This research has been supported by the Office of Naval Research Grant N00014-02-1-0037 and the Multidisciplinary Research Program of the University Research Initiative (MURI) Grant N00014-01-1-0677

The original CAPS architecture (Thibadeau et al., 1982) synthesizes symbolic and activation-based processing as it was understood in the early 1980s, and in this regard resembles other hybrid efforts of the time (Anderson, 1983; Hofstadter et al., 1983; Holland et al., 1985; Erman et al., 1980; Minsky, 1985; Rumelhart & McClelland, 1982). Its computational mechanisms include variable-binding, constituent-structured representations, graded activations, weights, thresholds, and parallel processing. The suitability of CAPS for accounting for high-level cognition has been demonstrated by successful models of language comprehension (Just & Carpenter, 1987; Thibadeau et al., 1982), mental rotation (Just & Carpenter, 1985), and problem solving (Carpenter et al., 1990).

CAPS was succeeded by 3CAPS (Just & Carpenter, 1992; Just & Varma, 2002), which adds constraints on the resources available for maintaining and processing representations. This enables computational explorations of individual differences on a number of tasks: sentence comprehension in young adults of different working memory capacities (Just & Carpenter, 1992); sentence comprehension in intact normals and aphasics (Haarmann et al., 1997); discourse comprehension in young adults (Goldman & Varma, 1995); problem solving in normal adults different in fluid intelligence (Just et al., 1996); problem solving in intact normals and patients with frontal lobe lesions (Goel et al., 2001); and human-computer interaction (Byrne & Bovair, 1997; Huguenard et al., 1997). The success of these models furthers the case that human information processing employs hybrid computational mechanisms in a capacity-constrained environment.

CAPS and 3CAPS models account for behavioral measures of high-level cognition collected from normal young adults and neuropsychological patients, broadly defined. 4CAPS, the latest member of the CAPS family, extends to new measures and new populations. Like their predecessors, 4CAPS models account for the time course of cognition and for individual differences. Unlike their predecessors, they also account for neuroimaging measures of normal cognition, and they provide much more precise accounts of the behavioral consequences of cortical lesions.

An initial principle is intended to capture the current consensus of the field.

0. Thinking is the product of the concurrent activity of multiple brain areas that collaborate in a large-scale cortical network.

1. Each cortical area can perform multiple cognitive functions, and conversely, many cognitive functions can be performed by more than one area.
2. Each cortical area has a limited capacity of computational resources, constraining its activity.
3. The topology of a large-scale cortical network changes dynamically during cognition, adapting itself to the resource limitations of different cortical areas and to the functional demands of the task at hand.
4. The communications infrastructure that supports collaborative processing is also subject to resource constraints, construed here as bandwidth limitations.

5. The activation of a cortical area as measured by imaging techniques such as fMRI and PET varies as a function of its cognitive workload.

The model defines a sim command for simulating comprehension of a sentence and a summ command for pretty-printing the temporal and resource utilization results. These are the components from which the above study-specific commands are built. The user can use them to write commands for simulating different studies. (The user must also extend the model's lexicon, which is defined in a straightforward fashion in the middle of the file.)

At the bottom of the file, five commands are defined for testing the model's performance on problems of increasing complexity. These are invoked as:
      (test1)
      (test2)
      (test3)
      (test4)
      (test5)
The model defines a sim command for simulating the solution of a given problem and a summ command for pretty-printing the temporal and resource utilization results. These are defined at the bottom of the file and used by the various test commands. It is easy to infer how these work and to write new commands that have the model solve different problems. There are two TOL studies. The "old" study is the published study Newman et al. (2003). The "new" study is the unpublished study conducted by Sharlene Newman and Greg Sliwoski. It uses different problems and more strictly varies problem complexity. The file for simulating the problems of these studies is located here. The following command simulates solution of all old problems:
     (old-sims)
This one simulates all new problems,
     (new-sims)
and this one all old and new problems:
     (all-sims)

The columns have the following meanings:
START: The starting state number. The state space is given in Newman et al. (2003), with each state numbered. (A problem is defined by a starting state and an ending state.)
END: The ending state number
RESULT: Whether the model solved the problem.
MIN?: Whether the problem was solved in a minimum number of moves.
MINMOV: The minimum number of moves required to solve the problem.
MODMOV: The number of moves required by the model.
CYCS: Time required by the model.
BLOPOS: Don't worry about this for now.

The following commands also simulate the solution of old and new problems, respectively, but display the results as a function of increasing minimum-length solutions.
     (fig-old-sims)
     (fig-new-sims)
They make clear the aspects of model performance that vary with increasing problem difficulty.

At the bottom of the file is a command for simulating the solution of the Shepard and Metzler (1971) (SM) problems used by Carpenter et al. (1999):
      Carpenter et al. (1999): (mr1999)

The model defines a sim command for simulating the solution of a given problem:
     (sim &key (angle 40) (mirror-p nil))
The angle parameter is the angular disparity between the two SM figures. When mirror-p is nil, the figures are congruent; when it is t, they are mirror-images of one another. All simulations run by the sim command currently use the same SM figure (and its mirror image). Why? The model itself is perfectly general. However, it is quite cumbersome to define new SM figures using the Marr and Nishihara (1977) representational scheme that the model adopts. The structure of the figure is documented in the header comment for the sim command, and can be changed by people of sufficient bravery.

The model also defines a summ command for pretty-printing the temporal and resource utilization results. These are defined at the bottom of the file and used by the mr1999 command. They can be combined by the user into commands that simulate the results of other studies.

At the bottom of the file is a command for simulating navigation of a road.
     (sim &key (rv *ccbi-rv*) (time 60))
The :rv ("road view") parameter is the road to be driven. Several are defined in the model:
     *ccbi-rv*: Polynomial approximation of the road driven by subjects in CCBI driving experiments.
     *easy-rv*: A road defined by a single sin curve.
     *medium-rv*: A road defined by the sum of two sin curves of different frequencies.
     *hard-rv*: A road defined by the sum of three sin curves of different frequencies.
The idea of defining roads sinusoidally was taken from Strayer and Johnston (2001). New polynomial or sinusoidal roads can be defined using the provided Lisp functions. The :time parameter is the number of seconds of driving to be simulated.

The model also defines a summ command for pretty-printing the temporal and resource utilization results.

At the bottom of the file, five commands are defined for testing the model?s performance on problems of increasing complexity. These are invoked as:
     (test3)
     (test4)
     (test5)
test3 simulates solution of the standard 3-disk problem, where a stack of 3 disks must be moved from the left peg to the right peg. test4 and test5 simulate solution of the standard 4-disk and 5-disk problems, respectively.

The model defines a sim command for simulating the solution of a given problem and a summ command for pretty-printing the temporal and resource utilization results. These are defined at the bottom of the file and used by the various test commands. It is easy to infer how they work and define commands for simulating the results of other studies.

There exist commands for simulating solution of problems used in behavioral studies of normal adults (Anderson, 1993; Carpenter et al., 1990; Just et al., 1996; Ruiz, 1987), behavioral studies of patients with frontal lesions (Goel et al., 2001; Morris et al., 1997a; Morris et al., 1997b), and fMRI studies of normal adults (Anderson et al., 2005; Fincham et al., 2002). These will be made available soon.

The glue script first defines a new facility for defining a "model." This is necessary for informing the system which model or models of the multiple defined models are to run for the task at. It also defines a new version of the main recognize-act loop for matching productions against declarative memory that is sensitive to the presence of multiple models and that records the activity or dormancy of each. Finally, it defines a generalized sim command for running one or more simulations at the same time and a generalized summ command for pretty-printing the results of one or more simulations.

The sentence comprehension and mental rotation models are defined next, as are commands for simulating the single-task conditions. (jv2005): Simulates comprehension of the sentences described in Just and Varma (2006). (mr1999): Simulates solution of the Shepard-Metzler problems solved by the Carpenter et al. (1999) subjects. These commands demonstrate the utility of the generalized sim and summ commands.

Finally, a command for simulating the Just et al. (2001) study of dual sentence comprehension and mental rotation is defined. (dt2001 &optional (summ-p t)) The :summ-p parameter is optional. It can be either t or nil. When t - its default value - the summ command is called after every simulation to pretty-print the results.

References
Carpenter, P. A., Just, M. A., Keller, T., Eddy, W. F., & Thulborn, K. R. (1999). Graded functional activation in the visuospatial system with the amount of task demand. Journal of Cognitive Neuroscience, 11, 9-24
Just, M. A., Carpenter, P. A., Keller, T. A., Emery, L., Zajac, H., & Thulborn, K. R. (2001). Interdependence of nonoverlapping cortical systems in dual cognitive tasks. NeuroImage, 14, 417-426.
Just, M. A., & Varma, S. (2006). The organization of thinking: What functional brain imaging reveals about the neuroarchitecture of complex cognition. Manuscript submitted for publication.

The glue script first defines a new facility for defining a "model." This is necessary for informing the system which model or models of the multiple defined models are to run for the task at hand. It also defines a new version of the main recognize-act loop for matching productions against declarative memory that is sensitive to the presence of multiple models and that records the activity or dormancy of each. Finally, it defines a generalized sim command for running one or more simulations at the same time and a generalized summ command for pretty-printing the results of one or more simulations.

The sentence comprehension and mental rotation models are defined next, as are commands for simulating the single-task conditions.
     (jv2005): Simulates comprehension of the sentences described in Just and Varma (2006).
     (drv2003 &key (time 15)): Simulates driving :time seconds on the *ccbi-rv* road view that subjects navigate in CCBI driving experiments
These commands that demonstrate the utility of the generalized sim and summ commands.

Finally, a command for simulating dual-task sentence comprehension and driving is defined.
(dt-driving &key (time (* 95 *secs-per-mcyc*))) The :time parameter is the number of seconds of driving to be simulated. It is converted in the parameter list to the temporal scale of 4CAPS, which is measured in cycles.

The Dual Comprehension model differs from the other dual-task models in that it does not consist of two independent models running at the same time, but rather the same model processing two input streams simultaneously - think dual threads, not dual processes. It is defined as follows:
     Start Common Lisp, load 4CAPS, and enter the "CL-USER" package.
     Load the DC model
     Load the script found here

The DC is a slight augmentation of the conventional SCM. It adds the task-goal class of declarative memory element - should the auditory input stream be attended, the visual input stream, or both - It also adds an Executive center to house these goals and Phonological and Orthographic centers to house percepts of the different modalities.

The sim command for simulating comprehension of a sentence has been elaborated into three separate commands:
     (aud-sim sent)
     (vis-sim sent)
     (dual-sim aud-sent vis-sent)
The sent, aud-sent, and vis-sent arguments to these commands are lists of words. These commands are defined at the bottom of the file. The summ command has also been extended to pretty-print the resource utilizations of the three new centers (as well as the four existing centers). It is also defined at the bottom of the file.