Go Uchida

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.

Object Representation in Inferior Temporal Cortex Is Organized Hierarchically in a Mosaic-Like Structure

There are two dominant models for the functional organization of brain regions underlying object recognition. One model postulates category-specific modules while the other proposes a distributed representation of objects with generic visual features. Functional imaging techniques relying on metabolic signals, such as fMRI and optical intrinsic signal imaging (OISI), have been used to support both models, but due to the indirect nature of the measurements in these techniques, the existing data for one model cannot be used to support the other model. Here, we used large-scale multielectrode recordings over a large surface of anterior inferior temporal (IT) cortex, and densely mapped stimulus-evoked neuronal responses. We found that IT cortex is subdivided into distinct domains characterized by similar patterns of responses to the objects in our stimulus set. Each domain spanned several millimeters on the cortex. Some of these domains represented faces (“face” domains) or monkey bodies (“monkey-body” domains). We also identified domains with low responsiveness to faces (“anti-face” domains). Meanwhile, the recording sites within domains that displayed category selectivity showed heterogeneous tuning profiles to different exemplars within each category. This local heterogeneity was consistent with the stimulus-evoked feature columns revealed by OISI. Taken together, our study revealed that regions with common functional properties (domains) consist of a finer functional structure (columns) in anterior IT cortex. The “domains” and previously proposed “patches” are rather like “mosaics” where a whole mosaic is characterized by overall similarity in stimulus responses and pieces of the mosaic correspond to feature columns.

Sliding Motion of Magnetizable Beads Coated with Chara Motor Protein in a Magnetic Field

We have investigated the sliding movement of magnetizable beads coated with Chara motor protein in a magnetic field using a Characean motility assay system. In the present study only the motion of the beads moving in the opposite direction to the magnetic force exerted on them has been observed. This investigation has revealed that Hills type equation describes relation between average sliding velocity of the beads and the magnetic force. We have also obtained traces of the single beads at every 1/30 s in order to investigate the sliding motion of the beads from a stochastic viewpoint. Application of our stochastic model for the sliding movement to analysis of the traces has made it clear that while the stroke frequency remains constant with increase of the magnetic force, the distance of the beads moved by a single impulse due to the interaction between the motor protein and actin decreases.

Characteristics in Sliding Motions of Small Organelles in a Nitella Internodal Cell

Steady velocities of small organelles smoothly moving on chloroplasts in a Nitella internodal cell have been investigated at various temperatures. It has been found that variance in the velocities of the organelles changes in proportion to their average velocity, which has been first elucidated from the temperature dependence of the organelles velocity. This result suggests that the generation process of the force due to the actin-myosin is a Poisson like stochastic one. Thus, we have discussed a stochastic model for the motion of the organelle with many myosin-like molecules and estimated the force to be 4.2×10 -12 N.

Searching for visual features that explain response variance of face neurons in inferior temporal cortex

Despite a large body of research on response properties of neurons in the inferior temporal (IT) cortex, studies to date have not yet produced quantitative feature descriptions that can predict responses to arbitrary objects. This deficit in the research prevents a thorough understanding of object representation in the IT cortex. Here we propose a fragment-based approach for finding quantitative feature descriptions of face neurons in the IT cortex. The development of the proposed method was driven by the assumption that it is possible to recover features from a set of natural image fragments if the set is sufficiently large. To find the feature from the set, we compared object responses predicted from each fragment and responses of neurons to these objects, and search for the fragment that revealed the highest correlation with neural object responses. Prediction of object responses of each fragment was made by normalizing Euclidian distance between the fragment and each object to 0 to 1 such that the smaller distance gives the higher value. The distance was calculated at the space where images were transformed to a local orientation space by a Gabor filter and a local max operation. The method allowed us to find features with a correlation coefficient between predicted and neural responses of 0.68 on average (number of object stimuli, 104) from among 560,000 feature candidates, reliably explaining differential responses among faces as well as a general preference for faces over to non-face objects. Furthermore, predicted responses of the resulting features to novel object images were significantly correlated with neural responses to these images. Identification of features comprising specific, moderately complex combinations of local orientations and colors enabled us to predict responses to upright and inverted faces, which provided a possible mechanism of face inversion effects. (292/300).

Independent Noise Enhances Synchronization in Heterogeneous Systems

We investigated effects of noise inputs on synchronous firing in a simple model neuron system with electrophysiological heterogeneity. The system consists of two leaky integrate-and-fire (LIF) neurons with different membrane time constants. They are uncoupled and driven by Gaussian white noise inputs. We found that correlation between spike trains of two LIF neurons was maximized at input correlation slightly smaller than one. The same result was obtained for a more realistic system consisting of two non-identical Hodgkin–Huxley neurons. We also revealed the mechanism underlying the effect.

How Images of Objects Are Represented in Macaque Inferotemporal Cortex

Visual object recognition is a simple and easy task in our daily life. However, the mechanisms for recognizing objects are not at all simple nor easy. To understand neural mechanisms of object recognition, we have investigated rep- resentation of object images in macaque inferior temporal cortex that is the area essential for object recognition. Optical intrinsic signal imaging has revealed that object images are represented by the combinatorial code at the columnar level, where each column represents a visual feature of object images. The visual features represented by columns include local features as well as global features repre- senting spatial arrangements of local features. Here, columns are supposed to be functional units for object representation. However, difference in object selectivity among nearby cells does not support the concept of columns as the functional units. Quantitative analysis of object responses of single cells and population activity revealed that each cell in a columnar region is characterized by cell specific prop- erty and property common across the cells in the columnar region, suggesting two different levels (single cell and columnar level) of object representation. Possible role of these two levels of object representation will be discussed.

Stimulus-Induced Pairwise Interaction Can Be Revealed by Information Geometric Approach

Understanding the interaction of neural activities is one of the most important themes in neuroscience. To resolve this question, cross-covariogram analysis of two neurons’ activities is one of most extensively used techniques. This analysis is conducted mostly against the null hypothesis of independent firing. Here, we argue that an additional analysis is required to understand the role of correlation with respect to behaviourally relevant parameters such as visual stimulus. Specifically, we propose conducting this analysis against the null hypothesis of the activity in a control period. We show that information geometric approach can achieve this task. Furthermore, we demonstrate the validity of this method using data taken from the inferior temporal cortex. The results indicate the possible existence of a stimulus-modulated correlation.