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Cited by 879Neural and Behavioral Psychology StudiesNeural dynamics and brain functionMemory and Neural Mechanisms

Interactions between frontal cortex and basal ganglia in working memory: A computational model

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FRANK, M. J., LOUGHRY, B., O'REILLY, R. C.·2001·Cognitive, Affective, & Behavioral Neuroscience
DOI 10.3758/cabn.1.2.137
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Abstract

The frontal cortex and the basal ganglia interact via a relatively well understood and elaborate system of interconnections. In the context of motor function, these interconnections can be understood as disinhibiting, or "releasing the brakes," on frontal motor action plans: The basal ganglia detect appropriate contexts for performing motor actions and enable the frontal cortex to execute such actions at the appropriate time. We build on this idea in the domain of working memory through the use of computational neural network models of this circuit. In our model, the frontal cortex exhibits robust active maintenance, whereas the basal ganglia contribute a selective, dynamic gating function that enables frontal memory representations to be rapidly updated in a task-relevant manner. We apply the model to a novel version of the continuous performance task that requires subroutine-like selective working memory updating and compare and contrast our model with other existing models and theories of frontal-cortex-basal-ganglia interactions.

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  • According to prominent neurocomputational models, a blunted phasic dopamine response should hinder gate opening.

    “According to prominent neurocomputational models (Chatham & Badre, 2015; Frank et al., 2001; Hazy et al., 2006; O’Reilly, 2006), a blunted phasic response should hinder gate opening.”

    From Baseline-dependent effect of dopamine’s precursor L-tyrosine on working memory gating but not updating (2020) · cites this paper as Frank et al., 2001

    The Gating section (page unavailable) describes earlier dopamine-based models in which phasic dopamine elevation permits working-memory updating. But the Relationship to the Dopamine-Based Gating Models section says this paper’s own basal-ganglia model assigns dopamine a role in learning rather than requiring phasic bursts to open the gate, particularly after a task is learned. Thus the cited paper supports the prediction for models it discusses, not as a general prediction of its own model. (LLM, conf=0.86)

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  • According to prominent neurocomputational models, the balance between maintenance and flexible updating in working memory is controlled by an input-gating mechanism that dynamically regulates access of input to working memory.

    “According to prominent neurocomputational models (Chatham & Badre, 2015; Frank, Loughry, & O’Reilly, 2001; Hazy et al., 2006; O’Reilly, 2006), the balance between the functionally opposite states of robust maintenance and flexible updating is controlled by an input-gating mechanism, which dynamically regulates the access of input to WM.”

    From Baseline-dependent effect of dopamine’s precursor L-tyrosine on working memory gating but not updating (2020) · cites this paper as Frank et al., 2001

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Research works printed but not linked: 11

  1. Baddeley, A. D. (1986). Working memory. New York: Oxford Univer- sity Press.
  2. Gelfand, J., Gullapalli,V., Johnson, M., Raye, C., & Henderson, J. (1997). The dynamics of prefrontal cortico-thalamo-basal ganglionic loops and short term memory interference phenomena. In Proceed- ings of the 19th Annual Conference of the Cognitive Science Society (pp. 253-258). Mahwah, NJ: Erlbaum.
  3. Gobbel, J. R. (1995). A biophysically-based model of the neostriatum as a dynamically reconfigurable network. In M. Boden & L.-E. Niklasson (Eds.), Proceedings of the Second Swedish Conference on Connectionism. Hillsdale, NJ: Erlbaum.
  4. Gobbel, J. R. (1997). The role of the neostriatum in the execution of ac- tion sequences. Unpublished doctoral dissertation, University of Cal- ifornia, San Diego.
  5. O'Reilly, R. C., & McClelland, J. L. (1994). Hippocampal conjunc- tive encoding, storage, and recall: Avoiding a tradeoff. Hippocam- pus, 4, 661-682.
  6. O'Reilly, R. C., & Munakata, Y. (2000). Computationalexplorations in cognitive neuroscience: Understanding the mind by simulating the brain. Cambridge, MA: MIT Press.
  7. O'Reilly, R. C., & Rudy, J. W. (2000). Computational principles of learning in the neocortex and hippocampus. Hippocampus, 10, 389- 397.
  8. Petrides, M. (1994). Frontal lobes and working memory: Evidence from investigations of the effects of cortical excisions in nonhuman primates. In F. Boller & J. Grafman (Eds.), Handbook of neuropsy- chology (Vol. 9, pp. 59-82). Amsterdam: Elsevier.
  9. Pucak, M. L., Levitt, J. B., Lund, J. S., & Lewis, D. A. (1996). Pat- terns of intrinsic and associational circuitry in monkey prefrontal cor- tex. Journal of Comparative Neurology, 376, 614-630.
  10. Schneider, J. S. (1987). Basal ganglia-motor influences: Role of sen- sory gating. In J. S. Schneider & T. I. Lidsky (Eds.), Basal ganglia and behavior: Sensory aspects of motor functioning (pp. 103-121). Toronto: Hans Huber.
  11. Wilson, C. J. (1993). The generation of natural firing patterns in neos- triatal neurons. In G. W. Arbuthnott & P. C. Emson (Eds.), Chemical signalling in the basal ganglia (Progress in Brain Research, Vol. 99, pp. 277-297). Amsterdam: Elsevier.

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Authors
FRANK, M. J., LOUGHRY, B., & O'REILLY, R. C.
Affiliations
University of Colorado Boulder (US)
ORCID
FRANK, M. J.
Venue
Cognitive, Affective, & Behavioral Neuroscience
Publisher
Springer Science and Business Media LLC
Published
2001-06-01
Volume
1
Issue
2
Pages
137-160
ISSN
  • 1530-7026 (ISSN-L)
  • 1531-135X
DOI
10.3758/cabn.1.2.137
OpenAlex
W2116704462
Cited by
879
References
130
Citations by year
2026: 23 · 2025: 26 · 2024: 45 · 2023: 36 · 2022: 40 · 2021: 35 · 2020: 39 · 2019: 42 · 2018: 48 · 2017: 51 · 2016: 45 · 2015: 43 · 2014: 49 · 2013: 46 · 2012: 30
FWCI
6.47
Type
journal article
Language
en
Open access
Licence
www.springer.com/tdm (tdm)
Locations
  • Cognitive Affective & Behavioral Neuroscience (publishedVersion)
  • PubMed (publishedVersion)
Funders
National Institute of Mental Health (MH-47566, P01MH047566)
Topics
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Neural and Behavioral Psychology Studies
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Memory and Neural Mechanisms
Keywords
frontal cortex, basal ganglia, working memory, computational neural network model, memory maintenance, memory updating, gating, continuous performance test
MeSH terms
Basal Ganglia, Frontal Lobe, Humans, Nerve Net, Mental Recall, Neural Networks, Computer

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