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Inhibitory control development from infancy to early childhood: A longitudinal fNIRS study.
The developmental period from infancy to early childhood is one of substantial change - in advancements in cognitive skills, such as early executive functions, but also in the maturation of the prefrontal and parietal cortices that parallel such advances. The current study aims to investigate the emergence and development of inhibitory control, a core executive function, from infancy to early childhood. We collected longitudinal functional near-infrared spectroscopy (fNIRS) data from the same sample of participants at 10-months, 16-months, and 3½ years of age whilst they completed the Early Childhood Inhibitory Touchscreen Task. In our previous publications, we reported that 10-month-old infants recruited right lateralised regions of the prefrontal and parietal cortex when inhibition was required. Despite no change in response inhibition performance, 16-month-olds recruited broader and bilateral regions of the prefrontal and parietal cortex. Results of the current study found that 3½-year-olds activated regions of the right inferior parietal cortex and the right inferior frontal gyrus when inhibition was required. Response inhibition performance was significantly improved by early childhood, yet there was commonality in the brain regions recruited at 16-months and 3½ years. This could suggest that these brain regions are fundamental neural indices of inhibitory control, even from toddlerhood.
Time on social networking sites is associated with impulsive decision-making
Almost five billion individuals worldwide use social networking sites (SNSs) such as Instagram, Facebook, Snapchat, and X (formerly known as Twitter). The social rewards obtained on these sites induce users to spend substantial durations of time on them. However, current research demonstrates mixed findings on whether greater time on SNSs is related to riskier decision-making and impulsive tendencies. To address these findings, we conducted an online study (n = 225) to assess how time across four SNSs relates to impulsive decision-making in the delay discounting task. We included each trial as an individual choice in a regression model predicting preference for the immediate reward, for a total of 20,265 choices. Greater average time across all SNSs was related with a higher likelihood of choosing the immediate, but smaller, reward. In other words, people who spent more time on SNSs also made more impulsive decisions. When including individual platforms, greater time on Instagram and X, but not Facebook or Snapchat, was related with a higher likelihood of choosing the immediate reward. These findings help clarify prior literature on the relationship between platform specific SNS use and impulsive decision-making. We discuss limitations, directions for future research, and broader implications for the field.
“You never know who you’re gonna speak to”: Exploring Psychological Wellbeing Practitioners' Experiences of Assessing Traumatic Events
Objectives: This study explored junior mental health workers' experiences of conducting assessments involving traumatic events. Method: Semi-structured interviews with eleven junior mental health workers from a UK primary care mental health service were analysed using reflexive thematic analysis. Results: Participants discussed themes of ambiguity in distinguishing trauma and PTSD, high levels of pressure, management of personal distress, appropriate training, and personal support in-service. Conclusions: Findings corroborate previous research regarding challenges experienced by junior mental health workers and offer novel insight into the challenges faced when assessing service-users' experiences of traumatic events. Recommendations regarding future training, service design and emotional outlets for junior mental health workers are offered.
Memories or decisions? Bridging accounts of frontopolar function.
Frontopolar cortex (FPC), for a long time elusive to functional description, is now associated with a wide range of cognitive processes. Prominent accounts of FPC function emerged from studies of memory (e.g., episodic and prospective memory; EM and PM, respectively) and of executive function (e.g., planning, multi-tasking, relational reasoning, cognitive branching, etc). In recent years, FPC function has begun to be described within the context of value-based decision making in terms of monitoring the value of alternatives and optimizing cognitive resources to balance the explore/exploit dilemma in the face of volatile environments. In this perspective, we propose that the broad counterfactual inference and behavioural flexibility account can help re-interpret findings from EM and PM studies and offer an explanatory bridge between the memory and executive function accounts. More specifically, we propose that counterfactual value monitoring in FPC modulates the reallocation of cognitive resources between present and past information and contributes to efficient episodic and prospective retrieval by concurrently assessing the value of competing memories in relation to the decision at hand and proactively evaluating future potential scenarios to anticipate optimal engagement of intentions.
Who Tweets for the autistic community? A natural language processing–driven investigation
The formation of autism advocacy organisations led by family members of autistic individuals led to intense criticism from some parts of the autistic community. In response to what was perceived as a misrepresentation of their interests, autistic individuals formed autistic self-advocacy groups, adopting the philosophy that autism advocacy should be led ‘by’ autistic people ‘for’ autistic people. However, recent claims that self-advocacy organisations represent only a narrow subset of the autistic community have prompted renewed debate surrounding the role of organisations in autism advocacy. While many individuals and groups have outlined their views, the debate has yet to be studied through computational means. In this study, we apply machine learning and natural language processing techniques to a large-scale collection of Tweets from organisations and individuals in autism advocacy. We conduct a specification curve analysis on the similarity of language across organisations and individuals, and find evidence to support claims of partial representation relevant to both self-advocacy groups and organisations led by non-autistic people. In introducing a novel approach to studying the long-standing conflict between different groups in the autism advocacy community, we hope to provide both organisations and individuals with new tools to help ground discussions of representation in empirical insight. Lay Abstract Some autism advocacy organisations are run by family members of autistic people, and claim to speak on behalf of autistic people. These organisations have been criticised by autistic people, who feel like autism charities do not adequately represent their true interests. In response to these organisations, autistic people have come together to form autistic self-advocacy organisations, or groups in which activists can spread awareness of autism from an autistic point-of-view. However, some people say that autistic self-advocacy organisations do not sufficiently represent the needs of all autistic people. These tensions between organisations and individuals have made it difficult to determine which organisations can make the claim that they represent all autism advocates individuals equally, instead of showing preference to a sub-group within the autism community. In this study, we try to approach this issue using computational tools to see if, in their Twitter posts, both kinds of organisations show a preference for the interests of autistic people or parents of autistic children. We do so by comparing a large body of Tweets by organisations to Tweets by autistic people and parents of autistic children. We find that both kinds of organisations match the interests of one group of autism advocates better than the other. The insight we provide has the potential to inspire new conversations and solutions to a long-standing conflict in autism advocacy.
Investigating the impact of electroconvulsive therapy on brain networks and sleep: an observational study protocol.
INTRODUCTION: Electroconvulsive therapy (ECT) is a highly effective treatment for refractory depression, but it may also cause cognitive side effects. Despite decades of use, the mechanisms by which ECT exerts both its antidepressant and cognitive effects are still poorly understood, with the latter substantially limiting referral and adherence to therapy. ECT induces changes in correlated neural activity-functional connectivity-across various brain networks, which may underlie both its clinical efficacy and associated cognitive side effects. Electroencephalography (EEG) could address these knowledge gaps by identifying biomarkers that predict therapeutic outcomes or cognitive side effects. Such developments could ultimately improve patient selection and adherence. Such markers likely span large-scale functional brain networks or temporal dynamics of brain activity during sleep. We hypothesise that enhancement in slow wave sleep mediates the relationship between antidepressant effects and changes in functional connectivity throughout the course of ECT. METHODS AND ANALYSIS: Disruptions of Brain Networks and Sleep by Electroconvulsive Therapy (DNS-ECT) is an ongoing observational study investigating the impact of ECT on large-scale brain functional networks and their relationships to sleep slow waves, an EEG marker linked to synaptic plasticity. The novelty of this study stems from our focus on the assessment of EEG markers during sleep, wakefulness and ECT-induced seizures over the course of therapy. Graph-based network analyses of high-density EEG signals allow characterisation of functional networks locally in specific subnetworks and globally over large-scale functional networks. Longitudinal assessments of EEG alongside clinical and cognitive outcomes provide a unique opportunity to improve our understanding of the circuit mechanisms underlying the development of cognitive impairments and antidepressant effects incurred during ECT. ETHICS AND DISSEMINATION: Recruitment for this 5-year study started in March 2023. Dissemination plans include presentations at scientific conferences and peer-reviewed publications. This study has been registered with ClinicalTrials.gov registry under identifier. TRIAL REGISTRATION NUMBER: NCT05905705.
Decision cost hypersensitivity underlies Huntington's disease apathy.
The neuropsychiatric syndrome of apathy is now recognized to be a common and disabling condition in Huntington's disease. However, the mechanisms underlying it are poorly understood. One way to investigate apathy is to use a theoretical framework of normal motivated behaviour, to determine where breakdown has occurred in people with this behavioural disruption. A fundamental computation underlying motivated, goal-directed behaviour across species is weighing up the costs and rewards associated with actions. Here, we asked whether people with apathy are more sensitive to costs of actions (physical effort and time delay), less sensitive to rewarding outcomes, or both. Based on the unique anatomical substrates associated with Huntington's disease pathology, we hypothesized that a general hypersensitivity to costs would underpin Huntington's disease apathy. Genetically confirmed carriers of the expanded Huntingtin gene (premanifest to mild motor manifest disease, n = 53) were compared to healthy controls (n = 38). Participants performed a physical effort-based decision-making task (Apple Gathering Task) and a delay discounting task (Money Choice Questionnaire). Choice data was analysed using linear regression and drift diffusion models that also accounted for the time taken to make decisions. Apathetic people with Huntington's disease accepted fewer offers overall on the Apple Gathering Task, specifically driven by increased sensitivity to physical effort costs, and not explained by motor severity, mood, cognition or medication. Drift diffusion modelling provided further evidence of effort hypersensitivity, with apathy associated with a faster drift rate towards rejecting offers as a function of varying effort. Increased delay sensitivity was also associated with apathy, both when analysing raw choice and drift rate, where there was moderate evidence of Huntington's disease apathy drifting faster towards the immediately available (low-cost) option. Furthermore, the effort and delay sensitivity parameters from these tasks were positively correlated. The results demonstrate a clear mechanism for apathy in Huntington's disease, cost hypersensitivity, which manifests in both the effort and time costs associated with actions towards rewarding goals. This suggests that Huntington's disease pathology may cause a domain-general disruption of cost processing, which is distinct from apathy occurrence in other brain disorders and may require different therapeutic approaches.
Correction to: From Intimate Exams to Ritual Nicking: Interpreting Nonconsensual Medicalized Genital Procedures as Sexual Boundary Violations (Current Sexual Health Reports, (2023), 15, 4, (291-300), 10.1007/s11930-023-00376-9)
The wrong Supplementary file was originally published with this article; it has now being removed. The original article has been corrected.
Hyperspectral characterization of natural lighting environments.
Lights are primary drivers of some crucial biological functions including vision and regulation of circadian rhythm. To understand the light exposure pattern that we experience in a daily life, many past studies measured the spectral composition of natural daylight and artificial lighting. The aim of this book chapter is to introduce a novel method to characterize directional spectral variation in natural lighting environments. An omnidirectional hyperspectral illumination map stores the spectra of lights coming from every direction toward a single point in a scene. Such illumination maps allow us to simulate a spatial light exposure pattern that reaches our eyes, providing useful resources to research areas such as chronobiology, vision science and any other fields which benefit from knowledge about the spectral nature of visual lighting environments.
New Perspective on Digital Well-Being by Distinguishing Digital Competency From Dependency: Network Approach
Background In the digital age, there is an emerging area of research focusing on digital well-being (DWB), yet conceptual frameworks of this novel construct are lacking. The current conceptualization either approaches the concept as the absence of digital ill-being, running the risk of pathologizing individual digital use, or follows the general subjective well-being framework, failing to highlight the complex digital nature at play. Objective This preregistered study aimed to address this gap by using a network analysis, which examined the strength of the relationships among affective (digital stress and web-based hedonic well-being), cognitive (online intrinsic needs satisfaction), and social (online social connectedness and state empathy) dimensions of DWB and their associations with some major DWB protective and risk factors (ie, emotional regulation, nomophobia, digital literacy, self-control, problematic internet use, coping styles, and online risk exposure). Methods The participants were 578 adults (mean age 38.7, SD 13.14 y; 277/578, 47.9% women) recruited from the United Kingdom and the United States who completed an online survey. Two network models were estimated. The first one assessed the relationships among multiple dimensions of DWB, and the second examined the relationships between DWB dimensions and related protective and risk factors. Results The 2 resulting network structures demonstrated high stability, with the correlation stability coefficients being 0.67 for the first and 0.75 for the second regularized Gaussian graphical network models. The first network indicated that all DWB variables were positively related, except for digital stress, which was negatively correlated with the most central node—online intrinsic needs satisfaction. The second network revealed 2 distinct communities: digital competency and digital dependency. Emotional regulation emerged as the most central node with the highest bridge expected influence, positively associated with emotion-focused coping in the digital competency cluster and negatively associated with avoidant coping in the digital dependency cluster. In addition, some demographic differences were observed. Women scored higher on nomophobia (χ24=10.7; P=.03) and emotion-focused coping (χ24=14.9; P=.01), while men scored higher on digital literacy (χ24=15.2; P=.01). Compared with their older counterparts, younger individuals scored lower on both emotional regulation (Spearman ρ=0.27; P<.001) and digital self-control (Spearman ρ=0.35; P<.001) and higher on both digital stress (Spearman ρ=−0.14; P<.001) and problematic internet use (Spearman ρ=−0.25; P<.001). Conclusions The network analysis revealed how different aspects of DWB were interconnected, with the cognitive component being the most influential. Emotional regulation and adaptive coping strategies were pivotal in distinguishing digital competency from dependency.
Sleep and circadian difficulties in schizophrenia: presentations, understanding, and treatment.
It is common in mental health care to ask about people's days but comparatively rare to ask about their nights. Most patients diagnosed with schizophrenia struggle at nighttime. The next-day effects can include a worsening of psychotic experiences, affective disturbances, and inactivity, which in turn affect the next night's sleep. Objective and subjective cognitive abilities may be affected too. Patients commonly experience a mix of sleep difficulties in a night and across a week. These difficulties include trouble falling asleep, staying asleep, or sleeping at all; nightmares and other awakenings; poor-quality sleep; oversleeping; tiredness; sleeping at the wrong times; and problems establishing a regular sleep pattern. The patient group is also more vulnerable to obstructive sleep apnea and restless legs syndrome. We describe in this article how the complex presentation of non-respiratory sleep difficulties arises from variation across five factors: timing, mental state, need for sleep, self-care, and environment. We set out 10 illustrative patterns of such difficulties experienced by patients with non-affective psychosis. These sleep problems are eminently treatable with intensive psychological therapy delivered over approximately eight sessions. We describe key techniques and their typical order of implementation by presentation. Sleep problems are an important issue for patients. Giving them the therapeutic attention patients often desire brings both real clinical benefits and improves views of services. Treatment is also very likely to lessen psychotic experiences and mood disturbances while improving daytime functioning and quality of life. Tackling sleep difficulties can be a route toward the successful treatment of psychosis.
Under pressure: UK preclinical neuroscience at a crossroads.
Graphical Abstract.
Relationships between depression, anxiety, and motivation in the real-world: Effects of physical activity and screentime.
BACKGROUND: Mood and anxiety disorders are highly prevalent and comorbid worldwide, with variability in symptom severity that fluctuates over time. Digital phenotyping, a growing field that aims to characterize clinical, cognitive and behavioral features via personal digital devices, enables continuous quantification of symptom severity in the real world, and in real-time. METHODS: In this study, N=114 individuals with a mood or anxiety disorder (MA) or healthy controls (HC) were enrolled and completed 30-days of ecological momentary assessments (EMA) of symptom severity. Novel real-world measures of anxiety, distress and depression were developed based on the established Mood and Anxiety Symptom Questionnaire (MASQ). The full MASQ was also completed in the laboratory (in-lab). Additional EMA measures related to extrinsic and intrinsic motivation, and passive activity data were also collected over the same 30-days. Mixed-effects models adjusting for time and individual tested the association between real-world symptom severity EMA and the corresponding full MASQ sub-scores. A graph theory neural network model (DEPNA) was applied to all data to estimate symptom interactions. RESULTS: There was overall good adherence over 30-days (MA=69.5%, HC=71.2% completion), with no group difference (t(58)=0.874, p=0.386). Real-world measures of anxiety/distress/depression were associated with their corresponding MASQ measure within the MA group (t's > 2.33, p's < 0.024). Physical activity (steps) was negatively associated with real-world distress and depression (IRRs > 0.93, p's ≤ 0.05). Both intrinsic and extrinsic motivation were negatively associated with real-world distress/depression (IRR's > 0.82, p's < 0.001). DEPNA revealed that both extrinsic and intrinsic motivation significantly influenced other symptom severity measures to a greater extent in the MA group compared to the HC group (extrinsic/intrinsic motivation: t(46) = 2.62, p < 0.02, q FDR < 0.05, Cohen's d = 0.76; t(46) = 2.69, p < 0.01, q FDR < 0.05, Cohen's d = 0.78 respectively), and that intrinsic motivation significantly influenced steps (t(46) = 3.24, p < 0.003, q FDR < 0.05, Cohen's d = 0.94). CONCLUSIONS: Novel real-world measures of anxiety, distress and depression significantly related to their corresponding established in-lab measures of these symptom domains in individuals with mood and anxiety disorders. Novel, exploratory measures of extrinsic and intrinsic motivation also significantly related to real-world mood and anxiety symptoms and had the greatest influencing degree on patients' overall symptom profile. This suggests that measures of cognitive constructs related to drive and activity may be useful in characterizing phenotypes in the real-world.