Unitary Events in Multiple Single-Neuron Spiking Activity: I. Detection and Significance

It has been proposed that cortical neurons organize dynamically into functional groups (cell assemblies) by the temporal structure of their joint spiking activity. Here, we describe a novel method to detect conspicuous patterns of coincident joint spike activity among simultaneously recorded single neurons. The statistical significance of these unitary events of coincident joint spike activity is evaluated by the joint-surprise. The method is tested and calibrated on the basis of simulated, stationary spike trains of independently firing neurons, into which coincident joint spike events were inserted under controlled conditions. The sensitivity and specificity of the method are investigated for their dependence on physiological parameters (firing rate, coincidence precision, coincidence pattern complexity) and temporal resolution of the analysis. In the companion article in this issue, we describe an extension of the method, designed to deal with nonstationary firing rates.

[1]  Sonja Grün,et al.  Analysis of Higher-Order Correlations in Multiple Parallel Processes , 2002, Neurocomputing.

[2]  M. Ahissar,et al.  Encoding of sound-source location and movement: activity of single neurons and interactions between adjacent neurons in the monkey auditory cortex. , 1992, Journal of neurophysiology.

[3]  Paul F M J Verschure,et al.  Existence of high-order correlations in cortical activity. , 2003, Physical review. E, Statistical, nonlinear, and soft matter physics.

[4]  Alessandro E. P. Villa,et al.  Evidence for spatiotemporal firing patterns within the auditory thalamus of the cat , 1990, Brain Research.

[5]  A. Aertsen,et al.  Spike synchronization and rate modulation differentially involved in motor cortical function. , 1997, Science.

[6]  Wolf Singer,et al.  Neuronal Synchrony: A Versatile Code for the Definition of Relations? , 1999, Neuron.

[7]  G. Palm Evidence, information, and surprise , 1981, Biological Cybernetics.

[8]  William L. Hays,et al.  Statistics, 5th ed. , 1994 .

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

[10]  J. Csicsvari,et al.  Replay and Time Compression of Recurring Spike Sequences in the Hippocampus , 1999, The Journal of Neuroscience.

[11]  Sonja Grün,et al.  Unitary joint events in multiple neuron spiking activity: detection, significance, and interpretation , 1996 .

[12]  A. Georgopoulos,et al.  Cognitive neurophysiology of the motor cortex. , 1993, Science.

[13]  W. Singer,et al.  Stimulus-specific neuronal oscillations in orientation columns of cat visual cortex. , 1989, Proceedings of the National Academy of Sciences of the United States of America.

[14]  Ronald Tetzlaff,et al.  Analysis of Multidimensional Neural Activity Via CNN-UM , 2003, Int. J. Neural Syst..

[15]  Ad Aertsen,et al.  From Synchrony to Harmony: Ideas on the Function of Neural Assemblies and on the Interpretation of Neural Synchrony , 1986 .

[16]  A. Aertsen,et al.  Neuronal assemblies , 1989, IEEE Transactions on Biomedical Engineering.

[17]  Sonja Grün,et al.  Dynamical changes and temporal precision of synchronized spiking activity in monkey motor cortex during movement preparation , 2000, Journal of Physiology-Paris.

[18]  W. Singer,et al.  The Role of Neuronal Synchronization in Response Selection: A Biologically Plausible Theory of Structured Representations in the Visual Cortex , 1996, Journal of Cognitive Neuroscience.

[19]  E. Vaadia,et al.  Spatiotemporal firing patterns in the frontal cortex of behaving monkeys. , 1993, Journal of neurophysiology.

[20]  Ad Aertsen,et al.  Stable propagation of synchronous spiking in cortical neural networks , 1999, Nature.

[21]  Shun-ichi Amari,et al.  Information-Geometric Measure for Neural Spikes , 2002, Neural Computation.

[22]  Horace Barlow,et al.  Single Cells versus Neuronal Assemblies , 1992 .

[23]  Kathryn B. Laskey,et al.  Neural Coding: Higher-Order Temporal Patterns in the Neurostatistics of Cell Assemblies , 2000, Neural Computation.

[24]  Sonja Grün,et al.  Significance of joint-spike events based on trial-shuffling by efficient combinatorial methods , 2003, Complex..

[25]  W. Singer Synchronization of cortical activity and its putative role in information processing and learning. , 1993, Annual review of physiology.

[26]  E Ahissar,et al.  Neural interactions in the frontal cortex of a behaving monkey: signs of dependence on stimulus context and behavioral state. , 1991, Journal fur Hirnforschung.

[27]  C R Legéndy Three principles of brain function and structure. , 1975, The International journal of neuroscience.

[28]  Carlos D. Brody,et al.  Disambiguating Different Covariation Types , 1999, Neural Computation.

[29]  M. Abeles Local Cortical Circuits: An Electrophysiological Study , 1982 .

[30]  M. Nicolelis,et al.  Sensorimotor encoding by synchronous neural ensemble activity at multiple levels of the somatosensory system. , 1995, Science.

[31]  R. Christopher deCharms,et al.  Primary cortical representation of sounds by the coordination of action-potential timing , 1996, Nature.

[32]  M. Abeles Quantification, smoothing, and confidence limits for single-units' histograms , 1982, Journal of Neuroscience Methods.

[33]  M. Abeles Role of the cortical neuron: integrator or coincidence detector? , 1982, Israel journal of medical sciences.

[34]  A. Riehle,et al.  Precise spike synchronization in monkey motor cortex involved in preparation for movement , 1999, Experimental Brain Research.

[35]  L. Paninski,et al.  Information about movement direction obtained from synchronous activity of motor cortical neurons. , 1998, Proceedings of the National Academy of Sciences of the United States of America.

[36]  Quentin Pauluis Temporal coding and cellular synchronisation in the superior colliculus , 1999 .

[37]  A. Aertsen,et al.  Response synchronization in the visual cortex , 1993, Current Opinion in Neurobiology.

[38]  A. Aertsen,et al.  Dynamics of neuronal interactions in monkey cortex in relation to behavioural events , 1995, Nature.

[39]  William Feller,et al.  An Introduction to Probability Theory and Its Applications , 1951 .

[40]  M. Laubach,et al.  Cortical ensemble activity increasingly predicts behaviour outcomes during learning of a motor task , 2022 .

[41]  Stefan Rotter,et al.  Statistical Significance of Coincident Spikes: Count-Based Versus Rate-Based Statistics , 2002, Neural Computation.

[42]  E E Fetz,et al.  Temporal Coding in Neural Populations? , 1997, Science.

[43]  Stefan Rotter,et al.  Single-trial estimation of neuronal firing rates: From single-neuron spike trains to population activity , 1999, Journal of Neuroscience Methods.

[44]  Christoph von der Malsburg,et al.  The Correlation Theory of Brain Function , 1994 .

[45]  Kathryn B. Laskey,et al.  Learning Exact Patterns of Quasi-synchronization among Spiking Neurons from Data on Multi-unit Recordings , 1996, NIPS.

[46]  A. Aertsen,et al.  On the significance of correlations among neuronal spike trains , 2004, Biological Cybernetics.

[47]  M K Habib,et al.  Dynamics of neuronal firing correlation: modulation of "effective connectivity". , 1989, Journal of neurophysiology.

[48]  G L Gerstein,et al.  Detecting spatiotemporal firing patterns among simultaneously recorded single neurons. , 1988, Journal of neurophysiology.

[49]  Moshe Abeles,et al.  Corticonics: Neural Circuits of Cerebral Cortex , 1991 .

[50]  Daniel Margoliash,et al.  Pattern Filtering for Detection of Neural Activity, with Examples from HVc Activity During Sleep in Zebra Finches , 2003, Neural Computation.

[51]  William H. Press,et al.  Numerical recipes in C , 2002 .

[52]  R N Lemon,et al.  Precise spatiotemporal repeating patterns in monkey primary and supplementary motor areas occur at chance levels. , 2000, Journal of neurophysiology.

[53]  Sonja Grün,et al.  Non-parametric significance estimation of joint-spike events by shuffling and resampling , 2003, Neurocomputing.

[54]  E. Niebur,et al.  Growth patterns in the developing brain detected by using continuum mechanical tensor maps , 2022 .

[55]  Arup Roy,et al.  Rate Limitations of Unitary Event Analysis , 2000, Neural Computation.

[56]  J. Donoghue,et al.  Oscillations in local field potentials of the primate motor cortex during voluntary movement. , 1993, Proceedings of the National Academy of Sciences of the United States of America.

[57]  W Singer,et al.  Visual feature integration and the temporal correlation hypothesis. , 1995, Annual review of neuroscience.

[58]  K. H. Britten,et al.  Neuronal correlates of a perceptual decision , 1989, Nature.

[59]  E. Fetz,et al.  Coherent 25- to 35-Hz oscillations in the sensorimotor cortex of awake behaving monkeys. , 1992, Proceedings of the National Academy of Sciences of the United States of America.

[60]  C. Legéndy,et al.  Bursts and recurrences of bursts in the spike trains of spontaneously active striate cortex neurons. , 1985, Journal of neurophysiology.

[61]  Stuart N. Baker,et al.  An Accurate Measure of the Instantaneous Discharge Probability, with Application to Unitary Joint-Event Analysis , 2000, Neural Computation.

[62]  Günther Palm,et al.  Detecting higher-order interactions among the spiking events in a group of neurons , 1995, Biological Cybernetics.

[63]  Thomas Wennekers,et al.  Spatial and Temporal Stochastic Interaction in Neuronal Assemblies , 2003 .

[64]  R. Eckhorn,et al.  Coherent oscillations: A mechanism of feature linking in the visual cortex? , 1988, Biological Cybernetics.

[65]  Sonja Grün,et al.  Detecting unitary events without discretization of time , 1999, Journal of Neuroscience Methods.

[66]  William Feller,et al.  An Introduction to Probability Theory and Its Applications , 1967 .

[67]  W. Singer,et al.  Neuronal assemblies: necessity, signature and detectability , 1997, Trends in Cognitive Sciences.

[68]  D. Hubel,et al.  Ferrier lecture - Functional architecture of macaque monkey visual cortex , 1977, Proceedings of the Royal Society of London. Series B. Biological Sciences.

[69]  J J Eggermont,et al.  Neural interaction in cat primary auditory cortex II. Effects of sound stimulation. , 1994, Journal of neurophysiology.

[70]  M. Abeles The Quantification and Graphic Display of Correlations Among Three Spike Trains , 1983, IEEE Transactions on Biomedical Engineering.

[71]  Daniel Margoliash,et al.  Detection of spike patterns using pattern filtering, with applications to sleep replay in birdsong , 2003, Neurocomputing.

[72]  G L Gerstein,et al.  Favored patterns in spike trains. II. Application. , 1983, Journal of neurophysiology.

[73]  W. Singer,et al.  Temporal coding in the visual cortex: new vistas on integration in the nervous system , 1992, Trends in Neurosciences.

[74]  Carlos D. Brody,et al.  Correlations Without Synchrony , 1999, Neural Computation.

[75]  J. Wallman,et al.  Directional asymmetries of optokinetic nystagmus: developmental changes and relation to the accessory optic system and to the vestibular system , 1985, The Journal of neuroscience : the official journal of the Society for Neuroscience.

[76]  W. Newsome,et al.  The Variable Discharge of Cortical Neurons: Implications for Connectivity, Computation, and Information Coding , 1998, The Journal of Neuroscience.

[77]  William R. Softky,et al.  The highly irregular firing of cortical cells is inconsistent with temporal integration of random EPSPs , 1993, The Journal of neuroscience : the official journal of the Society for Neuroscience.

[78]  E. Vaadia,et al.  Spatiotemporal structure of cortical activity: properties and behavioral relevance. , 1998, Journal of neurophysiology.

[79]  William H. Press,et al.  Numerical Recipes in C, 2nd Edition , 1992 .

[80]  Akira Date,et al.  On the temporal resolution of neural activity , 1998 .

[81]  Yoshio Sakurai,et al.  Population coding by cell assemblies—what it really is in the brain , 1996, Neuroscience Research.