title: Cortical oscillations arise from contextual interactions that regulate sparse coding.
abstract: Precise spike times carry information and are important for synaptic plasticity. Synchronizing oscillations such as gamma bursts could coordinate spike times, thus regulating information transmission in the cortex. Oscillations are driven by inhibitory neurons and are modulated by sensory stimuli and behavioral states. How their power and frequency are regulated is an open question. Using a model cortical circuit, we propose a regulatory mechanism that depends on the activity balance of monosynaptic and disynaptic pathways to inhibitory neurons: Monosynaptic input causes more powerful oscillations whereas disynaptic input increases the frequency of oscillations. The balance of stimulation to the two pathways modulates the overall distribution of spikes, with stronger disynaptic stimulation (e.g., preferred stimuli inside visual receptive fields) producing high firing rates and weak oscillations; in contrast, stronger monosynaptic stimulation (e.g., suppressive contextual stimulation from outside visual receptive fields) generates low firing rates and strong oscillatory regulation of spike timing, as observed in alert cortex processing complex natural stimuli. By accounting for otherwise paradoxical experimental findings, our results demonstrate how the frequency and power of oscillations, and hence spike times, can be modulated by both sensory input and behavioral context, with powerful oscillations signifying a cortical state under inhibitory control in which spikes are sparse and spike timing is precise.
authors.affiliation: Howard Hughes Medical Institute, Salk Institute for Biological Studies, La Jolla, CA 92037.
authors.forename: Monika P
authors.initials: MP
authors.lastname: Jadi
authors.forename: Terrence J
authors.initials: TJ
authors.lastname: Sejnowski
mesh_terms: D000200:Action Potentials; D005074:Evoked Potentials, Visual; D006801:Humans; D008959:Models, Neurological; D009415:Nerve Net / Q000502:physiology; D009474:Neurons / Q000502:physiology; D010775:Photic Stimulation; D009435:Synaptic Transmission; D014793:Visual Cortex / Q000502:physiology*
keywords: cerebral cortex; gamma oscillations; inhibitory interneurons; visual cortex model
references.citation: Neuron. 2009 Jun 25;62(6):850-61
references.pmid: 19555653
references.citation: Neuron. 2010 Sep 9;67(5):885-96
references.pmid: 20826318
references.citation: J Comput Neurosci. 2010 Dec;29(3):495-507
references.pmid: 19862612
references.citation: Proc Natl Acad Sci U S A. 1998 Feb 3;95(3):1259-64
references.pmid: 9448319
references.citation: PLoS Biol. 2013;11(2):e1001477
references.pmid: 23393427
references.citation: Neuron. 2010 Jan 14;65(1):107-21
references.pmid: 20152117
references.citation: Neuron. 2012 Jan 12;73(1):159-70
references.pmid: 22243754
references.citation: J Neurosci. 1983 May;3(5):1116-33
references.pmid: 6188819
references.citation: J Neurosci. 2004 Oct 13;24(41):9127-37
references.pmid: 15483131
references.citation: Nature. 1995 Feb 16;373(6515):612-5
references.pmid: 7854418
references.citation: Nat Neurosci. 2002 Aug;5(8):805-11
references.pmid: 12134152
references.citation: J Neurosci. 1996 Oct 15;16(20):6402-13
references.pmid: 8815919
references.citation: Nature. 2008 Apr 24;452(7190):956-60
references.pmid: 18344978
references.citation: J Neurosci. 2003 Aug 20;23(20):7690-701
references.pmid: 12930809
references.citation: PLoS One. 2011 May 06;6(5):e14804
references.pmid: 21573105
references.citation: Science. 1995 Jun 9;268(5216):1503-6
references.pmid: 7770778
references.citation: J Neurophysiol. 2003 Jul;90(1):415-30
references.pmid: 12611969
references.citation: Neuron. 2007 Jul 5;55(1):131-41
references.pmid: 17610822
references.citation: J Neurosci. 2013 Jan 2;33(1):17-25
references.pmid: 23283318
references.citation: Phys Rev E Stat Nonlin Soft Matter Phys. 2010 Nov;82(5 Pt 1):051903
references.pmid: 21230496
references.citation: Nature. 2004 Apr 22;428(6985):854-6
references.pmid: 15085147
references.citation: Neuron. 2013 Jan 23;77(2):361-75
references.pmid: 23352171
references.citation: Neuron. 2009 May 28;62(4):578-92
references.pmid: 19477158
references.citation: Nature. 2012 Oct 11;490(7419):226-31
references.pmid: 23060193
references.citation: Eur J Neurosci. 2008 Aug;28(3):447-59
references.pmid: 18702717
references.citation: Neuron. 2010 Apr 15;66(1):114-25
references.pmid: 20399733
references.citation: Neuron. 2013 Feb 20;77(4):762-74
references.pmid: 23439127
references.citation: Nature. 1996 Jun 6;381(6582):520-2
references.pmid: 8632824
references.citation: Nat Neurosci. 2004 Sep;7(9):982-91
references.pmid: 15322549
references.citation: Science. 1996 Dec 6;274(5293):1724-6
references.pmid: 8939866
references.citation: Nat Neurosci. 2001 Aug;4(8):819-25
references.pmid: 11477428
references.citation: Biophys J. 1972 Jan;12(1):1-24
references.pmid: 4332108
references.citation: Nat Rev Neurosci. 2011 Nov 23;13(1):51-62
references.pmid: 22108672
references.citation: Nature. 1989 Mar 23;338(6213):334-7
references.pmid: 2922061
references.citation: Nature. 2013 Jul 25;499(7459):476-80
references.pmid: 23803766
references.citation: Neural Comput. 2003 Mar;15(3):509-38
references.pmid: 12620157
references.citation: Science. 2001 Feb 23;291(5508):1560-3
references.pmid: 11222864
references.citation: Proc Natl Acad Sci U S A. 2014 May 6;111(18):6780-5
references.pmid: 24742427
references.citation: Nature. 2009 Jun 4;459(7247):663-7
references.pmid: 19396156
references.citation: Neuron. 2009 Sep 24;63(6):727-32
references.pmid: 19778503
references.citation: Nature. 2009 Jun 4;459(7247):698-702
references.pmid: 19396159