Sackler Centre for Consciousness Science


Reny Baykova PhD student

Reny BaykovaReny joined the Sackler Centre as a funded PhD student from the 4-Year Sussex Neuroscience PhD programme. Reny is using behavioural, neuroimaging, and computational methods to investigate how we build predictions in perception, and how mismatch negativity relates to perception within the framework of predictive coding. She has a background in psychology and previously completed an MSc in Research Methods in Psychological Science with Distinction at the University of Glasgow.

Clémence Compain PhD student

Image of Clemence CompainClémence joins us from Paris Descartes University where she completed her Master's in Cognitive Science and is now a student on the University of Sussex Leverhulme-funded PhD programme.

Under supervisors Prof. Anil Seth and Dr Maxine Sherman,Clémence is investigating perceptual biases and metacognition during visual decision-making. Humans have the ability to be aware of their own performance, an ability called metacognition. It is generally evaluated by a retrospective confidence judgment about the belief that the choice made is correct. Confidence judgments emerge from both sensory evidence and internal noise, reflecting the quantity and the quality of perceptual information. However, perception can be biased by prior beliefs and knowledge about the world. Clémence's research aims to investigate the awareness of humans’ objective and metacognitive biases, and the influence of the biases’ awareness on subsequent choices and on confidence about these choices

Guillaume Corlouer PhD student

Guillaume CorlouerGuillaume completed a BSc in fundamental physics and an MSc in pure mathematics and theoretical physics (University of Paris Saclay) working in algebraic geometry and representation theory.

He his now applying mathematics, in particular time series analysis, Granger causality and information-theoretic methods under the supervision of Dr. Lionel Barnett and Prof. Anil Seth to understand the flow of information in brain circuits correlated to various perceptions and quantify its complexity.

Tomek Korbak PhD student

Photo of Tomek KorbakTomek Korbak completed an MSc and a BSc in Cognitive Science and a BA in Philosophy at University of Warsaw where he worked on enactivist accounts of cognition and compositional generalisation in neural networks.

At Sussex, he is now focusing on Bayesian and biologically-inspired approaches in machine learning and computational neuroscience, working under the supervision of Dr. Chris Buckley and Prof. Anil Seth and supported by the Leverhulme Doctoral Scholarship. In particular, Tomek is interested in variational inference and its applications in reinforcement learning as part of frameworks such as active inference, control-as-inference and learning with intrinsic motivation.

Alberto Mariola PhD student

Alberto MariolaAlberto completed a BSc in Cognitive Psychology at the University of Trento and an MSc in Cognitive Neuroscience at the Berlin School of Mind and Brain (“Mind and Brain” Master - Track: Brain). He’s currently pursuing a Ph.D as part of the 4-Year Sussex Neuroscience PhD Programme under the supervision of Prof. Anil Seth, Dr. Warrick Roseboom and Dr. Luc Berthouze. 

His project aims at investigating the neural and phenomenological consequences of conviction about reality (CR) manipulations. More specifically, he is using SR/VR technologies, EEG and eye-tracking to assess the influence that metacognitive beliefs about reality can exert in cases of perceptual uncertainty about the environment.

Federico Micheli PhD student

Image of Federico MicheliFederico completed a BSc in Psychology at the University of Florence and an MSc in Cognitive Neuroscience at CiMeC (University of Trento). He has worked on patients with disorders of consciousness, complexity measures and neural correlates of Parkinson's disease.
He is now focusing on top-down generation of perceptual experience, working under the supervision of Prof. Anil Seth. In a "predictive brain" view, conscious perceptual content is determined by the brain's "best guess" of the causes of sensory inputs, and is shaped or constituted by predictions or expectancies about these causes. His project will investigate the neural dynamics underlying (human) conscious perception via different approaches. In particular, the project aims to shed light on the different role of "bottom-up" and "top-down" connections in the brain in the shaping of conscious experience.

Isabel Muranhao PhD student

Image of Isabel MuranhaoIsabel joined the Sackler Centre under the supervision of  Warrick Roseboom and Miguel Maravall. She uses behavioural and imaging methods to research the causes of individual differences in temporal processing, including in individuals who seem to have a deficit in these processes, like in dyslexia.

Nadine Spychala PhD student

Nadine SpychalaNadine completed a BSc in Psychology at the University of Hamburg and a MSc in Neurocognitive Psychology as well as a MA in Philosophy at the Carl von Ossietzky University of Oldenburg where she has been working on variational inference and integrated information. 

She is now focusing on neural measures of complexity and emergence related to conscious processing, working under the supervision of Prof. Anil Seth and Dr. Adam Barrett and supported by the Leverhulme Doctoral Scholarship. In particular, she aims to apply mathematical models based on information theory to neural data and use machine learning techniques to investigate how complexity and emergence may inform an account of differences in conscious states.

Alec Tschantz PhD student

Alec TschantzAlec completed a BSc in Psychology and Philosophy (University of Hull) and an MSc in Intelligent Systems (University of Sussex). During this time, he focused on modelling biological processes such as perception, action and learning.

Under the supervision of Prof. Anil Seth and Dr. Chris Buckley, Alec will now be looking at how humans actively extract information from their environment. In particular, he aims to ask whether saccacdic eye movements can be described by the active inference framework.