Network dysfunction during associative learning in schizophrenia: Increased activation, but decreased connectivity: an fMRI study

The importance of covert memory consolidation in schizophrenia: Dysfunctional network profiles of the hippocampus and the dorsolateral prefrontal cortex

Altered brain network profiles in schizophrenia (SCZ) during memory consolidation are typically observed during task-active periods such as encoding or retrieval. However active processes are also sub served by covert periods of memory consolidation. These periods are active in that they allow memories to be recapitulated even in the absence of overt sensorimotor processing. It is plausible that regions central to memory formation like the dlPFC and the hippocampus, exert network signatures during covert periods. Are these signatures altered in patients? The question is clinically relevant because real world learning and memory is facilitated by covert processing, and may be impaired in schizophrenia. Here, we compared network signatures of the dlPFC and the hippocampus during covert periods of a learning and memory task. Because behavioral proficiency increased non-linearly, functional connectivity of the dlPFC and hippocampus [psychophysiological interaction (PPI)] was estimated for each of the Early (linear increases in performance) and Late (asymptotic performance) covert periods. During Early periods, we observed hypo-modulation by the hippocampus but hyper-modulation by dlPFC. Conversely, during Late periods, we observed hypo-modulation by both the dlPFC and the hippocampus. We stitch these results into a conceptual model of network deficits during covert periods of memory consolidation.

Learning without contingencies: A loss of synergy between memory and reward circuits in schizophrenia

Motivational deficits in schizophrenia may interact with foundational cognitive processes including learning and memory to induce impaired cognitive proficiency. If such a loss of synergy exists, it is likely to be underpinned by a loss of synchrony between the brains learning and reward sub-networks. Moreover, this loss should be observed even during tasks devoid of explicit reward contingencies given that such tasks are better models of real world performance than those with artificial contingencies. Here we applied undirected functional connectivity (uFC) analyses to fMRI data acquired while participants engaged in an associative learning task without contingencies or feedback. uFC was estimated and inter-group differences (between schizophrenia patients and controls, n = 54 total, n = 28 patients) were assessed within and between reward (VTA and NAcc) and learning/memory (Basal Ganglia, DPFC, Hippocampus, Parahippocampus, Occipital Lobe) sub-networks. The task paradigm itself alternated between Encoding, Consolidation, and Retrieval conditions, and uFC differences were quantified for each of the conditions. Significantly reduced uFC dominated the connectivity profiles of patients across all conditions. More pertinent to our motivations, these reductions were observed within and across classes of sub-networks (reward-related and learning/memory related). We suggest that disrupted functional connectivity between reward and learning sub-networks may drive many of the performance deficits that characterize schizophrenia. Thus, cognitive deficits in schizophrenia may in fact be underpinned by a loss of synergy between reward-sensitivity and cognitive processes.

The topology, stability, and instability of learning-induced brain network repertoires in schizophrenia

There is a paucity of graph theoretic methods applied to task-based data in schizophrenia (SCZ). Tasks are useful for modulating brain network dynamics, and topology. Understanding how changes in task conditions impact inter-group differences in topology can elucidate unstable network characteristics in SCZ. Here, in a group of patients and healthy controls (n = 59 total, 32 SCZ), we used an associative learning task with four distinct conditions (Memory Formation, Post-Encoding Consolidation, Memory Retrieval, and Post-Retrieval Consolidation) to induce network dynamics. From the acquired fMRI time series data, betweenness centrality (BC), a metric of a node's integrative value was used to summarize network topology in each condition. Patients showed (a) differences in BC across multiple nodes and conditions; (b) decreased BC in more integrative nodes, but increased BC in less integrative nodes; (c) discordant node ranks in each of the conditions; and (d) complex patterns of stability and instability of node ranks across conditions. These analyses reveal that task conditions induce highly variegated patterns of network dys-organization in SCZ. We suggest that the dys-connection syndrome that is schizophrenia, is a contextually evoked process, and that the tools of network neuroscience should be oriented toward elucidating the limits of this dys-connection.

Magnocellular and parvocellular contributions to brain network dysfunction during learning and memory: Implications for schizophrenia

Memory deficits are core features of schizophrenia, and a central aim in biological psychiatry is to identify the etiology of these deficits. Scrutiny is naturally focused on the dorsolateral prefrontal cortex and the hippocampal cortices, given these structures' roles in memory and learning. The fronto-hippocampal framework is valuable but restrictive. Network-based underpinnings of learning and memory are substantially diverse and include interactions between hetero-modal and early sensory networks. Thus, a loss of fidelity in sensory information may impact memorial and cognitive processing in higher-order brain sub-networks, becoming a sensory source for learning and memory deficits. In this overview, we suggest that impairments in magno- and parvo-cellular visual pathways result in degraded inputs to core learning and memory networks. The ascending cascade of aberrant neural events significantly contributes to learning and memory deficits in schizophrenia. We outline the network bases of these effects, and suggest that any network perspectives of dysfunction in schizophrenia must assess the impact of impaired perceptual contributions. Finally, we speculate on how this framework enriches the space of biomarkers and expands intervention strategies to ameliorate this prototypical disconnection syndrome.

Inefficient white matter activity in Schizophrenia evoked during intra and inter-hemispheric communication

Intensive cognitive tasks induce inefficient regional and network responses in schizophrenia (SCZ). fMRI-based studies have naturally focused on gray matter, but appropriately titrated visuo-motor integration tasks reliably activate inter- and intra-hemispheric white matter pathways. Such tasks can assess network inefficiency without demanding intensive cognitive effort. Here, we provide the first application of this framework to the study of white matter functional responses in SCZ. Event-related fMRI data were acquired from 28 patients (nine females, mean age 43.3, ±11.7) and 28 age- and gender-comparable controls (nine females, mean age 42.1 ± 10.1), using the Poffenberger paradigm, a rapid visual detection task used to induce intra- (ipsi-lateral visual and motor cortex) or inter-hemispheric (contra-lateral visual and motor cortex) transfer. fMRI data were pre- and post-processed to reliably isolate activations in white matter, using probabilistic tractography-based white matter tracts. For intra- and inter-hemispheric transfer conditions, SCZ evinced hyper-activations in longitudinal and transverse white matter tracts, with hyper-activation in sub-regions of the corpus callosum primarily observed during inter-hemispheric transfer. Evidence for the functional inefficiency of white matter was observed in conjunction with small (~50 ms) but significant increases in response times. Functional inefficiencies in SCZ are (1) observable in white matter, with the degree of inefficiency contextually related to task-conditions, and (2) are evoked by simple detection tasks without intense cognitive processing. These cumulative results while expanding our understanding of this dys-connection syndrome, also extend the search of biomarkers beyond the traditional realm of fMRI studies of gray matter.

From mathematics to medicine: A practical primer on topological data analysis (TDA) and the development of related analytic tools for the functional discovery of latent structure in fMRI data

fMRI is the preeminent method for collecting signals from the human brain in vivo, for using these signals in the service of functional discovery, and relating these discoveries to anatomical structure. Numerous computational and mathematical techniques have been deployed to extract information from the fMRI signal. Yet, the application of Topological Data Analyses (TDA) remain limited to certain sub-areas such as connectomics (that is, with summarized versions of fMRI data). While connectomics is a natural and important area of application of TDA, applications of TDA in the service of extracting structure from the (non-summarized) fMRI data itself are heretofore nonexistent. “Structure” within fMRI data is determined by dynamic fluctuations in spatially distributed signals over time, and TDA is well positioned to help researchers better characterize mass dynamics of the signal by rigorously capturing shape within it. To accurately motivate this idea, we a) survey an established method in TDA (“persistent homology”) to reveal and describe how complex structures can be extracted from data sets generally, and b) describe how persistent homology can be applied specifically to fMRI data. We provide explanations for some of the mathematical underpinnings of TDA (with expository figures), building ideas in the following sequence: a) fMRI researchers can and should use TDA to extract structure from their data; b) this extraction serves an important role in the endeavor of functional discovery, and c) TDA approaches can complement other established approaches toward fMRI analyses (for which we provide examples). We also provide detailed applications of TDA to fMRI data collected using established paradigms, and offer our software pipeline for readers interested in emulating our methods. This working overview is both an inter-disciplinary synthesis of ideas (to draw researchers in TDA and fMRI toward each other) and a detailed description of methods that can motivate collaborative research.

A Study of the Brain Network Connectivity in Visual-Word Pairing Associative Learning and Episodic Memory Reactivating Task

Episodic memory allows a person to recall and mentally reexperience specific episodes from one's personal past. Studies of episodic memory are of great significance for the diagnosis and the exploration of the mechanism of memory generation. Most of the current studies focus on certain brain regions and pay less attention to the interrelationship between multiple brain regions. To explore the interrelationship in the brain network, we use an open fMRI dataset to construct the brain functional connectivity and effective connectivity network. We establish a binary directed network of the memory when it is reactivated. The binary directed network shows that the occipital lobe and parietal lobe have the most causal connections. The number of edges starting from the superior parietal lobule is the highest, with 49 edges, and 31 of which are connected to the occipital cortex. This means that the interaction between the superior parietal lobule and the occipital lobe plays the most important role in episodic memory, and the superior parietal lobule plays a more causal role in causality. In addition, memory regions such as the precuneus and fusiform also have some edges. The results show that the posterior parietal cortex plays an important role of hub node in the episodic memory network. From the brain network model, more information can be obtained, which is conducive to exploring the brain's changing pattern in the whole memory process.

The Role of Zebrafish and Laboratory Rodents in Schizophrenia Research

Schizophrenia is a severe disorder characterized by positive, negative and cognitive symptoms, which are still not fully understood. The development of efficient antipsychotics requires animal models of a strong validity, therefore the aims of the article were to summarize the construct, face and predictive validity of schizophrenia models based on rodents and zebrafish, to compare the advantages and disadvantages of these models, and to propose future directions in schizophrenia modeling and indicate when it is reasonable to combine these models. The advantages of rodent models stem primarily from the high homology between rodent and human physiology, neurochemistry, brain morphology and circuitry. The advantages of zebrafish models stem in the high fecundity, fast development and transparency of the embryo. Disadvantages of both models originate in behavioral repertoires not allowing specific symptoms to be modeled, even when the models are combined. Especially modeling the verbal component of certain positive, negative and cognitive symptoms is currently impossible.

Disordered directional brain network interactions during learning dynamics in schizophrenia revealed by multivariate autoregressive models

Directional network interactions underpin normative brain function in key domains including associative learning. Schizophrenia (SCZ) is characterized by altered learning dynamics, yet dysfunctional directional functional connectivity (dFC) evoked during learning is rarely assessed. Here, nonlinear learning dynamics were induced using a paradigm alternating between conditions (Encoding and Retrieval). Evoked fMRI time series data were modeled using multivariate autoregressive (MVAR) models, to discover dysfunctional direction interactions between brain network constituents during learning stages (Early vs. Late), and conditions. A functionally derived subnetwork of coactivated (healthy controls [HC] ∩ SCZ] nodes was identified. MVAR models quantified directional interactions between pairs of nodes, and coefficients were evaluated for intergroup differences (HC ≠ SCZ). In exploratory analyses, we quantified statistical effects of neuroleptic dosage on performance and MVAR measures. During Early Encoding, SCZ showed reduced dFC within a frontal–hippocampal–fusiform network, though during Late Encoding reduced dFC was associated with pathways toward the dorsolateral prefrontal cortex (dlPFC). During Early Retrieval, SCZ showed increased dFC in pathways to and from the dorsal anterior cingulate cortex, though during Late Retrieval, patients showed increased dFC in pathways toward the dlPFC, but decreased dFC in pathways from the dlPFC. These discoveries constitute novel extensions of our understanding of task‐evoked dysconnection in schizophrenia and motivate understanding of the directional aspect of the dysconnection in schizophrenia. Disordered directionality should be investigated using computational psychiatric approaches that complement the MVAR method used in our work.

Cognition and Reward Circuits in Schizophrenia: Synergistic, Not Separate

Schizophrenia has been studied from the perspective of cognitive or reward-related impairments, yet it cannot be wholly related to one or the other process and their corresponding neural circuits. We posit a comprehensive circuit-based model proposing that dysfunctional interactions between the brain's cognitive and reward circuits underlie schizophrenia. The model is underpinned by how the relationship between glutamatergic and dopaminergic dysfunction in schizophrenia drives interactions between cognition and reward circuits. We argue that this interaction is synergistic: that is, deficits of cognition and reward processing interact, and this interaction is a core feature of schizophrenia. In adopting this position, we undertake a focused review of animal physiology and human clinical data, and in proposing this synergistic model, we highlight dopaminergic afferents from the ventral tegmental area to nucleus accumbens (mesolimbic circuit) and frontal cortex (mesocortical circuit). We then expand on the role of glutamatergic inputs to these dopamine circuits and dopaminergic modulation of critical excitatory pathways with attention given to the role of glutamatergic hippocampal outputs onto nucleus accumbens. Finally, we present evidence for how in schizophrenia, dysfunction in the mesolimbic and mesocortical circuits and their corresponding glutamatergic inputs gives rise to clinical and cognitive phenotypes and is associated with positive and negative symptom dimensions. The synthesis attempted here provides an impetus for a conceptual shift that links cognitive and motivational aspects of schizophrenia and that can lead to treatment approaches that seek to harmonize network interactions between the brain's cognition and reward circuits with ameliorative effects in each behavioral domain.

Progress in iPSC-Based Modeling of Psychiatric Disorders

Progress in iPSC-based cellular systems provides new insights into human brain development and early neurodevelopmental deviations in psychiatric disorders. Among these, studies on schizophrenia (SCZ) take a prominent role owing to its high heritability and multifarious evidence that it evolves from a genetically induced vulnerability in brain development. Recent iPSC studies on patients with SCZ indicate that functional impairments of neural progenitor cells (NPCs) in monolayer culture extend to brain organoids by disrupting neocorticogenesis in an in vitro model. In addition, the formation of hippocampal circuit-like structures in vitro is impaired in patients with SCZ as is the case for glia development. Intriguingly, chimeric-mice experiments show altered oligodendrocyte and astrocyte development in vivo that highlights the importance of cell-cell interactions in the pathogenesis of early-onset SCZ. Likewise, cortical imbalances in excitatory-inhibitory signaling may result from a cell-autonomous defect in cortical interneuron (cIN) development. Overall, these findings indicate that genetic risk in SCZ impacts neocorticogenesis, hippocampal circuit formation, and the development of distinct glial and neuronal subtypes. In light of this remarkable progress, we discuss current limitations and further steps necessary to harvest the full potential of iPSC-based investigations on psychiatric disorders.

Cortical-hippocampal functional connectivity during covert consolidation sub-serves associative learning: Evidence for an active "rest" state

We studied modulation of undirected functional connectivity (uFC) in cortical-hippocampal sub-networks during associative learning. Nineteen healthy individuals were studied (fMRI acquired on a Siemens Verio 3T), and uFC was studied between nodes in a network of regions identified by standard activation models based on bivariate correlational analyses of time series data. The paradigm alternated between Memory Encoding, Rest and Retrieval. "Rest" intervals promoted covert consolidation. Over the task, performance was broadly separable into linear (Early) and asymptomatic (Late) regimes, with late performance reflecting successful memory consolidation. Significant modulation of uFC was observed during periods of covert consolidation. The sub-networks which were modulated constituted connections between frontal regions such as the dorsal prefrontal cortex (dPFC) and dorsal anterior cingulate cortex (dACC), the medial temporal lobe (hippocampus, HPC), the superior parietal cortex (SPC) and the fusiform gyrus (FG). uFC patterns were dynamic in that sub-networks modulated during Early learning (dACC ↔ SPC, dACC ↔ FG, dPFC ↔ HPC) were not identical to those modulated during Late learning (dACC ↔ HPC, dPFC ↔ FG, FG ↔ SPC). Covert consolidation exerts systematic effects, and these results add to emerging evidence for the constructive role of the brain's "resting state" in potentiating action.

Attempts at memory control induce dysfunctional brain activation profiles in Generalized Anxiety Disorder: An exploratory fMRI study

Suppression of aversive memories through memory control has historically been proposed as a central psychological defense mechanism. Inability to suppress memories is considered a central psychological trait in several psychiatric disorders, including Generalized Anxiety Disorder (GAD). Yet, few studies have attempted the focused identification of dysfunctional brain activation profiles when patients with Generalized Anxiety Disorders attempt memory control. Using a well-characterized behavioral paradigm we studied brain activation profiles in a group of adult GAD patients and well-matched healthy controls (HC). Participants learned word-association pairs before imaging. During fMRI when presented with one word of the pair, they were instructed to either suppress memory of, or retrieve the paired word. Subsequent behavioral testing indicated both GAD and HC were able to engage in the task, but attempts at memory control (suppression or retrieval) during fMRI revealed vastly different activation profiles. GAD were characterized by substantive hypo-activation signatures during both types of memory control, with effects particularly strong during suppression in brain regions including the dorsal anterior cingulate and the ventral prefrontal cortex. Attempts at memory control in GAD fail to engage brain regions to the same extent HC, providing a putative neuronal signature for a well-established psychological characteristic of the illness.

fNIRS can robustly measure brain activity during memory encoding and retrieval in healthy subjects

Early intervention in Alzheimer’s Disease (AD) requires novel biomarkers that can capture changes in brain activity at an early stage. Current AD biomarkers are expensive and/or invasive and therefore unsuitable for use as screening tools, but a non-invasive, inexpensive, easily accessible screening method could be useful in both clinical and research settings. Prior studies suggest that especially paired-associate learning tasks may be useful in detecting the earliest memory impairment in AD. Here, we investigated the utility of functional Near Infrared Spectroscopy in measuring brain activity from prefrontal, parietal and temporal cortices of healthy adults (n = 19) during memory encoding and retrieval under a face-name paired-associate learning task. Our findings demonstrate that encoding of novel face-name pairs compared to baseline as well as compared to repeated face-name pairs resulted in significant activation in left dorsolateral prefrontal cortex while recalling resulted in activation in dorsolateral prefrontal cortex bilaterally. Moreover, brain response to recalling was significantly higher than encoding in medial, superior and middle frontal cortices for novel faces. Overall, this study shows that fNIRS can reliably measure cortical brain activation during a face-name paired-associate learning task. Future work will include similar measurements in populations with progressing memory deficits.

Disrupted Working Memory Circuitry in Adolescent Psychosis

Individuals with schizophrenia (SZ) consistently show deficits in spatial working memory (WM) and associated atypical patterns of neural activity within key WM regions, including the dorsolateral prefrontal cortex (dlPFC) and parietal cortices. However, little research has focused on adolescent psychosis (AP) and potential age-associated disruptions of WM circuitry that may occur in youth with this severe form of illness. Here we utilized each subject's individual spatial WM capacity to investigate task-based neural dysfunction in 17 patients with AP (16.58 ± 2.60 years old) as compared to 17 typically developing, demographically comparable adolescents (18.07 ± 3.26 years old). AP patients showed lower behavioral performance at higher WM loads and lower overall WM capacity compared to healthy controls. Whole-brain activation analyses revealed greater bilateral precentral and right postcentral activity in controls relative to AP patients, when controlling for individual WM capacity. Seed-based psychophysiological interaction (PPI) analyses revealed significantly greater co-activation between the left dlPFC and left frontal pole in controls relative to AP patients. Significant group-by-age interactions were observed in both whole-brain and PPI analyses, with AP patients showing atypically greater neural activity and stronger coupling between WM task activated brain regions as a function of increasing age. Additionally, AP patients demonstrated positive relationships between right dlPFC neural activity and task performance, but unlike healthy controls, failed to show associations between neural activity and out-of-scanner neurocognitive performance. Collectively, these findings are consistent with atypical WM-related functioning and disrupted developmental processes in youth with AP.

Plasticity of prefrontal cortex connectivity in schizophrenia in response to antisaccade practice

People with schizophrenia exhibit difficulties in cognitive control that are often attributed to deficits in prefrontal cortex (PFC) circuitry. Practice paradigms have been used to improve these PFC-mediated deficits. The neural consequences of practice on task-based PFC activation have been addressed. Effects on task-based PFC connectivity, however, are largely unknown. We recruited people with schizophrenia and controls to practice antisaccades, a measure of PFC-mediated cognitive control that is disrupted in people with schizophrenia. Subjects performed antisaccades during functional magnetic resonance imaging (fMRI) before and after eight days of antisaccade practice. A group (schizophrenia, controls) × time (pre-, post-test) repeated measures ANOVA on the results of a psychophysiological interaction (PPI) analysis was used to evaluate changes in PFC connectivity; a similar model was used to evaluate changes in antisaccade behavior. After practice, antisaccade behavior improved and PFC connectivity with insular/temporal regions (involved in bottom-up orienting processes) increased in the schizophrenia group. The level of connectivity at post-test in the schizophrenia group was similar to that seen at pre-test in controls and positively correlated with antisaccade performance. Increases in connectivity between bottom-up and top-down regions may underlie behavioral improvements in people with schizophrenia after cognitive control practice.

Hyper-modulation of brain networks by the amygdala among women with Borderline Personality Disorder: Network signatures of affective interference during cognitive processing

Emotion dysregulation is a core characteristic of patients with Borderline Personality Disorder (BPD), and is often attributed to an imbalance in fronto-limbic network function. Hyperarousal of amygdala, especially in response to negative affective stimuli, results in affective interference with cognitive processing of executive functions. Clinical consequences include the impulsive-aggression, suicidal and self-injurious behaviors which characterize BPD. Dysfunctional interactions between amygdala and its network targets have not been well characterized during cognitive task performance. Using psychophysiological interaction analysis (PPI), we mapped network profiles of amygdala interaction with key regulatory regions during a Go No-Go task, modified to use negative, positive and neutral Ekman faces as targets. Fifty-six female subjects, 31 BPD and 25 healthy controls (HC), completed the affectively valenced Go No-Go task during fMRI scanning. In the negative affective condition, the amygdala exerted greater modulation of its targets in BPD compared to HC subjects in Rt. OFC, Rt. dACC, Rt. Parietal cortex, Rt. Basal Ganglia, and Rt. dlPFC. Across the spectrum of affective contrasts, hypermodulation in BPD subjects observed the following ordering: Negative > Neutral > Positive contrast. The amygdala seed exerted modulatory effects on specific target regions important in processing response inhibition and motor impulsiveness. The vulnerability of BPD subjects to affective interference with impulse control may be due to specific network dysfunction related to amygdala hyper-arousal and its effects on prefrontal regulatory regions such as the OFC and dACC.

Functional dynamics of hippocampal glutamate during associative learning assessed with in vivo 1H functional magnetic resonance spectroscopy

fMRI has provided vibrant characterization of regional and network responses associated with associative learning and memory; however, their relationship to functional neurochemistry is unclear. Here, we introduce a novel application of in vivo proton functional magnetic resonance spectroscopy (¹H fMRS) to investigate the dynamics of hippocampal glutamate during paired-associated learning and memory in healthy young adults. We show that the temporal dynamics of glutamate differed significantly during processes of memory consolidation and retrieval. Moreover, learning proficiency was predictive of the temporal dynamics of glutamate such that fast learners were characterized by a significant increase in glutamate levels early in learning, whereas this increase was only observed later in slow learners. The observed functional dynamics of glutamate provides a novel in vivo marker of brain function. Previously demonstrated N-methyl-D-aspartate (NMDA) receptor mediated synaptic plasticity during associative memory formation may be expressed in glutamate dynamics, which the novel application of ¹H MRS is sensitive to. The novel application of ¹H fMRS can provide highly innovative vistas for characterizing brain function in vivo, with significant implications for studying glutamatergic neurotransmission in health and disorders such as schizophrenia.

Practice and Learning: Spatiotemporal Differences in Thalamo-Cortical-Cerebellar Networks Engagement across Learning Phases in Schizophrenia

BACKGROUND

Understanding how practice mediates the transition of brain-behavior networks between early and later stages of learning is constrained by the common approach to analysis of fMRI data. Prior imaging studies have mostly relied on a single scan, and parametric, task-related analyses. Our experiment incorporates a multisession fMRI lexicon-learning experiment with multivariate, whole-brain analysis to further knowledge of the distributed networks supporting practice-related learning in schizophrenia (SZ).

METHODS

Participants with SZ were compared with healthy control (HC) participants as they learned a novel lexicon during two fMRI scans over a several day period. All participants were trained to equal task proficiency prior to scanning. Behavioral-Partial Least Squares, a multivariate analytic approach, was used to analyze the imaging data. Permutation testing was used to determine statistical significance and bootstrap resampling to determine the reliability of the findings.

RESULTS

With practice, HC participants transitioned to a brain-accuracy network incorporating dorsostriatal regions in late-learning stages. The SZ participants did not transition to this pattern despite comparable behavioral results. Instead, successful learners with SZ were differentiated primarily on the basis of greater engagement of perceptual and perceptual-integration brain regions.

CONCLUSION

There is a different spatiotemporal unfolding of brain-learning relationships in SZ. In SZ, given the same amount of practice, the movement from networks suggestive of effortful learning toward subcortically driven procedural one differs from HC participants. Learning performance in SZ is driven by varying levels of engagement in perceptual regions, which suggests perception itself is impaired and may impact downstream, "higher level" cognition.

Effects of ketamine on brain function during smooth pursuit eye movements

The uncompetitive NMDA receptor antagonist ketamine has been proposed to model symptoms of psychosis. Smooth pursuit eye movements (SPEM) are an established biomarker of schizophrenia. SPEM performance has been shown to be impaired in the schizophrenia spectrum and during ketamine administration in healthy volunteers. However, the neural mechanisms mediating SPEM impairments during ketamine administration are unknown. In a counter-balanced, placebo-controlled, double-blind, within-subjects design, 27 healthy participants received intravenous racemic ketamine (100 ng/mL target plasma concentration) on one of two assessment days and placebo (intravenous saline) on the other. Participants performed a block-design SPEM task during functional magnetic resonance imaging (fMRI) at 3 Tesla field strength. Self-ratings of psychosis-like experiences were obtained using the Psychotomimetic States Inventory (PSI). Ketamine administration induced psychosis-like symptoms, during ketamine infusion, participants showed increased ratings on the PSI dimensions cognitive disorganization, delusional thinking, perceptual distortion and mania. Ketamine led to robust deficits in SPEM performance, which were accompanied by reduced blood oxygen level dependent (BOLD) signal in the SPEM network including primary visual cortex, area V5 and the right frontal eye field (FEF), compared to placebo. A measure of connectivity with V5 and FEF as seed regions, however, was not significantly affected by ketamine. These results are similar to the deviations found in schizophrenia patients. Our findings support the role of glutamate dysfunction in impaired smooth pursuit performance and the use of ketamine as a pharmacological model of psychosis, especially when combined with oculomotor biomarkers. Hum Brain Mapp 37:4047-4060, 2016. © 2016 Wiley Periodicals, Inc.

Network Profiles of the Dorsal Anterior Cingulate and Dorsal Prefrontal Cortex in Schizophrenia During Hippocampal-Based Associative Memory

Schizophrenia is a disorder characterized by brain network dysfunction, particularly during behavioral tasks that depend on frontal and hippocampal mechanisms. Here, we investigated network profiles of the regions of the frontal cortex during memory encoding and retrieval, phases of processing essential to associative memory. Schizophrenia patients (n = 12) and healthy control (HC) subjects (n = 10) participated in an established object-location associative memory paradigm that drives frontal-hippocampal interactions. Network profiles were modeled of both the dorsal prefrontal (dPFC) and the dorsal anterior cingulate cortex (dACC) as seeds using psychophysiological interaction analyses, a robust framework for investigating seed-based connectivity in specific task contexts. The choice of seeds was motivated by previous evidence of involvement of these regions during associative memory. Differences between patients and controls were evaluated using second-level analyses of variance (ANOVA) with seed (dPFC vs. dACC), group (patients vs. controls), and memory process (encoding and retrieval) as factors. Patients showed a pattern of exaggerated modulation by each of the dACC and the dPFC during memory encoding and retrieval. Furthermore, group by memory process interactions were observed within regions of the hippocampus. In schizophrenia patients, relatively diminished modulation during encoding was associated with increased modulation during retrieval. These results suggest a pattern of complex dysfunctional network signatures of critical forebrain regions in schizophrenia. Evidence of dysfunctional frontal-medial temporal lobe network signatures in schizophrenia is consistent with the illness' characterization as a disconnection syndrome.

Inferring the Dysconnection Syndrome in Schizophrenia: Interpretational Considerations on Methods for the Network Analyses of fMRI Data

Schizophrenia has long been considered one of the most intractable psychiatric conditions. Its etiology is likely polygenic, and its symptoms are hypothesized to result from complex aberrations in network-level neuronal activity. While easily identifiable by psychiatrists based on clear behavioral signs, the biological substrate of the disease remains poorly understood. Here, we discuss current trends and key concepts in the theoretical framework surrounding schizophrenia and critically discuss network approaches applied to neuroimaging data that can illuminate the correlates of the illness. We first consider a theoretical framework encompassing basic principles of brain function ranging from neural units toward perspectives of network function. Next, we outline the strengths and limitations of several fMRI-based analytic methodologies for assessing in vivo brain network function, including undirected and directed functional connectivity and effective connectivity. The underlying assumptions of each approach for modeling fMRI data are treated in some quantitative detail, allowing for assessment of the utility of each for generating inferences about brain networks relevant to schizophrenia. fMRI and the analyses of fMRI signals provide a limited, yet vibrant platform from which to test specific hypotheses about brain network dysfunction in schizophrenia. Carefully considered and applied connectivity measures have the power to illuminate loss or change of function at the network level, thus providing insight into the underlying neurobiology which gives rise to the emergent symptoms seen in the altered cognition and behavior of schizophrenia patients.

Task-independent effects are potential confounders in longitudinal imaging studies of learning in schizophrenia

Learning impairment is a core deficit in schizophrenia that impacts on real-world functioning and yet, elucidating its underlying neural basis remains a challenge. A key issue when interpreting learning-task experiments is that task-independent changes may confound interpretation of task-related signal changes in neuroimaging studies. The nature of these task-independent changes in schizophrenia is unknown. Therefore, we examined task-independent “time effects” in a group of participants with schizophrenia contrasted with healthy participants in a longitudinal fMRI learning-experiment designed to allow for examination of non-specific effects of time. Flanking the learning portions of the experiment with a task-of-no-interest allowed us to extract task-independent BOLD changes. Task-independent effects occurred in both groups, but were more robust in the schizophrenia group. There was a significant interaction effect between group and time in a distributed activity pattern that included inferior and superior temporal regions, frontal areas (left anterior insula and superior medial gyri), and parietal areas (posterior cingulate cortices and precuneus). This pattern showed task-independent linear decrease in BOLD amplitude over the two scanning sessions for the schizophrenia group, but showed either opposite effect or no activity changes for the control group. There was a trend towards a correlation between task-independent effects and the presence of more negative symptoms in the schizophrenia group.

The strong interaction between group and time suggests that both the scanning experience as a whole and the transition between task-types evokes a different response in persons with schizophrenia and may confound interpretation of learning-related longitudinal imaging experiments if not explicitly considered.

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A robust method was used to identify task-independent fMRI BOLD changes in a multiday learning experiment in schizophrenia

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Task-independent effects were apparent in healthy control group and schizophrenia but differed in direction and magnitude

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In schizophrenia they were greater in magnitude and most prominent in areas of the salience and default mode networks

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Unless properly accounted for, these effects will compromise precise interpretation of fMRI learning data in schizophrenia.

Associations between polygenic risk for schizophrenia and brain function during probabilistic learning in healthy individuals

A substantial proportion of schizophrenia liability can be explained by additive genetic factors. Risk profile scores (RPS) directly index risk using a summated total of common risk variants weighted by their effect. Previous studies suggest that schizophrenia RPS predict alterations to neural networks that support working memory and verbal fluency. In this study, we apply schizophrenia RPS to fMRI data to elucidate the effects of polygenic risk on functional brain networks during a probabilistic‐learning neuroimaging paradigm. The neural networks recruited during this paradigm have previously been shown to be altered to unmedicated schizophrenia patients and relatives of schizophrenia patients, which may reflect genetic susceptibility. We created schizophrenia RPS using summary data from the Psychiatric Genetic Consortium (Schizophrenia Working Group) for 83 healthy individuals and explore associations between schizophrenia RPS and blood oxygen level dependency (BOLD) during periods of choice behavior (switch–stay) and reflection upon choice outcome (reward–punishment). We show that schizophrenia RPS is associated with alterations in the frontal pole (P_{WHOLE‐BRAIN‐CORRECTED} = 0.048) and the ventral striatum (P_{ROI‐CORRECTED} = 0.036), during choice behavior, but not choice outcome. We suggest that the common risk variants that increase susceptibility to schizophrenia can be associated with alterations in the neural circuitry that support the processing of changing reward contingencies. Hum Brain Mapp 37:491–500, 2016. © 2015 Wiley Periodicals, Inc.

Chronological age and its impact on associative learning proficiency and brain structure in middle adulthood

INTRODUCTION

The rate of biological change in middle-adulthood is relatively under-studied. Here, we used behavioral testing in conjunction with structural magnetic resonance imaging to examine the effects of chronological age on associative learning proficiency and on brain regions that previous functional MRI studies have closely related to the domain of associative learning.

METHODS

Participants (n=66) completed a previously established associative learning paradigm, and consented to be scanned using structural magnetic resonance imaging. Age-related effects were investigated both across sub-groups in the sample (younger vs. older) and across the entire sample (using regression approaches).

RESULTS

Chronological age had substantial effects on learning proficiency (independent of IQ and Education Level), with older adults showing a decrement compared to younger adults. In addition, decreases in estimated gray matter volume were observed in multiple brain regions including the hippocampus and the dorsal prefrontal cortex, both of which are strongly implicated in associative learning.

CONCLUSION

The results suggest that middle adulthood may be a more dynamic period of life-span change than previously believed. The conjunctive application of narrowly focused tasks, with conjointly acquired structural MRI data may allow us to enrich the search for, and the interpretation of, age-related changes in cross-sectional samples.

Transcription factor SP4 phosphorylation is altered in the postmortem cerebellum of bipolar disorder and schizophrenia subjects

Transcription factors play important roles in the control of neuronal function in physiological and pathological conditions. We previously reported reduced levels of transcription factor SP4 protein, but not transcript, in the cerebellum in bipolar disorder and associated with more severe negative symptoms in schizophrenia. We have recently reported phosphorylation of Sp4 at S770, which is regulated by membrane depolarization and NMDA receptor activity. The aim of this study was to investigate SP4 S770 phosphorylation in bipolar disorder and its association with negative symptoms in schizophrenia, and to explore the potential relationship between phosphorylation and protein abundance. Here we report a significant increase in SP4 phosphorylation in the cerebellum, but not the prefrontal cortex, of bipolar disorder subjects (n=10) (80% suicide) compared to matched controls (n=10). We found that SP4 phosphorylation inversely correlated with SP4 levels independently of disease status in both areas of the human brain. Moreover, SP4 phosphorylation in the cerebellum positively correlated with negative symptoms in schizophrenia subjects (n=15). Further, we observed that a phospho-mimetic mutation in truncated Sp4 was sufficient to significantly decrease Sp4 steady-state levels, while a non-phosphorylatable mutant showed increased stability in cultured rat cerebellar granule neurons. Our results indicate that SP4 S770 phosphorylation is increased in the cerebellum in bipolar disorder subjects that committed suicide and in severe schizophrenia subjects, and may be part of a degradation signal that controls Sp4 abundance in cerebellar granule neurons. This opens the possibility that modulation of SP4 phosphorylation may contribute to the molecular pathophysiology of psychotic disorders.

Affective context interferes with brain responses during cognitive processing in borderline personality disorder: fMRI evidence

Emotion dysregulation in borderline personality disorder (BPD) is associated with loss of cognitive control in the face of intense negative emotion. Negative emotional context may interfere with cognitive processing through the dysmodulation of brain regions involved in regulation of emotion, impulse control, executive function and memory. Structural and metabolic brain abnormalities have been reported in these regions in BPD. Using novel fMRI protocols, we investigated the neural basis of negative affective interference with cognitive processing targeting these regions. Attention-driven Go No-Go and X-CPT (continuous performance test) protocols, using positive, negative and neutral Ekman faces, targeted the orbital frontal cortex (OFC) and the anterior cingulate cortex (ACC), respectively. A stimulus-driven Episodic Memory task, using images from the International Affective Pictures System, targeted the hippocampus (HIP). Participants comprised 23 women with BPD, who were compared with 15 healthy controls. When Negative>Positive faces were compared in the Go No-Go task, BPD subjects had hyper-activation relative to controls in areas reflecting task-relevant processing: the superior parietal/precuneus and the basal ganglia. Decreased activation was also noted in the OFC, and increased activation in the amygdala (AMY). In the X-CPT, BPD subjects again showed hyper-activation in task-relevant areas: the superior parietal/precuneus and the ACC. In the stimulus-driven Episodic Memory task, BPD subjects had decreased activation relative to controls in the HIP, ACC, superior parietal/precuneus, and dorsal prefrontal cortex (dPFC) (for encoding), and the ACC, dPFC, and HIP for retrieval of Negative>Positive pictures, reflecting impairment of task-relevant functions. Negative affective interference with cognitive processing in BPD differs from that in healthy controls and is associated with functional abnormalities in brain networks reported to have structural or metabolic abnormalities. Task demands exert a differential effect on the cognitive response to negative emotion in BPD compared with control subjects.

Increased SP4 and SP1 transcription factor expression in the postmortem hippocampus of chronic schizophrenia

Altered levels of transcription factor specificity protein 4 (SP4) and 1 (SP1) in the cerebellum, prefrontal cortex and/or lymphocytes have been reported in severe psychiatric disorders, including early psychosis, bipolar disorder, and chronic schizophrenia subjects who have undergone long-term antipsychotic treatments. SP4 transgenic mice show altered hippocampal-dependent psychotic-like behaviours and altered development of hippocampal dentate gyrus. Moreover, NMDAR activity regulates SP4 function. The aim of this study was to investigate SP4 and SP1 expression levels in the hippocampus in schizophrenia, and the possible effect of antipsychotics and NMDAR blockade on SP protein levels in rodent hippocampus. We analysed SP4 and SP1 expression levels in the postmortem hippocampus of chronic schizophrenia (n = 14) and control (n = 11) subjects by immunoblot and quantitative RT-PCR. We tested the effect of NMDAR blockade on SP factors in the hippocampus of mouse treated with an acute dose of MK801. We also investigated the effect of subacute treatments with haloperidol and clozapine on SP protein levels in the rat hippocampus. We report that SP4 protein and both SP4 and SP1 mRNA expression levels are significantly increased in the hippocampus in chronic schizophrenia. Likewise, acute treatment with MK801 increased both SP4 and SP1 protein levels in mouse hippocampus. In contrast, subacute treatment with haloperidol and clozapine did not significantly alter SP protein levels in rat hippocampus. These results suggest that SP4 and SP1 upregulation may be part of the mechanisms deregulated downstream of glutamate signalling pathways in schizophrenia and might be contributing to the hippocampal-dependent cognitive deficits of the disorder.

Translational studies of goal-directed action as a framework for classifying deficits across psychiatric disorders

The ability to learn contingencies between actions and outcomes in a dynamic environment is critical for flexible, adaptive behavior. Goal-directed actions adapt to changes in action-outcome contingencies as well as to changes in the reward-value of the outcome. When networks involved in reward processing and contingency learning are maladaptive, this fundamental ability can be lost, with detrimental consequences for decision-making. Impaired decision-making is a core feature in a number of psychiatric disorders, ranging from depression to schizophrenia. The argument can be developed, therefore, that seemingly disparate symptoms across psychiatric disorders can be explained by dysfunction within common decision-making circuitry. From this perspective, gaining a better understanding of the neural processes involved in goal-directed action, will allow a comparison of deficits observed across traditional diagnostic boundaries within a unified theoretical framework. This review describes the key processes and neural circuits involved in goal-directed decision-making using evidence from animal studies and human neuroimaging. Select studies are discussed to outline what we currently know about causal judgments regarding actions and their consequences, action-related reward evaluation, and, most importantly, how these processes are integrated in goal-directed learning and performance. Finally, we look at how adaptive decision-making is impaired across a range of psychiatric disorders and how deepening our understanding of this circuitry may offer insights into phenotypes and more targeted interventions.