University of Birmingham
Psychology Title



Computational Psychology Lab


Research themes Methods Researchers and collaborators (current and past) Current and past sponsors

Visual attention & perception, Object recognition, Speed-accuracy-trade-off, cognitive control Computational modelling, Bayesian model fitting, Visual search tasks,
G. W. Humphreys (Oxford), A. Backhaus (PhD), Y. Zhao (PhD), E. Mavritsaki (PostDoc, now: Birmingham City), Y. Sun (PostDoc), G. Anderson (PhD), Y.-S. Lin (PhD, now: Tasmania), M. Kristan ( Ljubljana), V. Narbutas (PhD), A. Schofield (Aston Uni), D. Standage (PostDoc) EPSRC, BBSRC, EPSRC DTA, Marie-Curie

Interaction between visual processing and movement execution Choice reaching tasks, target reaching, Neurorobotics, Transcranial direct-current stimulation (tDCS) P. Woodgate (PhD), S. Strauss (PhD), J. Wolska (PhD), T. Trappenberg (Halifax, CA), A. Wing (UoB), C. Miall (UoB), J. Galea (UoB) EPSRC DTA

Extraction of action possibilities of objects (affordances) & tool use Computational modelling, Behavioural experiments, Transcranial magnetic stimulation (TMS), functional magnetic resonance imaging (fMRI) G. W. Humphreys (Oxford), C. Boehme (PhD), E. Y. Yoon (PhD), C. Mevorach (UoB), S. Xu (PhD, Now: Beijing Normal), F. Osiurak (Lyon) EPSRC

Psychological disorders (autism, Psychosis) Computational modelling, non-linear statistics A. Abu-Akel (PhD, now: Lausanne), C. Mevorach (UoB)

Social Cognition, Social processes Computational modelling, False recognition paradigm, Agent-based modelling Diana Orghian ( Lisbon; Media Lab, MIT), L. Garcia-Marques (Lisbon) ,J. Christian (UoB) Greg Carslaw (PhD), Z. Yousefi (PhD) Marie-Curie, ESRC-studenship

Visual attention & perception

This research theme mainly revolves around how humans process visual scenes. It is generally agreed that visual attention plays a critical role in dealing with the 'information overload' from such scenes typically. CPL's projects focus on how attention is directed towards behaviourally-relevant objects (visual search) and how these objects are recognized (object recognition). An interesting question (and rarely examined) is how the speed of finding object is balanced with the quality of detection (speed-accuracy-trade-off). Performing this balancing act is often attributed to cognitive control.

Selected publications
Narbutas, V., Lin, Y.-S., Kristan, M., & Heinke, D. (2017) Serial versus parallel search: A model comparison approach based on reaction time distributions. Visual Cognition , 1-3, 306-325.

Mavritsaki, E. , Heinke, D. , Allen H., Deco, G., & Humphreys, G. W. (2011) Bridging the gap between physiology and behavior: Evidence from the sSoTS model of human visual attention. Psychological Review, 118(1), 3-41.

Anderson, G.M, Heinke, D. & Humphreys, G. W. (2013) Top-down guidance of eye movements in conjunction search. Vision Research, 79, 36-46.

Zhao, Y., Heinke, D., Ivanoff, J., Klein, M. K. & Humphreys, G. W. (2011) Two components in IOR: Evidence for response bias and perceptual processing delays using the SAT methodology. Attention Perception & Psychophysics, 73(7), 2143-2159. DOI: 10.3758/s13414-011-0181-z

Heinke, D. & Backhaus, A.(2011) Modeling visual search with the Selective Attention for Identification model (VS-SAIM): A novel explanation for visual search asymmetries. Cognitive Computation, 3(1), 185-205. Open Access

Heinke, D., & Humphreys, G. W. (2003). Attention, spatial representation and visual neglect: Simulating emergent attention and spatial memory in the Selective Attention for Identification Model (SAIM). Psychological Review, 110(1):29-87. Abstract Complete draft (1.3MB)

Interaction between visual processing and movement execution

This research them is a more recent addition to CPL's research activities. It links with the visual attention&perception theme and is interested in how the processing of visual scenes is translated into reach movements towards behaviourally-relevant objects e.g., reaching for your cup of coffee on the breakfast table while ignoring the beer glass from last night. In cognitive neuroscience this constitutes a relatively novel research question as typically movement control and visual processing are examined separately. However, CPL novel approach is to examine both mechanisms in the same experimental set-up (e.g., choice reaching task). This empirical work also goes along with the development of control architectures for robot arms aiming to mimic human reaching (robotics models).

Selected publications
Fard, F. S., Hollensen, P., Heinke, D.,& Trappenberg, T. P. (2015) Modeling human target reaching with an adaptive observer implemented with dynamic neural fields. Neural Networks, 72, 13-30.

Strauss, S., Woodgate, P.J.W., Sami, S. A., & Heinke, D. (2015) Choice reaching with a LEGO arm robot (CoRLEGO): The motor system guides visual attention to movement-relevant information. Neural Networks, 72, 3-12.

Woodgate, P.J.W., Strauss, S., Sami, S. A., & Heinke, D. (2015) Motor cortex guides selection of predictable movement targets. Behavioural Brain Research, 287, 238-246.

Affordances & tool use

In this theme CPL examines how humans extract action possibilities (e.g. grasping, turning, and hammering) from visual objects. This theme particularly focus on how humans realize this extraction without the usage of semantic information (i.e., without recognising objects) and instead use geometrical properties e.g., handles. In recent years, CPL has extended this theme to how we are able to use tools. Of particular interest is the question how we are able to decide that we can use a pocket knife to turn a screw i.e., unusual tool use. Hereby CPL focuses not only on affordances but also at the involvement of problem solving.

Selected publications
Osiurak, F., & Heinke, D. (2018) Looking for Intoolligence: A unified framework for the cognitive study of human tool use and technology. American Psychologist , 73(2), 169-185.

Xu, S., & Heinke, D. (2017) Implied between-object actions affect response selection without knowledge about object functionality. Visual Cognition, 1-3, 152-168.

Xu, S., Humphreys, G. W., Mevorach, C., & Heinke, D. (2017) The involvement of the dorsal stream in processing implied actions between object pairs: a TMS study. Neuropsychologia, 95, 240-249.

Xu, S., Humphreys, G. W., & Heinke, D. (2015) Implied actions between paired objects lead to affordance selection by inhibition. Journal of Experimental Psychology: Human Perception and Performance, 41(4), 1021-1036.

Yoon, E. Y., Heinke, D., & Humphreys, G. W. (2002). Modelling direct perceptual constraints on action selection: The Naming and Action model (NAM). Visual Cognition, 9(4/5):615-661. Abstract

Psychological disorders

This theme is the latest addition to CPL's activities. CPL's contribution mainly focuses on using advanced statistics and computational modelling of cognitive mechanisms to advance our understanding of these disorders.

Selected publications
Abu-Akel, A., Heinke, D., Gillespie, S. M., Mitchell, I. J., & Bo, S. (2015) Metacognitive impairments in schizophrenia are arrested at extreme levels of psychopathy: The cut-off effect. Journal of Abnormal Psychology, 124, 4, 1102-1109.

Social processes

In this research theme CPL mainly focus on how a person's traits (e.g., good, intelligent, etc.) are inferred from the person's behaviours (e.g., helped an older lady across the street).
In addition we explore how the behaviour of social groups links with the behaviour of individuals using agent-based models.

Selected publications
Orghian, D., Smith, A., Garcia-Marques, L., & Heinke, D. (2017) Capturing spontaneous trait inference with the modified free association paradigm. Journal of Experimental Social Psychology, 73, 243-258.

Orghian, D., Garcia-Marquesa L., Uleman, J. S. , & Heinke, D. (2015) A Connectionist Model of Spontaneous Trait Inference and Spontaneous Trait Transference. Social Cognition, 33,1, 20 - 66.

Heinke, D., Carslaw, G. & Christian J. (2013) An Agent-based Simulation of Destigmatization (DSIM): Introducing a Contact Theory and Self-fulfilling Prophecy Approach. Journal of Artificial Societies and Social Simulation, 16(4), 10. paper