Stability of the memory of eye position in a recurrent network of conductance-based model neurons
Open accessAbstract
Studies of the neural correlates of short-term memory in a wide variety of brain areas have found that transient inputs can cause persistent changes in rates of action potential firing, through a mechanism that remains unknown. In a premotor area that is responsible for holding the eyes still during fixation, persistent neural firing encodes the angular position of the eyes in a characteristic manner: below a threshold position the neuron is silent, and above it the firing rate is linearly related to position. Both the threshold and linear slope vary from neuron to neuron. We have reproduced this behavior in a biophysically plausible network model. Persistence depends on precise tuning of the strength of synaptic feedback, and a relatively long synaptic time constant improves the robustness to mistuning.
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
Cites
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.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Miller et al. showed that fine-tuning of connectivity in the somatosensory discrimination model yields a line attractor capable of parametric working memory.
“Miller et al. (Miller et al., 2003) showed that fine-tuning of connectivity in this model yields a line attractor capable of parametric working memory, similar to the one in the gaze-control system (Seung et al., 2000).”
From Decision Making in Recurrent Neuronal Circuits (2008) · cites this paper as Seung et al., 2000
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
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 · see citing works
Craggs, J. W. (1973) · The Mathematical Gazette · doi:10.2307/3615195 · Cited by 4,167 · see citing works
Excitatory and Inhibitory Interactions in Localized Populations of Model Neurons
Wilson, H. R., & Cowan, J. D. (1972) · Biophysical Journal · doi:10.1016/s0006-3495(72)86068-5 · Cited by 3,579 · see citing works
Computing with Neural Circuits: A Model
Hopfield, J. J., & Tank, D. W. (1986) · Science · doi:10.1126/science.3755256 · Cited by 2,107 · see citing works
Self-citationNonlinear neural networks: Principles, mechanisms, and architectures
Grossberg, S. (1988) · Neural Networks · doi:10.1016/0893-6080(88)90021-4 · Cited by 1,623 · see citing works
Averaging Methods in Nonlinear Dynamical Systems
Sanders, J. A., Verhulst, F., & Murdock, J. A. (2007) · Applied Mathematical Sciences · doi:10.1007/978-0-387-48918-6 · Cited by 1,461 · see citing works
Averaging Methods in Nonlinear Dynamical Systems
Sanders, J. A., & Verhulst, F. (1985) · Applied mathematical sciences · doi:10.1007/978-1-4757-4575-7 · Cited by 1,376 · see citing works
Theory of orientation tuning in visual cortex.
Ben-Yishai, R., Bar‐Or, R. L., & Sompolinsky, H. (1995) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.92.9.3844 · Cited by 1,091 · see citing works
Zhang, K. (1996) · The Journal of Neuroscience · doi:10.1523/jneurosci.16-06-02112.1996 · Cited by 1,001 · see citing works
The mechanics of human saccadic eye movement
Robinson, D. A. (1964) · The Journal of Physiology · doi:10.1113/jphysiol.1964.sp007485 · Cited by 893 · see citing works
FOSTER, J. M. (1996) · The Journal of Nervous and Mental Disease · doi:10.1097/00005053-199606000-00014 · Cited by 755 · see citing works
Loss of the neural integrator of the oculomotor system from brain stem lesions in monkey
Cannon, S. C., & Robinson, D. A. (1987) · Journal of Neurophysiology · doi:10.1152/jn.1987.57.5.1383 · Cited by 728 · see citing works
Neural networks as spatio-temporal pattern-forming systems
Ermentrout, B. (1998) · Reports on Progress in Physics · doi:10.1088/0034-4885/61/4/002 · Cited by 672 · see citing works
Alternating and Synchronous Rhythms in Reciprocally Inhibitory Model Neurons
Wang, X., & Rinzel, J. (1992) · Neural Computation · doi:10.1162/neco.1992.4.1.84 · Cited by 607 · see citing works
How the brain keeps the eyes still
Seung, H. S. (1996) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.93.23.13339 · Cited by 534 · see citing works
Self-citationFuster, J. M. (1999) · Cited by 456 · see citing works
Anatomical connections of the nucleus prepositus of the cat
McCREA, R. A., & Baker, R. (1985) · The Journal of Comparative Neurology · doi:10.1002/cne.902370308 · Cited by 432 · see citing works
A bilateral model for central neural pathways in vestibuloocular reflex
Galiana, H. L., & Outerbridge, J. S. (1984) · Journal of Neurophysiology · doi:10.1152/jn.1984.51.2.210 · Cited by 366 · see citing works
Neuronal activity in prepositus nucleus correlated with eye movement in the alert cat
López‐Barneo, J., Darlot, C., Berthoz, A., & Baker, R. (1982) · Journal of Neurophysiology · doi:10.1152/jn.1982.47.2.329 · Cited by 357 · see citing works
Camperi, M., & Wang, X. (1998) · Journal of Computational Neuroscience · doi:10.1023/a:1008837311948 · Cited by 323 · see citing works
Robinson, D. A. (1989) · Annual Review of Neuroscience · doi:10.1146/annurev.ne.12.030189.000341 · Cited by 323 · see citing works
McFarland, J. L., & Fuchs, A. F. (1992) · Journal of Neurophysiology · doi:10.1152/jn.1992.68.1.319 · Cited by 323 · see citing works
Medial vestibular nucleus in the guinea-pig
Serafin, M., de Waele, C., Khateb, A., Vidal, P. P., & Mühlethaler, M. (1991) · Experimental Brain Research · doi:10.1007/bf00231464 · Cited by 287 · see citing works
Calcium Coding and Adaptive Temporal Computation in Cortical Pyramidal Neurons
Wang, X. (1998) · Journal of Neurophysiology · doi:10.1152/jn.1998.79.3.1549 · Cited by 285 · see citing works
Medial vestibular nucleus in the guinea-pig
Serafin, M., de Waele, C., Khateb, A., Vidal, P. P., & Mühlethaler, M. (1991) · Experimental Brain Research · doi:10.1007/bf00231465 · Cited by 279 · see citing works
Scudder, C. A., & Fuchs, A. F. (1992) · Journal of Neurophysiology · doi:10.1152/jn.1992.68.1.244 · Cited by 266 · see citing works
Linearization of F-I Curves by Adaptation
Ermentrout, B. (1998) · Neural Computation · doi:10.1162/089976698300017106 · Cited by 234 · see citing works
Escudero, M., de la Cruz, R. R., & Delgado-Garcia, J. M. (1992) · The Journal of Physiology · doi:10.1113/jphysiol.1992.sp019433 · Cited by 196 · see citing works
Escudero, M., & Delgado-Garc�a, J. M. (1988) · Experimental Brain Research · doi:10.1007/bf00247538 · Cited by 193 · see citing works
A proposed neural network for the integrator of the oculomotor system
Cannon, S., Robinson, D. A., & Shamma, S. (1983) · Biological cybernetics · doi:10.1007/bf00320393 · Cited by 173 · see citing works
Reduction of Conductance-Based Models with Slow Synapses to Neural Nets
Ermentrout, B. (1994) · Neural Computation · doi:10.1162/neco.1994.6.4.679 · Cited by 172 · see citing works
Spencer, R., Wenthold, R. J., & Baker, R. G. V. (1989) · Journal of Neuroscience · doi:10.1523/jneurosci.09-08-02718.1989 · Cited by 152 · see citing works
van Hemmen, J. L., & Kühn, R. (1986) · Physical Review Letters · doi:10.1103/physrevlett.57.913 · Cited by 150 · see citing works
Anatomical connections of the prepositus and abducens nuclei in the squirrel monkey
Belknap, D. B., & McCREA, R. A. (1988) · The Journal of Comparative Neurology · doi:10.1002/cne.902680103 · Cited by 148 · see citing works
Chéron, G., & Godaux, E. (1987) · The Journal of Physiology · doi:10.1113/jphysiol.1987.sp016870 · Cited by 140 · see citing works
Cannon, S. C., & Robinson, D. A. (1985) · Biological Cybernetics · doi:10.1007/bf00337026 · Cited by 139 · see citing works
Accuracy of saccadic eye movements and maintenance of eccentric eye positions in the dark
Becker, W., & Klein, H.-M. (1973) · Vision Research · doi:10.1016/0042-6989(73)90141-7 · Cited by 136 · see citing works
Lesions in the cat prepositus complex: effects on the vestibulo‐ocular reflex and saccades.
Chéron, G., Godaux, E., Laune, J.-M., & Vanderkelen, B. (1986) · The Journal of Physiology · doi:10.1113/jphysiol.1986.sp015998 · Cited by 135 · see citing works
The oculomotor integrator: testing of a neural network model
Arnold, D. B., & Robinson, D. A. (1997) · Experimental Brain Research · doi:10.1007/bf02454142 · Cited by 133 · see citing works
A learning network model of the neural integrator of the oculomotor system
Arnold, D. B., & Robinson, D. A. (1991) · Biological Cybernetics · doi:10.1007/bf00202608 · Cited by 124 · see citing works
The Autapse: A Simple Illustration of Short-Term Analog Memory Storage by Tuned Synaptic Feedback
Seung, H. S., Lee, D. D., Reis, B. Y., & Tank, D. W. (2000) · Journal of Computational Neuroscience · doi:10.1023/a:1008971908649 · Cited by 112 · see citing works
Self-citationKaneko, C. R. S. (1997) · Journal of Neurophysiology · doi:10.1152/jn.1997.78.4.1753 · Cited by 102 · see citing works
Eye position and eye velocity integrators reside in separate brainstem nuclei.
Pastor, Á. M., de la Cruz, R. R., & Baker, R. G. V. (1994) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.91.2.807 · Cited by 100 · see citing works
Mettens, P., Godaux, E., Chéron, G., & Galiana, H. L. (1994) · Journal of Neurophysiology · doi:10.1152/jn.1994.72.2.785 · Cited by 94 · see citing works
Straube, A., Kurzan, R., & B�ttner, U. (1991) · Experimental Brain Research · doi:10.1007/bf00228958 · Cited by 86 · see citing works
Yokota, J.-I., Reisine, H., & Cohen, B. (1992) · Experimental Brain Research · doi:10.1007/bf00230389 · Cited by 77 · see citing works
The neural integrators of the mammalian saccadic system
Moschovakis, A. K. (1997) · Frontiers in bioscience · doi:10.2741/a212 · Cited by 73 · see citing works
Lesions in the cat prepositus complex: effects on the optokinetic system.
Chéron, G., Gillis, P., & Godaux, E. (1986) · The Journal of Physiology · doi:10.1113/jphysiol.1986.sp015999 · Cited by 72 · see citing works
Membrane and firing properties of avian medial vestibular nucleus neuronsin vitro
Lac, S. D., & Lisberger, S. G. (1995) · Journal of Comparative Physiology A · doi:10.1007/bf01021584 · Cited by 64 · see citing works
Kaneko, C. R. S. (1999) · Journal of Neurophysiology · doi:10.1152/jn.1999.81.2.668 · Cited by 58 · see citing works
Spike-based Learning Rules and Stabilization of Persistent Neural Activity
Xie, X. S., & Seung, H. S. (1999) · Cited by 56 · see citing works
Self-citationShort-term vestibulo-ocular reflex adaptation in humans
Tiliket, C., Shelhamer, M., Roberts, D., & Zee, D. S. (1994) · Experimental Brain Research · doi:10.1007/bf00227201 · Cited by 50 · see citing works
Yokota, M., Peterson, J. W., Kaoutzanis, M. C., & Kowall, N. W. (1992) · Brain Research · doi:10.1016/0006-8993(92)91436-i · Cited by 47 · see citing works
Bower, J. M. (1997) · Springer eBooks · doi:10.1007/978-1-4757-9800-5 · Cited by 46 · see citing works
A neurological integrator for the oculomotor control system
Kamath, B. Y., & Keller, E. L. (1976) · Mathematical Biosciences · doi:10.1016/0025-5564(76)90073-0 · Cited by 44 · see citing works
A neural network model of the vestibulo-ocular reflex using a local synaptic learning rule
Arnold, D. B., & Robinson, D. A. (1992) · Philosophical Transactions of the Royal Society B Biological Sciences · doi:10.1098/rstb.1992.0110 · Cited by 43 · see citing works
Godaux, E., Mettens, P., & Chéron, G. (1993) · The Journal of Physiology · doi:10.1113/jphysiol.1993.sp019956 · Cited by 38 · see citing works
A Theoretical Neural Integrator
Rosen, M. (1972) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.1972.324139 · Cited by 33 · see citing works
Membrane and firing properties of avian medial vestibular nucleus neurons in vitro
Lac, S. D., & Lisberger, S. G. (1995) · Journal of Comparative Physiology A · doi:10.1007/bf00192493 · Cited by 30 · see citing works
NMDA receptors are involved in temporal integration in the oculomotor system of the cat
Mettens, P., Cheron, G. A., & Godaux, E. (1994) · Neuroreport · doi:10.1097/00001756-199406000-00010 · Cited by 25 · see citing works
Anastasio, T. J., & Robinson, D. A. (1991) · Neuroscience Letters · doi:10.1016/0304-3940(91)90900-e · Cited by 23 · see citing works
Activity Patterns of a Slow Synapse Network Predicted by Explicitly Averaging Spike Dynamics
Rinzel, J., & Frankel, P. H. (1992) · Neural Computation · doi:10.1162/neco.1992.4.4.534 · Cited by 19 · see citing works
Normal eye drift and saccadic drift correction in darkness
Hess, K., Reisine, H., & Dürsteler, M. (1985) · Neuro-Ophthalmology · doi:10.3109/01658108509004937 · Cited by 18 · see citing works
Nonlinear Network Models of the Oculomotor Integrator
Lee, D. D., Reis, B. Y., Seung, H. S., & Tank, D. W. (1997) · Springer eBooks · doi:10.1007/978-1-4757-9800-5_60 · Cited by 16 · see citing works
Self-citationEye movements evoked by microstimulations in the brainstem of the alert cat
Godaux, E., Cheron, G. A., & Gravis, F. (1989) · Experimental Brain Research · doi:10.1007/bf00250571 · Cited by 8 · see citing works
NMDA receptors are involved in temporal integration in the oculomotor system of the cat
Mettens, P., Cheron, G. A., & Godaux, E. (1994) · Neuroreport · doi:10.1097/00001756-199406270-00009 · Cited by 6 · see citing works
Flagged first, then by citations
Research works printed but not linked: 1
- tuned synaptic feedback. J. Comput. Neurosci., in press.
Cited by
Sorted by citations
Bogacz, R., Brown, E., Moehlis, J., Holmes, P. J., & Cohen, J. D. (2006) · Psychological Review · doi:10.1037/0033-295x.113.4.700 · Cited by 1,845 · see citing works
Neural Basis of a Perceptual Decision in the Parietal Cortex (Area LIP) of the Rhesus Monkey
Shadlen, M. N., & Newsome, W. T. (2001) · Journal of Neurophysiology · doi:10.1152/jn.2001.86.4.1916 · Cited by 1,755 · see citing works
Roitman, J. D., & Shadlen, M. N. (2002) · The Journal of Neuroscience · doi:10.1523/jneurosci.22-21-09475.2002 · Cited by 1,589 · see citing works
Probabilistic decision making by slow reverberation in cortical circuits
Wang, X.-J. (2002) · Neuron · doi:10.1016/s0896-6273(02)01092-9 · Cited by 1,242 · see citing works
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 · see citing works
Accurate Path Integration in Continuous Attractor Network Models of Grid Cells
Burak, Y., & Fiete, I. R. (2009) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1000291 · Cited by 779 · see citing works
Graded persistent activity in entorhinal cortex neurons
Egorov, A. V., Hamam, B. N., Fransén, E., Hasselmo, M. E., & Alonso, A. A. (2002) · Nature · doi:10.1038/nature01171 · Cited by 769 · see citing works
From the neuron doctrine to neural networks
Yuste, R. (2015) · Nature reviews. Neuroscience · doi:10.1038/nrn3962 · Cited by 748 · see citing works
Neurocomputational models of working memory
Durstewitz, D., Seamans, J. K., & B, T. J. S. A. (2000) · Nature Neuroscience · doi:10.1038/81460 · Cited by 710 · see citing works
A framework for studying emotions across species
Anderson, D. J., & Adolphs, R. (2014) · Cell · doi:10.1016/j.cell.2014.03.003 · Cited by 691 · see citing works
Decision Making in Recurrent Neuronal Circuits
Wang, X.-J. (2008) · Neuron · doi:10.1016/j.neuron.2008.09.034 · Cited by 679 · see citing works
“Miller et al. (Miller et al., 2003) showed that fine-tuning of connectivity in this model yields a line attractor capable of parametric working memory, similar to the one in the gazecontrol system (Seung et al., 2000).”
ResultAttractor dynamics of network UP states in the neocortex
Cossart, R., Aronov, D., & Yuste, R. (2003) · Nature · doi:10.1038/nature01614 · Cited by 659 · see citing works
A role for neural integrators in perceptual decision making
Mazurek, M. E., Roitman, J. D., Ditterich, J., & Shadlen, M. N. (2003) · Cerebral Cortex · doi:10.1093/cercor/bhg097 · Cited by 620 · see citing works
Huk, A. C., & Shadlen, M. N. (2005) · The Journal of Neuroscience · doi:10.1523/jneurosci.4684-04.2005 · Cited by 538 · see citing works
Flexible control of mutual inhibition: a neural model of two-interval discrimination
Machens, C. K., Romo, R., & Brody, C. D. (2005) · Science · doi:10.1126/science.1104171 · Cited by 535 · see citing works
Vogels, T. P., Rajan, K., & Abbott, L. F. (2005) · Annual Review of Neuroscience · doi:10.1146/annurev.neuro.28.061604.135637 · Cited by 497 · see citing works
Spatiotemporal dynamics of continuum neural fields
Bressloff, P. C. (2011) · Journal of Physics A Mathematical and Theoretical · doi:10.1088/1751-8113/45/3/033001 · Cited by 412 · see citing works
Lee, H. B., Simpson, G. V., Logothetis, N. K., & Rainer, G. (2005) · Neuron · doi:10.1016/j.neuron.2004.12.025 · Cited by 388 · see citing works
An Anatomically Constrained Model for Path Integration in the Bee Brain
Stone, T., Webb, B., Adden, A., Weddig, N. B., Honkanen, A., Templin, R., Wcislo, W., Scimeca, L., Warrant, E., & Heinze, S. (2017) · Current Biology · doi:10.1016/j.cub.2017.08.052 · Cited by 377 · see citing works
Kilman, V., van Rossum, M. C. W., & Turrigiano, G. G. (2002) · The Journal of Neuroscience · doi:10.1523/jneurosci.22-04-01328.2002 · Cited by 362 · see citing works
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 · see citing works
Timing and Neural Encoding of Somatosensory Parametric Working Memory in Macaque Prefrontal Cortex
Brody, C. D. (2003) · Cerebral Cortex · doi:10.1093/cercor/bhg100 · Cited by 350 · see citing works
Model for a robust neural integrator
Koulakov, A. A., Raghavachari, S., Kepecs, Á., & Lisman, J. E. (2002) · Nature Neuroscience · doi:10.1038/nn893 · Cited by 308 · see citing works
Brody, C. D., Romo, R., & Kepecs, A. (2003) · Current Opinion in Neurobiology · doi:10.1016/s0959-4388(03)00050-3 · Cited by 284 · see citing works
Mechanism of Graded Persistent Cellular Activity of Entorhinal Cortex Layer V Neurons
Fransén, E., Tahvildari, B., Egorov, A. V., Hasselmo, M. E., & Alonso, A. A. (2006) · Neuron · doi:10.1016/j.neuron.2006.01.036 · Cited by 279 · see citing works
Presynaptic regulation of recurrent excitation by D1 receptors in prefrontal circuits
Gao, W.-J., Krimer, L. S., & Goldman-Rakic, P. S. (2001) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.98.1.295 · Cited by 257 · see citing works
Renart, A., Song, P., & Wang, X. (2003) · Neuron · doi:10.1016/s0896-6273(03)00255-1 · Cited by 243 · see citing works
Seeing at a glance, smelling in a whiff: rapid forms of perceptual decision making
Uchida, N., Kepecs, Á., & Mainen, Z. F. (2006) · Nature reviews. Neuroscience · doi:10.1038/nrn1933 · Cited by 231 · see citing works
How to think about mental content
Egan, F. (2013) · Philosophical Studies · doi:10.1007/s11098-013-0172-0 · Cited by 227 · see citing works
A Neural Circuit Basis for Spatial Working Memory
Constantinidis, C., & Wang, X. (2004) · The Neuroscientist · doi:10.1177/1073858404268742 · Cited by 212 · see citing works
Building functional networks of spiking model neurons
Abbott, L. F., DePasquale, B., & Memmesheimer, R.-M. (2016) · Nature Neuroscience · doi:10.1038/nn.4241 · Cited by 199 · see citing works
A Flexible Model of Working Memory
Bouchacourt, F., & Buschman, T. J. (2019) · Neuron · doi:10.1016/j.neuron.2019.04.020 · Cited by 196 · see citing works
Memory search and the neural representation of context
Polyn, S. M., & Kahana, M. J. (2008) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2007.10.010 · Cited by 202 · see citing works
In vivo intracellular recording and perturbation of persistent activity in a neural integrator
Aksay, E., Gamkrelidze, G., Seung, H. S., Baker, R., & Tank, D. W. (2001) · Nature Neuroscience · doi:10.1038/84023 · Cited by 201 · see citing works
Self-citationSelf-Organizing Neural Integrator Predicts Interval Times through Climbing Activity
Durstewitz, D. (2003) · Journal of Neuroscience · doi:10.1523/jneurosci.23-12-05342.2003 · Cited by 194 · see citing works
Neural underpinnings of the evidence accumulator
Brody, C. D., & Hanks, T. D. (2016) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2016.01.003 · Cited by 184 · see citing works
Itskov, V., Curto, C., Pastalkova, E., & Buzsáki, G. (2011) · Journal of Neuroscience · doi:10.1523/jneurosci.3773-10.2011 · Cited by 173 · see citing works
Goldman, M. S. (2003) · Cerebral Cortex · doi:10.1093/cercor/bhg095 · Cited by 169 · see citing works
A Unified Approach to Building and Controlling Spiking Attractor Networks
Eliasmith, C. (2005) · Neural Computation · doi:10.1162/0899766053630332 · Cited by 167 · see citing works
Persistent Neural Activity in Head Direction Cells
Taube, J. S. (2003) · Cerebral Cortex · doi:10.1093/cercor/bhg102 · Cited by 164 · see citing works
Theoretical Neuroscience Rising
Abbott, L. F. (2008) · Neuron · doi:10.1016/j.neuron.2008.10.019 · Cited by 163 · see citing works
Song, P., & Wang, X. (2005) · Journal of Neuroscience · doi:10.1523/jneurosci.4172-04.2005 · Cited by 161 · see citing works
Thalamic control of cortical dynamics in a model of flexible motor sequencing
Logiaco, L., Abbott, L. F., & Escola, G. S. (2021) · Cell Reports · doi:10.1016/j.celrep.2021.109090 · Cited by 173 · see citing works
Spike timing dependent synaptic plasticity in biological systems
Roberts, P. D., & Bell, C. C. (2002) · Biological Cybernetics · doi:10.1007/s00422-002-0361-y · Cited by 156 · see citing works
Temporal integration by calcium dynamics in a model neuron
Loewenstein, Y., & Sompolinsky, H. (2003) · Nature Neuroscience · doi:10.1038/nn1109 · Cited by 148 · see citing works
NMDA receptor-mediated dendritic spikes and coincident signal amplification
Schiller, J., & Schiller, Y. (2001) · Current Opinion in Neurobiology · doi:10.1016/s0959-4388(00)00217-8 · Cited by 145 · see citing works
A recurrent network model of somatosensory parametric working memory in the prefrontal cortex
Miller, P. (2003) · Cerebral Cortex · doi:10.1093/cercor/bhg101 · Cited by 144 · see citing works
Synaptic mechanisms of persistent reverberatory activity in neuronal networks
Lau, P.-M., & Bi, G. (2005) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0500717102 · Cited by 144 · see citing works
Fundamental limits on persistent activity in networks of noisy neurons
Burak, Y., & Fiete, I. (2012) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1117386109 · Cited by 135 · see citing works
Spatial gradients and multidimensional dynamics in a neural integrator circuit
Miri, A., Daie, K., Arrenberg, A. B., Baier, H., Aksay, E., & Tank, D. W. (2011) · Nature Neuroscience · doi:10.1038/nn.2888 · Cited by 138 · see citing works
Self-citationShort-Term Plasticity Explains Irregular Persistent Activity in Working Memory Tasks
Hansel, D., & Mato, G. (2013) · Journal of Neuroscience · doi:10.1523/jneurosci.3455-12.2013 · Cited by 135 · see citing works
Functional dissection of circuitry in a neural integrator
Aksay, E., Olasagasti, I., Mensh, B. D., Baker, R., Goldman, M. S., & Tank, D. W. (2007) · Nature Neuroscience · doi:10.1038/nn1877 · Cited by 134 · see citing works
Self-citationOPTICAL IMAGING AND CONTROL OF GENETICALLY DESIGNATED NEURONS IN FUNCTIONING CIRCUITS
Miesenböck, G., & Kevrekidis, I. G. (2005) · Annual Review of Neuroscience · doi:10.1146/annurev.neuro.28.051804.101610 · Cited by 131 · see citing works
Dopamine modulates an mGluR5-mediated depolarization underlying prefrontal persistent activity
Sidiropoulou, K., Lu, F.-M., Fowler, M. A., Xiao, R., Phillips, C. W., Ozkan, E. D., Zhu, M. X., White, F. J., & Cooper, D. (2009) · Nature Neuroscience · doi:10.1038/nn.2245 · Cited by 129 · see citing works
A Controlled Attractor Network Model of Path Integration in the Rat
Conklin, J., & Eliasmith, C. (2005) · Journal of Computational Neuroscience · doi:10.1007/s10827-005-6558-z · Cited by 127 · see citing works
Existence and Stability of Persistent States in Large Neuronal Networks
Hansel, D., & Mato, G. (2001) · Physical Review Letters · doi:10.1103/physrevlett.86.4175 · Cited by 126 · see citing works
Reconstructing computational system dynamics from neural data with recurrent neural networks
Durstewitz, D., Koppe, G., & Thurm, M. I. (2023) · Nature reviews. Neuroscience · doi:10.1038/s41583-023-00740-7 · Cited by 133 · see citing works
Dynamics and Computation of Continuous Attractors
Wu, S., Hamaguchi, K., & Amari, S.-I. (2008) · Neural Computation · doi:10.1162/neco.2008.10-06-378 · Cited by 121 · see citing works
Aksay, E., Baker, R., Seung, H. S., & Tank, D. W. (2000) · Journal of Neurophysiology · doi:10.1152/jn.2000.84.2.1035 · Cited by 119 · see citing works
Self-citationPersistent Responses to Brief Stimuli: Feedback Excitation among Brainstem Neurons
Li, W., Soffe, S. R., Wolf, E., & Roberts, A. (2006) · Journal of Neuroscience · doi:10.1523/jneurosci.4727-05.2006 · Cited by 118 · see citing works
Stochastic Transitions between Neural States in Taste Processing and Decision-Making
Miller, P. C., & Katz, D. B. (2010) · Journal of Neuroscience · doi:10.1523/jneurosci.3047-09.2010 · Cited by 116 · see citing works
The Autapse: A Simple Illustration of Short-Term Analog Memory Storage by Tuned Synaptic Feedback
Seung, H. S., Lee, D. D., Reis, B. Y., & Tank, D. W. (2000) · Journal of Computational Neuroscience · doi:10.1023/a:1008971908649 · Cited by 112 · see citing works
Self-citationDynamics of networks of randomly connected excitatory and inhibitory spiking neurons
Brunel, N. (2000) · Journal of Physiology-Paris · doi:10.1016/s0928-4257(00)01084-6 · Cited by 108 · see citing works
Short-Term Facilitation may Stabilize Parametric Working Memory Trace
Itskov, V., Hansel, D., & Tsodyks, M. V. (2011) · Frontiers in Computational Neuroscience · doi:10.3389/fncom.2011.00040 · Cited by 108 · see citing works
Self-Tuned Critical Anti-Hebbian Networks
Magnasco, M. O., Piro, O., & Cecchi, G. (2009) · Physical Review Letters · doi:10.1103/physrevlett.102.258102 · Cited by 107 · see citing works
Spike-Based Population Coding and Working Memory
Martin, B., & Denève, S. (2011) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1001080 · Cited by 103 · see citing works
Structural Representations and the Brain
Shagrir, O. (2012) · The British Journal for the Philosophy of Science · doi:10.1093/bjps/axr038 · Cited by 107 · see citing works
Representing information in cell assemblies: persistent activity mediated by semilunar granule cells
Larimer, P., & Strowbridge, B. W. (2009) · Nature Neuroscience · doi:10.1038/nn.2458 · Cited by 95 · see citing works
Beyond bistability: Biophysics and temporal dynamics of working memory
Durstewitz, D., & Seamans, J. K. (2005) · Neuroscience · doi:10.1016/j.neuroscience.2005.06.094 · Cited by 93 · see citing works
A working memory model based on fast Hebbian learning
Sandberg, A., Tegner, J. N., & Lansner, A. (2003) · Network Computation in Neural Systems · doi:10.1088/0954-898x/14/4/309 · Cited by 90 · see citing works
Computational significance of transient dynamics in cortical networks
Durstewitz, D., & Deco, G. (2007) · European Journal of Neuroscience · doi:10.1111/j.1460-9568.2007.05976.x · Cited by 90 · see citing works
Miller, P. C., & Wang, X. (2005) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0508072103 · Cited by 88 · see citing works
Higher-Dimensional Neurons Explain the Tuning and Dynamics of Working Memory Cells
Singh, R., & Eliasmith, C. (2006) · Journal of Neuroscience · doi:10.1523/jneurosci.4864-05.2006 · Cited by 89 · see citing works
Solving the Problem of Negative Synaptic Weights in Cortical Models
Parisien, C., Anderson, C. H., & Eliasmith, C. (2008) · Neural Computation · doi:10.1162/neco.2008.07-06-295 · Cited by 83 · see citing works
Grid cells: The position code, neural network models of activity, and the problem of learning
Welinder, P., Burak, Y., & Fiete, I. (2008) · Hippocampus · doi:10.1002/hipo.20519 · Cited by 88 · see citing works
The Representation of Time for Motor Learning
Medina, J. F., Carey, M. R., & Lisberger, S. G. (2005) · Neuron · doi:10.1016/j.neuron.2004.12.017 · Cited by 89 · see citing works
Fine-Tuning and the Stability of Recurrent Neural Networks
MacNeil, D., & Eliasmith, C. (2011) · PLoS ONE · doi:10.1371/journal.pone.0022885 · Cited by 84 · see citing works
Surround Suppression Sharpens the Priority Map in the Lateral Intraparietal Area
Falkner, A. L., Krishna, B. S., & Goldberg, M. E. (2010) · Journal of Neuroscience · doi:10.1523/jneurosci.2327-10.2010 · Cited by 85 · see citing works
Neural representation of interval time
Durstewitz, D. (2004) · Neuroreport · doi:10.1097/00001756-200404090-00001 · Cited by 86 · see citing works
Purkinje Cells Directly Inhibit Granule Cells in Specialized Regions of the Cerebellar Cortex
Guo, C., Witter, L., Rudolph, S., Elliott, H. L., Ennis, K. A., & Regehr, W. G. (2016) · Neuron · doi:10.1016/j.neuron.2016.08.011 · Cited by 87 · see citing works
Firing Dynamics of Cerebellar Purkinje Cells
Fernandez, F. R., Engbers, J. D. T., & Turner, R. W. (2007) · Journal of Neurophysiology · doi:10.1152/jn.00306.2007 · Cited by 84 · see citing works
Psychophysical reverse correlation reflects both sensory and decision-making processes
Okazawa, G., Sha, L., Purcell, B. A., & Kiani, R. (2018) · Nature Communications · doi:10.1038/s41467-018-05797-y · Cited by 83 · see citing works
Compte, A. (2005) · Neuroscience · doi:10.1016/j.neuroscience.2005.06.011 · Cited by 81 · see citing works
Predicting non-linear dynamics by stable local learning in a recurrent spiking neural network
Gilra, A., & Gerstner, W. (2017) · eLife · doi:10.7554/elife.28295 · Cited by 89 · see citing works
Goldman, M. S., Compte, A., & Wang, X.-J. (2009) · Elsevier eBooks · doi:10.1016/b978-008045046-9.01434-0 · Cited by 77 · see citing works
Feng, J., & Feng, J. (2003) · Chapman & Hall/CRC eBooks · doi:10.1201/9780203494462-22 · Cited by 80 · see citing works
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 · see citing works
Self-citationKoppe, G., Toutounji, H., Kirsch, P., Lis, S., & Durstewitz, D. (2019) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1007263 · Cited by 74 · see citing works
Electron Microscopic Reconstruction of Functionally Identified Cells in a Neural Integrator
Vishwanathan, A., Daie, K., Ramirez, A. D., Lichtman, J. W., Aksay, E. R. F., & Seung, H. S. (2017) · Current Biology · doi:10.1016/j.cub.2017.06.028 · Cited by 74 · see citing works
Self-citationPsychiatric Illnesses as Disorders of Network Dynamics
Durstewitz, D., Huys, Q. J. M., & Koppe, G. (2020) · Biological Psychiatry Cognitive Neuroscience and Neuroimaging · doi:10.1016/j.bpsc.2020.01.001 · Cited by 80 · see citing works
Milojkovic, B. A., Radojicic, M. S., & Antic, S. D. (2005) · Journal of Neuroscience · doi:10.1523/jneurosci.5314-04.2005 · Cited by 70 · see citing works
An efficient automated parameter tuning framework for spiking neural networks
Carlson, K. D., Nageswaran, J. M., Dutt, N. D., & Krichmar, J. L. (2014) · Frontiers in Neuroscience · doi:10.3389/fnins.2014.00010 · Cited by 67 · see citing works
Nonassociative learning as gated neural integrator and differentiator in stimulus-response pathways
Poon, C., & Young, D. L. (2006) · Behavioral and Brain Functions · doi:10.1186/1744-9081-2-29 · Cited by 68 · see citing works
Continuous attractor network models of grid cell firing based on excitatory–inhibitory interactions
Shipston‐Sharman, O., Solanka, L., & Nolan, M. F. (2016) · The Journal of Physiology · doi:10.1113/jp270630 · Cited by 72 · see citing works
Self-Regulated Dynamical Criticality in Human ECoG
Solovey, G., Miller, K. J., Ojemann, J. G., Magnasco, M. O., & Cecchi, G. (2012) · Frontiers in Integrative Neuroscience · doi:10.3389/fnint.2012.00044 · Cited by 64 · see citing works
Background Synaptic Activity as a Switch Between Dynamical States in a Network
Salinas, E. (2003) · Neural Computation · doi:10.1162/089976603321891756 · Cited by 66 · see citing works
Theory of Gating in Recurrent Neural Networks
Krishnamurthy, K., Can, T., & Schwab, D. J. (2022) · Physical Review X · doi:10.1103/physrevx.12.011011 · Cited by 63 · see citing works
Computing with Continuous Attractors: Stability and Online Aspects
Wu, S., & Амари, Ш.-И. (2005) · Neural Computation · doi:10.1162/0899766054615626 · Cited by 62 · see citing works
Three brain states in the hippocampus and cortex
Kay, K., & Frank, L. M. (2018) · Hippocampus · doi:10.1002/hipo.22956 · Cited by 63 · see citing works
Dynamical systems, attractors, and neural circuits
Miller, P. C. (2016) · F1000Research · doi:10.12688/f1000research.7698.1 · Cited by 55 · see citing works
- Authors
- Seung, H. S., Lee, D. D., Reis, B. Y., & Tank, D. W.
- Affiliations
- Massachusetts Institute of Technology (US)
- Corresponding author
- Seung, H.Sebastian
- Venue
- Neuron
- Publisher
- Elsevier BV
- Published
- 2000-04
- Volume
- 26
- Issue
- 1
- Pages
- 259-271
- ISSN
- 0896-6273 (ISSN-L)
- OpenAlex
- W2052296894
- Cited by
- 339
- References
- 65
- Citations by year
- 2026: 4 · 2025: 13 · 2024: 9 · 2023: 11 · 2022: 12 · 2021: 12 · 2020: 6 · 2019: 13 · 2018: 15 · 2017: 14 · 2016: 11 · 2015: 15 · 2014: 13 · 2013: 14 · 2012: 13
- FWCI
- 9.58
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Neuron (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
- Life Sciences › Neuroscience › Cognitive Neuroscience › Memory and Neural Mechanisms
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Advanced Memory and Neural Computing
- Keywords
- short-term memory, eye position, eye fixations, recurrent neural networks, synaptic time constants, persistent firing, premotor neurons, memory stability
- MeSH terms
- Animals, Electric Conductivity, Eye Movements, Goldfish, Membrane Potentials, Memory, Short-Term, Oculomotor Muscles, Oculomotor Nerve, Neural Networks, Computer
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