A comprehensive keyword search of EMBASE (from 1980), PsycINFO (from 1801) and Medline (from 1950), was conducted using the following search strategy. The following Boolean phrase was used: {([Magnetic Resonance Imaging] OR [MRI]) AND ([Schizophrenia] OR [schizo*] OR [FTLD] OR [Fronto-Temporal Lobar Degeneration) AND ([Voxel] OR [VBM])}. Both free-text and expanded medical subject headings were be used. The search strategy was supplemented using a cited reference search, and by inspecting the reference lists of included articles. The search was conducted in January 2011. No time span was specified for date of publication.

Studies were considered for the review using the following inclusion criteria: 1) they were published in English as a peer-reviewed article (rather than a letter, abstract, or case report); 2) they compared a sample of formally diagnosed subjects with a group of unrelated healthy control subjects; 3) they utilized voxel-based analysis of gray matter in structural MRI scans to investigate differences in whole-brain; and 4) they reported the three-dimensional co-ordinates of changes in stereotactic space.

FTLD studies were considered if they consisted of subjects with Fronto-Temporal Lobar Degeneration or related diagnoses, such as Semantic Dementia. FES studies were considered if they included a group of subjects with schizophrenia or related diagnoses, specifically first episode schizoaffective disorder or psychosis. Only first-episode schizophrenia patients were included, therefore, papers must have documented that patients were experiencing symptoms related to psychosis without a prior diagnosis without administration of prior antipsychotic medication in order to be included in our meta-analysis.

Studies were excluded if: 1) there were insufficient data to extract the number of subjects in each group; 2) there were fewer than five subjects in either the patient group or the comparison group; 3) the comparison groups consisted of patients with minor non-psychiatric illnesses; 4) the patient group in the schizophrenia studies consisted of subjects with child-onset schizophrenia or chronic schizophrenia beyond the stage of first-episode psychosis; 5) the studies used region-of-interest volumetric analyses, or the deformation- or tensor-based volumetric methods for measuring regional brain volumes; and 6) the data contributed to another publication, in which case the publication with the largest group size under study was selected.

Data were extracted from two independent investigators (BO and IEW) and were double-checked. Information gathered from the studies included the authors, year of publication, demographic variables (number of subjects, age at baseline and gender), illness variables (diagnosis and duration of illness), and the reported stereotactic coordinates related to the comparisons between structural MRI scans of patients and controls from every selected study. Co-ordinates that were reported in the stereotactic space of the Montreal Neurological Institute (MNI) were converted to Talairach coordinates using the Lancaster transform (icbm2tal) in the GingerALE 2.0 program 29 . Talairach co-ordinates that had been generated by the Brett transform applied to statistical parametric mapping MNI co-ordinates were transformed back to MNI space in GingerALE and then to Talairach space using the Lancaster transform.

Meta-analyses were performed using the Talairach stereotactic coordinates derived from the included studies. Meta-analyses were carried out using GingerALE 2.0 29 . This uses the technique of Activation Likelihood Estimation (ALE) 25 and permits weighting of studies in the meta-analysis, e.g. based on sample size. This modification of ALE treats the spatial conjunction of co-ordinates from separate studies as more significant than conjunction of co-ordinates from a single study. The probability values can then be interpreted on an image-wide basis after correction for multiple testing using the False Discovery Rate, a method which controls the proportion of type 1 errors (false positives) among significant results 30 .

Descriptive meta-analyses were then performed to identify the distribution of brain changes in FES and FTLD, when compared to control subjects. The overlap of these two distributions was measured.

We tested the overlap of the FTLD co-ordinates with the FES spatial map generated by ALE using a randomisation method based on our previous work hybridising ALE spatial techniques with GSMA (Genome Scan Meta-Analysis) statistical methods 31 .

For each FTLD study, the reported loci of maximal anatomical difference were modeled as the peaks of three-dimensional Gaussian probability density functions with full-width half-maximum of 7 mm, within a brain mask of size N of linear dimension 2 mm. The voxels in this probability image were then ranked from N (highest probability) to 1 (lowest probability), giving voxels of equal probability a mean rank. This created a rank image for each study which was smoothed with a 7 mm Gaussian filter. This image was masked with the First Episode Schizophrenia spatial map generated by ALE and the total value of ranks within the mask was calculated. The total for all studies of ranks within the mask was calculated (‘FES Mask Total’).

A null distribution for the FES Mask Total result was derived by 1000 permutations of the same process, but using an equal number of co-ordinates for each study derived from a random uniform distribution of coordinates within the brain mask. The probability of a FES Mask Total under the null hypothesis was calculated as the proportion of permutations giving a value equal or greater than the actual value.

The data set being tested was included in the ranking of all known outcomes. The significance threshold was set at p < 0.05.

Eighteen FES studies included 185 co-ordinates of gray matter decreases. Meta-analysis of this data identified gray matter decreases in regions including bilateral head of caudate nucleus, bilateral insula, bilateral amygdala/uncus region and bilateral superior temporal region (Figure 2).

Twenty FTLD studies provided 260 co-ordinates of gray matter decreases. Meta-analysis of this data identified gray matter decreases in regions including bilateral head of caudate nucleus, bilateral insula, bilateral amygdala/uncus region and bilateral superior temporal region (Table 2, Figure 2).

Gray matter decreases were present in both disorders in regions including bilateral caudate head, left insula and bilateral uncus region (Figure 3).

The spatial congruence between the disorders was estimated by percentage overlap. The FTLD map of gray matter decreases comprised 2450 voxels in a brain mask of 201069 voxels. The FES map of gray matter decreases comprised 888 voxels in a brain mask of 201069 voxels. The overlap between the FTLD and FES maps was 124 voxels. Therefore the overlap of FTLD within FES was 14% (compared to an expected overlap of 1.2% if the FTLD map was randomly distributed in the brain mask). The overlap of FES within FTLD was 5% (compared to an expected overlap of 0.4% if the FES mask was randomly distributed in the brain mask). Applying the spatial overlap testing method, the overlap of the FTLD co-ordinates with the FES spatial map generated by ALE was significant (p = 0.001).

These results confirm those of previous meta-analyses of the two disorders, using smaller samples of primary studies. Several previous meta-analyses using ‘region-of-interest’ analyses have examined gray matter deficits in schizophrenia 83 84 , with consistent findings of medial temporal lobe atrophy 85 86 87 88 . Patients with FES also have smaller whole-brain volume, with greater lateral ventricular volume 89 . Frontal 90 91 and temporal 37 volumes have been reported to be smaller at first episode, and basal ganglia are also affected early in the illness 33 92 . The ALE method has also been used to investigate brain structural abnormalities in schizophrenia derived from studies using voxel-based morpometry analyses 1 93 . In a recent meta-analysis by Chan et al., patients with FES had lower gray matter volumes in frontal, temporal, striatal, and cerebellar regions compared with both control subjects and people who are at genetically high-risk of developing schizophrenia 94 . They mapped progressive changes from the high-risk stage to the first-episode stage, clarifying potential markers for disease risk (anterior cingulate and right insula volume reduction) and for disease onset (caudate volume reduction) 94 .

In FTLD, a meta-analysis of voxel-based morphometry studies found predominant frontal and temporal lobe involvement, with specific patterns of atrophy in the three clinical subtypes of FTLD, namely, FTD (frontotemporal dementia), SD (semantic dementia) and PNFA (progressive non-fluent aphasia) 95 . Correspondingly, diagnostic criteria for FTLD create a ‘triple dissociation’ of these subtypes with a high diagnostic accuracy clinically 96 . The clinical characteristics of each subtype of FTLD correspond well with the neuroanatomical deficits found.

The involvement of the basal ganglia (bilateral gray matter decreases in the caudate head in both disorders) agrees with Middleton and Strick’s prediction that abnormalities within cortico-striatal circuits may underlie neuropsychiatric symptoms 97 98 . Anatomical studies have revealed discrete connections between the basal ganglia and the cerebral cortex, reciprocally interconnecting a large and diverse set of cortical areas 99 . Dysregulation and abnormal dopaminergic transmission in these loops may contribute to hyperkinetic movements as well as cognitive impairments 100 101 102 . Robbins 103 proposed that the heterogeneous range of core symptoms associated with psychosis, appearing to be associated with a range of structural and functional abnormalities, might be explained by a frontal-striatal hypothesis, where an altered balance in the flow of information between through the basal ganglia could explain the seemingly disparate symptoms and characteristics of schizophrenia and psychotic episodes in FTLD. Our results indicate that the basal ganglia loop in particular incorporating the head of the caudate nucleus, are affected by FES and FTLD, which may at least partly explain their shared symptoms.

Our findings reveal that both disorders are characterised by reduced volumes of various paralimbic and limbic structures. Neuroanatomists and cytoarchitectologists have grouped the regions shown to be affected in FES and FTLD, namely the superior temporal gyrus (temporal pole), rostral and caudal anterior cingulate, posterior cingulate, orbital frontal cortex, insula, and parahippocampal regions, into the paralimbic cortex 104 105 . There is documented evidence to support paralimbic dysfunction in various psychiatric disorders, namely psychopathy 106 , bipolar disorder 72 , psychotic symptoms in depressive disorder 107 and attention deficit hyperactivity disorder 108 . Our results also indicate that both disorders are characterised by reduced caudate size, lesions of which cause impairments in learning, memory 109 and behaviour through the selection of appropriate sub-goals based on an evaluation of action-outcomes 110 . This may reflect the common symptomatology between the two disorders.

Various explanations need to be considered for the overlap in gray matter deficits between the two disorders. Firstly, the result could be due to coincidence. However, we have applied a statistical test to the spatial congruence which suggests that this is highly unlikely (the p value for the null hypothesis of a random distribution of FTLD co-ordinates within the FES spatial map was p = 0.001). Secondly, the symptoms of neuropsychiatric disorders are related to the anatomy of the brain pathology. Therefore, the selection of schizophrenia and FTLD, which share certain symptoms (as described above) may constrain the anatomical findings towards certain brain regions, in the absence of any other more meaningful connection between the neuropathology of the two disorders. The evidence that schizophrenia and FTLD co-occur in some families 6 suggests the possibility of a more fundamental connection between the two disorders. Thirdly, the neuropathology of the two disorders may be (at the neurochemical pathway level) distinct but the common network identified in this study may be ‘a final common pathway’ in the pathological process of both disorders, or a common reaction to such processes.

There are limitations of this meta-analysis. Firstly, by meta-analysing co-ordinates of maximum change from primary studies there is a loss of spatial information. This reduces the spatial resolution of the results. Secondly, as more primary studies are published the distribution of changes in each disorder may become more extensive as there is improved power to detect changes. Thirdly, there are alternative approaches for investigating spatial overlap of two disorders. For example, Yu et al., used a post-hoc meta-analytic estimation of the extent to which gray matter compares with controls in bipolar disorder and schizophrenia by using a modification of the ALE method 71 . Lastly, the mean age of patients with FES was 24.4 years, whereas in FTLD, the mean age was 63.6 years (Table 1). There are no validated methods to account for these differences in an ALE meta-analysis, and it is possible that some of the results may have been affected by “normal” structural brain aging processes 111 . Anatomical likelihood estimation analyses are a relatively novel and changing technique, and as time progresses, standardisation of meta-analysis techniques will help researchers evaluate results from different studies more objectively.

In the future, localized gray matter deficits detected via the above analyses may be combined with those identified in activation studies of cognitive deficits in schizophrenia and FTLD, in order to understand the correlation between functional and structural connectivity in both disorders. For example, the structural MRI gray matter deficits could be used as nodes for a network analysis 112 , as can now be done on individual scans 113 , which may be utilized to investigate and compare functional connectivity changes in FES and FTLD.