59 research outputs found
Recommended from our members
Amygdala Perfusion Is Predicted by Its Functional Connectivity with the Ventromedial Prefrontal Cortex and Negative Affect
Background: Previous studies have shown that the activity of the amygdala is elevated in people experiencing clinical and subclinical levels of anxiety and depression (negative affect). It has been proposed that a reduction in inhibitory input to the amygdala from the prefrontal cortex and resultant over-activity of the amygdala underlies this association. Prior studies have found relationships between negative affect and 1) amygdala over-activity and 2) reduced amygdala-prefrontal connectivity. However, it is not known whether elevated amygdala activity is associated with decreased amygdala-prefrontal connectivity during negative affect states. Methods: Here we used resting-state arterial spin labeling (ASL) and blood oxygenation level dependent (BOLD) functional magnetic resonance imaging (fMRI) in combination to test this model, measuring the activity (regional cerebral blood flow, rCBF) and functional connectivity (correlated fluctuations in the BOLD signal) of one subregion of the amygdala with strong connections with the prefrontal cortex, the basolateral nucleus (BLA), and subsyndromal anxiety levels in 38 healthy subjects. Results: BLA rCBF was strongly correlated with anxiety levels. Moreover, both BLA rCBF and anxiety were inversely correlated with the strength of the functional coupling of the BLA with the caudal ventromedial prefrontal cortex. Lastly, BLA perfusion was found to be a mediator of the relationship between BLA-prefrontal connectivity and anxiety. Conclusions: These results show that both perfusion of the BLA and a measure of its functional coupling with the prefrontal cortex directly index anxiety levels in healthy subjects, and that low BLA-prefrontal connectivity may lead to increased BLA activity and resulting anxiety. Thus, these data provide key evidence for an often-cited circuitry model of negative affect, using a novel, multi-modal imaging approach
Impairment in acquisition of conditioned fear in schizophrenia
Individuals with schizophrenia show impairments in associative learning. One well-studied, quantifiable form of associative learning is Pavlovian fear conditioning. However, to date, studies of fear conditioning in schizophrenia have been inconclusive, possibly because they lacked sufficient power. To address this issue, we pooled data from four independent fear conditioning studies that included a total of 77 individuals with schizophrenia and 74 control subjects. Skin conductance responses (SCRs) to stimuli that were paired (the CSâ+â) or not paired (CSâ) with an aversive, unconditioned stimulus were measured, and the success of acquisition of differential conditioning (the magnitude of CSâ+âvs. CSâ SCRs) and responses to CSâ+âand CSâ separately were assessed. We found that acquisition of differential conditioned fear responses was significantly lower in individuals with schizophrenia than in healthy controls (Cohenâs dâ=â0.53). This effect was primarily related to a significantly higher response to the CSâ stimulus in the schizophrenia compared to the control group. Moreover, the magnitude of this response to the CSâ in the schizophrenia group was correlated with the severity of delusional ideation (pâ=â0.006). Other symptoms or antipsychotic dose were not associated with fear conditioning measures. In conclusion, individuals with schizophrenia who endorse delusional beliefs may be over-responsive to neutral stimuli during fear conditioning. This finding is consistent with prior models of abnormal associative learning in psychosis
Recommended from our members
A parametric study of fear generalization to faces and non-face objects: relationship to discrimination thresholds
Fear generalization is the production of fear responses to a stimulus that is similarâbut not identicalâto a threatening stimulus. Although prior studies have found that fear generalization magnitudes are qualitatively related to the degree of perceptual similarity to the threatening stimulus, the precise relationship between these two functions has not been measured systematically. Also, it remains unknown whether fear generalization mechanisms differ for social and non-social information. To examine these questions, we measured perceptual discrimination and fear generalization in the same subjects, using images of human faces and non-face control stimuli (âblobsâ) that were perceptually matched to the faces. First, each subjectâs ability to discriminate between pairs of faces or blobs was measured. Each subject then underwent a Pavlovian fear conditioning procedure, in which each of the paired conditioned stimuli (CS) were either followed (CS+) or not followed (CSâ) by a shock. Skin conductance responses (SCRs) were also measured. Subjects were then presented with the CS+, CSâ and five levels of a CS+-to-CSâ morph continuum between the paired stimuli, which were identified based on individual discrimination thresholds. Finally, subjects rated the likelihood that each stimulus had been followed by a shock. Subjects showed both autonomic (SCR-based) and conscious (ratings-based) fear responses to morphs that they could not discriminate from the CS+ (generalization). For both faces and non-face objects, fear generalization was not found above discrimination thresholds. However, subjects exhibited greater fear generalization in the shock likelihood ratings compared to the SCRs, particularly for faces. These findings reveal that autonomic threat detection mechanisms in humans are highly sensitive to small perceptual differences between stimuli. Also, the conscious evaluation of threat shows broader generalization than autonomic responses, biased towards labeling a stimulus as threatening
A Data-Driven Investigation of Gray MatterâFunction Correlations in Schizophrenia during a Working Memory Task
The brain is a vastly interconnected organ and methods are needed to investigate its long range structure(S)âfunction(F) associations to better understand disorders such as schizophrenia that are hypothesized to be due to distributed disconnected brain regions. In previous work we introduced a methodology to reduce the whole brain SâF correlations to a histogram and here we reduce the correlations to brain clusters. The application of our approach to sMRI [gray matter (GM) concentration maps] and functional magnetic resonance imaging data (general linear model activation maps during Encode and Probe epochs of a working memory task) from patients with schizophrenia (SZ, nâ=â100) and healthy controls (HC, nâ=â100) presented the following results. In HC the whole brain correlation histograms for GMâEncode and GMâProbe overlap for Low and Medium loads and at High the histograms separate, but in SZ the histograms do not overlap for any of the load levels and Medium load shows the maximum difference. We computed GMâF differential correlation clusters using activation for Probe Medium, and they included regions in the left and right superior temporal gyri, anterior cingulate, cuneus, middle temporal gyrus, and the cerebellum. Inter-cluster GMâProbe correlations for Medium load were positive in HC but negative in SZ. Within group inter-cluster GMâEncode and GMâProbe correlation comparisons show no differences in HC but in SZ differences are evident in the same clusters where HC vs. SZ differences occurred for Probe Medium, indicating that the SâF integrity during Probe is aberrant in SZ. Through a data-driven whole brain analysis approach we find novel brain clusters and show how the SâF differential correlation changes during Probe and Encode at three memory load levels. Structural and functional anomalies have been extensively reported in schizophrenia and here we provide evidences to suggest that evaluating SâF associations can provide important additional information
Survival, neurocognitive function, and health-related quality of life outcomes after rituximab-methotrexate, BCNU, teniposide, and prednisolone for primary CNS lymphoma:Final results of the HOVON 105/ALLG NHL 24 study
Background. Studies on the efficacy of rituximab in primary CNS lymphoma (PCNSL) reported conflicting results. Our international randomized phase 3 study showed that the addition of rituximab to high-dose methotrexate, BCNU, teniposide, and prednisolone (MBVP) in PCNSL was not efficacious in the short term. Here we present long-term results after a median follow-up of 82.3 months. Methods. One hundred and ninety-nine eligible newly diagnosed, nonimmunocompromised patients with PCNSL aged 18â70 years with WHO performance status 0â3 was randomized between treatment with MBVP chemotherapy with or without rituximab, followed by high-dose cytarabine consolidation in responding patients, and reduced-dose WBRT in patients aged †60 years. Event-free survival was the primary endpoint. Overall survival rate, neurocognitive functioning (NCF), and health-related quality of life (HRQoL) were additionally assessed, with the IPCG test battery, EORTC QLQ-C30 and QLQ-BN20 questionnaires, respectively. Results. For event-free survival, the hazard ratio was 0.85, 95% CI 0.61â1.18, P = .33. Overall survival rate at 5 years for MBVP and R-MBVP was 49% (39â59) and 53% (43â63) respectively. In total, 64 patients died in the MBVP arm and 55 in the R-MBVP arm, of which 69% were due to PCNSL. At the group level, all domains of NCF and HRQoL improved to a clinically relevant extent after treatment initiation, and remained stable thereafter up to 60 months of follow-up, except for motor speed which deteriorated between 24 and 60 months. Although fatigue improved initially, high levels persisted in the long term. Conclusions. Long-term follow-up confirms the lack of added value of rituximab in addition to MBVP and HD-cytarabine for PCNSL.</p
Survival, neurocognitive function, and health-related quality of life outcomes after rituximab-methotrexate, BCNU, teniposide, and prednisolone for primary CNS lymphoma:Final results of the HOVON 105/ALLG NHL 24 study
Background. Studies on the efficacy of rituximab in primary CNS lymphoma (PCNSL) reported conflicting results. Our international randomized phase 3 study showed that the addition of rituximab to high-dose methotrexate, BCNU, teniposide, and prednisolone (MBVP) in PCNSL was not efficacious in the short term. Here we present long-term results after a median follow-up of 82.3 months. Methods. One hundred and ninety-nine eligible newly diagnosed, nonimmunocompromised patients with PCNSL aged 18â70 years with WHO performance status 0â3 was randomized between treatment with MBVP chemotherapy with or without rituximab, followed by high-dose cytarabine consolidation in responding patients, and reduced-dose WBRT in patients aged †60 years. Event-free survival was the primary endpoint. Overall survival rate, neurocognitive functioning (NCF), and health-related quality of life (HRQoL) were additionally assessed, with the IPCG test battery, EORTC QLQ-C30 and QLQ-BN20 questionnaires, respectively. Results. For event-free survival, the hazard ratio was 0.85, 95% CI 0.61â1.18, P = .33. Overall survival rate at 5 years for MBVP and R-MBVP was 49% (39â59) and 53% (43â63) respectively. In total, 64 patients died in the MBVP arm and 55 in the R-MBVP arm, of which 69% were due to PCNSL. At the group level, all domains of NCF and HRQoL improved to a clinically relevant extent after treatment initiation, and remained stable thereafter up to 60 months of follow-up, except for motor speed which deteriorated between 24 and 60 months. Although fatigue improved initially, high levels persisted in the long term. Conclusions. Long-term follow-up confirms the lack of added value of rituximab in addition to MBVP and HD-cytarabine for PCNSL.</p
Perfusion of the basolateral nucleus of the amygdala (BLA) is correlated with anxiety levels.
<p>Significant correlations were found between anxiety levels and perfusion of the left (A) and right (B) basolateral amygdala (BLA), as defined using anatomical regions-of-interest. These findings were then confirmed in a voxel-wise, whole brain regression analysis (C). In C, the BLA regions-of-interest are outlined in blue; the voxel-level display threshold is p<.005 (showing only clusters surviving whole-brain correction, see Methods). Clusters that showed cluster-wise significance (p<.05, whole brain corrected) are reported in the text and in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0097466#pone-0097466-t002" target="_blank">Table 2</a>. R, right.</p
Perfusion of a distributed network of regions outside of the amygdala is also correlated with anxiety levels.
<p>A voxel-wise whole brain regression analysis revealed that, in addition to the basolateral amygdala (BLA), perfusion of the superior frontal gyri and posterior cingulate cortex (A), and anterior putamen (B), among other regions (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0097466#pone-0097466-t002" target="_blank">Table 2</a>), were significantly correlated with anxiety levels. Whole-brain corrected results (see Methods) are displayed here using a voxel-level threshold of p<.005. Clusters that showed cluster-wise significance (p<.05, whole brain corrected) are reported in the text and in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0097466#pone-0097466-t002" target="_blank">Table 2</a>. R, right; PCC, posterior cingulate cortex; SFG, superior frontal gyri.</p
Basolateral amygdala functional connectivity.
<p>Areas of the brain showing significant functional connectivity with the basolateral amygdala (BLA) are listed. Clusters that are unshaded are those with positive functional coupling with the BLA, whereas clusters that are shaded grey are those showing negative functional coupling (inverse or anti-correlations) with the BLA (following global mean regression). Sites of connectivity within or abutting the BLA are not listed because of the difficulty of interpreting these findings. Also see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0097466#pone-0097466-g003" target="_blank">Figure 3</a>. BAâ=âBrodmann Area; Hemiâ=âhemisphere; Talâ=âTalaraich coordinates.</p
- âŠ