Activation in or near the fusiform gyrus was estimated to faces and control stimuli. Activation peaked at 165 ms and was strongest to digitized photographs of human faces, regardless of whether they were presented in color or grayscale, suggesting that face- and color-specific areas are functionally separate. Schematic sketche evoked approximately 30% less activation than did face photographs. Scrambling the locations of facial features reduced the response by approximately 25% in either hemisphere, suggesting that configurational versus analytic processing is not lateralized at this latency. Animal faces evoked approximately 50% less activity, and common objects, animal bodies or sensory controls evoked approximately 80% less activity than human faces. The (small) responses evoked by meaningless control images were stronger when they included surfaces and shading, suggesting that the fusiform gyrus may use these features in constructing its face-specific response. Putative fusiform activation was not significantly related to stimulus repetition, gender or emotional expression. A midline occipital source significantly distinguished between faces and control images as early as 110 ms, but was more sensitive to sensory qualities. This source significantly distinguished happy and sad faces from those with neutral expressions. We conclude that the fusiform gyrus may selectively encode faces at 165 ms, transforming sensory input for further processing.

Distortion of the sense of reality, actualized in delusions and hallucinations, is the key feature of psychosis but the underlying neuronal correlates remain largely unknown. We studied 11 highly functioning subjects with schizophrenia or schizoaffective disorder while they rated the reality of auditory verbal hallucinations (AVH) during functional magnetic resonance imaging (fMRI). The subjective reality of AVH correlated strongly and specifically with the hallucination-related activation strength of the inferior frontal gyri (IFG), including the Broca's language region. Furthermore, how real the hallucination that subjects experienced was depended on the hallucination-related coupling between the IFG, the ventral striatum, the auditory cortex, the right posterior temporal lobe, and the cingulate cortex. Our findings suggest that the subjective reality of AVH is related to motor mechanisms of speech comprehension, with contributions from sensory and salience-detection-related brain regions as well as circuitries related to self-monitoring and the experience of agency.

Meaningful behavior requires successful differentiation of events surfacing from one's mind from those arising from the external world. Such judgements may be especially demanding during pain because of the strong contribution from psychological factors to this experience. It is unknown how the subjective reality of pain (SRP) is constructed in the human brain, and neuronal mechanisms of the subjective reality are poorly understood in general. To address these questions, 14 suggestion-prone healthy subjects rated reality of pain that was induced either by laser pulses to the skin or by hypnotic suggestion during functional MRI. Both pain states were associated with activation of the brain's pain circuitry. During laser stimulation, the sensory parts of this circuitry were activated more strongly, and their activation strengths correlated positively with the SRP. During suggestion-induced pain, the reality estimates were lower and correlated positively with activation strengths in the rostral and perigenual anterior cingulate cortex and in the pericingulate regions of the medial prefrontal cortex; a similar trend was evident during laser-induced pain. These findings support the view that information about sensorydiscriminative characteristics of pain contributes to the SRP. Differences in such information between physically and psychologically induced pain, however, could be quantitative rather than qualitative and therefore insufficient for judging the reality of pain without knowledge about the source of this information. The medial prefrontal cortex is a likely area to contribute to such source monitoring.functional MRI ͉ suggestion ͉ hypnosis ͉ human ͉ cortex E vents surfacing from one's mind are usually differentiated from those arising from the external world by the subjective experience of reality. Ability to differentiate real and imaginal percepts, however, can be distorted in patients suffering from various organic and functional brain disorders and occasionally even in healthy subjects (1-3).Brain correlates of pain are affected by various psychological factors (4-7). According to recent brain imaging studies, painrelated brain areas can be activated without any physical stimulus, solely by cognitive cues (7-9). It remains unknown, however, how real the subject's experiences of such a psychologically induced pain are, and how the subjective reality of pain (SRP) is constructed in the human brain. Because the clarity of a percept likely affects the experience of its reality, and because both real and hallucinatory percepts may be associated with activation of sensory brain areas (10, 11), we hypothesized that a neuronal system subserving the SRP should involve components that process pain-related sensory-discriminative information, i.e., the primary and secondary somatosensory cortices and the posterior insula (12, 13). We also expected this system to include brain regions such as the perigenual anterior cingulate cortex (pACC) (14) that are able to support source monitoring, because a failure to differ...

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The outcome of first-episode psychosis (FEP) is highly variable, ranging from early sustained recovery to antipsychotic treatment resistance from the onset of illness. For clinicians, a possibility to predict patient outcomes would be highly valuable for the selection of antipsychotic treatment and in tailoring psychosocial treatments and psychoeducation. This selective review summarizes current knowledge of prognostic markers in FEP. We sought potential outcome predictors from clinical and sociodemographic factors, cognition, brain imaging, genetics, and blood-based biomarkers, and we considered different outcomes, like remission, recovery, physical comorbidities, and suicide risk. Based on the review, it is currently possible to predict the future for FEP patients to some extent. Some clinical features—like the longer duration of untreated psychosis (DUP), poor premorbid adjustment, the insidious mode of onset, the greater severity of negative symptoms, comorbid substance use disorders (SUDs), a history of suicide attempts and suicidal ideation and having non-affective psychosis—are associated with a worse outcome. Of the social and demographic factors, male gender, social disadvantage, neighborhood deprivation, dysfunctional family environment, and ethnicity may be relevant. Treatment non-adherence is a substantial risk factor for relapse, but a small minority of patients with acute onset of FEP and early remission may benefit from antipsychotic discontinuation. Cognitive functioning is associated with functional outcomes. Brain imaging currently has limited utility as an outcome predictor, but this may change with methodological advancements. Polygenic risk scores (PRSs) might be useful as one component of a predictive tool, and pharmacogenetic testing is already available and valuable for patients who have problems in treatment response or with side effects. Most blood-based biomarkers need further validation. None of the currently available predictive markers has adequate sensitivity or specificity used alone. However, personalized treatment of FEP will need predictive tools. We discuss some methodologies, such as machine learning (ML), and tools that could lead to the improved prediction and clinical utility of different prognostic markers in FEP. Combination of different markers in ML models with a user friendly interface, or novel findings from e.g., molecular genetics or neuroimaging, may result in computer-assisted clinical applications in the near future.

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It may be challenging to distinguish autoimmune encephalitis associated with anti-neuronal autoantibodies from primary psychiatric disorders. Here, serum was drawn from patients with a first-episode psychosis (n=70) or a clinical high-risk for psychosis (n=6) and controls (n=34). We investigated the serum prevalence of 24 anti-neuronal autoantibodies: IgG antibodies for anti-N-methyl-d-aspartate-type glutamate receptor (anti-NMDAR), glutamate and γ-aminobutyric acid alpha and beta receptors (GABA-a, GABA-b), alpha-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor (AMPA), glycine receptor (GlyR), metabotropic glutamate receptor 1 and 5 (mGluR1, mGluR5), anti-Tr/Delta/notch-like epidermal growth factor-related receptor (DNER), contactin-associated protein-like 2 (CASPR2), myelin oligodendrocyte glycoprotein (MOG), glutamic acid decarboxylase-65 (GAD65), collapsin response mediator protein 5/crossveinless-2 (CV2), aquaporin-4 (AQP4), anti-dipeptidyl-peptidase-like protein-6 (DPPX), type 1 anti-neuronal nuclear antibody (ANNA-1, Hu), Ri, Yo, IgLON5, Ma2, zinc finger protein 4 (ZIC4), Rho GTPase-activating protein 26, amphiphysin, and recoverin, as well as IgA and IgM for dopamine-2-receptor (DRD2). Anti-NMDA IgG antibodies were positive with serum titer 1:320 in one patient with a clinical high risk for psychosis. He did not receive a diagnosis of encephalitis after comprehensive neurological evaluation. All other antineuronal autoantibodies were negative and there were no additional findings with immunohistochemistry of brain issues.