Identifying Game-Based Digital Biomarkers of Cognitive Risk for Adolescent Substance Misuse: Protocol for a Proof-of-Concept Study.

BACKGROUND: Adolescents at risk for substance misuse are rarely identified early due to existing barriers to screening that include the lack of time and privacy in clinic settings. Games can be used for screening and thus mitigate these barriers. Performance in a game is influenced by cognitive processes such as working memory and inhibitory control. Deficits in these cognitive processes can increase the risk of substance use. Further, substance misuse affects these cognitive processes and may influence game performance, captured by in-game metrics such as reaction time or time for task completion. Digital biomarkers are measures generated from digital tools that explain underlying health processes and can be used to predict, identify, and monitor health outcomes. As such, in-game performance metrics may represent digital biomarkers of cognitive processes that can offer an objective method for assessing underlying risk for substance misuse. OBJECTIVE: This is a protocol for a proof-of-concept study to investigate the utility of in-game performance metrics as digital biomarkers of cognitive processes implicated in the development of substance misuse. METHODS: This study has 2 aims. In aim 1, using previously collected data from 166 adolescents aged 11-14 years, we extracted in-game performance metrics from a video game and are using machine learning methods to determine whether these metrics predict substance misuse. The extraction of in-game performance metrics was guided by literature review of in-game performance metrics and gameplay guidebooks provided by the game developers. In aim 2, using data from a new sample of 30 adolescents playing the same video game, we will test if metrics identified in aim 1 correlate with cognitive processes. Our hypothesis is that in-game performance metrics that are predictive of substance misuse in aim 1 will correlate with poor cognitive function in our second sample. RESULTS: This study was funded by National Institute on Drug Abuse through the Center for Technology and Behavioral Health Pilot Core in May 2022. To date, we have extracted 285 in-game performance metrics. We obtained institutional review board approval on October 11, 2022. Data collection for aim 2 is ongoing and projected to end in February 2024. Currently, we have enrolled 12 participants. Data analysis for aim 2 will begin once data collection is completed. The results from both aims will be reported in a subsequent publication, expected to be published in late 2024. CONCLUSIONS: Screening adolescents for substance use is not consistently done due to barriers that include the lack of time. Using games that provide an objective measure to identify adolescents at risk for substance misuse can increase screening rates, early identification, and intervention. The results will inform the utility of in-game performance metrics as digital biomarkers for identifying adolescents at high risk for substance misuse. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/46990.

Individual differences in spatial working memory strategies differentially reflected in the engagement of control and default brain networks.

Spatial locations can be encoded and maintained in working memory using high-precision, fine-grained representations that are cognitively demanding, or coarse and less demanding categorical representations. In this study, we employed an individual differences approach to identify brain activity correlates of the use of fine-grained and categorical representations in spatial working memory. We combined data from six fMRI studies, resulting in a sample of 153 (77 women, 25 ± 6 years) healthy participants performing a spatial working memory task. Our results showed that individual differences in the use of spatial representations in working memory were associated with distinct patterns of brain activation, with fine-grained representations requiring greater engagement of attentional and control brain systems, while categorical representations were associated with decreased inhibition of the default network. These findings may indicate a greater need for ongoing maintenance and protection against interference for fine-grained compared to categorical representations.

The spatial extent of anatomical connections within the thalamus varies across the cortical hierarchy in humans and macaques.

Each cortical area has a distinct pattern of anatomical connections within the thalamus, a central subcortical structure composed of functionally and structurally distinct nuclei. Previous studies have suggested that certain cortical areas may have more extensive anatomical connections that target multiple thalamic nuclei, which potentially allows them to modulate distributed information flow. However, there is a lack of quantitative investigations into anatomical connectivity patterns within the thalamus. Consequently, it remains unknown if cortical areas exhibit systematic differences in the extent of their anatomical connections within the thalamus. To address this knowledge gap, we used diffusion magnetic resonance imaging (dMRI) to perform brain-wide probabilistic tractography for 828 healthy adults from the Human Connectome Project. We then developed a framework to quantify the spatial extent of each cortical area's anatomical connections within the thalamus. Additionally, we leveraged resting-state functional MRI, cortical myelin, and human neural gene expression data to test if the extent of anatomical connections within the thalamus varied along the cortical hierarchy. Our results revealed two distinct corticothalamic tractography motifs: 1) a sensorimotor cortical motif characterized by focal thalamic connections targeting posterolateral thalamus, associated with fast, feed-forward information flow; and 2) an associative cortical motif characterized by diffuse thalamic connections targeting anteromedial thalamus, associated with slow, feed-back information flow. These findings were consistent across human subjects and were also observed in macaques, indicating cross-species generalizability. Overall, our study demonstrates that sensorimotor and association cortical areas exhibit differences in the spatial extent of their anatomical connections within the thalamus, which may support functionally-distinct cortico-thalamic information flow.

Illness Phase as a Key Assessment and Intervention Window for Psychosis.

The phenotype of schizophrenia, regardless of etiology, represents the most studied psychotic disorder with respect to neurobiology and distinct phases of illness. The early phase of illness represents a unique opportunity to provide effective and individualized interventions that can alter illness trajectories. Developmental age and illness stage, including temporal variation in neurobiology, can be targeted to develop phase-specific clinical assessment, biomarkers, and interventions. We review an earlier model whereby an initial glutamate signaling deficit progresses through different phases of allostatic adaptation, moving from potentially reversible functional abnormalities associated with early psychosis and working memory dysfunction, and ending with difficult-to-reverse structural changes after chronic illness. We integrate this model with evidence of dopaminergic abnormalities, including cortical D1 dysfunction, which develop during adolescence. We discuss how this model and a focus on a potential critical window of intervention in the early stages of schizophrenia impact the approach to research design and clinical care. This impact includes stage-specific considerations for symptom assessment as well as genetic, cognitive, and neurophysiological biomarkers. We examine how phase-specific biomarkers of illness phase and brain development can be incorporated into current strategies for large-scale research and clinical programs implementing coordinated specialty care. We highlight working memory and D1 dysfunction as early treatment targets that can substantially affect functional outcome.

Reward and loss incentives improve spatial working memory by shaping trial-by-trial posterior frontoparietal signals.

Integrating motivational signals with cognition is critical for goal-directed activities. The mechanisms that link neural changes with motivated working memory continue to be understood. Here, we tested how externally cued and non-cued (internally represented) reward and loss impact spatial working memory precision and neural circuits in human subjects using fMRI. We translated the classic delayed-response spatial working memory paradigm from non-human primate studies to take advantage of a continuous numeric measure of working memory precision, and the wealth of translational neuroscience yielded by these studies. Our results demonstrated that both cued and non-cued reward and loss improved spatial working memory precision. Visual association regions of the posterior prefrontal and parietal cortices, specifically the precentral sulcus (PCS) and intraparietal sulcus (IPS), had increased BOLD signal during incentivized spatial working memory. A subset of these regions had trial-by-trial increases in BOLD signal that were associated with better working memory precision, suggesting that these regions may be critical for linking neural signals with motivated working memory. In contrast, regions straddling executive networks, including areas in the dorsolateral prefrontal cortex, anterior parietal cortex and cerebellum displayed decreased BOLD signal during incentivized working memory. While reward and loss similarly impacted working memory processes, they dissociated during feedback when money won or avoided in loss was given based on working memory performance. During feedback, the trial-by-trial amount and valence of reward/loss received was dissociated amongst regions such as the ventral striatum, habenula and periaqueductal gray. Overall, this work suggests motivated spatial working memory is supported by complex sensory processes, and that the IPS and PCS in the posterior frontoparietal cortices may be key regions for integrating motivational signals with spatial working memory precision.

Dopamine D1R Receptor Stimulation as a Mechanistic Pro-cognitive Target for Schizophrenia.

Decades of research have highlighted the importance of optimal stimulation of cortical dopaminergic receptors, particularly the D1R receptor (D1R), for prefrontal-mediated cognition. This mechanism is particularly relevant to the cognitive deficits in schizophrenia, given the abnormalities in cortical dopamine (DA) neurotransmission and in the expression of D1R. Despite the critical need for D1R-based therapeutics, many factors have complicated their development and prevented this important therapeutic target from being adequately interrogated. Challenges include determination of the optimal level of D1R stimulation needed to improve cognitive performance, especially when D1R expression levels, affinity states, DA levels, and the resulting D1R occupancy by DA, are not clearly known in schizophrenia, and may display great interindividual and intraindividual variability related to cognitive states and other physiological variables. These directly affect the selection of the level of stimulation necessary to correct the underlying neurobiology. The optimal mechanism for stimulation is also unknown and could include partial or full agonism, biased agonism, or positive allosteric modulation. Furthermore, the development of D1R targeting drugs has been complicated by complexities in extrapolating from in vitro affinity determinations to in vivo use. Prior D1R-targeted drugs have been unsuccessful due to poor bioavailability, pharmacokinetics, and insufficient target engagement at tolerable doses. Newer drugs have recently become available, and these must be tested in the context of carefully designed paradigms that address methodological challenges. In this paper, we discuss how a better understanding of these challenges has shaped our proposed experimental design for testing a new D1R/D5R partial agonist, PF-06412562, renamed CVL-562.

Mapping brain-behavior space relationships along the psychosis spectrum.

Difficulties in advancing effective patient-specific therapies for psychiatric disorders highlight a need to develop a stable neurobiologically grounded mapping between neural and symptom variation. This gap is particularly acute for psychosis-spectrum disorders (PSD). Here, in a sample of 436 PSD patients spanning several diagnoses, we derived and replicated a dimensionality-reduced symptom space across hallmark psychopathology symptoms and cognitive deficits. In turn, these symptom axes mapped onto distinct, reproducible brain maps. Critically, we found that multivariate brain-behavior mapping techniques (e.g. canonical correlation analysis) do not produce stable results with current sample sizes. However, we show that a univariate brain-behavioral space (BBS) can resolve stable individualized prediction. Finally, we show a proof-of-principle framework for relating personalized BBS metrics with molecular targets via serotonin and glutamate receptor manipulations and neural gene expression maps derived from the Allen Human Brain Atlas. Collectively, these results highlight a stable and data-driven BBS mapping across PSD, which offers an actionable path that can be iteratively optimized for personalized clinical biomarker endpoints.

Refining the Empirical Constraints on Computational Models of Spatial Working Memory in Schizophrenia.

BACKGROUND: Impairments in spatial working memory (sWM) have been well documented in schizophrenia. Here we provide a comprehensive test of a microcircuit model of WM performance in schizophrenia that predicts enhanced effects of increasing delay duration and distractors based on a hypothesized imbalance of excitatory and inhibitory processes. METHODS: Model predictions were tested in 41 people with schizophrenia (PSZ) and 32 healthy control subjects (HCS) performing an sWM task. In one condition, a single target location was followed by delays of 0, 2, 4, or 8 seconds. In a second condition, distractors were presented during the 4-second delay interval at 20°, 30°, 40°, 50°, or 90° from the original target location. RESULTS: PSZ showed less precise sWM representations than HCS, and the rate of memory drift over time was greater in PSZ than in HCS. Relative to HCS, the spatial recall responses of PSZ were more repelled by distractors presented close to the target location and more attracted by distractors presented far from the target location. The degree of attraction to distant distractors was correlated with the rate of memory drift in the absence of distractors. CONCLUSIONS: Consistent with the microcircuit model, PSZ exhibited both a greater rate of drift and greater attraction to distant distractors relative to HCS. These two effects were correlated, consistent with the proposal that they arise from a single underlying mechanism. However, the repulsion effects produced by nearby distractors were not predicted by the model and thus require an updated modeling framework.

Effects of reward on spatial working memory in schizophrenia.

Reward processing and cognition are disrupted in schizophrenia (SCZ), yet how these processes interface is unknown. In SCZ, deficits in reward representation may affect motivated, goal-directed behaviors. To test this, we examined the effects of monetary reward on spatial working memory (WM) performance in patients with SCZ. To capture complimentary effects, we tested biophysically grounded computational models of neuropharmacologic manipulations onto a canonical fronto-parietal association cortical microcircuit capable of WM computations. Patients with SCZ (n = 33) and healthy control subjects (HCS; n = 32) performed a spatial WM task with 2 reward manipulations: reward cues presented prior to each trial, or contextually prior to a block of trials. WM performance was compared with cortical circuit models of WM subjected to feed-forward glutamatergic excitation, feed-forward GABAergic inhibition, or recurrent modulation strengthening local connections. Results demonstrated that both groups improved WM performance to reward cues presented prior to each trial (HCS d = -0.62; SCZ d = -1.0), with percent improvement correlating with baseline WM performance (r = .472, p < .001). However, rewards presented contextually before a block of trials did not improve WM performance in patients with SCZ (d = 0.01). Modeling simulations achieved improved WM precision through strengthened local connections via neuromodulation, or feed-forward inhibition. Taken together, this work demonstrates that patients with SCZ can improve WM performance to short-term, but not longer-term rewards-thus, motivated behaviors may be limited by strength of reward representation. A potential mechanism for transiently improved WM performance may be strengthening of local fronto-parietal microcircuit connections via neuromodulation or feed-forward inhibitory drive. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Schizophrenia is associated with a pattern of spatial working memory deficits consistent with cortical disinhibition.

Schizophrenia is associated with severe cognitive deficits, including impaired working memory (WM). A neural mechanism that may contribute to WM impairment is the disruption in excitation-inhibition (E/I) balance in cortical microcircuits. It remains unknown, however, how these alterations map onto quantifiable behavioral deficits in patients. Based on predictions from a validated microcircuit model of spatial WM, we hypothesized two key behavioral consequences: i) increased variability of WM traces over time, reducing performance precision; and ii) decreased ability to filter out distractors that overlap with WM representations. To test model predictions, we studied N=27 schizophrenia patients and N=28 matched healthy comparison subjects (HCS) who performed a spatial WM task designed to test the computational model. Specifically, we manipulated delay duration and distractor distance presented during the delay. Subjects used a high-sensitivity joystick to indicate the remembered location, yielding a continuous response measure. Results largely followed model predictions, whereby patients exhibited increased variance and less WM precision as the delay period increased relative to HCS. Schizophrenia patients also exhibited increased WM distractibility, with reports biased toward distractors at specific spatial locations, as predicted by the model. Finally, the magnitude of the WM drift and distractibility were significantly correlated, indicating a possibly shared underlying mechanism. Effects are consistent with elevated E/I ratio in schizophrenia, establishing a framework for translating neural circuit computational model of cognition to human experiments, explicitly testing mechanistic behavioral hypotheses of cellular-level neural deficits in patients.

Amygdala volume is reduced in early course schizophrenia.

Subcortical structural alterations have been implicated in the neuropathology of schizophrenia. Yet, the extent of anatomical alterations for subcortical structures across illness phases remains unknown. To assess this, magnetic resonance imaging (MRI) was used to examine volume differences of major subcortical structures: thalamus, nucleus accumbens, caudate, putamen, globus pallidus, amygdala and hippocampus. These differences were examined across four groups: (i) healthy comparison subjects (HCS, n=96); (ii) individuals at high risk (HR, n=21) for schizophrenia; (iii) early-course schizophrenia patients (EC-SCZ, n=28); and (iv) chronic schizophrenia patients (C-SCZ, n=20). Raw gray matter volumes and volumetric ratios (volume of specific structure/total gray matter volume) were extracted using automated segmentation tools. EC-SCZ group exhibited smaller bilateral amygdala volumetric ratios, compared to HCS and HR subjects. Findings did not change when corrected for age, level of education and medication use. Amygdala raw volumes did not differ among groups once adjusted for multiple comparisons, but the smaller amygdala volumetric ratio in EC-SCZ survived Bonferroni correction. Other structures were not different across the groups following Bonferroni correction. Smaller amygdala volumes during early illness course may reflect pathophysiologic changes specific to illness development, including disrupted salience processing and acute stress responses.

Amygdala connectivity differs among chronic, early course, and individuals at risk for developing schizophrenia.

Alterations in circuits involving the amygdala have been repeatedly implicated in schizophrenia neuropathology, given their role in stress, affective salience processing, and psychosis onset. Disturbances in amygdala whole-brain functional connectivity associated with schizophrenia have yet to be fully characterized despite their importance in psychosis. Moreover, it remains unknown if there are functional alterations in amygdala circuits across illness phases. To evaluate this possibility, we compared whole-brain amygdala connectivity in healthy comparison subjects (HCS), individuals at high risk (HR) for schizophrenia, individuals in the early course of schizophrenia (EC-SCZ), and patients with chronic schizophrenia (C-SCZ). We computed whole-brain resting-state connectivity using functional magnetic resonance imaging at 3T via anatomically defined individual-specific amygdala seeds. We identified significant alterations in amygdala connectivity with orbitofrontal cortex (OFC), driven by reductions in EC-SCZ and C-SCZ (effect sizes of 1.0 and 0.97, respectively), but not in HR for schizophrenia, relative to HCS. Reduced amygdala-OFC coupling was associated with schizophrenia symptom severity (r = .32, P < .015). Conversely, we identified a robust increase in amygdala connectivity with a brainstem region around noradrenergic arousal nuclei, particularly for HR individuals relative to HCS (effect size = 1.54), but not as prominently for other clinical groups. These results suggest that deficits in amygdala-OFC coupling could emerge during the initial episode of schizophrenia (EC-SCZ) and may present as an enduring feature of the illness (C-SCZ) in association with symptom severity but are not present in individuals with elevated risk for developing schizophrenia. Instead, in HR individuals, there appears to be increased connectivity in a circuit implicated in stress response.

Cortico-amygdala-striatal circuits are organized as hierarchical subsystems through the primate amygdala.

The prefrontal and insula cortex, amygdala, and striatum are key regions for emotional processing, yet the amygdala's role as an interface between the cortex and striatum is not well understood. In the nonhuman primate (Macaque fascicularis), we analyzed a collection of bidirectional tracer injections in the amygdala to understand how cortical inputs and striatal outputs are organized to form integrated cortico-amygdala-striatal circuits. Overall, diverse prefrontal and insular cortical regions projected to the basal and accessory basal nuclei of the amygdala. In turn, these amygdala regions projected to widespread striatal domains extending well beyond the classic ventral striatum. Analysis of the cases in aggregate revealed a topographic colocalization of cortical inputs and striatal outputs in the amygdala that was additionally distinguished by cortical cytoarchitecture. Specifically, the degree of cortical laminar differentiation of the cortical inputs predicted amygdalostriatal targets, and distinguished three main cortico-amygdala-striatal circuits. These three circuits were categorized as "primitive," "intermediate," and "developed," respectively, to emphasize the relative phylogenetic and ontogenetic features of the cortical inputs. Within the amygdala, these circuits appeared arranged in a pyramidal-like fashion, with the primitive circuit found in all examined subregions, and subsequent circuits hierarchically layered in discrete amygdala subregions. This arrangement suggests a stepwise integration of the functions of these circuits across amygdala subregions, providing a potential mechanism through which internal emotional states are managed with external social and sensory information toward emotionally informed complex behaviors.

Connectivity, pharmacology, and computation: toward a mechanistic understanding of neural system dysfunction in schizophrenia.

Neuropsychiatric diseases such as schizophrenia and bipolar illness alter the structure and function of distributed neural networks. Functional neuroimaging tools have evolved sufficiently to reliably detect system-level disturbances in neural networks. This review focuses on recent findings in schizophrenia and bipolar illness using resting-state neuroimaging, an advantageous approach for biomarker development given its ease of data collection and lack of task-based confounds. These benefits notwithstanding, neuroimaging does not yet allow the evaluation of individual neurons within local circuits, where pharmacological treatments ultimately exert their effects. This limitation constitutes an important obstacle in translating findings from animal research to humans and from healthy humans to patient populations. Integrating new neuroscientific tools may help to bridge some of these gaps. We specifically discuss two complementary approaches. The first is pharmacological manipulations in healthy volunteers, which transiently mimic some cardinal features of psychiatric conditions. We specifically focus on recent neuroimaging studies using the NMDA receptor antagonist, ketamine, to probe glutamate synaptic dysfunction associated with schizophrenia. Second, we discuss the combination of human pharmacological imaging with biophysically informed computational models developed to guide the interpretation of functional imaging studies and to inform the development of pathophysiologic hypotheses. To illustrate this approach, we review clinical investigations in addition to recent findings of how computational modeling has guided inferences drawn from our studies involving ketamine administration to healthy subjects. Thus, this review asserts that linking experimental studies in humans with computational models will advance to effort to bridge cellular, systems, and clinical neuroscience approaches to psychiatric disorders.

Nucleus accumbens, thalamus and insula connectivity during incentive anticipation in typical adults and adolescents.

Reward neurocircuitry links motivation with complex behavioral responses. Studies of incentive processing have repeatedly demonstrated activation of nucleus accumbens (NAc), thalamus, and anterior insula, three key components of reward neurocircuitry. The contribution of the thalamus to this circuitry in humans has been relatively ignored, a gap that needs to be filled, given the central role of this structure in processing and filtering information. This study aimed to understand how these three regions function as a network during gain or loss anticipation in adults and youth. Towards this goal, functional magnetic resonance imaging (fMRI) and dynamic causal modeling (DCM) were used to examine effective connectivity among these three nodes in healthy adults and adolescents who performed the monetary incentive delay (MID) task. Seven connectivity models, based on anatomic connections, were tested. They were estimated for incentive anticipation and underwent Bayesian Model Selection (BMS) to determine the best-fit model for each adult and adolescent group. Connection strengths were extracted from the best-fit model and examined for significance in each group. These variables were then entered into a linear mixed model to test between-group effects on effective connectivity in reward neurocircuitry. The best-fit model for both groups included all possible anatomic connections. Three main findings emerged: (1) Across the task, thalamus and insula significantly influenced NAc; (2) A broader set of significant connections was found for the loss-cue condition than the gain-cue condition in both groups; (3) Finally, between-group comparisons of connectivity strength failed to detect statistical differences, suggesting that adults and adolescents use this incentive-processing network in a similar manner. This study demonstrates the way in which the thalamus and insula influence the NAc during incentive processing in humans. Specifically, this is the first study to demonstrate in humans the key role of thalamus projections onto the NAc in support of reward processing. Our results suggest that anticipation of gain/loss involves an 'alerting' signal (thalamus) that converges with interoceptive information (insula) to shape action selection programs in the ventral striatum.