Project ID BE-MI2024_05


Co Supervisor 1A Institute of Psychiatry, Psychology & Neuroscience,School of Neuroscience, Department of NeuroimagingWebsite

Co Supervisor 1B Institute of Psychiatry, Psychology & Neuroscience, School of Neuroscience, Department of NeuroimagingWebsite

Additional Supervisor Dr Joseph Barnby

Self and Others: Multimodal Characterisation and Modelling of the role of Endogenous Modulatory Control Mechanisms in Responses to Aversive Stimuli in Health and Disease.

The way in which we process and interpret incoming aversive stimuli (such as pain) from the environment plays a fundamental role in many physical and mental health problems. Many conditions intuitively linked to aversive processing often occur together, for example, chronic pain and anxiety. Accordingly, it is possible that the way we encode aversive stimuli in general is underpinned by common brain mechanisms. An important likely set of candidate mechanisms includes “top-down” modulatory processes, which can magnify or diminish how we perceive incoming aversive stimuli. We hypothesise that these modulatory systems contribute to how we learn and make decisions, but importantly also that these processes change in patients with health problems.

Top-down processes occur within in an individual, but we think interactions between individuals are also important. We will investigate how modulation may be heightened or attenuated based on whether we believe the source of aversive stimuli comes from another human, rather than more generally from the outside world. In this project we will use cutting-edge multimodal neuroimaging technologies (EEG/fMRI) to characterise brain mechanisms underpinning top-down modulation of aversive stimuli. We will examine how social and environmental factors influence these processes and how they relate to symptoms reported by patients with common mental and physical health problems. The project will equip the successful candidate with skills in behavioural testing, acquisition and analysis of multimodal neuroimaging data and advanced statistical analysis and computational modelling techniques.

Yearly objectives:

1-Systematic review of the literature on top-down modulation of aversive responses across stimulus modalities on the individual and social level. Design of the main study, including task selection, design, and ethics application.
2-Data collection using the protocol designed in Year 1. Training in computational modelling and EEG and fMRI analysis.
3-Data analysis, thesis submission and results dissemination.

Representative Publications

1. Jackson JB, O’Daly O, Makovac E, Medina S, Rubio AL, McMahon SB, et al. Noxious pressure stimulation demonstrates robust, reliable estimates of brain activity and self-reported pain. Neuroimage. 2020;221:117178.

2.Makovac E, Venezia A, Hohenschurz-Schmidt D, Dipasquale O, Jackson JB, Medina S, et al. The association between pain-induced autonomic reactivity and descending pain control is mediated by the periaqueductal grey. J Physiol. 2021;599(23):5243-60.

3. Ruffle JK, Hyare H, Howard MA, Farmer AD, Apkarian AV, Williams SCR, et al. The autonomic brain: Multi-dimensional

1. Wise, T., & Dolan, R. J. (2020). Associations between aversive learning processes and transdiagnostic psychiatric symptoms in a general population sample. Nature Communications, 11(1), 4179.
2. Wise, T., Michely, J., Dayan, P., & Dolan, R. J. (2019). A computational account of threat-related attentional bias. PLoS Computational Biology, 15(10), e1007341.
3. Wise, T., Liu, Y., Chowdhury, F., & Dolan, R. J. (2021). Model-based aversive learning in humans is supported by preferential task state reactivation. Science Advances, 7(31), eabf9616.