Categorical encoding of color in the brain

Image classification and reconstruction from low-density EEG

Recent advances in visual decoding have enabled the classification and reconstruction of perceived images from the brain. However, previous approaches have predominantly relied on stationary, costly equipment like fMRI or high-density EEG, limiting the real-world availability and applicability of such projects. Additionally, several EEG-based paradigms have utilized artifactual, rather than stimulus-related information yielding flawed classification and reconstruction results. Our goal was to reduce the cost of the decoding paradigm, while increasing its flexibility. Therefore, we investigated whether the classification of an image category and the reconstruction of the image itself is possible from the visually evoked brain activity measured by a portable, 8-channel EEG. To compensate for the low electrode count and to avoid flawed predictions, we designed a theory-guided EEG setup and created a new experiment to obtain a dataset from 9 subjects. We compared five contemporary classification models with our setup reaching an average accuracy of 34.4% for 20 image classes on hold-out test recordings. For the reconstruction, the top-performing model was used as an EEG-encoder which was combined with a pretrained latent diffusion model via double-conditioning. After fine-tuning, we reconstructed images from the test set with a 1000 trial 50-class top-1 accuracy of 35.3%. While not reaching the same performance as MRI-based paradigms on unseen stimuli, our approach greatly improved the affordability and mobility of the visual decoding technology.

Multi-Semantic Decoding of Visual Perception with Graph Neural Networks

Constructing computational decoding models to account for the cortical representation of semantic information plays a crucial role in understanding visual perception. The human visual system processes interactive relationships among different objects when perceiving the semantic contents of natural visions. However, the existing semantic decoding models commonly regard categories as completely separate and independent visually and semantically and rarely consider the relationships from prior information. In this work, a novel semantic graph learning model was proposed to decode multiple semantic categories of perceived natural images from brain activity. The proposed model was validated on the functional magnetic resonance imaging data collected from five normal subjects while viewing 2750 natural images comprising 52 semantic categories. The results showed that the Graph Neural Network-based decoding model achieved higher accuracies than other deep neural network models. Moreover, the co-occurrence probability among semantic categories showed a significant correlation with the decoding accuracy. Additionally, the results suggested that semantic content organized in a hierarchical way with higher visual areas was more closely related to the internal visual experience. Together, this study provides a superior computational framework for multi-semantic decoding that supports the visual integration mechanism of semantic processing.

Rapid color categorization revealed by frequency-tagging-based EEG

There has been much debate on whether color categories affect how we perceive color. Recent theories have put emphasis on the role of top-down influence on color perception that the original continuous color space in the visual cortex may be transformed into categorical encoding due to top-down modulation. To test the influence of color categories on color perception, we adopted an RSVP paradigm, where color stimuli were presented at a fast speed of 100 ms per stimulus and were forward and backward masked by the preceding and following stimuli. Moreover, no explicit color naming or categorization was required. In theory, backward masking with such a short interval in a passive viewing task should constrain top-down influence from higher-level brain areas. To measure any potentially subtle differences in brain response elicited by different color categories, we embedded a sensitive frequency-tagging-based EEG paradigm within the RSVP stimuli stream where the oddball color stimuli were encoded with a different frequency from the base color stimuli. We showed that EEG responses to cross-category oddball colors at the frequency where the oddball stimuli were presented was significantly larger than the responses to within-category oddball colors. Our study suggested that the visual cortex can automatically and implicitly encode color categories when color stimuli are presented rapidly.

Tomatoes Are Red: The Perception of Achromatic Objects Elicits Retrieval of Associated Color Knowledge

When preparing to name an object, semantic knowledge about the object and its attributes is activated, including perceptual properties. It is unclear, however, whether semantic attribute activation contributes to lexical access or is a consequence of activating a concept irrespective of whether that concept is to be named or not. In this study, we measured neural responses using fMRI while participants named objects that are typically green or red, presented in black line drawings. Furthermore, participants underwent two other tasks with the same objects, color naming and semantic judgment, to see if the activation pattern we observe during picture naming is (a) similar to that of a task that requires accessing the color attribute and (b) distinct from that of a task that requires accessing the concept but not its name or color. We used representational similarity analysis to detect brain areas that show similar patterns within the same color category, but show different patterns across the two color categories. In all three tasks, activation in the bilateral fusiform gyri ("Human V4") correlated with a representational model encoding the red-green distinction weighted by the importance of color feature for the different objects. This result suggests that when seeing objects whose color attribute is highly diagnostic, color knowledge about the objects is retrieved irrespective of whether the color or the object itself have to be named.

Camouflage Detection and Its Association with Cognitive Style: A Functional Connectivity Study

Background: Individual differences exist in performance in tasks that require visual search, such as camouflage detection (CD). Field dependence/independence (FD/I), as assessed using the Group Embedded Figures Test (GEFT), is an extensively studied dimension of cognitive style that classifies participants based on their visual perceptual styles. Materials and Methods: In the present study, we utilized fMRI on 46 healthy participants to investigate the underlying neural mechanisms specific to the cognitive styles of FD/FI while performing a CD task using both activation magnitude and an exploratory functional connectivity (FC) analysis. Group differences between high and low performers on the two extremes of the accuracy continuum of GEFT were studied. Results: No statistically significant group differences were observed using whole-brain voxel-wise comparison. However, the exploratory FC analysis revealed an enhanced communication between various regions subserving the cognitive traits required for visual search by FI participants over and above their FD counterparts. Conclusion: These enhanced connectivities suggest additional recruitment of cognitive functions to provide computational support that might facilitate superior performance in CD task by the participants who display a field-independent cognitive style.

Corvids optimize working memory by categorizing continuous stimuli

Working memory (WM) is a crucial element of the higher cognition of primates and corvid songbirds. Despite its importance, WM has a severely limited capacity and is vulnerable to noise. In primates, attractor dynamics mitigate the effect of noise by discretizing continuous information. Yet, it remains unclear whether similar dynamics are seen in avian brains. Here, we show jackdaws (Corvus monedula) have similar behavioral biases as humans; memories are less precise and more biased as memory demands increase. Model-based analysis reveal discrete attractors are evenly spread across the stimulus space. Altogether, our comparative approach suggests attractor dynamics in primates and corvids mitigate the effect of noise by systematically drifting towards specific attractors. By demonstrating this effect in an evolutionary distant species, our results strengthen attractor dynamics as general, adaptive biological principle to efficiently use WM.

Perception of color in primates: A conceptual color neurons hypothesis

Perception of color by humans and other primates is a complex problem, studied by neurophysiology, psychophysiology, psycholinguistics, and even philosophy. Being mostly trichromats, simian primates have three types of opsin proteins, expressed in cone neurons in the eye, which allow for the sensing of color as the physical wavelength of light. Further, in neural networks of the retina, the coding principle changes from three types of sensor proteins to two opponent channels: activity of one type of neuron encode the evolutionarily ancient blue-yellow axis of color stimuli, and another more recent evolutionary channel, encoding the axis of red-green color stimuli. Both color channels are distinctive in neural organization at all levels from the eye to the neocortex, where it is thought that the perception of color (as philosophical qualia) emerges from the activity of some neuron ensembles. Here, using data from neurophysiology as a starting point, we propose a hypothesis on how the perception of color can be encoded in the activity of certain neurons in the neocortex. These conceptual neurons, herein referred to as 'color neurons', code only the hue of the color of visual stimulus, similar to place cells and number neurons, already described in primate brains. A case study with preliminary, but direct, evidence for existing conceptual color neurons in the human brain was published in 2008. We predict that the upcoming studies in non-human primates will be more extensive and provide a more detailed description of conceptual color neurons.

Categorical encoding of moving colors during location tracking

Categorical perception (CP) describes our tendency to perceive the visual world in a categorical manner, suggesting that high-level cognition may affect perception. While most studies are conducted in static visual scenes, Sun and colleagues found CP effects of color in multiple object tracking (MOT). This study used functional magnetic resonance imaging to investigate the neural mechanism behind the categorical effects of color in MOT. Categorical effects were associated with activities in a broad range of brain regions, including both the ventral (V4, middle temporal gyrus) and dorsal pathways (MT + /V5, inferior parietal lobule) of feature processing, as well as frontal regions (middle frontal gyrus, medial superior frontal gyrus). We proposed that these regions are hierarchically organized and responsible for distinct functions. The color-selective V4 encodes color categories, making cross-category colors more discriminable than within-category colors. Meanwhile, the language and/or semantic regions encode the verbal information of the colors. Both visual and nonvisual codes of color categories then modulate the activities of motion-sensitive MT + areas and frontal areas responsible for attentional processes.

Color-biased regions in the ventral visual pathway are food selective

Color-biased regions have been found between face- and place-selective areas in the ventral visual pathway. To investigate the function of the color-biased regions in a pathway responsible for object recognition, we analyzed the natural scenes dataset (NSD), a large 7T fMRI dataset from 8 participants who each viewed up to 30,000 trials of images of colored natural scenes over more than 30 scanning sessions. In a whole-brain analysis, we correlated the average color saturation of the images with voxel responses, revealing color-biased regions that diverge into two streams, beginning in V4 and extending medially and laterally relative to the fusiform face area in both hemispheres. We drew regions of interest (ROIs) for the two streams and found that the images for each ROI that evoked the largest responses had certain characteristics: they contained food, circular objects, warmer hues, and had higher color saturation. Further analyses showed that food images were the strongest predictor of activity in these regions, implying the existence of medial and lateral ventral food streams (VFSs). We found that color also contributed independently to voxel responses, suggesting that the medial and lateral VFSs use both color and form to represent food. Our findings illustrate how high-resolution datasets such as the NSD can be used to disentangle the multifaceted contributions of many visual features to the neural representations of natural scenes.

An "Instantaneous" Response of a Human Visual System to Hue: An EEG-Based Study

(1) The article presents a new technique to interpret biomedical data (EEG) to assess cortical responses to continuous color/hue variations. We propose an alternative approach to analyze EEG activity evoked by visual stimulation. This approach may augment the traditional VEP analysis. (2) Considering ensembles of EEG epochs as multidimensional spatial vectors evolving over time (rather than collections of time-domain signals) and evaluating the similarity between such vectors across different EEG epochs may result in a more accurate detection of colors that evoke greater responses of the visual system. To demonstrate its suitability, the developed analysis technique was applied to the EEG data that we previously collected from 19 participants with normal color vision, while exposing them to stimuli of continuously varying hue. (3) Orange/yellow and dark blue/violet colors generally aroused better-pronounced cortical responses. The selection of EEG channels allowed for assessing the activity that predominantly originates from specific cortical regions. With such channel selection, the strongest response to the hue was observed from Parieto-Temporal region of the right hemisphere. The statistical test-Kruskal-Wallis one-way analysis of variance-indicates that the distance evaluated for spatial EEG vectors at different post-stimulus latencies generally originate from different statistical distributions with a probability exceeding 99.9% (α = 0.001).

Color me impressed: A partner's target feature captures visual attention

Attending to a target is more difficult in the presence of a salient distractor. The present study investigated whether social value can modulate the extent to which distractors capture attention. Two participants sitting side-by-side performed a visual search task in cooperative and competitive conditions. Search displays contained either both targets, one target and a neutral stimulus or an ambiguous and a neutral stimulus. Results showed that agents took longer to respond to targets presented together with the partner's target compared to a neutral stimulus of equal salience. Agents also produced more false alarms in response to stimuli whose color lay between their own and the partner's target color compared to stimuli lying between the colors of their target and a neutral stimulus. These results suggest that stimuli with features relevant to a partner can capture attention more than neutral but equally salient stimuli, indicating that social value affects selective attention in a similar way as task goals and selection history.

Neural Hierarchy of Color Categorization: From Prototype Encoding to Boundary Encoding

A long-standing debate exists on how our brain assigns the fine-grained perceptual representation of color into discrete color categories. Recent functional magnetic resonance imaging (fMRI) studies have identified several regions as the candidate loci of color categorization, including the visual cortex, language-related areas, and non-language-related frontal regions, but the evidence is mixed. Distinct from most studies that emphasized the representational differences between color categories, the current study focused on the variability among members within a category (e.g., category prototypes and boundaries) to reveal category encoding in the brain. We compared and modeled brain activities evoked by color stimuli with varying distances from the category boundary in an active categorization task. The frontal areas, including the inferior and middle frontal gyri, medial superior frontal cortices, and insular cortices, showed larger responses for colors near the category boundary than those far from the boundary. In addition, the visual cortex encodes both within-category variability and cross-category differences. The left V1 in the calcarine showed greater responses to colors at the category center than to those far from the boundary, and the bilateral V4 showed enhanced responses for colors at the category center as well as colors around the boundary. The additional representational similarity analyses (RSA) revealed that the bilateral insulae and V4a carried information about cross-category differences, as cross-category colors exhibited larger dissimilarities in brain patterns than within-category colors. Our study suggested a hierarchically organized network in the human brain during active color categorization, with frontal (both lateral and medial) areas supporting domain-general decisional processes and the visual cortex encoding category structure and differences, likely due to top-down modulation.

Classification of brain electrophysiological changes in response to colour stimuli

In this study, the classification of ongoing brain activity occurring as a response to colour stimuli was managed and reported. Until now, the classification of the seen colour from brain electrical signals has not been investigated or reported in the related literature. In this study, we aimed to classify EEG brain responses corresponding to blue, green, and red coloured shapes. In addition to the current literature, we focused on ongoing EEG responses instead of using ERP metrics, with visual stimulus-related ERP metrics also compared throughout the study. The feature extraction process was carried out using the Fourier transform to obtain the conventional band power values of the EEG for each stimulus type. Delta, theta, alpha, beta, and gamma-band power values of each one-second period constituted the feature set. In addition to scalp measurements, a second feature set was obtained based on the inverse solution of the EEG waves. Furthermore, we applied one-way ANOVA for the feature selection prior to classification procedures. Four classifiers were implemented using the reduced feature set and the raw one as well. The differences between scalp responses were localized mainly around the temporal and temporoparietal regions. Our ERP-component findings support the fact that additional brain regions among the visual cortex participate in the colour categorization process of the brain. RGB colours were identified using 1 s EEG data. Ensemble-KNN and KNN achieved the highest accuracy values (93%) when used either with scalp spectral features or source space features.

Distributed chromatic processing at the interface between retina and brain in the larval zebrafish

Larval zebrafish (Danio rerio) are an ideal organism for studying color vision, as their retina possesses four types of cone photoreceptors, covering most of the visible range and into the UV.^1,2 Additionally, their eye and nervous systems are accessible to imaging, given that they are naturally transparent.^3-5 Recent studies have found that, through a set of wavelength-range-specific horizontal, bipolar, and retinal ganglion cells (RGCs),^6-9 the eye relays tetrachromatic information to several retinorecipient areas (RAs).^10-13 The main RA is the optic tectum, receiving 97% of the RGC axons via the neuropil mass termed arborization field 10 (AF10).^14,15 Here, we aim to understand the processing of chromatic signals at the interface between RGCs and their major brain targets. We used 2-photon calcium imaging to separately measure the responses of RGCs and neurons in the brain to four different chromatic stimuli in awake animals. We find that chromatic information is widespread throughout the brain, with a large variety of responses among RGCs, and an even greater diversity in their targets. Specific combinations of response types are enriched in specific nuclei, but there is no single color processing structure. In the main interface in this pathway, the connection between AF10 and tectum, we observe key elements of neural processing, such as enhanced signal decorrelation and improved chromatic decoding.^16,17 A richer stimulus set revealed that these enhancements occur in the context of a more distributed code in tectum, facilitating chromatic signal association in this small vertebrate brain.

Color Space Geometry Uncovered with Magnetoencephalography

The geometry that describes the relationship among colors, and the neural mechanisms that support color vision, are unsettled. Here, we use multivariate analyses of measurements of brain activity obtained with magnetoencephalography to reverse-engineer a geometry of the neural representation of color space. The analyses depend upon determining similarity relationships among the spatial patterns of neural responses to different colors and assessing how these relationships change in time. We evaluate the approach by relating the results to universal patterns in color naming. Two prominent patterns of color naming could be accounted for by the decoding results: the greater precision in naming warm colors compared to cool colors evident by an interaction of hue and lightness, and the preeminence among colors of reddish hues. Additional experiments showed that classifiers trained on responses to color words could decode color from data obtained using colored stimuli, but only at relatively long delays after stimulus onset. These results provide evidence that perceptual representations can give rise to semantic representations, but not the reverse. Taken together, the results uncover a dynamic geometry that provides neural correlates for color appearance and generates new hypotheses about the structure of color space.

Decoding chromaticity and luminance from patterns of EEG activity

A long-standing question in the field of vision research is whether scalp-recorded EEG activity contains sufficient information to identify stimulus chromaticity. Recent multivariate work suggests that it is possible to decode which chromaticity an observer is viewing from the multielectrode pattern of EEG activity. There is debate, however, about whether the claimed effects of stimulus chromaticity on visual evoked potentials (VEPs) are instead caused by unequal stimulus luminances, which are achromatic differences. Here, we tested whether stimulus chromaticity could be decoded when potential confounds with luminance were minimized by (1) equating chromatic stimuli in luminance using heterochromatic flicker photometry for each observer and (2) independently varying the chromaticity and luminance of target stimuli, enabling us to test whether the pattern for a given chromaticity generalized across wide variations in luminance. We also tested whether luminance variations can be decoded from the topography of voltage across the scalp. In Experiment 1, we presented two chromaticities (appearing red and green) at three luminance levels during separate trials. In Experiment 2, we presented four chromaticities (appearing red, orange, yellow, and green) at two luminance levels. Using a pattern classifier and the multielectrode pattern of EEG activity, we were able to accurately decode the chromaticity and luminance level of each stimulus. Furthermore, we were able to decode stimulus chromaticity when we trained the classifier on chromaticities presented at one luminance level and tested at a different luminance level. Thus, EEG topography contains robust information regarding stimulus chromaticity, despite large variations in stimulus luminance.

Color Naming and Categorization Depend on Distinct Functional Brain Networks

Naming a color can be understood as an act of categorization, that is, identifying it as a member of a category of colors that are referred to by the same name. But are naming and categorization equivalent cognitive processes and consequently rely on same neural substrates? Here, we used task and resting-state functional magnetic resonance imaging as well as behavioral measures to identify functional brain networks that modulated naming and categorization of colors. We first identified three bilateral color-sensitive regions in the ventro-occipital cortex. We then showed that, across participants, color naming and categorization response times (RTs) were correlated with different resting state connectivity networks seeded from the color-sensitive regions. Color naming RTs correlated with the connectivity between the left posterior color region, the left middle temporal gyrus, and the left angular gyrus. In contrast, color categorization RTs correlated with the connectivity between the bilateral posterior color regions, and left frontal, right temporal and bilateral parietal areas. The networks supporting naming and categorization had a minimal overlap, indicating that the 2 processes rely on different neural mechanisms.

Convolutional neural networks and genetic algorithm for visual imagery classification

Brain-Computer Interface (BCI) systems establish a channel for direct communication between the brain and the outside world without having to use the peripheral nervous system. While most BCI systems use evoked potentials and motor imagery, in the present work we present a technique that employs visual imagery. Our technique uses neural networks to classify the signals produced in visual imagery. To this end, we have used densely connected neural and convolutional networks, together with a genetic algorithm to find the best parameters for these networks. The results we obtained are a 60% success rate in the classification of four imagined objects (a tree, a dog, an airplane and a house) plus a state of relaxation, thus outperforming the state of the art in visual imagery classification.

New insights into the neural basis of cognitive control: An event-related fMRI study of task selection processes

To investigate cognitive control, researchers have repeatedly employed task switching paradigms. The comparison of switch relative to repeat trials reveals longer response times and higher error rates, a pattern that has been interpreted as switching costs. Functional magnetic resonance imaging (fMRI) studies have shown the involvement of different brain modules in switching conditions, including prefrontal and parietal regions together with other sub-cortical structures. In this study, the aim was to shed light on the brain basis of cognitive control using an approach that proved useful in previous studies investigating language control in bilinguals. We examined adult participants in one simple color naming context and two task selection mixed contexts. In the first mixed selection context, participants named the color or the shape of the stimulus based on a cue word. In the second, they named the color or the size of the stimulus. It was assumed that the comparison of brain responses to the same color naming in mixed selection contexts vs. in non-selection context will reveal the of engagement of cognitive control/task selection processes. Whole brain analysis of color naming in the different contexts showed a significant main effect of context. The comparison of brain responses in several frontal, parietal and sub-cortical regions, of which some are supposedly involved in cognitive control, demonstrated an increased activation during color naming in mixed relative the simple non-mixed context. The different cognitive control modules described in this study fit with recent bilingual language control and domain general cognitive models.

fMRI representational similarity analysis reveals graded preferences for chromatic and achromatic stimulus contrast across human visual cortex

Human visual cortex is partitioned into different functional areas that, from lower to higher, become increasingly selective and responsive to complex feature dimensions. Here we use a Representational Similarity Analysis (RSA) of fMRI-BOLD signals to make quantitative comparisons across LGN and multiple visual areas of the low-level stimulus information encoded in the patterns of voxel responses. Our stimulus set was picked to target the four functionally distinct subcortical channels that input visual cortex from the LGN: two achromatic sinewave stimuli that favor the responses of the high-temporal magnocellular and high-spatial parvocellular pathways, respectively, and two chromatic stimuli isolating the L/M-cone opponent and S-cone opponent pathways, respectively. Each stimulus type had three spatial extents to sample both foveal and para-central visual field. With the RSA, we compare quantitatively the response specializations for individual stimuli and combinations of stimuli in each area and how these change across visual cortex. First, our results replicate the known response preferences for motion/flicker in the dorsal visual areas. In addition, we identify two distinct gradients along the ventral visual stream. In the early visual areas (V1-V3), the strongest differential representation is for the achromatic high spatial frequency stimuli, suitable for form vision, and a very weak differentiation of chromatic versus achromatic contrast. Emerging in ventral occipital areas (V4, VO1 and VO2), however, is an increasingly strong separation of the responses to chromatic versus achromatic contrast and a decline in the high spatial frequency representation. These gradients provide new insight into how visual information is transformed across the visual cortex.

Computing the relevant colors that describe the color palette of paintings

In this paper, we introduce an innovative parameter that allows us to evaluate the so-called "relevant colors" in a painting; in other words, the number of colors that would stand out for an observer when just glancing at a painting. These relevant colors allow us to characterize the color palette of a scene and, on this basis, those discernible colors that are colorimetrically different within the scene. We tried to carry out this characterization of the chromatic range of paints according to authors and styles. We used a collection of 4,266 paintings by 91 painters, from which we extracted various parameters that are exclusively colorimetric to characterize the range of colors. After this refinement of the set of selected colors, our algorithm obtained an average number of 18 relevant colors, which partially agreed with the total 11-15 basic color names usually found in other categorical color studies.

Communication efficiency of color naming across languages provides a new framework for the evolution of color terms

Languages vary in their number of color terms. A widely accepted theory proposes that languages evolve, acquiring color terms in a stereotyped sequence. This theory, by Berlin and Kay (BK), is supported by analyzing best exemplars ("focal colors") of basic color terms in the World Color Survey (WCS) of 110 languages. But the instructions of the WCS were complex and the color chips confounded hue and saturation, which likely impacted focal-color selection. In addition, it is now known that even so-called early-stage languages nonetheless have a complete representation of color distributed across the population. These facts undermine the BK theory. Here we revisit the evolution of color terms using original color-naming data obtained with simple instructions in Tsimane', an Amazonian culture that has limited contact with industrialized society. We also collected data in Bolivian-Spanish speakers and English speakers. We discovered that information theory analysis of color-naming data was not influenced by color-chip saturation, which motivated a new analysis of the WCS data. Embedded within a universal pattern in which warm colors (reds, oranges) are always communicated more efficiently than cool colors (blues, greens), as languages increase in overall communicative efficiency about color, some colors undergo greater increases in communication efficiency compared to others. Communication efficiency increases first for yellow, then brown, then purple. The present analyses and results provide a new framework for understanding the evolution of color terms: what varies among cultures is not whether colors are seen differently, but the extent to which color is useful.

Language and Color Perception: Evidence From Mongolian and Chinese Speakers

The present research contributes to the debate in cognitive sentence on the relationship between language and perception by comparing Mongolian and Chinese speakers' color perception. In this study, featuring a free sorting task and a visual search task comparing Mongolian and Chinese performances, the results show that both universal and relativistic forces are at play. Chinese (Mandarin) and Mongolian color terms divide the blue spectrum differently but the green spectrum, similarly. In Mongolian, light blue ("qinker") and dark blue ("huhe") are strictly distinct, while both light green and dark green are described as one word, nogvgan. In Chinese, however, both light blue and dark blue are simply described by one word, lan, and both light green and dark green are described by a single word, lv. The current study used a free-sorting task and a visual search task to investigate whether this linguistic difference between Chinese and Mongolian speakers leads to a difference in color discrimination. In the free-sorting task, compared with Chinese speakers, Mongolian speakers exhibited different sorting in the blue region (by distinguishing light and dark blue) and the same sorting in the green region. Further results showed that Mongolian speakers discriminated visual search displays that fall into different linguistic categories in Mongolian (e.g., qinker or huhe) more quickly than visual search displays that belong to the same linguistic category (e.g., both qinker) in a visual search task. Moreover, this effect was disrupted in Mongolian participants who performed a secondary task engaging involving verbal working memory (but not a task engaging involving spatial working memory), suggested linguistic interference. Chinese (Mandarin) speakers performing the visual search task did not show such a category advantage under any of the conditions. The finding provides support for the Whorf hypothesis with evidence from an Altay language. Meanwhile, both Chinese and Mongolian speakers reacted faster to the green color than the blue color in the visual search task, suggesting that the variation in human color perception is constrained by certain universal forces. The difference in categorical effects between Chinese and Mongolian speakers in the blue region suggests a relativistic aspect of language and color perception, while the speed of visual search in blue and green suggests a universalistic aspect of language and color perception. Thus, our findings suggest that our perception is shaped by both relativistic and universal forces.

Functional MRI in the Nile crocodile: a new avenue for evolutionary neurobiology

Crocodilians are important for understanding the evolutionary history of amniote neural systems as they are the nearest extant relatives of modern birds and share a stem amniote ancestor with mammals. Although the crocodilian brain has been investigated anatomically, functional studies are rare. Here, we employed functional magnetic resonance imaging (fMRI), never tested in poikilotherms, to investigate crocodilian telencephalic sensory processing. Juvenile Crocodylus niloticus were placed in a 7 T MRI scanner to record blood oxygenation level-dependent (BOLD) signal changes during the presentation of visual and auditory stimuli. Visual stimulation increased BOLD signals in rostral to mid-caudal portions of the dorso-lateral anterior dorsal ventricular ridge (ADVR). Simple auditory stimuli led to signal increase in the rostromedial and caudocentral ADVR. These activation patterns are in line with previously described projection fields of diencephalic sensory fibres. Furthermore, complex auditory stimuli activated additional regions of the caudomedial ADVR. The recruitment of these additional, presumably higher-order, sensory areas reflects observations made in birds and mammals. Our results indicate that structural and functional aspects of sensory processing have been likely conserved during the evolution of sauropsids. In addition, our study shows that fMRI can be used to investigate neural processing in poikilotherms, providing a new avenue for neurobiological research in these critical species.

A two-level hierarchical framework of visual short-term memory

Over the last couple of decades, a vast amount of research has been dedicated to understanding the nature and the architecture of visual short-term memory (VSTM), the mechanism by which currently relevant visual information is maintained. According to discrete-capacity models, VSTM is constrained by a limited number of discrete representations held simultaneously. In contrast, shared-resource models regard VSTM as limited in resources, which can be distributed flexibly between varying numbers of representations; and a new interference model posits that capacity is limited by interference among items. In this article, we begin by reviewing benchmark findings regarding the debate over VSTM limitations, focusing on whether VSTM storage is all-or-none and on whether object complexity affects capacity. After that, we put forward a hybrid framework of VSTM architecture, arguing that this system is composed of a two-level hierarchy of memory stores, each containing a different set of representations: (1) perceptual memory, a resourcelike level containing analog automatically formed representations of visual stimuli in varying degrees of activation, and (2) visual working memory, in which a subset of three to four items from perceptual memory are bound to conceptual representations and to their locations, thus conveying discrete (digital/symbolic) information which appears quantized. While perceptual memory has a large capacity and is relatively nonselective, visual working memory is restricted in the number of items that can be maintained simultaneously, and its content is regulated by a gating mechanism.

Human V4 Activity Patterns Predict Behavioral Performance in Imagery of Object Color

Color is special among basic visual features in that it can form a defining part of objects that are engrained in our memory. Whereas most neuroimaging research on human color vision has focused on responses related to external stimulation, the present study investigated how sensory-driven color vision is linked to subjective color perception induced by object imagery. We recorded fMRI activity in male and female volunteers during viewing of abstract color stimuli that were red, green, or yellow in half of the runs. In the other half we asked them to produce mental images of colored, meaningful objects (such as tomato, grapes, banana) corresponding to the same three color categories. Although physically presented color could be decoded from all retinotopically mapped visual areas, only hV4 allowed predicting colors of imagined objects when classifiers were trained on responses to physical colors. Importantly, only neural signal in hV4 was predictive of behavioral performance in the color judgment task on a trial-by-trial basis. The commonality between neural representations of sensory-driven and imagined object color and the behavioral link to neural representations in hV4 identifies area hV4 as a perceptual hub linking externally triggered color vision with color in self-generated object imagery.SIGNIFICANCE STATEMENT Humans experience color not only when visually exploring the outside world, but also in the absence of visual input, for example when remembering, dreaming, and during imagery. It is not known where neural codes for sensory-driven and internally generated hue converge. In the current study we evoked matching subjective color percepts, one driven by physically presented color stimuli, the other by internally generated color imagery. This allowed us to identify area hV4 as the only site where neural codes of corresponding subjective color perception converged regardless of its origin. Color codes in hV4 also predicted behavioral performance in an imagery task, suggesting it forms a perceptual hub for color perception.

Is There a Role for Language in Emotion Perception?

What is the relationship between language, emotion concepts, and perceptual categories? Here I compare the strong Whorfian view of linguistic relativity, which argues that language plays a necessary role in the perception of emotions, to the alternative view that different levels of processing (e.g., linguistic, conceptual, perceptual) are relatively independent and thus, that language does not play a foundational role in emotion perception. I examine neuropsychological studies that have tested strong claims of linguistic relativity, and discuss research on categorical perception of emotional expressions, where the two accounts have been directly tested against each other. As in other perceptual domains, there is little evidence that language plays a foundational role in the perception of emotion.

Hue distinctiveness overrides category in determining performance in multiple object tracking

The visual distinctiveness between targets and distractors can significantly facilitate performance in multiple object tracking (MOT), in which color is a feature that has been commonly used. However, the processing of color can be more than "visual." Color is continuous in chromaticity, while it is commonly grouped into discrete categories (e.g., red, green). Evidence from color perception suggested that color categories may have a unique role in visual tasks independent of its chromatic appearance. Previous MOT studies have not examined the effect of chromatic and categorical distinctiveness on tracking separately. The current study aimed to reveal how chromatic (hue) and categorical distinctiveness of color between the targets and distractors affects tracking performance. With four experiments, we showed that tracking performance was largely facilitated by the increasing hue distance between the target set and the distractor set, suggesting that perceptual grouping was formed based on hue distinctiveness to aid tracking. However, we found no color categorical effect, because tracking performance was not significantly different when the targets and distractors were from the same or different categories. It was concluded that the chromatic distinctiveness of color overrides category in determining tracking performance, suggesting a dominant role of perceptual feature in MOT.

Color naming across languages reflects color use

What determines how languages categorize colors? We analyzed results of the World Color Survey (WCS) of 110 languages to show that despite gross differences across languages, communication of chromatic chips is always better for warm colors (yellows/reds) than cool colors (blues/greens). We present an analysis of color statistics in a large databank of natural images curated by human observers for salient objects and show that objects tend to have warm rather than cool colors. These results suggest that the cross-linguistic similarity in color-naming efficiency reflects colors of universal usefulness and provide an account of a principle (color use) that governs how color categories come about. We show that potential methodological issues with the WCS do not corrupt information-theoretic analyses, by collecting original data using two extreme versions of the color-naming task, in three groups: the Tsimane', a remote Amazonian hunter-gatherer isolate; Bolivian-Spanish speakers; and English speakers. These data also enabled us to test another prediction of the color-usefulness hypothesis: that differences in color categorization between languages are caused by differences in overall usefulness of color to a culture. In support, we found that color naming among Tsimane' had relatively low communicative efficiency, and the Tsimane' were less likely to use color terms when describing familiar objects. Color-naming among Tsimane' was boosted when naming artificially colored objects compared with natural objects, suggesting that industrialization promotes color usefulness.

Colour categories are reflected in sensory stages of colour perception when stimulus issues are resolved

Debate exists about the time course of the effect of colour categories on visual processing. We investigated the effect of colour categories for two groups who differed in whether they categorised a blue-green boundary colour as the same- or different-category to a reliably-named blue colour and a reliably-named green colour. Colour differences were equated in just-noticeable differences to be equally discriminable. We analysed event-related potentials for these colours elicited on a passive visual oddball task and investigated the time course of categorical effects on colour processing. Support for category effects was found 100 ms after stimulus onset, and over frontal sites around 250 ms, suggesting that colour naming affects both early sensory and later stages of chromatic processing.

Biological origins of color categorization

The biological basis of the commonality in color lexicons across languages has been hotly debated for decades. Prior evidence that infants categorize color could provide support for the hypothesis that color categorization systems are not purely constructed by communication and culture. Here, we investigate the relationship between infants' categorization of color and the commonality across color lexicons, and the potential biological origin of infant color categories. We systematically mapped infants' categorical recognition memory for hue onto a stimulus array used previously to document the color lexicons of 110 nonindustrialized languages. Following familiarization to a given hue, infants' response to a novel hue indicated that their recognition memory parses the hue continuum into red, yellow, green, blue, and purple categories. Infants' categorical distinctions aligned with common distinctions in color lexicons and are organized around hues that are commonly central to lexical categories across languages. The boundaries between infants' categorical distinctions also aligned, relative to the adaptation point, with the cardinal axes that describe the early stages of color representation in retinogeniculate pathways, indicating that infant color categorization may be partly organized by biological mechanisms of color vision. The findings suggest that color categorization in language and thought is partially biologically constrained and have implications for broader debate on how biology, culture, and communication interact in human cognition.

Is the Lateralized Categorical Perception of Color a Situational Effect of Language on Color Perception?

This study investigated whether and how a person's varied series of lexical categories corresponding to different discriminatory characteristics of the same colors affect his or her perception of colors. In three experiments, Chinese participants were primed to categorize four graduated colors-specifically dark green, light green, light blue, and dark blue-into green and blue; light color and dark color; and dark green, light green, light blue, and dark blue. The participants were then required to complete a visual search task. Reaction times in the visual search task indicated that different lateralized categorical perceptions (CPs) of color corresponded to the various priming situations. These results suggest that all of the lexical categories corresponding to different discriminatory characteristics of the same colors can influence people's perceptions of colors and that color perceptions can be influenced differently by distinct types of lexical categories depending on the context.

Neural Categorization of Vibrotactile Frequency in Flutter and Vibration Stimulations: An fMRI Study

As the use of wearable haptic devices with vibrating alert features is commonplace, an understanding of the perceptual categorization of vibrotactile frequencies has become important. This understanding can be substantially enhanced by unveiling how neural activity represents vibrotactile frequency information. Using functional magnetic resonance imaging (fMRI), this study investigated categorical clustering patterns of the frequency-dependent neural activity evoked by vibrotactile stimuli with gradually changing frequencies from 20 to 200 Hz. First, a searchlight multi-voxel pattern analysis (MVPA) was used to find brain regions exhibiting neural activities associated with frequency information. We found that the contralateral postcentral gyrus (S1) and the supramarginal gyrus (SMG) carried frequency-dependent information. Next, we applied multidimensional scaling (MDS) to find low-dimensional neural representations of different frequencies obtained from the multi-voxel activity patterns within these regions. The clustering analysis on the MDS results showed that neural activity patterns of 20-100 Hz and 120-200 Hz were divided into two distinct groups. Interestingly, this neural grouping conformed to the perceptual frequency categories found in the previous behavioral studies. Our findings therefore suggest that neural activity patterns in the somatosensory cortical regions may provide a neural basis for the perceptual categorization of vibrotactile frequency.

Colour in the eye of the beholder: receptor sensitivities and neural circuits underlying colour opponency and colour perception

Colour vision-the ability to discriminate spectral differences irrespective of variations in intensity-has two basic requirements: (1) photoreceptors with different spectral sensitivities, and (2) neural comparison of signals from these photoreceptors. Major progress has been made understanding the evolution of the basic stages of colour vision-opsin pigments, screening pigments, and the first neurons coding chromatic opponency, and similarities between mammals and insects point to general mechanisms. However, much work is still needed to unravel full colour pathways in various animals. While primates may have brain regions entirely dedicated to colour coding, animals with small brains, such as insects, likely combine colour information directly in parallel multisensory pathways controlling various behaviours.

Colour Terms Affect Detection of Colour and Colour-Associated Objects Suppressed from Visual Awareness

The idea that language can affect how we see the world continues to create controversy. A potentially important study in this field has shown that when an object is suppressed from visual awareness using continuous flash suppression (a form of binocular rivalry), detection of the object is differently affected by a preceding word prime depending on whether the prime matches or does not match the object. This may suggest that language can affect early stages of vision. We replicated this paradigm and further investigated whether colour terms likewise influence the detection of colours or colour-associated object images suppressed from visual awareness by continuous flash suppression. This method presents rapidly changing visual noise to one eye while the target stimulus is presented to the other. It has been shown to delay conscious perception of a target for up to several minutes. In Experiment 1 we presented greyscale photos of objects. They were either preceded by a congruent object label, an incongruent label, or white noise. Detection sensitivity (d') and hit rates were significantly poorer for suppressed objects preceded by an incongruent label compared to a congruent label or noise. In Experiment 2, targets were coloured discs preceded by a colour term. Detection sensitivity was significantly worse for suppressed colour patches preceded by an incongruent colour term as compared to a congruent term or white noise. In Experiment 3 targets were suppressed greyscale object images preceded by an auditory presentation of a colour term. On congruent trials the colour term matched the object's stereotypical colour and on incongruent trials the colour term mismatched. Detection sensitivity was significantly poorer on incongruent trials than congruent trials. Overall, these findings suggest that colour terms affect awareness of coloured stimuli and colour- associated objects, and provide new evidence for language-perception interaction in the brain.

Accurate rapid averaging of multihue ensembles is due to a limited capacity subsampling mechanism

It is claimed that the extraction of average features from rapidly presented ensembles is holistic, with attention distributed across the whole set. We investigated whether observers' extraction of mean hue is holistic or could reflect subsampling. Analysis of selections for the mean hue revealed a distribution that peaked at the expected mean hue. However, an ideal observer simulation suggested that a subsampling mechanism incorporating just two items from each ensemble would suffice to reproduce the precision of most observers. The results imply that hue may not be averaged as holistically and efficiently as other attributes.

Cortical response to categorical color perception in infants investigated by near-infrared spectroscopy

Perceptual color space is continuous; however, we tend to divide it into only a small number of categories. It is unclear whether categorical color perception is obtained solely through the development of the visual system or whether it is affected by language acquisition. To address this issue, we recruited prelinguistic infants (5- to 7-mo-olds) to measure changes in brain activity in relation to categorical color differences by using near-infrared spectroscopy (NIRS). We presented two sets of geometric figures to infants: One set altered in color between green and blue, and the other set altered between two different shades of green. We found a significant increase in hemodynamic responses during the between-category alternations, but not during the within-category alternations. These differences in hemodynamic response based on categorical relationship were observed only in the bilateral occipitotemporal regions, and not in the occipital region. We confirmed that categorical color differences yield behavioral differences in infants. We also observed comparable hemodynamic responses to categorical color differences in adults. The present study provided the first evidence, to our knowledge, that colors of different categories are represented differently in the visual cortex of prelinguistic infants, which implies that color categories may develop independently before language acquisition.

Functional magnetic resonance imaging adaptation reveals a noncategorical representation of hue in early visual cortex

Color names divide the fine-grained gamut of color percepts into discrete categories. A categorical transition must occur somewhere between the initial encoding of the continuous spectrum of light by the cones and the verbal report of the name of a color stimulus. Here, we used a functional magnetic resonance imaging (fMRI) adaptation experiment to examine the representation of hue in the early visual cortex. Our stimuli varied in hue between blue and green. We found in the early visual areas (V1, V2/3, and hV4) a smoothly increasing recovery from adaptation with increasing hue distance between adjacent stimuli during both passive viewing (Experiment 1) and active categorization (Experiment 2). We examined the form of the adaptation effect and found no evidence that a categorical representation mediates the release from adaptation for stimuli that cross the blue-green color boundary. Examination of the direct effect of stimulus hue on the fMRI response did, however, reveal an enhanced response to stimuli near the blue-green category border. This was largest in hV4 and when subjects were engaged in active categorization of the stimulus hue. In contrast with a recent report from another laboratory (Bird, Berens, Horner, & Franklin, 2014), we found no evidence for a categorical representation of color in the middle frontal gyrus. A post hoc whole-brain analysis, however, revealed several regions in the frontal cortex with a categorical effect in the adaptation response. Overall, our results support the idea that the representation of color in the early visual cortex is primarily fine grained and does not reflect color categories.

Neuron-based heredity and human evolution

It is widely recognized that human evolution has been driven by two systems of heredity: one DNA-based and the other based on the transmission of behaviorally acquired information via nervous system functions. The genetic system is ancient, going back to the appearance of life on Earth. It is responsible for the evolutionary processes described by Darwin. By comparison, the nervous system is relatively newly minted and in its highest form, responsible for ideation and mind-to-mind transmission of information. Here the informational capabilities and functions of the two systems are compared. While employing quite different mechanisms for encoding, storing and transmission of information, both systems perform these generic hereditary functions. Three additional features of neuron-based heredity in humans are identified: the ability to transfer hereditary information to other members of their population, not just progeny; a selection process for the information being transferred; and a profoundly shorter time span for creation and dissemination of survival-enhancing information in a population. The mechanisms underlying neuron-based heredity involve hippocampal neurogenesis and memory and learning processes modifying and creating new neural assemblages changing brain structure and functions. A fundamental process in rewiring brain circuitry is through increased neural activity (use) strengthening and increasing the number of synaptic connections. Decreased activity in circuitry (disuse) leads to loss of synapses. Use and disuse modifying an organ to bring about new modes of living, habits and functions are processes in line with Neolamarckian concepts of evolution (Packard, 1901). Evidence is presented of bipartite evolutionary processes-Darwinian and Neolamarckian-driving human descent from a common ancestor shared with the great apes.