M. Emrah Aktunç

I studied psychology at the undergraduate and graduate levels. My graduate work in psychology was at the University of Iowa where I did research in cognitive psychology (word learning and working memory) and behavioral neuroscience (neurobiology of spatial learning and reward processing).

 

At Iowa, I began being seriously interested in the philosophical and methodological issues that arise in psychological science, which led me to pursue a doctoral degree in science studies focusing on philosophy of science.

I got my Ph.D. from the Science and Technology Studies program at Virginia Tech where I wrote my dissertation under the supervision of Professor Deborah Mayo. My dissertation is entitled “Experimental Knowledge in Cognitive Neuroscience: Evidence, Errors, and Inference” and it focuses on the epistemology of functional neuroimaging. I addressed essential questions, such as 'what can we really learn from cognitive neuroscience?', and analyzed the logic, epistemology, and the statistics of functional neuroimaging experiments. A central aspect of my work was applying Deborah Mayo’s error-statistical philosophy of science to issues of evidence and inference that arise in this field with the aim of clarifying and hopefully helping resolve these issues. Specific themes included carrying out historical and conceptual analyses of elements of neuroimaging; such as the physical and physiological bases of the workings of neuroimaging machines, statistical analysis techniques, and the inferential relationships between hypotheses about human cognition and neuroimaging data.

 

My dissertation provides the outlines of the error-statistical approach to the cognitive sciences. I currently work on the further development and expansion of my doctoral work in pursuance of its theoretical and empirical consequences. My doctoral work began to clarify what we can reliably learn from neuroimaging and how this knowledge can be used to produce novel and fruitful conceptualizations of human cognition. These include new approaches to answering the question 'how is cognition realized by the central nervous system?' as well as exploring possibilities for novel cognitive architectures (perhaps including glial contributions to cognition) which can be investigated in biologically realistic neural network simulations.

In addition, I lead a group enthusiastic undergraduate students in which we do experimental work in the cognitive science of reasoning. This line of work includes behavioral experiments on tasks of inductive reasoning and inference in which factors that improve inductive reasoning and their neural substrates are investigated. Reasoning under uncertainty and cognitive processing of error and uncertainty under different contingencies are specific topics of our experimental projects.

 

I also plan to collaborate with computational neuroscientists to develop biologically realistic models of processes of inductive reasoning.