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Jeremy I. Skipper

Publications and source records attributed to Jeremy I. Skipper.

2 recordsLinked to original sources

How to set up a psychedelic study: Unique considerations for research involving human participants

Setting up a psychedelic study can be a long, arduous, and kafkaesque process. This rapidly-developing field poses several unique challenges for researchers, necessitating a range of considerations that have not yet been standardised. Many of the complexities inherent to psychedelic research also challenge existing assumptions around, for example, approaches to psychiatric prescribing, the conceptual framing of the placebo effect, and definitions of selfhood. This review paper brings together several of the major psychedelic research teams across the United Kingdom to formalise these unique considerations, identify continuing areas of debate, and provide a practical, experience-based guide, with recommendations for policymakers and future researchers intending to set up a psychedelic research study or clinical trial. We approach this such that the paper can either be read end to end, or treated as a manual: readers can dip into relevant sections as needed.

q-bio.NC

Separating Stimulus-Induced and Background Components of Dynamic Functional Connectivity in Naturalistic fMRI

We consider the challenges in extracting stimulus-related neural dynamics from other intrinsic processes and noise in naturalistic functional magnetic resonance imaging (fMRI). Most studies rely on inter-subject correlations (ISC) of low-level regional activity and neglect varying responses in individuals. We propose a novel, data-driven approach based on low-rank plus sparse (L+S) decomposition to isolate stimulus-driven dynamic changes in brain functional connectivity (FC) from the background noise, by exploiting shared network structure among subjects receiving the same naturalistic stimuli. The time-resolved multi-subject FC matrices are modeled as a sum of a low-rank component of correlated FC patterns across subjects, and a sparse component of subject-specific, idiosyncratic background activities. To recover the shared low-rank subspace, we introduce a fused version of principal component pursuit (PCP) by adding a fusion-type penalty on the differences between the rows of the low-rank matrix. The method improves the detection of stimulus-induced group-level homogeneity in the FC profile while capturing inter-subject variability. We develop an efficient algorithm via a linearized alternating direction method of multipliers to solve the fused-PCP. Simulations show accurate recovery by the fused-PCP even when a large fraction of FC edges are severely corrupted. When applied to natural fMRI data, our method reveals FC changes that were time-locked to auditory processing during movie watching, with dynamic engagement of sensorimotor systems for speech-in-noise. It also provides a better mapping to auditory content in the movie than ISC.

q-bio.NC