Neural correlations, population coding and computation

A Mathematical Theory of Communication

Shannon, C. E. (1948) · Bell System Technical Journal · doi:10.1002/j.1538-7305.1948.tb01338.x · Cited by 88,486

A Mathematical Theory of Communication

Shannon, C. E. (1948) · The MIT Press eBooks · doi:10.1002/j.1538-7305.1948.tb00917.x · Cited by 50,387

Receptive fields, binocular interaction and functional architecture in the cat’s visual cortex

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The Mathematical Theory of Communication

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An Information-Maximization Approach to Blind Separation and Blind Deconvolution

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Independent Component Analysis

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Statistical Inference

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Emergence of simple-cell receptive field properties by learning a sparse code for natural images

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Independent Component Analysis

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Neuronal Population Coding of Movement Direction

Georgopoulos, A. P., Schwartz, A. B., & Kettner, R. E. (1986) · Science · doi:10.1126/science.3749885 · Cited by 3,219

Lower neuronal variability in the monkey dorsolateral prefrontal than posterior parietal cortex

Qi, X.-L., & Constantinidis, C. (2015) · Journal of Neurophysiology · doi:10.1152/jn.00454.2015 · Cited by 14

Visual reconstruction from 2-photon calcium imaging suggests linear readout properties of neurons in mouse primary visual cortexPreprint

Garasto, S., Bharath, A. A., & Schultz, S. R. (2018) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/300392 · Cited by 14

Task-evoked activity quenches neural correlations and variability across cortical areasPreprint

Ito, T., Brincat, S. L., Siegel, M., Mill, R. D., He, B. J., Miller, E. K., Rotstein, H. G., & Cole, M. W. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/560730 · Cited by 14

Sensory coding and contrast invariance emerge from the control of plastic inhibition over emergent selectivity

Larisch, R., Gönner, L., Teichmann, M., & Hamker, F. H. (2021) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1009566 · Cited by 13

Behavioural relevance of redundant and synergistic stimulus information between functionally connected neurons in mouse auditory cortex

Koçillari, L., Celotto, M., Francis, N. A., Mukherjee, S., Babadi, B., Kanold, P. O., & Panzeri, S. (2023) · Brain Informatics · doi:10.1186/s40708-023-00212-9 · Cited by 13

Activation of M1 cholinergic receptors in mouse somatosensory cortex enhances information processing and detection behaviour

Mishra, W., Kheradpezhouh, E., & Arabzadeh, E. (2024) · Communications Biology · doi:10.1038/s42003-023-05699-w · Cited by 12

Peripheral neural interfaces for reading high-frequency brain signals

Ibáñez, J., Zicher, B., Burdet, E., Baker, S. N., Mehring, C., & Farina, D. (2025) · Nature Biomedical Engineering · doi:10.1038/s41551-025-01445-1 · Cited by 15

A Causal Perspective on the Analysis of Signal and Noise Correlations and Their Role in Population Coding

Chicharro, D. (2014) · Neural Computation · doi:10.1162/neco_a_00588 · Cited by 13

Origins of correlated spiking in the mammalian olfactory bulb

Gerkin, R. C., Tripathy, S. J., & Urban, N. N. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1303830110 · Cited by 14

Natural Vocalizations in the Mammalian Inferior Colliculus are Broadly Encoded by a Small Number of Independent Multi-Units

Lyzwa, D., Herrmann, J. M., & Wörgötter, F. (2016) · Frontiers in Neural Circuits · doi:10.3389/fncir.2015.00091 · Cited by 13

IS NEUROSCIENCE ADEQUATE AS THE FORTHCOMING "MINDSCIENCE"?

Manzotti, R., & Moderato, P. (2010) · Cited by 13

Adaptation modulates correlated subthreshold response variability in visual cortex

Wright, N. C., Hoseini, M. S., & Weßel, R. (2017) · Journal of Neurophysiology · doi:10.1152/jn.00124.2017 · Cited by 13

Correlated Variability in the Neurons With the Strongest Tuning Improves Direction Coding

Zavitz, E., Yu, H., Rosa, M. G. P., & Price, N. S. C. (2017) · Cerebral Cortex · doi:10.1093/cercor/bhx344 · Cited by 13

A Comparison Study of Point-Process Filter and Deep Learning Performance in Estimating Rat Position Using an Ensemble of Place Cells

Rezaei, M. R., Gillespie, A. K., Guidera, J. A., Nazari, B., Sadri, S., Frank, L. M., Eden, U. T., & Yousefi, A. (2018) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc.2018.8513154 · Cited by 13

The Refractory Period Matters: Unifying Mechanisms of Macroscopic Brain Waves

Weistuch, C., Mujica-Parodi, L. R., & Dill, K. A. (2021) · Neural Computation · doi:10.1162/neco_a_01371 · Cited by 13

Bridging the information and dynamics attributes of neural activities

Tian, Y., Li, G., & Sun, P. (2021) · Physical Review Research · doi:10.1103/physrevresearch.3.043085 · Cited by 14

Feature representation under crowding in macaque V1 and V4 neuronal populations

Henry, C. A., & Kohn, A. (2022) · Current Biology · doi:10.1016/j.cub.2022.10.049 · Cited by 13

Functional network properties of the auditory cortex

Lestang, J.-H., Cai, H., Averbeck, B. B., & Cohen, Y. E. (2023) · Hearing Research · doi:10.1016/j.heares.2023.108768 · Cited by 13

Robust encoding of natural stimuli by neuronal response sequences in monkey visual cortex

Yang, Y., Shapcott, K. A., Peter, A., Klon-Lipok, J., Huang, X., Lazăr, A., & Singer, W. (2023) · Nature Communications · doi:10.1038/s41467-023-38587-2 · Cited by 14

Sleep-like changes in neural processing emerge during sleep deprivation in early auditory cortex

Marmelshtein, A., Eckerling, A., Hadad, B., Ben‐Eliyahu, S., & Nir, Y. (2023) · Current Biology · doi:10.1016/j.cub.2023.06.022 · Cited by 15

Spike Train Statistics from Empirical Facts to Theory: The Case of the Retina

Cessac, B., & Palacios, A. G. (2012) · Springer eBooks · doi:10.1007/978-3-642-31208-3_8 · Cited by 13

Perception of auditory signals

Recanzone, G. H. (2011) · Annals of the New York Academy of Sciences · doi:10.1111/j.1749-6632.2010.05920.x · Cited by 13

Correlated activity supports efficient cortical processing

Hung, C. P., Cui, D., Chen, Y.-P., Lin, C.-P., & Levine, M. R. (2015) · Frontiers in Computational Neuroscience · doi:10.3389/fncom.2014.00171 · Cited by 13

Extensive excitatory network interactions shape temporal processing of communication signals in a model sensory system

Ma, X., Kohashi, T., & Carlson, B. A. (2013) · Journal of Neurophysiology · doi:10.1152/jn.00145.2013 · Cited by 13

The structured ‘low temperature’ phase of the retinal population code

Ioffe, M. L., & Berry, M. J. (2017) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1005792 · Cited by 13

Variability of Neuronal Responses: Types and Functional Significance in Neuroplasticity and Neural Darwinism

Chervyakov, A. V., Sinitsyn, D. O., & Пирадов, М. А. (2016) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2016.00603 · Cited by 14

When do correlations increase with firing rates in recurrent networks?

Barreiro, A. K., & Ly, C. (2017) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1005506 · Cited by 14

A modular high-density μ ECoG system on macaque vlPFC for auditory cognitive decoding

Chiang, C., Lee, J., Wang, C., Williams, A. J., Lucas, T. H., Cohen, Y. E., & Viventi, J. (2020) · Journal of Neural Engineering · doi:10.1088/1741-2552/ab9986 · Cited by 13

Representation of foreseeable choice outcomes in orbitofrontal cortex triplet-wise interactions

Balaguer‐Ballester, E., Nogueira, R., Abofalia, J. M., Moreno‐Bote, R., & Sanchez-Vives, M. V. (2020) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1007862 · Cited by 14

Collapse of complexity of brain and body activity due to excessive inhibition and MeCP2 disruption

Li, J., Kells, P. A., Osgood, A. C., Gautam, S. H., & Shew, W. L. (2021) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2106378118 · Cited by 13

Readout of the intrinsic and extrinsic properties of a stimulus from un-experienced neuronal activities: Towards cognitive neuroprostheses

Kia, S. F., Ästrand, E., Ibos, G., & Hamed, S. B. (2011) · Journal of Physiology-Paris · doi:10.1016/j.jphysparis.2011.07.015 · Cited by 16

Graphical Models of Functional and Effective Neuronal Connectivity

Eldawlatly, S., & Oweiss, K. G. (2010) · Elsevier eBooks · doi:10.1016/b978-0-12-375027-3.00005-3 · Cited by 13

Integrated Neuromorphic Photonic Computing for AI Acceleration: Emerging Devices, Network Architectures, and Future Paradigms

Wang, G., Che, J., Gao, C., Zhou, H., Shen, J., Cheng, Z., & Zhou, P. (2025) · Advanced Materials · doi:10.1002/adma.202508029 · Cited by 13

Privileged representational axes in biological and artificial neural networks

Khosla, M., Williams, A. H., McDermott, J. H., & Kanwisher, N. (2023) · Conference on Cognitive Computational Neuroscience (CCN) · doi:10.32470/ccn.2023.1664-0 · Cited by 14

Feedforward attentional selection in sensory cortex

Westerberg, J. A., Schall, J. D., Woodman, G. F., & Maier, A. (2023) · Nature Communications · doi:10.1038/s41467-023-41745-1 · Cited by 12

Neural populations within macaque early vestibular pathways are adapted to encode natural self-motion

Mohammadi, M., Carriot, J., Mackrous, I., Cullen, K. E., & Chacron, M. J. (2024) · PLoS Biology · doi:10.1371/journal.pbio.3002623 · Cited by 12

Stimulus type shapes the topology of cellular functional networks in mouse visual cortex

Tang, D., Zylberberg, J., Jia, X., & Choi, H. (2024) · Nature Communications · doi:10.1038/s41467-024-49704-0 · Cited by 12

Engineered biological neuronal networks as basic logic operators

Küchler, J., Vulić, K., Yao, H., Valmaggia, C., Ihle, S. J., Weaver, S., & Vörös, J. (2025) · Frontiers in Computational Neuroscience · doi:10.3389/fncom.2025.1559936 · Cited by 12

Revisiting the high-dimensional geometry of population responses in the visual cortex

Pospisil, D. A., & Pillow, J. W. (2025) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2506535122 · Cited by 15

Targeted dimensionality reduction enables reliable estimation of neural population coding accuracy from trial-limited data

Heller, C. R., & David, S. V. (2022) · PLoS ONE · doi:10.1371/journal.pone.0271136 · Cited by 12

The Role of Alpha and Beta Oscillations in the Human EEG During Perception and Memory Processes

Michelmann, S., Griffiths, B., & Hanslmayr, S. (2022) · Oxford University Press eBooks · doi:10.1093/oxfordhb/9780192898340.013.10 · Cited by 12

Transformation of acoustic information to sensory decision variables in the parietal cortex

Yao, J. D., Zemlianova, K. O., Hocker, D. L., Savin, C., Constantinople, C. M., Chung, S., & Sanes, D. H. (2023) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2212120120 · Cited by 12

Coherent mapping of position and head direction across auditory and visual cortex

Mertens, P. E. C., Marchesi, P., Ruikes, T. R., Lohuis, M. N. O., Krijger, Q., Pennartz, C. M. A., & Lansink, C. S. (2023) · Cerebral Cortex · doi:10.1093/cercor/bhad045 · Cited by 13

Information representation with an ensemble of Hodgkin–Huxley neurons

Lazar, A. A. (2006) · Neurocomputing · doi:10.1016/j.neucom.2006.10.128 · Cited by 12

A (Somewhat) New Solution to the Variable Binding Problem

Barrett, L., Feldman, J. A., & Dermed, L. M. (2008) · Neural Computation · doi:10.1162/neco.2008.07-06-290 · Cited by 12

Optimal attentional modulation of a neural population

Borji, A., & Itti, L. (2014) · Frontiers in Computational Neuroscience · doi:10.3389/fncom.2014.00034 · Cited by 13

A generative spike train model with time-structured higher order correlations

Trousdale, J., Hu, Y., Shea‐Brown, E., & Josić́, K. (2013) · Frontiers in Computational Neuroscience · doi:10.3389/fncom.2013.00084 · Cited by 12

Noise-Robust Modes of the Retinal Population Code Have the Geometry of “Ridges” and Correspond to Neuronal Communities

Loback, A., Prentice, J., Ioffe, M. L., & Berry, M. J. (2017) · Neural Computation · doi:10.1162/neco_a_01011 · Cited by 14

Learning the meaning of new stimuli increases the cross-correlated activity of prefrontal neurons

Nougaret, S., & Genovesio, A. (2018) · Scientific Reports · doi:10.1038/s41598-018-29862-0 · Cited by 12

Enhanced Discriminative Abilities of Auditory Cortex Neurons for Pup Calls Despite Reduced Evoked Responses in C57BL/6 Mother Mice

Royer, J., Huetz, C., Occelli, F., Cancela, J., & Edeline, J. (2020) · Neuroscience · doi:10.1016/j.neuroscience.2020.11.031 · Cited by 12

Synergistic population coding of natural communication stimuli by hindbrain electrosensory neurons

Wang, Z., & Chacron, M. J. (2021) · Scientific Reports · doi:10.1038/s41598-021-90413-1 · Cited by 13

Decorrelation of sensory-evoked neuronal responses in rat barrel cortex during postnatal development

Ikezoe, K., Tamura, H., Kimura, F., & Fujita, I. (2012) · Neuroscience Research · doi:10.1016/j.neures.2012.05.009 · Cited by 14

Minimum Mutual Information and Non-Gaussianity through the Maximum Entropy Method: Estimation from Finite Samples

Pires, C., & Perdigão, R. A. P. (2013) · Entropy · doi:10.3390/e15030721 · Cited by 12

Synergistic Coding by Cortical Neural Ensembles

Aghagolzadeh, M., Eldawlatly, S., & Oweiss, K. G. (2010) · IEEE Transactions on Information Theory · doi:10.1109/tit.2009.2037057 · Cited by 12

The Theory of Localist Representation and of a Purely Abstract Cognitive System: The Evidence from Cortical Columns, Category Cells, and Multisensory Neurons

Roy, A. (2017) · Frontiers in Psychology · doi:10.3389/fpsyg.2017.00186 · Cited by 13

Distinct Temporal Coordination of Spontaneous Population Activity between Basal Forebrain and Auditory Cortex

Yagüe, J. G., Tsunematsu, T., & Sakata, S. (2017) · Frontiers in Neural Circuits · doi:10.3389/fncir.2017.00064 · Cited by 12

Synchrony State Generation in Artificial Neural Networks with Stochastic Synapses

El-Laithy, K., & Bogdan, M. (2009) · Lecture notes in computer science · doi:10.1007/978-3-642-04274-4_19 · Cited by 12

Simultaneous multi-area recordings suggest that attention improves performance by reshaping stimulus representationsPreprint

Ruff, D. A., & Cohen, M. R. (2018) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/372888 · Cited by 12

Population Codes: Theoretic Aspects

Ma, W. J., & Pouget, A. (2009) · Elsevier eBooks · doi:10.1016/b978-008045046-9.01401-7 · Cited by 12

Dynamics and sources of response variability and its coordination in visual cortex

Hoseini, M. S., Wright, N. C., Xià, J., Clawson, W. P., Shew, W. L., & Weßel, R. (2019) · Visual Neuroscience · doi:10.1017/s0952523819000117 · Cited by 12

Worry and rumination elicit similar neural representations: neuroimaging evidence for repetitive negative thinking

Puccetti, N. A., Stamatis, C. A., Timpano, K. R., & Heller, A. S. (2024) · Cognitive Affective & Behavioral Neuroscience · doi:10.3758/s13415-024-01239-z · Cited by 11

Encoding Through Patterns: Regression Tree–Based Neuronal Population Models

Haslinger, R., Pipa, G., Lewis, L. D., Nikolić, D., Williams, Z. M., & Brown, E. N. (2013) · Neural Computation · doi:10.1162/neco_a_00464 · Cited by 11

Relating the Structure of Noise Correlations in Macaque Primary Visual Cortex to Decoder Performance

Mendels, O. P., & Shamir, M. (2018) · Frontiers in Computational Neuroscience · doi:10.3389/fncom.2018.00012 · Cited by 11

Representational untangling by the firing rate nonlinearity in V1 simple cells

Gáspár, M. E., Polack, P., Golshani, P., Lengyel, M., & Orbán, G. (2019) · eLife · doi:10.7554/elife.43625 · Cited by 11

Robust Detection of Absence of Slip in Robot Hands and Feet

Massalim, Y., Kappassov, Z., Varol, H. A., & Hayward, V. (2021) · IEEE Sensors Journal · doi:10.1109/jsen.2021.3127501 · Cited by 11

A Stochastic Leaky-Integrate-and-Fire Neuron Model With Floating Gate-Based Technology for Fast and Accurate Population Coding

Goda, A., Matsui, C., & Takeuchi, K. (2022) · IEEE Journal of the Electron Devices Society · doi:10.1109/jeds.2022.3206317 · Cited by 11

Neuronal Population Encoding of Identity in Primate Prefrontal Cortex

Sharma, K., Diltz, M. A., Lincoln, T., Albuquerque, E. R., & Romanski, L. M. (2023) · Journal of Neuroscience · doi:10.1523/jneurosci.0703-23.2023 · Cited by 11

A statistical description of neural ensemble dynamics

Long, J. D., II (2011) · Frontiers in Computational Neuroscience · doi:10.3389/fncom.2011.00052 · Cited by 11

Spike-based Decision Learning of Nash Equilibria in Two-Player Games

Friedrich, J. H., & Senn, W. (2012) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1002691 · Cited by 11

Circuit mechanisms revealed by spike-timing correlations in macaque area MT

Huang, X., & Lisberger, S. G. (2012) · Journal of Neurophysiology · doi:10.1152/jn.00775.2012 · Cited by 11

Predicting oculomotor behaviour from correlated populations of posterior parietal neurons

Graf, A. B. A., & Andersen, R. A. (2015) · Nature Communications · doi:10.1038/ncomms7024 · Cited by 12

Correlations between prefrontal neurons form a small-world network that optimizes the generation of multineuron sequences of activity

Luongo, F. J., Zimmerman, C. A., Horn, M. E., & Sohal, V. S. (2016) · Journal of Neurophysiology · doi:10.1152/jn.01043.2015 · Cited by 11

Brain-state invariant thalamo-cortical coordination revealed by non-linear encoders

Viejo, G. D., Cortier, T., & Peyrache, A. (2018) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1006041 · Cited by 11

Neuronal coupling benefits the encoding of weak periodic signals in symbolic spike patterns

Masoliver, M., & Masoller, C. (2019) · Communications in Nonlinear Science and Numerical Simulation · doi:10.1016/j.cnsns.2019.105023 · Cited by 11

The Noisy Brain: Power of Resting-State Fluctuations Predicts Individual Recognition Performance

Grossman, S., Yeagle, E. M., Harel, M., Espinal, E., Harpaz, R., Noy, N., Mégevand, P., Groppe, D. M., Mehta, A. D., & Malach, R. (2019) · Cell Reports · doi:10.1016/j.celrep.2019.11.081 · Cited by 12

Dual Roles for Spike Signaling in Cortical Neural Populations

Ballard, D. H., & Jehee, J. F. M. (2011) · Frontiers in Computational Neuroscience · doi:10.3389/fncom.2011.00022 · Cited by 11

Information Loss Associated with Imperfect Observation and Mismatched Decoding

Oizumi, M., Okada, M., & Амари, Ш.-И. (2011) · Frontiers in Computational Neuroscience · doi:10.3389/fncom.2011.00009 · Cited by 13

Organization of local horizontal functional interactions between neurons in the inferior temporal cortex of macaque monkeys

Tamura, H., Mori, Y., & Kaneko, H. (2014) · Journal of Neurophysiology · doi:10.1152/jn.00336.2013 · Cited by 11

Anthropic Correction of Information Estimates and Its Application to Neural Coding

Gastpar, M., Gill, P. R., Huth, A. G., & Theunissen, F. E. (2010) · IEEE Transactions on Information Theory · doi:10.1109/tit.2009.2037053 · Cited by 11

How biased are maximum entropy models

Macke, J. H., Murray, I., & Latham, P. E. (2011) · Max Planck Digital Library · Cited by 11

Effect of interacting second- and third-order stimulus-dependent correlations on population-coding asymmetries

Montangie, L., & Montani, F. (2016) · Physical review. E · doi:10.1103/physreve.94.042303 · Cited by 11

Distinct Correlation Structure Supporting a Rate-Code for Sound Localization in the Owl’s Auditory Forebrain

Beckert, M. V., Pavão, R., & Peña, J. L. (2017) · eNeuro · doi:10.1523/eneuro.0144-17.2017 · Cited by 12

Synergy, Redundancy and Common InformationPreprint

Banerjee, P. K., & Griffith, V. (2015) · arXiv (Cornell University) · doi:10.48550/arxiv.1509.03706 · Cited by 11

Geometry Linked to Untangling Efficiency Reveals Structure and Computation in Neural PopulationsPreprint

Chou, C.-N., Kim, R., Arend, L. A., Yang, Y.-Y., Mensh, B. D., Shim, W. M., Perich, M. G., & Chung, S. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.02.26.582157 · Cited by 14

From Functional Architecture to Organizing Principles of Neuronal Ensembles in Mouse Area V1Preprint

Papadopouli, M., Smyrnakis, I., Koniotakis, E., Savaglio, M. A., Brozi, C., Psilou, E., Palagina, G., & Smirnakis, S. M. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.02.29.582364 · Cited by 13

Coupled Dynamics of Stimulus-Evoked Gustatory Cortical and Basolateral Amygdalar Activity

Mahmood, A., Steindler, J. R., Germaine, H., Miller, P. C., & Katz, D. B. (2022) · Journal of Neuroscience · doi:10.1523/jneurosci.1412-22.2022 · Cited by 12

MINT: A toolbox for the analysis of multivariate neural information coding and transmission

Lorenz, G. M., Engel, N. M., Celotto, M., Koçillari, L., Curreli, S., Fellin, T., & Panzeri, S. (2025) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1012934 · Cited by 10

Neural population geometry and optimal coding of tasks with shared latent structure

Wakhloo, A. J., Slatton, W., & Chung, S. (2026) · Nature Neuroscience · doi:10.1038/s41593-025-02183-y · Cited by 16

Tuning and spontaneous spike time synchrony share a common structure in macaque inferior temporal cortex

Lin, C.-P., Chen, Y.-P., & Hung, C. P. (2014) · Journal of Neurophysiology · doi:10.1152/jn.00485.2013 · Cited by 10

A Moment-Based Maximum Entropy Model for Fitting Higher-Order Interactions in Neural Data

Cayco-Gajic, N. A., Zylberberg, J., & Shea‐Brown, E. (2018) · Entropy · doi:10.3390/e20070489 · Cited by 10

Heterogeneous Synaptic Weighting Improves Neural Coding in the Presence of Common Noise

Sachdeva, P., Livezey, J. A., & DeWeese, M. R. (2020) · Neural Computation · doi:10.1162/neco_a_01287 · Cited by 10

Electric Stimulation Elicits Heterogeneous Responses in ON but Not OFF Retinal Ganglion Cells to Transmit Rich Neural Information

Kang, J. H., Jang, Y. J., Kim, T., Lee, B. C., Lee, S. H., & Im, M. (2021) · IEEE Transactions on Neural Systems and Rehabilitation Engineering · doi:10.1109/tnsre.2020.3048973 · Cited by 10

Perceptual enhancement and suppression correlate with V1 neural activity during active sensing

Niemeyer, J. E., Akers-Campbell, S., Gregoire, A., & Paradiso, M. A. (2022) · Current Biology · doi:10.1016/j.cub.2022.04.067 · Cited by 11

Altered alpha/beta desynchronization during item–context binding contributes to the associative deficit in older age

Karlsson, A., & Sander, M. C. (2022) · Cerebral Cortex · doi:10.1093/cercor/bhac219 · Cited by 10

Arousal and Locomotion Differently Modulate Activity of Somatostatin Neurons across Cortex

Khoury, C. F., Fala, N. G., & Runyan, C. A. (2023) · eNeuro · doi:10.1523/eneuro.0136-23.2023 · Cited by 12

The Structure of Hippocampal CA1 Interactions Optimizes Spatial Coding across Experience

Nardin, M., Csicsvari, J., Tkačik, G., & Savin, C. (2023) · Journal of Neuroscience · doi:10.1523/jneurosci.0194-23.2023 · Cited by 11

Stable sound decoding despite modulated sound representation in the auditory cortex

Funamizu, A., Marbach, F., & Zador, A. M. (2023) · Current Biology · doi:10.1016/j.cub.2023.09.031 · Cited by 11

The Effect of Correlated Neuronal Firing and Neuronal Heterogeneity on Population Coding Accuracy in Guinea Pig Inferior Colliculus

Zohar, O., Shackleton, T. M., Palmer, A. R., & Shamir, M. (2013) · PLoS ONE · doi:10.1371/journal.pone.0081660 · Cited by 10

Predictive and postdictive mechanisms jointly contribute to visual awareness

Soga, R., Akaishi, R., & Sakai, K. (2009) · Consciousness and Cognition · doi:10.1016/j.concog.2009.04.007 · Cited by 11

Parallel coding schemes of whisker velocity in the rat's somatosensory system

Lottem, E., Gugig, E., & Azouz, R. (2015) · Journal of Neurophysiology · doi:10.1152/jn.00485.2014 · Cited by 10

Effects of noise correlations on population coding

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