Predictive Pattern Classification Can Distinguish Gender Identity Subtypes from Behavior and Brain Imaging.

The exact neurobiological underpinnings of gender identity (i.e., the subjective perception of oneself belonging to a certain gender) still remain unknown. Combining both resting-state functional connectivity and behavioral data, we examined gender identity in cisgender and transgender persons using a data-driven machine learning strategy. Intrinsic functional connectivity and questionnaire data were obtained from cisgender (men/women) and transgender (trans men/trans women) individuals. Machine learning algorithms reliably detected gender identity with high prediction accuracy in each of the four groups based on connectivity signatures alone. The four normative gender groups were classified with accuracies ranging from 48% to 62% (exceeding chance level at 25%). These connectivity-based classification accuracies exceeded those obtained from a widely established behavioral instrument for gender identity. Using canonical correlation analyses, functional brain measurements and questionnaire data were then integrated to delineate nine canonical vectors (i.e., brain-gender axes), providing a multilevel window into the conventional sex dichotomy. Our dimensional gender perspective captures four distinguishable brain phenotypes for gender identity, advocating a biologically grounded reconceptualization of gender dimorphism. We hope to pave the way towards objective, data-driven diagnostic markers for gender identity and transgender, taking into account neurobiological and behavioral differences in an integrative modeling approach.

Effect of MAOA Genotype on Resting-State Networks in Healthy Participants.

Up to now, it remains unclear how monoamine oxidase A (MAOA), which has been repeatedly linked to aggression, affects brain activity within resting-state networks (RSN). Here, we used functional magnetic resonance imaging (fMRI) to test whether the MAOA genotype might influence activity within the common RSN. Our results demonstrate that during rest, participants with the low-activity genotype (MAOA-L) exhibit more activity within frontoparietal and temporal parts of the default mode network (DMN) and the cerebellum. The executive control and salience RSN revealed reduced activity for the MAOA-L group in several areas related to executive control, namely the right middle frontal gyrus (BA 6 and BA 9), and the dorsal part of the anterior cingulate cortex. Participants with the high-activity genotype (MAOA-H) showed increased activity in the posterior cingulate part of the DMN. Taken together, we found widespread hyperactivity within the DMN and reduced activity in brain areas related to executive and inhibitory control for the MAOA-L group. We discuss how these first results examining the influence of MAOA on the resting brain might be related to previous findings regarding the genetics of aggression, while acknowledging that this is an exploratory study which needs further confirmation.

Respiratory function modulated during execution, observation, and imagination of walking via SII.

The Mirror Neurons System (MNS) consists of brain areas active during actions execution, as well as observation-imagination of the same actions. MNS represents a potential mechanism by which we understand other's action goals. We investigated MNS activation for legs actions, and its interaction with the autonomic nervous system. We performed a physiological and fMRI investigation on the common neural structures recruited during the execution, observation, and imagination of walking, and their effects on respiratory activity. Bilateral SMA were activated by all three tasks, suggesting that these areas are responsible for the core of the MNS effect for walking. Moreover, we observed in bilateral parietal opercula (OP1, secondary somatosensory cortex-SII) evidence of an MNS subtending walking execution-observation-imagination that also modulated the respiratory function. We suggest that SII, in modulating the vegetative response during motor activity but also during observation-imagination, consists of a re-enacting function which facilitates the understanding of motor actions.

Male-to-female gender dysphoria: Gender-specific differences in resting-state networks.

INTRODUCTION: Recent research found gender-related differences in resting-state functional connectivity (rs-FC) measured by functional magnetic resonance imaging (fMRI). To the best of our knowledge, there are no studies examining the differences in rs-FC between men, women, and individuals who report a discrepancy between their anatomical sex and their gender identity, i.e. gender dysphoria (GD). METHODS: To address this important issue, we present the first fMRI study systematically investigating the differences in typical resting-state networks (RSNs) and hormonal treatment effects in 26 male-to-female GD individuals (MtFs) compared with 19 men and 20 women. RESULTS: Differences between male and female control groups were found only in the auditory RSN, whereas differences between both control groups and MtFs were found in the auditory and fronto-parietal RSNs, including both primary sensory areas (e.g. calcarine gyrus) and higher order cognitive areas such as the middle and posterior cingulate and dorsomedial prefrontal cortex. Overall, differences in MtFs compared with men and women were more pronounced before cross-sex hormonal treatment. Interestingly, rs-FC between MtFs and women did not differ significantly after treatment. When comparing hormonally untreated and treated MtFs, we found differences in connectivity of the calcarine gyrus and thalamus in the context of the auditory network, as well as the inferior frontal gyrus in context of the fronto-parietal network. CONCLUSION: Our results provide first evidence that MtFs exhibit patterns of rs-FC which are different from both their assigned and their aspired gender, indicating an intermediate position between the two sexes. We suggest that the present study constitutes a starting point for future research designed to clarify whether the brains of individuals with GD are more similar to their assigned or their aspired gender.

Response inhibition failure to visual stimuli paired with a "single-type" stressor in PTSD patients: an fMRI pilot study.

Patients with post-traumatic stress disorder (PTSD) tend to misinterpret innocuous stimuli as potential threats, possibly due to a conditioning provoked by traumatic episodes. Previous neuroimaging evidence has shown an abnormal activation of the amygdala and prefrontal cortex in PTSD patients during fear conditioning and extinction. Nevertheless, the effects of a single-type adverse stressor on that circuit remain poorly explored. We tested the hypothesis that a single-type adverse episode is able to affect the prefrontal cortex and amygdala response to conditioned stimuli. To test this hypothesis, fMRI recordings were performed in PTSD patients and trauma-exposed controls during the observation of neutral and negative paired or non-paired pictures with an adverse stimulus by means of a single association. Results showed that left amygdala activation during negative reinforced stimuli was correlated with the score of PTSD clinical scale across all subjects. Furthermore, in the traumatized non-PTSD group, the activation of the dorso-medial prefrontal cortex and bilateral amygdala was lower during the observation of the reinforced (CS(+)) versus non-reinforced pictures (CS(-)) in response to emotionally negative stimuli. This was not the case in the PTSD patients. These results suggest that in PTSD patients, a single-episode conditioning unveils the failure of an inhibitory mechanism moderating the activity of the prefrontal cortex and amygdala in response to adverse and neutral stimuli.

Influence of anodal transcranial direct current stimulation (tDCS) over the right angular gyrus on brain activity during rest.

Although numerous studies examined resting-state networks (RSN) in the human brain, so far little is known about how activity within RSN might be modulated by non-invasive brain stimulation applied over parietal cortex. Investigating changes in RSN in response to parietal cortex stimulation might tell us more about how non-invasive techniques such as transcranial direct current stimulation (tDCS) modulate intrinsic brain activity, and further elaborate our understanding of how the resting brain responds to external stimulation. Here we examined how activity within the canonical RSN changed in response to anodal tDCS applied over the right angular gyrus (AG). We hypothesized that changes in resting-state activity can be induced by a single tDCS session and detected with functional magnetic resonance imaging (fMRI). Significant differences between two fMRI sessions (pre-tDCS and post-tDCS) were found in several RSN, including the cerebellar, medial visual, sensorimotor, right frontoparietal, and executive control RSN as well as the default mode and the task positive network. The present results revealed decreased and increased RSN activity following tDCS. Decreased RSN activity following tDCS was found in bilateral primary and secondary visual areas, and in the right putamen. Increased RSN activity following tDCS was widely distributed across the brain, covering thalamic, frontal, parietal and occipital regions. From these exploratory results we conclude that a single session of anodal tDCS over the right AG is sufficient to induce large-scale changes in resting-state activity. These changes were localized in sensory and cognitive areas, covering regions close to and distant from the stimulation site.

Frequency domains of resting state default mode network activity in schizophrenia.

Probabilistic independent component analysis was applied to identify the default mode network (DMN) in resting state data obtained with functional magnetic resonance imaging from 25 DSM-IV schizophrenia and 25 matched healthy subjects. Power spectrum analysis showed a significant diagnosis × frequency interaction and higher power in one frequency band, indicating an alteration of DMN frequency spectrum in schizophrenia.

Default mode network activity in schizophrenia studied at resting state using probabilistic ICA.

Alterations in brain function in schizophrenia and other neuropsychiatric disorders are evident not only during specific cognitive challenges, but also from functional MRI data obtained during a resting state. Here we apply probabilistic independent component analysis (pICA) to resting state fMRI series in 25 schizophrenia patients and 25 matched healthy controls. We use an automated algorithm to extract the ICA component representing the default mode network (DMN) as defined by a DMN-specific set of 14 brain regions, resulting in z-scores for each voxel of the (whole-brain) statistical map. While goodness of fit was found to be similar between the groups, the region of interest (ROI) as well as voxel-wise analysis of the DMN showed significant differences between groups. Healthy controls revealed stronger effects of pICA-derived connectivity measures in right and left dorsolateral prefrontal cortices, bilateral medial frontal cortex, left precuneus and left posterior lateral parietal cortex, while stronger effects in schizophrenia patients were found in the right amygdala, left orbitofrontal cortex, right anterior cingulate and bilateral inferior temporal cortices. In patients, we also found an inverse correlation of negative symptoms with right anterior prefrontal cortex activity at rest and negative symptoms. These findings suggest that aberrant default mode network connectivity contributes to regional functional pathology in schizophrenia and bears significance for core symptoms.