Cortical Columnar Organization Is Reconsidered in Inferior Temporal Cortex

The object selectivity of nearby cells in inferior temporal (IT) cortex is often different. To elucidate the relationship between columnar organization in IT cortex and the variability among neurons with respect to object selectivity, we used optical imaging technique to locate columnar regions (activity spots) and systematically compared object selectivity of individual neurons within and across the spots. The object selectivity of a given cell in a spot was similar to that of the averaged cellular activity within the spot. However, there was not such similarity among different spots (>600 μm apart). We suggest that each cell is characterized by 1) a cell-specific response property that cause cell-to-cell variability in object selectivity and 2) one or potentially a few numbers of response properties common across the cells within a spot, which provide the basis for columnar organization in IT cortex. Furthermore, similarity in object selectivity among cells within a randomly chosen site was lower than that for a cell in an activity spot identified by optical imaging beforehand. We suggest that the cortex may be organized in a region where neurons with similar response properties were densely clustered and a region where neurons with similar response properties were sparsely clustered.

[1]  V. Mountcastle.  Modality and topographic properties of single neurons of cat's somatic sensory cortex. , 1957, Journal of neurophysiology.

[2]  D. Hubel,et al.  Receptive fields, binocular interaction and functional architecture in the cat's visual cortex , 1962, The Journal of physiology.

[3]  D. B. Bender,et al.  Visual properties of neurons in inferotemporal cortex of the Macaque. , 1972, Journal of neurophysiology.

[4]  Ralph Roskies,et al.  Fourier Descriptors for Plane Closed Curves , 1972, IEEE Transactions on Computers.

[5]  D. Hubel,et al.  Laminar and columnar distribution of geniculo‐cortical fibers in the macaque monkey , 1972, The Journal of comparative neurology.

[6]  D. Marr,et al.  Representation and recognition of the spatial organization of three-dimensional shapes , 1978, Proceedings of the Royal Society of London. Series B. Biological Sciences.

[7]  R. Desimone,et al.  Shape recognition and inferior temporal neurons. , 1983, Proceedings of the National Academy of Sciences of the United States of America.

[8]  R. Desimone,et al.  Columnar organization of directionally selective cells in visual area MT of the macaque. , 1984, Journal of neurophysiology.

[9]  A. J. Mistlin,et al.  Neurones responsive to faces in the temporal cortex: studies of functional organization, sensitivity to identity and relation to perception. , 1984, Human neurobiology.

[10]  R. Desimone,et al.  Stimulus-selective properties of inferior temporal neurons in the macaque , 1984, The Journal of neuroscience : the official journal of the Society for Neuroscience.

[11]  Keiji Tanaka,et al.  Coding visual images of objects in the inferotemporal cortex of the macaque monkey. , 1991, Journal of neurophysiology.

[12]  Minami Ito,et al.  Columns for visual features of objects in monkey inferotemporal cortex , 1992, Nature.

[13]  K. Rockland,et al.  Specific and columnar projection from area TEO to TE in the macaque inferotemporal cortex. , 1993, Cerebral cortex.

[14]  A Grinvald,et al.  Optical imaging reveals the functional architecture of neurons processing shape and motion in owl monkey area MT , 1994, Proceedings of the Royal Society of London. Series B: Biological Sciences.

[15]  Keiji Tanaka,et al.  Neuronal selectivities to complex object features in the ventral visual pathway of the macaque cerebral cortex. , 1994, Journal of neurophysiology.

[16]  E T Rolls,et al.  Sparseness of the neuronal representation of stimuli in the primate temporal visual cortex. , 1995, Journal of neurophysiology.

[17]  Keiji Tanaka,et al.  Optical Imaging of Functional Organization in the Monkey Inferotemporal Cortex , 1996, Science.

[18]  Keiji Tanaka,et al.  Inferotemporal cortex and object vision. , 1996, Annual review of neuroscience.

[19]  Keiji Tanaka,et al.  Functional architecture in monkey inferotemporal cortex revealed by in vivo optical imaging , 1998, Neuroscience Research.

[20]  R. Vogels,et al.  Spatial sensitivity of macaque inferior temporal neurons , 2000, The Journal of comparative neurology.

[21]  Keiji Tanaka,et al.  Human Ocular Dominance Columns as Revealed by High-Field Functional Magnetic Resonance Imaging , 2001, Neuron.

[22]  Y. Yamane,et al.  Complex objects are represented in macaque inferotemporal cortex by the combination of feature columns , 2001, Nature Neuroscience.

[23]  Amiram Grinvald,et al.  Dural substitute for long-term imaging of cortical activity in behaving monkeys and its clinical implications , 2002, Journal of Neuroscience Methods.

[24]  E. K. Miller,et al.  Functional interactions among neurons in inferior temporal cortex of the awake macaque , 2004, Experimental Brain Research.

[25]  D. Perrett,et al.  Visual neurones responsive to faces in the monkey temporal cortex , 2004, Experimental Brain Research.

[26]  Form vision in the periphery , 2004 .

[27]  Functional selectivity of human extrastriate visual cortex at high resolution , 2004 .

[28]  Ichiro Fujita,et al.  Quantitative analysis of functional clustering of neurons in the macaque inferior temporal cortex , 2005, Neuroscience Research.

[29]  Doris Y. Tsao,et al.  A Cortical Region Consisting Entirely of Face-Selective Cells , 2006, Science.

[30]  Seong-Gi Kim,et al.  Mapping Iso-Orientation Columns by Contrast Agent-Enhanced Functional Magnetic Resonance Imaging: Reproducibility, Specificity, and Evaluation by Optical Imaging of Intrinsic Signal , 2006, The Journal of Neuroscience.

[31]  Manabu Tanifuji,et al.  Representation of the spatial relationship among object parts by neurons in macaque inferotemporal cortex. , 2006, Journal of neurophysiology.

[32]  T. Poggio,et al.  Object Selectivity of Local Field Potentials and Spikes in the Macaque Inferior Temporal Cortex , 2006, Neuron.

[33]  Andrzej W. Przybyszewski,et al.  Optical filtering removes non-homogenous illumination artifacts in optical imaging , 2008, Journal of Neuroscience Methods.