Spike train encoding by regular-spiking cells of the visual cortex. 1996

M Carandini, and F Mechler, and C S Leonard, and J A Movshon
Center for Neural Science, New York University, New York 10003, USA.

1. To study the encoding of input currents into output spike trains by regular-spiking cells, we recorded intracellularly from slices of the guinea pig visual cortex while injecting step, sinusoidal, and broadband noise currents. 2. When measured with sinusoidal currents, the frequency tuning of the spike responses was markedly band-pass. The preferred frequency was between 8 and 30 Hz, and grew with stimulus amplitude and mean intensity. 3. Stimulation with broadband noise currents dramatically enhanced the gain of the spike responses at low and high frequencies, yielding an essentially flat frequency tuning between 0.1 and 130 Hz. 4. The averaged spike responses to sinusoidal currents exhibited two nonlinearities: rectification and spike synchronization. By contrast, no nonlinearity was evident in the averaged responses to broadband noise stimuli. 5. These properties of the spike responses were not present in the membrane potential responses. The latter were roughly linear, and their frequency tuning was low-pass and well fit by a single-compartment passive model of the cell membrane composed of a resistance and a capacitance in parallel (RC circuit). 6. To account for the spike responses, we used a "sandwich model" consisting of a low-pass linear filter (the RC circuit), a rectification nonlinearity, and a high-pass linear filter. The model is described by six parameters and predicts analog firing rates rather than discrete spikes. It provided satisfactory fits to the firing rate responses to steps, sinusoids, and broadband noise currents. 7. The properties of spike encoding are consistent with temporal nonlinearities of the visual responses in V1, such as the dependence of response frequency tuning and latency on stimulus contrast and bandwidth. We speculate that one of the roles of the high-frequency membrane potential fluctuations observed in vivo could be to amplify and linearize the responses to lower, stimulus-related frequencies.

UI MeSH Term Description Entries
D008564 Membrane Potentials The voltage differences across a membrane. For cellular membranes they are computed by subtracting the voltage measured outside the membrane from the voltage measured inside the membrane. They result from differences of inside versus outside concentration of potassium, sodium, chloride, and other ions across cells' or ORGANELLES membranes. For excitable cells, the resting membrane potentials range between -30 and -100 millivolts. Physical, chemical, or electrical stimuli can make a membrane potential more negative (hyperpolarization), or less negative (depolarization). Resting Potentials,Transmembrane Potentials,Delta Psi,Resting Membrane Potential,Transmembrane Electrical Potential Difference,Transmembrane Potential Difference,Difference, Transmembrane Potential,Differences, Transmembrane Potential,Membrane Potential,Membrane Potential, Resting,Membrane Potentials, Resting,Potential Difference, Transmembrane,Potential Differences, Transmembrane,Potential, Membrane,Potential, Resting,Potential, Transmembrane,Potentials, Membrane,Potentials, Resting,Potentials, Transmembrane,Resting Membrane Potentials,Resting Potential,Transmembrane Potential,Transmembrane Potential Differences
D008954 Models, Biological Theoretical representations that simulate the behavior or activity of biological processes or diseases. For disease models in living animals, DISEASE MODELS, ANIMAL is available. Biological models include the use of mathematical equations, computers, and other electronic equipment. Biological Model,Biological Models,Model, Biological,Models, Biologic,Biologic Model,Biologic Models,Model, Biologic
D009622 Noise Any sound which is unwanted or interferes with HEARING other sounds. Noise Pollution,Noises,Pollution, Noise
D010775 Photic Stimulation Investigative technique commonly used during ELECTROENCEPHALOGRAPHY in which a series of bright light flashes or visual patterns are used to elicit brain activity. Stimulation, Photic,Visual Stimulation,Photic Stimulations,Stimulation, Visual,Stimulations, Photic,Stimulations, Visual,Visual Stimulations
D006168 Guinea Pigs A common name used for the genus Cavia. The most common species is Cavia porcellus which is the domesticated guinea pig used for pets and biomedical research. Cavia,Cavia porcellus,Guinea Pig,Pig, Guinea,Pigs, Guinea
D000818 Animals Unicellular or multicellular, heterotrophic organisms, that have sensation and the power of voluntary movement. Under the older five kingdom paradigm, Animalia was one of the kingdoms. Under the modern three domain model, Animalia represents one of the many groups in the domain EUKARYOTA. Animal,Metazoa,Animalia
D014793 Visual Cortex Area of the OCCIPITAL LOBE concerned with the processing of visual information relayed via VISUAL PATHWAYS. Area V2,Area V3,Area V4,Area V5,Associative Visual Cortex,Brodmann Area 18,Brodmann Area 19,Brodmann's Area 18,Brodmann's Area 19,Cortical Area V2,Cortical Area V3,Cortical Area V4,Cortical Area V5,Secondary Visual Cortex,Visual Cortex Secondary,Visual Cortex V2,Visual Cortex V3,Visual Cortex V3, V4, V5,Visual Cortex V4,Visual Cortex V5,Visual Cortex, Associative,Visual Motion Area,Extrastriate Cortex,Area 18, Brodmann,Area 18, Brodmann's,Area 19, Brodmann,Area 19, Brodmann's,Area V2, Cortical,Area V3, Cortical,Area V4, Cortical,Area V5, Cortical,Area, Visual Motion,Associative Visual Cortices,Brodmanns Area 18,Brodmanns Area 19,Cortex Secondary, Visual,Cortex V2, Visual,Cortex V3, Visual,Cortex, Associative Visual,Cortex, Extrastriate,Cortex, Secondary Visual,Cortex, Visual,Cortical Area V3s,Extrastriate Cortices,Secondary Visual Cortices,V3, Cortical Area,V3, Visual Cortex,V4, Area,V4, Cortical Area,V5, Area,V5, Cortical Area,V5, Visual Cortex,Visual Cortex Secondaries,Visual Cortex, Secondary,Visual Motion Areas

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