Regional and laminar differences in in vivo firing patterns of primate cortical neurons.

The firing rates of cortical neurons change in time; yet, some aspects of their in vivo firing characteristics remain unchanged and are specific to individual neurons. A recent study has shown that neurons in the monkey medial motor areas can be grouped into 2 firing types, "likely random" and "quasi-regular," according to a measure of local variation of interspike intervals. In the present study, we extended this analysis to area TE of the inferior temporal cortex and addressed whether this classification applies generally to different cortical areas and whether different types of neurons show different laminar distribution. We found that area TE did consist of 2 groups of neurons with different firing characteristics, one similar to the "likely random" type in the medial motor cortical areas, and the other exhibiting a "clumpy-bursty" firing pattern unique to TE. The quasi-regular type was rarely observed in area TE. The likely random firing type of neuron was more frequently found in layers V-VI than in layers II-III, whereas the opposite was true for the clumpy-bursty firing type. These results show that neocortical areas consist of heterogeneous neurons that differ from one area to another in their basic firing characteristics. Moreover, we show that spike trains obtained from a single cortical neuron can provide a clue that helps to identify its layer localization.

[1]  D. Cox,et al.  The statistical analysis of series of events , 1966 .

[2]  J. Hyvärinen,et al.  Cortical neuronal mechanisms in flutter-vibration studied in unanesthetized monkeys. Neuronal periodicity and frequency discrimination. , 1969, Journal of neurophysiology.

[3]  W. Chambers,et al.  Reflexes involving triceps surae from the ankle joint of the cat. , 1973, Experimental neurology.

[4]  J. B. Ranck,et al.  Studies on single neurons in dorsal hippocampal formation and septum in unrestrained rats. I. Behavioral correlates and firing repertoires. , 1973, Experimental neurology.

[5]  D. Rubin,et al.  Maximum likelihood from incomplete data via the EM - algorithm plus discussions on the paper , 1977 .

[6]  D. Simons Response properties of vibrissa units in rat SI somatosensory neocortex. , 1978, Journal of neurophysiology.

[7]  G. Buzsáki,et al.  Cellular bases of hippocampal EEG in the behaving rat , 1983, Brain Research Reviews.

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

[9]  E. G. Jones,et al.  Numbers and proportions of GABA-immunoreactive neurons in different areas of monkey cerebral cortex , 1987, The Journal of neuroscience : the official journal of the Society for Neuroscience.

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

[11]  J. B. Levitt,et al.  Comparison of intrinsic connectivity in different areas of macaque monkey cerebral cortex. , 1993, Cerebral cortex.

[12]  R. Malach,et al.  Cortical hierarchy reflected in the organization of intrinsic connections in macaque monkey visual cortex , 1993, The Journal of comparative neurology.

[13]  Y. Kawaguchi Physiological subgroups of nonpyramidal cells with specific morphological characteristics in layer II/III of rat frontal cortex , 1995, The Journal of neuroscience : the official journal of the Society for Neuroscience.

[14]  D. Snodderly,et al.  Organization of striate cortex of alert, trained monkeys (Macaca fascicularis): ongoing activity, stimulus selectivity, and widths of receptive field activating regions. , 1995, Journal of neurophysiology.

[15]  Barry W. Connors,et al.  Intrinsic Physiology and Morphology of Single Neurons in Neocortex , 1995 .

[16]  I Fujita,et al.  Intrinsic connections in the macaque inferior temporal cortex , 1996, The Journal of comparative neurology.

[17]  C. Gray,et al.  Chattering Cells: Superficial Pyramidal Neurons Contributing to the Generation of Synchronous Oscillations in the Visual Cortex , 1996, Science.

[18]  William R. Softky,et al.  Comparison of discharge variability in vitro and in vivo in cat visual cortex neurons. , 1996, Journal of neurophysiology.

[19]  J. Deuchars,et al.  Synaptic interactions in neocortical local circuits: dual intracellular recordings in vitro. , 1997, Cerebral cortex.

[20]  J. Csicsvari,et al.  Reliability and State Dependence of Pyramidal Cell–Interneuron Synapses in the Hippocampus an Ensemble Approach in the Behaving Rat , 1998, Neuron.

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

[22]  Yutaka Sakai,et al.  Temporally correlated inputs to leaky integrate-and-fire models can reproduce spiking statistics of cortical neurons , 1999, Neural Networks.

[23]  Yutaka Sakai,et al.  The Ornstein-Uhlenbeck Process Does Not Reproduce Spiking Statistics of Neurons in Prefrontal Cortex , 1999, Neural Computation.

[24]  J. Okada,et al.  Multineuronal spike classification based on multisite electrode recording, whole-waveform analysis, and hierarchical clustering , 1999, IEEE Transactions on Biomedical Engineering.

[25]  S Shinomoto,et al.  Modeling spiking behavior of neurons with time-dependent Poisson processes. , 2001, Physical review. E, Statistical, nonlinear, and soft matter physics.

[26]  I. Fujita The inferior temporal cortex: Architecture, computation, and representation , 2002, Journal of neurocytology.

[27]  Edward M Callaway,et al.  Cell type specificity of local cortical connections , 2002, Journal of neurocytology.

[28]  A. Thomson,et al.  Selectivity in the inter-laminar connections made by neocortical neurones , 2002, Journal of neurocytology.

[29]  J. Fuster Frontal lobe and cognitive development , 2002, Journal of neurocytology.

[30]  R. Yuste,et al.  Cortical area and species differences in dendritic spine morphology , 2002, Journal of neurocytology.

[31]  P. Goldman-Rakic,et al.  A role for inhibition in shaping the temporal flow of information in prefrontal cortex , 2002, Nature Neuroscience.

[32]  Maria V. Sanchez-Vives,et al.  Electrophysiological classes of cat primary visual cortical neurons in vivo as revealed by quantitative analyses. , 2003, Journal of neurophysiology.

[33]  Shigeru Shinomoto,et al.  Differences in Spiking Patterns Among Cortical Neurons , 2003, Neural Computation.

[34]  Ichiro Fujita,et al.  Presumed inhibitory neurons in the macaque inferior temporal cortex: visual response properties and functional interactions with adjacent neurons. , 2004, Journal of neurophysiology.

[35]  P. Somogyi,et al.  Quantitative distribution of GABA-immunoreactive neurons in the visual cortex (area 17) of the cat , 2004, Experimental Brain Research.

[36]  I. Fujita,et al.  Organization of horizontal axons in the inferior temporal cortex and primary visual cortex of the macaque monkey. , 2005, Cerebral cortex.

[37]  S. Shinomoto,et al.  A measure of local variation of inter-spike intervals. , 2005, Bio Systems.

[38]  GUY N. ELSTO,et al.  Cortical heterogeneity : Implications for visual processing and polysensory integration , 2022 .