The unique neural signature of your trip: Functional connectome fingerprints of subjective psilocybin experience

Psychedelic compounds such as LSD, DMT and psilocybin produce transient but profound altered states of consciousness (ASCs) that are increasingly investigated for therapeutic potential in conditions including depression, obsessive–compulsive disorder and addiction. Prior neuroimaging work indicates that these subjective effects are largely mediated by 5-HT2A receptor agonism and are accompanied by systematic reconfigurations of the brain's functional connectome (FC), notably reduced activity and connectivity within higher-level association systems such as the default-mode network (DMN) and increased connectivity among lower-level sensory systems. However, individuals differ markedly in both neural response and subjective experience under psychedelics, and it remains unclear which subject-specific FC features map onto the multifaceted acute drug experience. Tolle and colleagues set out to address this gap by applying brain-fingerprinting methods to 7-Tesla resting-state fMRI collected from healthy volunteers who received either 0.17 mg/kg psilocybin (n=21) or placebo (n=25). The study aimed to (i) compare FC fingerprint properties between psilocybin and placebo conditions and (ii) determine whether idiosyncratic FC edges—that is, connections that are temporally stable within an individual yet variable across individuals—improve prediction of each subject's retrospective report of their psilocybin experience using the 5D-ASC questionnaire decomposed into 11 subdimensions.

This was a randomised, placebo-controlled, double-blind parallel-group trial conducted at Maastricht University. From an initial pool of 60 volunteers with prior but not recent psychedelic experience, the final analysed sample comprised 46 participants who provided usable resting-state fMRI data: 21 in the psilocybin group and 25 in the placebo group. Participants received either 0.17 mg/kg psilocybin dissolved in bitter lemon or plain bitter lemon as placebo. Resting-state fMRI was acquired approximately 102 minutes post administration (during peak subjective effects); a 6-minute scan was collected on a MAGNETOM 7 Tesla scanner (TR = 1400 ms; voxel size 1.5 mm isotropic) while participants fixated a cross. Preprocessing combined standard tools (FSL, HD-BET) within the Apéro MATLAB toolbox. Structural images were denoised, skull-stripped and segmented to derive tissue masks, and the Schaefer cortical parcellation with 200 regions was transformed to subject space. Functional data underwent slice-timing correction, motion correction, nuisance regression (18 regressors: six motion parameters plus derivatives and tissue/whole-brain signals), bandpass filtering (0.01–0.25 Hz) and an additional component-based cleaning step; the first principal components of CSF, white matter and whole-brain signals were regressed out before averaging voxels into regional time series. Head motion was quantified per volume using Frame Displacement, DVARS and the global standard deviation, and volumes exceeding thresholds were flagged; motion was included as a covariate in group comparisons because psilocybin subjects showed slightly higher motion. Functional connectomes were constructed as 200×200 Pearson correlation matrices between regional time series. For each subject, the time series was split in half to create test and retest FCs (temporal stability within the session), and an additional FC was computed from the unsplit time series for prediction analyses. Brain-fingerprinting metrics were computed: Iself (test–retest similarity within subject), Iothers (similarity to other subjects in the same treatment group) and Idiff (Iself minus Iothers) to quantify identifiability. Edgewise idiosyncrasy was quantified by intraclass correlation (ICC) computed separately per treatment group; ICC strength for a region was defined as the sum of ICCs of all edges incident to that region. For prediction of subjective experience, the investigators reduced behavioural data (21 subjects × 11 5D-ASC subdimensions) by principal component analysis (PCA) and used the first behavioural PC (PC1, b) as the target, interpreted as overall intensity of the drug experience. They then selected sets of FC edges either ranked by ICC in the psilocybin group (ICCpsi) or chosen at random, performed PCA on each selected-edge matrix, and fitted linear models predicting b from the first three FC PCs (x, y, z). Models were compared across varying numbers of edges (n) and significance assessed against random-edge baselines. Group comparisons of fingerprint metrics controlled for motion using linear models (measure ~ group + motion) and multiple comparisons were handled with FDR where applicable.

Sample and data: After exclusions for incomplete data and excessive motion, 21 psilocybin and 25 placebo subjects remained for analysis. Motion was slightly higher in the psilocybin group (mean difference = 4.22 flagged volumes; t = 2.06; p = 0.0456) and was modelled as a confound where appropriate. Identifiability: Using the full FCs, Iself did not differ significantly between groups (df = 43, t = -0.20, p = 0.8460), but psilocybin subjects showed lower Iothers (df = 43, t = -3.33, p = 0.0018) and higher Idiff (df = 43, t = 2.10, p = 0.0414) than placebo subjects after accounting for motion. This pattern indicates greater inter-subject FC dissimilarity under psilocybin while within-subject temporal stability (within the same scan) was preserved. Edgewise and regional idiosyncrasy: Edgewise ICC matrices (ICCpsi and ICCpla) revealed differential spatial distributions of idiosyncrasy. Averaged by resting-state network (RSN) connections, visual (Vis) and DMN edges tended to be more idiosyncratic in the psilocybin condition, whereas frontoparietal network (FPN) edges showed the opposite trend. ICC strength comparisons showed significantly higher idiosyncrasy in psilocybin than placebo for Vis regions (df = 45, t = 2.77, p = 0.0099; fdr = 0.0351) and DMN regions (df = 45, t = 5.25, p ≈ 0.0000; fdr = 0.0000). The FPN effect (df = 45, t = -2.07, p = 0.0472) did not survive FDR correction (fdr = 0.1000). Spatially, idiosyncratic edges concentrated in right lateral prefrontal FPN regions in placebo but shifted to DMN-associated areas (medial prefrontal cortex, posterior cingulate cortex, inferior parietal cortex) in the psilocybin group. Iterative selection of edges ranked by ICCpsi optimised Idiff in the psilocybin group, with a peak at low n (n = 100), whereas Idiff in the placebo group remained essentially flat across n. Prediction of subjective experience: Behavioural PCA on the 11 5D-ASC subdimensions produced a first PC explaining 45.7% of variance; its highest-loading aspects were insightfulness, experience of unity, blissful state and changed meaning of percepts, so the authors interpreted the PC1 subject scores (b) as overall intensity of the drug experience. For prediction, PCA was applied to sets of FC edges (either ICCpsi-ranked or random) and linear models regressed b onto the first three FC PCs (x, y, z). Across a range of n, idiosyncrasy-informed models consistently achieved higher R² than averaged random-edge models for n below a convergence threshold; models based on ICCpsi reached statistical significance at n = 2250 (p = 0.0499), 2500 (p = 0.0450) and 2750 (p = 0.0480). Examination of single-predictor models indicated that PC2 (y) tended to carry most of the predictive signal; specifically, at n = 1000 the single predictor y significantly predicted b (p = 0.0082) with R² = 0.31. PC3 (z) was also predictive at different n (e.g. n = 6500) but PC1 of the FC PCA (x) generally did not predict subjective experience and may have captured non-behavioural variance such as session differences. Characterisation of predictive FC pattern: The FC pattern captured by PC2 of the 1000 most idiosyncratic edges had strong positive loadings on edges involving PCC and mPFC and strong negative loadings on edges of the right anterior cingulate cortex (ACC). Reconstructing and averaging these edges at the RSN level produced archetypal matrices for subjects with positive y (rFC y+) and negative y (rFC y-). rFC y+ showed reduced within-DMN and DMN–limbic connectivity and increased connectivity between DMN and attentional (dorsal and ventral attention) and sensory (visual, somatomotor) networks. By contrast, rFC y- closely resembled the platelet-level placebo matrix derived from the same edges. When the edge selection was not guided by idiosyncrasy (i.e. using all edges), only DMN–limbic connectivity remained significantly correlated with b after FDR correction, supporting the value of ICC-based edge selection for boosting prediction of subjective psilocybin experience.

Tolle and colleagues interpret their findings as evidence that idiosyncratic FC features can be a valuable heuristic for isolating connectivity patterns that map onto individual subjective responses to psilocybin. The observation that psilocybin increased inter-subject FC heterogeneity (lower Iothers) while preserving within-subject temporal stability (unchanged Iself) aligns with the known variability of psychedelic experiences and suggests that FC captures meaningful individual differences in drug response. The authors note that earlier work with ayahuasca reported increased FC similarity in the drug condition, and argue that contextual factors—in that study participants belonged to the same ritualistic group—may explain the divergent result by producing more homogeneous experiences among those subjects. A key insight was the shift in the spatial distribution of idiosyncrasy from frontoparietal regions under placebo to DMN regions under psilocybin. Given the DMN's high 5-HT2A receptor density and its long-standing association with self-referential processing, the authors suggest this shift supports a central role for DMN reconfiguration in producing acute psychedelic phenomenology. The idiosyncrasy-informed FC pattern that best predicted subjective intensity (PC2) was characterised by reduced within-DMN and DMN–limbic coupling and increased DMN–attentional and DMN–sensory connectivity. These findings resonate with prior reports linking DMN disintegration to ego dissolution and with theories such as REBUS, which posit that psychedelics weaken top-down priors from higher-level networks (like the DMN) and thereby permit increased bottom-up signalling from intermediate and lower-level systems. The authors also discuss limbic and ACC involvement, noting prior observations that hippocampal and mPFC glutamate changes relate to differing subjective qualities of ego dissolution. The paper highlights potential clinical implications: because acute subjective experiences—particularly aspects related to ego dissolution—have been associated with therapeutic outcomes in psilocybin trials, the idiosyncratic DMN-related patterns identified here could inform future precision-medicine strategies. The authors envisage computational simulation frameworks where patient-specific neuroimaging informs simulated responses to interventions and aids personalised treatment selection. They also acknowledge limitations: the modest sample size (n = 46), short resting-state scans (6 minutes), and the operationalisation of test–retest reliability as temporal stability within a single acquisition rather than across sessions. Slightly greater head motion in the psilocybin group and the difficulty of maintaining blinding in psychedelic studies are further caveats; the investigators controlled for motion statistically and argue that ICC ranks within groups are relatively robust to motion outliers. They recommend replication with independent, multi-session datasets and consider dose-comparison designs as a way to address blinding challenges.

The study concludes that functional connectivity of the DMN to limbic and attentional systems plays a central role in mediating the acute subjective effects of psilocybin. Moreover, idiosyncrasy—measured via ICC and brain-fingerprinting metrics—serves as a practical criterion for identifying FC patterns that predict individual drug responses, and the authors present a simple framework for isolating such patterns. They suggest this approach may be valuable for future pharmacological neuroimaging studies and for advancing personalised psychedelic therapies.