Integrated number sense tutoring remediates aberrant neural representations in children with mathematical disabilities.

Number sense is essential for early mathematical development but it is compromised in children with mathematical disabilities (MD). Here we investigate the impact of a personalized 4-week Integrated Number Sense (INS) tutoring program aimed at improving the connection between nonsymbolic (sets of objects) and symbolic (Arabic numerals) representations in children with MD. Utilizing neural pattern analysis, we found that INS tutoring not only improved cross-format mapping but also significantly boosted arithmetic fluency in children with MD. Critically, the tutoring normalized previously low levels of cross-format neural representations in these children to pre-tutoring levels observed in typically developing, especially in key brain regions associated with numerical cognition. Moreover, we identified distinct, 'inverted U-shaped' neurodevelopmental changes in the MD group, suggesting unique neural plasticity during mathematical skill development. Our findings highlight the effectiveness of targeted INS tutoring for remediating numerical deficits in MD, and offer a foundation for developing evidence-based educational interventions.

Space wandering in the rodent default mode network.

The default mode network (DMN) is a large-scale brain network known to be suppressed during a wide range of cognitive tasks. However, our comprehension of its role in naturalistic and unconstrained behaviors has remained elusive because most research on the DMN has been conducted within the restrictive confines of MRI scanners. Here, we use multisite GCaMP (a genetically encoded calcium indicator) fiber photometry with simultaneous videography to probe DMN function in awake, freely exploring rats. We examined neural dynamics in three core DMN nodes-the retrosplenial cortex, cingulate cortex, and prelimbic cortex-as well as the anterior insula node of the salience network, and their association with the rats' spatial exploration behaviors. We found that DMN nodes displayed a hierarchical functional organization during spatial exploration, characterized by stronger coupling with each other than with the anterior insula. Crucially, these DMN nodes encoded the kinematics of spatial exploration, including linear and angular velocity. Additionally, we identified latent brain states that encoded distinct patterns of time-varying exploration behaviors and found that higher linear velocity was associated with enhanced DMN activity, heightened synchronization among DMN nodes, and increased anticorrelation between the DMN and anterior insula. Our findings highlight the involvement of the DMN in collectively and dynamically encoding spatial exploration in a real-world setting. Our findings challenge the notion that the DMN is primarily a "task-negative" network disengaged from the external world. By illuminating the DMN's role in naturalistic behaviors, our study underscores the importance of investigating brain network function in ecologically valid contexts.

Direct Writing of Room Temperature Polariton Condensate Lattice.

Realizing lattices of exciton polariton condensates has been of much interest owing to the potential of such systems to realize analogue Hamiltonian simulators and physical computing architectures. Here, we report the realization of a room temperature polariton condensate lattice using a direct-write approach. Polariton condensation is achieved in a microcavity embedded with host-guest Frenkel excitons of an organic dye (rhodamine) in a small-molecule ionic isolation lattice (SMILES). The microcavity is patterned using focused ion beam etching to realize arbitrary lattice geometries, including defect sites on demand. The band structure of the lattice and the emergence of condensation are imaged using momentum-resolved spectroscopy. The introduction of defect sites is shown to lower the condensation threshold and result in the formation of a defect band in the condensation spectrum. The present approach allows us to study periodic, quasiperiodic, and disordered polariton condensate lattices at room temperature using a direct-write approach.

Robust and replicable functional brain signatures of 22q11.2 deletion syndrome and associated psychosis: a deep neural network-based multi-cohort study.

A major genetic risk factor for psychosis is 22q11.2 deletion (22q11.2DS). However, robust and replicable functional brain signatures of 22q11.2DS and 22q11.2DS-associated psychosis remain elusive due to small sample sizes and a focus on small single-site cohorts. Here, we identify functional brain signatures of 22q11.2DS and 22q11.2DS-associated psychosis, and their links with idiopathic early psychosis, using one of the largest multi-cohort data to date. We obtained multi-cohort clinical phenotypic and task-free fMRI data from 856 participants (101 22q11.2DS, 120 idiopathic early psychosis, 101 idiopathic autism, 123 idiopathic ADHD, and 411 healthy controls) in a case-control design. A novel spatiotemporal deep neural network (stDNN)-based analysis was applied to the multi-cohort data to identify functional brain signatures of 22q11.2DS and 22q11.2DS-associated psychosis. Next, stDNN was used to test the hypothesis that the functional brain signatures of 22q11.2DS-associated psychosis overlap with idiopathic early psychosis but not with autism and ADHD. stDNN-derived brain signatures distinguished 22q11.2DS from controls, and 22q11.2DS-associated psychosis with very high accuracies (86-94%) in the primary cohort and two fully independent cohorts without additional training. Robust distinguishing features of 22q11.2DS-associated psychosis emerged in the anterior insula node of the salience network and the striatum node of the dopaminergic reward pathway. These features also distinguished individuals with idiopathic early psychosis from controls, but not idiopathic autism or ADHD. Our results reveal that individuals with 22q11.2DS exhibit a highly distinct functional brain organization compared to controls. Additionally, the brain signatures of 22q11.2DS-associated psychosis overlap with those of idiopathic early psychosis in the salience network and dopaminergic reward pathway, providing substantial empirical support for the theoretical aberrant salience-based model of psychosis. Collectively, our findings, replicated across multiple independent cohorts, advance the understanding of 22q11.2DS and associated psychosis, underscoring the value of 22q11.2DS as a genetic model for probing the neurobiological underpinnings of psychosis and its progression.

Electrophysiological dynamics of a triple network model of cognitive control: A multi-experiment replication.

Dynamic interactions between large-scale brain networks are thought to underpin human cognitive processes, but their underlying electrophysiological dynamics remain unknown. The triple network model, which highlights the salience, default mode, and frontoparietal networks, provides a fundamental framework for understanding these interactions. To unravel the electrophysiological mechanisms underlying these network dynamics, we utilized intracranial EEG recordings from 177 participants across four distinct memory experiments. Our findings revealed a consistent pattern of directed information flow from the anterior insula, a key node of the salience network, to both the default mode and frontoparietal networks. Notably, this pattern of information transmission was observed regardless of the nature of the tasks, whether they involved externally driven stimuli during encoding or internally governed processes during free recall. Moreover, the directed information flow from the anterior insula to the other networks was present irrespective of the activation or suppression states of individual network nodes. Furthermore, we observed a specific suppression of high-gamma power in the posterior cingulate cortex/precuneus node of the default mode network during memory encoding, but not recall, suggesting a task-specific functional down-regulation of this region. Crucially, these results were reliably replicated across all four experiments, underscoring the robustness and generalizability of our findings. Our study significantly advances the understanding of how coordinated neural network interactions underpin cognitive operations and highlights the critical role of the anterior insula in orchestrating the dynamics of large-scale brain networks. These findings have important implications for elucidating the neural basis of cognitive control and its potential disruptions in various neurological and psychiatric disorders.

A multi-demand operating system underlying diverse cognitive tasks.

The existence of a multiple-demand cortical system with an adaptive, domain-general, role in cognition has been proposed, but the underlying dynamic mechanisms and their links to cognitive control abilities are poorly understood. Here we use a probabilistic generative Bayesian model of brain circuit dynamics to determine dynamic brain states across multiple cognitive domains, independent datasets, and participant groups, including task fMRI data from Human Connectome Project, Dual Mechanisms of Cognitive Control study and a neurodevelopment study. We discover a shared brain state across seven distinct cognitive tasks and found that the dynamics of this shared brain state predicted cognitive control abilities in each task. Our findings reveal the flexible engagement of dynamic brain processes across multiple cognitive domains and participant groups, and uncover the generative mechanisms underlying the functioning of a domain-general cognitive operating system. Our computational framework opens promising avenues for probing neurocognitive function and dysfunction.

Deep learning models reveal replicable, generalizable, and behaviorally relevant sex differences in human functional brain organization.

Sex plays a crucial role in human brain development, aging, and the manifestation of psychiatric and neurological disorders. However, our understanding of sex differences in human functional brain organization and their behavioral consequences has been hindered by inconsistent findings and a lack of replication. Here, we address these challenges using a spatiotemporal deep neural network (stDNN) model to uncover latent functional brain dynamics that distinguish male and female brains. Our stDNN model accurately differentiated male and female brains, demonstrating consistently high cross-validation accuracy (>90%), replicability, and generalizability across multisession data from the same individuals and three independent cohorts (N ~ 1,500 young adults aged 20 to 35). Explainable AI (XAI) analysis revealed that brain features associated with the default mode network, striatum, and limbic network consistently exhibited significant sex differences (effect sizes > 1.5) across sessions and independent cohorts. Furthermore, XAI-derived brain features accurately predicted sex-specific cognitive profiles, a finding that was also independently replicated. Our results demonstrate that sex differences in functional brain dynamics are not only highly replicable and generalizable but also behaviorally relevant, challenging the notion of a continuum in male-female brain organization. Our findings underscore the crucial role of sex as a biological determinant in human brain organization, have significant implications for developing personalized sex-specific biomarkers in psychiatric and neurological disorders, and provide innovative AI-based computational tools for future research.

Enhanced attention-related alertness following right anterior insular cortex neurofeedback training.

The anterior insular cortex, a central node of the salience network, plays a critical role in cognitive control and attention. Here, we investigated the feasibility of enhancing attention using real-time fMRI neurofeedback training that targets the right anterior insular cortex (rAIC). 56 healthy adults underwent two neurofeedback training sessions. The experimental group received feedback from neural responses in the rAIC, while control groups received sham feedback from the primary visual cortex or no feedback. Cognitive functioning was evaluated before, immediately after, and three months post-training. Our results showed that only the rAIC neurofeedback group successfully increased activity in the rAIC. Furthermore, this group showed enhanced attention-related alertness up to three months after the training. Our findings provide evidence for the potential of rAIC neurofeedback as a viable approach for enhancing attention-related alertness, which could pave the way for non-invasive therapeutic strategies to address conditions characterized by attention deficits.

Long-term abacus training gains in children are predicted by medial temporal lobe anatomy and circuitry.

Abacus-based mental calculation (AMC) is a widely used educational tool for enhancing math learning, offering an accessible and cost-effective method for classroom implementation. Despite its universal appeal, the neurocognitive mechanisms that drive the efficacy of AMC training remain poorly understood. Notably, although abacus training relies heavily on the rapid recall of number positions and sequences, the role of memory systems in driving long-term AMC learning remains unknown. Here, we sought to address this gap by investigating the role of the medial temporal lobe (MTL) memory system in predicting long-term AMC training gains in second-grade children, who were longitudinally assessed up to fifth grade. Leveraging multimodal neuroimaging data, we tested the hypothesis that MTL systems, known for their involvement in associative memory, are instrumental in facilitating AMC-induced improvements in math skills. We found that gray matter volume in bilateral MTL, along with functional connectivity between the MTL and frontal and ventral temporal-occipital cortices, significantly predicted learning gains. Intriguingly, greater gray matter volume but weaker connectivity of the posterior parietal cortex predicted better learning outcomes, offering a more nuanced view of brain systems at play in AMC training. Our findings not only underscore the critical role of the MTL memory system in AMC training but also illuminate the neurobiological factors contributing to individual differences in cognitive skill acquisition. RESEARCH HIGHLIGHTS: We investigated the role of medial temporal lobe (MTL) memory system in driving children's math learning following abacus-based mental calculation (AMC) training. AMC training improved math skills in elementary school children across their second and fifth grade. MTL structural integrity and functional connectivity with prefrontal and ventral temporal-occipital cortices predicted long-term AMC training-related gains.

Atypical pattern separation memory and its association with restricted interests and repetitive behaviors in autistic children.

LAY ABSTRACT: Memory challenges remain understudied in childhood autism. Our study investigates one specific aspect of memory function, known as pattern separation memory, in autistic children. Pattern separation memory refers to the critical ability to store unique memories of similar stimuli; however, its role in childhood autism remains largely uncharted. Our study first uncovered that the pattern separation memory was significantly reduced in autistic children, and then showed that reduced memory performance was linked to their symptoms of repetitive, restricted interest and behavior. We also identified distinct subgroups with profiles of reduced and increased generalization for pattern separation memory. More than 72% of autistic children showed a tendency to reduce memory generalization, focusing heavily on unique details of objects for memorization. This focus made it challenging for them to identify commonalities across similar entities. Interestingly, a smaller proportion of autistic children displayed an opposite pattern of increased generalization, marked by challenges in differentiating between similar yet distinct objects. Our findings advance the understanding of memory function in autism and have practical implications for devising personalized learning strategies that align with the unique memory patterns exhibited by autistic children. This study will be of broad interest to researchers in psychology, psychiatry, and brain development as well as teachers, parents, clinicians, and the wider public.

Addressing the Dark State Problem in Strongly Coupled Organic Exciton-Polariton Systems.

The manipulation of molecular excited state processes through strong coupling has attracted significant interest for its potential to provide precise control of photochemical phenomena. However, the key limiting factor for achieving this control has been the "dark-state problem", in which photoexcitation populates long-lived reservoir states with energies and dynamics similar to those of bare excitons. Here, we use a sensitive ultrafast transient reflection method with momentum and spectral resolution to achieve the selective excitation of organic exciton-polaritons in open photonic cavities. We show that the energy dispersions of these systems allow us to avoid the parasitic effect of the reservoir states. Under phase-matching conditions, we observe the direct population and decay of polaritons on time scales of less than 100 fs and find that momentum scattering processes occur on even faster time scales. We establish that it is possible to overcome the "dark state problem" through the careful design of strongly coupled systems.

Planar hyperbolic polaritons in 2D van der Waals materials.

Anisotropic planar polaritons - hybrid electromagnetic modes mediated by phonons, plasmons, or excitons - in biaxial two-dimensional (2D) van der Waals crystals have attracted significant attention due to their fundamental physics and potential nanophotonic applications. In this Perspective, we review the properties of planar hyperbolic polaritons and the variety of methods that can be used to experimentally tune them. We argue that such natural, planar hyperbolic media should be fairly common in biaxial and uniaxial 2D and 1D van der Waals crystals, and identify the untapped opportunities they could enable for functional (i.e. ferromagnetic, ferroelectric, and piezoelectric) polaritons. Lastly, we provide our perspectives on the technological applications of such planar hyperbolic polaritons.

Bouveret's syndrome: An old diagnosis. A modern multimodality approach (endoscopic and robotic surgical) of gastric outlet obstruction: Report of two cases.

INTRODUCTION AND IMPORTANCE: Bouveret's syndrome is an uncommon condition characterized by the impaction of a gallstone in the pylorus or duodenum via a cholecysto-enteric fistula causing gastric outlet obstruction. We report two unusual cases of Bouveret's syndrome causing gastric outlet obstruction in two elderly patients. CASE PRESENTATION: Two elderly female patients presented to the surgical assessment unit with features of gastric outlet obstruction. In both cases, an urgent computed tomography (CT) of the abdomen showed pneumobilia, gastric distension, and gallstones impaction at the duodenal bulb. In Patient 1, endoscopic removal of the impacted gallstones was done successfully. She was discharged three days following an uneventful recovery. In Patient 2, an endoscopic removal of a single large gallstone was attempted, which was unsuccessful. She underwent robotic gastrotomy with extraction of the large gallstone with primary repair. She was discharged on 8th postoperative day. CLINICAL DISCUSSION: Treatment options for Bouveret's syndrome include endoscopic management and surgery. The selection of treatment options depends upon factors like the degree of obstruction, the impaction site, number, type or size of gallstones, patient co-morbidities and clinical parameters at presentation, as well as expertise available, both endoscopic and surgical. CONCLUSIONS: Bouveret's syndrome is one of the rare complications of gallstone. Endoscopic management can be effective at removing the impacted gallstones, which is particularly helpful for those elderly patients who have multiple medical co-morbidities, as in our first patient. Surgical management like minimal invasive surgery (robotic) can be beneficial in failed endoscopic attempt of removal of stone like in the second patient.

Hippocampal-parietal cortex causal information flow in human episodic memory: replication across three experiments.

While extensive research has focused on hippocampus-prefrontal circuits in episodic memory and spatial navigation, the role of hippocampus-parietal cortex circuits remains understudied. We employed intracranial EEG to investigate these circuits across three different memory experiments, revealing a consistent, asymmetric pattern of higher causal information flow from the hippocampus to both lateral and medial posterior parietal cortex (PPC). This directional information flow was observed during both memory encoding and recall and across verbal and spatial episodic memory domains. Importantly, this directed information flow was not contingent upon activation or suppression states in the hippocampus or PPC. Frequency-specific directional interactions were also identified, with greater hippocampal-to-PPC flow in the delta-theta band and the reverse in the beta band. The robustness of these results was demonstrated through Bayesian replication analysis. Our findings shed new light on the frequency-dependent signaling within hippocampus-parietal circuits, broadening our understanding of their critical roles in human episodic memory.

UK cost-effectiveness analysis of endoscopic sleeve gastroplasty versus lifestyle modification alone for adults with class II obesity.

BACKGROUND: Endoscopic sleeve gastroplasty (ESG) is a minimally invasive procedure that has been demonstrated in the MERIT randomised, controlled trial to result in substantial and durable additional weight loss in adults with obesity compared with lifestyle modification (LM) alone. We sought to conduct the first cost-effectiveness analysis of ESG versus LM alone in adults with class II obesity (BMI 35.0-39.9 kg/m2) from a national healthcare system perspective in England based on results from this study. METHODS: A 6-state Markov model was developed comprising 5 BMI-based health states and an absorbing death state. Baseline characteristics, utilities, and transition probabilities were informed by patient-level data from the subset of patients with class II obesity in MERIT. Adverse events (AEs) were based on the MERIT safety population. Mortality was estimated by applying BMI-specific hazard ratios from the published literature to UK general population mortality rates. Utilities for the healthy weight and overweight health states were informed from the literature; disutility associated with increasing BMI in the class I-III obesity health states was estimated using MERIT utility data. Disutility due to AEs and the prevalence of obesity-related comorbidities were based on the literature. Costs included intervention costs, AE costs, and comorbidity costs. RESULTS: ESG resulted in higher overall costs than LM alone but led to an increase in quality-adjusted life years (QALYs). The incremental cost-effectiveness ratio (ICER) for ESG vs LM alone was £2453/QALY gained. ESG was consistently cost effective across a wide range of sensitivity analyses, with no ICER estimate exceeding £10,000/QALY gained. In probabilistic sensitivity analysis, the mean ICER was £2502/QALY gained and ESG remained cost effective in 98.25% of iterations at a willingness-to-pay threshold of £20,000/QALY. CONCLUSION: Our study indicates that ESG is highly cost effective versus LM alone for the treatment of adults with class II obesity in England.

Space wandering in the rodent default mode network.

The default mode network (DMN) is a large-scale brain network known to be suppressed during a wide range of cognitive tasks. However, our comprehension of its role in naturalistic and unconstrained behaviors has remained elusive because most research on the DMN has been conducted within the restrictive confines of MRI scanners. Here we use multisite GCaMP fiber photometry with simultaneous videography to probe DMN function in awake, freely exploring rats. We examined neural dynamics in three core DMN nodes- the retrosplenial cortex, cingulate cortex, and prelimbic cortex- as well as the anterior insula node of the salience network, and their association with the rats' spatial exploration behaviors. We found that DMN nodes displayed a hierarchical functional organization during spatial exploration, characterized by stronger coupling with each other than with the anterior insula. Crucially, these DMN nodes encoded the kinematics of spatial exploration, including linear and angular velocity. Additionally, we identified latent brain states that encoded distinct patterns of time-varying exploration behaviors and discovered that higher linear velocity was associated with enhanced DMN activity, heightened synchronization among DMN nodes, and increased anticorrelation between the DMN and anterior insula. Our findings highlight the involvement of the DMN in collectively and dynamically encoding spatial exploration in a real-world setting. Our findings challenge the notion that the DMN is primarily a "task-negative" network disengaged from the external world. By illuminating the DMN's role in naturalistic behaviors, our study underscores the importance of investigating brain network function in ecologically valid contexts.

Magneto-optics in a van der Waals magnet tuned by self-hybridized polaritons.

Controlling quantum materials with light is of fundamental and technological importance. By utilizing the strong coupling of light and matter in optical cavities1-3, recent studies were able to modify some of their most defining features4-6. Here we study the magneto-optical properties of a van der Waals magnet that supports strong coupling of photons and excitons even in the absence of external cavity mirrors. In this material-the layered magnetic semiconductor CrSBr-emergent light-matter hybrids called polaritons are shown to substantially increase the spectral bandwidth of correlations between the magnetic, electronic and optical properties, enabling largely tunable optical responses to applied magnetic fields and magnons. Our results highlight the importance of exciton-photon self-hybridization in van der Waals magnets and motivate novel directions for the manipulation of quantum material properties by strong light-matter coupling.

Atypical cognitive training-induced learning and brain plasticity and their relation to insistence on sameness in children with autism.

Children with autism spectrum disorders (ASDs) often display atypical learning styles; however, little is known regarding learning-related brain plasticity and its relation to clinical phenotypic features. Here, we investigate cognitive learning and neural plasticity using functional brain imaging and a novel numerical problem-solving training protocol. Children with ASD showed comparable learning relative to typically developing children but were less likely to shift from rule-based to memory-based strategy. While learning gains in typically developing children were associated with greater plasticity of neural representations in the medial temporal lobe and intraparietal sulcus, learning in children with ASD was associated with more stable neural representations. Crucially, the relation between learning and plasticity of neural representations was moderated by insistence on sameness, a core phenotypic feature of ASD. Our study uncovers atypical cognitive and neural mechanisms underlying learning in children with ASD, and informs pedagogical strategies for nurturing cognitive abilities in childhood autism.

Bariatric surgery improves access to renal transplantation and is safe in renal failure as well as after transplantation: A systematic review and meta-analysis.

INTRODUCTION: Effective workup and listing of end-stage renal disease (ESRD) patients for renal transplantation, often with multiple co-morbidities, poses a challenge for transplant teams. Obesity is a common co-morbidity associated with adverse outcomes in ESRD and kidney transplant (KT) recipients. Bariatric and metabolic surgery (BMS) has long been established as a safe and effective treatment for morbid obesity. In this study, the authors aimed to evaluate the strength of evidence for both the efficacy and safety of bariatric surgery in patients with ESRD or kidney transplantation. METHODS: A literature search was performed using key terms including "transplantation", "kidney", "renal", "obesity", and "bariatric". Databases searched include MEDLINE, EMBASE and Web of Science from inception to date (April 2021). Methodological quality was assessed using the Newcastle-Ottawa tool. Selected articles were then categorised into patients awaiting waiting list acceptance, patients awaiting transplantation, patients undergoing simultaneous BMS + KT and patients undergoing BMS following a previous renal transplant. Summary effects are presented with a level of statistical significance and 95% Confidence Intervals. RESULTS: A total of 28 articles were selected following the literature search. Fourteen studies on patients awaiting listing (n = 1903), nine on patients on the KT waiting list (n = 196), a single study on simultaneous BMS and KT and ten studies on patients undergoing BMS following KT (n = 198). Mean change in BMI for patients awaiting listing was -11.3 kg/m2 (95%CI: -15.3 to -7.3, p < 0.001), mean change in BMI for patients listed for KT was -11.2 kg/m 2(95%CI: -12.9 to -9.5, p 0.001) and mean change for patients with prior KT was -11.0 kg/m2 (95%CI: -7.09 to -14.9, p < 0.001). The combined mortality rate for patients who had undergone both BMS and KT was 4% (n = 15). DISCUSSION: This review demonstrates BMS is both safe and efficacious in patients with ESRD prior to KT and in those post KT. It would enable difficult-to-list obese recipients the possibility to undergo transplantation and should be considered as part of the work up process.

Bayesian dynamical system analysis of the effects of methylphenidate in children with attention-deficit/hyperactivity disorder: a randomized trial.

Methylphenidate is a widely used and effective treatment for attention-deficit/hyperactivity disorder (ADHD), yet the underlying neural mechanisms and their relationship to changes in behavior are not fully understood. Specifically, it remains unclear how methylphenidate affects brain and behavioral dynamics, and the interplay between these dynamics, in individuals with ADHD. To address this gap, we used a novel Bayesian dynamical system model to investigate the effects of methylphenidate on latent brain states in 27 children with ADHD and 49 typically developing children using a double-blind, placebo-controlled crossover design. Methylphenidate remediated greater behavioral variability on a continuous performance task in children with ADHD. Children with ADHD exhibited aberrant latent brain state dynamics compared to typically developing children, with a single latent state showing particularly abnormal dynamics, which was remediated by methylphenidate. Additionally, children with ADHD showed brain state-dependent hyper-connectivity in the default mode network, which was also remediated by methylphenidate. Finally, we found that methylphenidate-induced changes in latent brain state dynamics, as well as brain state-related functional connectivity between salience and default mode networks, were correlated with improvements in behavioral variability. Taken together, our findings reveal a novel latent brain state dynamical process and circuit mechanism underlying the therapeutic effects of methylphenidate in childhood ADHD. We suggest that Bayesian dynamical system models may be particularly useful for capturing complex nonlinear changes in neural activity and behavioral variability associated with ADHD. Our approach may be of value to clinicians and researchers investigating the neural mechanisms underlying pharmacological treatment of psychiatric disorders.