Auditory Oddball Responses Across the Schizophrenia-Bipolar Spectrum and Their Relationship to Cognitive and Clinical Features

Parker, David A.; Trotti, Rebekah; McDowell, Jennifer E.; Keedy, Sarah K.; Hill, S. Kristian; Gershon, Elliot S.; Ivleva, Elena I.; Pearlson, Godfrey D.; Keshavan, Matcheri S.; Tamminga, Carol A.; Clementz, Brett A.

doi:10.1176/appi.ajp.2021.20071043

Cited by 16 publications

(7 citation statements)

References 74 publications

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“…For example, one study reported that genes underlying dopamine function in the prefrontal cortex are similarly implicated in both schizophrenia and bipolar disorder (5). Parker et al (6) found that the neural similarities in both schizophrenia and bipolar disorder depends on severity of psychosis in bipolar disorder. Unlike bipolar patients without psychosis, bipolar disorder patients with psychosis tends to show similar EEG responses (particularly P50) to schizophrenia.…”

Section: Introductionmentioning

confidence: 99%

Pareidolia in Schizophrenia and Bipolar Disorder

Hamza

Kéri

Csigó³

et al. 2021

Front. Psychiatry

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While there are many studies on pareidolia in healthy individuals and patients with schizophrenia, to our knowledge, there are no prior studies on pareidolia in patients with bipolar disorder. Accordingly, in this study, we, for the first time, measured pareidolia in patients with bipolar disorder (N = 50), and compared that to patients with schizophrenia (N = 50) and healthy controls (N = 50). We have used (a) the scene test, which consists of 10 blurred images of natural scenes that was previously found to produce illusory face responses and (b) the noise test which had 32 black and white images consisting of visual noise and 8 images depicting human faces; participants indicated whether a face was present on these images and to point to the location where they saw the face. Illusory responses were defined as answers when observers falsely identified objects that were not on the images in the scene task (maximum illusory score: 10), and the number of noise images in which they reported the presence of a face (maximum illusory score: 32). Further, we also calculated the total pareidolia score for each task (the sum number of images with illusory responses in the scene and noise tests). The responses were scored by two independent raters with an excellent congruence (kappa > 0.9). Our results show that schizophrenia patients scored higher on pareidolia measures than both healthy controls and patients with bipolar disorder. Our findings are agreement with prior findings on more impaired cognitive processes in schizophrenia than in bipolar patients.

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Section: Introductionmentioning

confidence: 99%

Pareidolia in Schizophrenia and Bipolar Disorder

Hamza

Kéri

Csigó³

et al. 2021

Front. Psychiatry

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“…In this proof-of-concept study, we applied a fMRI adaptation of this tool, to examine our hypotheses and evaluate our methodological approach, which has wide applicability in other relevant populations ( Kendig, 2015 ). We consider that the TD process, and the study of the brain circuits involved betters our understanding of cognitive and perceptual processes in the healthy brain and in different neuropsychiatric conditions, especially in schizophrenia ( Andreasen et al, 1999 ; Davalos et al, 2011 ; Ortuño et al, 2011 ; Roy et al, 2012 ; Gómez et al, 2014 ; Alústiza et al, 2016 , 2018 ; Ciullo et al, 2016 ; Lošák et al, 2016 ; Parker et al, 2021 ; Todd et al, 2022 ).…”

Section: Discussionmentioning

confidence: 99%

Time discrimination and change detection could share a common brain network: findings of a task-based fMRI study

Goena,

Alústiza,

Vidal-Adroher

et al. 2023

Front. Psychol.

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IntroductionOver the past few years, several studies have described the brain activation pattern related to both time discrimination (TD) and change detection processes. We hypothesize that both processes share a common brain network which may play a significant role in more complex cognitive processes. The main goal of this proof-of-concept study is to describe the pattern of brain activity involved in TD and oddball detection (OD) paradigms, and in processes requiring higher cognitive effort.MethodsWe designed an experimental task, including an auditory test tool to assess TD and OD paradigms, which was conducted under functional magnetic resonance imaging (fMRI) in 14 healthy participants. We added a cognitive control component into both paradigms in our test tool. We used the general linear model (GLM) to analyze the individual fMRI data images and the random effects model for group inference.ResultsWe defined the areas of brain activation related to TD and OD paradigms. We performed a conjunction analysis of contrast TD (task > control) and OD (task > control) patterns, finding both similarities and significant differences between them.DiscussionWe conclude that change detection and other cognitive processes requiring an increase in cognitive effort require participation of overlapping functional and neuroanatomical components, suggesting the presence of a common time and change detection network. This is of particular relevance for future research on normal cognitive functioning in the healthy population, as well as for the study of cognitive impairment and clinical manifestations associated with various neuropsychiatric conditions such as schizophrenia.

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“…Participants completed comprehensive laboratory evaluations within a few weeks of their clinical assessments. Papers on the individual laboratory paradigms provide extensive data collection and analysis details [10,[21][22][23][24][25][26][27][28][29]. Details of biomarker quanti cation and numerical taxonomy procedures are in Clementz et al [8].…”

Section: Biomarker Panelmentioning

confidence: 99%

Differentiating Biomarker Features and Familial Characteristics of B-SNIP Psychosis Biotypes

Parker,

Trotti,

McDowell

et al. 2024

Preprint

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Idiopathic psychosis shows considerable biological heterogeneity across cases. B-SNIP used psychosis-relevant biomarkers to identity psychosis Biotypes, which will aid etiological and targeted treatment investigations. Psychosis probands from the B-SNIP consortium (n = 1907), their first-degree biological relatives (n = 705), and healthy participants (n = 895) completed a biomarker battery composed of cognition, saccades, and auditory EEG measurements. ERP quantifications were substantially modified from previous iterations of this approach. Multivariate integration reduced multiple biomarker outcomes to 11 “bio-factors”. Twenty-four different approaches indicated bio-factor data among probands were best distributed as three subgroups. Numerical taxonomy with k-means constructed psychosis Biotypes, and rand indices evaluated consistency of Biotype assignments. Psychosis subgroups, their non-psychotic first-degree relatives, and healthy individuals were compared across bio-factors. The three psychosis Biotypes differed significantly on all 11 bio-factors, especially prominent for general cognition, antisaccades, ERP magnitude, and intrinsic neural activity. Rand indices showed excellent consistency of clustering membership when samples included at least 1100 subjects. Canonical discriminant analysis described composite bio-factors that simplified group comparisons and captured neural dysregulation, neural vigor, and stimulus salience variates. Neural dysregulation captured Biotype-2, low neural vigor captured Biotype-1, and deviations of stimulus salience captured Biotype-3. First-degree relatives showed similar patterns as their Biotyped proband relatives on general cognition, antisaccades, ERP magnitudes, and intrinsic brain activity. Results extend previous efforts by the B-SNIP consortium to characterize biologically distinct psychosis Biotypes. They also show that at least 1100 observations are necessary to achieve consistent outcomes. First-degree relative data implicate specific bio-factor deviations to the subtype of their proband and may inform studies of genetic risk.

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Auditory Oddball Responses Across the Schizophrenia-Bipolar Spectrum and Their Relationship to Cognitive and Clinical Features

Cited by 16 publications

References 74 publications

Pareidolia in Schizophrenia and Bipolar Disorder

Pareidolia in Schizophrenia and Bipolar Disorder

Time discrimination and change detection could share a common brain network: findings of a task-based fMRI study

Differentiating Biomarker Features and Familial Characteristics of B-SNIP Psychosis Biotypes

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