Similarity in Neuronal Firing Regimes across Mammalian Species.

UNLABELLED: The architectonic subdivisions of the brain are believed to be functional modules, each processing parts of global functions. Previously, we showed that neurons in different regions operate in different firing regimes in monkeys. It is possible that firing regimes reflect differences in underlying information processing, and consequently the firing regimes in homologous regions across animal species might be similar. We analyzed neuronal spike trains recorded from behaving mice, rats, cats, and monkeys. The firing regularity differed systematically, with differences across regions in one species being greater than the differences in similar areas across species. Neuronal firing was consistently most regular in motor areas, nearly random in visual and prefrontal/medial prefrontal cortical areas, and bursting in the hippocampus in all animals examined. This suggests that firing regularity (or irregularity) plays a key role in neural computation in each functional subdivision, depending on the types of information being carried. SIGNIFICANCE STATEMENT: By analyzing neuronal spike trains recorded from mice, rats, cats, and monkeys, we found that different brain regions have intrinsically different firing regimes that are more similar in homologous areas across species than across areas in one species. Because different regions in the brain are specialized for different functions, the present finding suggests that the different activity regimes of neurons are important for supporting different functions, so that appropriate neuronal codes can be used for different modalities.

Representation of Natural Contours by a Neural Population in Monkey V4.

The cortical visual area, V4, has been considered to code contours that contribute to the intermediate-level representation of objects. The neural responses to the complex contour features intrinsic to natural contours are expected to clarify the essence of the representation. To approach the cortical coding of natural contours, we investigated the simultaneous coding of multiple contour features in monkey (Macaca fuscata) V4 neurons and their population-level representation. A substantial number of neurons showed significant tuning for two or more features such as curvature and closure, indicating that a substantial number of V4 neurons simultaneously code multiple contour features. A large portion of the neurons responded vigorously to acutely curved contours that surrounded the center of classical receptive field, suggesting that V4 neurons tend to code prominent features of object contours. The analysis of mutual information (MI) between the neural responses and each contour feature showed that most neurons exhibited similar magnitudes for each type of MI, indicating that many neurons showing the responses depended on multiple contour features. We next examined the population-level representation by using multidimensional scaling analysis. The neural preferences to the multiple contour features and that to natural stimuli compared with silhouette stimuli increased along with the primary and secondary axes, respectively, indicating the contribution of the multiple contour features and surface textures in the population responses. Our analyses suggested that V4 neurons simultaneously code multiple contour features in natural images and represent contour and surface properties in population.

Neuronal Population Activity in Macaque Visual Cortices Dynamically Changes through Repeated Fixations in Active Free Viewing.

During free viewing, we move our eyes and fixate on objects to recognize the visual scene of our surroundings. To investigate the neural representation of objects in this process, we studied individual and population neuronal activity in three different visual regions of the brains of macaque monkeys (Macaca fuscata): the primary and secondary visual cortices (V1, V2) and the inferotemporal cortex (IT). We designed a task where the animal freely selected objects in a stimulus image to fixate on while we examined the relationship between spiking activity, the order of fixations, and the fixated objects. We found that activity changed across repeated fixations on the same object in all three recorded areas, with observed reductions in firing rates. Furthermore, the responses of individual neurons became sparser and more selective with individual objects. The population activity for individual objects also became distinct. These results suggest that visual neurons respond dynamically to repeated input stimuli through a smaller number of spikes, thereby allowing for discrimination between individual objects with smaller energy.

Figure-ground responsive fields of monkey V4 neurons estimated from natural image patches.

Neurons in visual area V4 modulate their responses depending on the figure-ground (FG) organization in natural images containing a variety of shapes and textures. To clarify whether the responses depend on the extents of the figure and ground regions in and around the classical receptive fields (CRFs) of the neurons, we estimated the spatial extent of local figure and ground regions that evoked FG-dependent responses (RF-FGs) in natural images and their variants. Specifically, we applied the framework of spike triggered averaging (STA) to the combinations of neural responses and human-marked segmentation images (FG labels) that represent the extents of the figure and ground regions in the corresponding natural image stimuli. FG labels were weighted by the spike counts in response to the corresponding stimuli and averaged over. The bias due to the nonuniformity of FG labels was compensated by subtracting the ensemble average of FG labels from the weighted average. Approximately 50% of the neurons showed effective RF-FGs, and a large number exhibited structures that were similar to those observed in virtual neurons with ideal FG-dependent responses. The structures of the RF-FGs exhibited a subregion responsive to a preferred side (figure or ground) around the CRF center and a subregion responsive to a non-preferred side in the surroundings. The extents of the subregions responsive to figure were smaller than those responsive to ground in agreement with the Gestalt rule. We also estimated RF-FG by an adaptive filtering (AF) method, which does not require spherical symmetry (whiteness) in stimuli. RF-FGs estimated by AF and STA exhibited similar structures, supporting the veridicality of the proposed STA. To estimate the contribution of nonlinear processing in addition to linear processing, we estimated nonlinear RF-FGs based on the framework of spike triggered covariance (STC). The analyses of the models based on STA and STC did not show inconsiderable contribution of nonlinearity, suggesting spatial variance of FG regions. The results lead to an understanding of the neural responses that underlie the segregation of figures and the construction of surfaces in intermediate-level visual areas.

Latency shortening with enhanced sparseness and responsiveness in V1 during active visual sensing.

In natural vision, neuronal responses to visual stimuli occur due to self-initiated eye movements. Here, we compare single-unit activity in the primary visual cortex (V1) of non-human primates to flashed natural scenes (passive vision condition) to when they freely explore the images by self-initiated eye movements (active vision condition). Active vision enhances the number of neurons responding, and the response latencies become shorter and less variable across neurons. The increased responsiveness and shortened latency during active vision were not explained by increased visual contrast. While the neuronal activities in all layers of V1 show enhanced responsiveness and shortened latency, a significant increase in lifetime sparseness during active vision is observed only in the supragranular layer. These findings demonstrate that the neuronal responses become more distinct in active vision than passive vision, interpreted as consequences of top-down predictive mechanisms.

Population coding of figure and ground in natural image patches by V4 neurons.

Segmentation of a natural scene into objects and background is a fundamental but challenging task for recognizing objects. Investigating intermediate-level visual cortical areas with a focus on local information is a crucial step towards understanding the formation of the cortical representations of figure and ground. We examined the activity of a population of macaque V4 neurons during the presentation of natural image patches and their respective variations. The natural image patches were optimized to exclude the influence of global context but included various characteristics of local stimulus. Around one fourth of the patch-responsive V4 neurons exhibited significant modulation of firing activity that was dependent on the positional relation between the figural region of the stimulus and the classical receptive field of the neuron. However, the individual neurons showed low consistency in figure-ground modulation across a variety of image patches (55-62%), indicating that individual neurons were capable of correctly signaling figure and ground only for a limited number of stimuli. We examined whether integration of the activity of multiple neurons enabled higher consistency across a variety of natural patches by training a support vector machine to classify figure and ground of the stimuli from the population firing activity. The integration of the activity of a few tens of neurons yielded discrimination accuracy much greater than that of single neurons (up to 85%), suggesting a crucial role of population coding for figure-ground discrimination in natural images.

Switch from ambient to focal processing mode explains the dynamics of free viewing eye movements.

Previous studies have reported that humans employ ambient and focal modes of visual exploration while they freely view natural scenes. These two modes have been characterized based on eye movement parameters such as saccade amplitude and fixation duration, but not by any visual features of the viewed scenes. Here we propose a new characterization of eye movements during free viewing based on how eyes are moved from and to objects in a visual scene. We applied this characterization to data obtained from freely-viewing macaque monkeys. We show that the analysis based on this characterization gives a direct indication of a behavioral shift from ambient to focal processing mode along the course of free viewing exploration. We further propose a stochastic model of saccade sequence generation incorporating a switch between the two processing modes, which quantitatively reproduces the behavioral features observed in the data.

Representation of object images by combinations of visual features in the macaque inferior temporal cortex.

The ventral visual pathway is essential for object recognition where features necessary for recognition are extracted from object images. This pathway is not directly related to action; nevertheless extraction of features from object images through this pathway is closely related to actions since we determine our behaviour based on sensory information, such as object images in the scene. To link perception and action, we have investigated neural representation of object images in area TE. Area TE, the anterior part of the inferior temporal (IT) cortex, is the final purely visual area in the ventral visual pathway. Since individual neurons in this area respond to features less complex than object images, an object image is supposed to be represented by multiple features. Here, to investigate sets of features necessary for representation of object images, we conducted a combination study of an optical imaging technique and single cellular recordings from anesthetized macaque monkeys.

[Visual Recognition of the Shitsukan, or Material Properties, of Objects].

Natural objects, such as animals, flowers, and wood, as well as artificial objects, such as Japanese lacquerware, glass, and metal coins, have their own shape and surface appearances. Although object shapes play important roles in visual object recognition, the material properties or Shitsukan of objects are relevant for the recognition of visual objects. In this review, we introduce recent advances in the understanding of the neural basis of the cognition of Shitsukan. First, we introduce the results of single-neuron recording studies that examined neuronal activity in the inferior temporal cortex of macaque monkeys in response to the presentation of two-dimensional and three-dimensional shapes. Next, we introduce the studies of neuronal response property to the Shitsukan of objects, such as color, texture, glossiness, and the combinations of these features. Then, we discuss how the selective responses to Shitsukan are constructed by hierarchical processing in the ventral visual cortical pathway, which consists of V1, V2, and V4. Finally, we discuss the encoding of Shitsukan information in the inferior temporal cortex.

A neural code for three-dimensional object shape in macaque inferotemporal cortex.

Previous investigations of the neural code for complex object shape have focused on two-dimensional pattern representation. This may be the primary mode for object vision given its simplicity and direct relation to the retinal image. In contrast, three-dimensional shape representation requires higher-dimensional coding derived from extensive computation. We found evidence for an explicit neural code for complex three-dimensional object shape. We used an evolutionary stimulus strategy and linear/nonlinear response models to characterize three-dimensional shape responses in macaque monkey inferotemporal cortex (IT). We found widespread tuning for three-dimensional spatial configurations of surface fragments characterized by their three-dimensional orientations and joint principal curvatures. Configural representation of three-dimensional shape could provide specific knowledge of object structure to support guidance of complex physical interactions and evaluation of object functionality and utility.

Representation of the spatial relationship among object parts by neurons in macaque inferotemporal cortex.

We investigated object representation in area TE, the anterior part of monkey inferotemporal (IT) cortex, with a combination of optical and extracellular recordings in anesthetized monkeys. We found neurons that respond to visual stimuli composed of naturally distinguishable parts. These neurons were sensitive to a particular spatial arrangement of parts but less sensitive to differences in local features within individual parts. Thus these neurons were activated when arbitrary local features were arranged in a particular spatial configuration, suggesting that they may be responsible for representing the spatial configuration of object images. Previously it has been reported that many neurons in area TE respond to visual features less complex than natural objects, but it has remained unclear whether these features are related to local features of object images or to more global features. These results indicate that TE neurons represent not only local features but also global features such as the spatial relationship among object parts.

Differentiation of immature oligodendrocytes is regulated by phosphorylation of cyclic AMP-response element binding protein by a protein kinase C signaling cascade.

Previous experiments showed that the expression and phosphorylation levels of cyclic AMP-response element binding protein (CREB) are important factors that regulate oligodendrocyte differentiation. The present study was designed to determine whether CREB phosphorylation advances oligodendrocyte differentiation or vice versa and to identify the protein kinase that primarily regulates CREB phosphorylation. We examined the expression and phosphorylation levels of CREB in developing oligodendrocytes at a specific differentiation stage by double-immunocytochemical staining with specific differentiation markers and antibody for phosphorylated CREB. We found that the CREB expression level increased along oligodendrocyte differentiation, and that its phosphorylated level was highest in immature oligodendrocytes. We also showed that CREB phosphorylation was regulated principally by protein kinase C (PKC) activity in immature oligodendrocytes. Our findings suggest that CREB phosphorylation is dependent on a PKC signaling cascade, and this phosphorylation activates CREB-mediated transcription and advances the differentiation of immature to mature oligodendrocytes.