children performing a “dual-use” fMRI task, n = 39), and the implications of this approach are discussed.

Test-retest reliability of evoked BOLD signals from a cognitive-emotive fMRI test battery

Even more than in cognitive research applications, moving fMRI to the clinic and the drug development process requires the generation of stable and reliable signal changes. The performance characteristics of the fMRI paradigm constrain experimental power and may require different study designs (e.g., crossover vs. parallel groups), yet fMRI reliability characteristics can be strongly dependent on the nature of the fMRI task. The present study investigated both within-subject and group-level reliability of a combined three-task fMRI battery targeting three systems of wide applicability in clinical and cognitive neuroscience: an emotional (face matching), a motivational (monetary reward anticipation) and a cognitive (n-back working memory) task. A group of 25 young, healthy volunteers were scanned twice on a 3T MRI scanner with a mean test-retest interval of 14.6 days. FMRI reliability was quantified using the intraclass correlation coefficient (ICC) applied at three different levels ranging from a global to a localized and fine spatial scale: (1) reliability of group-level activation maps over the whole brain and within targeted regions of interest (ROIs); (2) within-subject reliability of ROI-mean amplitudes and (3) within-subject reliability of individual voxels in the target ROIs. Results showed robust evoked activation of all three tasks in their respective target regions (emotional task=amygdala; motivational task=ventral striatum; cognitive task=right dorsolateral prefrontal cortex and parietal cortices) with high effect sizes (ES) of ROI-mean summary values (ES=1.11-1.44 for the faces task, 0.96-1.43 for the reward task, 0.83-2.58 for the n-back task). Reliability of group level activation was excellent for all three tasks with ICCs of 0.89-0.98 at the whole brain level and 0.66-0.97 within target ROIs. Within-subject reliability of ROI-mean amplitudes across sessions was fair to good for the reward task (ICCs=0.56-0.62) and, dependent on the particular ROI, also fair-to-good for the n-back task (ICCs=0.44-0.57) but lower for the faces task (ICC=-0.02-0.16). In conclusion, all three tasks are well suited to between-subject designs, including imaging genetics. When specific recommendations are followed, the n-back and reward task are also suited for within-subject designs, including pharmaco-fMRI. The present study provides task-specific fMRI reliability performance measures that will inform the optimal use, powering and design of fMRI studies using comparable tasks.

Psychometrically matched tasks evaluating differential fMRI activation during form and motion processing

OBJECTIVE

Deficits in visual perception and working memory are commonly observed in neuropsychiatric disorders and have been investigated using functional MRI (fMRI). However, interpretation of differences in brain activation may be confounded with differences in task performance between groups. Differences in task difficulty across conditions may also pose interpretative issues in studies of visual processing in healthy subjects.

METHOD

To address these concerns, the present study characterized brain activation in tasks that were psychometrically matched for difficulty; fMRI was used to assess brain activation in 10 healthy subjects during discrimination and working memory judgments for static and moving stimuli. For all task conditions, performance accuracy was matched at 70.7%.

RESULTS

Areas associated with V2 and V5 in the dorsal stream were activated during motion processing tasks and V4 in the ventral stream were activated during form processing tasks. Frontoparietal areas associated with working memory were also statistically significant during the working memory tasks.

CONCLUSIONS

Application of psychophysical methods to equate task demands provides a practical method to equate performance levels across conditions in fMRI studies and to compare healthy and cognitively impaired groups at comparable levels of effort. These psychometrically matched tasks can be applied to patients with a variety of cognitive disorders to investigate dysfunction of multiple a priori defined brain regions. Measuring the changes in typical activation patterns in patients with these diseases can be useful for monitoring disease progression, evaluating new drug treatments, and possibly for developing methods for early diagnosis.

Test-retest variability underlying fMRI measurements

INTRODUCTION

A high test-retest reliability is of pivotal importance for many disciplines in fMRI research. To assess the current limits of fMRI reliability, we estimated the variability in true underlying Blood Oxygen Level Dependent (BOLD) activation, with which we mean the variability that would be found in the theoretical case when we could obtain an unlimited number of scans in each measurement.

METHODS

In this test-retest study, subjects were scanned twice with one week apart, while performing a visual and a motor inhibition task. We addressed the nature of the variability in the underlying BOLD signal, by separating for each brain area and each subject the between-session differences in the spatial pattern of BOLD activation, and the global (whole brain) changes in the amplitude of the spatial pattern of BOLD activation.

RESULTS

We found evidence for changes in the true underlying spatial pattern of BOLD activation for both tasks across the two sessions. The sizes of these changes in pattern activation were approximately 16% of the total activation within the pattern, irrespective of brain area and task. After spatial smoothing, this variability was greatly reduced, which suggests it takes place at a small spatial scale. The mean between-session differences in the amplitude of activation across the whole brain were 13.8% for the visual task and 23.4% for the motor inhibition task.

CONCLUSIONS

Between-session changes in the true underlying spatial pattern of BOLD activation are always present, but occur at a scale that is consistent with partial voluming effects or spatial distortions. We found no evidence that the reliability of the spatial pattern of activation differs systematically between brain areas. Consequently, between-session changes in the amplitude of activation are probably due to global effects. The observed variability in amplitude across sessions warrants caution when interpreting fMRI estimates of height of brain activation. A Matlab implementation of the used algorithm is available for download at www.ni-utrecht.nl/downloads/ura.

The neural bases of grapheme-color synesthesia are not localized in real color-sensitive areas

The subjective experience of color by synesthetes when viewing achromatic letters and numbers supposedly relates to real color experience, as exemplified by the recruitment of the V4 color center observed in some brain imaging studies. Phenomenological reports and psychophysics tests indicate, however, that both experiences are different. Using functional magnetic resonance imaging, we tried to precise the degree of coactivation by real and synesthetic colors, by evaluating each color center individually, and applying adaptation protocols across real and synesthetic colors. We also looked for structural differences between synesthetes and nonsynesthetes. In 10 synesthetes, we found that color areas and retinotopic areas were not activated by synesthetic colors, whatever the strength of synesthetic associations measured objectively for each subject. Voxel-based morphometry revealed no white matter (WM) or gray matter difference in those regions when compared with 25 control subjects. But synesthetes had more WM in the retrosplenial cortex bilaterally. The joint coding of real and synesthetic colors, if it exists, must therefore be distributed rather than localized in the visual cortex. Alternatively, the key to synesthetic color experience might not lie in the color system.

A mutual information-based metric for evaluation of fMRI data-processing approaches

We propose a novel approach for evaluating the performance of activation detection in real (experimental) datasets using a new mutual information (MI)-based metric and compare its sensitivity to several existing performance metrics in both simulated and real datasets. The proposed approach is based on measuring the approximate MI between the fMRI time-series of a validation dataset and a calculated activation map (thresholded label map or continuous map) from an independent training dataset. The MI metric is used to measure the amount of information preserved during the extraction of an activation map from experimentally related fMRI time-series. The processing method that preserves maximal information between the maps and related time-series is proposed to be superior. The results on simulation datasets for multiple analysis models are consistent with the results of ROC curves, but are shown to have lower information content than for real datasets, limiting their generalizability. In real datasets for group analyses using the general linear model (GLM; FSL4 and SPM5), we show that MI values are (1) larger for groups of 15 versus 10 subjects and (2) more sensitive measures than reproducibility (for continuous maps) or Jaccard overlap metrics (for thresholded maps). We also show that (1) for an increasing fraction of nominally active voxels, both MI and false discovery rate (FDR) increase, and (2) at a fixed FDR, GLM using FSL4 tends to extract more voxels and more information than SPM5 using the default processing techniques in each package.

Using brain imaging measures in studies of procognitive pharmacologic agents in schizophrenia: psychometric and quality assurance considerations

The first phase of the Cognitive Neuroscience Treatment Research to Improve Cognition in Schizophrenia (CNTRICs) initiative focused on the identification of cognitive constructs from human and animal neuroscience that were relevant to understanding cognitive deficits in schizophrenia, as well as promising task paradigms that could be used to assess these constructs behaviorally. The current phase of CNTRICs has the goal of expanding this initial work by including measures of brain function that can augment these behavioral tasks as biomarkers to be used in drug development processing. Here we review many of the psychometric issues that need to be addressed regarding the development and inclusion of such methods in the drug development process. In addition, we review quality assurance concerns, issues associated with multicenter trials, concerns associated with potential pharmacologic confounds on imaging measures, as well as power and analysis considerations. Although review is couched in the context of the use of biomarkers for treatment studies in schizophrenia, we believe the issues and suggestions included are relevant to the entire range of neuropsychiatric disorders as well as to a wide range of imaging modalities (i.e., functional magnetic resonance imaging, positron emission tomography, event-related potentials, electroencephalography, transcranial magnetic stimulation, near infrared spectroscopy, etc.) and are relevant to both pharmacologic and psychological intervention approaches.

Stability of fMRI striatal response to alcohol cues: a hierarchical linear modeling approach

In functional magnetic resonance imaging (fMRI) studies of alcohol-dependent individuals, alcohol cues elicit activation of the ventral and dorsal aspects of the striatum (VS and DS), which are believed to underlie aspects of reward learning critical to the initiation and maintenance of alcohol dependence. Cue-elicited striatal activation may represent a biological substrate through which treatment efficacy may be measured. However, to be useful for this purpose, VS or DS activation must first demonstrate stability across time. Using hierarchical linear modeling (HLM), this study tested the stability of cue-elicited activation in anatomically and functionally defined regions of interest in bilateral VS and DS. Nine non-treatment-seeking alcohol-dependent participants twice completed an alcohol cue reactivity task during two fMRI scans separated by 14 days. HLM analyses demonstrated that, across all participants, alcohol cues elicited significant activation in each of the regions of interest. At the group level, these activations attenuated slightly between scans, but session-wise differences were not significant. Within-participants stability was best in the anatomically defined right VS and DS and in a functionally defined region that encompassed right caudate and putamen (intraclass correlation coefficients of .75, .81, and .76, respectively). Thus, within this small sample, alcohol cue-elicited fMRI activation had good reliability in the right striatum, though a larger sample is necessary to ensure generalizability and further evaluate stability. This study also demonstrates the utility of HLM analytic techniques for serial fMRI studies, in which separating within-participants variance (individual changes in activation) from between-participants factors (time or treatment) is critical.

Physiological noise effects on the flip angle selection in BOLD fMRI

This work addresses the choice of imaging flip angle in blood oxygenation level dependent (BOLD) functional magnetic resonance imaging (fMRI). When noise of physiological origin becomes the dominant noise source in fMRI timeseries, it causes a nonlinear dependence of the temporal signal-to-noise ratio (TSNR) versus signal-to-noise ratio (SNR) that can be exploited to perform BOLD fMRI at angles well below the Ernst angle without any detrimental effect on our ability to detect sites of neuronal activation. We show, both experimentally and theoretically, that for situations where available SNR is high and physiological noise dominates over system/thermal noise, although TSNR still reaches it maximum for the Ernst angle, reduction of imaging flip angle well below this angle results in negligible loss in TSNR. Moreover, we provide a way to compute a suggested imaging flip angle, which constitutes a conservative estimate of the minimum flip angle that can be used under given experimental SNR and physiological noise levels. For our experimental conditions, this suggested angle equals 7.63° for the grey matter compartment, while the Ernst angle=77°. Finally, using data from eight subjects with a combined visual-motor task we show that imaging at angles as low as 9° introduces no significant differences in observed hemodynamic response time-course, contrast-to-noise ratio, voxel-wise effect size or statistical maps of activation as compared to imaging at 75° (an angle close to the Ernst angle). These results suggest that using low flip angles in BOLD fMRI experimentation to obtain benefits such as (1) reduction of RF power, (2) limitation of apparent T(1)-related inflow effects, (3) reduction of through-plane motion artifacts, (4) lower levels of physiological noise, and (5) improved tissue contrast is feasible when physiological noise dominates and SNR is high.

Reliability of functional magnetic resonance imaging associative encoding memory paradigms in non-demented elderly adults

Functional magnetic resonance imaging (fMRI) holds significant potential to aid in the development of early interventions to improve memory function, and to assess longitudinal change in memory systems in aging and early Alzheimer's disease (AD). However, the test-retest reliability of hippocampal activation and of "beneficial" deactivation in the precuneus has yet to be fully established during memory encoding tasks in older subjects. Using a mixed block and event-related face-name associative encoding paradigm, we assessed the reliability of hippocampal activation and default network deactivation over a 4- to 6-week interscan interval in 27 older individuals who were cognitively normal [Clinical Dementia Rating (CDR) Scale = 0; n = 18] or mildly impaired (CDR = 0.5; n = 9). Reliability was assessed in whole brain maps and regions of interest using both a full-task paradigm of six functional runs as well as an abbreviated paradigm of the first two functional runs, which would be advantageous for use in clinical trials. We found reliable hippocampal signal response across both block- and event-related designs in the right hippocampus. Comparable reliability in hippocampal activation was found in the full and the abbreviated paradigm. Similar reliability in hippocampal activation was observed across both CDR groups overall, but the CDR 0.5 group was more variable in left hippocampal activity. Task-related deactivation in the precuneus demonstrated much greater variability than hippocampal activation in all analyses. Overall, these results are encouraging for the utility of fMRI in "Proof of Concept" clinical trials investigating the efficacy of potentially therapeutic agents for treatment of age-related memory changes, cognitive impairment, and early AD.

Effect of a prescan patient-radiologist encounter on functional MR image quality

BACKGROUND AND PURPOSE

A substantial number of clinical fMRI examinations inadequately assess language localization or lateralization, usually due to patient movement and suboptimal participation. We hypothesized that a prescan interview of the patient by the radiologist would reduce the fraction of nondiagnostic scans.

MATERIALS AND METHODS

A single noise score for each acquisition was produced from time-series data on the basis of a weighted sum of 22 factors. Scores were recorded as the following quartiles: 0-5 = excellent, 5-10 = adequate, 10-15= marginal, and >15 = unacceptable. This measure was evaluated for 202 consecutive fMRI patients: 96 without and 106 with a physician prescan interview. The data were analyzed to compute the fraction of all nondiagnostic sequences and entire studies and were compared between the 2 groups. Image-noise characteristics included the SDs of linear and angular displacements of the head and the number of time-series outliers caused by focal motion.

RESULTS

Of 999 sequences acquired, 539 had a prescan interview. The mean noise score significantly decreased for both individual sequence (from 7.9 to 6.3, P = <.001) and study-based (from 7.7 to 6.2, P = .05) methods. The fraction of sequences or studies scored as unacceptable decreased for sequence-based (from 15.2% to 10.9%, P = .04) and study-based (from 9.4% to 1.9%, P = .02) analyses. SDs of head motion decreased for linear (by 12%-14%, P < .01) and angular displacement (by 38%-48%, P < .001). The number of time-series spikes decreased by 10% (P = .004).

CONCLUSIONS

We report that a prescan physician-patient interview modestly but significantly reduces fMRI noise scores. These results support the newly added billable costs of professional intervention before fMRI scans.

Between- and within-scanner variability in the CaliBrain study n-back cognitive task

Psychiatric neuroimaging techniques are likely to improve understanding of the brain in health and disease, but studies tend to be small, based in one imaging centre and of unclear generalisability. Multicentre studies have great appeal but face problems if functional magnetic resonance imaging (fMRI) data from different centres are to be combined. Fourteen healthy volunteers had two brain scans on different days at three scanners. Considerable effort was first made to use similar scanning sequences and standardise task implementation across centres. The n-back cognitive task was used to investigate between- and within-scanner reproducibility and reliability. Both the functional imaging and behavioural results were in good accord with the existing literature. We found no significant differences in the activation/deactivation maps between scanners, or between repeat visits to the same scanners. Between- and within-scanner reproducibility and reliability was very similar. However, the smoothness of images from the scanners differed, suggesting that smoothness equalization might further reduce inter-scanner variability. Our results for the n-back task suggest it is possible to acquire fMRI data from different scanners which allows pooling across centres, when the same field strength scanners are used and scanning sequences and paradigm implementations are standardised.

Impact of cognitive performance on the reproducibility of fMRI activation in schizophrenia

BACKGROUND

Longitudinal functional magnetic resonance imaging (fMRI) studies in patients with schizophrenia allow exploration of the course of the illness and brain activity after therapy. A crucial question, however, is whether fMRI findings are reliable, because they can be affected by performance deficits in patients with schizophrenia. Our aim was to evaluate the reproducibility of fMRI activations in highly integrated language areas in patients with schizophrenia, taking into account task performance.

METHODS

Ten patients with schizophrenia and 10 matched healthy controls were scanned twice, 21 months apart, while performing a story comprehension task. The reproducibility of the activations in each participant was evaluated globally by the percentage of spatial overlap between the 2 sessions and locally by a voxel-wise computation of the between-session relative standard deviation. We performed between-group comparisons both with and without the inclusion of comprehension scores (measuring task performance) as a covariate.

RESULTS

On average, patients with schizophrenia had significantly lower comprehension scores than controls (4.5/12 v. 7.8/12, p = 0.002). The mean spatial overlap between fMRI sessions was 30.6% in the patient group and 47.0% in the control group (p = 0.017). Locally, the lower reproducibility in patients was most prominent in the left posterior middle temporal gyrus, inferior frontal gyrus and medial prefrontal cortex (p < 0.001 uncorrected for multiple comparisons). Comprehension scores were positively correlated with both reproducibility measures in patients (overlap: r = 0.82, p = 0.004; relative standard deviation: several significant clusters at p < 0.001). When we included the comprehension scores as a covariate, most of the local between-group differences in reproducibility were removed, and the difference in overlap was not significant.

LIMITATIONS

Owing to the small sample size, we could not investigate the impact of clinical subtypes and different types of medications on reproducibility.

CONCLUSION

Our findings suggest that the greater variability in activation in patients with schizophrenia compared with controls concerns high-level areas and is mainly attributable to deficient task performance. Consequently, cognitive performance must be carefully controlled when longitudinal fMRI studies are undertaken.