The DOI matches its Crossref record; 13 of the 13 references it cites were found in a registry or an index.
History-dependent variability in population dynamics during evidence accumulation in cortex
Open accessAbstract
We studied how the posterior parietal cortex combines new information with ongoing activity dynamics as mice accumulate evidence during a virtual navigation task. Using new methods to analyze population activity on single trials, we found that activity transitioned rapidly between different sets of active neurons. Each event in a trial, whether an evidence cue or a behavioral choice, caused seconds-long modifications to the probabilities that govern how one activity pattern transitions to the next, forming a short-term memory. A sequence of evidence cues triggered a chain of these modifications resulting in a signal for accumulated evidence. Multiple distinguishable activity patterns were possible for the same accumulated evidence because representations of ongoing events were influenced by previous within- and across-trial events. Therefore, evidence accumulation need not require the explicit competition between groups of neurons, as in winner-take-all models, but could instead emerge implicitly from general dynamical properties that instantiate short-term memory.
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LIBSVM: A library for support vector machines
Chang, C.-C., & Lin, C.-J. (2011) · ACM Transactions on Intelligent Systems and Technology · doi:10.1145/1961189.1961199 · Cited by 40,918
Harnessing Nonlinearity: Predicting Chaotic Systems and Saving Energy in Wireless Communication
Jaeger, H., & Haas, H. (2004) · Science · doi:10.1126/science.1091277 · Cited by 3,811
The Neural Basis of Decision Making
Gold, J. I., & Shadlen, M. N. (2007) · Annual Review of Neuroscience · doi:10.1146/annurev.neuro.29.051605.113038 · Cited by 3,764
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
The importance of mixed selectivity in complex cognitive tasks
Rigotti, M., Barak, O., Warden, M. R., Wang, X.-J., Daw, N. D., Miller, E. K., & Fusi, S. (2013) · Nature · doi:10.1038/nature12160 · Cited by 1,639
Stimulus onset quenches neural variability: A widespread cortical phenomenon
Churchland, M. M., Yu, B. M., Cunningham, J. P., Sugrue, L. P., Cohen, M. R., Corrado, G. S., Newsome, W. T., Clark, A. M., Hosseini, P., Scott, B. B., et al. (2010) · Nature Neuroscience · doi:10.1038/nn.2501 · Cited by 1,084
Functional imaging of hippocampal place cells at cellular resolution during virtual navigation
Dombeck, D. A., Harvey, C. D., Tian, L., Looger, L. L., & Tank, D. W. (2010) · Nature Neuroscience · doi:10.1038/nn.2648 · Cited by 873
Self-citationFast nonnegative deconvolution for spike train inference from population calcium imaging
Vogelstein, J. T., Packer, A. M., Machado, T. A., Sippy, T., Babadi, B., Yuste, R., & Paninski, L. (2010) · Journal of Neurophysiology · doi:10.1152/jn.01073.2009 · Cited by 449
Variance as a signature of neural computations during decision making
Churchland, A. K., Kiani, R., Chaudhuri, R., Wang, X.-J., Pouget, A., & Shadlen, M. N. (2011) · Neuron · doi:10.1016/j.neuron.2010.12.037 · Cited by 350 · cited 1×
“Trials of the same type therefore had distinguishable trajectories of activity patterns and did not converge to similar paths through a small set of clusters, which is consistent with previous studies of variability in the activity of cortical neurons 21,22,27-29 .”
Separate Signals for Target Selection and Movement Specification in the Superior Colliculus
Horwitz, G. D., & Newsome, W. T. (1999) · Science · doi:10.1126/science.284.5417.1158 · Cited by 346
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Driscoll, L. N., Pettit, N. L., Minderer, M., Chettih, S. N., & Harvey, C. D. (2017) · Cell · doi:10.1016/j.cell.2017.07.021 · Cited by 445
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Morcos, A. S., Barrett, D. G. T., Rabinowitz, N. C., & Botvinick, M. (2018) · arXiv · doi:10.48550/arxiv.1803.06959 · Cited by 305
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Xu, Y. (2017) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2017.06.013 · Cited by 264
Accurate Estimation of Neural Population Dynamics without Spike Sorting
Trautmann, E. M., Stavisky, S. D., Lahiri, S., Ames, K. C., Kaufman, M. T., O’Shea, D. J., Vyas, S., Sun, X., Ryu, S. I., Ganguli, S., et al. (2019) · Neuron · doi:10.1016/j.neuron.2019.05.003 · Cited by 255
Metadata
- Authors
- Morcos, A. S., & Harvey, C. D.
- Venue
- Nature Neuroscience
- Published
- 2016-10-03
- Volume
- 19
- Issue
- 12
- Pages
- 1672-1681
- ISSN
- 1097-6256 (ISSN-L)
- 1546-1726
- OpenAlex
- W2527978657
- Cited by
- 247
- References
- 13
- FWCI
- 16.06
- Type
- journal article
- Language
- en
- Open access
- green
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