Spontaneous low-frequency fluctuations in the blood oxygen level-dependent (BOLD) functional magnetic resonance imaging (MRI) signal have been shown to reflect neural synchrony between brain regions. ...A "default network" of spontaneous low-frequency fluctuations has been described in healthy volunteers during stimulus-independent thought. Negatively correlated with this network are regions activated during attention-demanding tasks. Both these networks involve brain regions and functions that have been linked with schizophrenia in previous research. The present study examined spontaneous slow fluctuations in the BOLD signal at rest, as measured by correlation with low-frequency oscillations in the posterior cingulate, in 17 schizophrenic patients, and 17 comparable healthy volunteers. Healthy volunteers demonstrated correlation between spontaneous low-frequency fluctuations of the BOLD signal in the posterior cingulate and fluctuations in the lateral parietal, medial prefrontal, and cerebellar regions, similar to previous reports. Schizophrenic patients had significantly less correlation between spontaneous slow activity in the posterior cingulate and that in the lateral parietal, medial prefrontal, and cerebellar regions. Connectivity of the posterior cingulate was found to vary with both positive and negative symptoms in schizophrenic patients. Because these data suggest significant abnormalities in resting-state neural networks in schizophrenia, further investigations of spontaneous slow fluctuations of the BOLD signal seem warranted in this population.
Long-distance vocal communication exists in many group-living carnivores. Understanding its behavioral and ecological significance suffers from few quantitative studies in undisturbed, wild ...populations. In Yellowstone National Park, Wyoming, United States, we examined seasonal changes in occurrence of wolf howls and howling replies based on more than 11,000 unsolicited howls given over a 10-year period. Howling was 5-fold most frequent in the pre-breeding and breeding seasons. Pack howls primarily, but also single howls, were most common during these seasons. Answers during these seasons were predominately interpack howls. These howling peaks correlated with elevations in estradiol, testosterone, and luteinizing hormone reported elsewhere. Following the breeding season, overall howling abruptly decreased through March and April, although howling at den sites was frequent, particularly in April and May. Howling frequency remained low all summer, during which time answers switched abruptly and almost exclusively from interpack to intrapack. Single howls stimulated distant pack members to answer with increasing frequency as the summer progressed. Although not independent, the frequency of both total howls and interpack howling rose throughout the fall. We relate these seasonal changes in total howling and interpack answers largely to breeding and spacing behavior in pre-breeding and breeding seasons, and intrapack answers to pack cohesion in other seasons. Because our results may reflect a high-density, unexploited wolf population, comparative studies under other conditions would be useful.
Despite the known benefits of data-driven approaches, the lack of approaches for identifying functional neuroimaging patterns that capture both individual variations and inter-subject correspondence ...limits the clinical utility of rsfMRI and its application to single-subject analyses. Here, using rsfMRI data from over 100k individuals across private and public datasets, we identify replicable multi-spatial-scale canonical intrinsic connectivity network (ICN) templates via the use of multi-model-order independent component analysis (ICA). We also study the feasibility of estimating subject-specific ICNs via spatially constrained ICA. The results show that the subject-level ICN estimations vary as a function of the ICN itself, the data length, and the spatial resolution. In general, large-scale ICNs require less data to achieve specific levels of (within- and between-subject) spatial similarity with their templates. Importantly, increasing data length can reduce an ICN's subject-level specificity, suggesting longer scans may not always be desirable. We also find a positive linear relationship between data length and spatial smoothness (possibly due to averaging over intrinsic dynamics), suggesting studies examining optimized data length should consider spatial smoothness. Finally, consistency in spatial similarity between ICNs estimated using the full data and subsets across different data lengths suggests lower within-subject spatial similarity in shorter data is not wholly defined by lower reliability in ICN estimates, but may be an indication of meaningful brain dynamics which average out as data length increases.
Objective
One factor potentially contributing to the heterogeneity of previous results on structural grey matter alterations in adult participants suffering from post‐traumatic stress disorder (PTSD) ...is the varying levels of dissociative symptomatology. The aim of this study was therefore to test whether the recently defined dissociative subtype of PTSD characterized by symptoms of depersonalization and derealization is characterized by specific differences in volumetric brain morphology.
Method
Whole‐brain MRI data were acquired for 59 patients with PTSD. Voxel‐based morphometry was carried out to test for group differences between patients classified as belonging (n = 15) vs. not belonging (n = 44) to the dissociative subtype of PTSD. The correlation between dissociation (depersonalization/derealization) severity and grey matter volume was computed.
Results
Patients with PTSD classified as belonging to the dissociative subtype exhibited greater grey matter volume in the right precentral and fusiform gyri as well as less volume in the right inferior temporal gyrus. Greater dissociation severity was associated with greater volume in the right middle frontal gyrus.
Conclusion
The results of this first whole‐brain investigation of specific grey matter volume in dissociative subtype PTSD indentified structural aberrations in regions subserving the processing and regulation of emotional arousal. These might constitute characteristic biomarkers for the dissociative subtype PTSD.
Objective
Electroencephalographic (EEG) neurofeedback training has been shown to produce plastic modulations in salience network and default mode network functional connectivity in healthy ...individuals. In this study, we investigated whether a single session of neurofeedback training aimed at the voluntary reduction of alpha rhythm (8–12 Hz) amplitude would be related to differences in EEG network oscillations, functional MRI (fMRI) connectivity, and subjective measures of state anxiety and arousal in a group of individuals with post‐traumatic stress disorder (PTSD).
Method
Twenty‐one individuals with PTSD related to childhood abuse underwent 30 min of EEG neurofeedback training preceded and followed by a resting‐state fMRI scan.
Results
Alpha desynchronizing neurofeedback was associated with decreased alpha amplitude during training, followed by a significant increase (‘rebound’) in resting‐state alpha synchronization. This rebound was linked to increased calmness, greater salience network connectivity with the right insula, and enhanced default mode network connectivity with bilateral posterior cingulate, right middle frontal gyrus, and left medial prefrontal cortex.
Conclusion
Our study represents a first step in elucidating the potential neurobehavioural mechanisms mediating the effects of neurofeedback treatment on regulatory systems in PTSD. Moreover, it documents for the first time a spontaneous EEG ‘rebound’ after neurofeedback, pointing to homeostatic/compensatory mechanisms operating in the brain.
Objective
To investigate the functional connectivity of large‐scale intrinsic connectivity networks (ICNs) in post‐traumatic stress disorder (PTSD) during subliminal and supraliminal presentation of ...threat‐related stimuli.
Method
Group independent component analysis was utilized to study functional connectivity within the ICNs most correlated with the Default‐mode Network (DMN), Salience Network (SN), and Central Executive Network (CEN) in PTSD participants (n = 26) as compared to healthy controls (n = 20) during sub‐ and supraliminal processing of threat‐related stimuli.
Results
Comparing patients with PTSD with healthy participants, prefrontal and anterior cingulate cortex involved in top‐down regulation showed increased integration during subliminal threat processing within the CEN and SN and during supraliminal threat processing within the DMN. The right amygdala showed increased connectivity with the DMN during subliminal processing in PTSD as compared to controls. Brain regions associated with self‐awareness and consciousness exhibited decreased connectivity during subliminal threat processing in PTSD as compared to controls: the claustrum within the SN and the precuneus within the DMN.
Conclusion
Key nodes of the ICNs showed altered functional connectivity in PTSD as compared to controls, and differential results characterized sub‐ and supraliminal processing of threat‐related stimuli. These findings enhance our understanding of ICNs underlying PTSD at different levels of conscious threat perception.
Objective: The goal of this study was to investigate the relationship between default mode network connectivity and the severity of post‐traumatic stress disorder (PTSD) symptoms in a sample of ...eleven acutely traumatized subjects.
Method: Participants underwent a 5.5 min resting functional magnetic resonance imaging scan. Brain areas whose activity positively correlated with that of the posterior cingulate/precuneus (PCC) were assessed. To assess the relationship between severity of PTSD symptoms and PCC connectivity, the contrast image representing areas positively correlated with the PCC was correlated with the subjects’ Clinician Administered PTSD Scale scores.
Results: Results suggest that resting state connectivity of the PCC with the perigenual anterior cingulate and the right amygdala is associated with current PTSD symptoms and that correlation with the right amygdala predicts future PTSD symptoms.
Conclusion: These results may contribute to the development of prognostic tools to distinguish between those who will and those who will not develop PTSD.
Brain oscillations exhibit long-range temporal correlations (LRTCs), which reflect the regularity of their fluctuations: low values representing more random (decorrelated) while high values more ...persistent (correlated) dynamics. LRTCs constitute supporting evidence that the brain operates near criticality, a state where neuronal activities are balanced between order and randomness. Here, healthy adults used closed-loop brain training (neurofeedback, NFB) to reduce the amplitude of alpha oscillations, producing a significant increase in spontaneous LRTCs post-training. This effect was reproduced in patients with post-traumatic stress disorder, where abnormally random dynamics were reversed by NFB, correlating with significant improvements in hyperarousal. Notably, regions manifesting abnormally low LRTCs (i.e., excessive randomness) normalized toward healthy population levels, consistent with theoretical predictions about self-organized criticality. Hence, when exposed to appropriate training, spontaneous cortical activity reveals a residual capacity for "self-tuning" its own temporal complexity, despite manifesting the abnormal dynamics seen in individuals with psychiatric disorder. Lastly, we observed an inverse-U relationship between strength of LRTC and oscillation amplitude, suggesting a breakdown of long-range dependence at high/low synchronization extremes, in line with recent computational models. Together, our findings offer a broader mechanistic framework for motivating research and clinical applications of NFB, encompassing disorders with perturbed LRTCs.
Immune-mediated thrombotic thrombocytopenic purpura (iTTP) is a rare condition caused by severe ADAMTS13 deficiency, leading to platelet aggregation and thrombosis. Despite treatment, patients are ...prone to cognitive impairment and depression. We investigated brain changes in iTTP patients during remission using advanced magnetic resonance imaging (MRI) techniques, correlating these changes with mood and neurocognitive tests. Twenty iTTP patients in remission (30 days post-haematological remission) were compared with six healthy controls. MRI scans, including standard and specialized sequences, were conducted to assess white matter health. Increased T1 relaxation times were found in the cingulate cortex (p < 0.05), and elevated T2 relaxation times were observed in the cingulate cortex, frontal, parietal and temporal lobes (p < 0.05). Pathological changes in these areas are correlated with impaired cognitive and depressive scores in concentration, short-term memory and verbal memory. This study highlights persistent white matter damage in iTTP patients, potentially contributing to depression and cognitive impairment. Key regions affected include the frontal lobe and cingulate cortex. These findings have significant implications for the acute and long-term management of iTTP, suggesting a need for re-evaluation of treatment approaches during both active phases and remission. Further research is warranted to enhance our understanding of these complexities.
Objective
This study determined the clinical utility of an fMRI classification algorithm predicting medication‐class of response in patients with challenging mood diagnoses.
Methods
Ninety‐nine ...16–27‐year‐olds underwent resting state fMRI scans in three groups—BD, MDD and healthy controls. A predictive algorithm was trained and cross‐validated on the known‐diagnosis patients using maximally spatially independent components (ICs), constructing a similarity matrix among subjects, partitioning the matrix in kernel space and optimizing support vector machine classifiers and IC combinations. This classifier was also applied to each of 12 new individual patients with unclear mood disorder diagnoses.
Results
Classification within the known‐diagnosis group was approximately 92.4% accurate. The five maximally contributory ICs were identified. Applied to the complicated patients, the algorithm diagnosis was consistent with optimal medication‐class of response to sustained recovery in 11 of 12 cases (i.e., almost 92% accuracy).
Conclusion
This classification algorithm performed well for the know‐diagnosis but also predicted medication‐class of response in difficult‐to‐diagnose patients. Further research can enhance this approach and extend these findings to be more clinically accessible.
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