Posters

Background: Current biomarker candidates of psychosis risk are informative but lack clinical utility beyond the group level. Mechanistic specificity at the individual-level is required. The 20Hz auditory steady-state response (20HzASSR) elicits both a 20Hz and 40Hz steady-state harmonic response (40HzSSHR), indexing SST+ and PV+ interneurons that stabilise pyramidal output. Disruption of this coordination is central to excitation/inhibition imbalance models of schizophrenia and directly linked to perceptual abnormalities (PAs), a core feature of psychosis and clinical high risk (CHR). Here, 20-40Hz co-modulation was examined to test whether this relationship could be indexed using EEG and whether predict PA outcomes.

Methods: Electroencephalogram (EEG) was recorded from CHR (CHR-S,n=15) with persistent attenuated psychotic symptoms at 1 year follow-up (FU) and healthy controls (HC,n=17) during 20Hz stimulation. 20HzASSR and 40HzSSHR amplitudes (0-750ms) were extracted. Co-modulation was quantified by regression of 40HzSSHR on 20HzASSR, with cluster-based permutation testing and prospective prediction of 1-year outcomes.

Results: 20HzASSR was reduced in CHR-S vs HC (U=185,p=.031,r=-.45); 40HzSSHR (ns). The 20-40 relationship was positive in HC (r=0.54,p=.025) but negative in CHR-S (r=-0.33,n.s.), with significant contrast (z=2.40,p=.016). Dynamic slope analysis identified 325-645ms divergence (p_cluster=.036), HC=0.155 vs CHR-S=-0.120 (t=2.38,p=.027,d=0.87). Baseline slopes predicted FU-PAs (β=-1.41,p=.033,R²=.238). Conclusions: Cross-frequency co-modulation, rather than amplitude alone, differentiates CHR-S from HC and predicts future PAs. This provides preliminary evidence that the 20-40 relationship may serve as an EEG Index of Circuit Instability (E-ICI) at the individual-level. Following validation, the E-ICI may serve as a mechanistically interpretative biomarker with potential for early risk stratification, monitoring, and treatment development.

Background: Mobile apps can support children and young people’s (CYP) mental health, but sustaining engagement, especially among those with higher needs, remains difficult. This study examined engagement with MindCraft, a mental health app using artificial intelligence (AI)-based nudges and both active (self-report) and passive (sensor) tracking. It assessed whether engagement differed by Strengths and Difficulties Questionnaire (SDQ) risk level and intervention group.

Aim(s): • To examine how baseline mental health influences engagement with active and passive tracking and AI nudges. • To compare engagement across three intervention groups over time. - Methods: 130 adolescents (aged 14–18) from London schools completed baseline questionnaires, installed MindCraft, and were randomly assigned to intervention, active control, or control groups. Engagement over three weeks was measured via active tracker use, passive data sharing, AI nudge completion, and total app use days. Data were compared by SDQ risk level and intervention arm.

Results: No significant engagement differences were found by risk group (p > .076) or intervention arm (p > .083). Passive data sharing was moderate, while active engagement varied widely between individuals. The sample was demographically skewed and mostly low risk, limiting generalisability. - Conclusion: Adolescent engagement with mobile interventions appears more influenced by personal, contextual, and behavioural factors than by mental health risk or intervention type. The absence of group differences highlights the need to better understand adolescents’ digital preferences and barriers. Future research should extend monitoring periods, recruit more diverse samples, and adopt participatory design to enhance the relevance and impact of mental health apps.

Apathy is a common symptom in neurological conditions, associated with poor prognosis and increased caregiver burden. There are currently no proven treatments. A loss of precision on action outcomes may cause apathy by reducing the expected difference between the state of the world following action versus non-action. We test if this loss of precision is reversible with GABAergic medication in individuals with syndromes associated with frontotemporal degeneration. Twenty healthy controls, twenty people with behavioural variant frontotemporal dementia and twenty people with progressive supranuclear palsy took part in a randomised placebo-controlled double-blind trial using zolpidem, an allosteric GABAA modulator. We use the ‘Goal Prior Assay’ task and dynamic causal modelling of MEG resting-state data to explore the cognitive and neural concomitants of prior precision, and the effect of GABAergic regulation on both prior precision and superficial pyramidal gain. We found strong evidence for a difference in prior precision between patients and controls on placebo (B=20.4, p<0.01), but not in the drug condition (B=0.86, p=0.11). There was strong evidence of a correlation between apathy and prior precision across groups (B>100, p<0.001). Dynamic causal modelling confirmed that reductions in gain on the prefrontal superficial pyramidal neurons were associated with prior precision in the patient group, and partially restored on zolpidem. We suggest that apathy is in part caused by a reduction in prior precision on action outcomes, mediated by reduced synaptic gain of prefrontal superficial pyramidal neurons, which can be partially restored using GABAergic intervention.

The World Health Organization reports that approximately 332 million people in the world have depression and that this common mental disorder can significantly impair people’s social relationships, work performance, and other aspects of life. In 2021, an estimated 727,000 people lost their lives to suicide, so reasonably there is strong motivation to discover viable treatments for depression. A variety of different treatments aimed at decreasing depression in participants have been developed including psychopharmacology and brain stimulation techniques such as transcranial magnetic stimulation. Yet important questions about this line of research remain. For example, how effective is transcranial magnetic stimulation at reducing major depression? The purpose of the present meta-analytic research is to address this question by systematically reviewing all relevant studies that compared the influence of transcranial magnetic stimulation versus sham stimulation on major depression as measured by the Montgomery-Asberg Depression Rating Scale. Following PRISMA guidelines and using a random effects model, this meta-analysis found a small yet significant effect for transcranial magnetic stimulation versus sham stimulation on decreasing major depression in participants (k = 8, SMD = -0.241, p = 0.009). Here we highlight the results of this meta-analytic research on transcranial magnetic stimulation and major depression, comment on its practical value, and identify limitations and prospects for future research.