Dendritic discrimination of temporal input sequences in cortical neurons
Open accessAbstract
Discriminating Dendrites: Can dendrites read out spatiotemporal input sequences? Combining two-photon glutamate uncaging and two-photon calcium imaging, electrophysiology, and computational modeling, Branco et al. (p. 1671 , published online 12 August; see the Perspective by Destexhe ) discovered that single dendrites were indeed sensitive to both the direction and velocity of synaptic inputs. This direction- and velocity-sensitivity was measurable with only a few inputs and should thus be engaged frequently during normal brain function.
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?
Detailed studies of synaptic integration in dendrites of cortical pyramidal neurons suggested the primary role of the voltage-dependent current through synaptic NMDA receptors, including at subthreshold and suprathreshold NMDA-spike regimes.
“Detailed studies of synaptic integration in dendrites of cortical pyramidal neurons suggested the primary role of the voltage-dependent current through synaptic NMDA receptors, including at the subthreshold and suprathreshold (the NMDA-spike) regimes (Polsky, Mel, and Schiller 2004; Branco, Clark, and Häusser 2010).”
From Single cortical neurons as deep artificial neural networks (2021) · cites this paper as Branco, Clark, and Häusser 2010
The paper’s passage on direction and velocity sensitivity (section labeled Abstract; page unavailable) shows that synaptic NMDA receptors are important for voltage-dependent, supralinear integration in cortical pyramidal dendrites: blocking them abolished EPSP supralinearity. It does not establish the claimed distinction between subthreshold and suprathreshold NMDA-spike regimes; instead, it says the observed supralinearity developed gradually without a clear somatic threshold. (LLM, conf=0.88)
Experimental — accuracy not yet measuredThe DNN predicted peak somatic voltage for random activation sequences of the 9 input synapses with a correlation coefficient of 0.99, superior to the directionality index proposed by Branco et al. with correlation 0.86.
“Interestingly, our DNN acts as a much better predictor for the peak somatic voltage.”
From Single cortical neurons as deep artificial neural networks (2021) · cites this paper as Branco, Clark, and Häusser 2010
The supplied passage on ordered synaptic activation reports direction-sensitive somatic responses, supporting the connection to Branco et al.’s work. Our copy does not identify a directionality index or report a 0.86 correlation; the DNN’s 0.99 correlation is the citing authors’ own result, not a finding attributed to Branco et al. (LLM, conf=0.78)
Experimental — accuracy not yet measured
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
Matsuzaki, M., Ellis-Davies, G. C. R., Nemoto, T., Miyashita, Y., Iino, M., & Kasai, H. (2001) · Nature Neuroscience · doi:10.1038/nn736 · Cited by 1,563 · see citing works
Reverberation of recent visual experience in spontaneous cortical waves
Han, F., Caporale, N., & Dan, Y. (2008) · Neuron · doi:10.1016/j.neuron.2008.08.026 · Cited by 268 · see citing works
Flagged first, then by citations
Research works printed but not linked: 33
- [1]Meister M Lagnado L Baylor DA Science 1995 270 1207 7502047
- [2]deCharms RC Merzenich MM Nature 1996 381 610 8637597
- [3]Wehr M Laurent G Nature 1996 384 162 8906790
- [4]Johansson RS Birznieks I Nat Neurosci 2004 7 170 14730306
- [5]Thorpe S Delorme A Van Rullen R Neural Netw 2001 14 715 11665765
- [6]Gutig R Sompolinsky H Nat Neurosci 2006 9 420 16474393
- [7]Lazar A Pipa G Triesch J Front Comput Neurosci 2009 3 23 19893759 PMC2773171
- [8]Magee JC Nat Rev Neurosci 2000 1 181 11257906
- [9]Johnston D Narayanan R Trends Neurosci 2008 31 309 18471907
- [10]London M Hausser M Annu Rev Neurosci 2005 28 503 16033324
- [11]Schiller J Schiller Y Stuart G Sakmann B J Physiol 1997 505 Pt 3 605 9457639 PMC1160039
- [12]Golding NL Spruston N Neuron 1998 21 1189 9856473
- [13]Schiller J Major G Koester HJ Schiller Y Nature 2000 404 285 10749211
- [14]Williams SR Stuart GJ Trends Neurosci 2003 26 147 12591217
- [15]Losonczy A Magee JC Neuron 2006 50 291 16630839
- [16]Poirazi P Brannon T Mel BW Neuron 2003 37 989 12670427
- [17]Mel BW J Neurophysiol 1993 70 1086 8229160
- [18]Major G Polsky A Denk W Schiller J Tank DW J Neurophysiol 2008 99 2584 18337370
- [19]Rall W Neural Theory and Modeling Reiss R Stanford Univ. Press Stanford, CA 1964 73 97
- [20]Euler T Detwiler PB Denk W Nature 2002 418 845 12192402
- [21]Barlow HB Levick WR J Physiol 1965 178 477 5827909 PMC1357309
- [22]Borg-Graham LJ Grzywacz NM Single Neuron Computation McKenna T Davis J Zornetzer ZF Academic Press San Diego 1992 347 376
- [23]Matsuzaki M Nat Neurosci 2001 4 1086 11687814 PMC4229049
- [24]Larkum ME Nevian T Sandler M Polsky A Schiller J Science 2009 325 756 19661433
- [25]Steriade M Nunez A Amzica F J Neurosci 1993 13 3252 8340806 PMC6576541
- [26]Sanchez-Vives MV McCormick DA Nat Neurosci 2000 3 1027 11017176
- [27]Golding NL Staff NP Spruston N Nature 2002 418 326 12124625
- [28]Sjöström PJ Rancz EA Roth A Häusser M Physiol Rev 2008 88 769 18391179
- [29]Gordon U Polsky A Schiller J J Neurosci 2006 26 12717 PMC6674852 17151275
- [30]Losonczy A Makara JK Magee JC Nature 2008 452 436 18368112
- [31]Han F Caporale N Dan Y Neuron 2008 60 321 18957223 PMC3576032
- [32]Lee SH Blake R Heeger DJ Nat Neurosci 2005 8 22 15580269 PMC1215464
- [33]Ferezou I Bolea S Petersen CC Neuron 2006 50 617 16701211
Cited by
Sorted by citations
Hippocampal theta sequences reflect current goals
Wikenheiser, A. M., & Redish, A. D. (2015) · Nature Neuroscience · doi:10.1038/nn.3909 · Cited by 367 · see citing works
The single dendritic branch as a fundamental functional unit in the nervous system
Branco, T., & Häusser, M. (2010) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2010.07.009 · Cited by 355 · see citing works
Self-citationLocally synchronized synaptic inputs
Takahashi, N., Kitamura, K., Matsuo, N., Mayford, M., Kano, M., Matsuki, N., & Ikegaya, Y. (2012) · Science · doi:10.1126/science.1210362 · Cited by 352 · see citing works
Dense connectomic reconstruction in layer 4 of the somatosensory cortex
Motta, A., Berning, M., Boergens, K. M., Staffler, B., Beining, M., Loomba, S., Hennig, P., Wissler, H., & Helmstaedter, M. (2019) · Science · doi:10.1126/science.aay3134 · Cited by 333 · see citing works
Dendritic spines: from structure to in vivo function
Rochefort, N. L., & Konnerth, A. (2012) · The EMBO Reports · doi:10.1038/embor.2012.102 · Cited by 299 · see citing works
Synaptic amplification by dendritic spines enhances input cooperativity
Harnett, M. T., Makara, J. K., Spruston, N., Kath, W. L., & Magee, J. C. (2012) · Nature · doi:10.1038/nature11554 · Cited by 288 · see citing works
Structure and function of a neocortical synapse
Holler, S., Köstinger, G., Martin, K. A. C., Schuhknecht, G. F. P., & Stratford, K. J. (2021) · Nature · doi:10.1038/s41586-020-03134-2 · Cited by 249 · see citing works
Single cortical neurons as deep artificial neural networks
Beniaguev, D., Segev, I., & London, M. (2021) · Neuron · doi:10.1016/j.neuron.2021.07.002 · Cited by 254 · see citing works
Olfactory cortical neurons read out a relative time code in the olfactory bulb
Haddad, R., Lanjuin, A., Madisen, L., Zeng, H., Murthy, V. N., & Uchida, N. (2013) · Nature Neuroscience · doi:10.1038/nn.3407 · Cited by 216 · see citing works
A dendritic disinhibitory circuit mechanism for pathway-specific gating
Yang, G. R., Murray, J. D., & Wang, X.-J. (2016) · Nature Communications · doi:10.1038/ncomms12815 · Cited by 148 · see citing works
Harnett, M. T., Magee, J. C., & Williams, S. R. (2015) · The Journal of Neuroscience · doi:10.1523/jneurosci.2813-14.2015 · Cited by 148 · see citing works
Somato-dendritic synaptic plasticity and error-backpropagation in active dendrites
Schiess, M., Urbanczik, R., & Senn, W. (2016) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1004638 · Cited by 75 · see citing works
Functional Specialization of Neural Input Elements to the Drosophila ON Motion Detector
Ammer, G., Leonhardt, A., Bahl, A., Dickson, B. J., & Borst, A. (2015) · Current Biology · doi:10.1016/j.cub.2015.07.014 · Cited by 61 · see citing works
A Multi-scale View of the Emergent Complexity of Life: A Free-Energy Proposal
Hesp, C., Ramstead, M., Constant, A., Badcock, P., Kirchhoff, M., & Friston, K. (2019) · Springer Proceedings in Complexity · doi:10.1007/978-3-030-00075-2_7 · Cited by 63 · see citing works
Ripple band phase precession of place cell firing during replay
Bush, D., Ólafsdóttir, H. F., Barry, C., & Burgess, N. (2022) · Current Biology · doi:10.1016/j.cub.2021.10.033 · Cited by 20 · see citing works
- Authors
- Branco, T., Clark, B. A., & Häusser, M.
- Affiliations
- University College London (GB)
- Corresponding author
- Häusser, Michael
- Venue
- Science
- Published
- 2010-09-24
- Volume
- 329
- Issue
- 5999
- Pages
- 1671-1675
- ISSN
- 0036-8075 (ISSN-L)
- 1095-9203
- PMC
- PMC6354899
- OpenAlex
- W2088955805
- Cited by
- 497
- References
- 2
- Citations by year
- 2026: 29 · 2025: 27 · 2024: 41 · 2023: 33 · 2022: 20 · 2021: 40 · 2020: 23 · 2019: 48 · 2018: 19 · 2017: 22 · 2016: 28 · 2015: 24 · 2014: 24 · 2013: 48 · 2012: 43
- FWCI
- 15.23
- Type
- journal article
- Language
- en
- Open access
- green
- europepmc.org
- Locations
- Science (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- UCL Discovery (University College London) (submittedVersion)
- The HKU Scholars Hub (University of Hong Kong) (submittedVersion)
- Funders
- Wellcome Trust (068080)
- Topics
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neuroscience and Neuropharmacology Research
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
- Life Sciences › Neuroscience › Cognitive Neuroscience › Memory and Neural Mechanisms
- Keywords
- cortical pyramidal neurons, dendritic calcium signaling, NMDA receptor activation, glutamate uncaging, dendritic computation
- MeSH terms
- Action Potentials, Animals, Calcium, Dendrites, Models, Neurological, Somatosensory Cortex, Synapses, Time Factors, Visual Cortex, Receptors, N-Methyl-D-Aspartate, Rats, Sprague-Dawley, Pyramidal Cells, Excitatory Postsynaptic Potentials, Calcium Signaling, Dendritic Spines, Rats
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