Cognitive psychology, simply stated, is the study of the nervous system’s information processing. It includes the circuitry that performs such processing, as well as the behaviors following from it. As Neisser first defined it, “cognition refers to all the processes by which the sensory input is transformed, reduced, elaborated, stored, recovered, and used” (Neisser, 1967, via Wikipedia). Several approaches to the discipline have developed, each distinguished by its domain, techniques, assumptions, strengths, and weaknesses: experimental, neuroscience, neuropsychology, and computational science have each contributed to our growing understanding of the brain’s organization and function (Eysenck and Keane, 2010).
The early pioneers of modern cognitive psychology used experimental techniques to test their speculations about cognitive processes, and were in turn forced to develop novel theories to explain the sometimes surprising results. The fruits of their work are enjoyed throughout psychology’s subdisciplines, for which experimental cognitive psychology has provided key theoretical frameworks. Though it has been the central methodological catalyst for cognitive psychology since the “cognitive revolution” of the late 1950s and 1960s (which was sparked by Chomsky’s critique of behaviorism – the then dominant paradigm in psychology – and propelled by [my mentor’s mentor] Donald Broadbent’s early work), experimentation’s limitations (such as theoretical vagary, paradigm specificity, and the lack of native theoretical frameworks) have, over time, driven many cognitive psychologists to bring other approaches to bear on the field.
One such approach, cognitive neuroscience, investigates processing wielding high-tech imaging technologies that grant unprecedented access to the inner workings of the living brain. Using such diverse techniques as single-unit recording, event-related potentials (ERPs), positron emission tomography (PET), functional magnetic resonance imaging (fMRI), event-related functional magnetic resonance imaging (efMRI), magneto-encephalography (MEG), and transcranial magnetic stimulation (TMS), cognitive neuroscience offers “excellent temporal and spatial resolution” (Ibid.) of neural activity corollary to the observed behavior or instructions. But as with all approaches, functional neuroimaging techniques suffer from a number of limitations, such as uncertain relevance, task restriction, and limited ecological validity, only fully overcome through converging operations (Ibid.).
Cognitive neuropsychology uses double dissociations to distinguish processing systems in brain-damaged patients. Neuropsychology assumes functional modularity, anatomical modularity, and species-wide uniformity of functional architecture, and investigates both case studies and group (Ibid.). But again, limitations, such as patient’s potential compensatory strategies and the inherent arbitrariness of each injury’s extent, make the approach dependent on the strengths of others, such as computational cognitive science. Computational approaches bring precision to the often vague formulations generated by experimenters and systems-scale structure to the correlational evidence generated by neuroscientists. But computational models are seldom predictive, and are insensitive to motivational and emotional factors (Ibid.).