Cognition in at-risk mental states for psychosis

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ARTICLE IN PRESS

NBR-2265; No. of Pages 10

Neuroscience and Biobehavioral Reviews xxx (2015) xxx–xxx

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Neuroscience and Biobehavioral Reviews journal homepage: www.elsevier.com/locate/neubiorev

Review

Cognition in at-risk mental states for psychosis André Luiz Damião de Paula a,b , Jaime Eduardo Cecílio Hallak a,b , João Paulo Maia-de-Oliveira b,c , Rodrigo A. Bressan d , João Paulo Machado-de-Sousa a,b,∗ a

Department of Neuroscience and Behavior, Ribeirão Preto Medical School, University of São Paulo, Brazil National Institute for Translational Medicine, CNPq, Brazil Department of Clinical Medicine, Federal University of Rio Grande do Norte, Natal, Brazil d Federal University of São Paulo, São Paulo, Brazil b c

a r t i c l e

i n f o

Article history: Received 10 February 2015 Accepted 8 September 2015 Available online xxx Keywords: Schizophrenia Cognition Ultra high risk Early detection

a b s t r a c t Rationale: The devastating nature of schizophrenia and treatment limitations have triggered a search for early detection methods to enable interventions to be implemented as soon as the first signs and symptoms appear. In this effort, several studies have investigated the cognitive functions in individuals regarded as being in at-risk mental states (ARMS) for psychosis. Objective: Our aim was to make a systematic review of the literature regarding basic and social cognition in individuals in ARMS following the guidelines of the PRISMA statement. Results: In general, the results of the 49 articles included in the review show that individuals in ARMS have pervasive cognitive deficits that seem to be greater in individuals who later convert to psychosis. Conclusions: Cognitive impairment can be detected in individuals considered to be in ARMS according to current classifications and may serve as a risk marker for psychotic conversion; however, the lack of standardized criteria to define ARMS and of homogeneous cognitive assessment methods hamper the generalization of findings from different studies. © 2015 Elsevier Ltd. All rights reserved.

Contents 1. 2. 3.

4.

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 00 Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 00 2.1. Article search and selection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 00 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 00 3.1. Selected articles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 00 3.2. Samples . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 00 3.3. Instruments and criteria used for the early detection of psychosis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 00 3.4. Basic cognition in ARMS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 00 3.5. Social cognition in ARMS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 00 3.6. Cognitive performance of samples in studies without a control group . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 00 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 00 4.1. Basic cognition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 00 4.2. Social cognition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 00 4.3. Basic cognition and risk of conversion to psychosis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 00 4.4. Social cognition and risk of conversion to psychosis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 00 4.5. Cognition and early (EPS) and late (LPS) states . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 00 4.6. General methodological issues in research on cognition and ARMS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 00 4.7. Ethical aspects: potential issues in the early detection and treatment of psychosis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 00 4.8. Future perspectives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 00

∗ Corresponding author at: Hospital das Clínicas da Faculdade de Medicina de Ribeirão Preto – USP, Av. Bandeirantes, 3900, Monte Alegre, Ribeirão Preto, SP, CEP 14048-900, Brazil. E-mail address: [email protected] (J.P. Machado-de-Sousa). http://dx.doi.org/10.1016/j.neubiorev.2015.09.006 0149-7634/© 2015 Elsevier Ltd. All rights reserved.

Please cite this article in press as: de Paula, A.L.D., et al., Cognition in at-risk mental states for psychosis. Neurosci. Biobehav. Rev. (2015), http://dx.doi.org/10.1016/j.neubiorev.2015.09.006

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5.

Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 00 Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 00 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 00

1. Introduction Schizophrenia is a severe psychiatric disorder characterized by the presence of positive (hallucinations, delusions), negative (apathy, anhedonia, social withdrawal, etc.), and cognitive symptoms. In respect to cognition, research has shown that the most affected domains are memory, attention, executive functions, language, and intelligence (Fioravanti et al., 2012). Similar impairments are also found in social cognition, affecting the capacity to recognize facial expressions of emotion (Marwick and Hall, 2008; Kohler et al., 2010) and to infer the mental state of others (Brüne, 2005; Sprong et al., 2007), abilities that are central to successful interpersonal relationships (Adolphs, 1999; Frith and Frith, 2007). Evidence suggests that these deficits would be a core feature of schizophrenia directly related to the decline in social functioning seen in patients (Addington and Addington, 1999; Couture et al., 2006; Jabben et al., 2010). Despite significant progress in the comprehension of the pathological mechanisms underlying schizophrenia, the full picture of its etiology remains elusive. Current pharmacological treatments have important limitations, since although the drugs available have partial success in the control of positive symptoms, little is achieved in what regards negative and cognitive symptoms (Keefe et al., 2007). The first signs and symptoms of schizophrenia usually appear between the end of adolescence and beginning of early adulthood, with a later onset in women (África and Schwartz, 1995). The disorder has a chronic course with successive psychotic episodes that generally lead to deterioration in cognitive and social functioning (Andreasen, 2000; África and Schwartz, 1995; Mueser and McGurk, 2004; Schultz and Andreasen, 1999) and treatment resistance tends to appear over time. Together, these characteristics point to possible degenerative processes, which would also be associated with progressive cognitive decline (Pukrop et al., 2006). Because of the suffering of patients and their relatives and the huge social and economic burden of schizophrenia (Wu et al., 2005), the recognition and early treatment of the disorder are a highly relevant focus of research, and it seems plausible that pharmacological and non-pharmacological interventions implemented soon after the appearance of the first signs and symptoms could minimize cognitive deficits and symptom severity and even prevent the onset of frank psychosis, hence improving the social functioning and quality of life of affected individuals. As a result of the burden described, several research groups around the globe have been working to develop methods for the early detection of psychosis (Gross et al., 1987; Hafner et al., 2004; Klosterkötter et al., 2001; McGlashan et al., 2001; Miller et al., 2003; Yung and McGorry, 1996) and proposed a number of instruments and classifications for the assessment and definition of at-risk mental states. The Personal Assessment and Crisis Evaluation clinic (PACE; Yung and McGorry, 1996) in Australia was the first service specifically focused on the treatment and study of individuals considered to be at risk for psychosis. PACE uses the classification of “ultrahigh-risk” (UHR) for psychosis and created an instrument called Comprehensive Assessment of At-Risk Mental States (CAARMS; Yung et al., 2005) with the specific purpose of detecting psychosis early. The CAARMS is a semi-structured clinical interview consisting of three groups of criteria to screen for signs and symptoms of psychosis. Individuals that fulfill the criteria of one or more of the

groups are classified as being at risk of developing psychotic disorders. Group 1 is called “attenuated psychotic symptoms”, group 2 is called “brief Limited Intermittent Psychotic Symptoms and group 3 is called “trait and state risk factors”. The observation that the severity of cognitive impairment is directly associated with the social functioning level of schizophrenia patients suggests that cognition could act as a physiopathological marker of the disorder. This view is supported by reports that cognitive impairments may be present even before the occurrence of a full-blown psychotic episode, although in attenuated form (Lencz et al., 2006). Knowledge about the severity and specificities of cognitive impairments could enable the construction of more accurate algorithms to predict conversion to psychosis, in addition to providing new targets for treatment and prevention strategies. The investigation of cognitive functioning in ARMS individuals could also provide important data regarding vulnerability factors in psychosis and thus contribute to elucidate the physiopathological mechanisms of schizophrenia. Here, we made a systematic review of the literature available regarding basic and social cognition in individuals considered to be at risk for the development of psychosis. Specifically, we describe and discuss the methods used for the assessment of cognitive function in ARMS individuals and the relationship between cognitive impairment, rates of conversion to psychosis, and severity of psychotic disorders. 2. Methods 2.1. Article search and selection The following combinations of search terms were used to seek for relevant articles to the subject of this review: cognit*, prodrome, (psychosis or schizophrenia); cognit*, ultra high risk, (psychosis or schizophrenia) and cognit*, “early psychosis”. The databases searched were PubMed, PsycINFO, LILACS and SciELO. We included articles that assessed basic and/or social cognitive functions in ARMS individuals, written in Portuguese, English, Spanish or French and published until June 3, 2013. Articles describing studies that involved only groups of subjects with confirmed diagnoses of psychotic disorders, review articles, letters to the editor, case reports and pharmacological trials were not included in the review. 3. Results 3.1. Selected articles A search in the PubMed yielded 300 matches, 38 of which fulfilled our inclusion criteria. The search engine PsycINFO returned 292 references, of which three were selected. One article was found via SciELO, which found 8 matches, and the search in the LILACS database returned no matches for the search terms used. Forty-two articles were selected through the databases searched and another seven were included from the reference lists of the former, adding to the total of 49 articles reviewed after the application of the inclusion and exclusion criteria. The articles included were published between 2002 and 2013 and described studies performed in the United States (n = 12),

Please cite this article in press as: de Paula, A.L.D., et al., Cognition in at-risk mental states for psychosis. Neurosci. Biobehav. Rev. (2015), http://dx.doi.org/10.1016/j.neubiorev.2015.09.006

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Australia (n = 7), Germany (n = 6), Switzerland (n = 5), South Korea (n = 5), England (n = 4), The Netherlands (n = 3), France (n = 2), Canada (n = 2), Ireland (n = 1), Austria (n = 1), and Argentina (n = 1). 3.2. Samples The 49 studies reviewed included a total of 2024 men and 1515 women. The mean number of male participants was 41.2 (range = 7–153; SD = 35.52; median = 27) and the mean number of females was 30.91 (range = 3–172; SD = 32.4; median = 19), with great variations in sample sizes as indicated by the large standard deviations from the means. Sixteen studies included groups of first-episode psychosis (FEP) patients besides individuals in ARMS, with a total of 412 men and 204 women. The mean number of males in FEP groups was 25.75 (range = 5–67; SD = 17.7; median = 23) and the mean number of females was 12.75 (range = 3–34; SD = 7.68; median = 11). Finally, the 41 studies that included control groups for comparison enrolled a total of 2102 healthy subjects, with 1136 men and 966 women. The mean number of healthy male subjects in control samples was 27.7 (range = 5–96; SD = 19.83; median = 22) and the mean number of females was 23.56 (range = 3–116; SD = 24.96; median = 16). 3.3. Instruments and criteria used for the early detection of psychosis To define the status of ARMS in their samples, the studies included in the review used a number of different methods, described in detail below. - Comprehensive Assessment of At-Risk Mental States (CAARMS; Yung et al., 2005): the CAARMS is semi-structured interview consisting of sub-scales that assess typical signs and symptoms of psychosis. Respondents are classified in three groups according to the presence and frequency of symptoms. Group 1 receives the name of ‘attenuated psychotic symptoms’ and includes ideas of reference, strange beliefs, magical thinking, perceptual alterations and paranoid ideation. Symptoms occur at least once a week and changes in mental state should not be present for more than five years. Group 2 is named ‘brief limited psychotic symptoms’ and includes the same symptoms described in Group 1, with the difference that they cannot last for more than one week, have spontaneous remission, and have occurred over the previous year. Group 3 is called ‘trait and state risk factors’ and includes the following criteria: first-degree relative with a diagnosis of psychotic disorder or schizotypal personality disorder and significant impairment in social functioning as assessed with the Global Assessment of Functioning (GAF; American Psychiatric Association, 1994), lasting for at least one month and no more than five years. Twenty-one of the articles included in this review used the CAARMS to classify subjects in ARMS groups. - Structured Interview for Prodromal Symptoms (SIPS; McGlashan et al., 2001; Miller et al., 2003): the SIPS contemplates the same three groups of signs and symptoms as the CAARMS, with small differences namely (1) attenuated positive symptoms (APS); (2) brief, limited, or intermittent psychotic symptoms (BLIPS; a brief psychotic episode of less than 1 week’s duration that spontaneously remits without antipsychotic medication); (3) a 30% reduction in overall level of social, occupational/school, and psychological functioning (i.e., global assessment of functioning [GAF; American Psychiatric Association, 1994]) in the past year, combined with a genetic risk of psychosis. The SIPS was also used in 21 studies included in this review.

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- Recognition Inventory/Interview for the Retrospective Assessment of the Onset of Schizophrenia (RIRAOS; Hafner et al., 2004): four of the studies reviewed subdivided their samples of individuals in ARMS into groups in ‘early prodomal stage’ and ‘late prodromal stage’ using the RIRAOS. The definition of early prodromal stage is based on the Scale for the Assessment of Basic Symptoms (SABS; Gross et al., 1987). The SABS contemplates basic psychotic manifestations in the categories of thought interference, perseveration and blocking, language disturbances, decreased capacity to differentiate between ideas and perceptions, fantasies and false memories, ideas of reference, derealization, and perceptual disturbances. These symptoms should be present over the previous three months, several times a week. The definition of basic symptoms also includes a decrease of at least 30% in social functioning, concomitant or not with the symptoms described, as assessed with the GAF over the previous year, besides the following risk factors: first-degree relative with a diagnosis of schizophrenia or other psychotic disorders and pre- or peri-natal complications. The definition of ‘late prodromal stage’ follows the criteria adopted for groups 1 and 2 of the CAARMS. - Scale for the Assessment of Basic Symptoms (SABS; Gross et al., 1987): three studies classified their ARMS participants as having “basic symptoms” using the SABS criteria. The criteria for the classification of basic symptoms of the instrument have been described in the previous item. - Schizophrenia Prediction Instrument – Adult Version (SPI-A; Klosterkötter et al., 2001): one study classified their participants in ARMS as having basic symptoms using the SPI-A, which covers thought interference and blocking, language disorders, derealization, perception disorders, visual and hearing disorders and reference ideas. 3.4. Basic cognition in ARMS Twenty-four studies included in the review compared ARMS individuals and healthy controls using tasks that assess basic cognitive functions. In all studies, the performance of ARMS individuals to be significantly worse than that of healthy participants. Table 1 shows the domains of basic cognition assessed in each investigation, groups compared and a summary of their main results. As shown in the table, 14 studies included samples of patients with first-episode psychosis (FEP) in addition to groups of ARMS individuals. The results of nine of these investigations show the performance of FEP patients to be significantly impaired in comparison with both healthy volunteers and individuals in ARMS, whose cognitive performance was intermediate between the FEP and control groups (Eastvold et al., 2007; Hambrecht et al., 2002; Jahshan et al., 2010; Keefe et al., 2006; Kim et al., 2011b; Mirzakhanian et al., 2013; Pukrop et al., 2006; Simon et al., 2007; Jhung et al., 2013). In addition to individuals with FEP and ARMS, one investigation also included patients with multiple psychotic episodes (MPE), who presented the most severe cognitive impairments, followed by individuals with FEP and ARMS (Pukrop et al., 2006). The five remaining studies involving samples of individuals with FEP and ARMS found no significant differences between these two groups, although cognitive performance worse than that of healthy volunteers (Francey et al., 2005; Simon et al., 2012; Wilquin and Delevoye-Turrell, 2012; Thompson et al., 2012). The only exception was the study of Silverstein et al., 2006 that revealed no differences between the experimental groups and healthy volunteers. 3.5. Social cognition in ARMS Ten studies assessed cognitive functions related to the processing of information from the social and interpersonal environment, grouped here under the general term ‘social

Please cite this article in press as: de Paula, A.L.D., et al., Cognition in at-risk mental states for psychosis. Neurosci. Biobehav. Rev. (2015), http://dx.doi.org/10.1016/j.neubiorev.2015.09.006

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Table 1 Summary of the results of studies assessing the performance of individuals in ARMS, healthy controls and related experimental groups in basic cognitive tasks. Reference

Experimental groups (F/M)

Control group (F/M)

Domains assessed

Main results

Becker et al. (2010)

24 UHR-NCP (8/16) 17 UHR-CP (4/13)

17 (8/9)

Brewer et al. (2005)

64 UHR-NCP (28/36) 34 UHR-CP (19/15)

37 (9/28)

Chung et al. (2008)

33 UHR (14/19)

36 (16/20)

↓ Verbal memory UHR who converted to psychosis showed no major impairment ↓ Intelligence and verbal memory Only between UHR-CP ↓ Executive functions and working memory

Frommann et al. (2011)

116 EPS (40/76) 89 LPS (36/53)

87 (38/49)

Fusar-Poli et al. (2010) Gschwandtner et al. (2006)

15 ARMS (7/8) 40 AR (20/20)

15 (6/9) 42 (20/22)

Hurlemann et al. (2008)

20 EPS (8/12) 16 LPS (8/8)

30 (7/23)

Attention, executive functions, verbal and visuospatial memory, verbal fluency, motor speed and intelligence Attention, executive functions, intelligence, verbal memory and learning Attention, executive functions, intelligence, working memory, visual memory, learning and processing speed Attention, executive functions, intelligence, verbal fluency, processing, memory and verbal learning Intelligence and working memory Working memory, intelligence, attention and executive functions Episodic memory

Hur et al. (2012)

24 UHR + OCS (10/14) 41 UHR-OCS (15/26)

40 (15/25)

Kelleher et al. (2013)

14 PS (3/11)

153 (78/74)

Kim et al. (2011)

36 UHR-NCP (15/21) 13 UHR-CP (4/9)

45 (17/28)

Lencz et al. (2006)

38 CHR (16/22)

39 (15/24)

Lin et al. (2013)

UHR (172/153)

66 (27/39)

Magaud et al. (2010)

77 UHR (26/51)

61 (26/40)

Myles-Worsley et al. (2007)

98 GHR (52/46)

212 GLR (116/96)

Pflueger et al. (2007)

60 ARMS (26/34)

51 (23/28)

Pukrop et al. (2007)

39 IPS-NP (14/25) 44 IPS-P (12/32)

44 (31/13)

Schulze et al. (2012)

22 ARMS-CP (7/15) 25 ARMS-NCP (13/12) 34 DC (20/14)

76 (37/39)

Seidman et al. (2010)

167 CHR (60/107) 49 FHR (26/23)

109 (61/48)

Processing speed, verbal fluency, executive functions, visual and learning memory

Serrani (2011)

27 UHR (5/22)

38 (7/31)

Smith et al. (2006)

15 CHR (7/8)

15 (6/9)

Roiser et al. (2012)

18 UHR (11/7)

18 (8/10)

van Rijn et al. (2011a,b) Wood et al. (2003)

36 UHR (11/25) 38 UHR (19/19)

23 (10/13) 49 (17/32)

Wood et al. (2007)

7 UHR-CP (2/5) 9 UHR-NCP (4/5)

17 (3/14)

Attention, working memory, visual and verbal learning and visuospatial memory Intelligence and visuospatial working memory Intelligence, working memory, processing speed, visuospatial memory and intelligence Inhibitory control Working memory, short term memory and intelligence Executive functions, intelligence, attention, learning, and visual memory

Attention, intelligence, executive functions, verbal fluency, verbal memory and visual learning Attention, working memory, processing speed, verbal fluency, learning and executive functions Executive functions, visual memory, learning, processing speed, working memory and verbal memory

Verbal memory, working memory, executive functions, verbal fluency, attention, language, visuospatial processing and intelligence Intelligence, visual memory, verbal and learning memory, attention and verbal fluency Semantic and phonological verbal fluency Visuospatial memory, working memory and attention Intelligence, executive functions, working memory and attention Attention, working memory, visual and learning memory, processing speed, executive functions, verbal fluency and intelligence Attention, working memory, executive functions and intelligence

↓↓ LPS ↓ EPS All domains ↓ Working memory ↓ Sustained attention and working memory ↓ Episodic memory Hippocampal reduction correlated with impairment in episodic memory in the LPS group ↓ Attention and visual learning Only in the UHR-OC group ↓ Processing speed and working memory ↓↓ Executive functions, working memory, verbal memory and visual memory in the UHR-CP ↓ Same cognitive domains in UHR-NCP ↓ All domains More pronounced memory impairment in the group who converted to psychosis ↓ Verbal and learning memory, processing speed and attention ↓ Semantic verbal fluency ↓ Working memory, immediate logical memory and attention in the GHR group ↓ All domains ↓ All domains Worse performance in the IPS-P group ↓ Working memory and executive functions Both ARMS groups. No difference between them ↓ All domains Impairments more pronounced between CHR subjects who converted to psychosis ↓ Working memory and visual and verbal learning ↓ Visuospatial working memory ↓ Visuospatial memory and processing speed ↓ Inhibitory control ↓ Working memory ↓ Visual memory and attention Specific decline in the UHR-CP group on follow up

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Table 1 (Continued) Reference

Experimental groups (F/M)

Control group (F/M)

Domains assessed

Main results

Eastvold et al. (2007)

40 AR (19/21); 15 FEP (7/8)

36 (17/19)

↓ All domains ↓↓ FEP ↓ AR

Hambrecht et al. (2002)

29 PS (7/22); 29 FEP (7/22)

29 (7/22)

Processing speed, working memory, episodic memory, executive functions and intelligence Attention, working memory, visual and verbal memory, visual memory, verbal fluency and executive functions

Jahshan et al. (2010)

46 AR (19/27); 18 FEP (3/15)

29 (15/14)

Executive functions, verbal learning, working memory and intelligence

Keefe et al. (2006)

37 AR (17/20); 59 FEP (10/49)

47 (19/28)

Kim et al. (2011)

27 UHR (13/14); 25 FEP (12/13)

33 (17/16)

Mirzakhanian et al. (2013)

109 AR (46/63); 90 FEP (23/67)

102 (55/47)

Verbal fluency, attention, verbal memory and learning, working memory and processing speed Executive functions, verbal memory, visual memory, working memory, attention and intelligence Sustained attention

Pukrop et al. (2006)

EIPS (12/26) LIPS (35/65) FEP (34/52) MEP (27/61)

179 (99/80)

Intelligence, attention, working memory, verbal and learning memory, visual memory and executive functions

Simon et al. (2007)

69 UHR (29/40); 24 BS (9/15); 43 FEP (13/30)

49 (10/39)

Working memory, intelligence, executive functions, processing speed, attention and verbal working memory

Thompson et al. (2012)

30 UHR (16/14); 40 FEP (15/25)

30 (18/12)

Visual and verbal working memory and intelligence

Francey et al. (2005)

70 UHR (33/37); 32 FEP (8/24)

51 (32/19)

Attention

Silverstein et al. (2006)

70 UHR (24/46); 54 FEP (20/34) AD (4/9) 73 UHR (29/44); 26 BS (9/17); 48 FEP (16/32)

24 (6/18)

Perceptual organization and intelligence

49 (10/39)

Intelligence, working memory, processing speed, verbal fluency, executive functions, verbal and learning memory and attention

Wilquin and Delevoye-Turrell (2012)

15 UHR (8/7); 17 FEP (8/9)

36 (23/13)

Jhung et al. (2013)

13 UHR (4/9) 12 FEP (7/5)

13 (8/5)

Executive functions, working memory, short term memory and processing speed Working memory

Simon et al. (2012)

↓ Attention, verbal fluency, verbal memory and visual memory ↓↓ FEP ↓ PS ↓ Working memory and processing speed ↓↓ FEP ↓ AR Cognitive deterioration in AR group who converted to psychosis ↓↓ All domains ↓↓ FEP ↓↓ AR ↓ All domains ↓↓ FEP ↓ AR ↓ More severe impairment in AR group who converted to psychosis ↓ All domains ↓↓↓↓ MEP ↓↓↓ FEP ↓↓ LIPS: impairments only in verbal memory and attention ↓ EIPS impairments only in verbal memory ↓ Working memory, verbal memory, verbal fluency and processing speed ↓↓↓ FEP ↓↓ UHR ↓ BS There were no significant differences between the UHR and FEP groups ↓ ↓ FEP ↓ Deficits in attention did not predict transition to psychosis in UHR group There were no significant differences between groups ↓ FEP ↓ UHR In the baseline ↓ FEP ↓ UHR-NR In the follow-up No significant differences between the UHR-R and controls in the follow-up ↓ All domains ↓ FEP ↓ UHR ↓ FEP

UHR = ultra high risk; UHR-NCP = ultra high risk not converted to psychosis; UHR-CP = ultra high risk converted to psychosis; UHR + OCS = ultra high risk with obsessive compulsive symptoms; UHR-OCS = ultra high risk without obsessive compulsive symptoms; UHR-R = ultra high risk remitted; UHR-NR = ultra high risk not remitted; ARMS = at risk mental states; AR = at risk; ARMS-CP = at risk mental states converted to psychosis; ARMS-NCP = at risk mental states not converted to psychosis; CHR = clinical high risk; FHR = family high risk; BS = basic symptoms; EPS = early prodromal state; LPS = late prodromal state; EIPS = early initial prodromal symptoms; LIPS = late initial prodromal symptoms; IPS-NP = initial prodromal symptoms not psychotic; IPS-P = initial prodromal symptoms psychotic; PS = prodromal symptoms; GHR = genetic high risk; GLR = genetic low risk; FEP = first episode of psychosis; MEP = multiple episodes of psychosis; AD = anxiety disorders; DC = depressive controls.

cognition’. Table 2 presents the main characteristics of these investigations. In all the studies included in this review, individuals in ARMS had a poor performance in social cognition tasks compared with healthy

volunteers. Four of these investigations also included FEP patients, with one describing greater impairment in FEP compared with ARMS (Kim et al., 2010) and three reporting no differences across groups (Amminger et al., 2012; Thompson et al., 2012; Wilquin and

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Table 2 Main characteristics and results of studies comparing the performance of individuals in ARMS, healthy controls and related experimental groups in social cognition tasks. Reference

Experimental groups (F/M)

Domains assessed

Main results

Chung et al. (2008) Kim et al. (2011)

33 UHR (14/19) 36 UHR-NCP (15/21) 13 UHR-CP (4/9) 27 UHR (5/22) 36 UHR (11/25) 34 UHR (11/23) 20 UHR (7/13) 18 FEP (9/9) 30 UHR (16/14) 40 FEP (15/25)

36 (16/20) 45 (17/28)

Theory of mind Theory of mind

38 (7/31) 23 (10/13) 21 (8/13) 20 (6/14)

Theory of mind Facial emotion recognition Emotional awareness Face recognition

30 (18/12)

Amminger et al. (2012)

79 UHR (53/26); 30 FEP (12/18)

30 (15/15)

Theory of mind, facial and vocal emotional recognition and social perception Facial and vocal emotional recognition

Wilquin and Delevoye-Turrell (2012)

15 UHR (8/7); 17 PEP (8/9)

36 (23/13)

(–) ↓↓ UHR-CP ↓ UHR-NCP ↓ ↓ ↓ ↓↓ FEP ↓ UHR ↓ All domains ↓ FEP ↓ UHR ↓ All domains ↓ FEP ↓ UHR ↓ FEP ↓ UHR

Serrani (2011) van Rijn et al. (2011a,b) van Rijn et al. (2011a,b) Kim et al. (2010) Thompson et al. (2012)

Control group (F/M)

Sense of agency

UHR = ultra high risk; UHR-NCP = ultra high risk not converted to psychosis; UHR-CP = ultra high risk converted to psychosis; FEP = first episode of psychosis.

Delevoye-Turrell, 2012), although all were significantly impaired relative to controls. 3.6. Cognitive performance of samples in studies without a control group Eight of the studies reviewed had no control groups and used different strategies to compare the performance of their samples. Four of these compared the cognitive performance of individuals in ARMS with normative data and all described significantly inferior performance in basic cognition tasks (Hawkins et al., 2004; Niendam et al., 2006, 2007; Olvet et al., 2010). One longitudinal study (Barbato et al., 2013) divided their sample in ARMS into a subgroup of subjects that converted to psychosis and another that remained stable. The results showed that subjects who later developed psychosis had significantly worse cognitive performance at baseline than subjects who did not convert. Another longitudinal investigation assessed cognitive performance and social functioning in ARMS and revealed that worse social functioning at baseline was associated with specific cognitive deficits involving memory, verbal learning, processing speed, attention, and verbal fluency (Lin et al., 2011). At last, one study divided its sample in ARMS into subgroups fulfilling criteria for early and late prodromal stages (EPS and LPS). The results showed that individuals classified as being in LPS had cognitive impairments compared with individuals in EPS, although the difference was not significant (Schultze-Lutter et al., 2007). Addington et al. (2012) assessed social cognition in ARMS in relation to individuals seeking for mental health assistance but who did not fulfill criteria for the ARMS classification. The authors reported that both groups had deficits in facial emotion recognition tasks relative to normative data, and that there were no differences between individuals in ARMS and seeking mental health assistance (Table 3).

2007), intelligence (Eastvold et al., 2007), semantic verbal fluency (Magaud et al., 2010) and attention (Pflueger et al., 2007). Furthermore, our analysis suggests that the cognitive deficits observed seem to worsen over time and with the onset of a frank psychotic disorder. Eight studies involving patients with an established diagnosis of schizophrenia showed that FEP patients have still greater deficits than those seen in ARMS in the domains of working memory (Eastvold et al., 2007), verbal memory (Hambrecht et al., 2002), visual memory (Kim et al., 2011), episodic memory (Eastvold et al., 2007), verbal fluency (Keefe et al., 2006), executive functions (Kim et al., 2011), intelligence (Pukrop et al., 2006), attention (Pukrop et al., 2006) and processing speed (Simon et al., 2007). In addition, one study involving patients with multiple psychotic episodes revealed that this group had the worst cognitive deterioration, followed by FEP patients and individuals in ARMS (Pukrop et al., 2006). These results lend support to the hypothesis underlying the studies reviewed; namely, that progressive cognitive decline precedes the onset of psychotic disorders and develops after the first episode of psychosis. Nevertheless, there is evidence that points in the opposite direction, with four recent investigations (Francey et al., 2005; Simon et al., 2007; Thompson et al., 2012; Wilquin and Delevoye-Turrell, 2012) reporting absence of differences between FEP patients and individuals in ARMS, although in the four studies these two groups had significant deficits compared with healthy volunteers. Silverstein et al. (2006) also failed to find differences between FEP and ARMS and, in this single case, the performance of these groups did not differ from that of healthy volunteers in assessments of perceptual organization, suggesting the preservation of this function. It should be noted that this study did not control for the and education of participants and, according to the authors, it had an important limitation related to possible biases in the selection of volunteers in ARMS, which could explain the absence of the deficit reported.

4. Discussion 4.2. Social cognition 4.1. Basic cognition This survey provided systematic evidence on the existence of basic cognition impairments in individuals in ARMS, since all 24 studies assessing basic cognition in this population revealed the presence of significant impairments in ARMS compared with healthy subjects in the following domains: working memory (Chung et al., 2008), verbal memory (Hambrecht et al., 2002), visual memory (Kim et al., 2011), episodic memory (Hurlemann et al., 2008), executive functions (Lencz et al., 2006), processing speed (Lin et al., 2013), visual and verbal learning (Pukrop et al.,

In addition to impaired basic cognition, the articles reviewed also described systematic social cognition deficits in ARMS. All the studies comparing social cognition in ARMS and healthy volunteers described significant deficits in subjects at risk for psychosis, affecting the domains of theory of mind (Chung et al., 2008; Serrani, 2011; Thompson et al., 2012), emotional management (van Rijn et al., 2011b), facial emotion recognition (Amminger et al., 2012; Kim et al., 2010; Thompson et al., 2012; van Rijn et al., 2011a), vocal emotion recognition (Amminger et al., 2012; Thompson et al., 2012) and sense of agency (Wilquin and Delevoye-Turrell, 2012).

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Table 3 Main characteristics and results of studies without a control group. Reference

Experimental groups (F/M)

Domains assessed

Main results

Hawkins et al. (2004)

36 HR (13/23)

HR group showed performance below that observed in normative data in all domains

Niendam et al. (2006)

45 UHR (16/29)

Niendam et al. (2007)

35 UHR (14/21)

Barbato et al. (2013)

151 CHR (66/85)

Lin et al. (2011)

41 UHR-PO (18/23) 189 UHR-GO (113/76)

Schultze-Lutter et al. (2007)

33 EPS (9/24) 69 LPS (25/44)

Addington et al. (2012)

171 CHR (73/98) 100 HS (44/56)

Intelligence, working memory, attention, processing speed, spatial perception, memory and executive functions Processing speed, reasoning and problem solving, visual learning and memory, verbal working memory and motor speed Processing speed, reasoning and problem solving, visual learning and memory, verbal learning and memory verbal working memory, and motor speed Verbal memory, verbal and spatial working memory, executive functions, verbal fluency, attention and processing speed Intelligence, verbal learning and memory, processing speed, verbal fluency, attention Attention, working memory, memory and learning, processing speed and executive functions Facial emotion recognition

Olvet et al. (2010)

24 CHR-CP (4/20) 8 CHR-CBP (3/5) 115 CHR-NC (39/76)

Intelligence attention and memory

↓ Speed processing, verbal learning and memory and motor speed

↓ Processing speed and motor speed at baseline Half of the UHR group maintained cognitive impairment in the follow-up

↓ Verbal memory, verbal and spatial working memory, verbal fluency, executive functions Only in the CHR group who converted to psychosis ↓ Verbal learning and memory, processing speed, attention, verbal fluency Only in the UHR-PO group LPS group had inferior performance to the EPS group in all domains, but the difference was not statistically significant ↓ Both groups compared to normative data There were no differences between the CHR and HS group ↓ All domains ↓↓ CHR-CP ↓ CHR-NC No differences between the groups CHR-CP and CHR-CBP

HR = high risk; UHR = ultra high risk; CHR = clinical high risk; UHR-PO = ultra high risk poor outcome; UHR-GO = ultra high risk good outcome; EPS = early prodromal state; LPS = late prodromal state; HS = help-seeking; CHR-CP = clinical high risk converted to psychosis; CHR-BP = clinical high risk converted to bipolar spectrum disorder; CHRNC = clinical high risk not converted to psychosis or bipolar spectrum disorder.

As seen in respect to basic cognition, social cognition impairment was greater in FEP than in ARMS (Kim et al., 2010), suggesting that social cognitive functioning also deteriorates with the progression of symptoms. Nonetheless, once again this interpretation should be considered with caution, since Amminger et al. (2012), and Wilquin and Delevoye-Turrell (2012) respectively assessed facial and vocal emotion recognition and sense of agency and found no significant differences between FEP and ARMS, although both groups had significantly worse performance compared with healthy volunteers in the two studies.

4.3. Basic cognition and risk of conversion to psychosis The results of the studies included in this review point to the existence of pervasive cognitive deficits in individuals in ARMS and the domains of basic cognition that proved especially affected and more strongly associated with the risk of conversion to psychosis were working memory (Kim et al., 2011), verbal memory (Lencz et al., 2006), executive function (Pukrop et al., 2007), and processing speed (Seidman et al., 2010). Furthermore, individuals in ARMS who later develop frank psychosis have still greater cognitive deficits than those that do not convert (Barbato et al., 2013; Brewer et al., 2005; Eastvold et al., 2007; Jahshan et al., 2010; Keefe et al., 2006; Kim et al., 2011a; Lencz et al., 2006; Pukrop et al., 2007; Seidman et al., 2010; Simon et al., 2012; Wood et al., 2007). This last remark is particularly relevant, as it suggests that comprehensive cognitive assessments may constitute a useful tool in the early detection of psychosis as they may help refine the classification of ARMS and the implementation of individually-tailored treatment strategies. Conversely, there is no consensus regarding the possibility of predicting the occurrence of psychosis based on cognitive functioning, since longitudinal studies (Niendam et al., 2007; Lin et al.,

2013) suggest that baseline cognitive deficits may not be good predictors of the risk of conversion. Also, Francey et al. (2005) showed that, despite the existence of sustained attention deficits in ARMS, there were no differences between subjects who converted to psychosis and those who did not, which led the authors to suggest that such deficits, although they may constitute a vulnerability factor, are insufficient for reliable predictions of the risk of conversion to psychosis. 4.4. Social cognition and risk of conversion to psychosis Discrepant findings have also been reported in respect to the prediction of conversion to psychosis based on assessments of social cognition. A longitudinal study by Kim et al. (2011) revealed that individuals in ARMS who later develop psychosis have greater deficits in theory of mind compared with those who did not convert, an observation that led the authors to conclude that “deficits in theory of mind could act as markers for the prediction of the development of psychosis”. However, Addington et al. (2012) found no significant differences between subjects who developed psychosis and those who did not in respect to the capacity to recognize facial emotion, although both subgroups had impaired performance compared with normative data. The authors of these studies suggest that social cognition deficits seem to indicate vulnerability for psychosis, but maybe do not constitute a marker that is able to predict the development of frank psychotic disorders. 4.5. Cognition and early (EPS) and late (LPS) states EPS is characterized by the presence of basic symptoms and/or reduction of at least 30% in social functioning according to the GAF

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(American Psychiatric Association, 1994) and pre- or peri-natal complications, whereas LPS is defined by the presence of attenuated psychotic symptoms and/or brief limited and intermittent psychotic symptoms (Yung et al., 2005). As the name suggests, individuals in LPS have more severe prodromal signs than subjects in EPS. Given that, the differentiation between the two states may be an efficient methodological strategy to assess the possible relationship between cognitive deficits and symptom severity. In fact, Pukrop et al. (2006) showed that individuals in both EPS and LPS had impairments in executive function and verbal memory; however, individuals in LPS also had impaired attention. In the same line, Fromman et al. (2010) reported that subjects in LPS had deficits in all cognitive domains assessed (working memory, verbal memory and learning, executive function and processing speed), whereas subjects in EPS had less severe deficits limited to the domains of executive function and processing speed. Furthermore, Schultze-Lutter et al. (2007) investigated subjective and objective aspects of cognition in individuals in EPS and LPS and observed that, once again, individuals in LPS had more pronounced cognitive deficits than individuals in EPS. Hurlemann et al. (2008) assessed volunteers in EPS and LPS with a task that assesses verbal learning and memory and measured hippocampal volume using magnetic resonance spectroscopy. Their results showed that both groups volume reduction in the hippocampus; however, this reduction correlated with impaired performance in the verbal learning and memory task in LPS individuals. This led the authors to suggest that reductions in hippocampal volume could be associated with increased risk of conversion to psychosis, highlighting the importance of investigations combining cognitive assessments and neuroimaging techniques to expand our comprehension of ARMS and refine this classification in order to make it clinically operational. 4.6. General methodological issues in research on cognition and ARMS An important finding that emerges from the global exam of the articles included in this review is the lack of standardized criteria and definition for the classification of ARMS, which hampers the constitution of homogeneous samples and may be a confounding factor in the comparative analysis of results available to date. This is made clear by the variety of instruments and classifications used in the studies reviewed and described above. Additionally, there is no specific neuropsychological battery to assess cognition in ARMS, which may contribute for the divergent findings described and hamper the systematization of results. Longitudinal studies are needed to investigate cognitive functioning over time and its possible relationship with symptoms and rates of conversion to psychosis. From the 49 articles included in this review, 16 used a longitudinal design. Although this number is not irrelevant, the mentioned limitations concerning the lack of standardized classifications of ARMS and of homogeneous methods of cognitive assessment also hinder the comparison of their results. Finally, eight studies did not include control groups in their comparisons, which hampers the contrast of their results with data from healthy populations. 4.7. Ethical aspects: potential issues in the early detection and treatment of psychosis Although we now have sufficient evidence to conclude that the early detection and treatment of psychosis are central measures in the search for the best possible management of psychotic disorders, this raises major ethical issues that have to be carefully dealt with in order to avoid potential damage to individuals classified as being in ARMS.

Most of the studies included in this review use the word ‘patients’ to describe volunteers classified as at-risk for the development of psychosis. The classification of individuals in ARMS as patients seems at least inadequate in the absence of a specific diagnosis and, especially in what concerns mental health, may give rise to stigmatizing feelings and attitudes in the community and the individual himself. It seems possible that the lack of adequate terms to refer to individuals in ARMS is a sign of still limited capacity to deal with the problem of the early stages of psychosis e the pressing need for substantial intellectual and financial investment in research in this field. Another important issue with ethical and technical implications refers to pharmacological interventions in ARMS. Since the available methodology to detect the early signs of psychosis is still limited and characterized by high rates of false positive and false negative results, treatments with pharmacological agents with high potential of adverse effects such as antipsychotics becomes a questionable strategy. Conversely, the early detection of individuals in ARMS will be of little use if we do not have efficient methods of intervention at this stage. As in the case of the classification criteria and nomenclature, this is a topic that requires substantial effort on the part of the academic community in the search for satisfactory answers. 4.8. Future perspectives The observations above suggest that future studies should seek to improve the methods used both in the early detection of psychosis and in the assessment of cognitive functions in ARMS. The lack of standardized criteria and classifications results in the enrollment of non-homogeneous samples and hampers the comparison of results, which favors the occurrence of divergent and contradictory data. Although this is already in course, future research in the field should contemplate the assessment of social cognition, since available evidence shows that basic functions subserving social cognition are impaired in ARMS and that the characterization of deficits in this domain may contribute to a more accurate classification of these cases. Ideally, methodological improvements should be accompanied by the employment of multiple investigation techniques, including structural and functional neuroimaging and genetic and biochemical markers. The combination of these techniques should enhance the early detection of psychosis, reducing rates of false positives and false negatives and fostering a better understanding of the physiopathology underlying psychotic disorders. Finally, there is a pressing need for studies assessing the efficacy of pharmacological and non-pharmacological interventions for individuals in ARMS, including cognitive stimulation, psychotherapy and psychosocial strategies. 5. Conclusions The survey of the articles included in this review supports the conclusion that there are pervasive basic and social cognition deficits in ARMS. The cognitive functioning of individuals that later converted to psychosis seems to be even more impaired than that of individuals who did not convert during the different follow-up periods in the studies reviewed, which suggests that cognition could be used as risk marker for the onset of full-blown psychotic disorders (Barbato et al., 2013; Brewer et al., 2005; Eastvold et al., 2007; Jahshan et al., 2010; Keefe et al., 2006; Kim et al., 2011a; Lencz et al., 2006; Pukrop et al., 2007; Seidman et al., 2010; Simon et al., 2012; Wood et al., 2007). There is consistent evidence that schizophrenia is associated

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with progressive cognitive decline beginning even before the first psychotic episode, since cognitive deficits are more pronounced in patients with diagnosed schizophrenia compared to first-episode patients and individuals in ARMS (Eastvold et al., 2007; Hambrecht et al., 2002; Jahshan et al., 2010; Keefe et al., 2006; Kim et al., 2011b; Mirzakhanian et al., 2013; Pukrop et al., 2006; Simon et al., 2007). Furthermore, individuals in later prodromal stages seem to have greater cognitive impairment compared with individuals in earlier prodromal stages, suggesting that the severity of pre-psychotic symptoms increases along with cognitive decline (Frommann et al., 2011; Hurlemann et al., 2008; Pukrop et al., 2006; Schultze-Lutter et al., 2007). The investigation of basic cognitive functions seems promising in the search for a better comprehension of psychosis since its early stages. The refinement of methods for the early detection of psychosis and the establishment of a common, specific neuropsychological assessment battery for individuals in ARMS could enable the development of accurate predictive algorithms for schizophrenia, besides informing the design of rehabilitation techniques aimed at reducing cognitive impairment and, thus, improving social functioning and the quality of life of individuals in ARMS and schizophrenia patients as well. Acknowledgements This study was supported by grants from the São Paulo Research Foundation (Process number 11/50740-5 – Projeto Cuca Legal) and the National Council of Technological and Scientific Development (CNPq – National Institute of Science and Technology – Translational Medicine). Mr. De Paula received a Master’s degree scholarship from Coordenac¸ão de Aperfeic¸oamento de Pessoal de Nível Superior (CAPES). References Addington, J., Addington, D., 1999. Neurocognitive and social functioning in schizophrenia. Schizophr. Bull. 25, 173–182. Addington, J., Piskulic, D., Perkins, D., Woods, S.W., Liu, L., Penn, D.L., 2012. Affect recognition in people at clinical high risk of psychosis. Schizophr. Res. 140, 87–92, http://dx.doi.org/10.1016/j.schres.2012.06.012. Adolphs, R., 1999. Social cognition and the human brain. Trends Cogn. Sci. 3, 469–479. África, B., Schwartz, S.R., 1995. Schizophrenic disorders. In: Goldman, H. (Ed.), Review of General Psychiatry. , fourth ed. Appleton & Lang, Norwalk, CT, pp. 214–245. American Psychiatric Association, 1994. Diagnostic and Statistical Manual of Mental Disorders, fourth ed. American Psychiatric Association, Washington, DC. Amminger, G.P., Schäfer, M.R., Klier, C.M., Schlögelhofer, M., Mossaheb, N., Thompson, A., Bechdolf, A., Allott, K., McGorry, P.D., Nelson, B., 2012. Facial and vocal affect perception in people at ultra-high risk of psychosis, first-episode schizophrenia and healthy controls. Early Interv. Psychiatry 6, 450–454, http:// dx.doi.org/10.1111/j.1751-7893.2012.00362.x. Andreasen, N.C., 2000. Schizophrenia: the fundamental questions. Brain Res. Rev. 31, 106–112, http://dx.doi.org/10.1016/S0165-0173(99)00027-2. Barbato, M., Colijn, M.A., Keefe, R.S.E., Perkins, D.O., Woods, S.W., Hawkins, K.A., Christensen, B.K., Addington, J., 2013. The course of cognitive functioning over six months in individuals at clinical high risk for psychosis. Psychiatry Res. 206, 195–199, http://dx.doi.org/10.1016/j.psychres.2012.10.013. Becker, H.E., Nieman, D.H., Wiltink, S., Dingemans, P.M., Fliert, J.R., Velthorst, E., Haan, L., Amelsvoort, T.A., Linszen, D.H., 2010. Neurocognitive functioning before and after the first psychotic episode: does psychosis result in cognitive deterioration? Psychol. Med. 40, 1599–1606, http://dx.doi.org/10.1017/ S0033291710000048. Brewer, W.J., Francey, S.M., Wood, S.J., Jackson, H.J., Pantelis, C., Phillips, L.J., Yung, A.R., Anderson, V.A., McGorry, P.D., 2005. Memory impairments identified in people at ultra-high risk for psychosis who later develop first-episode psychosis. Am. J. Psychiatry 162, 71–78, http://dx.doi.org/10.1176/appi.ajp. 162.1.71. Brüne, M., 2005. “Theory of mind” in schizophrenia: a review of the literature. Schizophr. Bull. 31 (January), 21–42, http://dx.doi.org/10.1093/schbul/sbi002. Chung, Y.S., Kang, D.H., Shin, N.Y., Yoo, S.Y., Kwon, J.S., 2008. Deficit of theory of mind in individuals at ultra-high-risk for schizophrenia. Schizophr. Res. 99, 111–118, http://dx.doi.org/10.1016/j.schres.2007.11.012.

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Please cite this article in press as: de Paula, A.L.D., et al., Cognition in at-risk mental states for psychosis. Neurosci. Biobehav. Rev. (2015), http://dx.doi.org/10.1016/j.neubiorev.2015.09.006