Automated Quantification of Eye Tics Using Computer Vision and Deep Learning Techniques.

BACKGROUND: Tourette syndrome (TS) tics are typically quantified using "paper and pencil" rating scales that are susceptible to factors that adversely impact validity. Video-based methods to more objectively quantify tics have been developed but are challenged by reliance on human raters and procedures that are resource intensive. Computer vision approaches that automate detection of atypical movements may be useful to apply to tic quantification. OBJECTIVE: The current proof-of-concept study applied a computer vision approach to train a supervised deep learning algorithm to detect eye tics in video, the most common tic type in patients with TS. METHODS: Videos (N = 54) of 11 adolescent patients with TS were rigorously coded by trained human raters to identify 1.5-second clips depicting "eye tic events" (N = 1775) and "non-tic events" (N = 3680). Clips were encoded into three-dimensional facial landmarks. Supervised deep learning was applied to processed data using random split and disjoint split regimens to simulate model validity under different conditions. RESULTS: Area under receiver operating characteristic curve was 0.89 for the random split regimen, indicating high accuracy in the algorithm's ability to properly classify eye tic vs. non-eye tic movements. Area under receiver operating characteristic curve was 0.74 for the disjoint split regimen, suggesting that algorithm generalizability is more limited when trained on a small patient sample. CONCLUSIONS: The algorithm was successful in detecting eye tics in unseen validation sets. Automated tic detection from video is a promising approach for tic quantification that may have future utility in TS screening, diagnostics, and treatment outcome measurement. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Monoallelic and biallelic mutations in RELN underlie a graded series of neurodevelopmental disorders.

Reelin, a large extracellular protein, plays several critical roles in brain development and function. It is encoded by RELN, first identified as the gene disrupted in the reeler mouse, a classic neurological mutant exhibiting ataxia, tremors and a 'reeling' gait. In humans, biallelic variants in RELN have been associated with a recessive lissencephaly variant with cerebellar hypoplasia, which matches well with the homozygous mouse mutant that has abnormal cortical structure, small hippocampi and severe cerebellar hypoplasia. Despite the large size of the gene, only 11 individuals with RELN-related lissencephaly with cerebellar hypoplasia from six families have previously been reported. Heterozygous carriers in these families were briefly reported as unaffected, although putative loss-of-function variants are practically absent in the population (probability of loss of function intolerance = 1). Here we present data on seven individuals from four families with biallelic and 13 individuals from seven families with monoallelic (heterozygous) variants of RELN and frontotemporal or temporal-predominant lissencephaly variant. Some individuals with monoallelic variants have moderate frontotemporal lissencephaly, but with normal cerebellar structure and intellectual disability with severe behavioural dysfunction. However, one adult had abnormal MRI with normal intelligence and neurological profile. Thorough literature analysis supports a causal role for monoallelic RELN variants in four seemingly distinct phenotypes including frontotemporal lissencephaly, epilepsy, autism and probably schizophrenia. Notably, we observed a significantly higher proportion of loss-of-function variants in the biallelic compared to the monoallelic cohort, where the variant spectrum included missense and splice-site variants. We assessed the impact of two canonical splice-site variants observed as biallelic or monoallelic variants in individuals with moderately affected or normal cerebellum and demonstrated exon skipping causing in-frame loss of 46 or 52 amino acids in the central RELN domain. Previously reported functional studies demonstrated severe reduction in overall RELN secretion caused by heterozygous missense variants p.Cys539Arg and p.Arg3207Cys associated with lissencephaly suggesting a dominant-negative effect. We conclude that biallelic variants resulting in complete absence of RELN expression are associated with a consistent and severe phenotype that includes cerebellar hypoplasia. However, reduced expression of RELN remains sufficient to maintain nearly normal cerebellar structure. Monoallelic variants are associated with incomplete penetrance and variable expressivity even within the same family and may have dominant-negative effects. Reduced RELN secretion in heterozygous individuals affects only cortical structure whereas the cerebellum remains intact. Our data expand the spectrum of RELN-related neurodevelopmental disorders ranging from lethal brain malformations to adult phenotypes with normal brain imaging.

Long term effects of chronic intranasal oxytocin on adult pair bonding behavior and brain glucose uptake in titi monkeys (Plecturocebus cupreus).

Intranasal oxytocin (IN OXT) administration has been proposed as a pharmacological treatment for a range of biomedical conditions including neurodevelopmental disorders. However, studies evaluating the potential long-lasting effects of chronic IN OXT during development are still scarce. Here we conducted a follow-up study of a cohort of adult titi monkeys that received intranasal oxytocin 0.8 IU/kg (n = 15) or saline (n = 14) daily for six months during their juvenile period (12 to 18 months of age), with the goal of evaluating the potential long-lasting behavioral and neural effects one year post-treatment. Subjects were paired with an opposite-sex mate at 30 months of age (one year post-treatment). We examined pair affiliative behavior in the home cage during the first four months and tested for behavioral components of pair bonding at one week and four months post-pairing. We assessed long-term changes in brain glucose uptake using 18FDG positron emission tomography (PET) scans. Our results showed that OXT-treated animals were more affiliative across a number of measures, including tail twining, compared to SAL treated subjects (tail twining is considered the "highest" type of affiliation in titi monkeys). Neuroimaging showed no treatment differences in glucose uptake between SAL and OXT-treated animals; however, females showed higher glucose uptake in whole brain at 23 months, and in both the whole brain and the social salience network at 33 months of age compared to males. Our results suggest that chronic IN OXT administration during development can have long-term effects on adult social behavior.

Phenoscreening: a developmental approach to research domain criteria-motivated sampling.

BACKGROUND: To advance early identification efforts, we must detect and characterize neurodevelopmental sequelae of risk among population-based samples early in development. However, variability across the typical-to-atypical continuum and heterogeneity within and across early emerging psychiatric/neurodevelopmental disorders represent fundamental challenges to overcome. Identifying multidimensionally determined profiles of risk, agnostic to DSM categories, via data-driven computational approaches represents an avenue to improve early identification of risk. METHODS: Factor mixture modeling (FMM) was used to identify subgroups and characterize phenotypic risk profiles, derived from multiple parent-report measures of typical and atypical behaviors common to autism spectrum disorder, in a community-based sample of 17- to 25-month-old toddlers (n = 1,570). To examine the utility of risk profile classification, a subsample of toddlers (n = 107) was assessed on a distal, independent outcome examining internalizing, externalizing, and dysregulation at approximately 30 months. RESULTS: FMM results identified five asymmetrically sized subgroups. The putative high- and moderate-risk groups comprised 6% of the sample. Follow-up analyses corroborated the utility of the risk profile classification; the high-, moderate-, and low-risk groups were differentially stratified (i.e., HR > moderate-risk > LR) on outcome measures and comparison of high- and low-risk groups revealed large effect sizes for internalizing (d = 0.83), externalizing (d = 1.39), and dysregulation (d = 1.19). CONCLUSIONS: This data-driven approach yielded five subgroups of toddlers, the utility of which was corroborated by later outcomes. Data-driven approaches, leveraging multiple developmentally appropriate dimensional RDoC constructs, hold promise for future efforts aimed toward early identification of at-risk-phenotypes for a variety of early emerging neurodevelopmental disorders.

The journey to autism: Insights from neuroimaging studies of infants and toddlers.

By definition, autism spectrum disorder (ASD) is a neurodevelopmental disorder that emerges during early childhood. It is during this time that infants and toddlers transition from appearing typical across multiple domains to exhibiting the behavioral phenotype of ASD. Neuroimaging studies focused on this period of development have provided crucial knowledge pertaining to this process, including possible mechanisms underlying pathogenesis of the disorder and offering the possibility of prodromal or presymptomatic prediction of risk. In this paper, we review findings from structural and functional brain imaging studies of ASD focused on the first years of life and discuss implications for next steps in research and clinical applications.

Escitalopram pharmacogenetics: CYP2C19 relationships with dosing and clinical outcomes in autism spectrum disorder.

BACKGROUND AND AIM: Selective serotonin reuptake inhibitors such as escitalopram are commonly used to treat patients with autism spectrum disorder (ASD), but there are individual differences in treatment response and tolerability. CYP2C19 encodes the primary enzyme responsible for escitalopram metabolism and we investigated whether polymorphisms in CYP2C19 were related to symptoms and dosing in a pharmacogenetic study of ASD. PARTICIPANTS AND METHODS: Participants completed the Aberrant Behavior Checklist--Community Version (ABC-CV) weekly for 6 weeks. Escitalopram was initiated at a dose of 2.5 mg per day, with weekly increases to 20 mg unless intolerable side-effects occurred. Three CYP2C19 metabolizer groups, including ultrarapid, extensive, and reduced metabolizers, were examined in relation to symptom improvement and tolerated dose. RESULTS: ABC-CV scores improved over the course of treatment (P<0.0001). No differences were identified in the rate of improvement across metabolizer groups for the ABC-CV irritability subscale, which was the primary outcome for clinical symptoms. There was a trend for a metabolizer group by time interaction with respect to dose (P=0.10). This interaction was driven by the linear rate of change from week 1 to study endpoint between the reduced metabolizers and ultrarapid metabolizer groups (P=0.05). Post-hoc analyses identified significant differences in the rate of dose escalation between ultrarapid metabolizers and extensive metabolizers and for ultrarapid metabolizers compared with reduced metabolizers (P's<0.04), whereby ultrarapid metabolizers showed a slower rate of change in dose over time. CONCLUSION: CYP2C19 ultrarapid metabolizers were associated with reduced tolerance to a fixed titration schedule of open-label escitalopram in this ASD study sample. Possible explanations may involve the altered kinetics of faster metabolizers or previously unknown activities of escitalopram metabolites.

Individual common variants exert weak effects on the risk for autism spectrum disorders.

While it is apparent that rare variation can play an important role in the genetic architecture of autism spectrum disorders (ASDs), the contribution of common variation to the risk of developing ASD is less clear. To produce a more comprehensive picture, we report Stage 2 of the Autism Genome Project genome-wide association study, adding 1301 ASD families and bringing the total to 2705 families analysed (Stages 1 and 2). In addition to evaluating the association of individual single nucleotide polymorphisms (SNPs), we also sought evidence that common variants, en masse, might affect the risk. Despite genotyping over a million SNPs covering the genome, no single SNP shows significant association with ASD or selected phenotypes at a genome-wide level. The SNP that achieves the smallest P-value from secondary analyses is rs1718101. It falls in CNTNAP2, a gene previously implicated in susceptibility for ASD. This SNP also shows modest association with age of word/phrase acquisition in ASD subjects, of interest because features of language development are also associated with other variation in CNTNAP2. In contrast, allele scores derived from the transmission of common alleles to Stage 1 cases significantly predict case status in the independent Stage 2 sample. Despite being significant, the variance explained by these allele scores was small (Vm< 1%). Based on results from individual SNPs and their en masse effect on risk, as inferred from the allele score results, it is reasonable to conclude that common variants affect the risk for ASD but their individual effects are modest.

Oxytocin and its links through scientific lineage.

Scientific inquiry and methodology are based on third person objectivity. Yet, as humans we experience everything through our first-person lens and second-person relational learning. The purpose of this review is to share the journey of discoveries about science and oxytocin from this author's unique and diverse perspective. Hormones are signaling molecules and long distant messengers required to regulate an organism's physiology and behavior. Oxytocin has taken the lead as the most investigated neurohormone that modulates social cognition, influences parenting behaviors, facilitates within or across-species bonding, and even biologically buffers against stressors such as isolation. Our increasing understanding that social connection, community belonging, and trust in others influence both physical and mental health outcomes, has led to numerous intervention and treatment oxytocin studies across a myriad of conditions. No longer just a way to facilitate female reproduction and lactation, oxytocin is now viewed as the "social influencer" that affects not just women but also men along with its closely related neurohormone, vasopressin. This review uses the narrative lens to illustrate how scientific lineage shapes what we study and how investigating oxytocin has been a microcosm to macrocosm metaphor for our collective social learning as a scientific community.

Traffic coordination by reducing jamming attackers in VANET using probabilistic Manhattan Grid Topology for automobile applications.

In recent years Intelligent Transportation System (ITS) has been growing interest in the development of vehicular communication technology. The traffic in India shows considerable fluctuations owing to the static and dynamic characteristics of road vehicles in VANET (Vehicular Adhoc Network). These vehicles take up a convenient side lane position on the road, disregarding lane discipline. They utilize the opposing lane to overtake slower-moving vehicles, even when there are oncoming vehicles approaching. The primary objective of this study is to minimize injuries resulting from vehicle interactions in mixed traffic conditions on undivided roads. This is achieved through the implementation of the Modified Manhattan grid topology, which primarily serves to guide drivers in the correct path when navigating undivided roads. Furthermore, the Fuzzy C-Means algorithm (FCM) is applied to detect potential jamming attackers, while the Modified Fisheye State Routing (MFSR) Algorithm is employed to minimize the amount of information exchanged among vehicles. Subsequently, the Particle Swarm Optimization (PSO) algorithm is developed to enhance the accuracy of determining the coordinates of jamming attackers within individual clusters. The effectiveness of the outcomes is affirmed through the utilization of the Fuzzy C-Means algorithm, showcasing a notable 30% reduction in the number of attackers, along with the attainment of a 70% accuracy rate in this research endeavor.

Comparison of behavioral profiles for anxiety-related comorbidities including ADHD and selective mutism in children.

BACKGROUND: Elucidating differences in social-behavioral profiles of children with comorbid presentations, utilizing caregiver as well as teacher reports, will refine our understanding of how contextual symptoms vary across anxiety-related disorders. METHODS: In our pediatric anxiety clinic, the most frequent diagnoses and comorbidities were mixed anxiety (MA; ≥ 1 anxiety disorder; N = 155), anxiety with comorbid attention-deficit hyperactivity disorder (MA/ADHD, N = 47) and selective mutism (SM, N = 48). Behavioral measures (CPRS, CTRS) were analyzed using multiple one-way multivariate analyses of covariance tests. Differences between the three diagnostic groups were examined using completed parent and teacher reports (N = 135, 46, and 48 for MA, MA/ADHD, and SM groups, respectively). RESULTS: Comparisons across the MA, MA/ADHD, and SM groups indicate a significant multivariate main effect of group for caregiver and teacher responses (P < 0.01). Caregivers reported that children with SM are similar in profile to those with MA, and both groups were significantly different from the MA/ADHD group. Teachers reported that children with SM had more problems with social behaviors than with the MA or MA/ADHD groups. Further comparison indicates a significant main effect of group (P < 0.001), such that children with SM have the greatest differences in behavior observed by teachers versus caregivers. CONCLUSIONS: Clinical profiles between MA/ADHD, MA, and SM groups varied, illustrating the importance of multi-rater assessment scales to capture subtle distinctions and to inform treatment planning given that comorbidities occur frequently in children who present with anxiety.

Paternally inherited HLA alleles are associated with women's choice of male odor.

The major histocompatibility complex (MHC) is a source of unique individual odors that influence individual recognition, mating preferences, nesting behavior and selective block of pregnancy in animals. Such phenomena have been difficult to study in humans, because the human leukocyte antigen (HLA, human MHC) loci are the most polymorphic loci in the human genome, with the potential to generate millions of unique combinations of genotypes. In addition, high variability in background odors, encoded by the rest of the genome and influenced by cultural practices, contribute to a low signal-to-noise ratio that could mask HLA-based olfactory cues. Here we show that women can detect differences of one HLA allele among male odor donors with different MHC genotypes. Notably, the mechanism for a woman's ability to discriminate and choose odors is based on HLA alleles inherited from her father but not her mother. The parents' HLA alleles that she does not inherit show no relationship with odor choice, despite exposure to these HLA-encoded odors throughout her life. Our data indicate that paternally inherited HLA-associated odors influence odor preference and may serve as social cues.

Auditory Domain Sensitivity and Neuroplasticity-Based Targeted Cognitive Training in Autism Spectrum Disorder.

Sensory processing, along with the integration of external inputs into stable representations of the environment, is integral to social cognitive functioning; challenges in these processes have been reported in Autism Spectrum Disorder (ASD) since the earliest descriptions of autism. Recently, neuroplasticity-based targeted cognitive training (TCT) has shown promise as an approach to improve functional impairments in clinical patients. However, few computerized and adaptive brain-based programs have been trialed in ASD. For individuals with sensory processing sensitivities (SPS), the inclusion of some auditory components in TCT protocols may be aversive. Thus, with the goal of developing a web-based, remotely accessible intervention that incorporates SPS concerns in the auditory domain, we assessed auditory SPS in autistic adolescents and young adults (N = 25) who started a novel, computerized auditory-based TCT program designed to improve working memory and information processing speed and accuracy. We found within-subject gains across the training program and between pre/post-intervention assessments. We also identified auditory, clinical, and cognitive characteristics that are associated with TCT outcomes and program engagement. These initial findings may be used to inform therapeutic decisions about which individuals would more likely engage in and benefit from an auditory-based, computerized TCT program.

Integrating Causal Discovery and Clinically-Relevant Insights to Explore Directional Relationships between Autistic Features, Sex at Birth, and Cognitive Abilities.

Prevalence in autism spectrum disorder (ASD) diagnosis has long been strongly male-biased. Yet, consensus has not been reached on mechanisms and clinical features that underlie sex-based discrepancies. Whereas females may be under-diagnosed because of inconsistencies in diagnostic/ascertainment procedures (sex-biased criteria, social camouflaging), diagnosed males may have exhibited more overt behaviors (e.g., hyperactivity, aggression) that prompted clinical evaluation. Applying a novel network-theory-based approach, we extracted data-driven, clinically-relevant insights from a large, well-characterized sample (Simons Simplex Collection) of 2175 autistic males (Ages = 8.9±3.5 years) and 334 autistic females (Ages = 9.2±3.7 years). Exploratory factor analysis (EFA) and expert clinical review reduced data dimensionality to 15 factors of interest. To offset inherent confounds of an imbalanced sample, we identified a subset of males (N=331) matched to females on key variables (Age, IQ) and applied data-driven CDA using Greedy Fast Causal Inference (GFCI) for three groups (All Females, All Males, and Matched Males). Structural equation modeling (SEM) extracted measures of model fit and effect sizes for causal relationships between sex, age, and, IQ on EFA-selected factors capturing phenotypic representations of autism across sensory, social, and restricted and repetitive behavior domains. Our methodology unveiled sex-specific directional relationships to inform developmental outcomes and targeted interventions.

Learning signatures of decision making from many individuals playing the same game.

Human behavior is incredibly complex and the factors that drive decision making--from instinct, to strategy, to biases between individuals--often vary over multiple timescales. In this paper, we design a predictive framework that learns representations to encode an individual's 'behavioral style', i.e. long-term behavioral trends, while simultaneously predicting future actions and choices. The model explicitly separates representations into three latent spaces: the recent past space, the short-term space, and the long-term space where we hope to capture individual differences. To simultaneously extract both global and local variables from complex human behavior, our method combines a multi-scale temporal convolutional network with latent prediction tasks, where we encourage embeddings across the entire sequence, as well as subsets of the sequence, to be mapped to similar points in the latent space. We develop and apply our method to a large-scale behavioral dataset from 1,000 humans playing a 3-armed bandit task, and analyze what our model's resulting embeddings reveal about the human decision making process. In addition to predicting future choices, we show that our model can learn rich representations of human behavior over multiple timescales and provide signatures of differences in individuals.

Learning signatures of decision making from many individuals playing the same game.

Human behavior is incredibly complex and the factors that drive decision making-from instinct, to strategy, to biases between individuals-often vary over multiple timescales. In this paper, we design a predictive framework that learns representations to encode an individual's 'behavioral style', i.e. long-term behavioral trends, while simultaneously predicting future actions and choices. The model explicitly separates representations into three latent spaces: the recent past space, the short-term space, and the long-term space where we hope to capture individual differences. To simultaneously extract both global and local variables from complex human behavior, our method combines a multi-scale temporal convolutional network with latent prediction tasks, where we encourage embeddings across the entire sequence, as well as subsets of the sequence, to be mapped to similar points in the latent space. We develop and apply our method to a large-scale behavioral dataset from 1,000 humans playing a 3-armed bandit task, and analyze what our model's resulting embeddings reveal about the human decision making process. In addition to predicting future choices, we show that our model can learn rich representations of human behavior over multiple timescales and provide signatures of differences in individuals.

The CBIT+TMS Trial: study protocol for a two-phase randomized controlled trial testing neuromodulation to augment behavior therapy for youth with chronic tics.

Background: Comprehensive Behavioral Intervention for Tics (CBIT) is a first-line treatment for tic disorders that aims to improve controllability over tics that an individual finds distressing or impairing. However, it is only effective for approximately half of patients. Supplementary motor area (SMA)-directed neurocircuitry plays a strong role in motor inhibition, and activity in this region is thought to contribute to tic expression. Targeted modulation of SMA using transcranial magnetic stimulation (TMS) may increase CBIT efficacy by improving patient ability to implement tic controllability behaviors. Methods: The CBIT+TMS trial is a two-phase, milestone driven early-stage randomized controlled trial. The trial will test whether augmenting CBIT with inhibitory, noninvasive stimulation of SMA with TMS modifies activity in SMA-mediated circuits and enhances tic controllability in youth ages 12-21 years with chronic tics. Phase 1 will directly compare two rTMS augmentation strategies (1Hz rTMS vs. cTBS) vs. sham in N = 60 participants. Quantifiable, a priori "Go/No Go Criteria" guide the decision to proceed to Phase 2 and selection of the optimal TMS regimen. Phase 2 will compare the optimal regimen vs. sham and test the link between neural target engagement and clinical outcomes in a new sample of N = 60 participants. Discussion: This clinical trial is one of few to date testing TMS augmentation of therapy in a pediatric sample. Results will provide insight into whether TMS is a potentially viable strategy for enhancing CBIT efficacy and reveal potential neural and behavioral mechanisms of change. Trial registration: ClinicalTrials.gov Identifier: NCT04578912.

The CBIT + TMS trial: study protocol for a two-phase randomized controlled trial testing neuromodulation to augment behavior therapy for youth with chronic tics.

BACKGROUND: Comprehensive Behavioral Intervention for Tics (CBIT) is a first-line treatment for tic disorders that aims to improve controllability over tics that an individual finds distressing or impairing. However, it is only effective for approximately half of patients. Supplementary motor area (SMA)-directed neurocircuitry plays a strong role in motor inhibition, and activity in this region is thought to contribute to tic expression. Targeted modulation of SMA using transcranial magnetic stimulation (TMS) may increase CBIT efficacy by improving patients' ability to implement tic controllability behaviors. METHODS: The CBIT + TMS trial is a two-phase, milestone-driven early-stage randomized controlled trial. The trial will test whether augmenting CBIT with inhibitory, non-invasive stimulation of SMA with TMS modifies activity in SMA-mediated circuits and enhances tic controllability in youth ages 12-21 years with chronic tics. Phase 1 will directly compare two rTMS augmentation strategies (1 Hz rTMS vs. cTBS) vs. sham in N = 60 participants. Quantifiable, a priori "Go/No Go Criteria" guide the decision to proceed to phase 2 and the selection of the optimal TMS regimen. Phase 2 will compare the optimal regimen vs. sham and test the link between neural target engagement and clinical outcomes in a new sample of N = 60 participants. DISCUSSION: This clinical trial is one of few to date testing TMS augmentation of therapy in a pediatric sample. The results will provide insight into whether TMS is a potentially viable strategy for enhancing CBIT efficacy and reveal potential neural and behavioral mechanisms of change. TRIAL REGISTRATION: ClinicalTrials.gov NCT04578912 . Registered on October 8, 2020.

Utility of Downstream Biomarkers to Assess and Optimize Intranasal Delivery of Oxytocin.

Oxytocin (OT), a mammalian neurohormone associated with social cognition and behavior, can be administered in its synthetic form intranasally (IN) and impact brain chemistry and behavior. IN-OT shows potential as a noninvasive intervention for disorders characterized by social challenges, e.g., autism spectrum disorder (ASD) and anorexia nervosa (AN). To evaluate IN-OT's efficacy, we must quantify OT uptake, availability, and clearance; thus, we assessed OT levels in urine (uOT) before and after participants (26 ASD, 7 AN, and 7 healthy controls) received 40 IU IN-OT or placebo across two sessions using double-blind, placebo-controlled crossover designs. We also measured uOT and plasma (pOT) levels in a subset of participants to compare the two sampling methods. We found significantly higher uOT and pOT following intranasal delivery of active compound versus placebo, but analyses yielded larger effect sizes and more clearly differentiated pre-post-OT levels for uOT than pOT. Further, we applied a two-step cluster (TSC), blinded backward-chaining approach to determine whether active/placebo groups could be identified by uOT and pOT change alone; uOT levels may serve as an accessible and accurate systemic biomarker for OT dose-response. Future studies will explore whether uOT levels correlate directly with behavioral targets to improve dosing for therapeutic goals.

Experimental data exploring the effects of intranasal oxytocin on young adult social preference and attachment to romantic partners, parents, friends, and strangers.

Experimental studies exploring the effects of intranasal oxytocin are typically underpowered due to small samples. Open access to experimental data and procedures and the use of previously employed measures is critical to building more robust and replicable findings, especially in less studied areas of oxytocin research. In this paper, data is provided from a double-blind placebo-controlled crossover study exploring the effects of intranasal oxytocin (IN-OT: 24 IU) on social preference to romantic partners, parents, peers, and strangers. Young adults (N = 44; 91% female) in committed dating relationships completed three phases of data collection including a screening survey followed by two cmd kwdnextpage ?>laboratory visits. In addition to romantic partner-, and stranger attraction ratings, the data is the first to provide comparisons between attachment and social preference ratings to parents, close friends, and romantic partners under placebo and IN-OT conditions. The data also include differences by situational and life history factors known to moderate oxytocin effects. The detailed protocol, and dataflow can be accessed to verify the analysis and findings or to conduct a replication study. The standardized experimental design and common IN-OT protocol add to the capacity for a meta-analysis exploring oxytocin effects on partner preference and may also be directly ported to existing or future studies with related questions to increase sample size and power.

Differential extrinsic brain network connectivity and social cognitive task-specific demands in Autism Spectrum Disorder (ASD).

Few studies have used task-based functional connectivity (FC) magnetic resonance imaging to examine emotion-processing during the critical neurodevelopmental period of adolescence in Autism Spectrum Disorders (ASDs). Moreover, task designs with pervasive confounds (e.g., lack of appropriate controls) persist because they activate neural circuits of interest reliably. As an alternative approach to "subtracting" activity from putative control conditions, we propose examining FC across an entire task run. By pivoting our analysis and interpretation of existing paradigms, we may better understand neural response to non-focal instances of socially-relevant stimuli that approximate real-world experiences more closely. Hence, using two well-established affective tasks (face-viewing, face-matching) with diverging social-cognitive demands, we investigated extrinsic FC from amygdala (AMG) and fusiform gyrus (FG) seeds in typically-developing (TD; N = 17) and ASD (N = 17) male adolescents (10-18 yo) and clinical correlations (Social Communication Questionnaire; SCQ) of group FC differences. Participant data (4TD, 6ASD) with excessive head-motion were excluded from final analysis. Direct between-group comparisons revealed significant differences between groups for neural response but not task performance (accuracy, reaction time). During face-viewing, we found greater FC from AMG and FG seeds for ASD participants (ASD > TD) in regions involved in the Default Mode and Fronto-Parietal Task Control Networks. During face-matching, we found greater FC from AMG and FG seeds for TD participants (TD > ASD), in regions associated with the Salience, Dorsal Attention, and Somatosensory Networks. SCQ scores correlated positively with regions with group differences on the face-viewing task and negatively with regions identified for the face-matching task. Task-dependent group differences in FC despite comparable behavioral performance suggest that high-functioning ASD may wield compensatory strategies; clinically-correlated FC patterns may associate with differential task-demands, ecological validity, and context-dependent processing. Employing this novel approach may further the development of targeted therapeutic interventions informed by individual differences in the highly heterogeneous ASD population.