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Brain asymmetries are hypothesized to reduce functional duplication and thus have evolutionary advantages. The goal of this study was to examine whether early brain lateralization contributes to skill development within the speech-language domain. To achieve this goal, 25 infants (2-13 months old) underwent behavioral language examination and fMRI during sleep while listening to forward and backward speech, and then were assessed on various language skills at 55-69 months old. We observed that infant functional lateralization of the superior temporal gyrus (STG) for forward > backward speech was associated with phonological, vocabulary, and expressive language skills 4 to 5 years later. However, we failed to observe that infant language skills or the anatomical lateralization of STG were related to subsequent language skills. Overall, our findings suggest that infant functional lateralization of STG for speech perception may scaffold subsequent language acquisition, supporting the hypothesis that functional hemisphere asymmetries are advantageous.

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Introduction: The relationship between neural social cognition patterns and performance on social cognition tasks in daily life is a topic of debate, with key consideration given to the extent to which theory of mind (ToM) brain circuits share properties reflecting everyday social functioning. To test the efficacy of ecological stimuli in eliciting brain activation within the ToM brain circuits, we adapted the Edinburgh Social Cognition test social scenarios, consisting of dynamic ecological contextually embedded social stimuli, to a fMRI paradigm. Methods: Forty-two adults (21 men, mean age ± SD = 34.19 years ±12.57) were enrolled and underwent an fMRI assessment which consisted of a ToM task using the Edinburgh Social Cognition test scenarios. We used the same stimuli to prompt implicit (movie viewing) and explicit (silent and two-choice answers) reasoning on cognitive and affective mental states. The fMRI analysis was based on the classical random effect analysis. Group inferences were complemented with supplemental analyses using overlap maps to assess inter-subject variability. Results: We found that explicit mentalizing reasoning yielded wide neural activations when two-choice answers were used. We also observed that the nature of ToM reasoning, that is, affective or cognitive, played a significant role in activating different neural circuits. Discussion: The ESCoT stimuli were particularly effective in evoking ToM core neural underpinnings and elicited executive frontal loops. Future work may employ the task in a clinical setting to investigate ToM network reorganization and plasticity.

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Introduction: Functional magnetic resonance imaging (fMRI) has become a fundamental tool for studying brain function. However, the presence of serial correlations in fMRI data complicates data analysis, violates the statistical assumptions of analyses methods, and can lead to incorrect conclusions in fMRI studies. Methods: In this paper, we show that conventional whitening procedures designed for data with longer repetition times (TRs) (>2 s) are inadequate for the increasing use of short-TR fMRI data. Furthermore, we comprehensively investigate the shortcomings of existing whitening methods and introduce an iterative whitening approach named "IDAR" (Iterative Data-adaptive Autoregressive model) to address these shortcomings. IDAR employs high-order autoregressive (AR) models with flexible and data-driven orders, offering the capability to model complex serial correlation structures in both short-TR and long-TR fMRI datasets. Results: Conventional whitening methods, such as AR(1), ARMA(1,1), and higher-order AR, were effective in reducing serial correlation in long-TR data but were largely ineffective in even reducing serial correlation in short-TR data. In contrast, IDAR significantly outperformed conventional methods in addressing serial correlation, power, and Type-I error for both long-TR and especially short-TR data. However, IDAR could not simultaneously address residual correlations and inflated Type-I error effectively. Discussion: This study highlights the urgent need to address the problem of serial correlation in short-TR (< 1 s) fMRI data, which are increasingly used in the field. Although IDAR can address this issue for a wide range of applications and datasets, the complexity of short-TR data necessitates continued exploration and innovative approaches. These efforts are essential to simultaneously reduce serial correlations and control Type-I error rates without compromising analytical power.

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BACKGROUND: Previous task-related functional magnetic resonance imaging (task-fMRI) investigations have documented abnormal brain activation associated with subclinical depression (SD), defined as a clinically relevant level of depressive symptoms that does not meet the diagnostic criteria for major depressive disorder. However, these task-fMRI studies have not reported consistent conclusions. Performing a voxel-based meta-analysis of task-fMRI studies may yield reliable findings. METHODS: We extracted the peak coordinates and t values of included studies and analyzed brain activation between individuals with SD and healthy controls (HCs) using anisotropic effect-size signed differential mapping (AES-SDM). RESULTS: A systematic literature search identified eight studies, including 266 individuals with SD and 281 HCs (aged 14 to 25). The meta-analysis showed that individuals with SD exhibited significantly greater activation in the right lenticular nucleus and putamen according to task-fMRI. The meta-regression analysis revealed a negative correlation between the proportion of females in a group and activation in the right striatum. LIMITATIONS: The recruitment criteria for individuals with SD, type of tasks and MRI acquisition parameters of included studies were heterogeneous. The results should be interpreted cautiously due to insufficient included studies. CONCLUSION: Our findings suggest that individuals with SD exhibit increased activation in the right lenticular nucleus, putamen and striatum, which may indicate a compensatory increase in response to an impairment of insular and striatal function caused by depression. These results provide valuable insights into the potential pathophysiology of brain dysfunction in SD.

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US Food and Drug Administration (FDA) cleared a Transcranial Magnetic Stimulation (TMS) system with functional Magnetic Resonance Imaging-guided (fMRI) individualized treatment protocol for major depressive disorder, which employs resting state-fMRI (RS-fMRI) functional connectivity (FC) to pinpoint the target individually to increase the accuracy and effeteness of the stimulation. Furthermore, task activation-guided TMS, as well as the use of RS-fMRI local metrics for targeted the specific abnormal brain regions, are considered a precise scheme for TMS targeting. Since 1.5 T MRI is more available in hospitals, systematic evaluation of the test-retest reliability and sensitivity of fMRI metrics on 1.5 T and 3 T MRI may provide reference for the application of fMRI-guided individualized-precise TMS stimulation. Twenty participants underwent three RS-fMRI scans and one scan of finger-tapping task fMRI with self-initiated (SI) and visual-guided (VG) conditions at both 3 T and 1.5 T. Then the location reliability derived by FC (with three seed regions) and peak activation were assessed by intra-individual distance. The test-retest reliability and sensitivity of five RS-fMRI local metrics were evaluated using intra-class correlation and effect size, separately. The intra-individual distance of peak activation location between 1.5 T and 3 T was 15.8 mm and 19 mm for two conditions, respectively. The intra-individual distance for the FC derived targets at 1.5 T was 9.6-31.2 mm, compared to that of 3 T (7.6-31.1 mm). The test-retest reliability and sensitivity of RS-fMRI local metrics showed similar trends on 1.5 T and 3 T. These findings hasten the application of fMRI-guided individualized TMS treatment in clinical practice.

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Entropy indicates irregularity of a dynamic system, with higher entropy indicating higher irregularity and more transit states. In the human brain, regional brain entropy (BEN) has been increasingly assessed using resting state fMRI (rs-fMRI), while changes of regional BEN during task-based fMRI have been scarcely studied. The purpose of this study is to characterize task-induced regional BEN alterations using the large Human Connectome Project (HCP) data. To control the potential modulation by the block design, BEN of task-fMRI was calculated from the fMRI images acquired during the task conditions only (task BEN) and then compared to BEN of rs-fMRI (resting BEN). Moreover, BEN was separately calculated from the control blocks of the task-fMRI runs (control BEN) and compared to task BEN. Finally, control BEN was compared to resting BEN to test for residual task effects in the control condition. With respect to resting state, task performance unanimously induced BEN reduction in the peripheral cortical area and BEN increase in the centric part of the sensorimotor and perception networks. Control compared to resting BEN showed similar entropy alterations, suggesting large residual task effects. Task compared to control BEN was characterized by reduced entropy in occipital, orbitofrontal, and parietal regions.

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The human brain is localized and distributed. On the one hand, each cognitive function tends to involve one hemisphere more than the other, also known as the principle of lateralization. On the other hand, interactions among brain regions in the form of functional connectivity (FC) are indispensable for intact function. Recent years have seen growing interest in the association between lateralization and FC. However, FC metrics vary from spurious correlation to causal associations. If lateralization manifests local processing and causal network interactions, more causally valid FC metrics should predict lateralization index (LI) better than FC based on simple correlations. The present study directly investigates this hypothesis within the activity flow framework to compare the association between lateralization and four brain connectivity metrics: correlation-based FC, multiple-regression FC, partial-correlation FC, and combinedFC. We propose two modeling approaches: the one-step approach, which models the relationship between LI and FC directly, and the two-step approach, which predicts the brain activation and calculates the LI. Our results indicated that multiple-regression FC, partial-correlation FC, and combinedFC could significantly improve the model prediction compared to correlation-based FC, which was consistent in a spatial working memory task (typically right-lateralized) and a language task (typically left-lateralized). The one-step and two-step approach yielded similar conclusions. In addition, the finding was replicated in a clinical sample of schizophrenia (SZ), bipolar disorder (BP), and attention deficit hyperactivity disorder (ADHD). The present study suggests that the causal interactions among brain regions help shape the lateralization pattern.

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Introduction: The mental load caused by simultaneous multitasking can affect visual information processing and reduce its ability. This study investigated the effect of mental load caused by cognitive tasks simultaneously with visual task on the number of active voxels in the visual cortex. Methods: This study recruited 22 individuals with a mean age of 24.72 ± 5.47 years. 3-Tesla functional magnetic resonance imaging (fMRI) was used to examine the functions of the visual cortex and amygdala region during three different task conditions: visual task alone, visual task with an auditory n-back task, and visual task with an arithmetic task. The visual stimuli consisted of Gabor patches with a contrast of 55% at spatial frequencies of 0.25, 4, and 9 cycles per degree (cpd). These were presented in three trials of eight blocks with a stimulation time of 12 sec and a rest time of 14 sec. Results: Activated brain voxels in the primary, secondary, and associated visual cortex areas were reduced in response to the mental load imposed by the n-back and arithmetic tasks. This reduction was greater for a spatial frequency of 0.25 cpd in the n-back task condition and spatial frequency of 9 cpd in the arithmetic task condition. In addition, the amygdala was stimulated in 2-back task and arithmetic task conditions. Conclusions: This study revealed a decline in the number of activated voxels of the visual cortex due to the mental load caused by simultaneous cognitive tasks, confirming the findings of previous psychophysical studies.

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Risk-taking often occurs in childhood as a compex outcome influenced by individual, family, and social factors. The ability to govern risky decision-making in a balanced manner is a hallmark of the integrity of cognitive and affective development from childhood to adulthood. The Triadic Neural Systems Model posits that the nuanced coordination of motivational approach, avoidance and prefrontal control systems is crucial to regulate adaptive risk-taking and related behaviors. Although widely studied in adolescence and adulthood, how these systems develop in childhood remains elusive. Here, we show heterogenous age-related differences in the triadic neural systems involved in risky decision-making in 218 school-age children relative to 80 young adults. Children were generally less reward-seeking and less risk-taking than adults, and exhibited gradual increases in risk-taking behaviors from 6 to 12 years-old, which are associated with age-related differences in brain activation patterns underlying reward and risk processing. In comparison to adults, children exhibited weaker activation in control-related prefrontal systems, but stronger activation in reward-related striatal systems. Network analyses revealed that children showed greater reward-related functional connectivity within and between the triadic systems. Our findings support an immature and unbalanced developmental view of the core neurocognitive systems involved in risky decision-making and related behaviors in middle to late childhood.

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Hypokinetic dysarthria (HD) is a difficult-to-treat symptom affecting quality of life in patients with Parkinson's disease (PD). Levodopa may partially alleviate some symptoms of HD in PD, but the neural correlates of these effects are not fully understood. The aim of our study was to identify neural mechanisms by which levodopa affects articulation and prosody in patients with PD. Altogether 20 PD patients participated in a task fMRI study (overt sentence reading). Using a single dose of levodopa after an overnight withdrawal of dopaminergic medication, levodopa-induced BOLD signal changes within the articulatory pathway (in regions of interest; ROIs) were studied. We also correlated levodopa-induced BOLD signal changes with the changes in acoustic parameters of speech. We observed no significant changes in acoustic parameters due to acute levodopa administration. After levodopa administration as compared to the OFF dopaminergic condition, patients showed task-induced BOLD signal decreases in the left ventral thalamus (p = 0.0033). The changes in thalamic activation were associated with changes in pitch variation (R = 0.67, p = 0.006), while the changes in caudate nucleus activation were related to changes in the second formant variability which evaluates precise articulation (R = 0.70, p = 0.003). The results are in line with the notion that levodopa does not have a major impact on HD in PD, but it may induce neural changes within the basal ganglia circuitries that are related to changes in speech prosody and articulation.

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Focused attention meditation (FAM) training has been shown to improve attention, but the neural basis of FAM on attention has not been thoroughly understood. Here, we aim to investigate the neural effect of a 2-month FAM training on novice meditators in a visual oddball task (a frequently adopted task to evaluate attention), evaluated with both ASL and BOLD fMRI. Using ASL, activation was increased in the middle cingulate (part of the salience network, SN) and temporoparietal (part of the frontoparietal network, FPN) regions; the FAM practice time was negatively associated with the longitudinal changes in activation in the medial prefrontal (part of the default mode network, DMN) and middle frontal (part of the FPN) regions. Using BOLD, the FAM practice time was positively associated with the longitudinal changes of activation in the inferior parietal (part of the dorsal attention network, DAN), dorsolateral prefrontal (part of the FPN), and precentral (part of the DAN) regions. The effect sizes for the activation changes and their association with practice time using ASL are significantly larger than those using BOLD. Our study suggests that FAM training may improve attention via modulation of the DMN, DAN, SN, and FPN, and ASL may be a sensitive tool to study the FAM effect on attention.

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How to retrieve latent neurobehavioural processes from complex neurobiological signals is an important yet unresolved challenge. Here, we develop a novel approach, orthogonal-Decoding multi-Cognitive Processes (DeCoP), to reveal underlying latent neurobehavioural processing and show that its performance is superior to traditional non-orthogonal decoding in terms of both false inference and robustness. Processing value and salience information are two fundamental but mutually confounded pathways of reward reinforcement essential for decision making. During reward/punishment anticipation, we applied DeCoP to decode brain-wide responses into spatially overlapping, yet functionally independent, evaluation and readiness processes, which are modulated differentially by meso­limbic vs nigro-striatal dopamine systems. Using DeCoP, we further demonstrated that most brain regions only encoded abstract information but not the exact input, except for dorsal anterior cingulate cortex and insula. Furthermore, we anticipate our novel analytical principle to be applied generally in decoding multiple latent neurobehavioral processes and thus advance both the design and hypothesis testing for cognitive tasks.

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Congenital cleft lip and palate is one of the common deformities in the craniomaxillofacial region. The current study aimed to explore the perceptual pattern of cleft-related speech produced by Mandarin-speaking patients with repaired cleft palate using the task-based functional magnetic resonance imaging (task-fMRI) technique. Three blocks of speech stimuli, including hypernasal speech, the glottal stop, and typical speech, were played to 30 typical adult listeners with no history of cleft palate speech exploration. Using a randomized block design paradigm, the participants were instructed to assess the intelligibility of the stimuli. Simultaneously, fMRI data were collected. Brain activation was compared among the three types of speech stimuli. Results revealed that greater blood-oxygen-level-dependent (BOLD) responses to the cleft-related glottal stop than to typical speech were localized in the right fusiform gyrus and the left inferior occipital gyrus. The regions responding to the contrast between the glottal stop and cleft-related hypernasal speech were located in the right fusiform gyrus. More significant BOLD responses to hypernasal speech than to the glottal stop were localized in the left orbital part of the inferior frontal gyrus and middle temporal gyrus. More significant BOLD responses to typical speech than to the glottal stop were localized in the left inferior temporal gyrus, left superior temporal gyrus, left medial superior frontal gyrus, and right angular gyrus. Furthermore, there was no significant difference between hypernasal speech and typical speech. In conclusion, the typical listener would initiate different neural processes to perceive cleft-related speech. Our findings lay a foundation for exploring the perceptual pattern of patients with repaired cleft palate.

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There is a growing body of research showing that cerebral pathophysiological processes triggered by pediatric mild traumatic brain injury (pmTBI) may extend beyond the usual clinical recovery timeline. It is paramount to further unravel these processes, because the possible long-term cognitive effects resulting from ongoing secondary injury in the developing brain are not known. In the current fMRI study, neural processes related to cognitive control were studied in 181 patients with pmTBI at sub-acute (SA; ~1 week) and early chronic (EC; ~4 months) stages post-injury. Additionally, a group of 162 age- and sex-matched healthy controls (HC) were recruited at equivalent time points. Proactive (post-cue) and reactive (post-probe) cognitive control were examined using a multimodal attention fMRI paradigm for either congruent or incongruent stimuli. To study brain network function, the triple-network model was used, consisting of the executive and salience networks (collectively known as the cognitive control network), and the default mode network. Additionally, whole-brain voxel-wise analyses were performed. Decreased deactivation was found within the default mode network at the EC stage following pmTBI during both proactive and reactive control. Voxel-wise analyses revealed sub-acute hypoactivation of a frontal area of the cognitive control network (left pre-supplementary motor area) during proactive control, with a reversed effect at the EC stage after pmTBI. Similar effects were observed in areas outside of the triple-network during reactive control. Group differences in activation during proactive control were limited to the visual domain, whereas for reactive control findings were more pronounced during the attendance of auditory stimuli. No significant correlations were present between task-related activations and (persistent) post-concussive symptoms. In aggregate, current results show alterations in neural functioning during cognitive control in pmTBI up to 4 months post-injury, regardless of clinical recovery. We propose that subacute decreases in activity reflect a general state of hypo-excitability due to the injury, while early chronic hyperactivation represents a compensatory mechanism to prevent default mode interference and to retain cognitive control.

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Reductions in the ability to encode and retrieve past experiences in rich spatial contextual detail (episodic memory) are apparent by midlife-a time when most females experience spontaneous menopause. Yet, little is known about how menopause status affects episodic memory-related brain activity at encoding and retrieval in middle-aged premenopausal and postmenopausal females, and whether any observed group differences in brain activity and memory performance correlate with chronological age within group. We conducted an event-related task fMRI study of episodic memory for spatial context to address this knowledge gap. Multivariate behavioral partial least squares was used to investigate how chronological age and retrieval accuracy correlated with brain activity in 31 premenopausal females (age range, 39.55-53.30 years; mean age, 44.28 years; SD age, 3.12 years) and 41 postmenopausal females (age range, 46.70-65.14 years; mean age, 57.56 years; SD age, 3.93 years). We found that postmenopausal status, and advanced age within postmenopause, was associated with lower spatial context memory. The fMRI analysis showed that only in postmenopausal females, advanced age was correlated with decreased activity in occipitotemporal, parahippocampal, and inferior parietal cortices during encoding and retrieval, and poorer spatial context memory performance. In contrast, only premenopausal females exhibited an overlap in encoding and retrieval activity in angular gyrus, midline cortical regions, and prefrontal cortex, which correlated with better spatial context retrieval accuracy. These results highlight how menopause status and chronological age, nested within menopause group, affect episodic memory and its neural correlates at midlife.SIGNIFICANCE STATEMENT This is the first fMRI study to examine how premenopause and postmenopause status affect the neural correlates of episodic memory encoding and retrieval, and how chronological age contributes to any observed group similarities and differences. We found that both menopause status (endocrine age) and chronological age affect spatial context memory and its neural correlates. Menopause status directly affected the direction of age-related and performance-related correlations with brain activity in inferior parietal, parahippocampal, and occipitotemporal cortices across encoding and retrieval. Moreover, we found that only premenopausal females exhibited cortical reinstatement of encoding-related activity in midline cortical, prefrontal, and angular gyrus, at retrieval. This suggests that spatial context memory abilities may rely on distinct brain systems at premenopause compared with postmenopause.

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BACKGROUND: Few studies have focused on the changes in human brain function activities caused by reading Chinese characters with different intelligibility and whether it can reflect the understanding and cognitive ability of the human brain. OBJECTIVE: Task-fMRI based on Chinese character reading tasks with different intelligibility was used to explore activated brain regions and their cognitive changes. METHODS: Volunteers were randomly recruited using advertisements. Forty volunteers were recruited based on strict inclusion and exclusion criteria, and 40 volunteers were recruited. Brain function data of 40 healthy right-handed volunteers in fuzzy/clear Chinese reading tasks were collected using a Siemens Skyra 3.0T magnetic resonance scanner. Data were preprocessed and statistically analyzed using the statistical software SPM12.0 to observe the activation of the cortex and analyze its characteristics and possible changes in cognitive function. RESULTS: Task-fMRI analysis: (1) The main brain regions activated in fuzzy/clear reading tasks were located in the occipital visual cortex (P < 0.001); (2) a paired sample t-test suggested that there was a significant difference in BOLD signals in the brain regions activated by fuzzy/clear reading tasks (P < 0.001, equiv Z = 4.25). Compared with the fuzzy reading task, the brain regions more strongly activated in the clear reading task were mainly located in the right superior frontal gyrus and the bilateral temporal lobe. Compared with the clear reading task, the brain region that was more strongly activated in the fuzzy reading task was mainly located in the right fusiform gyrus. CONCLUSION: Clear Chinese character information mainly activates the dorsal stream of the visual-spatial network. This reflects the information transmission of the brain after understanding the text content and is responsible for guiding and controlling attention. Fuzzy words that cannot provide clear text content activate the fusiform gyrus of the ventral stream of the visual-spatial network, strengthening the function of orthographic processing.

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With the diversity in aphasia coupled with diminished gains at the chronic phase, it is imperative to deliver effective rehabilitation plans. Treatment outcomes have therefore been predicted using lesion-to-symptom mapping, but this method lacks holistic functional information about the language-network. This study, therefore, aims to develop whole-brain task-fMRI multivariate analysis to neurobiologically inspect lesion impacts on the language-network and predict behavioral outcomes in persons with aphasia (PWA) undergoing language therapy. In 14 chronic PWA, semantic fluency task-fMRI and behavioral measures were collected to develop prediction methodologies for post-treatment outcomes. Then, a recently developed imaging-based multivariate method to predict behavior (i.e., LESYMAP) was optimized to intake whole-brain task-fMRI data, and systematically tested for reliability with mass univariate methods. We also accounted for lesion size in both methods. Results showed that both mass univariate and multivariate methods identified unique biomarkers for semantic fluency improvements from baseline to 2-weeks post-treatment. Additionally, both methods demonstrated reliable spatial overlap in task-specific areas including the right middle frontal gyrus when identifying biomarkers of language discourse. Thus whole-brain task-fMRI multivariate analysis has the potential to identify functionally meaningful prognostic biomarkers even for relatively small sample sizes. In sum, our task-fMRI based multivariate approach holistically estimates post-treatment response for both word and sentence production and may serve as a complementary tool to mass univariate analysis in developing brain-behavior relationships for improved personalization of aphasia rehabilitation regimens.

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Resting-state fMRI is an increasingly popular alternative to task-based fMRI. However, a formal quantification of the amount of information provided by resting-state fMRI as opposed to active task conditions about neural responses is lacking. We conducted a systematic comparison of the quality of inferences derived from a resting-state and a task fMRI paradigm by means of Bayesian Data Comparison. In this framework, data quality is formally quantified in information-theoretic terms as the precision and amount of information provided by the data on the parameters of interest. Parameters of effective connectivity, estimated from the cross-spectral densities of resting-state- and task time series by means of dynamic causal modelling (DCM), were subjected to the analysis. Data from 50 individuals undergoing resting-state and a Theory-of-Mind task were compared, both datasets provided by the Human Connectome Project. A threshold of very strong evidence was reached in favour of the Theory-of-Mind task (>10 bits or natural units) regarding information gain, which could be attributed to the active task condition eliciting stronger effective connectivity. Extending these analyses to other tasks and cognitive systems will reveal whether the superior informative value of task-based fMRI observed here is case specific or a more general trend.

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RATIONALE: Emotion regulation (ER) difficulties have been previously described in bipolar disorder (BD). Whilst lithium has been shown to be effective in the treatment of BD, the mechanisms underlying lithium's effect on mood stabilisation remain unclear. OBJECTIVES: Unravelling lithium's effect on psychological processes impaired in BD, such as ER, could address this translational gap and inform the development of new treatments. METHODS: This study investigated the neural effects of lithium (800mg) on ER in 33 healthy volunteers in a double-blind between-groups design, randomised to lithium (n=17) or placebo (n=16) for 11 days. At treatment completion, participants underwent 3-Tesla fMRI scan whilst performing an ER task. RESULTS: Reappraisal reduced negative affect across groups and led to the expected increase in frontal brain activity. Participants receiving lithium showed (1) decreased activation in prefrontal and posterior parietal cortices and connectivity between the fronto-limbic network (Z>2.3, p<0.05 corrected); and (2) increased activity in the right superior temporal gyrus (Z>3.1, p<0.05 corrected) and connectivity between the right medial temporal gyrus (MTG) and left middle frontal gyrus (Z>2.3, p<0.05 corrected) during reappraisal. Further effects of lithium were found in response to negative picture presentation, whereby an anticorrelation was found between the left amygdala and the frontal cortex, and greater connectivity between the right MTG and the bilateral medial prefrontal cortex extending into the paracingulate gyrus, compared to placebo (Z>2.3, p < 0.05 corrected). CONCLUSIONS: These results show a potential effect of lithium on ER through its effects on activity and connectivity, and further elaborate the neural underpinnings of cognitive reappraisal. Future work should investigate longer term effects of lithium on ER in BD, ultimately benefitting the development of novel and more effective treatments.

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Predictions of task-based functional magnetic resonance imaging (fMRI) from task-free resting-state (rs) fMRI have gained popularity over the past decade. This method holds a great promise for studying individual variability in brain function without the need to perform highly demanding tasks. However, in order to be broadly used, prediction models must prove to generalize beyond the dataset they were trained on. In this work, we test the generalizability of prediction of task-fMRI from rs-fMRI across sites, MRI vendors and age-groups. Moreover, we investigate the data requirements for successful prediction. We use the Human Connectome Project (HCP) dataset to explore how different combinations of training sample sizes and number of fMRI datapoints affect prediction success in various cognitive tasks. We then apply models trained on HCP data to predict brain activations in data from a different site, a different MRI vendor (Phillips vs. Siemens scanners) and a different age group (children from the HCP-development project). We demonstrate that, depending on the task, a training set of approximately 20 participants with 100 fMRI timepoints each yields the largest gain in model performance. Nevertheless, further increasing sample size and number of timepoints results in significantly improved predictions, until reaching approximately 450-600 training participants and 800-1000 timepoints. Overall, the number of fMRI timepoints influences prediction success more than the sample size. We further show that models trained on adequate amounts of data successfully generalize across sites, vendors and age groups and provide predictions that are both accurate and individual-specific. These findings suggest that large-scale publicly available datasets may be utilized to study brain function in smaller, unique samples.

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