Mapping structural covariance networks of facial emotion recognition in early psychosis: A pilot study

Abstract

People with psychosis show deficits recognizing facial emotions and disrupted activation in the underlying neural circuitry. We evaluated associations between facial emotion recognition and cortical thickness using a correlation-based approach to map structural covariance networks across the brain. Fifteen people with an early psychosis provided magnetic resonance scans and completed the Penn Emotion Recognition and Differentiation tasks. Fifteen historical controls provided magnetic resonance scans. Cortical thickness was computed using CIVET and analyzed with linear models. Seed-based structural covariance analysis was done using the mapping anatomical correlations across the cerebral cortex methodology. To map structural covariance networks involved in facial emotion recognition, the right somatosensory cortex and bilateral fusiform face areas were selected as seeds. Statistics were run in SurfStat. Findings showed increased cortical covariance between the right fusiform face region seed and right orbitofrontal cortex in controls than early psychosis subjects. Facial emotion recognition scores were not significantly associated with thickness in any region. A negative effect of Penn Differentiation scores on cortical covariance was seen between the left fusiform face area seed and right superior parietal lobule in early psychosis subjects. Results suggest that facial emotion recognition ability is related to covariance in a temporal-parietal network in early psychosis.

Introduction

Social cognition is defined as the mental processes involved in understanding, observing, and interpreting information in one's social environment. Research has established that people with psychosis show difficulties in social cognition, most prominently in recognizing facial emotions (Kohler et al., 2010). These deficits are present at all stages of the illness including the first-episode (Barkl et al., 2014) and are related to poorer social and occupational functioning (Couture et al., 2006, Fett et al., 2011, Irani et al., 2012).

Functional magnetic resonance imaging (fMRI) studies in non-clinical subjects have shown that processing of emotional faces in humans activates a network of regions that includes visual (fusiform face area), limbic (amygdala), temporal-parietal, and prefrontal brain areas (Fusar-Poli et al., 2009). Evidence from lesion studies (Adolphs et al., 2000, Adolphs et al., 2003) and experiments using transcranial magnetic stimulation (Pitcher et al., 2008) have demonstrated that the face region of the right somatosensory cortex is also critical for accurate facial emotion recognition. A growing literature indicates that people with psychosis show abnormal activation in these brain regions when making judgements about facial emotional expressions, and these deviant activation patterns are thought to contribute to impairments in recognizing facial emotions (Gur et al., 2007, Li et al., 2010, Pinkham et al., 2011). However, the relationship between facial emotion recognition ability and neural structure in people with psychosis is largely understudied, and should be investigated using sophisticated imaging analyses and at differing illness stages such as soon after the onset of a psychosis. Functional imaging data suggests that the “face network” may have developed atypically in this population, which may also be reflected in aberrant structure or structural networks.

Recent developments in structural imaging analyses provide an opportunity to study associations between neuroanatomy and behavioral measures, including cognition (Dziobek et al., 2010, Lerch et al., 2006). Cortical thickness measures can be extracted through a fully-automated measurement of magnetic resonance (MR) images at a subvoxel resolution, and are believed to primarily reflect morphometric gray matter features such as the size, density or arrangement of cells. (Lerch and Evans, 2005, Parent and Carpenter, 1995). Structural covariance analysis of MR-based cortical thickness data can be used to further map inter-regional anatomical networks. This approach allows measurement of cortical thickness/gray matter volume in which areas of the cortex correlate with one another, allowing evaluation of anatomical relationships in the context of large-scale networks. Covariations in gray matter are thought to result from mutually trophic and maturational influences, and have been shown to partially reflect underlying white matter tracts and functional connectivity networks (Alexander-Bloch et al., 2013, Mechelli et al., 2005, Raznahan et al., 2011). A combined approach involving cortical thickness and structural covariance network analyses has the potential to provide information about underlying patterns of structure and network relationships that are associated with facial emotion recognition abilities in people with psychosis, which is lacking in the current literature.

The aims of the current study were fourfold. Our first aim was to compare cortical thickness in an early psychosis sample to a historical control group. In line with meta-analytic results (Bora et al., 2011) we hypothesized reduced cortical thickness in early psychosis subjects compared to controls in frontal and temporal regions. Our second aim was to assess structural covariance within intrinsic networks of facial emotion recognition, using the right somatosensory cortex (Pitcher et al., 2008) and bilateral fusiform face areas (Fusar-Poli et al., 2009) as seed regions of interest, in early psychosis subjects vs. controls. We hypothesized that early psychosis subjects would show alterations in network properties compared with controls. Our third aim was to evaluate associations between facial emotion recognition and cortical thickness across the cortical mantle in the early psychosis group, using the right somatosensory cortex and bilateral fusiform face regions as seeds. In line with functional imaging data showing that poorer facial emotion abilities are associated with altered activation in widespread cortical regions in this population (Gur et al., 2007), we hypothesized that early psychosis subjects would show different patterns of associations between cortical thickness and facial emotion recognition ability than controls. Our fourth aim was to evaluate the modulation of facial emotion recognition on structural covariance between thickness in right somatosensory cortex and bilateral fusiform face area seeds and thickness across the brain in early psychosis subjects. Given the limited published research on structural covariance analyses, aim four was exploratory and no hypothesis was put forth.