Deep learning of spontaneous arousal fluctuations detects early cholinergic defects across neurodevelopmental mouse models and patients

Transfer Learning in Cancer Genetics, Mutation Detection, Gene Expression Analysis, and Syndrome Recognition

Artificial intelligence (AI), encompassing machine learning (ML) and deep learning (DL), has revolutionized medical research, facilitating advancements in drug discovery and cancer diagnosis. ML identifies patterns in data, while DL employs neural networks for intricate processing. Predictive modeling challenges, such as data labeling, are addressed by transfer learning (TL), leveraging pre-existing models for faster training. TL shows potential in genetic research, improving tasks like gene expression analysis, mutation detection, genetic syndrome recognition, and genotype-phenotype association. This review explores the role of TL in overcoming challenges in mutation detection, genetic syndrome detection, gene expression, or phenotype-genotype association. TL has shown effectiveness in various aspects of genetic research. TL enhances the accuracy and efficiency of mutation detection, aiding in the identification of genetic abnormalities. TL can improve the diagnostic accuracy of syndrome-related genetic patterns. Moreover, TL plays a crucial role in gene expression analysis in order to accurately predict gene expression levels and their interactions. Additionally, TL enhances phenotype-genotype association studies by leveraging pre-trained models. In conclusion, TL enhances AI efficiency by improving mutation prediction, gene expression analysis, and genetic syndrome detection. Future studies should focus on increasing domain similarities, expanding databases, and incorporating clinical data for better predictions.

Sound elicits stereotyped facial movements that provide a sensitive index of hearing abilities in mice

Sound elicits rapid movements of muscles in the face, ears, and eyes that protect the body from injury and trigger brain-wide internal state changes. Here, we performed quantitative facial videography from mice resting atop a piezoelectric force plate and observed that broadband sounds elicited rapid and stereotyped facial twitches. Facial motion energy (FME) adjacent to the whisker array was 30 dB more sensitive than the acoustic startle reflex and offered greater inter-trial and inter-animal reliability than sound-evoked pupil dilations or movement of other facial and body regions. FME tracked the low-frequency envelope of broadband sounds, providing a means to study behavioral discrimination of complex auditory stimuli, such as speech phonemes in noise. Approximately 25% of layer 5-6 units in the auditory cortex (ACtx) exhibited firing rate changes during facial movements. However, FME facilitation during ACtx photoinhibition indicated that sound-evoked facial movements were mediated by a midbrain pathway and modulated by descending corticofugal input. FME and auditory brainstem response (ABR) thresholds were closely aligned after noise-induced sensorineural hearing loss, yet FME growth slopes were disproportionately steep at spared frequencies, reflecting a central plasticity that matched commensurate changes in ABR wave 4. Sound-evoked facial movements were also hypersensitive in Ptchd1 knockout mice, highlighting the use of FME for identifying sensory hyper-reactivity phenotypes after adult-onset hyperacusis and inherited deficiencies in autism risk genes. These findings present a sensitive and integrative measure of hearing while also highlighting that even low-intensity broadband sounds can elicit a complex mixture of auditory, motor, and reafferent somatosensory neural activity.

Cell type-specific expression, regulation and compensation of CDKL5 activity in mouse brain

CDKL5 is a brain-enriched serine/threonine kinase, associated with a profound developmental and epileptic encephalopathy called CDKL5 deficiency disorder (CDD). To design targeted therapies for CDD, it is essential to determine where CDKL5 is expressed and is active in the brain and test if compensatory mechanisms exist at cellular level. We generated conditional Cdkl5 knockout mice in excitatory neurons, inhibitory neurons and astrocytes. To assess CDKL5 activity, we utilized a phosphospecific antibody for phosphorylated EB2, a well-known substrate of CDKL5. We found that CDKL5 and EB2 pS222 were prominent in excitatory and inhibitory neurons but were not detected in astrocytes. We observed that approximately 15-20% of EB2 pS222 remained in Cdkl5 knockout brains and primary neurons. Surprisingly, the remaining phosphorylation was modulated by NMDA and PP1/PP2A in neuronal CDKL5 knockout cultures, indicating the presence of a compensating kinase. Using a screen of candidate kinases with highest homology to the CDKL5 kinase domain, we found that CDKL2 and ICK can phosphorylate EB2 S222 in HEK293T cells and in primary neurons. We then generated Cdkl5/Cdkl2 dual knockout mice to directly test if CDKL2 phosphorylates EB2 in vivo and found that CDKL2 phosphorylates CDKL5 substrates in the brain. This study is the first indication that CDKL2 could potentially replace CDKL5 functions in the brain, alluding to novel therapeutic possibilities.

Epilepsy-linked kinase CDKL5 phosphorylates voltage-gated calcium channel Cav2.3, altering inactivation kinetics and neuronal excitability

Developmental and epileptic encephalopathies (DEEs) are a group of rare childhood disorders characterized by severe epilepsy and cognitive deficits. Numerous DEE genes have been discovered thanks to advances in genomic diagnosis, yet putative molecular links between these disorders are unknown. CDKL5 deficiency disorder (CDD, DEE2), one of the most common genetic epilepsies, is caused by loss-of-function mutations in the brain-enriched kinase CDKL5. To elucidate CDKL5 function, we looked for CDKL5 substrates using a SILAC-based phosphoproteomic screen. We identified the voltage-gated Ca2+ channel Cav2.3 (encoded by CACNA1E) as a physiological target of CDKL5 in mice and humans. Recombinant channel electrophysiology and interdisciplinary characterization of Cav2.3 phosphomutant mice revealed that loss of Cav2.3 phosphorylation leads to channel gain-of-function via slower inactivation and enhanced cholinergic stimulation, resulting in increased neuronal excitability. Our results thus show that CDD is partly a channelopathy. The properties of unphosphorylated Cav2.3 closely resemble those described for CACNA1E gain-of-function mutations causing DEE69, a disorder sharing clinical features with CDD. We show that these two single-gene diseases are mechanistically related and could be ameliorated with Cav2.3 inhibitors.

Identification of diagnostic markers for ASD: a restrictive interest analysis based on EEG combined with eye tracking

Electroencephalography (EEG) functional connectivity (EFC) and eye tracking (ET) have been explored as objective screening methods for autism spectrum disorder (ASD), but no study has yet evaluated restricted and repetitive behavior (RRBs) simultaneously to infer early ASD diagnosis. Typically developing (TD) children (n = 27) and ASD (n = 32), age- and sex-matched, were evaluated with EFC and ET simultaneously, using the restricted interest stimulus paradigm. Network-based machine learning prediction (NBS-predict) was used to identify ASD. Correlations between EFC, ET, and Autism Diagnostic Observation Schedule-Second Edition (ADOS-2) were performed. The Area Under the Curve (AUC) of receiver-operating characteristics (ROC) was measured to evaluate the predictive performance. Under high restrictive interest stimuli (HRIS), ASD children have significantly higher α band connectivity and significantly more total fixation time (TFT)/pupil enlargement of ET relative to TD children (p = 0.04299). These biomarkers were not only significantly positively correlated with each other (R = 0.716, p = 8.26e-4), but also with ADOS total scores (R = 0.749, p = 34e-4) and RRBs sub-score (R = 0.770, p = 1.87e-4) for EFC (R = 0.641, p = 0.0148) for TFT. The accuracy of NBS-predict in identifying ASD was 63.4%. ROC curve demonstrated TFT with 91 and 90% sensitivity, and 78.7% and 77.4% specificity for ADOS total and RRB sub-scores, respectively. Simultaneous EFC and ET evaluation in ASD is highly correlated with RRB symptoms measured by ADOS-2. NBS-predict of EFC offered a direct prediction of ASD. The use of both EFC and ET improve early ASD diagnosis.

Probiotic and intra-nasal oxytocin combination therapy on autonomic function and gut-brain axis signaling in young children and teens with autism spectrum disorder

Autonomic dysfunction has been widely studied in individuals with autism spectral disorder (ASD); however, the autonomic response to probiotic and oxytocin (OT) combination intervention has not yet been explored. We conducted the present study that includes 35 individuals with ASD aged 3-20 years to explore autonomic responses to daily Lactobacillus plantarum probiotic supplementation and OT nasal spray treatment both alone and in combination. We identified significant improvements in autonomic indices from subjects receiving combination treatment relative to those receiving placebo. Parameters that were observed to improve following combination treatment are time domain metrics of heart rate variability (HRV), including the root mean square of successive differences between normal heartbeats (RMSSD), standard deviation of normal-to-normal R-R intervals (SDNN), and proportion of the number of pairs of adjacent NN intervals that differ by more than 50ms (pNN50, p < 0.05). Furthermore, individuals that received either probiotics or OT alone demonstrated fewer changes in RMSSD, pNN50, and SDNN. Several parameters that demonstrated significant improvements in combination therapy were found to be correlated with baseline levels of OT (LF power: r = -0.86, p = 0.024; mean HR: r = 0.89, p = 0.012). Additionally, Social Responsiveness Scale (SRS) raw total scores (mean HR, r = 0.86, p = 0.024) and Aberrant Behavior Checklist (ABC) raw total scores (mean HR r = 0.94, p = 0.017) were correlated with mean heart rate (HR) and HRV-derived parameters. These results provide further evidence of synergy of probiotic and OT combination and help us gain a better understanding of the role of the gut-brain axis in ASD phenotypes and pathogenesis.

Detection of Frog Virus 3 by Integrating RPA-CRISPR/Cas12a-SPM with Deep Learning

A fast, easy-to-implement, highly sensitive, and point-of-care (POC) detection system for frog virus 3 (FV3) is proposed. Combining recombinase polymerase amplification (RPA) and CRISPR/Cas12a, a limit of detection (LoD) of 100 aM (60.2 copies/μL) is achieved by optimizing RPA primers and CRISPR RNAs (crRNAs). For POC detection, smartphone microscopy is implemented, and an LoD of 10 aM is achieved in 40 min. The proposed system detects four positive animal-derived samples with a quantitation cycle (Cq) value of quantitative PCR (qPCR) in the range of 13 to 32. In addition, deep learning models are deployed for binary classification (positive or negative samples) and multiclass classification (different concentrations of FV3 and negative samples), achieving 100 and 98.75% accuracy, respectively. Without temperature regulation and expensive equipment, the proposed RPA-CRISPR/Cas12a combined with smartphone readouts and artificial-intelligence-assisted classification showcases the great potential for FV3 detection, specifically POC detection of DNA virus.

Altered pupil responses to social and non-social stimuli in Shank3 mutant dogs

Pupillary response, an important process in visual perception and social and emotional cognition, has been widely studied for understanding the neural mechanisms of neuropsychiatric disorders. However, there have been few studies on pupil response to social and non-social stimuli in animal models of neurodevelopmental disorders including autism spectrum disorder (ASD) and attention deficit hyperactivity disorder. Here, we developed a pupilometer using a robust eye feature-detection algorithm for real-time pupillometry in dogs. In a pilot study, we found that a brief light flash induced a less-pronounced and slower pupil dilation response in gene-edited dogs carrying mutations in Shank3; mutations of its ortholog in humans were repeatedly identified in ASD patients. We further found that obnoxious, loud firecracker sound of 120 dB induced a stronger and longer pupil dilation response in Shank3 mutant dogs, whereas a high reward food induced a weaker pupillary response in Shank3 mutants than in wild-type control dogs. In addition, we found that Shank3 mutants showed compromised pupillary synchrony during dog-human interaction. These findings of altered pupil response in Shank3 mutant dogs recapitulate the altered sensory responses in ASD patients. Thus, this study demonstrates the validity and value of the pupilometer for dogs, and provides an effective paradigm for studying the underlying neural mechanisms of ASD and potentially other psychiatric disorders.

Shank3 deletion in PV neurons is associated with abnormal behaviors and neuronal functions that are rescued by increasing GABAergic signaling

BACKGROUND

Phelan-McDermid syndrome (PMS) is a neurodevelopmental disorder characterized by developmental delay, intellectual disability, and autistic-like behaviors and is primarily caused by haploinsufficiency of SHANK3 gene. Currently, there is no specific treatment for PMS, highlighting the need for a better understanding of SHANK3 functions and the underlying pathophysiological mechanisms in the brain. We hypothesize that SHANK3 haploinsufficiency may lead to alterations in the inhibitory system, which could be linked to the excitatory/inhibitory imbalance observed in models of autism spectrum disorder (ASD). Investigation of these neuropathological features may shed light on the pathogenesis of PMS and potential therapeutic interventions.

METHODS

We recorded local field potentials and visual evoked responses in the visual cortex of Shank3∆11-/- mice. Then, to understand the impact of Shank3 in inhibitory neurons, we generated Pv-cre+/- Shank3Fl/Wt conditional mice, in which Shank3 was deleted in parvalbumin-positive neurons. We characterized the phenotype of this murine model and we compared this phenotype before and after ganaxolone administration.

RESULTS

We found, in the primary visual cortex, an alteration of the gain control of Shank3 KO compared with Wt mice, indicating a deficit of inhibition on pyramidal neurons. This alteration was rescued after the potentiation of GABAA receptor activity by Midazolam. Behavioral analysis showed an impairment in grooming, memory, and motor coordination of Pv-cre+/- Shank3Fl/Wt compared with Pv-cre+/- Shank3Wt/Wt mice. These deficits were rescued with ganaxolone, a positive modulator of GABAA receptors. Furthermore, we demonstrated that treatment with ganaxolone also ameliorated evocative memory deficits and repetitive behavior of Shank3 KO mice.

LIMITATIONS

Despite the significant findings of our study, some limitations remain. Firstly, the neurobiological mechanisms underlying the link between Shank3 deletion in PV neurons and behavioral alterations need further investigation. Additionally, the impact of Shank3 on other classes of inhibitory neurons requires further exploration. Finally, the pharmacological activity of ganaxolone needs further characterization to improve our understanding of its potential therapeutic effects.

CONCLUSIONS

Our study provides evidence that Shank3 deletion leads to an alteration in inhibitory feedback on cortical pyramidal neurons, resulting in cortical hyperexcitability and ASD-like behavioral problems. Specifically, cell type-specific deletion of Shank3 in PV neurons was associated with these behavioral deficits. Our findings suggest that ganaxolone may be a potential pharmacological approach for treating PMS, as it was able to rescue the behavioral deficits in Shank3 KO mice. Overall, our study highlights the importance of investigating the role of inhibitory neurons and potential therapeutic interventions in neurodevelopmental disorders such as PMS.

Lynx1 and the family of endogenous mammalian neurotoxin-like proteins and their roles in modulating nAChR function

The promise of nicotinic receptors as a therapeutic target has yet to be fully realized, despite solid data supporting their involvement in neurological and neuropsychiatric diseases. The reasons for this are likely complex and manifold, having to do with the widespread action of the cholinergic system and the biophysical mechanism of action of nicotinic receptors leading to fast desensitization and down-regulation. Conventional drug development strategies tend to focus on receptor subtype-specific action of candidate therapeutics, although the broad agonist, nicotine, is being explored in the clinic. The potential negative effects of nicotine make the search for alternate strategies warranted. Prototoxins are a promising yet little-explored avenue of nicotinic receptor drug development. Nicotinic receptors in the brain belong to a complex of proteins, including those that bind to the extracellular face of the receptor, as well as chaperones that bind the intracellular domain, etc. Lynx prototoxins have allosteric modularity effects on receptor function and number and have been implicated in complex in vivo processes such as neuroplasticity, learning, and memory. Their mechanism of action and binding specificity on sets of nAChR subtypes present intriguing possibilities for more efficacious and nuanced therapeutic targeting than nicotinic receptor subtypes alone. An allosteric drug may restrict its actions to physiologically relevant time points, which tend to be correlated with salient events which would be encoded into long-term memory storage. Rather than blanketing the brain with a steady and prolonged elevation of agonist, an allosteric nAChR compound could avoid side effects and loss of efficacy over time. This review details the potential strengths and challenges of prototoxin proteins as therapeutic targets, and some of the utility of such therapeutics based on the emerging understanding of cholinergic signaling in a growing number of complex neural processes.

Mecp2 deletion results in profound alterations of developmental and adult functional connectivity

As a regressive neurodevelopmental disorder with a well-established genetic cause, Rett syndrome and its Mecp2 loss-of-function mouse model provide an excellent opportunity to define potentially translatable functional signatures of disease progression, as well as offer insight into the role of Mecp2 in functional circuit development. Thus, we applied widefield optical fluorescence imaging to assess mesoscale calcium functional connectivity (FC) in the Mecp2 cortex both at postnatal day (P)35 in development and during the disease-related decline. We found that FC between numerous cortical regions was disrupted in Mecp2 mutant males both in juvenile development and early adulthood. Female Mecp2 mice displayed an increase in homotopic contralateral FC in the motor cortex at P35 but not in adulthood, where instead more posterior parietal regions were implicated. An increase in the amplitude of connection strength, both with more positive correlations and more negative anticorrelations, was observed across the male cortex in numerous functional regions. Widespread rescue of MeCP2 protein in GABAergic neurons rescued none of these functional deficits, nor, surprisingly, the expected male lifespan. Altogether, the female results identify early signs of disease progression, while the results in males indicate MeCP2 protein is required for typical FC in the brain.

Microglia-mediated synaptic pruning in the nucleus accumbens during adolescence: A preliminary study of the proteomic consequences and putative female-specific pruning target

Adolescence is a period of copious neural development, particularly in the 'reward' circuitry of the brain, and reward-related behavioral development, including social development. One neurodevelopmental mechanism that appears to be common across brain regions and developmental periods is the requirement for synaptic pruning to produce mature neural communication and circuits. We published that microglia-C3-mediated synaptic pruning also occurs in the nucleus accumbens (NAc) reward region during adolescence to mediate social development in male and female rats. However, both the adolescent stage in which microglial pruning occurred, and the synaptic pruning target, were sex specific. NAc pruning occurred between early and mid-adolescence in male rats to eliminate dopamine D1 receptors (D1rs), and between pre- and early adolescence in female rats (P20-30) to eliminate an unknown, non-D1r target. In this report, we sought to better understand the proteomic consequences of microglial pruning in the NAc, and what the female pruning target might be. To do this, we inhibited microglial pruning in the NAc during each sex's pruning period and collected tissue for mass spectrometry proteomic analysis and ELISA validation. We found that the proteomic consequences of inhibiting microglial pruning in the NAc were inversely proportional between the sexes, and a novel, female-specific pruning target may be Lynx1. Please note, if this preprint will be pushed further to publication it will not be by me (AMK), as I am leaving academia. So, I'm going to write more conversationally.

From pupil to the brain: New insights for studying cortical plasticity through pupillometry

Pupil size variations have been associated with changes in brain activity patterns related with specific cognitive factors, such as arousal, attention, and mental effort. The locus coeruleus (LC), a key hub in the noradrenergic system of the brain, is considered to be a key regulator of cognitive control on pupil size, with changes in pupil diameter corresponding to the release of norepinephrine (NE). Advances in eye-tracking technology and open-source software have facilitated accurate pupil size measurement in various experimental settings, leading to increased interest in using pupillometry to track the nervous system activation state and as a potential biomarker for brain disorders. This review explores pupillometry as a non-invasive and fully translational tool for studying cortical plasticity starting from recent literature suggesting that pupillometry could be a promising technique for estimating the degree of residual plasticity in human subjects. Given that NE is known to be a critical mediator of cortical plasticity and arousal, the review includes data revealing the importance of the LC-NE system in modulating brain plasticity and pupil size. Finally, we will review data suggesting that pupillometry could provide a quantitative and complementary measure of cortical plasticity also in pre-clinical studies.

The Impact of Artificial Intelligence in the Odyssey of Rare Diseases

Emerging machine learning (ML) technologies have the potential to significantly improve the research and treatment of rare diseases, which constitute a vast set of diseases that affect a small proportion of the total population. Artificial Intelligence (AI) algorithms can help to quickly identify patterns and associations that would be difficult or impossible for human analysts to detect. Predictive modeling techniques, such as deep learning, have been used to forecast the progression of rare diseases, enabling the development of more targeted treatments. Moreover, AI has also shown promise in the field of drug development for rare diseases with the identification of subpopulations of patients who may be most likely to respond to a particular drug. This review aims to highlight the achievements of AI algorithms in the study of rare diseases in the past decade and advise researchers on which methods have proven to be most effective. The review will focus on specific rare diseases, as defined by a prevalence rate that does not exceed 1-9/100,000 on Orphanet, and will examine which AI methods have been most successful in their study. We believe this review can guide clinicians and researchers in the successful application of ML in rare diseases.

Catecholaminergic and cholinergic neuromodulation in autism spectrum disorder: A comparison to attention-deficit hyperactivity disorder

Autism spectrum disorder (ASD) is a heterogeneous neurodevelopmental disorder characterized by social impairments and restricted, repetitive behaviors. Treatment of ASD is notoriously difficult and might benefit from identification of underlying mechanisms that overlap with those disturbed in other developmental disorders, for which treatment options are more obvious. One example of the latter is attention-deficit hyperactivity disorder (ADHD), given the efficacy of especially stimulants in treatment of ADHD. Deficiencies in catecholaminergic systems [dopamine (DA), norepinephrine (NE)] in ADHD are obvious targets for stimulant treatment. Recent findings suggest that dysfunction in catecholaminergic systems may also be a factor in at least a subgroup of ASD. In this review we scrutinize the evidence for catecholaminergic mechanisms underlying ASD symptoms, and also include in this analysis a third classic ascending arousing system, the acetylcholinergic (ACh) network. We complement this with a comprehensive review of DA-, NE-, and ACh-targeted interventions in ASD, and an exploratory search for potential treatment-response predictors (biomarkers) in ASD, genetically or otherwise. Based on this review and analysis we propose that (1) stimulant treatment may be a viable option for an ASD subcategory, possibly defined by genetic subtyping; (2) cerebellar dysfunction is pronounced for a relatively small ADHD subgroup but much more common in ASD and in both cases may point toward NE- or ACh-directed intervention; (3) deficiency of the cortical salience network is sizable in subgroups of both disorders, and biomarkers such as eye blink rate and pupillometric data may predict the efficacy of targeting this underlying deficiency via DA, NE, or ACh in both ASD and ADHD.

Behavioral impulsivity is associated with pupillary alterations and hyperactivity in CDKL5 mutant mice

Cyclin-dependent kinase-like 5 (Cdkl5) deficiency disorder (CDD) is a severe neurodevelopmental condition caused by mutations in the X-linked Cdkl5 gene. CDD is characterized by early-onset seizures in the first month of life, intellectual disability, motor and social impairment. No effective treatment is currently available and medical management is only symptomatic and supportive. Recently, mouse models of Cdkl5 disorder have demonstrated that mice lacking Cdkl5 exhibit autism-like phenotypes, hyperactivity and dysregulations of the arousal system, suggesting the possibility to use these features as translational biomarkers. In this study, we tested Cdkl5 male and female mutant mice in an appetitive operant conditioning chamber to assess cognitive and motor abilities, and performed pupillometry to assess the integrity of the arousal system. Then, we evaluated the performance of artificial intelligence models to classify the genotype of the animals from the behavioral and physiological phenotype. The behavioral results show that CDD mice display impulsivity, together with low levels of cognitive flexibility and perseverative behaviors. We assessed arousal levels by simultaneously recording pupil size and locomotor activity. Pupillometry reveals in CDD mice a smaller pupil size and an impaired response to unexpected stimuli associated with hyperlocomotion, demonstrating a global defect in arousal modulation. Finally, machine learning reveals that both behavioral and pupillometry parameters can be considered good predictors of CDD. Since early diagnosis is essential to evaluate treatment outcomes and pupillary measures can be performed easily, we proposed the monitoring of pupil size as a promising biomarker for CDD.

Role of Brain Modulators in Neurodevelopment: Focus on Autism Spectrum Disorder and Associated Comorbidities

Autism spectrum disorder (ASD) and associated neurodevelopmental disorders share similar pathogenesis and clinical features. Pathophysiological changes in these diseases are rooted in early neuronal stem cells in the uterus. Several genetic and environmental factors potentially perturb neurogenesis and synaptogenesis processes causing incomplete or altered maturation of the brain that precedes the symptomology later in life. In this review, the impact of several endogenous neuromodulators and pharmacological agents on the foetus during pregnancy, manifested on numerous aspects of neurodevelopment is discussed. Within this context, some possible insults that may alter these modulators and therefore alter their role in neurodevelopment are high-lighted. Sometimes, a particular insult could influence several neuromodulator systems as is supported by recent research in the field of ASD and associated disorders. Dopaminergic hy-pothesis prevailed on the table for discussion of the pathogenesis of schizophrenia (SCH), atten-tion-deficit hyperactivity disorder (ADHD) and ASD for a long time. However, recent cumulative evidence suggests otherwise. Indeed, the neuromodulators that are dysregulated in ASD and comorbid disorders are as diverse as the causes and symptoms of this disease. Additionally, these neuromodulators have roles in brain development, further complicating their involvement in comorbidity. This review will survey the current understanding of the neuromodulating systems to serve the pharmacological field during pregnancy and to minimize drug-related insults in pa-tients with ASD and associated comorbidity disorders, e.g., SCH or ADHD.

Improving clinical trial readiness to accelerate development of new therapeutics for Rett syndrome

Rett syndrome is associated with severe functional impairments and many comorbidities, each in urgent need of treatments. Mutations in the MECP2 gene were identified as causing Rett syndrome in 1999. Over the past 20 years there has been an abundance of preclinical research with some studies leading to human clinical trials. Despite this, few viable therapeutic options have emerged from this investment of effort. Reasons for this lack of success as they relate both to preclinical research and the clinical trial landscape are discussed. Considering what needs to be done to promote further success in the field, we take a positive and constructive approach and introduce the concept of clinical trial readiness and its necessary ingredients for Rett syndrome. These include: listening to the needs of families; support from advocacy groups; optimising use of existing clinic infrastructures and available natural history data; and, finally, the validation of existing outcome measures and/or the development and validation of new measures. We conclude by reiterating the need for a collaborative and coordinated approach amongst the many different stakeholder groups and the need to engage in new types of trial design which could be much more efficient, less costly and much less burdensome on families.

Capturing the complexity of autism: Applying a developmental cascades framework

Developmental change emerges from dynamic interactions among networks of neural activity, behavior systems, and experience-dependent processes. A developmental cascades framework captures the sequential, multilevel, cross-domain nature of human development and is ideal for demonstrating how interconnected systems have far-reaching effects in typical and atypical development. Neurodevelopmental disorders represent an intriguing application of this framework. Autism spectrum disorder (ASD) is complex and heterogeneous, with biological and behavioral features that cut across multiple developmental domains, including those that are motor, cognitive, sensory, and bioregulatory. Mapping developmental cascades in ASD can be transformational in elucidating how seemingly unrelated behaviors (e.g., those emerging at different points in development and occurring in multiple domains) are part of an interconnected neurodevelopmental pathway. In this article, we review evidence for specific developmental cascades implicated in ASD and suggest that theoretical and empirical advances in etiology and change mechanisms can be accelerated using a developmental cascades framework.

Transfer learning for non-image data in clinical research: A scoping review

BACKGROUND

Transfer learning is a form of machine learning where a pre-trained model trained on a specific task is reused as a starting point and tailored to another task in a different dataset. While transfer learning has garnered considerable attention in medical image analysis, its use for clinical non-image data is not well studied. Therefore, the objective of this scoping review was to explore the use of transfer learning for non-image data in the clinical literature.

METHODS AND FINDINGS

We systematically searched medical databases (PubMed, EMBASE, CINAHL) for peer-reviewed clinical studies that used transfer learning on human non-image data. We included 83 studies in the review. More than half of the studies (63%) were published within 12 months of the search. Transfer learning was most often applied to time series data (61%), followed by tabular data (18%), audio (12%) and text (8%). Thirty-three (40%) studies applied an image-based model to non-image data after transforming data into images (e.g. spectrograms). Twenty-nine (35%) studies did not have any authors with a health-related affiliation. Many studies used publicly available datasets (66%) and models (49%), but fewer shared their code (27%).

CONCLUSIONS

In this scoping review, we have described current trends in the use of transfer learning for non-image data in the clinical literature. We found that the use of transfer learning has grown rapidly within the last few years. We have identified studies and demonstrated the potential of transfer learning in clinical research in a wide range of medical specialties. More interdisciplinary collaborations and the wider adaption of reproducible research principles are needed to increase the impact of transfer learning in clinical research.

Artificial intelligence-driven phenotyping of zebrafish psychoactive drug responses

Zebrafish (Danio rerio) are rapidly emerging in biomedicine as promising tools for disease modelling and drug discovery. The use of zebrafish for neuroscience research is also growing rapidly, necessitating novel reliable and unbiased methods of neurophenotypic data collection and analyses. Here, we applied the artificial intelligence (AI) neural network-based algorithms to a large dataset of adult zebrafish locomotor tracks collected previously in a series of in vivo experiments with multiple established psychotropic drugs. We first trained AI to recognize various drugs from a wide range of psychotropic agents tested, and then confirmed prediction accuracy of trained AI by comparing several agents with known similar behavioral and pharmacological profiles. Presenting a framework for innovative neurophenotyping, this proof-of-concept study aims to improve AI-driven movement pattern classification in zebrafish, thereby fostering drug discovery and development utilizing this key model organism.

Electrophysiological biomarkers of brain function in CDKL5 deficiency disorder

CDKL5 deficiency disorder is a debilitating developmental and epileptic encephalopathy for which no targeted treatment exists. A number of promising therapeutics are under development for CDKL5 deficiency disorder but a lack of validated biomarkers of brain function and clinical severity may limit the ability to objectively assess the efficacy of new treatments as they become available. To address this need, the current study quantified electrophysiological measures in individuals with CDKL5 deficiency disorder and the association between these parameters and clinical severity. Visual and auditory evoked potentials, as well as resting EEG, were acquired across 5 clinical sites from 26 individuals with CDKL5 deficiency disorder. Evoked potential and quantitative EEG features were calculated and compared with typically developing individuals in an age- and sex-matched cohort. Baseline and Year 1 data, when available, were analysed and the repeatability of the results was tested. Two clinician-completed severity scales were used for evaluating the clinical relevance of the electrophysiological parameters. Group-level comparisons revealed reduced visual evoked potential amplitude in CDKL5 deficiency disorder individuals versus typically developing individuals. There were no group differences in the latency of the visual evoked potentials or in the latency or amplitude of the auditory evoked potentials. Within the CDKL5 deficiency disorder group, auditory evoked potential amplitude correlated with disease severity at baseline as well as Year 1. Multiple quantitative EEG features differed between CDKL5 deficiency disorder and typically developing participants, including amplitude standard deviation, 1/f slope and global delta, theta, alpha and beta power. Several quantitative EEG features correlated with clinical severity, including amplitude skewness, theta/delta ratio and alpha/delta ratio. The theta/delta ratio was the overall strongest predictor of severity and also among the most repeatable qEEG measures from baseline to Year 1. Together, the present findings point to the utility of evoked potentials and quantitative EEG parameters as objective measures of brain function and disease severity in future clinical trials for CDKL5 deficiency disorder. The results also underscore the utility of the current methods, which could be similarly applied to the identification and validation of electrophysiological biomarkers of brain function for other developmental encephalopathies.

Differential Expression Patterns of Lynx Proteins and Involvement of Lynx1 in Prepulse Inhibition

Negative allosteric modulators, such as lynx1 and lynx2, directly interact with nicotinic acetylcholine receptors (nAChRs). The nAChRs are integral to cholinergic signaling in the brain and have been shown to mediate different aspects of cognitive function. Given the interaction between lynx proteins and these receptors, we examined whether these endogenous negative allosteric modulators are involved in cognitive behaviors associated with cholinergic function. We found both cell-specific and overlapping expression patterns of lynx1 and lynx2 mRNA in brain regions associated with cognition, learning, memory, and sensorimotor processing, including the prefrontal cortex (PFC), cingulate cortex, septum, hippocampus, amygdala, striatum, and pontine nuclei. Since lynx proteins are thought to play a role in conditioned associations and given the expression patterns across brain regions, we first assessed whether lynx knockout mice would differ in a cognitive flexibility task. We found no deficits in reversal learning in either the lynx1^–/– or lynx2^–/– knockout mice. Thereafter, sensorimotor gating was examined with the prepulse inhibition (PPI) assessment. Interestingly, we found that both male and female lynx1^–/– mice exhibited a deficit in the PPI behavioral response. Given the comparable expression of lynx2 in regions involved in sensorimotor gating, we then examined whether removal of the lynx2 protein would lead to similar behavioral effects. Unexpectedly, we found that while male lynx2^–/– mice exhibited a decrease in the baseline startle response, no differences were found in sensorimotor gating for either male or female lynx2^–/– mice. Taken together, these studies provide insight into the expression patterns of lynx1 and lynx2 across multiple brain regions and illustrate the modulatory effects of the lynx1 protein in sensorimotor gating.

Dynamical Characteristics of Wild-Type Mouse Spontaneous Pupillary Fluctuations. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2021;2021:853-856. [PMID: 34891424 DOI: 10.1109/embc46164.2021.9630747] [Citation(s) in RCA: 0] [Impact Index Per Article: 0]

Spontaneous pupil size fluctuations in humans and mouse models are noninvasively measured data that can be used for early detection of neurodevelopmental spectrum disorders. While highly valuable in such applied studies, pupillometry dynamics and dynamical characteristics have not been fully investigated, although their understanding may potentially lead to the discovery of new information, which cannot be readily uncovered by conventional methods. Properties of pupillometry dynamics, such as determinism, were previously investigated for healthy human subjects; however, the dynamical characteristics of pupillometry data in mouse models, and whether they are similar to those of human subjects, remain largely unknown. Therefore, it is necessary to establish a thorough understanding of the dynamical properties of mouse pupillometry dynamics and to clarify whether it is similar to that of humans. In this study, dynamical pupillometry characteristics from 115 wild-type mouse datasets were investigated by methods of nonlinear time series analysis. Results clearly demonstrated a strong underlying determinism in the investigated data. Additionally, the data's trajectory divergence rate and predictability were estimated.

MEYE: Web App for Translational and Real-Time Pupillometry

Pupil dynamics alterations have been found in patients affected by a variety of neuropsychiatric conditions, including autism. Studies in mouse models have used pupillometry for phenotypic assessment and as a proxy for arousal. Both in mice and humans, pupillometry is noninvasive and allows for longitudinal experiments supporting temporal specificity; however, its measure requires dedicated setups. Here, we introduce a convolutional neural network that performs online pupillometry in both mice and humans in a web app format. This solution dramatically simplifies the usage of the tool for the nonspecialist and nontechnical operators. Because a modern web browser is the only software requirement, this choice is of great interest given its easy deployment and setup time reduction. The tested model performances indicate that the tool is sensitive enough to detect both locomotor-induced and stimulus-evoked pupillary changes, and its output is comparable to state-of-the-art commercial devices.

The promise of precision medicine in autism

Autism spectrum disorder (ASD) is a clinically and etiologically diverse developmental condition characterized by diminished social interactions, impaired communication, and repetitive and/or restrictive behaviors. Recent advances in ASD genetics pave the way for implementation of precision medicine in clinical management of autism.

DeepLearnMOR: a deep-learning framework for fluorescence image-based classification of organelle morphology

The proper biogenesis, morphogenesis, and dynamics of subcellular organelles are essential to their metabolic functions. Conventional techniques for identifying, classifying, and quantifying abnormalities in organelle morphology are largely manual and time-consuming, and require specific expertise. Deep learning has the potential to revolutionize image-based screens by greatly improving their scope, speed, and efficiency. Here, we used transfer learning and a convolutional neural network (CNN) to analyze over 47,000 confocal microscopy images from Arabidopsis wild-type and mutant plants with abnormal division of one of three essential energy organelles: chloroplasts, mitochondria, or peroxisomes. We have built a deep-learning framework, DeepLearnMOR (Deep Learning of the Morphology of Organelles), which can rapidly classify image categories and identify abnormalities in organelle morphology with over 97% accuracy. Feature visualization analysis identified important features used by the CNN to predict morphological abnormalities, and visual clues helped to better understand the decision-making process, thereby validating the reliability and interpretability of the neural network. This framework establishes a foundation for future larger-scale research with broader scopes and greater data set diversity and heterogeneity.

Identification of attention-deficit hyperactivity disorder based on the complexity and symmetricity of pupil diameter

Adult attention-deficit/hyperactivity disorder (ADHD) frequently leads to psychological/social dysfunction if unaddressed. Identifying a reliable biomarker would assist the diagnosis of adult ADHD and ensure that adults with ADHD receive treatment. Pupil diameter can reflect inherent neural activity and deficits of attention or arousal characteristic of ADHD. Furthermore, distinct profiles of the complexity and symmetricity of neural activity are associated with some psychiatric disorders. We hypothesized that analysing the relationship between the size, complexity of temporal patterns, and asymmetricity of pupil diameters will help characterize the nervous systems of adults with ADHD and that an identification method combining these features would ease the diagnosis of adult ADHD. To validate this hypothesis, we evaluated the resting state hippus in adult participants with or without ADHD by examining the pupil diameter and its temporal complexity using sample entropy and the asymmetricity of the left and right pupils using transfer entropy. We found that large pupil diameters and low temporal complexity and symmetry were associated with ADHD. Moreover, the combination of these factors by the classifier enhanced the accuracy of ADHD identification. These findings may contribute to the development of tools to diagnose adult ADHD.

Pupillometric Complexity and Symmetricity Follow Inverted-U Curves Against Baseline Diameter Due to Crossed Locus Coeruleus Projections to the Edinger-Westphal Nucleus

In addition to photic reflex function, the temporal behavior of the pupil diameter reflects levels of arousal and attention and thus internal cognitive neural activity. Recent studies have reported that these behaviors are characterized by baseline activity, temporal complexity, and symmetricity (i.e., degree of symmetry) between the right and left pupil diameters. We hypothesized that experimental analysis to reveal relationships among these characteristics and model-based analysis focusing on the newly discovered contralateral projection from the locus coeruleus (LC) to the Edinger-Westphal nucleus (EWN) within the neural system for controlling pupil diameter could contribute to another dimension of understanding of complex pupil dynamics. In this study, we aimed to validate our hypothesis by analyzing the pupillary hippus in the healthy resting state in terms of sample entropy (SampEn), to capture complexity, and transfer entropy (TranEn), to capture symmetricity. We also constructed a neural model embedded with the new findings on neural pathways. The following results were observed: first, according to surrogate data analysis, the complexity and symmetricity of pupil diameter changes reflect a non-linear deterministic process. Second, both the complexity and the symmetricity are unimodal, peaking at intermediate pupil diameters. Third, according to simulation results, the neural network that controls pupil diameter has an inverted U-shaped profile of complexity and symmetricity vs. baseline LC activity; this tendency is enhanced by the contralateral synaptic projections from the LCs to the EWNs. Thus, we characterized the typical relationships between the baseline activity and the complexity and symmetricity of the pupillometric data in terms of SampEn and TranEn. Our evaluation method and findings may facilitate the development of estimation and diagnostic tools for exploring states of the healthy brain and psychiatric disorders based on measurements of pupil diameter.

Nicotinic regulation of local and long-range input balance drives top-down attentional circuit maturation

Cognitive function depends on frontal cortex development; however, the mechanisms driving this process are poorly understood. Here, we identify that dynamic regulation of the nicotinic cholinergic system is a key driver of attentional circuit maturation associated with top-down frontal neurons projecting to visual cortex. The top-down neurons receive robust cholinergic inputs, but their nicotinic tone decreases following adolescence by increasing expression of a nicotinic brake, Lynx1 Lynx1 shifts a balance between local and long-range inputs onto top-down frontal neurons following adolescence and promotes the establishment of attentional behavior in adulthood. This key maturational process is disrupted in a mouse model of fragile X syndrome but was rescued by a suppression of nicotinic tone through the introduction of Lynx1 in top-down projections. Nicotinic signaling may serve as a target to rebalance local/long-range balance and treat cognitive deficits in neurodevelopmental disorders.

Pupillometry as a reliable metric of auditory detection and discrimination across diverse stimulus paradigms in animal models

Estimates of detection and discrimination thresholds are often used to explore broad perceptual similarities between human subjects and animal models. Pupillometry shows great promise as a non-invasive, easily-deployable method of comparing human and animal thresholds. Using pupillometry, previous studies in animal models have obtained threshold estimates to simple stimuli such as pure tones, but have not explored whether similar pupil responses can be evoked by complex stimuli, what other stimulus contingencies might affect stimulus-evoked pupil responses, and if pupil responses can be modulated by experience or short-term training. In this study, we used an auditory oddball paradigm to estimate detection and discrimination thresholds across a wide range of stimuli in guinea pigs. We demonstrate that pupillometry yields reliable detection and discrimination thresholds across a range of simple (tones) and complex (conspecific vocalizations) stimuli; that pupil responses can be robustly evoked using different stimulus contingencies (low-level acoustic changes, or higher level categorical changes); and that pupil responses are modulated by short-term training. These results lay the foundation for using pupillometry as a reliable method of estimating thresholds in large experimental cohorts, and unveil the full potential of using pupillometry to explore broad similarities between humans and animal models.

Genes and environments, development and time

A now substantial body of science implicates a dynamic interplay between genetic and environmental variation in the development of individual differences in behavior and health. Such outcomes are affected by molecular, often epigenetic, processes involving gene-environment (G-E) interplay that can influence gene expression. Early environments with exposures to poverty, chronic adversities, and acutely stressful events have been linked to maladaptive development and compromised health and behavior. Genetic differences can impart either enhanced or blunted susceptibility to the effects of such pathogenic environments. However, largely missing from present discourse regarding G-E interplay is the role of time, a "third factor" guiding the emergence of complex developmental endpoints across different scales of time. Trajectories of development increasingly appear best accounted for by a complex, dynamic interchange among the highly linked elements of genes, contexts, and time at multiple scales, including neurobiological (minutes to milliseconds), genomic (hours to minutes), developmental (years and months), and evolutionary (centuries and millennia) time. This special issue of PNAS thus explores time and timing among G-E transactions: The importance of timing and timescales in plasticity and critical periods of brain development; epigenetics and the molecular underpinnings of biologically embedded experience; the encoding of experience across time and biological levels of organization; and gene-regulatory networks in behavior and development and their linkages to neuronal networks. Taken together, the collection of papers offers perspectives on how G-E interplay operates contingently within and against a backdrop of time and timescales.

Circuitry Underlying Experience-Dependent Plasticity in the Mouse Visual System

Since the discovery of ocular dominance plasticity, neuroscientists have understood that changes in visual experience during a discrete developmental time, the critical period, trigger robust changes in the visual cortex. State-of-the-art tools used to probe connectivity with cell-type-specific resolution have expanded the understanding of circuit changes underlying experience-dependent plasticity. Here, we review the visual circuitry of the mouse, describing projections from retina to thalamus, between thalamus and cortex, and within cortex. We discuss how visual circuit development leads to precise connectivity and identify synaptic loci, which can be altered by activity or experience. Plasticity extends to visual features beyond ocular dominance, involving subcortical and cortical regions, and connections between cortical inhibitory interneurons. Experience-dependent plasticity contributes to the alignment of networks spanning retina to thalamus to cortex. Disruption of this plasticity may underlie aberrant sensory processing in some neurodevelopmental disorders.

The Role of Nicotinic Receptors in the Attenuation of Autism-Related Behaviors in a Murine BTBR T + tf/J Autistic Model

Nicotinic receptors are distributed throughout the central and peripheral nervous system. Postmortem studies have reported that some nicotinic receptor subtypes are altered in the brains of autistic people. Recent studies have demonstrated the importance of nicotinic acetylcholine receptors (nAChRs) in the autistic behavior of BTBR T + tf/J mouse model of autism. This study was undertaken to examine the behavioral effects of targeted nAChRs using pharmacological ligands, including nicotine and mecamylamine in BTBR T + tf/J and C57BL/6J mice in a panel of behavioral tests relating to autism. These behavioral tests included the three-chamber social interaction, self-grooming, marble burying, locomotor activity, and rotarod test. We examined the effect of various oral doses of nicotine (50, 100, and 400 mcg/mL; po) over a period of 2 weeks in BTBR T + tf/J mouse model. The results indicated that the chronic administration of nicotine modulated sociability and repetitive behavior in BTBR T + tf/J mice while no effects observed in C57BL/6J mice. Furthermore, the nonselective nAChR antagonist, mecamylamine, reversed nicotine effects on sociability and increased repetitive behaviors in BTBR T + tf/J mice. Overall, the findings indicate that the pharmacological modulation of nicotinic receptors is involved in modulating core behavioral phenotypes in the BTBR T + tf/J mouse model. LAY SUMMARY: The involvement of brain nicotinic neurotransmission system plays a crucial role in regulating autism-related behavioral features. In addition, the brain of the autistic-like mouse model has a low acetylcholine level. Here, we report that nicotine, at certain doses, improved sociability and reduced repetitive behaviors in a mouse model of autism, implicating the potential therapeutic values of a pharmacological intervention targeting nicotinic receptors for autism therapy. Autism Res 2020, 13: 1311-1334. © 2020 International Society for Autism Research, Wiley Periodicals, Inc.

Evoked Potentials and EEG Analysis in Rett Syndrome and Related Developmental Encephalopathies: Towards a Biomarker for Translational Research

Rett syndrome is a debilitating neurodevelopmental disorder for which no disease-modifying treatment is available. Fortunately, advances in our understanding of the genetics and pathophysiology of Rett syndrome has led to the development of promising new therapeutics for the condition. Several of these therapeutics are currently being tested in clinical trials with others likely to progress to clinical trials in the coming years. The failure of recent clinical trials for Rett syndrome and other neurodevelopmental disorders has highlighted the need for electrophysiological or other objective biological markers of treatment response to support the success of clinical trials moving forward. The purpose of this review is to describe the existing studies of electroencephalography (EEG) and evoked potentials (EPs) in Rett syndrome and discuss the open questions that must be addressed before the field can adopt these measures as surrogate endpoints in clinical trials. In addition to summarizing the human work on Rett syndrome, we also describe relevant studies with animal models and the limited research that has been carried out on Rett-related disorders, particularly methyl-CpG binding protein 2 (MECP2) duplication syndrome, CDKL5 deficiency disorder, and FOXG1 disorder.

Intellectual and Developmental Disabilities Research Centers: A Multidisciplinary Approach to Understand the Pathogenesis of Methyl-CpG Binding Protein 2-related Disorders

Disruptions in the gene encoding methyl-CpG binding protein 2 (MECP2) underlie complex neurodevelopmental disorders including Rett Syndrome (RTT), MECP2 duplication disorder, intellectual disabilities, and autism. Significant progress has been made on the molecular and cellular basis of MECP2-related disorders providing a new framework for understanding how altered epigenetic landscape can derail the formation and refinement of neuronal circuits in early postnatal life and proper neurological function. This review will summarize selected major findings from the past years and particularly highlight the integrated and multidisciplinary work done at eight NIH-funded Intellectual and Developmental Disabilities Research Centers (IDDRC) across the US. Finally, we will outline a path forward with identification of reliable biomarkers and outcome measures, longitudinal preclinical and clinical studies, reproducibility of results across centers as a synergistic effort to decode and treat the pathogenesis of the complex MeCP2 disorders.