The DOI matches its Crossref record; 27 of the 27 references it cites were found in a registry or an index.
Small modulation of ongoing cortical dynamics by sensory input during natural vision.
Abstract
During vision, it is believed that neural activity in the primary visual cortex is predominantly driven by sensory input from the environment. However, visual cortical neurons respond to repeated presentations of the same stimulus with a high degree of variability. Although this variability has been considered to be noise owing to random spontaneous activity within the cortex, recent studies show that spontaneous activity has a highly coherent spatio-temporal structure. This raises the possibility that the pattern of this spontaneous activity may shape neural responses during natural viewing conditions to a larger extent than previously thought. Here, we examine the relationship between spontaneous activity and the response of primary visual cortical neurons to dynamic natural-scene and random-noise film images in awake, freely viewing ferrets from the time of eye opening to maturity. The correspondence between evoked neural activity and the structure of the input signal was weak in young animals, but systematically improved with age. This improvement was linked to a shift in the dynamics of spontaneous activity. At all ages including the mature animal, correlations in spontaneous neural firing were only slightly modified by visual stimulation, irrespective of the sensory input. These results suggest that in both the developing and mature visual cortex, sensory evoked neural activity represents the modulation and triggering of ongoing circuit dynamics by input signals, rather than directly reflecting the structure of the input signal itself.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
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?
In the citing paper
“several experimental studies arrive at the conclusion that external stimuli only modulate the highly stochastic spontaneous firing activity of cortical networks of neurons [7], [8].”
From Neural dynamics as sampling: a model for stochastic computation in recurrent networks of spiking neurons (2011) · cites this paper as [7]
In the citing paper
“This alternative perspective suggests that the brain is active even in the absence of task, primarily driven by internal dynamics, with external events modulating rather than determining the activity of the system (24)(25)(26)(27)(28).”
From Spontaneous neuronal activity distinguishes human dorsal and ventral attention systems (2006) · cites this paper as [25]
Citations
Cites
An Energy Budget for Signaling in the Grey Matter of the Brain
Attwell, D., & Laughlin, S. B. (2001) · Journal of Cerebral Blood Flow & Metabolism · doi:10.1097/00004647-200110000-00001 · Cited by 3,543
Shadlen, M. N., & Newsome, W. T. (1998) · The Journal of Neuroscience · doi:10.1523/jneurosci.18-10-03870.1998 · Cited by 2,178
Sparse Coding and Decorrelation in Primary Visual Cortex During Natural Vision
Vinje, W. E., & Gallant, J. L. (2000) · Science · doi:10.1126/science.287.5456.1273 · Cited by 1,286
Correlated neuronal discharge rate and its implications for psychophysical performance
Zohary, E., Shadlen, M. N., & Newsome, W. T. (1994) · Nature · doi:10.1038/370140a0 · Cited by 1,237
The cost of cortical computation.
Lennie, P. (2003) · Current Biology · doi:10.1016/s0960-9822(03)00135-0 · Cited by 1,134
Synchronous bursts of action potentials in ganglion cells of the developing mammalian retina
Meister, M., Wong, R. O. L., Baylor, D. A., & Shatz, C. J. (1991) · Science · doi:10.1126/science.2035024 · Cited by 1,110
Spontaneously emerging cortical representations of visual attributes
Kenet, T., Bibitchkov, D., Tsodyks, M., Grinvald, A., & Arieli, A. (2003) · Nature · doi:10.1038/nature02078 · Cited by 924
Linking Spontaneous Activity of Single Cortical Neurons and the Underlying Functional Architecture
Tsodyks, M. V., Kenet, T., Grinvald, A., & Arieli, A. (1999) · Science · doi:10.1126/science.286.5446.1943 · Cited by 715
Attractor dynamics of network UP states in the neocortex
Cossart, R., Aronov, D., & Yuste, R. (2003) · Nature · doi:10.1038/nature01614 · Cited by 659
I NFERENCE AND C OMPUTATION WITH P OPULATION C ODES
Pouget, A., Dayan, P., & Zemel, R. S. (2003) · Annual Review of Neuroscience · doi:10.1146/annurev.neuro.26.041002.131112 · Cited by 446
Cited by
Sorted by citations
Items 301–400 of 425
Cortical activity pattern computation
András, P., & Wennekers, T. (2006) · Biosystems · doi:10.1016/j.biosystems.2006.09.012 · Cited by 6
A ubiquitous spectrolaminar motif of local field potential power across the primate cortex?Preprint
Mackey, C. A., Neymotin, S. A., Durá-Bernal, S., Haegens, S., Jones, S. R., Ding, M., & Schroeder, C. E. (2024) · OSF Preprints (OSF Preprints) · doi:10.31219/osf.io/6wfkx · Cited by 6
Synaptic topography – Converging connections and emerging function
Takahashi, N. (2018) · Neuroscience Research · doi:10.1016/j.neures.2018.11.001 · Cited by 8
Bordier, C., & Macaluso, E. (2015) · Human Brain Mapping · doi:10.1002/hbm.22852 · Cited by 5
Visually Evoked Spiking Evolves While Spontaneous Ongoing Dynamics Persist
Huys, R., Jirsa, V., Darokhan, Z., Valentiniene, S., & Roland, P. E. (2016) · Frontiers in Systems Neuroscience · doi:10.3389/fnsys.2015.00183 · Cited by 5
Stochastic neural fields as gradient dynamical systems
Bressloff, P. C., & Carroll, S. R. (2019) · Physical review. E · doi:10.1103/physreve.100.012402 · Cited by 5
Long-Tailed Characteristics of Neural Activity Induced by Structural Network Properties
Nobukawa, S. (2022) · Frontiers in Applied Mathematics and Statistics · doi:10.3389/fams.2022.905807 · Cited by 6
Altavini, T. S., Conde‐Ocazionez, S., Eriksson, D., Wunderle, T., & Schmidt, K. E. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2016.09.048 · Cited by 6
Visual epidural field potentials possess high functional specificity in single trials
Fischer, B., Schander, A., Kreiter, A. K., Lang, W., & Wegener, D. (2019) · Journal of Neurophysiology · doi:10.1152/jn.00510.2019 · Cited by 5
Saccade-related activity in areas 18 and 21a of cats freely viewing complex scenes
Moeller, G. U., Kayser, C., & Peter König, B. (2007) · Neuroreport · doi:10.1097/wnr.0b013e3280125686 · Cited by 5
Instability with a purpose: how the visual brain makes decisions in a volatile worldPreprint
Cao, R., Pastukhov, A., Aleshin, S. E., Mattia, M., & Braun, J. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.06.09.142497 · Cited by 5
Learning shapes cortical dynamics to enhance integration of relevant sensory inputPreprint
Chadwick, A., Khan, A. G., Poort, J., Blot, A., Hofer, S. B., Mrsic‐Flogel, T. D., & Sahani, M. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.08.02.454726 · Cited by 4
Spatial dynamics of spontaneous activity in the developing and adult cortices
Murakami, T. (2024) · Neuroscience Research · doi:10.1016/j.neures.2024.12.002 · Cited by 7
Brain Rhythms Provide a Framework for Neural Syntax
Buzsáki, G. (2019) · Oxford University Press eBooks · doi:10.1093/oso/9780190905385.003.0006 · Cited by 3
Taillefumier, T. O., Touboul, J., & Magnasco, M. O. (2012) · Neural Computation · doi:10.1162/neco_a_00346 · Cited by 4
Timing of Cortical Events Preceding Voluntary Movement
Vvedensky, V. L., & Prokofyev, A. O. (2015) · Neural Computation · doi:10.1162/neco_a_00802 · Cited by 4
Intrinsic Activity and Consciousness
Raichle, M. E. (2011) · Research and perspectives in neurosciences · doi:10.1007/978-3-642-18015-6_9 · Cited by 4
Spatial effects of shifting prisms on properties of posterior parietal cortex neurons
Karkhanis, A. N., Heider, B., Silva, F. M., & Siegel, R. M. (2014) · The Journal of Physiology · doi:10.1113/jphysiol.2014.270942 · Cited by 4
Bidirectional interaction of sleep and synaptic plasticity: A view from visual cortex
Miyamoto, H., & Hensch, T. K. (2006) · Sleep and Biological Rhythms · doi:10.1111/j.1479-8425.2006.00204.x · Cited by 4
The other kind of perceptual learning
Fiser, J. (2009) · Learning & Perception · doi:10.1556/lp.1.2009.1.6 · Cited by 4
Self-citationMatsuda, T., Kitajo, K., Yamaguchi, Y., & Komaki, F. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2017.02.068 · Cited by 4
Off-manifold coding in visual cortex revealed by sleepPreprint
de Oliveira, E. F., Kim, S., Qiu, T. S., Peyrache, A., Batista‐Brito, R., & Sjulson, L. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.06.10.495710 · Cited by 4
Gamma oscillations in the mouse primary visual cortex as an endophenotype of schizophrenia
Welle, C. G. (2010) · ScholarlyCommons (University of Pennsylvania) · Cited by 3
Demanuele, C., Capilla, A., Pérez-Hernández, E., Sonuga-Barke, E. J. S., & James, C. J. (2010) · Journal of Psychophysiology · doi:10.1027/0269-8803/a000002 · Cited by 3
Yoshida, T., Sakagami, M., Yamazaki, K., Katura, T., Iwamoto, M., & Tanaka, N. (2007) · IEEJ Transactions on Electronics Information and Systems · doi:10.1541/ieejeiss.127.1642 · Cited by 3
Optical imaging of the prefrontal activity in joint attention experience
Qiu, L., Zhang, X., & Li, J. (2015) · Biomedical Optics Express · doi:10.1364/boe.6.003437 · Cited by 3
Veale, R., Briggs, G., & Scheutz, M. J. (2013) · eScholarship (California Digital Library) · Cited by 3
BRAIN ACTIVITY AT THE EMBRYONIC STAGES OF DEVELOPMENT
Valeeva, G., & Colonnese, M. T. (2015) · DOAJ (DOAJ: Directory of Open Access Journals) · Cited by 3
Hidden Markov Models Predict the Future Choice Better Than a PSTH-Based Method
Marcos, E., Londei, F., & Genovesio, A. (2019) · Neural Computation · doi:10.1162/neco_a_01216 · Cited by 3
Study on Caenorhabditis Elegans as a Combined Model of Microdosimetry and Biology
Yu, W., Long, H., Gao, J., Wang, Y., Tu, Y., Sun, L., & Chen, N. (2021) · Dose-Response · doi:10.1177/1559325821990125 · Cited by 3
Buzsáki, G. (2019) · Oxford University Press eBooks · doi:10.1093/oso/9780190905385.003.0001 · Cited by 4
Strong, but not weak, noise correlations are beneficial for population codingPreprint
Mahuas, G., Buffet, T., Marre, O., Ferrari, U., & Mora, T. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.06.26.600826 · Cited by 4
Neural traveling waves in cortex: Network mechanisms and potential roles in neural computation
Muller, L., Busch, A. N., Davis, Z. W., & Reynolds, J. H. (2026) · Neuron · doi:10.1016/j.neuron.2026.06.019 · Cited by 6
Nobukawa, S., Nishimura, H., & Yamanishi, T. (2018) · IEEE International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC) · doi:10.1109/icci-cc.2018.8482070 · Cited by 2
Serial dependence in face-gender classification revealed in low-beta frequency EEG
Ranieri, G., Burr, D. C., Bell, J., & Morrone, M. C. (2025) · BMC Biology · doi:10.1186/s12915-025-02289-6 · Cited by 2
Spontaneous activity modeling in spiking neural systems with log-normal synaptic weight distribution
Nobukawa, S., Maruo, T., & Nishimura, H. (2014) · SICE Annual Conference (SICE) · doi:10.1109/sice.2014.6935186 · Cited by 2
Auditory recovery and speechreading in cochlear implanted deaf patients: A review
Barone, P., Strelnikov, K., & Déguine, O. (2010) · Hearing Balance and Communication · doi:10.3109/1651386x.2010.495243 · Cited by 2
Wennekers, T., Ay, N., & András, P. (2006) · Biosystems · doi:10.1016/j.biosystems.2006.04.017 · Cited by 2
A Statistical Model for In Vivo Neuronal Dynamics
Surace, S. C., & Pfister, J.-P. (2015) · PLoS ONE · doi:10.1371/journal.pone.0142435 · Cited by 2
Visual stimulation quenches global alpha range activity in awake primate V4: a case study
Deneux, T., Masquelier, T., Bermúdez, M. A., Masson, G. S., Deco, G., & Vanzetta, I. (2017) · Neurophotonics · doi:10.1117/1.nph.4.3.031222 · Cited by 2
Assessing the Impacts of Correlated Variability with Dissociated Timescales
Takahashi, T., Maruyama, Y., Ito, H., & Miura, K. (2019) · eNeuro · doi:10.1523/eneuro.0395-18.2019 · Cited by 2
Internally Organized Cell Assembly Trajectories
Buzsáki, G. (2019) · Oxford University Press eBooks · doi:10.1093/oso/9780190905385.003.0007 · Cited by 1
Spatial resolution of local field potential signals in macaque V4
Foroushani, A. N., Neupane, S., Pastor, P. D. H., Pack, C. C., & Sawan, M. (2020) · Journal of Neural Engineering · doi:10.1088/1741-2552/ab7321 · Cited by 3
Machine Perception in Unstructured and Unknown Environments
Scheding, S., Grover, R., & Durrant-Whyte, H. F. (2007) · Springer eBooks · doi:10.1007/978-3-540-75388-9_5 · Cited by 2
Consciousness and integrated energy differences in the brainPreprint
Pepperell, R. (2018) · PsyArXiv (OSF Preprints) · doi:10.31234/osf.io/fvjt2 · Cited by 2
Towards the Next Generation of Retinal Neuroprosthesis: Visual Computation with SpikesPreprint
Yu, Z., Liu, J. K., Jia, S., Zhang, Y., Zheng, Y., Tian, Y., & Huang, T. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2001.04064 · Cited by 2
Predicting perturbation effects from resting activity using functional causal flowPreprint
Nejatbakhsh, A., Fumarola, F., Esteki, S., Toyoizumi, T., Kiani, R., & Mazzucato, L. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.11.23.394916 · Cited by 2
Improved spatio-temporal measurements of visually-evoked fields using optically-pumped magnetometersPreprint
Gialopsou, A., Abel, C., James, T. M., Coussens, T., Bason, M. G., Puddy, R. K., Lorenzo, F. D., Rolfs, K., Voigt, J., Sander, T. H., et al. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.01.27.428396 · Cited by 2
High-Fidelity Coding with Correlated NeuronsPreprint
da Silveira, R. A., & Berry, M. J. (2013) · arXiv (Cornell University) · doi:10.48550/arxiv.1307.3591 · Cited by 2
Recurrent connectivity underlies lateralized temporal processing differences in Auditory CortexPreprint
Neophytou, D., Arribas, D. M., Levy, R. B., Park, M., & Oviedo, H. V. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.04.14.439872 · Cited by 2
Doherty, D. W., Jung, J., Durá-Bernal, S., & Lytton, W. W. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.01.13.632866 · Cited by 2
Buzsáki, G. (2019) · Oxford University Press eBooks · doi:10.1093/oso/9780190905385.003.0003 · Cited by 1
Niraula, S., Hauser, W. L., Rouse, A. G., & Subramanian, J. (2023) · Scientific Reports · doi:10.1038/s41598-023-47957-1 · Cited by 1
Khan, A. A., Naaz, F., Ahmad, N., Prusty, J. S., Kumar, A., Kalia, N. P., Khan, I. A., Rajput, V. S., & Shafi, S. (2025) · ChemistrySelect · doi:10.1002/slct.202500069 · Cited by 1
Multisensory integration in chaotic networks
Ponzi, A. P. D., & Suzuki, K. (2025) · Neural Networks · doi:10.1016/j.neunet.2025.107766 · Cited by 1
Revealing Stimulus-Dependent Dynamics Through Statistical Complexity
de Paula, E. V., Jungmann, R. M., Fontenele, A. J., Aguiar, L. A. A., Carelli, P. V., Matias, F. S., Copelli, M., & de Vasconcelos, N. A. P. (2026) · PRX Life · doi:10.1103/wndc-k654 · Cited by 1
Causation and Logic in Neuroscience
Buzsáki, G. (2019) · Oxford University Press eBooks · doi:10.1093/oso/9780190905385.003.0002 · Cited by 1
Orientation and Distance Dependence of Pairwise Correlation in Macaque V1
Hu, L., Hu, Q., & Chen, Y. (2020) · International Conference on Biomedical and Bioinformatics Engineering (ICBBE) · doi:10.1145/3444884.3444893 · Cited by 1
Buzsáki, G. (2019) · Oxford University Press eBooks · doi:10.1093/oso/9780190905385.003.0010 · Cited by 1
Intrinsic dynamic shapes responses to external stimulation in the human brain
Nentwich, M., Leszczyński, M., Schroeder, C. E., Bickel, S., & Parra, L. C. (2025) · eLife · doi:10.7554/elife.104996.3 · Cited by 2
Extraction of an activity pattern language from EEG data
András, P. (2006) · Neurocomputing · doi:10.1016/j.neucom.2005.12.099 · Cited by 1
Bridi, M., Hong, S. Z., Severín, D., Moreno, C., Contreras, A., & Kirkwood, A. (2024) · Journal of Neuroscience · doi:10.1523/jneurosci.0021-23.2024 · Cited by 1
Estimation of Spike Train Statistics in Spontaneously Active Biological Neural Networks
Tuckwell, H. C., & Feng, J. (2007) · Springer eBooks · doi:10.1007/978-1-84628-780-0_6 · Cited by 1
Apparitions of difference: essays on the vocation of reflexive anthropology
Hadder, R. N. (2007) · Texas ScholarWorks (Texas Digital Library) · Cited by 1
Correction: Coherence Potentials: Loss-Less, All-or-None Network Events in the Cortex
Thiagarajan, T. C., Lebedev, M., Nicolelis, M. A. L., & Plenz, D. (2010) · PLoS Biology · doi:10.1371/annotation/f6193dfe-a90c-4110-b0a0-22d81a87b921 · Cited by 1
Vision: In the Brain of the Beholder
Sengpiel, F. (2004) · Current Biology · doi:10.1016/j.cub.2004.11.021 · Cited by 1
Neural Ensembles in Taste Coding
Fontanini, A., Grossman, S. E., Revill, B. A., & Katz, D. B. (2008) · Elsevier eBooks · doi:10.1016/b978-012370880-9.00088-8 · Cited by 1
Analysis of the structure of time-frequency information in electromagnetic brain signals
Mäkinen, V. T. (2006) · Aaltodoc (Aalto University) · Cited by 1
Stimulus content shapes cortical response statisticsPreprint
Bányai, M., Lazăr, A., Klein, L., Klon-Lipok, J., Singer, W., & Orbán, G. (2017) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/238774 · Cited by 1
Bridi, M., Hong, S. Z., Severín, D., & Kirkwood, A. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.12.01.518760 · Cited by 1
Intrinsic dynamic shapes responses to external stimulation in the human brainPreprint
Nentwich, M., Leszczyński, M., Schroeder, C. E., Bickel, S., & Parra, L. C. (2025) · eLife · doi:10.7554/elife.104996 · Cited by 1
Intrinsic dynamic shapes responses to external stimulation in the human brainPreprint
Nentwich, M., Leszczyński, M., Schroeder, C. E., Bickel, S., & Parra, L. C. (2025) · eLife · doi:10.7554/elife.104996.2 · Cited by 1
The Nature of Qualia : A Neurophilosophical Analysis
de Sousa, C. E. B. (2009) · KOPS (University of Konstanz) · Cited by 1
Kada, H., Teramae, J.-N., & Tokuda, I. T. (2015) · Journal of Signal Processing · doi:10.2299/jsp.19.107
Neuron-Less Neural-Like Networks with Exponential Association Capacity at Tabula Rasa
Battaglia, D. A. (2009) · Lecture notes in computer science · doi:10.1007/978-3-642-02264-7_20
Characterizing the neural correlates of reasoningPreprint
Papo, D. (2015) · arXiv (Cornell University) · doi:10.48550/arxiv.1501.05174
The Language of Cortical Dynamics
András, P. (2006) · Lecture notes in computer science · doi:10.1007/11875741_24
Normative Visual Development: Innate Learning In The Early Visual System
Albert, M. V. (2010) · eCommons (Cornell University)
Stability and amplification in plastic cortical circuits
Hennequin, G. (2013) · Infoscience (Ecole Polytechnique Fédérale de Lausanne) · doi:10.5075/epfl-thesis-5585
Self-generated neural activity: models and perspective
Gros, C. (2009) · BMC Neuroscience · doi:10.1186/1471-2202-10-s1-p272
Brain Dynamical Networks: Contextualizing the Function of Primary Cortices
del Solar, J. W., & Rojas‐Líbano, D. (2013) · Journal of Neuroscience · doi:10.1523/jneurosci.1768-13.2013
About the oscillatory possibilities of the dynamical systemsPreprint
Herrero, R., Pi, F., Rius, J., & Orriols, G. T. (2009) · arXiv (Cornell University) · doi:10.48550/arxiv.0911.2157
An entropy-based investigation of underpinnings and impact of oscillations in a model of PD
Cruz, A. V. (2012) · UCL Discovery (University College London)
UNCERTAINTY AND DECISION-MAKING IN THE HUMAN BRAIN
Vilares, I. (2013) · Portuguese National Funding Agency for Science, Research and Technology (RCAAP Project by FCT)
Ayad, O. (2016) · uO Research (University of Ottawa) · doi:10.20381/ruor-5979
Nobukawa, S., Nishimura, H., & Maruo, T. (2016) · Elsevier eBooks · doi:10.1016/b978-0-12-804203-8.00004-3
Berkes, P., Lengyel, M., & Fiser, J. (2011)
Self-citationThe Impact of Cortical State on Neural Coding and Behavior
Beaman, C. B. (2016) · Digital Commons-TMC (Texas Medical Center)
Brain-inspired Stochastic Models and Implementations
Al-Shedivat, M. (2015) · King Abdullah University of Science and Technology Repository (King Abdullah University of Science and Technology) · doi:10.25781/kaust-5szyj
Prediction in Human Auditory CortexPreprint
Forseth, K. J., Hickok, G. S., Rollo, P. S., & Tandon, N. (2018) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/474718
Buzsáki, G. (2019) · Oxford University Press eBooks · doi:10.1093/oso/9780190905385.003.0011
Natural computation, much ado about nothing
Baudot, P. (2006) · HAL
Buzsáki, G. (2019) · Oxford University Press eBooks · doi:10.1093/oso/9780190905385.003.0012
Buzsáki, G. (2019) · Oxford University Press eBooks · doi:10.1093/oso/9780190905385.003.0005
Buzsáki, G. (2019) · Oxford University Press eBooks · doi:10.1093/oso/9780190905385.003.0013
Enhancing Brain Performance by Externalizing Thought
Buzsáki, G. (2019) · Oxford University Press eBooks · doi:10.1093/oso/9780190905385.003.0009
Internally Organized Activity During Offline Brain States
Buzsáki, G. (2019) · Oxford University Press eBooks · doi:10.1093/oso/9780190905385.003.0008
Buzsáki, G. (2019) · Oxford University Press eBooks · doi:10.1093/oso/9780190905385.003.0004
A Computer Vision System for Visual Perception in Unknown Environments
Wang, X., Wang, X., & Wilkes, D. M. (2019) · Springer eBooks · doi:10.1007/978-981-13-9217-7_3
Metadata
- Authors
- Fiser, J., Chiu, C., & Weliky, M.
- Affiliations
- University of Rochester (US)
- Corresponding author
- Weliky, Michael
- Venue
- Nature
- Published
- 2004-09
- Volume
- 431
- Issue
- 7008
- Pages
- 573-578
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- OpenAlex
- W2107313868
- Cited by
- 423
- References
- 27
- Citations by year
- 2026: 4 · 2025: 11 · 2024: 11 · 2023: 9 · 2022: 14 · 2021: 18 · 2020: 20 · 2019: 34 · 2018: 16 · 2017: 19 · 2016: 23 · 2015: 29 · 2014: 14 · 2013: 31 · 2012: 19
- FWCI
- 10.09
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Nature (publishedVersion)
- PubMed (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Funders
- National Science Foundation
- National Institutes of Health
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Visual perception and processing mechanisms
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neuroscience and Neuropharmacology Research
- Keywords
- spontaneous neuronal activity, primary visual cortex, sensory evoked potentials, natural images, cortical dynamics, visual development, ferrets, neural variability, visual cortex maturation
- MeSH terms
- Action Potentials, Aging, Animals, Evoked Potentials, Visual, Ferrets, Neurons, Photic Stimulation, Saccades, Visual Cortex, Visual Perception
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
