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Evaluation of a Nature-based Psychological Intervention: Dose of Nature Young People’s Programme
Full text linkBackground: With growing mental health and environmental concerns, the interest in the wellbeing and pro-environmental benefits that connection to nature brings is increasing, making mental health interventions that engage individuals with nature on the rise. This study examines a nature-based mental health intervention, DoN’s young people’s programme (15 to 25 years old), aiming to understand what it is about the intervention that benefits mental wellbeing. Evidence is needed to understand the underlying mechanism of the benefits brought about by these interventions.
Methodology: In this qualitative study, 1-to-1 interviews were conducted with 10 DoN clients and analysed with Thematic Analysis.
Results: Three themes underpin successful nature prescriptions: Connecting with Oneself (sub-themes: Self-Restoration and Self-Expression), Connecting with Others (sub-themes: Meaningful Relationship with Guide and Meaningful Relationship with Community), and Connecting with the Environment (sub-themes: Engaging the Senses and Emotional Bond to the Environment). The most present elements are Self-Expression and Emotional Bond to the Environment.
Discussion: Findings highlight the clinical value of a relationship to the natural world. There are a couple of limitations to the study: participants’ arguments could have been influenced by a social desirability response bias; and the present study cannot draw long-term conclusions on the benefits of the intervention. A randomized control trial with long term follow-up should be conducted for this purpose.
Conclusion: As most nature-based interventions focus on nature contact and knowledge-based activities, the current study provides valuable insight into an alternative approach, focused on fostering a relationship with the community and the natural world
Emotional Anatomy of Fake News: Leveraging Sentiment and Explainable AI for Misinformation Detection
No full textThe emotional dimension of fake news plays a pivotal role in shaping how misinformation spreads and influences public perception. This study explores the emotional anatomy of fake news by re-annotating the widely used LIAR dataset, creating the Emotion-Labelled Fake News Dataset (ELFND). By leveraging advanced NLP methods, with a focus on VADER sentiment analysis, the dataset categorizes news articles according to emotions tone conveyed. Ensemble machine learning models, Random Forest and Gradient Boosting are employed to detect fake news by analyzing its emotional content. Furthermore, AI explainability methods, including LIME and SHAP, are utilized to offer a deeper understanding of how the model generates predictions, shedding light on how specific emotions contribute to the classification of news as fake. The findings reveal that emotions are crucial in the structure of fake news, and the use of XAI enhances transparency in misinformation detection, offering a clearer understanding of the emotional drivers behind fake news
Simulating the point of no return in human volitional action in a brain-constrained model of sensory and motor areas
Full text linkFollowing a decision to act, motor execution exhibits a typical "point of no return", a time after which movement can no longer be prevented [1]. Why are we unable to veto action beyond a certain point? We used a 6-area brain-constrained neural-network model mimicking neurophysiological and anatomical features of relevant cortical areas to investigate the brain mechanisms underlying this phenomenon. The same model was previously used to explain emergence of self-paced action decisions as spontaneous ignitions of learnt “perception-action” (or Cell Assembly, CA) circuits caused by noise reverberation in them [2]. We ask here if such distributed circuits exhibit a natural threshold, an activity level beyond which ignition always occurs.
We recorded network activity over ~6mil steps in absence of any “sensory” input and observed regular, spontaneous within-CA-circuit activity peaks, driven by noise. Each CA’s activity typically peaked near the circuit’s own maximum (100%) level, indicating a full ignition (or a “volitional action decision”). Using KMeans clustering (bootstrapping with resampling, N=3000), we then analysed within-CA activity, looking for a possible distinct group of peaks centred at values below ignition levels. A “between-clusters gap” would indicate the presence of an inherent threshold which, if reached, would always be followed by full CA ignition, thus reproducing (and explaining) the point-of-no-return effect seen in volitional action experiments.
We found that, for ten of the twelve learnt CA circuits, activity peaks could be grouped into at least two different clusters (Fig. 1), a higher, “full-ignition” one, and lower, “sub-ignition” one/s, indicating the presence, in each assembly, of a natural threshold (model correlate of the point of no return, PNR) lying near the upper boundary of the highest of the “sub” clusters. (Two of the circuits were excluded as they failed to exhibit full ignitions: their upper clusters were lower than those of the remaining CAs). We also found between-circuit differences in natural-threshold (PNR) values, ranging from 10% to 70% of a circuit’s maximal activity, suggesting the presence of memory-trace-specific PNRs, and, hence, dynamic features.
The existence of a non-empty set of levels between the "sub-" and "full-ignition" clusters of activity peaks in which CA-circuit activity is unstable (as observed for 83% of the CAs) suggests that each circuit does have an inherent activity threshold which, once reached, is always followed by full ignition. Our model thus offers a tentative mechanistic explanation for the existence of a point of no return in volitional action: the ability to stop movement only up to a certain time after having committed to it may be due to the inherently unstable, positive-feedback dynamics of the sensorimotor memory traces our cortex learns via repeated action execution, which spontaneously ignite when baseline neural activity reverberates in them
AI Infrastructures, Total Mobilisation and Decomputing
No full textThis chapter examines the broad impact of AI infrastructures on the possibility of sustainable social and ecological relations. It problematises these infrastructures not only in terms of energy demand but as a degradation of labour and social relations, and highlights the ways in which AI itself fails to deliver on its claims. Identifying the driving principle of ‘scale’ as central to these problems, it positions AI infrastructures with the wider frame of growth ideology. Addressing the contradictions between AI’s harmful fallibilities and the vast investments of financial and political capital in its infrastructures, the chapter offers Ernst Jünger’s concept of ‘total mobilisation’ as a way to grasp the underlying, epochal dynamics. This framing also helps to explain the observable overlap between Silicon Valley’s own ideologies and the rise of far right political forces. The chapter proposes the idea of ‘decomputing’ as a counter to the cumulative harms of AI infrastructures. It develops the concept of decomputing in relation to ideas of degrowth and de-automatisation, and suggests some practical steps forward based on the collective adoption of convivial technologies
A case of mistaken identity: Miscategorisation of the ingroup as a historically rivalrous outgroup triggers collective narcissism
Full text linkCollective narcissism’s links with intergroup relations, such as intergroup hostility, are well established, but less is known about the intergroup conditions that trigger it. We experimentally examined whether categorisation threat—operationalised as mistaking the ingroup for a historically rivalrous outgroup, thus undermining the ingroup’s uniqueness—heightens collective narcissism, and whether this, in turn, escalates hostility toward the pertinent outgroup through collective narcissism. Additionally, we compared collective narcissism to another form of ingroup positivity: ingroup satisfaction. We conducted four experiments (N = 1,537) manipulating categorisation threat in two national contexts (Poland, Portugal), and carried out an internal meta-analysis. As hypothesised, the findings revealed an increase in collective narcissism, as well as a positive indirect effect of categorisation threat on outgroup hostility mediated by collective narcissism, but not by ingroup satisfaction. This research establishes categorisation threat as a robust trigger of collective narcissism
Obsessive-Compulsive Symptoms Predict Increased Fronto-Parahippocampal Synchronisation During Thought Suppression
No full textBackground: Thought suppression is suggested as a causal factor in obsessive-compulsive disorder (OCD), as it can lead to an increase in intrusive thoughts. However, the neural mechanisms through which obsessive-compulsive symptoms (OCS) influence thought suppression, particularly in the context of preferential processing of negatively valenced stimuli, remains unclear. We hypothesized that OCS would predict increased inhibitory communication between frontal and parahippocampal neurocircuitry during the suppression of negative words. Additionally, we tested an exploratory analysis to see whether this was mediated by preferential processing of these stimuli.
Methods: EEG was recorded from 47 participants tasked with directed forgetting of negative and neutral words. Data from 38 of these participants were analyzed. We examined the influence of OCS on fronto-parahippocampal beta-1 (13-18 Hz) synchronization during a Directed Forgetting task. An exploratory analysis of the mediating role of stimulus processing bias, measured via the late positive potential (LPP) following the word stimulus, was assessed using a mediated moderation model.
Results: OCS predicted enhanced fronto-parahippocampal beta-1 synchronisation when instructed to forget negative words. The moderating effect of valence was mediated by preferential processing of negative stimuli, as indicated by increased LPP.
Conclusions: Healthy individuals with relatively high OCS exhibit compensatory connectivity between frontal and parahippocampal regions when attempting to suppress negative emotional stimuli. Exploratory analysis showed this compensatory activity is influenced by both preferential processing of negative stimuli and the severity of OCS, providing preliminary evidence of a neural mechanism that may contribute to the persistence of intrusive thoughts in OCD
From Spontaneous Ignitions to Sensorimotor Cell Assemblies via Dopamine: A Spiking Neurocomputational Model of Infants’ Hand Action Acquisition
Full text linkBackground/Objectives: From birth, infants learn how to interact with the world through exploration. It has been proposed that this early learning phase is driven by motor babbling: the spontaneous generation of exploratory movements that are progressively consolidated through associative mechanisms. This process leads to the acquisition of a repertoire of hand movements such as single- or multi-finger flexion, extension, touching, and pushing. Later, in a second phase, some of these movements (e.g., those that happen to enable access to biologically salient stimuli, such as grasping food) are further reinforced and consolidated through rewards obtained from the environment. However, the neural mechanisms underlying these processes remain unclear. Here, we used a fully neuroanatomically and neurophysiologically constrained neural network model to investigate the brain correlates of these processes.
Methods: The model consists of six neural maps simulating six human brain areas, including three pre-central (motor-related) and three post-central (sensory-related) regions. Each map is composed of excitatory and inhibitory spiking neurons, with biologically constrained within- and between-area connectivity forming recurrent circuits. Hand action execution and corresponding haptic perception are simulated simply as activity in primary motor and somatosensory model areas, respectively. During an initial “exploratory” phase, the network learned, via Hebbian mechanisms, associations—as emerging distributed cell assembly (CA) circuits—linking “motor” to corresponding “haptic feedback” patterns. As a result of this initial training, the model began to exhibit spontaneous ignitions of these CA circuits, an emergent phenomenon taken to represent internally generated, non-stimulus-driven attempts at hand action exploitation. In a second phase, a global reward signal, simulating dopamine-mediated reward encoding, was applied to only a subset of “successful” actions upon their noise-driven ignition.
Results: During the first exploratory phase, the neural architecture autonomously developed “action-perception” circuits corresponding to multiple possible hand actions. During the subsequent exploitation phase, positively reinforced circuits increased in size and, consequently, in frequency of spontaneous ignition, when compared to non-rewarded “actions”.
Conclusions: These results provide a mechanistic account, at the cortical-circuit level, of the early acquisition of hand actions, of their subsequent consolidation, and of the spontaneous transition of an agent’s behavior from exploration to reward-seeking, as typically observed in humans and animals during development
“The house is burning, and we are looking elsewhere:” the urgency of researching consumption injustices
Full text linkThis provocation piece calls for a fundamental shift in marketing and consumer research, arguing that the discipline must address the urgent and systemic injustices embedded within global consumption practices. Building on discussions from the 2023 CCT Conference, we urge scholars to redirect attention from mainstream consumer narratives to the peripheries where injustices are often rendered invisible. Through collective reflection, we identify three intersecting realms where injustices proliferate: underprivileged beings, peripheral places, and non-hegemonic epistemologies. By embracing reflexivity and acknowledging the field’s entanglement in sustaining these injustices, we invite scholars to approach consumption critically and advocate for impactful research that disrupts oppressive structures. This work aims to move consumption injustices from the periphery to the core of consumer research, fostering scholarly discourse that prioritises ethical urgency and societal relevance over traditional academic hierarchies
Bridging the digital divide: community resilience in educational access during the pandemic
Full text linkThe COVID-19 pandemic exacerbated existing educational inequalities in India, particularly for students in government-funded schools with limited access to digital infrastructure. This paper examines the processual nature of resilience in bridging the educational digital divide during the COVID-19 pandemic in TPuri (pseudonymized), a low-income community in the National Capital Region of India. Drawing on fieldwork, interviews, and observations, the study highlights how resilience is not a static attribute but an evolving process, shaped by human infrastructure – a network of teachers, parents, Civil Society Organization (CSO) workers, and community volunteers. As digital exclusion widened inequalities, these actors engaged in adaptive and iterative strategies, leveraging self-organization, redundancy, and flexibility to ensure continued access to education. While government policies failed to account for resource constraints in marginalized communities, resilience materialized through everyday infrastructuring, where informal tutoring networks, WhatsApp-based coordination, and peer-driven digital literacy efforts enabled learning. By foregrounding resilience as a dynamic and context-specific process, the findings challenge techno-solutionist approaches and emphasize the need for community-centered, adaptable policy frameworks that acknowledge the lived realities of underserved communities. This research contributes to critical discussions on equity, digital education, and grassroots resilience in crisis settings
Literature, Children, and Expansive Understandings of Global Identities
No full textThis chapter recognises the importance of listening to children’s voices and how children read, respond to, and create new texts in the study of children’s/YA literature. Focusing on our research as part of the global Critical Connections Multilingual Digital Storytelling Project (2012-ongoing) we explore children’s emerging global identities through an ecological lens. We draw on key theoretical ecological perspectives to analyse children’s multilingual poetry and digital stories across a range of languages (with English subtitles) and carried out with children both online and in classrooms. We analyse the Arabic poetry and digital story Breeze created by 12-14-year-old migrant students in Turkey; Greek poetry and digital story Waking up from a Nightmare created by 8–9-year-olds in Cyprus in response to reading a Japanese story ‘Baku: The Eater of Dreams’; and French poetry and digital story From my Window- De ma Fenêtre created by 9-10-year-olds in England