Influence of ionic conductances on spike timing reliability of cortical neurons for suprathreshold rhythmic inputs.

Spike timing reliability of neuronal responses depends on the frequency content of the input. We investigate how intrinsic properties of cortical neurons affect spike timing reliability in response to rhythmic inputs of suprathreshold mean. Analyzing reliability of conductance-based cortical model neurons on the basis of a correlation measure, we show two aspects of how ionic conductances influence spike timing reliability. First, they set the preferred frequency for spike timing reliability, which in accordance with the resonance effect of spike timing reliability is well approximated by the firing rate of a neuron in response to the DC component in the input. We demonstrate that a slow potassium current can modulate the spike timing frequency preference over a broad range of frequencies. This result is confirmed experimentally by dynamic-clamp recordings from rat prefrontal cortical neurons in vitro. Second, we provide evidence that ionic conductances also influence spike timing beyond changes in preferred frequency. Cells with the same DC firing rate exhibit more reliable spike timing at the preferred frequency and its harmonics if the slow potassium current is larger and its kinetics are faster, whereas a larger persistent sodium current impairs reliability. We predict that potassium channels are an efficient target for neuromodulators that can tune spike timing reliability to a given rhythmic input.

[1]  J. D. Hunter,et al.  Amplitude and frequency dependence of spike timing: implications for dynamic regulation. , 2003, Journal of neurophysiology.

[2]  P. Bressloff,et al.  Mode locking and Arnold tongues in integrate-and-fire neural oscillators. , 1999, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.

[3]  T. Sejnowski,et al.  A model of spindle rhythmicity in the isolated thalamic reticular nucleus. , 1994, Journal of neurophysiology.

[4]  Y. Amitai,et al.  Propagating neuronal discharges in neocortical slices: computational and experimental study. , 1997, Journal of neurophysiology.

[5]  Paul H. E. Tiesinga,et al.  A New Correlation-Based Measure of Spike Timing Reliability , 2002, Neurocomputing.

[6]  Boris S. Gutkin,et al.  Spike Generating Dynamics and the Conditions for Spike-Time Precision in Cortical Neurons , 2003, Journal of Computational Neuroscience.

[7]  B. Knight The Relationship between the Firing Rate of a Single Neuron and the Level of Activity in a Population of Neurons , 1972, The Journal of general physiology.

[8]  Paul H. E. Tiesinga,et al.  Attractor Reliability Reveals Deterministic Structure in Neuronal Spike Trains , 2002, Neural Computation.

[9]  B. Connors,et al.  Intrinsic firing patterns of diverse neocortical neurons , 1990, Trends in Neurosciences.

[10]  R. Reid,et al.  Precise Firing Events Are Conserved across Neurons , 2002, The Journal of Neuroscience.

[11]  E. Marder,et al.  Dynamic clamp: computer-generated conductances in real neurons. , 1993, Journal of neurophysiology.

[12]  J M Bower,et al.  Synaptic Control of Spiking in Cerebellar Purkinje Cells: Dynamic Current Clamp Based on Model Conductances , 1999, The Journal of Neuroscience.

[13]  O. Prospero-Garcia,et al.  Reliability of Spike Timing in Neocortical Neurons , 1995 .

[14]  Rajesh P. N. Rao,et al.  Frequency dependence of spike timing reliability in cortical pyramidal cells and interneurons. , 2001, Journal of neurophysiology.

[15]  Maria V. Sanchez-Vives,et al.  Influence of low and high frequency inputs on spike timing in visual cortical neurons. , 1997, Cerebral cortex.

[16]  Idan Segev,et al.  Subthreshold oscillations and resonant frequency in guinea‐pig cortical neurons: physiology and modelling. , 1995, The Journal of physiology.

[17]  E Marder,et al.  Memory from the dynamics of intrinsic membrane currents. , 1996, Proceedings of the National Academy of Sciences of the United States of America.

[18]  E. Marder,et al.  Activity-dependent changes in the intrinsic properties of cultured neurons. , 1994, Science.

[19]  R. Purple,et al.  A neuronal model for the discharge patterns produced by cyclic inputs. , 1970, The Bulletin of mathematical biophysics.

[20]  P H E Tiesinga,et al.  Precision and reliability of periodically and quasiperiodically driven integrate-and-fire neurons. , 2002, Physical review. E, Statistical, nonlinear, and soft matter physics.

[21]  B. Gähwiler,et al.  L-Type Ca2+ channels mediate the slow Ca2+-dependent afterhyperpolarization current in rat CA3 pyramidal cells in vitro. , 1998, Journal of neurophysiology.

[22]  J. White,et al.  Frequency selectivity of layer II stellate cells in the medial entorhinal cortex. , 2002, Journal of neurophysiology.

[23]  J. Rinzel,et al.  INTEGRATE-AND-FIRE MODELS OF NERVE MEMBRANE RESPONSE TO OSCILLATORY INPUT. , 1981 .

[24]  Emmanuel Guigon,et al.  Reliability of Spike Timing Is a General Property of Spiking Model Neurons , 2003, Neural Computation.

[25]  T J Sejnowski,et al.  Ionic mechanisms for intrinsic slow oscillations in thalamic relay neurons. , 1993, Biophysical journal.

[26]  E. Marder,et al.  Global Structure, Robustness, and Modulation of Neuronal Models , 2001, The Journal of Neuroscience.

[27]  Y. Nakazato,et al.  Ouabain distinguishes between nicotinic and muscarinic receptor‐mediated catecholamine secretions in perfused adrenal glands of cat , 1989, British journal of pharmacology.

[28]  R. Jensen Synchronization of randomly driven nonlinear oscillators , 1998 .

[29]  Comparisons of neocortex and hippocampus , 1990, Trends in Neurosciences.

[30]  P. Alstrøm,et al.  Characterization of reliability of spike timing in spinal interneurons during oscillating inputs. , 2001, Journal of neurophysiology.

[31]  M. R. Mehta,et al.  Role of experience and oscillations in transforming a rate code into a temporal code , 2002, Nature.

[32]  Jeffrey C Magee,et al.  A prominent role for intrinsic neuronal properties in temporal coding , 2003, Trends in Neurosciences.

[33]  Germán Mato,et al.  Electrical Synapses and Synchrony: The Role of Intrinsic Currents , 2003, The Journal of Neuroscience.

[34]  J. D. Hunter,et al.  Resonance effect for neural spike time reliability. , 1998, Journal of neurophysiology.

[35]  S. Hughes,et al.  Dynamic clamp study of Ih modulation of burst firing and δ oscillations in thalamocortical neurons in vitro , 1998, Neuroscience.

[36]  M. Hasselmo,et al.  Modulation of associative memory function in a biophysical simulation of rat piriform cortex. , 1994, Journal of neurophysiology.

[37]  D. McCormick,et al.  Comparative electrophysiology of pyramidal and sparsely spiny stellate neurons of the neocortex. , 1985, Journal of neurophysiology.

[38]  J. Storm Potassium currents in hippocampal pyramidal cells. , 1990, Progress in brain research.

[39]  Bertil Hille Ion Channels of Excitable Membranes , Third Edition , 2022 .

[40]  T. Sejnowski,et al.  The Monetary Transmission Mechanism in the United Kingdom: Pass-Through and Policy Rules. manuscript , 1996 .

[41]  Bruce R. Johnson,et al.  Activity-Independent Homeostasis in Rhythmically Active Neurons , 2003, Neuron.

[42]  Richard Miles,et al.  EPSP Amplification and the Precision of Spike Timing in Hippocampal Neurons , 2000, Neuron.