Ohki, K., Chung, S., Ch'Ng, Y.H., Kara, P. & Reid, R.C. Functional imaging with cellular resolution reveals precise micro-architecture in visual cortex. Nature 433, 597-603

Harvard University, Cambridge, Massachusetts, United States
Nature (Impact Factor: 41.46). 03/2005; 433(7026):597-603. DOI: 10.1038/nature03274
Source: PubMed


Neurons in the cerebral cortex are organized into anatomical columns, with ensembles of cells arranged from the surface to the white matter. Within a column, neurons often share functional properties, such as selectivity for stimulus orientation; columns with distinct properties, such as different preferred orientations, tile the cortical surface in orderly patterns. This functional architecture was discovered with the relatively sparse sampling of microelectrode recordings. Optical imaging of membrane voltage or metabolic activity elucidated the overall geometry of functional maps, but is averaged over many cells (resolution >100 microm). Consequently, the purity of functional domains and the precision of the borders between them could not be resolved. Here, we labelled thousands of neurons of the visual cortex with a calcium-sensitive indicator in vivo. We then imaged the activity of neuronal populations at single-cell resolution with two-photon microscopy up to a depth of 400 microm. In rat primary visual cortex, neurons had robust orientation selectivity but there was no discernible local structure; neighbouring neurons often responded to different orientations. In area 18 of cat visual cortex, functional maps were organized at a fine scale. Neurons with opposite preferences for stimulus direction were segregated with extraordinary spatial precision in three dimensions, with columnar borders one to two cells wide. These results indicate that cortical maps can be built with single-cell precision.

Full-text preview

Available from:
  • Source
    • "Determining connectivity in populations of neurons is fundamental to understanding neural computation and function. In recent years, calcium imaging has emerged as a promising technique for measuring synaptic activity and mapping neural micro-circuits [1] [2] [3] [4] [5]. Fluorescent calcium-sensitive dyes and genetically-encoded calcium indicators can be loaded into neurons, which can then be imaged for spiking activity either in vivo or in vitro. "
    [Show abstract] [Hide abstract]
    ABSTRACT: Fluorescent calcium imaging provides a potentially powerful tool for inferring connectivity in neural circuits with up to thousands of neurons. However, a key challenge in using calcium imaging for connectivity detection is that current systems often have a temporal response and frame rate that can be orders of magnitude slower than the underlying neural spiking process. Bayesian inference methods based on expectation-maximization (EM) have been proposed to overcome these limitations, but are often computationally demanding since the E-step in the EM procedure typically involves state estimation for a high-dimensional nonlinear dynamical system. In this work, we propose a computationally fast method for the state estimation based on a hybrid of loopy belief propagation and approximate message passing (AMP). The key insight is that a neural system as viewed through calcium imaging can be factorized into simple scalar dynamical systems for each neuron with linear interconnections between the neurons. Using the structure, the updates in the proposed hybrid AMP methodology can be computed by a set of one-dimensional state estimation procedures and linear transforms with the connectivity matrix. This yields a computationally scalable method for inferring connectivity of large neural circuits. Simulations of the method on realistic neural networks demonstrate good accuracy with computation times that are potentially significantly faster than current approaches based on Markov Chain Monte Carlo methods.
    Advances in neural information processing systems 09/2014; 4.
  • Source
    • "In the visual cortex of all examined mammalian species (Hubel and Wiesel, 1959, 1962), many neurons respond strongly to bars or edges at a particular preferred orientation. In some mammals such as carnivores, primates, and tree shrews, these orientation-selective cells are organized into functional columns (Hubel and Wiesel, 1962, 1968; Humphrey and Norton, 1980), and in other animals such as rodents there are no maps of orientation selectivity yet individual cells exhibit strong orientation selectivity (Girman et al., 1999; Ohki et al., 2005; Van Hooser et al., 2005; Mrsic-Flogel et al., 2007). Further, a substantial subset of orientation-selective cells also exhibit direction selectivity (Hubel and Wiesel, 1962; Weliky et al., 1996). "
    [Show abstract] [Hide abstract]
    ABSTRACT: Neurons in the visual cortex of all examined mammals exhibit orientation or direction tuning. New imaging techniques are allowing the circuit mechanisms underlying orientation and direction selectivity to be studied with clarity that was not possible a decade ago. However, these new techniques bring new challenges: robust quantitative measurements are needed to evaluate the findings from these studies, which can involve thousands of cells of varying response strength. Here we show that traditional measures of selectivity such as the orientation index (OI) and direction index (DI) are poorly suited for quantitative evaluation of orientation and direction tuning. We explore several alternative methods for quantifying tuning and for addressing a variety of questions that arise in studies on orientation- and direction-tuned cells and cell populations. We provide recommendations for which methods are best suited to which applications and we offer tips for avoiding potential pitfalls in applying these methods. Our goal is to supply a solid quantitative foundation for studies involving orientation and direction tuning.
    Frontiers in Neural Circuits 08/2014; 8:92. DOI:10.3389/fncir.2014.00092 · 3.60 Impact Factor
  • Source
    • "The advent of modern approaches using in vivo two-photon calcium imaging enables us to measure physiological properties and to identify anatomical locations simultaneously (Ohki et al., 2005). This powerful experimental application is particularly useful for studying the neocortex. "
    [Show abstract] [Hide abstract]
    ABSTRACT: The auditory lemniscal thalamocortical (TC) pathway conveys information from the ventral division of the medial geniculate body to the primary auditory cortex (A1). Although their general topographic organization has been well characterized, functional transformations at the lemniscal TC synapse still remain incompletely codified, largely due to the need for integration of functional anatomical results with the variability observed with various animal models and experimental techniques. In this review, we discuss these issues with classical approaches, such as in vivo extracellular recordings and tracer injections to physiologically identified areas in A1, and then compare these studies with modern approaches, such as in vivo two-photon calcium imaging, in vivo whole-cell recordings, optogenetic methods, and in vitro methods using slice preparations. A surprising finding from a comparison of classical and modern approaches is the similar degree of convergence from thalamic neurons to single A1 neurons and clusters of A1 neurons, although, thalamic convergence to single A1 neurons is more restricted from areas within putative thalamic frequency lamina. These comparisons suggest that frequency convergence from thalamic input to A1 is functionally limited. Finally, we consider synaptic organization of TC projections and future directions for research.
    Frontiers in Neural Circuits 07/2014; 8(75):1-9. DOI:10.3389/fncir.2014.00075 · 3.60 Impact Factor
Show more