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Maltreatment during childhood is a major risk factor for anxiety and depression, which are major public health problems. However, the underlying brain mechanism linking maltreatment and internalizing disorders remains poorly understood. Maltreatment may alter the activation of fear circuitry, but little is known about its impact on the connectivity of this circuitry in adolescence and whether such brain changes actually lead to internalizing symptoms. We examined the associations between experiences of maltreatment during childhood, resting-state functional brain connectivity (rs-FC) of the amygdala and hippocampus, and internalizing symptoms in 64 adolescents participating in a longitudinal community study. Childhood experiences of maltreatment were associated with lower hippocampus–subgenual cingulate rs-FC in both adolescent females and males and lower amygdala–subgenual cingulate rs-FC in females only. Furthermore, rs-FC mediated the association of maltreatment during childhood with adolescent internalizing symptoms. Thus, maltreatment in childhood, even at the lower severity levels found in a community sample, may alter the regulatory capacity of the brain’s fear circuit, leading to increased internalizing symptoms by late adolescence. These findings highlight the importance of fronto–hippocampal connectivity for both sexes in internalizing symptoms following maltreatment in childhood. Furthermore, the impact of maltreatment during childhood on both fronto–amygdala and –hippocampal connectivity in females may help explain their higher risk for internalizing disorders such as anxiety and depression.
Early life stress (ELS) and function of the hypothalamic-pituitary-adrenal axis predict later psychopathology. Animal studies and cross-sectional human studies suggest that this process might operate through amygdala-ventromedial prefrontal cortex (vmPFC) circuitry implicated in the regulation of emotion. Here we prospectively investigated the roles of ELS and childhood basal cortisol amounts in the development of adolescent resting-state functional connectivity (rs-FC), assessed by functional connectivity magnetic resonance imaging (fcMRI), in the amygdala-PFC circuit. In females only, greater ELS predicted increased childhood cortisol levels, which predicted decreased amygdala-vmPFC rs-FC 14 years later. For females, adolescent amygdala-vmPFC functional connectivity was inversely correlated with concurrent anxiety symptoms but positively associated with depressive symptoms, suggesting differing pathways from childhood cortisol levels function through adolescent amygdala-vmPFC functional connectivity to anxiety and depression. These data highlight that, for females, the effects of ELS and early HPA-axis function may be detected much later in the intrinsic processing of emotion-related brain circuits.
OBJECTIVE: High-density EEG recording offers increased spatial resolution but requires careful consideration of how the density of electrodes affects the potentials being measured. Power differences as a function of electrode density and electrolyte spreading were examined and a method for correcting these differences was tested. METHODS: Separate EEG recordings from 8 participants were made using a high-density electrode net, first with 6 of 128 electrodes active followed by recordings with all electrodes active. For a subset of 4 participants measurements were counterbalanced with recordings made in the reversed order by drying the hair after the high-density recordings and using a fresh dry electrode net of the same size for the low-density recordings. Mean power values over 6 resting eyes open/closed EEG recordings at the 6 active electrodes common to both recording conditions were compared. Evidence for possible electrolyte spreading or bridging between electrodes was acquired by computing Hjorth electrical distances. Spherical spline interpolation was tested for correcting power values at electrodes affected by electrolyte spreading for these participants and for a subset of participants from a larger previous study. RESULTS: For both the complete set and the counterbalanced subset, significant decreases in power at the 6 common electrodes for the high-density recordings were observed across the range of the standard EEG bands (1-44 Hz). The number of bridges or amount of electrolyte spreading towards the reference electrode as evidenced by small Hjorth electrical distances served as a predictor of this power decrease. Spherical spline interpolation increased the power values at electrodes affected by electrolyte spreading and by a significant amount for the larger number of participants in the second group. CONCLUSIONS: Understanding signal effects caused by closely spaced electrodes, detecting electrolyte spreading and correcting its effects are important considerations for high-density EEG recordings. A combination of scalp maps of power density and plots of small Hjorth electrical distances can be used to identify electrodes affected by electrolyte spreading. Interpolation using spherical splines offers a method for correcting the potentials measured at these electrodes.
Neuroanatomists posit that the central nucleus of the amygdala (Ce) and bed nucleus of the stria terminalis (BST) comprise two major nodes of a macrostructural forebrain entity termed the extended amygdala. The extended amygdala is thought to play a critical role in adaptive motivational behavior and is implicated in the pathophysiology of maladaptive fear and anxiety. Resting functional connectivity of the Ce was examined in 107 young anesthetized rhesus monkeys and 105 young humans using standard resting-state functional magnetic resonance imaging (fMRI) methods to assess temporal correlations across the brain. The data expand the neuroanatomical concept of the extended amygdala by finding, in both species, highly significant functional coupling between the Ce and the BST. These results support the use of in vivo functional imaging methods in nonhuman and human primates to probe the functional anatomy of major brain networks such as the extended amygdala.
Here, we describe a novel method for volumetric segmentation of the amygdala from MRI images collected from 35 human subjects. This approach is adapted from open-source techniques employed previously with the hippocampus (Suh et al., 2011; Wang et al., 2011a,b). Using multi-atlas segmentation and machine learning-based correction, we were able to produce automated amygdala segments with high Dice (Mean = 0.918 for the left amygdala; 0.916 for the right amygdala) and Jaccard coefficients (Mean = 0.850 for the left; 0.846 for the right) compared to rigorously hand-traced volumes. This automated routine also produced amygdala segments with high intra-class correlations (consistency = 0.830, absolute agreement = 0.819 for the left; consistency = 0.786, absolute agreement = 0.783 for the right) and bivariate (r = 0.831 for the left; r = 0.797 for the right) compared to hand-drawn amygdala. Our results are discussed in relation to other cutting-edge segmentation techniques, as well as commonly available approaches to amygdala segmentation (e.g., Freesurfer). We believe this new technique has broad application to research with large sample sizes for which amygdala quantification might be needed.
An individual's affective style is influenced by many things, including the manner in which an individual responds to an emotional challenge. Emotional response is composed of a number of factors, two of which are the initial reactivity to an emotional stimulus and the subsequent recovery once the stimulus terminates or ceases to be relevant. However, most neuroimaging studies examining emotional processing in humans focus on the magnitude of initial reactivity to a stimulus rather than the prolonged response. In this study, we use functional magnetic resonance imaging to study the time course of amygdala activity in healthy adults in response to presentation of negative images. We split the amygdala time course into an initial reactivity period and a recovery period beginning after the offset of the stimulus. We find that initial reactivity in the amygdala does not predict trait measures of affective style. Conversely, amygdala recovery shows predictive power such that slower amygdala recovery from negative images predicts greater trait neuroticism, in addition to lower levels of likability of a set of social stimuli (neutral faces). These data underscore the importance of taking into account temporal dynamics when studying affective processing using neuroimaging.