Disrupted Intersubject Variability Architecture in Functional Connectomes in Schizophrenia

Schizophrenia (SCZ) is a highly heterogeneous disorder with remarkable intersubject variability in clinical presentations. Previous neuroimaging studies in SCZ have primarily focused on identifying group-averaged differences in the brain connectome between patients and healthy controls (HCs), largely neglecting the intersubject differences among patients. We acquired whole-brain resting-state functional MRI data from 121 SCZ patients and 183 HCs and examined the intersubject variability of the functional connectome (IVFC) in SCZ patients and HCs. Between-group differences were determined using permutation analysis. Then, we evaluated the relationship between IVFC and clinical variables in SCZ. Finally, we used datasets of patients with bipolar disorder (BD) and major depressive disorder (MDD) to assess the specificity of IVFC alteration in SCZ. The whole-brain IVFC pattern in the SCZ group was generally similar to that in HCs. Compared with the HC group, the SCZ group exhibited higher IVFC in the bilateral sensorimotor, visual, auditory, and subcortical regions. Moreover, altered IVFC was negatively correlated with age of onset, illness duration, and Brief Psychiatric Rating Scale scores and positively correlated with clinical heterogeneity. Although the SCZ shared altered IVFC in the visual cortex with BD and MDD, the alterations of IVFC in the sensorimotor, auditory, and subcortical cortices were specific to SCZ. The alterations of whole-brain IVFC in SCZ have potential implications for the understanding of the high clinical heterogeneity of SCZ and the future individualized clinical diagnosis and treatment of this disease.     

Bayesian estimation of maximum entropy model for individualized energy landscape analysis of brain state dynamics

The pairwise maximum entropy model (MEM) for resting state functional MRI (rsfMRI) has been used to generate energy landscape of brain states and to explore nonlinear brain state dynamics. Researches using MEM, however, has mostly been restricted to fixed‐effect group‐level analyses, using concatenated time series across individuals, due to the need for large samples in the parameter estimation of MEM. To mitigate the small sample problem in analyzing energy landscapes for individuals, we propose a Bayesian estimation of individual MEM using variational Bayes approximation (BMEM). We evaluated the performances of BMEM with respect to sample sizes and prior information using simulation. BMEM showed advantages over conventional maximum likelihood estimation in reliably estimating model parameters for individuals with small sample data, particularly utilizing the empirical priors derived from group data. We then analyzed individual rsfMRI of the Human Connectome Project to show the usefulness of MEM in differentiating individuals and in exploring neural correlates for human behavior. MEM and its energy landscape properties showed high subject specificity comparable to that of functional connectivity. Canonical correlation analysis identified canonical variables for MEM highly associated with cognitive scores. Inter‐individual variations of cognitive scores were also reflected in energy landscape properties such as energies, occupation times, and basin sizes at local minima. We conclude that BMEM provides an efficient method to characterize dynamic properties of individuals using energy landscape analysis of individual brain states.     

Multi-session delivery of synchronous rTMS and sensory stimulation induces long-term plasticity

BackgroundCombining training or sensory stimulation with non-invasive brain stimulation has shown to improve performance in healthy subjects and improve brain function in patients after brain injury. However, the plasticity mechanisms and the optimal parameters to induce long-term and sustainable enhanced performance remain unknown.ObjectiveThis work was designed to identify the protocols of which combining sensory stimulation with repetitive transcranial magnetic stimulation (rTMS) will facilitate the greatest changes in fMRI activation maps in the rat's primary somatosensory cortex (S1).MethodsSeveral protocols of combining forepaw electrical stimulation with rTMS were tested, including a single stimulation session compared to multiple, daily stimulation sessions, as well as synchronous and asynchronous delivery of both modalities. High-resolution fMRI was used to determine how pairing sensory stimulation with rTMS induced short and long-term plasticity in the rat S1.ResultsAll groups that received a single session of rTMS showed short-term increases in S1 activity, but these increases did not last three days after the session. The group that received a stimulation protocol of 10 Hz forepaw stimulation that was delivered simultaneously with 10 Hz rTMS for five consecutive days demonstrated the greatest increases in the extent of the evoked fMRI responses compared to groups that received other stimulation protocols.ConclusionsOur results provide direct indication that pairing peripheral stimulation with rTMS induces long-term plasticity, and this phenomenon appears to follow a time-dependent plasticity mechanism. These results will be important to lead the design of new training and rehabilitation paradigms and training towards achieving maximal performance in healthy subjects.     

The impact of individual electrical fields and anatomical factors on the neurophysiological outcomes of tDCS: A TMS-MEP and MRI study

BackgroundTranscranial direct current stimulation (tDCS), a neuromodulatory non-invasive brain stimulation technique, has shown promising results in basic and clinical studies. The known interindividual variability of the effects, however, limits the efficacy of the technique. Recently we reported neurophysiological effects of tDCS applied over the primary motor cortex at the group level, based on data from twenty-nine participants who received 15min of either sham, 0.5, 1.0, 1.5 or 2.0 mA anodal, or cathodal tDCS. The neurophysiological effects were evaluated via changes in: 1) transcranial magnetic stimulation (TMS)-induced motor evoked potentials (MEP), and 2) cerebral blood flow (CBF) measured by functional magnetic resonance imaging (MRI) via arterial spin labeling (ASL). At the group level, dose-dependent effects of the intervention were obtained, which however displayed interindividual variability.MethodIn the present study, we investigated the cause of the observed inter-individual variability. To this end, for each participant, a MRI-based realistic head model was designed to 1) calculate anatomical factors and 2) simulate the tDCS- and TMS-induced electrical fields (EFs). We first investigated at the regional level which individual anatomical factors explained the simulated EFs (magnitude and normal component). Then, we explored which specific anatomical and/or EF factors predicted the neurophysiological outcomes of tDCS.ResultsThe results highlight a significant negative correlation between regional electrode-to-cortex distance (rECD) as well as regional CSF (rCSF) thickness, and the individual EF characteristics. In addition, while both rCSF thickness and rECD anticorrelated with tDCS-induced physiological changes, EFs positively correlated with the effects.ConclusionThese results provide novel insights into the dependency of the neuromodulatory effects of tDCS on individual physical factors.     

Neurodevelopmental differences in child and adult number processing: An fMRI-based validation of the triple code model

The triple code model of numerical cognition (TCM) details the neurocognitive mechanisms associated with perceiving and manipulating numerical information in exact symbolic (Arabic digits and number words) and approximate nonsymbolic numerical magnitude (e.g., dot arrays) representation codes. The current study provides a first empirical fMRI-based investigation into neurodevelopmental differences in 30 healthy children’s and 44 healthy adults’ recruitment of neural correlates associated with the Arabic digit, number word, and nonsymbolic magnitude codes. Differences between the two groups were found in cingulate regions commonly associated with domain-general aspects of cognitive control, as opposed to neural correlates of number processing per se. A primary developmental difference was identified in verbal number discrimination, where only adults recruited left-lateralized perisylvian language areas in accordance with the TCM. We therefore call for a revision of the verbal code and a formulation of separate child and adult-specific neurocognitive mechanisms associated with the discrimination of number words. Although further research is necessary, results indicate that numerical discrimination abilities in middle-school-aged children operate close to adult-level maturity. Neurodevelopmental differences may be more apparent in younger children, or on the level of functional network dynamics as opposed to a shift in recruited neural substrates.     

Multimodal brain predictors of current weight and weight gain in children enrolled in the ABCD study ®

Multimodal neuroimaging assessments were utilized to identify generalizable brain correlates of current body mass index (BMI) and predictors of pathological weight gain (i.e., beyond normative development) one year later. Multimodal data from children enrolled in the Adolescent Brain Cognitive Development Study® at 9-to-10-years-old, consisted of structural magnetic resonance imaging (MRI), diffusion tensor imaging (DTI), resting state (rs), and three task-based functional (f) MRI scans assessing reward processing, inhibitory control, and working memory. Cross-validated elastic-net regression revealed widespread structural associations with BMI (e.g., cortical thickness, surface area, subcortical volume, and DTI), which explained 35% of the variance in the training set and generalized well to the test set (R² = 0.27). Widespread rsfMRI inter- and intra-network correlations were related to BMI (R²_train = 0.21; R²_test = 0.14), as were regional activations on the working memory task (R²_train = 0.20; (R² _test = 0.16). However, reward and inhibitory control tasks were unrelated to BMI. Further, pathological weight gain was predicted by structural features (Area Under the Curve (AUC)_train = 0.83; AUC_test = 0.83, p < 0.001), but not by fMRI nor rsfMRI. These results establish generalizable brain correlates of current weight and future pathological weight gain. These results also suggest that sMRI may have particular value for identifying children at risk for pathological weight gain.     

Reward-related neural correlates of early life stress in school-aged children

ObjectivesEarly life stress likely contributes to dysfunction in neural reward processing systems. However, studies to date have focused almost exclusively on adolescents and adults, measured early life stress retrospectively, and have often failed to control for concurrent levels of stress. The current study examined the contribution of prospectively measured cumulative life stress in preschool-age children on reward-related neural activation and connectivity in school-age children.MethodsChildren (N = 46) and caregivers reported children’s exposure to early life stress between birth and preschool age (mean = 4.8 years, SD = 0.80). At follow-up (mean age = 7.52 years, SD = .78), participants performed a child-friendly monetary incentive delay task during functional magnetic resonance imaging.ResultsChildren with higher levels of cumulative early life stress, controlling for concurrent stressful life events, exhibited aberrant patterns of neural activation and connectivity in reward- and emotion-related regions (e.g., prefrontal cortex, temporal pole, culmen), depending on the presence of a potential reward and whether or not the target was hit or missed.ConclusionsFindings suggest that stress exposure during early childhood may impact neural reward processing systems earlier in development than has previously been demonstrated. Understanding how early life stress relates to alterations in reward processing could guide earlier, more mechanistic interventions.