Search

Transcranial direct current stimulation (tDCS) has wide ranging applications in neuro-behavioural and physiological research, and in neurological rehabilitation. However, it is currently limited by substantial inter-subject variability in responses, which may be explained, at least in part, by anatomical differences that lead to variability in the electric field (E-field) induced in the cortex. Here, we tested whether the variability in the E-field in the stimulated cortex during anodal tDCS, estimated using computational simulations, explains the variability in tDCS induced changes in GABA, a neurophysiological marker of stimulation effect. Data from five previously conducted MRS studies were combined. The anode was placed over the left primary motor cortex (M1, 3 studies, N = 24) or right temporal cortex (2 studies, N = 32), with the cathode over the contralateral supraorbital ridge. Single voxel spectroscopy was performed in a 2x2x2cm voxel under the anode in all cases. MRS data were acquired before and either during or after 1 mA tDCS using either a sLASER sequence (7T) or a MEGA-PRESS sequence (3T). sLASER MRS data were analysed using LCModel, and MEGA-PRESS using FID-A and Gannet. E-fields were simulated in a finite element model of the head, based on individual structural MR images, using SimNIBS. Separate linear mixed effects models were run for each E-field variable (mean and 95th percentile; magnitude, and components normal and tangential to grey matter surface, within the MRS voxel). The model included effects of time (pre or post tDCS), E-field, grey matter volume in the MRS voxel, and a 3-way interaction between time, E-field and grey matter volume. Additionally, we ran a permutation analysis using PALM to determine whether E-field anywhere in the brain, not just in the MRS voxel, correlated with GABA change. In M1, higher mean E-field magnitude was associated with greater anodal tDCS-induced decreases in GABA (t(24) = 3.24, p = 0.003). Further, the association between mean E-field magnitude and GABA change was moderated by the grey matter volume in the MRS voxel (t(24) = −3.55, p = 0.002). These relationships were consistent across all E-field variables except the mean of the normal component. No significant relationship was found between tDCS-induced GABA decrease and E-field in the temporal voxel. No significant clusters were found in the whole brain analysis. Our data suggest that the electric field induced by tDCS within the brain is variable, and is significantly related to anodal tDCS-induced decrease in GABA, a key neurophysiological marker of stimulation. These findings strongly support individualised dosing of tDCS, at least in M1. Further studies examining E-fields in relation to other outcome measures, including behaviour, will help determine the optimal E-fields required for any desired effects. • We study the link between individually simulated electric field dose and anodal tDCS-induced change in GABA in the cortex. • The electric field strength in the brain correlates with a decrease in GABA in the motor cortex. • The correlation between the electric field and GABA change is modulated by the amount of grey matter in the MRS voxel. • We find no association between the electric field and GABA in the temporal cortex. [ABSTRACT FROM AUTHOR]

The hippocampus and the entorhinal cortex are considered the main brain structures for allocentric representation of the external environment. Here, we show that the amygdala and the ventral visual stream are involved in allocentric representation. Thirty-one young men explored 35 virtual environments during high-resolution functional magnetic resonance imaging (fMRI) of the medial temporal lobe (MTL) and were subsequently tested on recall of the allocentric pattern of the objects in each environment—in other words, the positions of the objects relative to each other and to the outer perimeter. We find increasingly unique brain activation patterns associated with increasing allocentric accuracy in distinct neural populations in the perirhinal cortex, parahippocampal cortex, fusiform cortex, amygdala, hippocampus, and entorhinal cortex. In contrast to the traditional view of a hierarchical MTL network with the hippocampus at the top, we demonstrate, using recently developed graph analyses, a hierarchical allocentric MTL network without a main connector hub. • The allocentric medial temporal lobe network is globally efficient, with no main hub • Ventral visual stream plays a particularly central role in the allocentric network • Allocentric representations are in distinct but neighboring neural populations • The human brain encodes both scaled and true Euclidean representations Evensmoen et al. demonstrate that the human brain encodes scaled and true Euclidean representations of allocentric space within an extensively connected medial temporal lobe network with no main connector hub. The network includes the parahippocampal cortex, fusiform cortex, hippocampus, amygdala, perirhinal cortex, and entorhinal cortex. [ABSTRACT FROM AUTHOR]

Background: Pathophysiological models of bipolar disorder postulate that mood dysregulation arises from fronto-limbic dysfunction, marked by reduced prefrontal cortex (PFC) inhibitory control. This might occur due to both disruptions within PFC networks and abnormal inhibition over subcortical structures involved in emotional processing. However, no study has examined global PFC dysconnectivity in bipolar disorder and tested whether regions with within-PFC dysconnectivity also exhibit fronto-limbic connectivity deficits. Furthermore, no study has investigated whether such connectivity disruptions differ for bipolar patients with psychosis history, who might exhibit a more severe clinical course. Methods: We collected resting-state functional magnetic resonance imaging at 3T in 68 remitted bipolar I patients (34 with psychosis history) and 51 demographically matched healthy participants. We employed a recently developed global brain connectivity method, restricted to PFC (rGBC). We also independently tested connectivity between anatomically defined amygdala and PFC. Results: Bipolar patients exhibited reduced medial prefrontal cortex (mPFC) rGBC, increased amygdala–mPFC connectivity, and reduced connectivity between amygdala and dorsolateral PFC. All effects were driven by psychosis history. Moreover, the magnitude of observed effects was significantly associated with lifetime psychotic symptom severity. Conclusions: This convergence between rGBC, seed-based amygdala findings, and symptom severity analyses highlights that mPFC, a core emotion regulation region, exhibits both within-PFC dysconnectivity and connectivity abnormalities with limbic structures in bipolar illness. Furthermore, lateral PFC dysconnectivity in patients with psychosis history converges with published work in schizophrenia, indicating possible shared risk factors. Observed dysconnectivity in remitted patients suggests a bipolar trait characteristic and might constitute a risk factor for phasic features of the disorder. [Copyright &y& Elsevier]

Background: Despite overwhelming evidence that major depression is highly heritable, recent studies have localized only a single depression-related locus reaching genome-wide significance and have yet to identify a causal gene. Focusing on family-based studies of quantitative intermediate phenotypes or endophenotypes, in tandem with studies of unrelated individuals using categorical diagnoses, should improve the likelihood of identifying major depression genes. However, there is currently no empirically derived statistically rigorous method for selecting optimal endophentypes for mental illnesses. Here, we describe the endophenotype ranking value, a new objective index of the genetic utility of endophenotypes for any heritable illness. Methods: Applying endophenotype ranking value analysis to a high-dimensional set of over 11,000 traits drawn from behavioral/neurocognitive, neuroanatomic, and transcriptomic phenotypic domains, we identified a set of objective endophenotypes for recurrent major depression in a sample of Mexican American individuals (n = 1122) from large randomly selected extended pedigrees. Results: Top-ranked endophenotypes included the Beck Depression Inventory, bilateral ventral diencephalon volume, and expression levels of the RNF123 transcript. To illustrate the utility of endophentypes in this context, each of these traits were utlized along with disease status in bivariate linkage analysis. A genome-wide significant quantitative trait locus was localized on chromsome 4p15 (logarithm of odds = 3.5) exhibiting pleiotropic effects on both the endophenotype (lymphocyte-derived expression levels of the RNF123 gene) and disease risk. Conclusions: The wider use of quantitative endophenotypes, combined with unbiased methods for selecting among these measures, should spur new insights into the biological mechanisms that influence mental illnesses like major depression. [Copyright &y& Elsevier]

Abstract: Working memory is a highly heritable complex cognitive trait that is critical for a number of higher-level functions. However, the neural substrates of this behavioral phenotype are intricate and it is unknown through what precise biological mechanism variation in working memory is transmitted. In this review we explore different functional and structural components of the working memory circuitry, and the degree to which each of them is contributed to by genetic factors. Specifically, we consider dopaminergic function, glutamatergic function, white matter integrity and gray matter structure all of which provide potential mechanisms for the inheritance of working memory deficits. In addition to discussing the overall heritability of these measures we also address specific genes that may play a role. Each of these heritable components has the potential to uniquely contribute to the working memory deficits observed in genetic disorders, including 22q deletion syndrome, fragile X syndrome, phenylketonuria (PKU), and schizophrenia. By observing the individual contributions of disruptions in different components of the working memory circuitry to behavioral performance, we highlight the concept that there may be many routes to a working memory deficit; even though the same cognitive measure may be a valid endophenotype across different disorders, the underlying cause of, and treatment for, the deficit may differ. This has implications for our understanding of the transmission of working memory deficits in both healthy and disordered populations. [Copyright &y& Elsevier]

Imaging research has not yet delivered reliable psychiatric biomarkers. One challenge, particularly among youth, is high comorbidity. This challenge might be met through canonical correlation analysis designed to model mutual dependencies between symptom dimensions and neural measures. We mapped the multivariate associations that intrinsic functional connectivity manifests with pediatric symptoms of anxiety, irritability, and attention-deficit/hyperactivity disorder (ADHD) as common, impactful, co-occurring problems. We evaluate the replicability of such latent dimensions in an independent sample. We obtained ratings of anxiety, irritability, and ADHD, and 10 minutes of resting-state functional magnetic resonance imaging data, from two independent cohorts. Both cohorts (discovery: n = 182; replication: n = 326) included treatment-seeking youth with anxiety disorders, with disruptive mood dysregulation disorder, with ADHD, or without psychopathology. Functional connectivity was modeled as partial correlations among 216 brain areas. Using canonical correlation analysis and independent component analysis jointly we sought maximally correlated, maximally interpretable latent dimensions of brain connectivity and clinical symptoms. We identified seven canonical variates in the discovery and five in the replication cohort. Of these canonical variates, three exhibited similarities across datasets: two variates consistently captured shared aspects of irritability, ADHD, and anxiety, while the third was specific to anxiety. Across cohorts, canonical variates did not relate to specific resting-state networks but comprised edges interconnecting established networks within and across both hemispheres. Findings revealed two replicable types of clinical variates, one related to multiple symptom dimensions and a second relatively specific to anxiety. Both types involved a multitude of broadly distributed, weak brain connections as opposed to strong connections encompassing known resting-state networks. [ABSTRACT FROM AUTHOR]

While translational theories link neurodevelopmental changes in threat learning to pathological anxiety, findings from studies in patients inconsistently support these theories. This inconsistency may reflect difficulties in studying large patient samples with wide age ranges using consistent methods. A dearth of imaging data in patients further limits translational advances. We address these gaps through a psychophysiology and structural brain imaging study in a large sample of patients across the lifespan. A total of 351 participants (8–50 years of age; 209 female subjects; 195 healthy participants and 156 medication-free, treatment-seeking patients with anxiety) completed a differential threat conditioning and extinction paradigm that has been validated in pediatric and adult populations. Skin conductance response indexed psychophysiological response to conditioned (CS+, CS−) and unconditioned threat stimuli. Structural magnetic resonance imaging data were available for 250 participants. Analyses tested anxiety and age associations with psychophysiological response in addition to associations between psychophysiology and brain structure. Regardless of age, patients and healthy comparison subjects demonstrated comparable differential threat conditioning and extinction. The magnitude of skin conductance response to both conditioned stimulus types differentiated patients from comparison subjects and covaried with dorsal prefrontal cortical thickness; structure–response associations were moderated by anxiety and age in several regions. Unconditioned responding was unrelated to anxiety and brain structure. Rather than impaired threat learning, pathological anxiety involves heightened skin conductance response to potential but not immediately present threats; this anxiety-related potentiation of anticipatory responding also relates to variation in brain structure. These findings inform theoretical considerations by highlighting anticipatory response to potential threat in anxiety. [ABSTRACT FROM AUTHOR]

Anxiety disorders are among the most prevalent psychiatric disorders. Neuroimaging findings remain uncertain, and resting state functional magnetic resonance (rs-fMRI) connectivity is of particular interest since it is a scalable functional imaging modality. Given heterogeneous past findings for rs-fMRI in anxious individuals, we characterize patterns across anxiety disorders by conducting a systematic review and meta-analysis. Studies were included if they contained at the time of scanning both a healthy group and a patient group. Due to insufficient study numbers, the quantitative meta-analysis only included seed-based studies. We performed an activation likelihood estimation (ALE) analysis that compared patients and healthy volunteers. All analyses were corrected for family-wise error with a cluster-level threshold of p <.05. Patients exhibited hypo-connectivity between the amygdala and the medial frontal gyrus, anterior cingulate cortex, and cingulate gyrus. This finding, however, was not robust to potential file-drawer effects. Though limited by strict inclusion criteria, our results highlight the heterogeneous nature of reported findings. This underscores the need for data sharing when attempting to detect reliable patterns of disruption in brain activity across anxiety disorders. • There are numerous studies investigating rs-fMRI and anxiety; however, the methodologies are inconsistent. • Anxiety patients show hypoconnectivity between the amygdala and the medial prefrontal cortex. • This finding is not robust against possible publication bias. Thus, no strong findings manifest in available literature. • More studies are needed with standardized methods and larger sample sizes. [ABSTRACT FROM AUTHOR]

Background Although case-control approaches are beginning to disentangle schizophrenia’s complex polygenic burden, other methods will likely be necessary to fully identify and characterize risk genes. Endophenotypes, traits genetically correlated with an illness, can help characterize the impact of risk genes by providing genetically relevant traits that are more tractable than the behavioral symptoms that classify mental illness. Here, we present an analytic approach for discovering and empirically validating endophenotypes in extended pedigrees with very few affected individuals. Our approach indexes each family member’s risk as a function of shared genetic kinship with an affected individual, often referred to as the coefficient of relatedness. To demonstrate the utility of this approach, we search for neurocognitive and neuroanatomic endophenotypes for schizophrenia in large unselected multigenerational pedigrees. Methods A fixed-effects test within the variance component framework was performed on neurocognitive and cortical surface area traits in 1606 Mexican-American individuals from large, randomly ascertained extended pedigrees who participated in the Genetics of Brain Structure and Function study. As affecteds were excluded from analyses, results were not influenced by disease state or medication usage. Results Despite having sampled just 6 individuals with schizophrenia, our sample provided 233 individuals at various levels of genetic risk for the disorder. We identified three neurocognitive measures (digit-symbol substitution, facial memory, and emotion recognition) and six medial temporal and prefrontal cortical surfaces associated with liability for schizophrenia. Conclusions With our novel analytic approach, one can discover and rank endophenotypes for schizophrenia, or any heritable disease, in randomly ascertained pedigrees. [ABSTRACT FROM AUTHOR]

• Cross-species research suggests that conditioned inhibition reduces fear responding. • This is the first study of conditioned inhibition in pediatric anxiety. • Children with anxiety disorders showed differential activity in vmPFC. • Future research should further examine conditioned inhibition in pediatric anxiety. Cognitive-behavioral therapy (CBT), a first-line treatment for pediatric anxiety disorders, is based on principles of threat learning and extinction. However, CBT does not work sufficiently for up to 40% of clinically anxious youth. The neural and behavioral correlates of conditioned inhibition might provide promising targets for attempts to improve CBT response. During conditioned inhibition, threat and safety cues appear together, forming a safety compound. Here, we test whether this safety compound elicits a reduced fear response compared to pairing the threat cue with a novel cue (novel compound). The current pilot study compares behavioral, physiological, and neural correlates of conditioned inhibition between children with (n = 17, M age = 13.09, SD age = 3.05) and without (n = 18, M age = 14.49, SD age = 2.38) anxiety disorders. Behavioral and physiological measures did not differ between children with and without anxiety disorders during fear acquisition. During testing, children with anxiety disorders showed overall higher skin conductance response and expected to hear the aversive sound following the novel compound more often than children without anxiety disorders. Children with anxiety disorders showed more activity in the right ventromedial prefrontal cortex (vmPFC) to the safety versus novel compound. Children without anxiety disorders showed the opposite pattern – more right vmPFC activity to the novel versus safety compound (F (1,31) = 5.40, p = 0.03). No group differences manifested within the amygdala, dorsal anterior cingulate cortex, or hippocampus. These pilot findings suggest a feasible approach for examining conditioned inhibition in pediatric anxiety disorders. If replicated in larger samples, findings may implicate perturbed conditioned inhibition in pediatric anxiety disorders and provide targets for CBT. [ABSTRACT FROM AUTHOR]

• Aerobic exercise has been proposed to improve cognitive health, via brain structure. • 12-weeks of aerobic exercise did not change cognitive, grey or white matter measures. • Interventions may need to be longer lasting or multifactorial. While there is strong evidence from observational studies that physical activity is associated with reduced risk of cognitive decline and dementia, the extent to which aerobic training interventions impact on cognitive health and brain structure remains subject to debate. In a pilot study of 46 healthy older adults (66.6 years ± 5.2 years, 63% female), we compared the effects of a twelve-week aerobic training programme to a waitlist control condition on cardiorespiratory fitness, cognition and magnetic resonance imaging (MRI) outcomes. Cardiorespiratory fitness was assessed by VO 2 max testing. Cognitive assessments spanned executive function, memory and processing speed. Structural MRI analysis included examination of hippocampal volume, and voxel-wise assessment of grey matter volumes using voxel-based morphometry. Diffusion tensor imaging analysis of fractional anisotropy, axial diffusivity and radial diffusivity was performed using tract-based spatial statistics. While the intervention successfully increased cardiorespiratory fitness, there was no evidence that the aerobic training programme led to changes in cognitive functioning or measures of brain structure in older adults. Interventions that are longer lasting, multi-factorial, or targeted at specific high-risk populations, may yield more encouraging results. [ABSTRACT FROM AUTHOR]

• Somatosensory experience results in DTI changes in white matter (WM). • Macroscale metrics of WM structure correlate with mRNA markers of cortical activity. • MBP immunohistochemistry and mRNA expression indicate changes in myelin. • Both molecular and cellular evidence are consistent with DTI findings. • Myelination is one component of macroscale measures of WM plasticity. White matter (WM) plasticity during adulthood is a recently described phenomenon by which experience can shape brain structure. It has been observed in humans using diffusion tensor imaging (DTI) and myelination has been suggested as a possible mechanism. Here, we set out to identify molecular and cellular changes associated with WM plasticity measured by DTI. We combined DTI, immunohistochemistry and mRNA expression analysis and examined the effects of somatosensory experience in adult rats. First, we observed experience-induced DTI differences in WM and in grey matter structure. C-Fos mRNA expression, a marker of cortical activity, in the barrel cortex correlated with the MRI WM metrics, indicating that molecular correlates of cortical activity relate to macroscale measures of WM structure. Analysis of myelin-related genes revealed higher myelin basic protein (MBP) mRNA expression. Higher MBP protein expression was also found via immunohistochemistry in WM. Finally, unbiased RNA sequencing analysis identified 134 differentially expressed genes encoding proteins involved in functions related to cell proliferation and differentiation, regulation of myelination and neuronal activity modulation. In conclusion, macroscale measures of WM plasticity are supported by both molecular and cellular evidence and confirm that myelination is one of the underlying mechanisms. [ABSTRACT FROM AUTHOR]