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 Therefore, in this study, we use previously unpublished task fMRI data to conduct the first network-level investigation of impaired relational episodic encoding in SZ.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.

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.

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.