Comparison of continuously acquired resting state and extracted analogues from active tasks

Similarities and differences between intermittent and continuous resting-state fMRI

Introduction

Functional Magnetic Resonance Imaging (fMRI) block-design experiments typically include active ON-blocks with presentation of cognitive tasks which are contrasted with OFF- blocks with no tasks presented. OFF-blocks in between ON-blocks can however, also be seen as a proxy for intermittent periods of resting, inducing temporary resting-states. We still do not know if brain activity during such intermittent periods reflects the same kind of resting-state activity as that obtained during a continuous period, as is typically the case in studies of the classic Default Mode Network (DMN). The purpose of the current study was therefore to investigate both similarities and differences in brain activity between intermittent and continuous resting conditions.

Methods

There were 47 healthy participants in the 3T fMRI experiment. Data for the intermittent resting-state condition were acquired from resting-periods in between active task-processing periods in a standard ON-OFF block design, with three different cognitive tasks presented during ON-blocks. Data for the continuous resting-state condition were acquired during a 5 min resting period after the task-design had been presented.

Results and discussion

The results showed that activity was overall similar in the two conditions, but with some differences. These differences were within the DMN network, and for the interaction of DMN with other brain networks. DMN maps showed weak overlap between conditions in the medial prefrontal cortex (MPFC), and in particular for the intermittent compared to the continuous resting-state condition. Moreover, DMN showed strong connectivity with the salience network (SN) in the intermittent resting-state condition, particularly in the anterior insula and the supramarginal gyrus. The observed differences may reflect a "carry-over" effect from task-processing to the next resting-state period, not present in the continuous resting-state condition, causing interference from the ON-blocks. Further research is needed to fully understand the extent of differences between intermittent and continuous resting-state conditions.

Validation of ketamine as a pharmacological model of thalamic dysconnectivity across the illness course of schizophrenia

N-methyl-D-aspartate receptor (NMDAR) hypofunction is a leading pathophysiological model of schizophrenia. Resting-state functional magnetic resonance imaging (rsfMRI) studies demonstrate a thalamic dysconnectivity pattern in schizophrenia involving excessive connectivity with sensory regions and deficient connectivity with frontal, cerebellar, and thalamic regions. The NMDAR antagonist ketamine, when administered at sub-anesthetic doses to healthy volunteers, induces transient schizophrenia-like symptoms and alters rsfMRI thalamic connectivity. However, the extent to which ketamine-induced thalamic dysconnectivity resembles schizophrenia thalamic dysconnectivity has not been directly tested. The current double-blind, placebo-controlled study derived an NMDAR hypofunction model of thalamic dysconnectivity from healthy volunteers undergoing ketamine infusions during rsfMRI. To assess whether ketamine-induced thalamic dysconnectivity was mediated by excess glutamate release, we tested whether pre-treatment with lamotrigine, a glutamate release inhibitor, attenuated ketamine's effects. Ketamine produced robust thalamo-cortical hyper-connectivity with sensory and motor regions that was not reduced by lamotrigine pre-treatment. To test whether the ketamine thalamic dysconnectivity pattern resembled the schizophrenia pattern, a whole-brain template representing ketamine's thalamic dysconnectivity effect was correlated with individual participant rsfMRI thalamic dysconnectivity maps, generating "ketamine similarity coefficients" for people with chronic (SZ) and early illness (ESZ) schizophrenia, individuals at clinical high-risk for psychosis (CHR-P), and healthy controls (HC). Similarity coefficients were higher in SZ and ESZ than in HC, with CHR-P showing an intermediate trend. Higher ketamine similarity coefficients correlated with greater hallucination severity in SZ. Thus, NMDAR hypofunction, modeled with ketamine, reproduces the thalamic hyper-connectivity observed in schizophrenia across its illness course, including the CHR-P period preceding psychosis onset, and may contribute to hallucination severity.

Basolateral and central amygdala orchestrate how we learn whom to trust

Cooperation and mutual trust are essential in our society, yet not everybody is trustworthy. In this fMRI study, 62 healthy volunteers performed a repeated trust game, placing trust in a trustworthy or an untrustworthy player. We found that the central amygdala was active during trust behavior planning while the basolateral amygdala was active during outcome evaluation. When planning the trust behavior, central and basolateral amygdala activation was stronger for the untrustworthy player compared to the trustworthy player but only in participants who actually learned to differentiate the trustworthiness of the players. Independent of learning success, nucleus accumbens encoded whether trust was reciprocated. This suggests that learning whom to trust is not related to reward processing in the nucleus accumbens, but rather to engagement of the amygdala. Our study overcomes major empirical gaps between animal models and human neuroimaging and shows how different subnuclei of the amygdala and connected areas orchestrate learning to form different subjective trustworthiness beliefs about others and guide trust choice behavior.

Sex Matters: A Multivariate Pattern Analysis of Sex- and Gender-Related Neuroanatomical Differences in Cis- and Transgender Individuals Using Structural Magnetic Resonance Imaging

Univariate analyses of structural neuroimaging data have produced heterogeneous results regarding anatomical sex- and gender-related differences. The current study aimed at delineating and cross-validating brain volumetric surrogates of sex and gender by comparing the structural magnetic resonance imaging data of cis- and transgender subjects using multivariate pattern analysis. Gray matter (GM) tissue maps of 29 transgender men, 23 transgender women, 35 cisgender women, and 34 cisgender men were created using voxel-based morphometry and analyzed using support vector classification. Generalizability of the models was estimated using repeated nested cross-validation. For external validation, significant models were applied to hormone-treated transgender subjects (n = 32) and individuals diagnosed with depression (n = 27). Sex was identified with a balanced accuracy (BAC) of 82.6% (false discovery rate [pFDR] < 0.001) in cisgender, but only with 67.5% (pFDR = 0.04) in transgender participants indicating differences in the neuroanatomical patterns associated with sex in transgender despite the major effect of sex on GM volume irrespective of the self-identification as a woman or man. Gender identity and gender incongruence could not be reliably identified (all pFDR > 0.05). The neuroanatomical signature of sex in cisgender did not interact with depressive features (BAC = 74.7%) but was affected by hormone therapy when applied in transgender women (P < 0.001).

Language network reorganization before and after temporal lobe epilepsy surgery

OBJECTIVE

Epilepsy surgery is the recommended treatment option for patients with drug-resistant temporal lobe epilepsy (TLE). This method offers a good chance of seizure freedom but carries a considerable risk of postoperative language impairment. The extremely variable neurocognitive profiles in surgical epilepsy patients cannot be fully explained by extent of resection, fiber integrity, or current task-based functional MRI (fMRI). In this study, the authors aimed to investigate pathology- and surgery-triggered language organization in TLE by using fMRI activation and network analysis as well as considering structural and neuropsychological measures.

METHODS

Twenty-eight patients with unilateral TLE (16 right, 12 left) underwent T1-weighted imaging, diffusion tensor imaging, and task-based language fMRI pre- and postoperatively (n = 15 anterior temporal lobectomy, n = 11 selective amygdalohippocampectomy, n = 2 focal resection). Twenty-two healthy subjects served as the control cohort. Functional connectivity, activation maps, and laterality indices for language dominance were analyzed from fMRI data. Postoperative fractional anisotropy values of 7 major tracts were calculated. Naming, semantic, and phonematic verbal fluency scores before and after surgery were correlated with imaging parameters.

RESULTS

fMRI network analysis revealed widespread, bihemispheric alterations in language architecture that were not captured by activation analysis. These network changes were found preoperatively and proceeded after surgery with characteristic patterns in the left and right TLEs. Ipsilesional fronto-temporal connectivity decreased in both left and right TLE. In left TLE specifically, preoperative atypical language dominance predicted better postoperative verbal fluency and naming function. In right TLE, left frontal language dominance correlated with good semantic verbal fluency before and after surgery, and left fronto-temporal language laterality predicted good naming outcome. Ongoing seizures after surgery (Engel classes ID-IV) were associated with naming deterioration irrespective of seizure side. Functional findings were not explained by the extent of resection or integrity of major white matter tracts.

CONCLUSIONS

Functional connectivity analysis contributes unique insight into bihemispheric remodeling processes of language networks after epilepsy surgery, with characteristic findings in left and right TLE. Presurgical contralateral language recruitment is associated with better postsurgical language outcome in left and right TLE.

Lesion-Specific Language Network Alterations in Temporal Lobe Epilepsy

BACKGROUND AND PURPOSE

Temporal lobe epilepsy, structural or nonlesional, may negatively affect language function. However, little is known about the lesion-specific influence on language networks. We hypothesized that different epileptogenic lesions are related to distinct alterations in the functional language connectome detected by fMRI.

MATERIALS AND METHODS

One hundred one patients with epilepsy due to mesiotemporal sclerosis (21 left, 22 right), low-grade mesiotemporal tumors (12 left), or nonlesional temporal lobe epilepsy (22 left, 24 right) and 22 healthy subjects performed 3T task-based language fMRI. Task-based activation maps (laterality indices) and functional connectivity analysis (global and connectivity strengths between language areas) were correlated with language scores.

RESULTS

Laterality indices based on fMRI activation maps failed to discriminate among patient groups. Functional connectivity analysis revealed the most extended language network alterations in left mesiotemporal sclerosis (involving the left temporal pole, left inferior frontal gyrus, and bilateral premotor areas). The other patient groups showed less extended but also predominantly ipsilesional network changes compared with healthy controls. Left-to-right hippocampal connectivity strength correlated positively with naming function (P = .01), and connectivity strength between the left Wernicke area and the left hippocampus was linked to verbal fluency scores (P = .01) across all groups.

CONCLUSIONS

Different pathologies underlying temporal lobe epilepsy are related to distinct alterations of the functional language connectome visualized by fMRI functional connectivity analysis. Network analysis allows new insights into language organization and provides possible imaging biomarkers for language function. These imaging findings emphasize the importance of a personalized treatment strategy in patients with epilepsy.

Accelerated Aging of Functional Brain Networks Supporting Cognitive Function in Psychotic Disorders

BACKGROUND

Across networks, connectivity within the frontoparietal network (FPN) and cingulo-opercular network (CON) exhibits reductions earliest during healthy aging, contributing to cognitive impairment. Individuals with psychotic disorders demonstrate evidence of accelerated aging across multiple biological systems. By leveraging a large sample of patients with psychosis from early to chronic illness stages, this study sought to determine whether the CON and FPN exhibit evidence of accelerated aging in psychotic disorders, confirm associations between network efficiency and cognition, and determine whether reduced network efficiency is observed in early-stage psychosis.

METHODS

Resting-state functional magnetic resonance imaging and cognitive data were obtained on 240 patients with psychotic disorder and 178 healthy control participants (HCs). Global efficiency, a measure of functional integration, was calculated for the CON, FPN, subcortical network, and visual network. Associations with age and cognition were assessed and compared between groups.

RESULTS

Consistent with accelerated aging, significant group by age interactions reflected significantly stronger relationships between efficiency and age in patients with psychosis than in HCs for both the CON (psychosis: r = -.37; HC: r = -.16) and FPN (psychosis: r = -.31; HC: r = -.05). Accelerated aging was not observed in either the subcortical or visual network, suggesting specificity for cognitive networks that decline earliest in healthy aging. Replicating prior findings, efficiency of both the CON and FPN correlated with cognitive function across all participants (rs > .11, ps < .031). Furthermore, patients with chronic psychosis (p = .004), but not patients with early psychosis (p = .553), exhibited significantly lower FPN efficiency compared with HCs.

CONCLUSIONS

Functional integration of higher-order cognitive networks is intact in early psychosis but exhibits evidence of accelerated aging, suggesting the potential for intervention targeting cognition within the early psychosis period.

Making Sense of Connectivity

In addition to the assessment of local alterations of specific brain regions, the investigation of entire networks with in vivo neuroimaging techniques has gained increasing attention. In general, connectivity analysis refers to the investigation of links between brain regions, with the aim to characterize their interactions and information transfer. These may represent or relate to different physiological characteristics (structural, functional, or metabolic information) and can be calculated across different levels of granularity (2 regions vs whole brain). In this article, we provide an overview of different connectivity analysis approaches with interpretations and limitations as well as examples in pharmacological imaging and clinical applications. Structural connectivity obtained from diffusion MRI enables the reconstruction of neuronal fiber tracts. These physical links represent major constraints of functional connections, which are in turn defined as correlations between signal time courses. In addition, molecular connectivity approaches based on PET imaging enable the assessment of interregional associations of metabolic demands and neurotransmitter systems. Application of these approaches in clinical investigations has demonstrated novel alterations in various neurological and psychiatric disorders on a network level. Future work should aim for the combined assessment of multiple imaging modalities and to establish robust biomarkers for clinical use. These advancements will further improve the biological interpretation of connectivity metrics and networks of the human brain.

Exploring distinct default mode and semantic networks using a systematic ICA approach

Resting-state networks (RSNs; groups of regions consistently co-activated without an explicit task) are hugely influential in modern brain research. Despite this popularity, the link between specific RSNs and their functions remains elusive, limiting the impact on cognitive neuroscience (where the goal is to link cognition to neural systems). Here we present a series of logical steps to formally test the relationship between a coherent RSN with a cognitive domain. This approach is applied to a challenging and significant test-case; extracting a recently-proposed semantic RSN, determining its relation with a well-known RSN, the default mode network (DMN), and assessing their roles in semantic cognition. Results showed the DMN and semantic network are two distinct coherent RSNs. Assessing the cognitive signature of these spatiotemporally coherent networks directly (and therefore accounting for overlapping networks) showed involvement of the proposed semantic network, but not the DMN, in task-based semantic cognition. Following the steps presented here, researchers could formally test specific hypotheses regarding the function of RSNs, including other possible functions of the DMN.

Correspondence Between Resting-State and Episodic Memory-Task Related Networks in Elderly Subjects

Resting-state fMRI studies demonstrated temporally synchronous fluctuations in brain activity among ensembles of brain regions, suggesting the existence of intrinsic functional networks. A spatial match between some of the resting-state networks and regional brain activation during cognitive tasks has been noted, suggesting that resting-state networks support particular cognitive abilities. However, the spatial match and predictive value of any resting-state network and regional brain activation during episodic memory is only poorly understood. In order to address this research gap, we obtained fMRI acquired both during rest and a face-name association task in 38 healthy elderly subjects. In separate independent component analyses, networks of correlated brain activity during rest or the episodic memory task were identified. For the independent components identified for task-based fMRI, the design matrix of successful encoding or retrieval trials was regressed against the time course of each of the component to identify significantly activated networks. Spatial regression was used to assess the match of resting-state networks against those related to successful memory encoding or retrieval. We found that resting-state networks covering the medial temporal, middle temporal, and frontal areas showed increased activity during successful encoding. Resting-state networks located within posterior brain regions showed increased activity during successful recognition. However, the level of resting-state network connectivity was not predictive of the task-related activity in these networks. These results suggest that a circumscribed number of functional networks detectable during rest become engaged during successful episodic memory. However, higher intrinsic connectivity at rest may not translate into higher network expression during episodic memory.

Estimation of brain functional connectivity from hypercapnia BOLD MRI data: Validation in a lifespan cohort of 170 subjects

Functional connectivity MRI, based on Blood-Oxygenation-Level-Dependent (BOLD) signals, is typically performed while the subject is at rest. On the other hand, BOLD is also widely used in physiological imaging such as cerebrovascular reactivity (CVR) mapping using hypercapnia (HC) as a modulator. We therefore hypothesize that hypercapnia BOLD data can be used to extract FC metrics after factoring out the effects of the physiological modulation, which will allow simultaneous assessment of neural and vascular function and may be particularly important in populations such as aging and cerebrovascular diseases. The present work aims to systematically examine the feasibility of hypercapnia BOLD-based FC mapping using three commonly applied analysis methods, specifically dual-regression Independent Component Analysis (ICA), region-based FC matrix analysis, and graph-theory based network analysis, in a large cohort of 170 healthy subjects ranging from 20 to 88 years old. To validate the hypercapnia BOLD results, we also compared these FC metrics with those obtained from conventional resting-state data. ICA analysis of the hypercapnia BOLD data revealed FC maps that strongly resembled those reported in the literature. FC matrix using region-based analysis showed a correlation of 0.97 on the group-level and 0.54 ± 0.10 on the individual-level, when comparing between hypercapnia and resting-state results. Although the correspondence on the individual-level was moderate, this was primarily attributed to variations intrinsic to FC mapping, because a corresponding resting-vs-resting comparison in a sub-cohort (N = 39) revealed a similar correlation of 0.57 ± 0.09. Graph-theory computations were also feasible in hypercapnia BOLD data and indices of global efficiency, clustering coefficient, modularity, and segregation were successfully derived. Hypercapnia FC results revealed age-dependent differences in which within-network connections generally exhibited an age-dependent decrease while between-network connections showed an age-dependent increase.

Magnitude and Temporal Variability of Inter-stimulus EEG Modulate the Linear Relationship Between Laser-Evoked Potentials and Fast-Pain Perception

The level of pain perception is correlated with the magnitude of pain-evoked brain responses, such as laser-evoked potentials (LEP), across trials. The positive LEP-pain relationship lays the foundation for pain prediction based on single-trial LEP, but cross-individual pain prediction does not have a good performance because the LEP-pain relationship exhibits substantial cross-individual difference. In this study, we aim to explain the cross-individual difference in the LEP-pain relationship using inter-stimulus EEG (isEEG) features. The isEEG features (root mean square as magnitude and mean square successive difference as temporal variability) were estimated from isEEG data (at full band and five frequency bands) recorded between painful stimuli. A linear model was fitted to investigate the relationship between pain ratings and LEP response for fast-pain trials on a trial-by-trial basis. Then the correlation between isEEG features and the parameters of LEP-pain model (slope and intercept) was evaluated. We found that the magnitude and temporal variability of isEEG could modulate the parameters of an individual's linear LEP-pain model for fast-pain trials. Based on this, we further developed a new individualized fast-pain prediction scheme, which only used training individuals with similar isEEG features as the test individual to train the fast-pain prediction model, and obtained improved accuracy in cross-individual fast-pain prediction. The findings could help elucidate the neural mechanism of cross-individual difference in pain experience and the proposed fast-pain prediction scheme could be potentially used as a practical and feasible pain prediction method in clinical practice.

An fMRI study of coherent visual motion processing in children and adults

There is a large corpus of brain imaging studies examining the dorsal visual pathway, especially area V5/MT during visual motion perception. However, despite evidence suggesting a protracted development of the dorsal visual stream, and a role of this pathway in neurodevelopmental disorders, V5/MT has not been characterized developmentally. Further, experiential factors such as reading acquisition may play a modulating role in any age-dependent changes. Here we used a coherent visual motion detection task to examine V5/MT activity and connectivity in typical participants in two studies: a Cross- Sectional Study comparing adults and children; and a Longitudinal Study of 2nd graders followed into 3rd grade. In the Cross-Sectional Study, a whole-brain analysis revealed no differences between the two groups, whereas a region of interest (ROI) approach identified greater activation in left (right trending) V5/MT in adults compared to children. However, when we measured V5/MT activation individually for each participant, children and adults showed no difference in the location or intensity of activation, although children did exhibit relatively larger extent of V5/MT activation bilaterally. There was also relatively greater functional connectivity in the children between left and right occipitotemporal cortex, including V5/MT. The Longitudinal Study revealed no changes in V5/MT activation for any measures of activation or functional connectivity from 2nd to 3rd grade. Finally, there was no evidence of an association between reading and V5/MT over time, nor predictive power of V5/MT activity for later reading. Together, our results indicate similar V5/MT activity across age groups, with relatively greater extent of V5/MT activation and functional connectivity in children relative to adults, bilaterally. These differences were not apparent over the time course of one year, suggesting that these developmental changes occur over a more protracted period.

The Role of Ethnicity and Environment in the Regulation of Response to Sensory Stimulus in Children: Protocol and Pilot Findings of a Neurophysiological Study

BACKGROUND

The ability to regulate the response to sensory stimuli has been associated with successful behavioral patterns necessary for daily activities. However, it is not known whether a child's ethnicity and environment can influence autonomic regulatory mechanisms.

OBJECTIVE

This study aims to explore the role of ethnicity and environment in the regulation of responses to sensory stimuli in children.

METHODS

In this study, we intend to recruit 128 children from different ethnic groups or environment contexts as follows: (1) 32 typically developing Chinese children living in Hong Kong; (2) 32 typically developing Filipino children living in Hong Kong; (3) 32 typically developing Filipino children who are living in urban areas; and (4) 32 typically developing Filipino children who are living in rural areas in Philippines. Autonomic activity (heart rate variability [HRV] and electrodermal activity [EDA]) will be measured and recorded using Polar H2 heart rate monitor and eSense GSR skin response sensor. Autonomic activity (HRV-low frequency, HRV-high frequency, and EDA) at different conditions between pairwise groupings will be tested using multivariate analysis of variance (MANOVA). All significant levels will be set at P ≤.05.

RESULTS

We present the research protocol of this study, as well as a short discussion of the preliminary findings from our pilot data, with consequent power and sample size analysis that informs the appropriate sample needed to test our hypothesis.

CONCLUSIONS

This study will increase the understanding on the role of individual differences related to a child's ethnicity and environment in the regulation of response to sensory stimuli. The findings of this research may further shed light on the evaluation and treatment planning for children across and within cultures.

Task-relevant brain networks identified with simultaneous PET/MR imaging of metabolism and connectivity

Except for task-specific functional MRI, the vast majority of imaging studies assessed human brain function at resting conditions. However, tracking task-specific neuronal activity yields important insight how the brain responds to stimulation. We specifically investigated changes in glucose metabolism, functional connectivity and white matter microstructure during task performance using several recent methodological advancements. Opening the eyes and right finger tapping had elicited an increased glucose metabolism in primary visual and motor cortices, respectively. Furthermore, a decreased metabolism was observed in the regions of the default mode network, which allowed absolute quantification of commonly described deactivations during cognitive tasks. These brain regions showed widespread task-specific changes in functional connectivity, which stretched beyond their primary resting-state networks and presumably reflected the level of recruitment of certain brain regions for each task. Finally, the corresponding white matter fiber pathways exhibited changes in axial and radial diffusivity during the tasks, which were regionally distinctive for certain tract groups. These results highlight that even simple task performance leads to substantial changes of entire brain networks. Exploiting the complementary nature of the different imaging modalities may reveal novel insights how the brain processes external stimuli and which networks are involved in certain tasks.

The Effect of Low-Frequency Physiological Correction on the Reproducibility and Specificity of Resting-State fMRI Metrics: Functional Connectivity, ALFF, and ReHo

The resting-state fMRI (rs-fMRI) signal is affected by a variety of low-frequency physiological phenomena, including variations in cardiac-rate (CRV), respiratory-volume (RVT), and end-tidal CO₂ (PETCO₂). While these effects have become better understood in recent years, the impact that their correction has on the quality of rs-fMRI measurements has yet to be clarified. The objective of this paper is to investigate the effect of correcting for CRV, RVT and PETCO₂ on the rs-fMRI measurements. Nine healthy subjects underwent a test-retest rs-fMRI acquisition using repetition times (TRs) of 2 s (long-TR) and 0.323 s (short-TR), and the data were processed using eight different physiological correction strategies. Subsequently, regional homogeneity (ReHo), amplitude of low-frequency fluctuation (ALFF), and resting-state connectivity of the motor and default-mode networks are calculated for each strategy. Reproducibility is calculated using intra-class correlation and the Dice Coefficient, while the accuracy of functional-connectivity measures is assessed through network separability, sensitivity and specificity. We found that: (1) the reproducibility of the rs-fMRI measures improved significantly after correction for PETCO₂; (2) separability of functional networks increased after PETCO₂ correction but was not affected by RVT and CRV correction; (3) the effect of physiological correction does not depend on the data sampling-rate; (4) the effect of physiological processes and correction strategies is network-specific. Our findings highlight limitations in our understanding of rs-fMRI quality measures, and underscore the importance of using multiple quality measures to determine the optimal physiological correction strategy.

A Hitchhiker's Guide to Functional Magnetic Resonance Imaging

Functional Magnetic Resonance Imaging (fMRI) studies have become increasingly popular both with clinicians and researchers as they are capable of providing unique insights into brain functions. However, multiple technical considerations (ranging from specifics of paradigm design to imaging artifacts, complex protocol definition, and multitude of processing and methods of analysis, as well as intrinsic methodological limitations) must be considered and addressed in order to optimize fMRI analysis and to arrive at the most accurate and grounded interpretation of the data. In practice, the researcher/clinician must choose, from many available options, the most suitable software tool for each stage of the fMRI analysis pipeline. Herein we provide a straightforward guide designed to address, for each of the major stages, the techniques, and tools involved in the process. We have developed this guide both to help those new to the technique to overcome the most critical difficulties in its use, as well as to serve as a resource for the neuroimaging community.