Thesis title: Novel neurometric measures to discriminate models of speeded decision making
Carmen’s PhD research explores how sensory information is accumulated and used to guide behaviour, a process known as perceptual decision making. She focuses on a particular group of computational models which describe this process, namely sequential sampling models. These models propose that people make perceptual decisions by accumulating noisy sensory evidence until a decision threshold is reached. In her project, Carmen aims to evaluate the accuracy of these models. To do this, a number of models (Drift Diffusion Model, Linear Ballistic Accumulator, Leaky Competing Accumulator) are fit to behavioural data to produce predictions of evidence accumulation. She also collects EEG (electroencephalography) and MEP (motor evoked potential) data to explore neural activity patterns which are thought to reflect the accumulation of evidence (such as event-related potentials and event-related desynchronisation). By directly comparing neural signals to model predictions, she hopes to evaluate sequential sampling models and gain a better insight into evidence accumulation in speeded decision making.
- EEG analysis
- Computational Modeling (system level models)
- Perceptual Decision Making
- Brain Stimulation (including magnetic and electrical stimulation)
Skills & Methods:
- Matlab (Mathworks): data analysis & visualisation, experimental design (Matlab toolboxes include Psychtoolbox (Brainard, 1997; Pelli, 1997; Kleiner et al, 2007), EEGLAB toolbox (Swartz Centre for Computational Neuroscience), FieldTrip (Donders Institute)
- Electroencephalography (EEG): types of analysis include event-related potentials, event-related (de-)synchronisation, (time-)frequency decompositions, permutation-based cluster analyses etc.
- Transcranial magnetic stimulation (TMS)
- Transcranial electrical stimulation (tDCS/tACS/tRNS)
- Electromyography (EMG)
- Eye tracking (EyeLink 1000)
Publications & Conference Contributions
- Kohl, C., Spieser, L., Forster, B., Bestmann, S. & Yarrow, K. (2016). Neural Substrates of the Decision Variable: Exploring the CPP under Speed/Accuracy Instructions. In: LSNeuron2016 Abstract Proceedings 06-07 March 2016 London, UK. London, UK, 21.
- Kohl, C., Spieser, L., Forster, B., Bestmann, S. & Yarrow, K. (2015). Testing Models of Speeded Decision Making. Poster Presentation. Model-Based Neuroscience Summer School.
- Bennetts, R., Bate, S., Penton, T., Kohl, C. and Banissy, M., 2015. Transcranial random noise stimulation and cognitive training improves face perception. In: Cognitive Neuroscience Society Annual Meeting 28-31 March 2015 San Francisco, California. Davis, California: Cognitive Neuroscience Society, 153.
- Kohl, C. & Robertson, J. (2014). The Sexual Overperception Bias: An Exploration of the Relationship between Mate Value and Perception of Sexual Interest, Evolutionary Behavioral Sciences, 1(8), 31-43.
- Bennetts, R., Penton, T., Kohl, C., Banissy, M. and Bate, S., 2014. Transcranial electric stimulation and cognitive training improves face perception. In: Perception: European Conference on Visual Perception 24-28 August 2014 Belgrade, Serbia. London, UK: Pion, 16.
Awards & Grants
- 2015 Travel Grant: Okinawa Institute of Science and Technology (Computational Neuroscience Course)
- 2014 PhD Scholarship funded by the Leverhulme Trust
- 2014 Goldsmiths Psychology Prize for highest overall degree
- 2013 British Psychological Society Award for Undergraduate Psychology
- Developing Research Skills in Counselling Psychology: Statistics and SPSS tutorials for doctoral students
- Research Design and Statistics: Statistics lectures and SPSS tutorials for postgraduate students