A cognitive model is a representation of one or more cognitive processes in humans or other animals for the purposes of comprehension and prediction. There are many types of cognitive models, and they can range from box-and-arrow diagrams to a set of equations to software programs that interact with the same tools that humans use to complete tasks (e.g., computer mouse and keyboard).Sun, R. (ed.), (2008). The Cambridge Handbook of Computational Psychology. New York: Cambridge University Press. In terms of information processing, cognitive modeling is modeling of human perception, reasoning, memory and action.
Knowledge about the representation of cognitive processes in humans originated in Philosophy. It relies on two opposing philosophical approaches, internalism and externalism, which together explain the nature of the mind and its relation to the body and the external world. From the internalist's perspective, the modeling of human perception, reasoning, memory, and action is independent of the external world.Giuseppina D'Oro, "Collingwood, psychologism and internalism," European Journal of Philosophy 12(2):163–177 (2004). Current academic literature generally categorizes Internalism's cognitive models into three groups of representations of cognitive processes in humans: Box-and-Arrow models, these models identify the components involved in cognition; Computational Models explain the "rules" that govern how information moves between the structures defined above; Dynamical systems focus on how the system changes every instant.Palm, G. (2016). "Neural Information Processing in Cognition: We Start to Understand the Orchestra, but Where is the Conductor?" Frontiers in Computational Neuroscience, 10(3). https://doi.org/10.3389/fncom.2016.00003Xiong, A.; Proctor, R. W. (2018). "Information Processing: The Language and Analytical Tools for Cognitive Psychology in the Information Age". Frontiers in Psychology, 9, 1270. https://doi.org/10.3389/fpsyg.2018.01270 Philosophical ideas of Professors Andy Clark and David Chalmers have developed an externalist approach to modeling cognition, based on the active role of the environment in driving cognitive processes: extended mind thesis. According to this approach, because external objects play a significant role in aiding cognitive processes, the mind and the environment act as a "coupled system" that can be seen as a complete cognitive system of its own.; reprinted as: ; and available online as: Externalism is represented by the Mother-fetus neurocognitive model, which explains cognitive development in part as a function of the environment.
Relationship to cognitive architectures Cognitive models can be developed within or without a cognitive architecture, though the two are not always easily distinguishable. In contrast to cognitive architectures, cognitive models tend to be focused on a single cognitive phenomenon or process (e.g., list learning), how two or more processes interact (e.g., visual search and decision making), or making behavioral predictions for a specific task or tool (e.g., how instituting a new software package will affect productivity). Cognitive architectures tend to be focused on the structural properties of the modeled system, and help constrain the development of cognitive models within the architecture. Likewise, model development helps to inform limitations and shortcomings of the architecture. Some of the most popular architectures for cognitive modeling include ACT-R, Clarion, LIDA, and Soar.
History Cognitive modeling historically developed within cognitive psychology/cognitive science (including human factors), and has received contributions from the fields of machine learning and artificial intelligence among others. However, long before the "Cognitive Revolution" of the 1960s, scientists already began approaching mathematical and mechanical models of the mind. The early contribution to the field was made in 1885. Ludwig Lichtheim proposed an idea (later expanded on by Carl Wernicke) arguably the first prerequisite of the "Box-and-Arrow" model, mapping language processing into specialized "boxes" for auditory recognition and speech production, connected by neural pathways (arrows).Lichtheim, L. (1885). On aphasia. Broca’s Region, 318-347. Retrieved: https://pure.mpg.de/rest/items/item_2354888_3/component/file_2354887/content He established the Connectionist-Localist paradigm, which holds that complex functions such as language are not located in a single place but result from information flowing between specialized centers.Catani, M., & Mesulam, M. (2008). "The arcuate fasciculus and the disconnection theme: The history and current state of the concept". Cortex, 44(8), 953–961. https://doi.org/10.1016/j.cortex.2008.04.002 In 1943, Warren McCulloch and Walter Pitts created a mathematical model of a neuron as a set of logic gates to show how the brain could "compute" in their paper "A Logical Calculus of the Ideas Immanent in Nervous Activity".McCulloch, W. S.; Pitts, W. (1943). "A logical calculus of the ideas immanent in nervous activity". The bulletin of mathematical biophysics. 5(4), 115-133. In the same year, Kenneth Craik argued in "The Nature of Explanation" that the brain is a "calculating machine" building internal models of the world.Craik, K. J. W. (1967). The nature of explanation (Vol. 445). CUP Archive. Retrieved: https://books.google.lv/books?hl=it&lr=&id=wT04AAAAIAAJ&oi=fnd&pg=PA1&dq=Kenneth+Craik+(1943)&ots=09yTWwkUv8&sig=BP48fOTf5aJ8t50o0Ml8MWbFUrQ&redir_esc=y#v=onepage&q=Kenneth%20Craik%20(1943)&f=false Professors Richard Atkinson and Richard Shiffrin launched the "Box-and-Arrow" era in 1968 with the Atkinson-Shiffrin Multi-Store Model of Memory. This made the "Information-Processing" approach famous by drawing three distinct boxes for memory, describing flow between the sensory register (SR), short-term memory (STM), and long-term memory (LTM). In 1998, Professor van Gelder published the dynamical hypothesis in cognitive science. His dynamical model described how the system's state changes over time using several differential equations based on tracking data of the internal dynamics.van Gelder, T. (1998). The dynamical hypothesis in cognitive science . Behavioral and Brain Sciences, 21, 615-665. The opposite, externalist view on the cognition development was put forward by Latvian professor Igor Val Danilov in his Mother-fetus neurocognitive model in 2024.
Box-and-arrow models
The Box-and-Arrow model represents the mind as a system of functional components (the "boxes") connected by pathways of information flow (the "arrows"). This group of models describes what the mind does without necessarily explaining how the neurons fire. The most influential applications of this model include:
Atkinson-Shiffrin Multi-Store Model (1968): A classic memory theory proposing that information flows through three distinct "boxes": Sensory Memory, Short-Term Memory, and Long-Term Memory.
Broadbent’s Filter Model (1958): One of the earliest "bottleneck" theories of selective attention, using a box-and-arrow diagram to show how sensory information is filtered before reaching higher-level processing.Lachter, J.; Forster, K. I.; Ruthruff, E. (2004). "Forty-five years after Broadbent (1958): Still no identification without attention". Psychological Review, 111(4), 880–913.
Baddeley’s Working Memory Model (1974/2000): Refines the "short-term memory box" into a multi-component system including the Central Executive, Phonological Loop, and Visuospatial Sketchpad.Baddeley, A. D. (2000). "The episodic buffer: A new component of working memory?" Trends in Cognitive Sciences, 4(11), 417–423. DOI: 10.1016/S1364-6613(00)01538-2
Norman and Shallice (1986) CS/SS Model: A model of cognitive control that uses "boxes" to represent Contention Scheduling (routine actions) and the Supervisory Attentional System (complex tasks).Cooper, R.; Shallice, T. (2000). "Contention scheduling and the control of routine activities". Cognitive Neuropsychology, 17(4), 297–338. https://doi.org/10.1080/026432900380427
Three major principles:
Modularity: the mind is composed of separate "modules."Fodor, J. A. (1983). The modularity of mind: An essay on faculty psychology. MIT Press.
Serial Processing (Directional Flow): information usually moves in a linear, step-by-step fashion.Sternberg, S. (1969). "The discovery of processing stages: Extensions of Donders' method". Acta psychologica, 30, 276-315. https://doi.org/10.1016/0001-6918(69)90055-9
Discrete Stages: each box completes its job in its entirety before passing the result to the next box. This is the opposite of the Dynamical Systems approach, which sees everything as a continuous, messy overlap.
Computational models
A computational model is a mathematical model in computational science that requires extensive computational resources to study the behavior of a complex system by computer simulation. Computational cognitive models examine cognition and cognitive functions by developing process-based computational models formulated as sets of mathematical equations or computer simulations. The system under study is often a complex nonlinear system for which simple, intuitive analytical solutions are not readily available. Rather than deriving a mathematical analytical solution to the problem, experimentation with the model is done by changing the parameters of the system in the computer, and studying the differences in the outcome of the experiments. Theories of operation of the model can be derived/deduced from these computational experiments. Examples of common computational models are weather forecasting models, earth simulator models, flight simulator models, molecular protein folding models, and neural network models.
Symbolic A symbolic model is expressed in characters, usually non-numeric ones, that require translation before they can be used.
Subsymbolic A cognitive model is subsymbolic if it is made by constituent entities that are not representations in their turn, e.g., pixels, sound images as perceived by the ear, signal samples; subsymbolic units in neural networks can be considered particular cases of this category.
Hybrid Hybrid computers are computers that exhibit features of analog computers and digital computers. The digital component normally serves as the controller and provides logical operations, while the analog component normally serves as a solver of differential equations. See more details at hybrid intelligent system.
Dynamical systems
In the traditional computational approach, representations are viewed as static structures of discrete symbols. Cognition takes place by transforming static symbol structures in discrete, sequential steps. Sensory information is transformed into symbolic inputs, which produce symbolic outputs that get transformed into motor outputs. The entire system operates in an ongoing cycle.
What is missing from this traditional view is that human cognition happens continuously and in real time. Breaking down the processes into discrete time steps may not fully capture this behavior. An alternative approach is to define a system with (1) a state of the system at any given time, (2) a behavior, defined as the change over time in overall state, and (3) a state set or state space, representing the totality of overall states the system could be in. The system is distinguished by the fact that a change in any aspect of the system state depends on other aspects of the same or other system states.van Gelder, T. & Port, R. F. (1995). It's about time: An overview of the dynamical Approach to cognition . In R.F. Port and T. van Gelder (Eds.), Mind as motion: Explorations in the Dynamics of Cognition. (pp. 1-43). Cambridge, Massachusetts: MIT Press.