***TASK*** the task is to summarize an input biomedical literature in six sentences 
    ***INPUT*** the input is a biomedical literature 
    ***OUTPUT*** the output is the summary of an input biomedical literature in six sentences 
    ***DOCUMENTATION*** 
    ***EXAMPLES*** 
    Input: Medication management in schizophrenia is a lengthy process , as the lack of clinical response can only be confirmed after at least 4 weeks of antipsychotic treatment at a therapeutic dose . Thus , there is a clear need for the discovery of biomarkers that have the potential to accelerate the management of treatment . Using resting-state functional MRI , we examined the functional connectivity of the ventral tegmental area ( VTA ) , the origin of the mesocorticolimbic dopamine projections , in 21 healthy controls and 21 unmedicated patients with schizophrenia at baseline ( pre-treatment ) and after 1 week of treatment with the antipsychotic drug risperidone ( 1-week post-treatment ) . Group-level functional connectivity maps were obtained and group differences in connectivity were assessed on the groups ’ participant-level functional connectivity maps . We also examined the relationship between pre-treatment/1-week post-treatment functional connectivity and treatment response . Compared with controls , patients exhibited significantly reduced pre-treatment VTA/midbrain connectivity to multiple cortical and subcortical regions , including the dorsal anterior cingulate cortex ( dACC ) and thalamus . After 1 week of treatment , VTA/midbrain connectivity to bilateral regions of the thalamus was re-established . Pre-treatment VTA/midbrain connectivity strength to dACC was positively correlated with good response to a 6-week course of risperidone , whereas pre-treatment VTA/midbrain connectivity strength to the default mode network was negatively correlated . Our findings suggest that VTA/midbrain resting-state connectivity may be a useful biomarker for the prediction of treatment response OBJECTIVE Clinical response to antipsychotic drug treatment is highly variable , yet prognostic biomarkers are lacking . The authors recently demonstrated that successful antipsychotic drug treatment alters resting-state functional connectivity of the striatum . The goal of the present study was to test whether intrinsic striatal connectivity patterns provide prognostic information and can serve as a potential biomarker of treatment response to antipsychotic drugs . METHOD The authors used resting-state functional MRI ( fMRI ) to develop a prognostic index in a discovery cohort of 41 first-episode schizophrenia patients , then tested this index in an independent cohort of 40 newly hospitalized chronic patients with acute psychosis . In the discovery cohort , patients underwent  resting-state fMRI scanning at the initiation of r and omized controlled treatment with a second-generation antipsychotic . Whole-brain functional connectivity maps were generated for each subject from striatal seed regions . A stringent measure of clinical response was calculated that required sustained improvement over two consecutive study visits . Clinical response was entered into a survival analysis , and Cox regression was applied to the functional connectivity data . A striatal connectivity index was created , comprising functional connections of the striatum that predicted treatment response . This striatal connectivity index was tested on a generalizability cohort of patients with psychotic disorders who were hospitalized for an acute psychotic episode . RESULTS A total of 91 regions functionally connected with the striatum provided significant prognostic information . Connectivity in these regions was used to create a baseline striatal connectivity index that predicted response to antipsychotic treatment with high sensitivity and specificity in both the discovery and generalizability cohorts . CONCLUSIONS These results provide evidence that individual differences in striatal functional connectivity predict response to antipsychotic drug treatment in acutely psychotic patients . With further development , this has the potential to serve as a prognostic biomarker with clinical utility and to reduce the overall burden associated with psychotic illnesses IMPORTANCE Previous evidence has implicated corticostriatal abnormalities in the pathophysiology of psychosis . Although the striatum is the primary target of all efficacious antipsychotics , the relationship between its functional connectivity and symptomatic reduction remains unknown . OBJECTIVE To explore the longitudinal effect of treatment with second-generation antipsychotics on functional connectivity of the striatum during the resting state in patients experiencing a first episode of psychosis . DESIGN , SETTING , AND PARTICIPANTS This prospect i ve controlled study took place at a clinical research center and included 24 patients with first-episode psychosis and 24 healthy participants matched for age , sex , education , and h and edness . Medications were administered in a double-blind r and omized manner . INTERVENTIONS Patients were scanned at baseline and after 12 weeks of treatment with either risperidone or aripiprazole . Their symptoms were evaluated with the Brief Psychiatric Rating Scale at baseline and follow-up . Healthy participants were scanned twice within a 12-week interval . MAIN OUTCOMES AND MEASURES Functional connectivity of striatal regions was examined via functional magnetic resonance imaging using a seed-based approach . Changes in functional connectivity of these seeds were compared with reductions in ratings of psychotic symptoms . RESULTS Patients had a median exposure of 1 day to antipsychotic medication prior to being scanned ( mean [ SD ] = 4.5 [ 6.1 ] ) . Eleven patients were treated with  aripiprazole and 13 patients were treated with risperidone . As psychosis improved , we observed an increase in functional connectivity between striatal seed regions and the anterior cingulate , dorsolateral prefrontal cortex , and limbic regions such as the hippocampus and anterior insula ( P < .05 , corrected for multiple comparisons ) . Conversely , a negative relationship was observed between reduction in psychosis and functional connectivity of striatal regions with structures within the parietal lobe ( P < .05 , corrected for multiple comparisons ) . CONCLUSIONS AND RELEVANCE Our results indicated that corticostriatal functional dysconnectivity in psychosis is a state-dependent phenomenon . Increased functional connectivity of the striatum with prefrontal and limbic regions may be a biomarker for improvement in symptoms associated with antipsychotic treatment BACKGROUND The adaptability of the human brain to the constantly changing environment is reduced in patients with psychotic disorders , leading to impaired cognitive functions . Brain signal complexity , which may reflect adaptability , can be readily quantified via resting-state functional magnetic resonance imaging ( fMRI ) signals . We hypothesized that resting-state brain signal complexity is altered in psychotic disorders , and is correlated with cognitive impairment . METHODS We assessed 156 healthy controls ( HC ) and 330 prob and s , including 125 patients with psychotic bipolar disorder ( BP ) , 107 patients with schizophrenia ( SZ ) , 98 patients with schizoaffective disorder ( SAD ) and 230 of their unaffected first-degree relatives ( 76 BPR , 79 SADR , and 75 SZR ) from four sites of the Bipolar-Schizophrenia Network on Intermediate Phenotypes ( B-SNIP ) consortium . Using multi-scale entropy analysis , we determined whether patients and /or relatives had pathologic differences in complexity of resting-state fMRI signals toward regularity ( reduced entropy in all time scales ) , or toward uncorrelated r and omness ( increased entropy in fine time scales that decays as the time scale increases ) and how these complexity differences might be associated with cognitive impairment . RESULTS Compared to HC subjects , prob and groups showed either decreased complexity toward regularity or toward r and omness . SZ prob and s showed decreased complexity toward regular signal in hypothalamus , and BP prob and s in left inferior occipital , right pre central and left superior parietal regions , whereas no brain region with decreased complexity toward regularity was found in SAD prob and s. All prob and groups showed significantly increased brain signal r and omness in dorsal and ventral prefrontal cortex ( PFC ) , and unaffected relatives showed no complexity differences in PFC regions . SZ had the largest area of involvement in both dorsal and ventral PFC . BP and SAD prob and s shared increased brain signal r and omness in ventral medial PFC , BP and SZ prob and s shared increased brain signal r and omness in ventral lateral PFC , whereas SAD and SZ prob and s shared increased brain signal r and omness in dorsal medial PFC . Only SZ showed increased brain signal r and omness in dorsal lateral PFC . The increased brain signal r and omness in dorsal or ventral PFC was weakly associated with reduced cognitive performance in psychotic prob and s. CONCLUSION These observations support the loss of brain complexity hypothesis in psychotic prob and s. Furthermore , we found significant differences as well as overlaps of pathologic brain signal complexity between psychotic prob and s by DSM diagnoses , thus suggesting a biological approach to categorizing psychosis based on functional neuroimaging data Recently , independent component analysis ( ICA ) has been widely used in the analysis of brain imaging data . An important problem with most ICA algorithms is , however , that they are stochastic ; that is , their results may be somewhat different in different runs of the algorithm . Thus , the outputs of a single run of an ICA algorithm should be interpreted with some reserve , and further analysis of the algorithmic reliability of the components is needed . Moreover , as with any statistical method , the results are affected by the r and om sampling of the data , and some analysis of the statistical significance or reliability should be done as well . Here we present a method for assessing both the algorithmic and statistical reliability of estimated independent components . The method is based on running the ICA algorithm many times with slightly different conditions and visualizing the clustering structure of the obtained components in the signal space . In experiments with magnetoencephalographic ( MEG ) and functional magnetic resonance imaging ( fMRI ) data , the method was able to show that expected components are reliable ; furthermore , it pointed out components whose interpretation was not obvious but whose reliability should incite the experimenter to investigate the underlying technical or physical phenomena . The method is implemented in a software package called Icasso IMPORTANCE Increased glutamate levels in the right associative striatum have been described in patients during a first episode of psychosis . Whether this increase would persist after effective antipsychotic treatment is unknown . OBJECTIVES To compare the glutamate levels in  antipsychotic-naive patients with first-episode psychosis in the right associative striatum and right cerebellar cortex using proton magnetic resonance spectroscopy before and 4 weeks after antipsychotic treatment and to compare these results with normative data from sex-matched healthy control subjects . DESIGN , SETTING , AND PARTICIPANTS Before-after trial in an inpatient psychiatric research unit among 24 antipsychotic-naive patients with first-episode psychosis and 18 healthy controls matched for age , sex , h and edness , and cigarette smoking . INTERVENTIONS Participants underwent 2 proton magnetic resonance spectroscopy studies : patients were imaged at baseline and after 4 weeks of antipsychotic treatment , while controls were imaged at baseline and at 4 weeks after the baseline measurement . Patients were treated with oral risperidone ( open label ) for 4 weeks with dosages that were titrated on the basis of clinical judgment . MAIN OUTCOMES AND MEASURES Glutamate levels were estimated using LCModel ( version 6.2 - 1 T ) and were corrected for the cerebrospinal fluid proportion within the voxel . RESULTS Patients with first-episode psychosis had higher levels of glutamate in the associative striatum and the cerebellum during the antipsychotic-naive condition compared with controls . After clinical ly effective antipsychotic treatment , glutamate levels significantly decreased in the associative striatum , with no significant change in the cerebellum . No differences in glutamate levels were observed between groups at 4 weeks . CONCLUSIONS AND RELEVANCE Increased glutamate levels observed at baseline in patients with first-episode psychosis normalized after 4 weeks of clinical ly effective antipsychotic treatment . These results provide support for the hypothesis that improvement in clinical symptoms might be related to a decrease in glutamate levels 
    Output:
    
Structural neuroimaging studies suggest white matter integrity deficits that are consistent across the illnesses , while gray matter reductions appear more widespread in schizophrenia compared to bipolar disorder .
Spectroscopy studies in cortical gray matter report evidence of decreased neuronal integrity in both disorders .
Functional neuroimaging studies typically report similar functional architecture of brain networks in healthy controls and patients across the psychosis spectrum , but find differential extent of alterations in task related activation and resting state connectivity between illnesses .
The very limited imaging-genetic literature suggests a relationship between psychosis risk genes and brain structure , and possible gene by diagnosis interaction effects on functional imaging markers .