Cited by 724

The DOI matches its Crossref record; 12 of the 12 references it cites were found in a registry or an index.

Neurocomputational models of working memory

Durstewitz, Daniel, Seamans, Jeremy K., Sejnowski, Terrence J.·2000·Nature Neuroscience

DOI 10.1038/81460

Open this paper in CoChat — free account

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

Integrity signals

Registry

Crossref · 10.1038/81460

Cites

12 of 12 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Neural networks and physical systems with emergent collective computational abilities.
Hopfield, J. J. (1982) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.79.8.2554 · Cited by 19,270
The Organization of Behavior
Hebb, D. O. (2005) · doi:10.4324/9781410612403 · Cited by 9,825
Mnemonic coding of visual space in the monkey's dorsolateral prefrontal cortex
Funahashi, S., Bruce, C. J., & Goldman-Rakic, P. S. (1989) · Journal of Neurophysiology · doi:10.1152/jn.1989.61.2.331 · Cited by 2,685
Temporal dynamics of brain activation during a working memory task
Cohen, J. D., Perlstein, W. M., Braver, T. S., Nystrom, L. E., Noll, D. C., Jonides, J., & Smith, E. E. (1997) · Nature · doi:10.1038/386604a0 · Cited by 1,876
Models of Information Processing in the Basal Ganglia
(1994) · doi:10.7551/mitpress/4708.001.0001 · Cited by 1,190
Synaptic Mechanisms and Network Dynamics Underlying Spatial Working Memory in a Cortical Network Model
Compte, A. (2000) · Cerebral Cortex · doi:10.1093/cercor/10.9.910 · Cited by 1,143
Physiology and anatomy of synaptic connections between thick tufted pyramidal neurones in the developing rat neocortex.
Markram, H., Lübke, J., Frotscher, M., Roth, A., & Sakmann, B. (1997) · The Journal of Physiology · doi:10.1113/jphysiol.1997.sp022031 · Cited by 960
Neuronal correlates of parametric working memory in the prefrontal cortex
Romo, R., Brody, C. D., Hernández, A., & Lemus, L. (1999) · Nature · doi:10.1038/20939 · Cited by 822
Reward expectancy in primate prefrental neurons
Watanabe, M. (1996) · Nature · doi:10.1038/382629a0 · Cited by 684
Prospective coding for objects in primate prefrontal cortex
Rainer, G., Rao, S. C., & Miller, E. K. (1999) · The Journal of Neuroscience · doi:10.1523/jneurosci.19-13-05493.1999 · Cited by 432 · cited 1×
“2 , PFC neurons in vivo are never silent but fire spontaneously at rates of 1–10 Hz between different trials of a working memory task, outside a task context, or even during the delay phases if they are not tuned to the current stimulus or respons”
Background

Show all 12 references

The Cognitive Neuroscience of Working Memory
D'Esposito, M., & Postle, B. R. (2015) · Annual Review of Psychology · doi:10.1146/annurev-psych-010814-015031 · Cited by 1,653
The principal features and mechanisms of dopamine modulation in the prefrontal cortex
Seamans, J. K., & Yang, C. R. (2004) · Progress in Neurobiology · doi:10.1016/j.pneurobio.2004.05.006 · Cited by 1,592
Self-citation
Neuroscience-Inspired Artificial Intelligence
Hassabis, D., Kumaran, D., Summerfield, C., & Botvinick, M. (2017) · Neuron · doi:10.1016/j.neuron.2017.06.011 · Cited by 1,557
Synaptic reverberation underlying mnemonic persistent activity
Wang, X.-J. (2001) · Trends in Neurosciences · doi:10.1016/s0166-2236(00)01868-3 · Cited by 1,059
The dynamic brain: from spiking neurons to neural masses and cortical fields
Deco, G., Jirsa, V. K., Robinson, P. A., Breakspear, M., & Friston, K. (2008) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1000092 · Cited by 1,084
Turning on and off recurrent balanced cortical activity
Shu, Y., Hasenstaub, A., & McCormick, D. A. (2003) · Nature · doi:10.1038/nature01616 · Cited by 1,054
Interactions between frontal cortex and basal ganglia in working memory: A computational model
FRANK, M. J., LOUGHRY, B., & O'REILLY, R. C. (2001) · Cognitive, Affective, & Behavioral Neuroscience · doi:10.3758/cabn.1.2.137 · Cited by 879
‘Activity-silent’ working memory in prefrontal cortex: a dynamic coding framework
Stokes, M. G. (2015) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2015.05.004 · Cited by 850
Working Memory 2.0
Miller, E. K., Lundqvist, M., & Bastos, A. M. (2018) · Neuron · doi:10.1016/j.neuron.2018.09.023 · Cited by 797
The Catechol-O-Methyltransferase Polymorphism: Relations to the Tonic–Phasic Dopamine Hypothesis and Neuropsychiatric Phenotypes
Bilder, R. M., Volavka, J., Lachman, H. M., & Grace, A. A. (2004) · Neuropsychopharmacology · doi:10.1038/sj.npp.1300542 · Cited by 769
Neural dynamics for landmark orientation and angular path integration
Seelig, J. D., & Jayaraman, V. (2015) · Nature · doi:10.1038/nature14446 · Cited by 718
Attractor dynamics of network UP states in the neocortex
Cossart, R., Aronov, D., & Yuste, R. (2003) · Nature · doi:10.1038/nature01614 · Cited by 659
Slow cortical dynamics and the accumulation of information over long timescales
Honey, C. J., Thesen, T., Donner, T. H., Silbert, L. J., Carlson, C. E., Devinsky, O., Doyle, W. K., Rubin, N., Heeger, D. J., & Hasson, U. (2012) · Neuron · doi:10.1016/j.neuron.2012.08.011 · Cited by 532
The Dual-State Theory of Prefrontal Cortex Dopamine Function with Relevance to Catechol-O-Methyltransferase Genotypes and Schizophrenia
Durstewitz, D., & Seamans, J. K. (2008) · Biological Psychiatry · doi:10.1016/j.biopsych.2008.05.015 · Cited by 586
Self-citation
Dopamine and Cognitive Control in Prefrontal Cortex
Ott, T., & Nieder, A. (2019) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2018.12.006 · Cited by 530
Targeting the dopamine D1 receptor in schizophrenia: insights for cognitive dysfunction
Goldman-Rakic, P., Castner, S., Svensson, T., Siever, L., & Williams, G. (2004) · Psychopharmacology · doi:10.1007/s00213-004-1793-y · Cited by 544
The neuroscience of working memory capacity and training
Constantinidis, C., & Klingberg, T. (2016) · Nature Reviews Neuroscience · doi:10.1038/nrn.2016.43 · Cited by 533
Heterogeneity in the pyramidal network of the medial prefrontal cortex
Wang, Y., Markram, H., Goodman, P. H., Berger, T. K., Ma, J., & Goldman-Rakic, P. S. (2006) · Nature Neuroscience · doi:10.1038/nn1670 · Cited by 503
Robust timing and motor patterns by taming chaos in recurrent neural networks
Laje, R., & Buonomano, D. V. (2013) · Nature Neuroscience · doi:10.1038/nn.3405 · Cited by 454
A connectome of the Drosophila central complex reveals network motifs suitable for flexible navigation and context-dependent action selection
Hulse, B. K., Haberkern, H., Franconville, R., Turner-Evans, D., Takemura, S.-Y., Wolff, T., Noorman, M., Dreher, M., Dan, C., Parekh, R., et al. (2021) · eLife · doi:10.7554/elife.66039 · Cited by 392
Memory without Feedback in a Neural Network
Goldman, M. S. (2009) · Neuron · doi:10.1016/j.neuron.2008.12.012 · Cited by 342
Mechanism for top-down control of working memory capacity
Edin, F., Klingberg, T., Johansson, P., McNab, F., Tegnér, J., & Compte, A. (2009) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0901894106 · Cited by 365
The cortex as a central pattern generator
Yuste, R., MacLean, J. N., Smith, J., & Lansner, A. (2005) · Nature Reviews Neuroscience · doi:10.1038/nrn1686 · Cited by 355
Prefrontal dopamine and behavioral flexibility: shifting from an “inverted-U” toward a family of functions
Floresco, S. B. (2013) · Frontiers in Neuroscience · doi:10.3389/fnins.2013.00062 · Cited by 336
Functional connectivity during working memory maintenance
GAZZALEY, A., RISSMAN, J., & D'ESPOSITO, M. (2004) · Cognitive, Affective, & Behavioral Neuroscience · doi:10.3758/cabn.4.4.580 · Cited by 337
Under the curve: Critical issues for elucidating D1 receptor function in working memory
Williams, G. V., & Castner, S. A. (2006) · Neuroscience · doi:10.1016/j.neuroscience.2005.09.028 · Cited by 326
Control of visual cortical signals by prefrontal dopamine
Noudoost, B., & Moore, T. (2011) · Nature · doi:10.1038/nature09995 · Cited by 324
Mechanisms of Dopamine Activation of Fast-Spiking Interneurons That Exert Inhibition in Rat Prefrontal Cortex
Gorelova, N., Seamans, J. K., & Yang, C. R. (2002) · Journal of Neurophysiology · doi:10.1152/jn.00335.2002 · Cited by 302
Self-citation
Dysfunctional and Compensatory Prefrontal Cortical Systems, Genes and the Pathogenesis of Schizophrenia
Tan, H.-Y., Callicott, J. H., & Weinberger, D. R. (2007) · Cerebral Cortex · doi:10.1093/cercor/bhm069 · Cited by 266
Mechanisms underlying working memory for novel information
Hasselmo, M. E., & Stern, C. E. (2006) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2006.09.005 · Cited by 249
Modulation of Hippocampus-Dependent Learning and Synaptic Plasticity by Nicotine
Kenney, J. W., & Gould, T. J. (2008) · Molecular Neurobiology · doi:10.1007/s12035-008-8037-9 · Cited by 242
Prefrontal Cortical Mechanisms Underlying Individual Differences in Cognitive Flexibility and Stability
Armbruster, D. J. N., Ueltzhöffer, K., Basten, U., & Fiebach, C. J. (2012) · Journal of Cognitive Neuroscience · doi:10.1162/jocn_a_00286 · Cited by 202
A specialized NMDA receptor function in layer 5 recurrent microcircuitry of the adult rat prefrontal cortex
Wang, H., Stradtman, G. G., Wang, X.-J., & Gao, W.-J. (2008) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0804318105 · Cited by 199
Translational perspectives for computational neuroimaging
Stephan, K. E., Iglesias, S., Heinzle, J., & Diaconescu, A. O. (2015) · Neuron · doi:10.1016/j.neuron.2015.07.008 · Cited by 169
A place for time: The spatiotemporal structure of neural dynamics during natural audition
Stephens, G. J., Honey, C. J., & Hasson, U. (2013) · Journal of Neurophysiology · doi:10.1152/jn.00268.2013 · Cited by 141
Post-pubertal Emergence of Prefrontal Cortical Up States Induced by D1-NMDA Co-activation
Tseng, K. Y. (2004) · Cerebral Cortex · doi:10.1093/cercor/bhh107 · Cited by 169
A Dynamical Systems Hypothesis of Schizophrenia
Loh, M., Rolls, E. T., & Deco, G. (2007) · PLoS Computational Biology · doi:10.1371/journal.pcbi.0030228 · Cited by 164
Breathing Rhythm and Pattern and Their Influence on Emotion
Ashhad, S., Kam, K., Del Negro, C. A., & Feldman, J. L. (2022) · Annual Review of Neuroscience · doi:10.1146/annurev-neuro-090121-014424 · Cited by 161
Accessing Real-Life Episodic Information from Minutes versus Hours Earlier Modulates Hippocampal and High-Order Cortical Dynamics
Chen, J., Honey, C. J., Simony, E., Arcaro, M. J., Norman, K. A., & Hasson, U. (2016) · Cerebral Cortex · doi:10.1093/cercor/bhv155 · Cited by 135
Stimulus-specific hypothalamic encoding of a persistent defensive state
Kennedy, A., Kunwar, P. S., Li, L.-Y., Stagkourakis, S., Wagenaar, D. A., & Anderson, D. J. (2020) · Nature · doi:10.1038/s41586-020-2728-4 · Cited by 144
Catechol-O-Methyltransferase Val158Met Modulation of Prefrontal–Parietal–Striatal Brain Systems during Arithmetic and Temporal Transformations in Working Memory
Tan, H.-Y., Chen, Q., Goldberg, T. E., Mattay, V. S., Meyer-Lindenberg, A., Weinberger, D. R., & Callicott, J. H. (2007) · The Journal of Neuroscience · doi:10.1523/jneurosci.4041-07.2007 · Cited by 144
An in vivo assay of synaptic function mediating human cognition
Moran, R. J., Symmonds, M., Stephan, K. E., Friston, K. J., & Dolan, R. J. (2011) · Current Biology · doi:10.1016/j.cub.2011.06.053 · Cited by 137
Untitled work
Qin (2011) · doi:10.1016/j.neuroimage.2011.05.006 · Cited by 124
Slow integration leads to persistent action potential firing in distal axons of coupled interneurons
Sheffield, M. E. J., Best, T. K., Mensh, B. D., Kath, W. L., & Spruston, N. (2011) · Nature Neuroscience · doi:10.1038/nn.2728 · Cited by 125
Successful choice behavior is associated with distinct and coherent network states in anterior cingulate cortex
Lapish, C. C., Durstewitz, D., Chandler, L. J., & Seamans, J. K. (2008) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0804045105 · Cited by 119
Self-citation
From an Executive Network to Executive Control: A Computational Model of the n-back Task
Chatham, C. H., Herd, S. A., Brant, A. M., Hazy, T. E., Miyake, A., O'Reilly, R., & Friedman, N. P. (2011) · Journal of Cognitive Neuroscience · doi:10.1162/jocn_a_00047 · Cited by 115
Timecourse of object‐related neural activity in the primate prefrontal cortex during a short‐term memory task
Rainer, G., & Miller, E. K. (2002) · European Journal of Neuroscience · doi:10.1046/j.1460-9568.2002.01958.x · Cited by 113
MGluR-Mediated Calcium Waves that Invade the Soma Regulate Firing in Layer V Medial Prefrontal Cortical Pyramidal Neurons
Hagenston, A. M., Fitzpatrick, J. S., & Yeckel, M. F. (2008) · Cerebral Cortex · doi:10.1093/cercor/bhm075 · Cited by 109
A Modeling Framework for Deriving the Structural and Functional Architecture of a Short-Term Memory Microcircuit
Fisher, D., Olasagasti, I., Tank, D. W., Aksay, E. R. F., & Goldman, M. S. (2013) · Neuron · doi:10.1016/j.neuron.2013.06.041 · Cited by 75
Connecting neural codes with behavior in the auditory system of Drosophila
Clemens, J., Girardin, C. C., Coen, P., Guan, X.-J., Dickson, B. J., & Murthy, M. (2015) · Neuron · doi:10.1016/j.neuron.2015.08.014 · Cited by 69
Consistent spectral predictors for dynamic causal models of steady-state responses
Moran, R. J., Stephan, K. E., Dolan, R. J., & Friston, K. J. (2011) · NeuroImage · doi:10.1016/j.neuroimage.2011.01.012 · Cited by 75
Adult cortical plasticity depends on an early postnatal critical period
Greenhill, S. D., Juczewski, K., de Haan, A. M., Seaton, G., Fox, K., & Hardingham, N. R. (2015) · Science · doi:10.1126/science.aaa8481 · Cited by 76
Covert rapid action-memory simulation (CRAMS): a hypothesis of hippocampal-prefrontal interactions for adaptive behavior
Wang, J. X., Cohen, N. J., & Voss, J. L. (2015) · Neurobiology of Learning and Memory · doi:10.1016/j.nlm.2014.04.003 · Cited by 75
Modulation of Hippocampus-Prefrontal Cortex Synaptic Transmission and Disruption of Executive Cognitive Functions by MK-801
Blot, K., Kimura, S.-I., Bai, J., Kemp, A., Manahan-Vaughan, D., Giros, B., Tzavara, E., & Otani, S. (2015) · Cerebral Cortex · doi:10.1093/cercor/bht329 · Cited by 58
A connectome of the Drosophila central complex reveals network motifs suitable for flexible navigation and context-dependent action selection
Hulse, B. K., Haberkern, H., Franconville, R., Turner-Evans, D. B., Takemura, S., Wolff, T., Noorman, M., Dreher, M., Dan, C., Parekh, R., et al. (2020) · doi:10.1101/2020.12.08.413955 · Cited by 392
“Such persistent representations have long been believed to be generated, updated and maintained by recurrent attractor networks (Brody et al., 2003; Durstewitz et al., 2000).”
Background
Executive functions and prefrontal cortex: a matter of persistence?
Ball, G., Stokes, P. R., Rhodes, R. A., Bose, S. K., Rezek, I., Wink, A.-M., Lord, L.-D., Mehta, M. A., Grasby, P. M., & Turkheimer, F. E. (2011) · Frontiers in Systems Neuroscience · doi:10.3389/fnsys.2011.00003 · Cited by 50
Glutamate, obsessive–compulsive disorder, schizophrenia, and the stability of cortical attractor neuronal networks
Rolls, E. T. (2012) · Pharmacology Biochemistry and Behavior · doi:10.1016/j.pbb.2011.06.017 · Cited by 39
Chronometric readout from a memory trace: Gamma-frequency field stimulation recruits timed recurrent activity in the rat CA3 network
Fujisawa, S., Matsuki, N., & Ikegaya, Y. (2004) · The Journal of Physiology · doi:10.1113/jphysiol.2004.066639 · Cited by 36
Expectancy, ambiguity, and behavioral flexibility: separable and complementary roles of the orbital frontal cortex and amygdala in processing reward expectancies
Pauli, W. M., Hazy, T. E., & O'Reilly, R. C. (2012) · Journal of Cognitive Neuroscience · doi:10.1162/jocn_a_00155 · Cited by 32
Sensitivity to value-driven attention is predicted by how we learn from value
Jahfari, S., & Theeuwes, J. (2017) · Psychonomic Bulletin & Review · doi:10.3758/s13423-016-1106-6 · Cited by 28
Encoding certainty in bump attractors
Carroll, S., Josić, K., & Kilpatrick, Z. P. (2014) · Journal of Computational Neuroscience · doi:10.1007/s10827-013-0486-0 · Cited by 23
Neural correlates of working memory training: An fMRI meta-analysis
Zhang, Y., Fu, J., & Zhao, X. (2024) · NeuroImage · doi:10.1016/j.neuroimage.2024.120885 · Cited by 20
Sleep deprivation accelerates delay-related loss of visual short-term memories without affecting precision
Wee, N., Asplund, C. L., & Chee, M. W. L. (2013) · Sleep · doi:10.5665/sleep.2710 · Cited by 17
Functional alterations of the prefrontal circuit underlying cognitive aging in mice
Chong, H. R., Ranjbar-Slamloo, Y., Ho, M. Z. H., Ouyang, X., & Kamigaki, T. (2023) · Nature Communications · doi:10.1038/s41467-023-43142-0 · Cited by 19
Frontostriatal contribution to the interplay of flexibility and stability in serial prediction
Trempler, I., Schiffer, A.-M., El-Sourani, N., Ahlheim, C., Fink, G. R., & Schubotz, R. I. (2017) · Journal of Cognitive Neuroscience · doi:10.1162/jocn_a_01040 · Cited by 18
Childhood Executive Functioning Inventory: Adaptação e Propriedades Psicométricas da Versão Brasileira
Trevisan, B. T., Dias, N. M., Berberian, A. D. A., & Seabra, A. G. (2017) · Psico-USF · doi:10.1590/1413-82712017220106 · Cited by 14
Evidence of multistability in a realistic computer simulation of hippocampus subfield CA1
Siekmeier, P. J. (2009) · Behavioural Brain Research · doi:10.1016/j.bbr.2009.01.021 · Cited by 9
Impaired context-sensitive adjustment of behaviour in Parkinson’s disease patients tested on and off medication: an fMRI study
Trempler, I., Bürkner, P.-C., El-Sourani, N., Binder, E., Reker, P., Fink, G. R., & Schubotz, R. I. (2020) · NeuroImage · doi:10.1016/j.neuroimage.2020.116674 · Cited by 6

Authors: Durstewitz, D., Seamans, J. K., & Sejnowski, T. J.
Venue: Nature Neuroscience
Publisher: Springer Science and Business Media LLC
Published: 2000-11
Volume: 3
Issue: S11
Pages: 1184-1191
ISSN: 1097-6256 (ISSN-L)
1546-1726
DOI: 10.1038/81460
OpenAlex: W1604195904
Cited by: 724
References: 12
FWCI: 8.61
Type: journal article
Language: en
Open access: closed

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.

Neurocomputational models of working memory

Overview

Integrity signals

Verification

Claims the paper makes

Self-check

Citations

Cites

Cited by

Metadata

Record

About these checks

Data sources