Correlated connectivity and the distribution of firing rates in the neocortex. Koulakov, A., A., Hromádka, T., & Zador, A., M. The Journal of neuroscience : the official journal of the Society for Neuroscience, 29(12):3685-3694, 3, 2009.
Paper
Website abstract bibtex Two recent experimental observations pose a challenge to many cortical models. First, the activity in the auditory cortex is sparse, and firing rates can be described by a lognormal distribution. Second, the distribution of nonzero synaptic strengths between nearby cortical neurons can also be described by a lognormal distribution. Here we use a simple model of cortical activity to reconcile these observations. The model makes the experimentally testable prediction that synaptic efficacies onto a given cortical neuron are statistically correlated, i.e., it predicts that some neurons receive stronger synapses than other neurons. We propose a simple Hebb-like learning rule that gives rise to such correlations and yields both lognormal firing rates and synaptic efficacies. Our results represent a first step toward reconciling sparse activity and sparse connectivity in cortical networks.
@article{
title = {Correlated connectivity and the distribution of firing rates in the neocortex.},
type = {article},
year = {2009},
identifiers = {[object Object]},
keywords = {Action Potentials,Animals,Models,Neocortex,Neocortex: physiology,Nerve Net,Nerve Net: physiology,Neurological,Neurons,Neurons: physiology,Synapses,Synapses: physiology},
pages = {3685-3694},
volume = {29},
websites = {http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=2784918&tool=pmcentrez&rendertype=abstract,http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=2784918&tool=pmcentrez&rendertype=abstract},
month = {3},
day = {25},
id = {b3de7d5f-018c-3310-a00c-78414187215f},
created = {2016-10-18T09:36:50.000Z},
accessed = {2015-04-07},
file_attached = {true},
profile_id = {a284bdcb-0ee1-3dea-9317-7f47c0e9b4ec},
group_id = {9e2da818-7db2-32de-9369-b0c1c4c7aea1},
last_modified = {2016-10-18T09:36:50.000Z},
read = {false},
starred = {false},
authored = {false},
confirmed = {true},
hidden = {false},
citation_key = {Koulakov2009},
source_type = {article},
abstract = {Two recent experimental observations pose a challenge to many cortical models. First, the activity in the auditory cortex is sparse, and firing rates can be described by a lognormal distribution. Second, the distribution of nonzero synaptic strengths between nearby cortical neurons can also be described by a lognormal distribution. Here we use a simple model of cortical activity to reconcile these observations. The model makes the experimentally testable prediction that synaptic efficacies onto a given cortical neuron are statistically correlated, i.e., it predicts that some neurons receive stronger synapses than other neurons. We propose a simple Hebb-like learning rule that gives rise to such correlations and yields both lognormal firing rates and synaptic efficacies. Our results represent a first step toward reconciling sparse activity and sparse connectivity in cortical networks.},
bibtype = {article},
author = {Koulakov, Alexei A and Hromádka, Tomás and Zador, Anthony M},
journal = {The Journal of neuroscience : the official journal of the Society for Neuroscience},
number = {12}
}
Downloads: 0
{"_id":"nRG5mCeJf9gr3n4Zd","bibbaseid":"koulakov-hromdka-zador-correlatedconnectivityandthedistributionoffiringratesintheneocortex-2009","downloads":0,"creationDate":"2016-10-18T09:55:23.142Z","title":"Correlated connectivity and the distribution of firing rates in the neocortex.","author_short":["Koulakov, A., A.","Hromádka, T.","Zador, A., M."],"year":2009,"bibtype":"article","biburl":null,"bibdata":{"title":"Correlated connectivity and the distribution of firing rates in the neocortex.","type":"article","year":"2009","identifiers":"[object Object]","keywords":"Action Potentials,Animals,Models,Neocortex,Neocortex: physiology,Nerve Net,Nerve Net: physiology,Neurological,Neurons,Neurons: physiology,Synapses,Synapses: physiology","pages":"3685-3694","volume":"29","websites":"http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=2784918&tool=pmcentrez&rendertype=abstract,http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=2784918&tool=pmcentrez&rendertype=abstract","month":"3","day":"25","id":"b3de7d5f-018c-3310-a00c-78414187215f","created":"2016-10-18T09:36:50.000Z","accessed":"2015-04-07","file_attached":"true","profile_id":"a284bdcb-0ee1-3dea-9317-7f47c0e9b4ec","group_id":"9e2da818-7db2-32de-9369-b0c1c4c7aea1","last_modified":"2016-10-18T09:36:50.000Z","read":false,"starred":false,"authored":false,"confirmed":"true","hidden":false,"citation_key":"Koulakov2009","source_type":"article","abstract":"Two recent experimental observations pose a challenge to many cortical models. First, the activity in the auditory cortex is sparse, and firing rates can be described by a lognormal distribution. Second, the distribution of nonzero synaptic strengths between nearby cortical neurons can also be described by a lognormal distribution. Here we use a simple model of cortical activity to reconcile these observations. The model makes the experimentally testable prediction that synaptic efficacies onto a given cortical neuron are statistically correlated, i.e., it predicts that some neurons receive stronger synapses than other neurons. We propose a simple Hebb-like learning rule that gives rise to such correlations and yields both lognormal firing rates and synaptic efficacies. Our results represent a first step toward reconciling sparse activity and sparse connectivity in cortical networks.","bibtype":"article","author":"Koulakov, Alexei A and Hromádka, Tomás and Zador, Anthony M","journal":"The Journal of neuroscience : the official journal of the Society for Neuroscience","number":"12","bibtex":"@article{\n title = {Correlated connectivity and the distribution of firing rates in the neocortex.},\n type = {article},\n year = {2009},\n identifiers = {[object Object]},\n keywords = {Action Potentials,Animals,Models,Neocortex,Neocortex: physiology,Nerve Net,Nerve Net: physiology,Neurological,Neurons,Neurons: physiology,Synapses,Synapses: physiology},\n pages = {3685-3694},\n volume = {29},\n websites = {http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=2784918&tool=pmcentrez&rendertype=abstract,http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=2784918&tool=pmcentrez&rendertype=abstract},\n month = {3},\n day = {25},\n id = {b3de7d5f-018c-3310-a00c-78414187215f},\n created = {2016-10-18T09:36:50.000Z},\n accessed = {2015-04-07},\n file_attached = {true},\n profile_id = {a284bdcb-0ee1-3dea-9317-7f47c0e9b4ec},\n group_id = {9e2da818-7db2-32de-9369-b0c1c4c7aea1},\n last_modified = {2016-10-18T09:36:50.000Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {Koulakov2009},\n source_type = {article},\n abstract = {Two recent experimental observations pose a challenge to many cortical models. First, the activity in the auditory cortex is sparse, and firing rates can be described by a lognormal distribution. Second, the distribution of nonzero synaptic strengths between nearby cortical neurons can also be described by a lognormal distribution. Here we use a simple model of cortical activity to reconcile these observations. The model makes the experimentally testable prediction that synaptic efficacies onto a given cortical neuron are statistically correlated, i.e., it predicts that some neurons receive stronger synapses than other neurons. We propose a simple Hebb-like learning rule that gives rise to such correlations and yields both lognormal firing rates and synaptic efficacies. Our results represent a first step toward reconciling sparse activity and sparse connectivity in cortical networks.},\n bibtype = {article},\n author = {Koulakov, Alexei A and Hromádka, Tomás and Zador, Anthony M},\n journal = {The Journal of neuroscience : the official journal of the Society for Neuroscience},\n number = {12}\n}","author_short":["Koulakov, A., A.","Hromádka, T.","Zador, A., M."],"urls":{"Paper":"http://bibbase.org/service/mendeley/a284bdcb-0ee1-3dea-9317-7f47c0e9b4ec/file/7fd43998-ba2e-be6f-3338-2b8a9a932a2e/2009-Correlated_connectivity_and_the_distribution_of_firing_rates_in_the_neocortex..pdf.pdf","Website":"http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=2784918&tool=pmcentrez&rendertype=abstract,http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=2784918&tool=pmcentrez&rendertype=abstract"},"bibbaseid":"koulakov-hromdka-zador-correlatedconnectivityandthedistributionoffiringratesintheneocortex-2009","role":"author","keyword":["Action Potentials","Animals","Models","Neocortex","Neocortex: physiology","Nerve Net","Nerve Net: physiology","Neurological","Neurons","Neurons: physiology","Synapses","Synapses: physiology"],"downloads":0},"search_terms":["correlated","connectivity","distribution","firing","rates","neocortex","koulakov","hromádka","zador"],"keywords":["action potentials","animals","models","neocortex","neocortex: physiology","nerve net","nerve net: physiology","neurological","neurons","neurons: physiology","synapses","synapses: physiology"],"authorIDs":[]}