Modeling some effects of frontal lobe damage—Novelty and perseveration

Levine, Daniel S.; Prueitt, Paul S.

doi:10.1016/0893-6080(89)90027-0

Cited by 156 publications

(59 citation statements)

References 24 publications

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“…Some models have addressed specific component processes of frontal executive functions, such as maintaining state information in working memory (Dreher, Guigon, & Burnod, 2002;Rougier & O'Reilly, 2002;Durstewitz, Seamans, & Sejnowski, 2000;Moody, Wise, Pellegrino, & Zipser, 1997) and response sequencing (Dehaene & Changeux 1997;Bapi & Levine, 1994). Several models have accounted for both context maintenance and response selection/response inhibition, e.g., in the Wisconsin Card Sorting task (Berdia & Metz, 1998;Levine & Prueitt, 1989), Stroop interference task (Cohen, Dunbar, & McClelland, 1990), verbal response selection tasks (Gullapalli & Gelfand, 1995), delayed response tasks (Guignon, Dorizzi, B., Burnod, Y., & Schultz, 1995;Dehaene & Changeux, 1989), and continuous performance tasks (Rougier & O'Reilly, 2002;Braver, Barch, & Cohen, 1999;Cohen, Braver, & O'Reilly, 1996). In most of these models, PFC units are given prespecified meanings, e.g., ''sort cards by color'' or ''name the ink color.''…”

Section: Discussionmentioning

confidence: 99%

A Computational Model of Prefrontal Control in Free Recall: Strategic Memory Use in the California Verbal Learning Task

Becker

Lim

2003

Journal of Cognitive Neuroscience

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Abstract& Several decades of research into the function of the frontal lobes in brain-damaged patients, and more recently in intact individuals using function brain imaging, has delineated the complex executive functions of the frontal cortex. And yet, the mechanisms by which the brain achieves these functions remain poorly understood. Here, we present a computational model of the role of the prefrontal cortex (PFC) in controlled memory use that may help to shed light on the mechanisms underlying one aspect of frontal control: the development and deployment of recall strategies. The model accounts for interactions between the PFC and medial temporal lobe in strategic memory use. The PFC self-organizes its own mnemonic codes using internally derived performance measures. These mnemonic codes serve as retrieval cues by biasing retrieval in the medial temporal lobe memory system. We present data from three simulation experiments that demonstrate strategic encoding and retrieval in the free recall of categorized lists of words. Experiment 1 compares the performance of the model with two control networks to evaluate the contribution of various components of the model. Experiment 2 compares the performance of normal and frontally lesioned models to data from several studies using frontally intact and frontally lesioned individuals, as well as normal, healthy individuals under conditions of divided attention. Experiment 3 compares the model's performance on the recall of blocked and unblocked categorized lists of words to data from Stuss et al. (1994) for individuals with control and frontal lobe lesions. Overall, our model captures a number of aspects of human performance on free recall tasks: an increase in total words recalled and in semantic clustering scores across trials, superiority on blocked lists of related items compared to unblocked lists of related items, and similar patterns of performance across trials in the normal and frontally lesioned models, with poorer overall performance of the lesioned models on all measures. The model also has a number of shortcomings, in light of which we suggest extensions to the model that would enable more sophisticated forms of strategic control. &

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Section: Discussionmentioning

confidence: 99%

A Computational Model of Prefrontal Control in Free Recall: Strategic Memory Use in the California Verbal Learning Task

Becker

Lim

2003

Journal of Cognitive Neuroscience

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“…D iamond, 1991). F urthermore, th e context-p roviding role of the dyna mic learning-co ntext signal in O SC A R is highly similar to the role of maintaining representati ons of task -related contextu a l info r mation assigned to pre-fronta l cortex in several co mputation al models of pre-fro ntal fu nction (see, e.g., C ohen & Servan -Schreiber, 1992; C ooper & Sh allice, 1997; D ehaene & C han geux, 1989; Levine & Prueitt, 1989). It is therefore possible that the develop menta l changes in OS CA R 's learning -context signal assu med in the present account to underpin SO R d evelop ment can be related to conco mitant develop ment in fronta l lobe functio n. A similar interpretatio n of O SC A R has been given by M aylor et al (in press) in ap plying the model to chan ges in memory for serial o rder in elderly adults.…”

Section: Relation To Neurobiologymentioning

confidence: 99%

The Development of Memory for Serial Order: A Temporal‐contextual Distinctiveness Model

et al. 1999

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A model of adult hu man memory, O SC AR , is applied to the develop ment of memory for serial order. In the model, develop ment of serial order memory is assumed to result fro m age-related changes in a dyna mic learning-context signal that underpins memory for serial order. Developm ental improve ment in this dyna mic learning-conte xt signal leads to more te mporally distinctive representations in memory, and this leads in turn to a reduction in order errors. It is shown that the model correctly predicts develop mental cha nges in the movement error gradients in children's serially ordered recall, as well as develop mental changes in the nu mber of movement errors obtaine d. The model is also applied to repetition errors across develop ment.Un mode Á le de meÂ moire hu maine adulte, OSC AR, est appliqueÂ a Á l' eÂ tude du deÂ veloppe ment de la meÂ moire de l' ordre seÂ riel. Dans ce mode Á le, le deÂ veloppe ment de la meÂ moire seÂ rielle est le produit de change ment lieÂ s a Á l' aÃ ge au niveau d' un contexte dyna mique d' apprentissage qui soutien t la meÂ moire seÂ rielle. Des ameÂ lioration s lors du deÂ veloppe ment, dans ce contexte dyna mique d' apprentissage, me Á nent a Á des repreÂ sentatio ns en meÂ moire qui sont plus distinctes au plan te mporel, entra õ Ã nant un dim inution des erreurs d' ordre. Lors d' un rappel seÂ riel, le mode Á le preÂ dit adeÂ quatem ent les chang ements lieÂ s au deÂ veloppe ment dans les gradients d' erreurs ainsi que dans le no mbre d' erreurs observeÂ chez les enfants. Le mode Á le est aussi appliqu eÂ aux erreurs de reÂ peÂ tition observeÂ es en fonction de l' aÃ ge.T he aim of this paper is to develop and test a comp utationally explicit accoun t of th e develop ment of short-te r m me mory fo r serial order, as no such account is availab le at present. A ccording to the mo del, the develop ment of serial order me mory results in part fro m imp rovements in a dynamic intern al learning-co ntext signa l that is involved in representing info r mation about serial order. T his implements the idea that the serial o rder of ite ms can be represented in ter ms of their locatio n along a te mporal dimension, a nd that you nger children h ave less temporally distin ctive representati ons avai lable to the m. Existing ModelsRecent models of children's memo ry for serial order have largely been d evelop ed to accoun t for d ata collected using speci® c experimental p arad igms. H ere we focus on data fro m th e most w idely used paradigm: serially ordered recall (SO R).T he con cept of subvoc al rehearsal has been accorded a central role in recent acco unts of SO R develop ment.Initial accounts e mphasized the role of develop mentally increasing use of subvocal rehearsal in maintaining information in short-te r m me mo ry. C onsistent w ith the importan ce of rehearsal in SO R develop ment, memory span for verbal materials is linearly related to th e rate at which the to-be-re membered items can be rehearsed (B add eley,

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“…Much of this work has been focused on deficits in word reading-the acquired dyslexias (Mozer & Behrmann, 1990;Patterson, Seidenberg, & McClelland, 1990;Plaut & Shallice, 1993a)-but there has also been considerable work in other domains, including spelling (Shallice, Glasspool, & Houghton, 1995;Olson & Caramazza, 1994), speech production (Harley & MacAndrew, 1992;Martin, Dell, & Schwartz, 1994), face recognition (Burton, Young, Bruce, Johnston, & Ellis, 1991;Farah, O'Reilly, & Vecera, 1993), visual object naming (Gordon, 1982;Plaut & Shallice, 1993b), spatial attention (Cohen, Romero, Servan-Schreiber, & Farah, 1994;Humphreys, Freeman, & Müller, 1992), learning and memory McClelland, McNaughton, & O'Reilly, 1995), semantic memory (Farah & McClelland, 1991;Horn, Ruppin, Usher, & Hermann, 1993), and control of action and responding (Bapi & Levine, 1990;Cohen & Servan-Schreiber, 1992;Levine & Prueitt, 1989). Although still in its infancy, the relative success of this work suggests that connectionist modeling may provide an appropriate formalism within which to explore how disorders of brain function give rise to disorders of cognition.…”

Section: Introductionmentioning

confidence: 99%

Relearning after Damage in Connectionist Networks: Toward a Theory of Rehabilitation

1996

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Connectionist modeling offers a useful computational framework for exploring the nature of normal and impaired cognitive processes. The current work extends the relevance of connectionist modeling in neuropsychology to address issues in cognitive rehabilitation: the degree and speed of recovery through retraining, the extent to which improvement on treated items generalizes to untreated items, and how treated items are selected to maximize this generalization. A network previously used to model impairments in mapping orthography to semantics is retrained after damage. The degree of relearning and generalization varies considerably for different lesion locations, and has interesting implications for understanding the nature and variability of recovery in patients. In a second simulation, retraining on words whose semantics are atypical of their category yields more generalization than retraining on more typical words, suggesting a counterintuitive strategy for selecting items in patient therapy to maximize recovery. In a final simulation, changes in the pattern of errors produced by the network over the course of recovery is used to constrain explanations of the nature of recovery of analogous braindamaged patients. Taken together, the findings demonstrate that the nature of relearning in damaged connectionist networks can make important contributions to a theory of rehabilitation in patients.

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Modeling some effects of frontal lobe damage—Novelty and perseveration

Cited by 156 publications

References 24 publications

A Computational Model of Prefrontal Control in Free Recall: Strategic Memory Use in the California Verbal Learning Task

A Computational Model of Prefrontal Control in Free Recall: Strategic Memory Use in the California Verbal Learning Task

The Development of Memory for Serial Order: A Temporal‐contextual Distinctiveness Model

Relearning after Damage in Connectionist Networks: Toward a Theory of Rehabilitation

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