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      Coding principles of the canonical cortical microcircuit in the avian brain.

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          Abstract

          Mammalian neocortex is characterized by a layered architecture and a common or "canonical" microcircuit governing information flow among layers. This microcircuit is thought to underlie the computations required for complex behavior. Despite the absence of a six-layered cortex, birds are capable of complex cognition and behavior. In addition, the avian auditory pallium is composed of adjacent information-processing regions with genetically identified neuron types and projections among regions comparable with those found in the neocortex. Here, we show that the avian auditory pallium exhibits the same information-processing principles that define the canonical cortical microcircuit, long thought to have evolved only in mammals. These results suggest that the canonical cortical microcircuit evolved in a common ancestor of mammals and birds and provide a physiological explanation for the evolution of neural processes that give rise to complex behavior in the absence of cortical lamination.

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          Most cited references 61

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          Unsupervised spike detection and sorting with wavelets and superparamagnetic clustering.

          This study introduces a new method for detecting and sorting spikes from multiunit recordings. The method combines the wavelet transform, which localizes distinctive spike features, with superparamagnetic clustering, which allows automatic classification of the data without assumptions such as low variance or gaussian distributions. Moreover, an improved method for setting amplitude thresholds for spike detection is proposed. We describe several criteria for implementation that render the algorithm unsupervised and fast. The algorithm is compared to other conventional methods using several simulated data sets whose characteristics closely resemble those of in vivo recordings. For these data sets, we found that the proposed algorithm outperformed conventional methods.
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            Neuronal circuits of the neocortex.

            We explore the extent to which neocortical circuits generalize, i.e., to what extent can neocortical neurons and the circuits they form be considered as canonical? We find that, as has long been suspected by cortical neuroanatomists, the same basic laminar and tangential organization of the excitatory neurons of the neocortex is evident wherever it has been sought. Similarly, the inhibitory neurons show characteristic morphology and patterns of connections throughout the neocortex. We offer a simple model of cortical processing that is consistent with the major features of cortical circuits: The superficial layer neurons within local patches of cortex, and within areas, cooperate to explore all possible interpretations of different cortical input and cooperatively select an interpretation consistent with their various cortical and subcortical inputs.
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              Slow dynamics and high variability in balanced cortical networks with clustered connections.

              Anatomical studies demonstrate that excitatory connections in cortex are not uniformly distributed across a network but instead exhibit clustering into groups of highly connected neurons. The implications of clustering for cortical activity are unclear. We studied the effect of clustered excitatory connections on the dynamics of neuronal networks that exhibited high spike time variability owing to a balance between excitation and inhibition. Even modest clustering substantially changed the behavior of these networks, introducing slow dynamics during which clusters of neurons transiently increased or decreased their firing rate. Consequently, neurons exhibited both fast spiking variability and slow firing rate fluctuations. A simplified model shows how stimuli bias networks toward particular activity states, thereby reducing firing rate variability as observed experimentally in many cortical areas. Our model thus relates cortical architecture to the reported variability in spontaneous and evoked spiking activity.
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                Author and article information

                Journal
                Proc. Natl. Acad. Sci. U.S.A.
                Proceedings of the National Academy of Sciences of the United States of America
                1091-6490
                0027-8424
                Mar 17 2015
                : 112
                : 11
                Affiliations
                [1 ] Program in Neurobiology and Behavior.
                [2 ] Program in Neurobiology and Behavior, Psychology Department, and Kavli Institute, Columbia University, New York, NY 10027 sw2277@columbia.edu.
                Article
                1408545112
                10.1073/pnas.1408545112
                25691736

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