Altered hippocampal function in major depression despite intact structure and resting perfusion

Background: Hippocampal volume reductions in major depression have been frequently reported. However, evidence for functional abnormalities in the same region in depression has been less clear. We investigated hippocampal function in depression using functional magnetic resonance imaging (fMRI) and neuropsychological tasks tapping spatial memory function, with complementing measures of hippocampal volume and resting blood flow to aid interpretation. Method: A total of 20 patients with major depressive disorder (MDD) and a matched group of 20 healthy individuals participated. Participants underwent multimodal magnetic resonance imaging (MRI): fMRI during a spatial memory task, and structural MRI and resting blood flow measurements of the hippocampal region using arterial spin labelling. An offline battery of neuropsychological tests, including several measures of spatial memory, was also completed. Results: The fMRI analysis showed significant group differences in bilateral anterior regions of the hippocampus. While control participants showed task-dependent differences in blood oxygen level-dependent (BOLD) signal, depressed patients did not. No group differences were detected with regard to hippocampal volume or resting blood flow. Patients showed reduced performance in several offline neuropsychological measures. All group differences were independent of differences in hippocampal volume and hippocampal blood flow. Conclusions: Functional abnormalities of the hippocampus can be observed in patients with MDD even when the volume and resting perfusion in the same region appear normal. This suggests that changes in hippocampal function can be observed independently of structural abnormalities of the hippocampus in depression

Static and Dynamic Characteristics of Cerebral Blood Flow During the Resting State in Schizophrenia

Background: The cerebral network that is active during rest and is deactivated during goal-oriented activity is called the default mode network (DMN). It appears to be involved in self-referential mental activity. Atypical functional connectivity in the DMN has been observed in schizophrenia. One hypothesis suggests that pathologically increased DMN connectivity in schizophrenia is linked with a main symptom of psychosis, namely, misattribution of thoughts. Methods: A resting-state pseudocontinuous arterial spin labeling (ASL) study was conducted to measure absolute cerebral blood flow (CBF) in 34 schizophrenia patients and 27 healthy controls. Using independent component analysis (ICA), the DMN was extracted from ASL data. Mean CBF and DMN connectivity were compared between groups using a 2-sample t test. Results: Schizophrenia patients showed decreased mean CBF in the frontal and temporal regions (P < .001). ICA demonstrated significantly increased DMN connectivity in the precuneus (x/y/z = −16/−64/38) in patients than in controls (P < .001). CBF was not elevated in the respective regions. DMN connectivity in the precuneus was significantly correlated with the Positive and Negative Syndrome Scale scores (P < .01). Conclusions: In schizophrenia patients, the posterior hub—which is considered the strongest part of the DMN—showed increased DMN connectivity. We hypothesize that this increase hinders the deactivation of the DMN and, thus, the translation of cognitive processes from an internal to an external focus. This might explain symptoms related to defective self-monitoring, such as auditory verbal hallucinations or ego disturbance

Neuroplasticity hypothesis of the mechanism of electroconvulsive therapy: a proton magnetic resonance and functional connectivity investigation

INTRODUCTION: Major depressive disorder (MDD) is characterized by ongoing feelings of guilt, sadness, and memory and cognition impairment. It is a multidimensional illness that affects many functionally integrated pathways of the brain. Understanding the underlying brain dysfunction that gives rise to this complex illness has been challenging, and by extension the search for appropriate treatments. MDD patients who are considered treatment resistant make up the primary population that receives electroconvulsive therapy (ECT). Remarkably, ECT shows a 75% remission rate in this patient population and is considered the “gold standard” treatment for major depression. Although the exact mechanism of its function is unknown, it is well accepted that the induced grand-mal seizure confers its therapeutic effect. The seizure likely has broad effect that somehow corrects the underlying dysfunction in brain circuitry. Here, we specifically examined studies of functional connectivity and metabolite changes. METHODS: Through literature search, we examined six studies in functional connectivity and four studies in magnetic resonance spectroscopy (MRS). RESULTS: Functional Connectivity: Studies have found that after bilateral ECT treatments, patients with major depression showed reduction of functional connectivity (FC) from the left dorsolateral prefrontal cortex (DLPFC) to other cortical and limbic structures. Correlated activity between the superior frontal gyri, middle frontal gyri and angular gyri were significantly increased after ECT. Hyperdeactivation of the orbitofrontal cortex to negative emotional stimuli in patients was decreased, and it was associated with improvement in depressive symptoms. Regional activity in the subgenual anterior cingulate cortex (sgACC) and functional connectivity between the sgACC and left hippocampus in treatment naïve patients after ECT were increased and correlated to reduction of depressive symptoms. Reduced connectivity between the amygdale and sgACC and increased connectivity between the amygdale and DLPFC was found by sequential assessments over a course of ECT treatments. Lastly, ECT increased the functional connectivity between DLPFC and the default mode network. MRS: Studies found decreased levels of glutamate or glx (glutamate/glutamine/ GABA) in patients in the anterior cingulate cortex and dorsolateral prefrontal cortex (DLPFC) compared to healthy controls. Additionally, it was found that glx levels increased after ECT treatments and that this increase was only in those who responded to treatment. Lastly, GABA level increased after ECT treatment in the occipital cortex. Discussion: Results from functional connectivity and brain metabolite studies in patients with major depression point to induced neuroplasticity as part of ECT’s therapeutic mechanism. Remodeling connectivity and mediating metabolite changes both will require modifications at the synaptic level. The wide spread changes seen in several different brain regions that have been implicated in depression further suggests that ECT’s effects are both highly specific and broad. CONCLUSION: Electroconvulsive therapy has consistently demonstrated impressive efficacy among the most severely depressed patients and is known to produce widely distributed effects in the brain. However, this also makes assessing its therapeutic mechanism challenging. Magnetic resonance imaging studies assessing functional connectivity and brain metabolite levels have demonstrated that ECT likely produces neuroplastic changes to remodel aberrant connectivity and dysfunctional excitatory and inhibitory neurotransmission in cortical and limbic areas. Although these findings should be interpreted with caution, this field of research has provided an unprecedented opportunity to examine the living brain in great detail. Further studies with larger sample sizes and improved technical specifications will likely yield greater results

Brain perfusion patterns are altered in chronic knee pain:a spatial covariance analysis of arterial spin labelling MRI

Chronic musculoskeletal pain is a common problem globally. Current evidence suggests that maladapted central pain pathways are associated with pain chronicity, for example, in postoperative pain after knee replacement. Other factors such as low mood, anxiety, and tendency to catastrophize are also important contributors. We aimed to investigate brain imaging features that underpin pain chronicity based on multivariate pattern analysis of cerebral blood flow (CBF), as a marker of maladaptive brain changes. This was achieved by identifying CBF patterns that discriminate chronic pain from pain-free conditions and by exploring their explanatory power for factors thought to drive pain chronification. In 44 chronic knee pain and 29 pain-free participants, we acquired both CBF and T1-weighted data. Participants completed questionnaires related to affective processes and pressure and cuff algometry to assess pain sensitization. Two factor scores were extracted from these scores representing negative affect and pain sensitization. A spatial covariance principal component analysis of CBF identified 5 components that significantly discriminated chronic pain participants from controls, with the unified network achieving 0.83 discriminatory accuracy (area under the curve). In chronic knee pain, significant patterns of relative hypoperfusion were evident in anterior default-mode and salience network hubs, while hyperperfusion was seen in posterior default mode, thalamus, and sensory regions. One component correlated positively with the pain sensitization score (r = 0.43, P = 0.006), suggesting that this CBF pattern reflects neural activity changes encoding pain sensitization. Here, we report a distinct chronic knee pain-related representation of CBF, pointing toward a brain signature underpinning central aspects of pain sensitization

Application of resting-state fMRI methods to acute ischemic stroke

Diffusion weighted imaging (DWI) and dynamic susceptibility contrast-enhanced (DSC) perfusion-weighted imaging (PWI) are commonly employed in clinical practice and in research to give pathophysiological information for patients with acute ischemic stroke. DWI is thought to roughly reflect the severely damaged infarct core, while DSC-PWI reflects the area of hypoperfusion. The volumetric difference between DWI and DSC-PWI is termed the PWI/DWI-mismatch, and has been suggested as an MRI surrogate of the ischemic penumbra. However, due to the application of a contrast agent, which has potentially severe side-effects (e.g., nephrogenic systemic fibrosis), the DSC-PWI precludes repetitive examinations for monitoring purposes. New approaches are being sought to overcome this shortcoming. BOLD (blood oxygen-level dependent) signal can reflect the metabolism of blood oxygen in the brain and hemodynamics can be assessed with resting-state fMRI. The aim of this thesis was to use resting-state fMRI as a new approach to give similar information as DSC-PWI. This thesis comprises two studies: In the first study (see Chapter 2), two resting-state fMRI methods, local methods which compare low frequency amplitudes between two hemispheres and a k-means clustering approach, were applied to investigate the functional damage of patients with acute ischemic stroke both in the time domain and frequency domain. We found that the lesion areas had lower amplitudes than contralateral homotopic healthy tissues. We also differentiated the lesion areas from healthy tissues using a k-means clustering approach. In the second study (see Chapter 3), time-shift analysis (TSA), which assesses time delays of the spontaneous low frequency fluctuations of the resting-state BOLD signal, was applied to give similar pathophysiological information as DSC-PWI in the acute phase of stroke. We found that areas which showed a pronounced time delay to the respective mean time course were very similar to the hypoperfusion area. In summary, we suggest that the resting-state fMRI methods, especially the time-shift analysis (TSA), may provide comparable information to DSC-PWI and thus serve as a useful diagnostic tool for stroke MRI without the need for the application of a contrast agent

Dimensions of Depression and Cerebellar Subregion Volumes in Older Adults

The present study examined the relationship between subthreshold depressive symptoms and gray matter volume in subregions of the posterior cerebellum in middle-aged to older adults. Structural magnetic resonance imaging data from 38 adults aged 51 to 80 years were analyzed along with participants’ responses to the Center for Epidemiologic Studies Depression Scale. Subscale scores for depressed mood, somatic symptoms, and lack of positive affect were calculated, and multiple regression analyses were used to examine the relationship between symptom dimensions and cerebellar volumes. Greater somatic symptoms of depression were significantly related to larger vermis VI volumes, as were total depressive scores. Exploratory analyses revealed that greater severity on the lack of positive affect subscale was related to larger vermis VIII volumes. These results support that depressive symptom profiles have unique relationships within the cerebellum that may be important as the field moves towards targeted treatment approaches for depression

Arterial Spin Labeling Perfusion of the Brain: Emerging Clinical Applications

Arterial spin labeling (ASL) is a magnetic resonance (MR) imaging technique used to assess cerebral blood flow noninvasively by magnetically labeling inflowing blood. In this article, the main labeling techniques, notably pulsed and pseudocontinuous ASL, as well as emerging clinical applications will be reviewed. In dementia, the pattern of hypoperfusion on ASL images closely matches the established patterns of hypometabolism on fluorine 18 fluorodeoxyglucose (FDG) positron emission tomography (PET) images due to the close coupling of perfusion and metabolism in the brain. This suggests that ASL might be considered as an alternative for FDG, reserving PET to be used for the molecular disease-specific amyloid and tau tracers. In stroke, ASL can be used to assess perfusion alterations both in the acute and the chronic phase. In arteriovenous malformations and dural arteriovenous fistulas, ASL is very sensitive to detect even small degrees of shunting. In epilepsy, ASL can be used to assess the epileptogenic focus, both in peri- and interictal period. In neoplasms, ASL is of particular interest in cases in which gadolinium-based perfusion is contraindicated (eg, allergy, renal impairment) and holds promise in differentiating tumor progression from benign causes of enhancement. Finally, various neurologic and psychiatric diseases including mild traumatic brain injury or posttraumatic stress disorder display alterations on ASL images in the absence of visualized structural changes. In the final part, current limitations and future developments of ASL techniques to improve clinical applicability, such as multiple inversion time ASL sequences to assess alterations of transit time, reproducibility and quantification of cerebral blood flow, and to measure cerebrovascular reserve, will be reviewed

SEARCHING NEUROIMAGING BIOMARKERS IN MENTAL DISORDERS WITH GRAPH AND MULTIMODAL FUSION ANALYSIS OF FUNCTIONAL CONNECTIVITY

Mental disorders such as schizophrenia (SZ), bipolar (BD), and major depression disorders (MDD) can cause severe symptoms and life disruption. They share some symptoms, which can pose a major clinical challenge to their differentiation. Objective biomarkers based on neuroimaging may help to improve diagnostic accuracy and facilitate optimal treatment for patients. Over the last decades, non-invasive in-vivo neuroimaging techniques such as magnetic resonance imaging (MRI) have been increasingly applied to measure structure and function in human brains. With functional MRI (fMRI) or structural MRI (sMRI), studies have identified neurophysiological deficits in patients’ brain from different perspective. Functional connectivity (FC) analysis is an approach that measures functional integration in brains. By assessing the temporal coherence of the hemodynamic activity among brain regions, FC is considered capable of characterizing the large-scale integrity of neural activity. In this work, we present two data analysis frameworks for biomarker detection on brain imaging with FC, 1) graph analysis of FC and 2) multimodal fusion analysis, to better understand the human brain. Graph analysis reveals the interaction among brain regions based on graph theory, while the multimodal fusion framework enables us to utilize the strength of different imaging modalities through joint analysis. Four applications related to FC using these frameworks were developed. First, FC was estimated using a model-based approach, and revealed altered the small-world network structure in SZ. Secondly, we applied graph analysis on functional network connectivity (FNC) to differentiate BD and MDD during resting-state. Thirdly, two functional measures, FNC and fractional amplitude of low frequency fluctuations (fALFF), were spatially overlaid to compare the FC and spatial alterations in SZ. And finally, we utilized a multimodal fusion analysis framework, multi-set canonical correlation analysis + joint independent component analysis (mCCA+jICA) to link functional and structural abnormalities in BD and MDD. We also evaluated the accuracy of predictive diagnosis through classifiers generated on the selected features. In summary, via the two frameworks, our work has made several contributions to advance FC analysis, which improves our understanding of underlying brain function and structure, and our findings may be ultimately useful for the development of biomarkers of mental disease

Resting-state abnormalities in heroin-dependent individuals

Drug addiction is a major health problem worldwide. Recent neuroimaging studies have shed light into the underlying mechanisms of drug addiction as well as its consequences to the human brain. The most vulnerable, to heroin addiction, brain regions have been reported to be specific prefrontal, parietal, occipital, and temporal regions, as well as, some subcortical regions. The brain regions involved are usually linked with reward, motivation/drive, memory/learning, inhibition as well as emotional control and seem to form circuits that interact with each other. So, along with neuroimaging studies, recent advances in resting-state dynamics might allow further assessments upon the multilayer complexity of addiction. In the current manuscript, we comprehensively review and discuss existing resting-state neuroimaging findings classified into three overlapping and interconnected groups: functional connectivity alterations, structural deficits and abnormal topological properties. Moreover, behavioral traits of heroin-addicted individuals as well as the limitations of the currently available studies are also reviewed. Finally, in need of a contemporary therapy a multimodal therapeutic approach is suggested using classical treatment practices along with current neurotechonologies, such as neurofeedback and goal-oriented video-games

Assessing regional cerebral blood flow in depression using 320-slice computed tomography

While there is evidence that the development and course of major depressive disorder (MDD) symptomatology is associated with vascular disease, and that there are changes in energy utilization in the disorder, the extent to which cerebral blood flow is changed in this condition is not clear. This study utilized a novel imaging technique previously used in coronary and stroke patients, 320-slice Computed-Tomography (CT), to assess regional cerebral blood flow (rCBF) in those with MDD and examine the pattern of regional cerebral perfusion. Thirty nine participants with depressive symptoms (Hamilton Depression Rating Scale 24 (HAMD24) score &gt;20, and Self-Rating Depression Scale (SDS) score &gt;53) and 41 healthy volunteers were studied. For all subjects, 3 ml of venous blood was collected to assess hematological parameters. Trancranial Doppler (TCD) ultrasound was utilized to measure parameters of cerebral artery rCBFV and analyse the Pulsatility Index (PI). 16 subjects (8 =  MDD; 8 =  healthy) also had rCBF measured in different cerebral artery regions using 320-slice CT. Differences among groups were analyzed using ANOVA and Pearson\u27s tests were employed in our statistical analyses. Compared with the control group, whole blood viscosity (including high\middle\low shear rate)and hematocrit (HCT) were significantly increased in the MDD group. PI values in different cerebral artery regions and parameters of rCBFV in the cerebral arteries were decreased in depressive participants, and there was a positive relationship between rCBFV and the corresponding vascular rCBF in both gray and white matter. rCBF of the left gray matter was lower than that of the right in MDD. Major depression is characterized by a wide range of CBF impairments and prominent changes in gray matter blood flow. 320-slice CT appears to be a valid and promising tool for measuring rCBF, and could thus be employed in psychiatric settings for biomarker and treatment response purposes