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Previous studies using resting-state functional neuroimaging have revealed alterations in whole-brain images, connectome-wide functional connectivity and graph-based metrics in groups of patients with schizophrenia relative to groups of healthy controls. However, it is unclear which of these measures best captures the neural correlates of this disorder at the level of the individual patient.
Here we investigated the relative diagnostic value of these measures. A total of 295 patients with schizophrenia and 452 healthy controls were investigated using resting-state functional Magnetic Resonance Imaging at five research centres. Connectome-wide functional networks were constructed by thresholding correlation matrices of 90 brain regions, and their topological properties were analyzed using graph theory-based methods. Single-subject classification was performed using three machine learning (ML) approaches associated with varying degrees of complexity and abstraction, namely logistic regression, support vector machine and deep learning technology.
Connectome-wide functional connectivity allowed single-subject classification of patients and controls with higher accuracy (average: 81%) than both whole-brain images (average: 53%) and graph-based metrics (average: 69%). Classification based on connectome-wide functional connectivity was driven by a distributed bilateral network including the thalamus and temporal regions.
These results were replicated across the three employed ML approaches. Connectome-wide functional connectivity permits differentiation of patients with schizophrenia from healthy controls at single-subject level with greater accuracy; this pattern of results is consistent with the ‘dysconnectivity hypothesis’ of schizophrenia, which states that the neural basis of the disorder is best understood in terms of system-level functional connectivity alterations.
Altered autobiographical memory (ABM) functioning has been implicated in the pathogenesis of depression and posttraumatic stress disorder and may represent one mechanism by which childhood maltreatment elevates psychiatric risk.
To investigate the impact of childhood maltreatment on ABM functioning.
Thirty-four children with documented maltreatment and 33 matched controls recalled specific ABMs in response to emotionally valenced cue words during functional magnetic resonance imaging.
Children with maltreatment experience showed reduced hippocampal and increased middle temporal and parahippocampal activation during positive ABM recall compared with peers. During negative ABM recall they exhibited increased amygdala activation, and greater amygdala connectivity with the salience network.
Childhood maltreatment is associated with altered ABM functioning, specifically reduced activation in areas encoding specification of positive memories, and greater activation of the salience network for negative memories. This pattern may confer latent vulnerability to future depression and posttraumatic stress disorder.
It is unclear to what extent the traditional distinction between
neurological and psychiatric disorders reflects biological
To examine neuroimaging evidence for the distinction between neurological
and psychiatric disorders.
We performed an activation likelihood estimation meta-analysis on
voxel-based morphometry studies reporting decreased grey matter in 14
neurological and 10 psychiatric disorders, and compared the regional and
network-level alterations for these two classes of disease. In addition,
we estimated neuroanatomical heterogeneity within and between the two
Basal ganglia, insula, sensorimotor and temporal cortex showed greater
impairment in neurological disorders; whereas cingulate, medial frontal,
superior frontal and occipital cortex showed greater impairment in
psychiatric disorders. The two classes of disorders affected distinct
functional networks. Similarity within classes was higher than between
classes; furthermore, similarity within class was higher for neurological
than psychiatric disorders.
From a neuroimaging perspective, neurological and psychiatric disorders
represent two distinct classes of disorders.
While maltreatment is known to impact social and emotional functioning, threat processing, and neural structure, the potentially dimorphic influence of sex on these outcomes remains relatively understudied. We investigated sex differences across these domains in a large community sample of children aged 10 to 14 years (n = 122) comprising 62 children with verified maltreatment experience and 60 well-matched nonmaltreated peers. The maltreated group relative to the nonmaltreated comparison group exhibited poorer social and emotional functioning (more peer problems and heightened emotional reactivity). Cognitively, they displayed a pattern of attentional avoidance of threat in a visual dot-probe task. Similar patterns were observed in males and females in these domains. Reduced gray matter volume was found to characterize the maltreated group in the medial orbitofrontal cortex, bilateral middle temporal lobes, and bilateral supramarginal gyrus; sex differences were observed only in the supramarginal gyrus. In addition, a disordinal interaction between maltreatment exposure and sex was found in the postcentral gyrus. Finally, attentional avoidance to threat mediated the relationship between maltreatment and emotional reactivity, and medial orbitofrontal cortex gray matter volume mediated the relationship between maltreatment and peer functioning. Similar mediation patterns were observed across sexes. This study highlights the utility of combining multiple levels of analysis when studying the “latent vulnerability” engendered by childhood maltreatment and yields tentative findings regarding a neural basis of sex differences in long-term outcomes for maltreated children.
The majority of people at ultra high risk (UHR) of psychosis also present with co-morbid affective disorders such as depression or anxiety. The neuroanatomical and clinical impact of UHR co-morbidity is unknown.
We investigated group differences in grey matter volume using baseline magnetic resonance images from 121 participants in four groups: UHR with depressive or anxiety co-morbidity; UHR alone; major depressive disorder; and healthy controls. The impact of grey matter volume on baseline and longitudinal clinical/functional data was assessed with regression analyses.
The UHR-co-morbidity group had lower grey matter volume in the anterior cingulate cortex than the UHR-alone group, with an intermediate effect between controls and patients with major depressive disorder. In the UHR-co-morbidity group, baseline anterior cingulate volume was negatively correlated with baseline suicidality/self-harm and obsessive–compulsive disorder symptoms.
Co-morbid depression and anxiety disorders contributed distinctive grey matter volume reductions of the anterior cingulate cortex in people at UHR of psychosis. These volumetric deficits were correlated with baseline measures of depression and anxiety, suggesting that co-morbid depressive and anxiety diagnoses should be carefully considered in future clinical and imaging studies of the psychosis high-risk state.
Grey matter volume and cortical thickness represent two complementary aspects of brain structure. Several studies have described reductions in grey matter volume in people at ultra-high risk (UHR) of psychosis; however, little is known about cortical thickness in this group. The aim of the present study was to investigate cortical thickness alterations in UHR subjects and compare individuals who subsequently did and did not develop psychosis.
We examined magnetic resonance imaging data collected at four different scanning sites. The UHR subjects were followed up for at least 2 years. Subsequent to scanning, 50 UHR subjects developed psychosis and 117 did not. Cortical thickness was examined in regions previously identified as sites of neuroanatomical alterations in UHR subjects, using voxel-based cortical thickness.
At baseline UHR subjects, compared with controls, showed reduced cortical thickness in the right parahippocampal gyrus (p < 0.05, familywise error corrected). There were no significant differences in cortical thickness between the UHR subjects who later developed psychosis and those who did not.
These data suggest that UHR symptomatology is characterized by alterations in the thickness of the medial temporal cortex. We did not find evidence that the later progression to psychosis was linked to additional alterations in cortical thickness, although we cannot exclude the possibility that the study lacked sufficient power to detect such differences.
At present there are no objective, biological markers that can be used to reliably identify individuals with post-traumatic stress disorder (PTSD). This study assessed the diagnostic potential of structural magnetic resonance imaging (sMRI) for identifying trauma-exposed individuals with and without PTSD.
sMRI scans were acquired from 50 survivors of the Sichuan earthquake of 2008 who had developed PTSD, 50 survivors who had not developed PTSD and 40 healthy controls who had not been exposed to the earthquake. Support vector machine (SVM), a multivariate pattern recognition technique, was used to develop an algorithm that distinguished between the three groups at an individual level. The accuracy of the algorithm and its statistical significance were estimated using leave-one-out cross-validation and permutation testing.
When survivors with PTSD were compared against healthy controls, both grey and white matter allowed discrimination with an accuracy of 91% (p < 0.001). When survivors without PTSD were compared against healthy controls, the two groups could be discriminated with accuracies of 76% (p < 0.001) and 85% (p < 0.001) based on grey and white matter, respectively. Finally, when survivors with and without PTSD were compared directly, grey matter allowed discrimination with an accuracy of 67% (p < 0.001); in contrast the two groups could not be distinguished based on white matter.
These results reveal patterns of neuroanatomical alterations that could be used to inform the identification of trauma survivors with and without PTSD at the individual level, and provide preliminary support to the development of SVM as a clinically useful diagnostic aid.
Childhood adversity is associated with significantly increased risk of psychiatric disorder. To date, functional magnetic resonance imaging (fMRI) studies of children have mainly focused on institutionalisation and investigated conscious processing of affect.
To investigate neural response to pre-attentively presented affect cues in a community sample of children with documented experiences of maltreatment in the home.
A masked dot-probe paradigm involving pre-attentive presentation of angry, happy and neutral facial expressions was employed. Eighteen maltreated children were compared with 23 carefully matched non-maltreated peers.
Increased neural response was observed in the right amygdala for pre-attentively presented angry and happy faces in maltreated v. non-maltreated children. Level of amygdala activation was negatively associated with age at onset for several abuse subtypes.
Maltreatment is associated with heightened neural response to positive and negative facial affect, even to stimuli outside awareness. This may represent a latent neural risk factor for future psychiatric disorder.
Group-level results suggest that relative to healthy controls (HCs), ultra-high-risk (UHR) and first-episode psychosis (FEP) subjects show alterations in neuroanatomy, neurofunction and cognition that may be mediated genetically. It is unclear, however, whether these groups can be differentiated at single-subject level, for instance using the machine learning analysis support vector machine (SVM). Here, we used a multimodal approach to examine the ability of structural magnetic resonance imaging (sMRI), functional MRI (fMRI), diffusion tensor neuroimaging (DTI), genetic and cognitive data to differentiate between UHR, FEP and HC subjects at the single-subject level using SVM.
Three age- and gender-matched SVM paired comparison groups were created comprising 19, 19 and 15 subject pairs for FEP versus HC, UHR versus HC and FEP versus UHR, respectively. Genetic, sMRI, DTI, fMRI and cognitive data were obtained for each participant and the ability of each to discriminate subjects at the individual level in conjunction with SVM was tested.
Successful classification accuracies (p < 0.05) comprised FEP versus HC (genotype, 67.86%; DTI, 65.79%; fMRI, 65.79% and 68.42%; cognitive data, 73.69%), UHR versus HC (sMRI, 68.42%; DTI, 65.79%), and FEP versus UHR (sMRI, 76.67%; fMRI, 73.33%; cognitive data, 66.67%).
The results suggest that FEP subjects are identifiable at the individual level using a range of biological and cognitive measures. Comparatively, only sMRI and DTI allowed discrimination of UHR from HC subjects. For the first time FEP and UHR subjects have been shown to be directly differentiable at the single-subject level using cognitive, sMRI and fMRI data. Preliminarily, the results support clinical development of SVM to help inform identification of FEP and UHR subjects, though future work is needed to provide enhanced levels of accuracy.
Schizotypy is conceptualized as a subclinical manifestation of the same underlying biological factors that give rise to schizophrenia and other schizophrenia spectrum disorders. Individuals with psychometric schizotypy (PS) experience subthreshold psychotic signs and can be psychometrically identified among the general population. Previous research using magnetic resonance imaging (MRI) has shown gray-matter volume (GMV) abnormalities in chronic schizophrenia, in subjects with an at-risk mental state (ARMS) and in individuals with schizotypal personality disorder (SPD). However, to date, no studies have investigated the neuroanatomical correlates of PS.
Six hundred first- and second-year university students completed the Community Assessment of Psychic Experiences (CAPE), a self-report instrument on psychosis proneness measuring attenuated positive psychotic experiences. A total of 38 subjects with high and low PS were identified and subsequently scanned with MRI. Voxel-based morphometry (VBM) was applied to examine GMV differences between subjects with high and low positive PS.
Subjects with high positive PS showed larger global volumes compared to subjects with low PS, and larger regional volumes in the medial posterior cingulate cortex (PCC) and the precuneus. There were no regions where GMV was greater in low than in high positive PS subjects.
These regions, the PCC and precuneus, have also been sites of volumetric differences in MRI studies of ARMS subjects and schizophrenia, suggesting that psychotic or psychotic-like experiences may have common neuroanatomical correlates across schizophrenia spectrum disorders.
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