Clinical, cognitive, and functional connectivity correlations of resting-state intrinsic brain activity alterations in unmedicated depression

Resting-State Seed-Based Analysis: An Alternative to Task-Based Language fMRI and Its Laterality Index

BACKGROUND AND PURPOSE

Language is a cardinal function that makes human unique. Preservation of language function poses a great challenge for surgeons during resection. The aim of the study was to assess the efficacy of resting-state fMRI in the lateralization of language function in healthy subjects to permit its further testing in patients who are unable to perform task-based fMRI.

MATERIALS AND METHODS

Eighteen healthy right-handed volunteers were prospectively evaluated with resting-state fMRI and task-based fMRI to assess language networks. The laterality indices of Broca and Wernicke areas were calculated by using task-based fMRI via a voxel-value approach. We adopted seed-based resting-state fMRI connectivity analysis together with parameters such as amplitude of low-frequency fluctuation and fractional amplitude of low-frequency fluctuation (fALFF). Resting-state fMRI connectivity maps for language networks were obtained from Broca and Wernicke areas in both hemispheres. We performed correlation analysis between the laterality index and the z scores of functional connectivity, amplitude of low-frequency fluctuation, and fALFF.

RESULTS

Pearson correlation analysis between signals obtained from the z score of fALFF and the laterality index yielded a correlation coefficient of 0.849 (P < .05). Regression analysis of the fALFF with the laterality index yielded an R² value of 0.721, indicating that 72.1% of the variance in the laterality index of task-based fMRI could be predicted from the fALFF of resting-state fMRI.

CONCLUSIONS

The present study demonstrates that fALFF can be used as an alternative to task-based fMRI for assessing language laterality. There was a strong positive correlation between the fALFF of the Broca area of resting-state fMRI with the laterality index of task-based fMRI. Furthermore, we demonstrated the efficacy of fALFF for predicting the laterality of task-based fMRI.

Altered fractional amplitude of low frequency fluctuation associated with cognitive dysfunction in first-episode drug-naïve major depressive disorder patients

BACKGROUND

Previous studies have demonstrated that abnormities of both resting-state brain activity and cognitive dysfunction are frequently observed in patients with major depressive disorder (MDD). However, the underlying relationship between these two aspects is less investigated. In this context, the aim of the present study was to investigate the association between cognitive dysfunction and altered resting-state brain function in first-episode drug-naïve MDD patients.

METHODS

Twenty-five drug-naïve MDD patients and twenty-six age-, sex-, and education-matched normal controls were recruited in this study. Cognitive function was evaluated by using a series of validated test procedures. The resting-state functional magnetic resonance imaging data were obtained on a Philips 3.0 Tesla scanner and analysed using the fractional amplitude of low frequency fluctuation (fALFF) method. Correlations of fALFF values with cognitive dysfunction were further analysed.

RESULTS

Compared with healthy controls, MDD patients showed significantly fewer completed categories in the Wisconsin Card Sorting Test (WCST) and decreased scores in the first and second subtests of the Continuous Performance Test (CPT). However, the two groups did not differ in their performance on the Stroop Colour Word Test and Trail-making Test. MDD patients exhibited significantly decreased fALFF values in the left superior frontal gyrus (SFG), left middle frontal gyrus, and left inferior frontal gyrus, as well as increased fALFF values in the left inferior temporal gyrus (ITG), bilateral parahippocampal gyrus, and the right caudate. Finally, the correlation analyses revealed that fALFF values in the left SFG and left ITG were associated with the number of WSCT completed categories and scores on the second subtest of the CPT in MDD, respectively.

CONCLUSIONS

The present findings suggest that there is little evidence of an association between regional abnormalities in resting-state brain function and cognitive deficits in MDD.

Propofol attenuates low-frequency fluctuations of resting-state fMRI BOLD signal in the anterior frontal cortex upon loss of consciousness

Recent studies indicate that spontaneous low-frequency fluctuations (LFFs) of resting-state functional magnetic resonance imaging (rs-fMRI) blood oxygen level-dependent (BOLD) signals are driven by the slow (<0.1Hz) modulation of ongoing neuronal activity synchronized locally and across remote brain regions. How regional LFFs of the BOLD fMRI signal are altered during anesthetic-induced alteration of consciousness is not well understood. Using rs-fMRI in 15 healthy participants, we show that during administration of propofol to achieve loss of behavioral responsiveness indexing unconsciousness, the fractional amplitude of LFF (fALFF index) was reduced in comparison to wakeful baseline in the anterior frontal regions, temporal pole, hippocampus, parahippocampal gyrus, and amygdala. Such changes were absent in large areas of the motor, parietal, and sensory cortices. During light sedation characterized by the preservation of overt responsiveness and therefore consciousness, fALFF was reduced in the subcortical areas, temporal pole, medial orbital frontal cortex, cingulate cortex, and cerebellum. Between light sedation and deep sedation, fALFF was reduced primarily in the medial and dorsolateral frontal areas. The preferential reduction of LFFs in the anterior frontal regions is consistent with frontal to sensory-motor cortical disconnection and may contribute to the suppression of consciousness during general anesthesia.

Isolating biomarkers for symptomatic states: considering symptom-substrate chronometry

A long-standing goal of psychopathology research is to develop objective markers of symptomatic states, yet progress has been far slower than expected. Although prior reviews have attributed this state of affairs to diagnostic heterogeneity, symptom comorbidity and phenotypic complexity, little attention has been paid to the implications of intra-individual symptom dynamics and inter-relatedness for biomarker study designs. In this critical review, we consider the impact of short-term symptom fluctuations on widely used study designs that regress the 'average level' of a given symptom against biological data collected at a single time point, and summarize findings from ambulatory assessment studies suggesting that such designs may be sub-optimal to detect symptom-substrate relationships. Although such designs have a crucial role in advancing our understanding of biological substrates related to more stable, longer-term changes (for example, gray matter thinning during a depressive episode), they may be less optimal for the detection of symptoms that exhibit high frequency fluctuations, are susceptible to common reporting biases, or may be heavily influenced by the presence of other symptoms. We propose that a greater emphasis on intra-individual symptom chronometry may be useful for identifying subgroups of patients with common, proximal pathological indicators. Taken together, these three recent developments in the areas of symptom conceptualization and measurement raise important considerations for future studies attempting to identify reliable biomarkers in psychiatry.

Altered neuronal spontaneous activity correlates with glutamate concentration in medial prefrontal cortex of major depressed females: An fMRI-MRS study

BACKGROUND

Major depressive disorder (MDD) is twice more prevalent in females than in males. Yet, there have only been a few studies on the functional brain activity in female MDD patients and the detailed mechanisms underlying their neurobiology merit further investigations. In the present work, we used combined fMRI-MRS methods to investigate the altered intrinsic neuronal activity and its association with neurotransmitter concentration in female MDD patients.

METHODS

The whole brain amplitude of low frequency fluctuation (ALFF) analysis using resting state functional magnetic resonance imaging (fMRI) was performed to explore the alteration of intrinsic neuronal signals in MDD females (n=11) compared with female healthy controls (n=11). With a specific interest in the medial prefrontal cortex (mPFC) area, we quantified the concentration of amino acid neurotransmitters including GABA ((r-aminobutyric acid)), Glu (Glutamate), and Glx (Glutamate + Glutamine) using (1)H-MRS technology. Moreover, we conducted Pearson correlation analysis between the ALFF value and neurotransmitter concentration to find out the functional-biochemical relation in mPFC area. The relationship between the metabolites concentration and MDD symptomatology was also examined through Spearman correlation analysis.

RESULTS

We found that the female MDD patients showed increased neuronal spontaneous activity in left medial prefrontal cortex (mPFC) and left middle frontal cortex, with decreased ALFF level in right putamen and right middle temporal cortex (p<0.01, Alphasim corrected). The ALFF in mPFC was shown positively correlated with Glu concentration in female MDD patients (r=0.67, p=0.023). The Glu concentration in mPFC was positively correlated with patients HAMA scores (r=0.641, p=0.033).

LIMITATIONS

The relatively small sample size, metabolite information acquired only in mPFC and not all patients were unmedicated are the major limitations of our study.

CONCLUSIONS

Using combined fMRI-MRS methods, we found increased spontaneous neuronal activity was correlated with Glu concentration in mPFC of female MDD patients. Other regions including left middle frontal gyrus, right putamen and middle temporal gyrus also showed altered spontaneous neuronal activities. The abnormal intrinsic neuronal activities in fronto-cortical regions shed light on the pathogenesis underlying MDD females. The multimodal resting-state neuroimaging technique served as a useful tool for functional-biochemical investigation of MDD pathophysiology.

Pharmacological modulation of pulvinar resting-state regional oscillations and network dynamics in major depression

The pulvinar, the largest thalamus nucleus, has rich anatomical connections with several different cortical and subcortical regions suggesting its important involvement in high-level cognitive and emotional functions. Unfortunately, pulvinar dysfunction in psychiatric disorders particularly major depression disorder has not been thoroughly examined to date. In this study we explored the alterations in the baseline regional and network activities of the pulvinar in MDD by applying spectral analysis of resting-state oscillatory activity, functional connectivity and directed (effective) connectivity on resting-state fMRI data acquired from 20 healthy controls and 19 participants with MDD. Furthermore, we tested how pharmacological treatment with duloxetine can modulate the measured local and network variables in ten participants who completed treatment. Our results revealed a frequency-band dependent modulation of power spectrum characteristics of pulvinar regional oscillatory activity. At the network level, we found MDD is associated with aberrant causal interactions between pulvinar and several systems including default-mode and posterior insular networks. It was also shown that duloxetine treatment can correct or overcompensate the pathologic network behavior of the pulvinar. In conclusion, we suggest that pulvinar regional baseline oscillatory activity and its resting-state network dynamics are compromised in MDD and can be modulated therapeutically by pharmacological treatment.

Biophysical changes in subcortical nuclei: the impact of diabetes and major depression

Magnetization transfer (MT) is a neuroimaging technique that is frequently used to characterize the biophysical abnormalities in both gray and white matter regions of the brain. In our study, we used MT to examine the integrity of key nodes in frontal-subcortical circuits in four subject groups: patients diagnosed with type 2 diabetes with and without major depression (MDD), a healthy control group, and a group diagnosed with MDD without diabetes. In the MDD group, MT studies demonstrated lower magnetization transfer ratios (MTR), a marker of abnormalities in the macromolecular protein pool, in the thalami when compared with the control groups. The group with diabetes and MDD showed lower MTR in the globus pallidus when compared with the group with MDD. Biophysical measures, in subcortical nuclei, correlated inversely with measures of glycemic control, cerebrovascular burden and depression scores. These findings have broad implications for the underlying neuronal circuitry and neurobiology of mood disorders.

Association of thalamic hyperactivity with treatment-resistant depression and poor response in early treatment for major depression: a resting-state fMRI study using fractional amplitude of low-frequency fluctuations

Despite novel antidepressant development, 10-30% of patients with major depressive disorder (MDD) have antidepressant treatment-resistant depression (TRD). Although new therapies are needed, lack of knowledge regarding the neural mechanisms underlying TRD hinders development of new therapeutic options. We aimed to identify brain regions in which spontaneous neural activity is not only altered in TRD but also associated with early treatment resistance in MDD. Sixteen patients with TRD, 16 patients with early-phase non-TRD and 26 healthy control (HC) subjects underwent resting-state functional magnetic resonance imaging. To identify brain region differences in spontaneous neural activity between patients with and without TRD, we assessed fractional amplitude of low-frequency fluctuations (fALFF). We also calculated correlations between the percent change in the Hamilton Rating Scale for Depression (HRSD17) scores and fALFF values in brain regions with differing activity for patients with and without TRD. Patients with TRD had increased right-thalamic fALFF values compared with patients without TRD. The percent change in HRSD17 scores negatively correlated with fALFF values in patients with non-TRD. In addition, patients with TRD showed increased fALFF values in the right inferior frontal gyrus (IFG), inferior parietal lobule (IPL) and vermis, compared with patients with non-TRD and HC subjects. Our results show that spontaneous activity in the right thalamus correlates with antidepressant treatment response. We also demonstrate that spontaneous activity in the right IFG, IPL and vermis may be specifically implicated in the neural pathophysiology of TRD.

Functional connectivity between prefrontal cortex and striatum estimated by phase locking value

The interplay between the prefrontal cortex (PFC) and striatum has an important role in cognitive processes. To investigate interactive functions between the two areas in reward processing, we recorded local field potentials (LFPs) simultaneously from the two areas of two monkeys performing a reward prediction task (large reward vs small reward). The power of the LFPs was calculated in three frequency bands: the beta band (15-29 Hz), the low gamma band (30-49 Hz), and the high gamma band (50-100 Hz). We found that both the PFC and striatum encoded the reward information in the beta band. The reward information was also found in the high gamma band in the PFC, not in the striatum. We further calculated the phase-locking value (PLV) between two LFP signals to measure the phase synchrony between the PFC and striatum. It was found that significant differences occurred between PLVs in different task periods and in different frequency bands. The PLVs in small reward condition were significant higher than that in large reward condition in the beta band. In contrast, the PLVs in the high gamma band were stronger in large reward trials than in small trials. These results suggested that the functional connectivity between the PFC and striatum depended on the task periods and reward conditions. The beta synchrony between the PFC and striatum may regulate behavioral outputs of the monkeys in the small reward condition.

Altered resting-state functional connectivity in late-life depression: A cross-sectional study

BACKGROUND

Disrupted brain connectivity is implicated in the pathophysiology of late-life depression (LLD). There are few studies in this area using resting-state functional magnetic resonance imaging (rs-fMRI). In this pilot case-control study, we compare rs-fMRI data between age-matched depressed and non-depressed older adults.

METHODS

Older participants (≥55 years) with current major depressive disorder (MDD) were recruited to participate in an ongoing study of LLD, and were compared to the age-matched, non-depressed controls. Rs-fMRI data were collected using a 3-Tesla MRI system. In this study, a data-driven approach was chosen and an independent component analysis (ICA) was performed.

RESULTS

Seventeen subjects with MDD were compared to 31 controls. The depressed group showed increased connectivity in three main networks compared to the controls (p(corr)<0.05), including connectivity between the default mode network (DMN) and the posterior superior temporal sulcus (pSTS). Increased connectivity was also observed within the visual network in the medial, lateral and ventral regions of the occipital lobes, and within the auditory network throughout the right superior temporal cortex.

CONCLUSION

This data-driven, pilot study finds patterns of increased connectivity that may be unique to LLD in the DMN, as well as visual and auditory networks. The functional implications of this aberrant connectivity remains to be determined. These findings should be further explored in larger samples.

Neural complexity in patients with poststroke depression: A resting EEG study

BACKGROUND

Poststroke depression (PSD) is one of the most common emotional disorders affecting post-stroke patients. However, the neurophysiological mechanism remains elusive. This study was aimed to study the relationship between complexity of neural electrical activity and PSD.

METHODS

Resting state eye-closed electroencephalogram (EEG) signals of 16 electrodes were recorded in 21 ischemic poststroke depression (PSD) patients, 22 ischemic poststroke non-depression (PSND) patients and 15 healthy controls (CONT). Lempel-Ziv Complexity (LZC) was used to evaluate changes in EEG complexity in PSD patients. Statistical analysis was performed to explore difference among different groups and electrodes. Correlation between the severity of depression (HDRS) and EEG complexity was determined with pearson correlation coefficients. Receiver operating characteristic (ROC) and binary logistic regression analysis were conducted to estimate the discriminating ability of LZC for PSD in specificity, sensitivity and accuracy.

RESULTS

PSD patients showed lower neural complexity compared with PSND and CONT subjects in the whole brain regions. There was no significant difference among different brain regions, and no interactions between group and electrodes. None of the LZC significantly correlated with overall depression severity or differentiated symptom severity of 7 items in PSD patients, but in stroke patients, significant correlation was found between HDRS and LZC in the whole brain regions, especially in frontal and temporal. LZC parameters used for PSD recognition possessed more than 85% in specificity, sensitivity and accuracy, suggesting the feasibility of LZC to serve as screening indicators for PSD. Increased slow wave rhythms were found in PSD patients and clearly correlation was confirmed between neuronal complexity and spectral power of the four EEG rhythms.

LIMITATIONS

Lesion location of stroke patients in the study distributed in different brain regions, and most of the PSD patients were mild or moderate in depressive severity.

CONCLUSIONS

Compared with conventional spectral analysis, complexity of neural activity using LZC was more sensitive and stationary in the measurement of abnormal brain activity in PSD patients and may offer a potential approach to facilitate clinical screening of this disease.

Development of a selective left-hemispheric fronto-temporal network for processing syntactic complexity in language comprehension

The development of language comprehension abilities in childhood is closely related to the maturation of the brain, especially the ability to process syntactically complex sentences. Recent studies proposed that the fronto-temporal connection within left perisylvian regions, supporting the processing of syntactically complex sentences, is still immature at preschool age. In the current study, resting state functional magnetic resonance imaging data were acquired from typically developing 5-year-old children and adults to shed further light on the brain functional development. Children additionally performed a behavioral syntactic comprehension test outside the scanner. The amplitude of low-frequency fluctuations was analyzed in order to identify the functional correlation networks of language-relevant brain regions. Results showed an intrahemispheric correlation between left inferior frontal gyrus (IFG) and left posterior superior temporal sulcus (pSTS) in adults, whereas an interhemispheric correlation between left IFG and its right-hemispheric homolog was predominant in children. Correlation analysis between resting-state functional connectivity and sentence processing performance in 5-year-olds revealed that local connectivity within the left IFG is associated with competence of processing syntactically simple canonical sentences, while long-range connectivity between IFG and pSTS in left hemisphere is associated with competence of processing syntactically relatively more complex non-canonical sentences. The present developmental data suggest that a selective left fronto-temporal connectivity network for processing complex syntax is already in functional connection at the age of 5 years when measured in a non-task situation. The correlational findings provide new insight into the relationship between intrinsic functional connectivity and syntactic language abilities in preschool children.

•

resting state ALFF correlated in adults between left IFG and left pSTS.

•

resting state ALFF correlated in children between left IFG and right homolog area.

•

intrahemispheric connectivity co-varies with syntactic processing skills in children.