Overlap between individual differences in cognition and symptoms of schizophrenia.

BACKGROUND: Neurocognitive impairment is a core feature of schizophrenia spectrum disorders (SSDs), and the relationship between cognition and symptoms in SSDs has been widely researched. Negative symptoms are related to a wide range of cognitive impairments; however, the aspects of negative symptoms that underpin this relationship have yet to be specified. STUDY DESIGN: We used iterative Constrained Principal Component Analysis (iCPCA) to explore the relationship between 18 cognitive measures (including processing speed, attention, working, spatial and verbal memory and executive functions) and 46 symptoms in schizophrenia at the individual item level while minimizing the risk of Type I errors. ICPCA was conducted on a sample of SSD patients in the early stages of psychiatric treatment (n = 121) to determine the components of cognition overlapping with symptoms measured by the Scale for the Assessment of Negative Symptoms (SANS) and the Scale for the Assessment of Positive Symptoms (SAPS). RESULTS: We found that a verbal memory component was associated with items from SANS and SAPS related to impoverished and disorganized emotional communication, language, and thought. In contrast, a working memory component was associated with SANS items related to motor system impoverishment. CONCLUSIONS: The iCPCA allowed us to explore the associations between individual items, optimized to understand the overlap between symptoms and cognition. The specific symptoms linked to verbal and working memory impairments imply distinct brain networks, which further investigation may lead to our deeper understanding of the illness and the development of treatment methods.

Reduced Functional Connectivity in Brain Networks Underlying Paired Associates Memory Encoding in Schizophrenia.

BACKGROUND: Deficits in relational episodic memory encoding are characteristic of schizophrenia (SZ), but whole-brain multivariate analyses of these deficits have been lacking. Open science has provided task-based functional magnetic resonance imaging (fMRI) data investigating paired associate encoding in SZ, but it has not yet been mobilized to address this gap in the literature. Therefore, in this study, we use previously unpublished task fMRI data to conduct the first network-level investigation of impaired relational episodic encoding in SZ. METHODS: Using fMRI data acquired from 40 healthy control participants and 40 age- and sex-matched persons with SZ, we examined the networks involved in successful versus unsuccessful encoding of verbal paired associates using an associative semantic strategy. RESULTS: Constrained principal component analysis for fMRI revealed 3 distinct functional networks recruited during encoding: a responding network, a linguistic processing/attention network, and the default mode network. Relative to the healthy control group, the SZ group exhibited aberrant activity in all 3 networks during successful encoding; namely, hypoactivation in the linguistic processing/attention network, lower peak activation in the responding network, and weaker suppression in the default mode network. Independent of group effects, a pattern of stronger anticorrelating linguistic processing/attention-default mode network activity during successful encoding significantly predicted subsequent retrieval of paired associates. CONCLUSIONS: Together with previous observations of language network hypoactivation during controlled semantic processes, these results suggest that abnormalities in networks representing language and meaning may contribute to difficulties employing deep semantic strategies during relational episodic encoding in SZ.

Dimensions of beliefs without strong supporting evidence and reasons for holding them.

Beliefs without strong supporting evidence (BWSSE) are commonplace, such as religious beliefs and conspiracy theories. The goals of the current study were to identify dimensions of BWSSE in the general public and study how reasons for holding each dimension depend on the strength of the belief. Participants completed a BWSSE questionnaire online, and principal component analysis suggested that the questionnaire captured 6 dimensions of beliefs that range in strength: New Age Spiritual, Traditional Spiritual, Nonconformist, Science, Mythical, and Conspiracy Theory. Mixed-model analyses of variance showed that while high-strength believers in both New Age and Traditional Spiritual shifted their reasons-for-belief away from 'just believe' and towards personal experience, only Traditional Spiritual shifted away from 'just believe' to culture. In contrast, for Conspiracy Theory and Mythical, the dominant reason for belief was media, but for Conspiracy Theory only, there was a shift from media to education/personal research for high-strength believers. This demonstrates that although spiritual beliefs are strengthened by personal experience, conspiracy theory beliefs are strengthened by information gathering. Understanding the source of an existing belief is important for debiasing attempts to move people towards beliefs with strong supporting evidence, including greater acceptance of evidence provided by experts, a likely requirement for negotiating global humanitarian emergencies in the not-so-distant future. Statement of Relevance. Beliefs without strong supporting evidence (BWSSE) have been gaining attention in mainstream society; particularly, the sources of information that may contribute to their formation and resistance to correction. Understanding the source of an existing belief is important for debiasing attempts to move people towards beliefs with strong supporting evidence, including greater acceptance of evidence provided by experts, a likely requirement for negotiating global humanitarian emergencies in the not-so-distant future.

Tracking momentary fluctuations in human attention with a cognitive brain-machine interface.

Selective attention produces systematic effects on neural states. It is unclear whether, conversely, momentary fluctuations in neural states have behavioral significance for attention. We investigated this question in the human brain with a cognitive brain-machine interface (cBMI) for tracking electrophysiological steady-state visually evoked potentials (SSVEPs) in real-time. Discrimination accuracy (d') was significantly higher when target stimuli were triggered at high, versus low, SSVEP power states. Target and distractor SSVEP power was uncorrelated across the hemifields, and target d' was unaffected by distractor SSVEP power states. Next, we trained participants on an auditory neurofeedback paradigm to generate biased, cross-hemispheric competitive interactions between target and distractor SSVEPs. The strongest behavioral effects emerged when competitive SSVEP dynamics unfolded at a timescale corresponding to the deployment of endogenous attention. In sum, SSVEP power dynamics provide a reliable readout of attentional state, a result with critical implications for tracking and training human attention.

Functional brain networks underlying probabilistic reasoning and delusions in schizophrenia.

Delusions in schizophrenia are false beliefs that are assigned certainty and not afforded the scrutiny that normally gives rise to doubt, even under conditions of weak evidence. The goal of the current functional magnetic resonance imaging (fMRI) study is to identify the brain network(s) involved in gathering information under conditions of weak evidence, in people with schizophrenia experiencing delusions. fMRI activity during probabilistic reasoning in people with schizophrenia experiencing delusions (n = 29) compared to people with schizophrenia not experiencing delusions (n = 41) and healthy controls (n = 41) was observed when participants made judgments based on evidence that weakly or strongly matched (or mismatched) with the focal hypothesis. A brain network involved in visual attention was strongly elicited for conditions of weak evidence for healthy controls and patients not experiencing delusions, but this increase was absent for patients experiencing delusions. This suggests that the state associated with delusions manifests in fMRI as reduced activity in an early visual attentional process whereby weak evidence is incorrectly stamped as conclusive, manifestating as a feeling of fluency and misplaced certainty, short-circuiting the search for evidence, and providing a candidate neural process for 'seeding' delusions.

Real-Time Symptom Capture of Hallucinations in Schizophrenia with fMRI: Absence of Duration-Dependent Activity.

Background: While advances in the field of functional magnetic resonance imaging (fMRI) provide new opportunities to study brain networks underlying the experience of hallucinations in psychosis, there are methodological challenges unique to symptom-capture studies. Study Design: We extracted brain networks activated during hallucination-capture for schizophrenia patients when fMRI data collected from two sites was merged (combined N = 27). A multidimensional analysis technique was applied, which would allow separation of brain networks involved in the hallucinatory experience itself from those involved in the motor response of indicating the beginning and end of the perceived hallucinatory experience. To avoid reverse inference when attributing a function (e.g., a hallucination) to anatomical regions, it was required that longer hallucinatory experiences produce extended brain responses relative to shorter. Study Results: For radio-speech sound files, an auditory perception brain network emerged, and displayed speech-duration-dependent hemodynamic responses (HDRs). However, in the hallucination-capture blocks, no network showed hallucination-duration-dependent HDRs, but a retrieved network that was anatomically classified as motor response emerged. Conclusions: During symptom capture of hallucinations during fMRI, no HDR showed duration dependence, but a brain network anatomically matching the motor response network was retrieved. Previous reports on brain networks detected by fMRI during hallucination capture are reviewed in this context; namely, that the brain networks interpreted as involved in hallucinations may in fact be involved only in the motor response indicating the onset of the hallucination.

Item-specific overlap between hallucinatory experiences and cognition in the general population: A three-step multivariate analysis of international multi-site data.

Hallucinatory experiences (HEs) can be pronounced in psychosis, but similar experiences also occur in nonclinical populations. Cognitive mechanisms hypothesized to underpin HEs include dysfunctional source monitoring, heightened signal detection, and impaired attentional processes. Using data from an international multisite study on non-clinical participants (N = 419), we described the overlap between two sets of variables - one measuring cognition and the other HEs - at the level of individual items. We used a three-step method to extract and examine item-specific signal, which is typically obscured when summary scores are analyzed using traditional methodologies. The three-step method involved: (1) constraining variance in cognition variables to that which is predictable from HE variables, followed by dimension reduction, (2) determining reliable HE items using split-halves and permutation tests, and (3) selecting cognition items for interpretation using a leave-one-out procedure followed by repetition of Steps 1 and 2. The results showed that the overlap between HEs and cognition variables can be conceptualized as bi-dimensional, with two distinct mechanisms emerging as candidates for separate pathways to the development of HEs: HEs involving perceptual distortions on one hand (including voices), underpinned by a low threshold for signal detection in cognition, and HEs involving sensory overload on the other hand, underpinned by reduced laterality in cognition. We propose that these two dimensions of HEs involving distortions/liberal signal detection, and sensation overload/reduced laterality may map onto psychosis-spectrum and dissociation-spectrum anomalous experiences, respectively.

Hallucination-Specific structure-function associations in schizophrenia.

Combining structural (sMRI) and functional magnetic resonance imaging (fMRI) data in schizophrenia patients with and without auditory hallucinations (9 SZ_AVH, 12 SZ_nAVH), 18 patients with bipolar disorder, and 22 healthy controls, we examined whether cortical thinning was associated with abnormal activity in functional brain networks associated with auditory hallucinations. Language-task fMRI data were combined with mean cortical thickness values from 148 brain regions in a constrained principal component analysis (CPCA) to identify brain structure-function associations predictable from group differences. Two components emerged from the multimodal analysis. The "AVH component" highlighted an association of frontotemporal and cingulate thinning with altered brain activity characteristic of hallucinations among patients with AVH. In contrast, the "Bipolar component" distinguished bipolar patients from healthy controls and linked increased activity in the language network with cortical thinning in the left occipital-temporal lobe. Our findings add to a body of evidence of the biological underpinnings of hallucinations and illustrate a method for multimodal data analysis of structure-function associations in psychiatric illness.