The functional architecture of the ventral temporal cortex and its role in categorization

Development of human visual cortical function: A scoping review of task- and naturalistic-fMRI studies through the interactive specialization and maturational frameworks

Overarching theories such as the interactive specialization and maturational frameworks have been proposed to describe human functional brain development. However, these frameworks have not yet been systematically examined across the fMRI literature. Visual processing is one of the most well-studied fields in neuroimaging, and research in this area has recently expanded to include naturalistic paradigms that facilitate study in younger age ranges, allowing for an in-depth critical appraisal of these frameworks across childhood. To this end, we conducted a scoping review of 94 developmental visual fMRI studies, including both traditional experimental task and naturalistic studies, across multiple sub-domains (early visual processing, category-specific higher order processing, naturalistic visual processing). We found that across domains, many studies reported progressive development, but few studies describe regressive or emergent changes necessary to fit the maturational or interactive specialization frameworks. Our findings suggest a need for the expansion of developmental frameworks and clearer reporting of both progressive and regressive changes, along with well-powered, longitudinal studies.

Reading instruction causes changes in category-selective visual cortex

Education sculpts specialized neural circuits for skills like reading that are critical to success in modern society but were not anticipated by the selective pressures of evolution. Does the emergence of brain regions that selectively process novel visual stimuli like words occur at the expense of cortical representations of other stimuli like faces and objects? "Neuronal Recycling" predicts that learning to read should enhance the response to words in ventral occipitotemporal cortex (VOTC) and decrease the response to other visual categories such as faces and objects. To test this hypothesis, and more broadly to understand the changes that are induced by the early stages of literacy instruction, we conducted a randomized controlled trial with pre-school children (five years of age). Children were randomly assigned to intervention programs focused on either reading skills or oral language skills and magnetoencephalography (MEG) data collected before and after the intervention was used to measure visual responses to images of text, faces, and objects. We found that being taught reading versus oral language skills induced different patterns of change in category-selective regions of visual cortex, but that there was not a clear tradeoff between the response to words versus other categories. Within a predefined region of VOTC corresponding to the visual word form area (VWFA) we found that the relative amplitude of responses to text, faces, and objects changed, but increases in the response to words were not linked to decreases in the response to faces or objects. How these changes play out over a longer timescale is still unknown but, based on these data, we can surmise that high-level visual cortex undergoes rapid changes as children enter school and begin establishing new skills like literacy.

Representations of imaginary scenes and their properties in cortical alpha activity

Imagining natural scenes enables us to engage with a myriad of simulated environments. How do our brains generate such complex mental images? Recent research suggests that cortical alpha activity carries information about individual objects during visual imagery. However, it remains unclear if more complex imagined contents such as natural scenes are similarly represented in alpha activity. Here, we answer this question by decoding the contents of imagined scenes from rhythmic cortical activity patterns. In an EEG experiment, participants imagined natural scenes based on detailed written descriptions, which conveyed four complementary scene properties: openness, naturalness, clutter level and brightness. By conducting classification analyses on EEG power patterns across neural frequencies, we were able to decode both individual imagined scenes as well as their properties from the alpha band, showing that also the contents of complex visual images are represented in alpha rhythms. A cross-classification analysis between alpha power patterns during the imagery task and during a perception task, in which participants were presented images of the described scenes, showed that scene representations in the alpha band are partly shared between imagery and late stages of perception. This suggests that alpha activity mediates the top-down re-activation of scene-related visual contents during imagery.

Perception and Memory Reinstatement Engage Overlapping Face-Selective Regions within Human Ventral Temporal Cortex

Humans have the remarkable ability to vividly retrieve sensory details of past events. According to the theory of sensory reinstatement, during remembering, brain regions specialized for processing specific sensory stimuli are reactivated to support content-specific retrieval. Recently, several studies have emphasized transformations in the spatial organization of these reinstated activity patterns. Specifically, studies of scene stimuli suggest a clear anterior shift in the location of retrieval activations compared with the activity observed during perception. However, it is not clear that such transformations occur universally, with inconsistent evidence for other important stimulus categories, particularly faces. One challenge in addressing this question is the careful delineation of face-selective cortices, which are interdigitated with other selective regions, in configurations that spatially differ across individuals. Therefore, we conducted a multisession neuroimaging study to first carefully map individual participants' (nine males and seven females) face-selective regions within ventral temporal cortex (VTC), followed by a second session to examine the activity patterns within these regions during face memory encoding and retrieval. While face-selective regions were expectedly engaged during face perception at encoding, memory retrieval engagement exhibited a more selective and constricted reinstatement pattern within these regions, but did not show any consistent direction of spatial transformation (e.g., anteriorization). We also report on unique human intracranial recordings from VTC under the same experimental conditions. These findings highlight the importance of considering the complex configuration of category-selective cortex in elucidating principles shaping the neural transformations that occur from perception to memory.

Movement trajectories as a window into the dynamics of emerging neural representations

The rapid transformation of sensory inputs into meaningful neural representations is critical to adaptive human behaviour. While non-invasive neuroimaging methods are the de-facto method for investigating neural representations, they remain expensive, not widely available, time-consuming, and restrictive. Here we show that movement trajectories can be used to measure emerging neural representations with fine temporal resolution. By combining online computer mouse-tracking and publicly available neuroimaging data via representational similarity analysis (RSA), we show that movement trajectories track the unfolding of stimulus- and category-wise neural representations along key dimensions of the human visual system. We demonstrate that time-resolved representational structures derived from movement trajectories overlap with those derived from M/EEG (albeit delayed) and those derived from fMRI in functionally-relevant brain areas. Our findings highlight the richness of movement trajectories and the power of the RSA framework to reveal and compare their information content, opening new avenues to better understand human perception.

Predicting high-level visual areas in the absence of task fMRI

The ventral visual stream is organized into units, or functional regions of interest (fROIs), specialized for processing high-level visual categories. Task-based fMRI scans ("localizers") are typically used to identify each individual's nuanced set of fROIs. The unique landscape of an individual's functional activation may rely in large part on their specialized connectivity patterns; recent studies corroborate this by showing that connectivity can predict individual differences in neural responses. We focus on the ventral visual stream and ask: how well can an individual's resting state functional connectivity localize their fROIs for face, body, scene, and object perception? And are the neural processors for any particular visual category better predicted by connectivity than others, suggesting a tighter mechanistic relationship between connectivity and function? We found, among 18 fROIs predicted from connectivity for each subject, all but one were selective for their preferred visual category. Defining an individual's fROIs based on their connectivity patterns yielded regions that were more selective than regions identified from previous studies or atlases in nearly all cases. Overall, we found that in the absence of a domain-specific localizer task, a 10-min resting state scan can be reliably used for defining these fROIs.

Functional Resilience of the Neural Visual Recognition System Post-Pediatric Occipitotemporal Resection

In the typically developing (TD) brain, neural representations for visual stimulus categories (e.g., faces, objects, and words) emerge in bilateral occipitotemporal cortex (OTC), albeit with weighted asymmetry; in parallel, recognition behavior continues to be refined. A fundamental question is whether two hemispheres are necessary or redundant for the emergence of neural representations and recognition behavior typically distributed across both hemispheres. The rare population of patients undergoing unilateral OTC resection in childhood offers a unique opportunity to evaluate whether neural computations for visual stimulus individuation suffice for recognition with only a single developing OTC. Here, using functional magnetic resonance imaging, we mapped category selectivity (CS) and neural representations for individual stimulus exemplars using repetition suppression (RS) in the non-resected hemisphere of pediatric OTC resection patients (n = 9) and control patients with resection outside of OTC (n = 12), as well as in both hemispheres of TD controls (n = 21). There were no univariate group differences in the magnitude of CS or RS or any multivariate differences (per representational similarity analysis) in neural activation to faces, objects, or words across groups. Notwithstanding their comparable neural profiles, accuracy of OTC resection patients on face and object recognition, but not word recognition, was statistically inferior to that of controls. The comparable neural signature of the OTC resection patients' preserved hemisphere and the other two groups highlights the resilience of the system following damage to the contralateral homologue. Critically, however, a single OTC does not suffice for normal behavior, and, thereby, implicates the necessity for two hemispheres.

A unifying framework for functional organization in early and higher ventral visual cortex

A key feature of cortical systems is functional organization: the arrangement of functionally distinct neurons in characteristic spatial patterns. However, the principles underlying the emergence of functional organization in the cortex are poorly understood. Here, we develop the topographic deep artificial neural network (TDANN), the first model to predict several aspects of the functional organization of multiple cortical areas in the primate visual system. We analyze the factors driving the TDANN's success and find that it balances two objectives: learning a task-general sensory representation and maximizing the spatial smoothness of responses according to a metric that scales with cortical surface area. In turn, the representations learned by the TDANN are more brain-like than in spatially unconstrained models. Finally, we provide evidence that the TDANN's functional organization balances performance with between-area connection length. Our results offer a unified principle for understanding the functional organization of the primate ventral visual system.

Post-retrieval stress impairs subsequent memory depending on hippocampal memory trace reinstatement during reactivation

Upon retrieval, memories can become susceptible to meaningful events, such as stress. Post-retrieval memory changes may be attributed to an alteration of the original memory trace during reactivation-dependent reconsolidation or, alternatively, to the modification of retrieval-related memory traces that impact future remembering. Hence, how post-retrieval memory changes emerge in the human brain is unknown. In a 3-day functional magnetic resonance imaging study, we show that post-retrieval stress impairs subsequent memory depending on the strength of neural reinstatement of the original memory trace during reactivation, driven by the hippocampus and its cross-talk with neocortical representation areas. Comparison of neural patterns during immediate and final memory testing further revealed that successful retrieval was linked to pattern-dissimilarity in controls, suggesting the use of a different trace, whereas stressed participants relied on the original memory representation. These representation changes were again dependent on neocortical reinstatement during reactivation. Our findings show disruptive stress effects on the consolidation of retrieval-related memory traces that support future remembering.

Position- and scale-invariant object-centered spatial localization in monkey frontoparietal cortex dynamically adapts to cognitive demand

Egocentric encoding is a well-known property of brain areas along the dorsal pathway. Different to previous experiments, which typically only demanded egocentric spatial processing during movement preparation, we designed a task where two male rhesus monkeys memorized an on-the-object target position and then planned a reach to this position after the object re-occurred at variable location with potentially different size. We found allocentric (in addition to egocentric) encoding in the dorsal stream reach planning areas, parietal reach region and dorsal premotor cortex, which is invariant with respect to the position, and, remarkably, also the size of the object. The dynamic adjustment from predominantly allocentric encoding during visual memory to predominantly egocentric during reach planning in the same brain areas and often the same neurons, suggests that the prevailing frame of reference is less a question of brain area or processing stream, but more of the cognitive demands.

Assessing Spontaneous Categorical Processing of Visual Shapes via Frequency-Tagging EEG

Categorization is an essential cognitive and perceptual process, which happens spontaneously. However, earlier research often neglected the spontaneous nature of this process by mainly adopting explicit tasks in behavioral or neuroimaging paradigms. Here, we use frequency-tagging (FT) during electroencephalography (EEG) in 22 healthy human participants (both male and female) as a direct approach to pinpoint spontaneous visual categorical processing. Starting from schematic natural visual stimuli, we created morph sequences comprising 11 equal steps. Mirroring a behavioral categorical perception discrimination paradigm, we administered a FT-EEG oddball paradigm, assessing neural sensitivity for equally sized differences within and between stimulus categories. Likewise, mirroring a behavioral category classification paradigm, we administered a sweep FT-EEG oddball paradigm, sweeping from one end of the morph sequence to the other, thereby allowing us to objectively pinpoint the neural category boundary. We found that FT-EEG can implicitly measure categorical processing and discrimination. More specifically, we could derive an objective neural index of the required level to differentiate between the two categories, and this neural index showed the typical marker of categorical perception (i.e., stronger discrimination across as compared with within categories). The neural findings of the implicit paradigms were also validated using an explicit behavioral task. These results provide evidence that FT-EEG can be used as an objective tool to measure discrimination and categorization and that the human brain inherently and spontaneously (without any conscious or decisional processes) uses higher-level meaningful categorization information to interpret ambiguous (morph) shapes.

Investigating lexical categorization in reading based on joint diagnostic and training approaches for language learners

Efficient reading is essential for societal participation, so reading proficiency is a central educational goal. Here, we use an individualized diagnostics and training framework to investigate processes in visual word recognition and evaluate its usefulness for detecting training responders. We (i) motivated a training procedure based on the Lexical Categorization Model (LCM) to introduce the framework. The LCM describes pre-lexical orthographic processing implemented in the left-ventral occipital cortex and is vital to reading. German language learners trained their lexical categorization abilities while we monitored reading speed change. In three studies, most language learners increased their reading skills. Next, we (ii) estimated, for each word, the LCM-based features and assessed each reader's lexical categorization capabilities. Finally, we (iii) explored machine learning procedures to find the optimal feature selection and regression model to predict the benefit of the lexical categorization training for each individual. The best-performing pipeline increased reading speed from 23% in the unselected group to 43% in the machine-selected group. This selection process strongly depended on parameters associated with the LCM. Thus, training in lexical categorization can increase reading skills, and accurate computational descriptions of brain functions that allow the motivation of a training procedure combined with machine learning can be powerful for individualized reading training procedures.

Fast saccades to faces during the feedforward sweep

Saccadic choice tasks use eye movements as a response method, typically in a task where observers are asked to saccade as quickly as possible to an image of a prespecified target category. Using this approach, face-selective saccades have been observed within 100 ms poststimulus. When taking into account oculomotor processing, this suggests that faces can be detected in as little as 70 to 80 ms. It has therefore been suggested that face detection must occur during the initial feedforward sweep, since this latency leaves little time for feedback processing. In the current experiment, we tested this hypothesis using backward masking-a technique shown to primarily disrupt feedback processing while leaving feedforward activation relatively intact. Based on minimum saccadic reaction time, we found that face detection benefited from ultra-fast, accurate saccades within 110 to 160 ms and that these eye movements are obtainable even under extreme masking conditions that limit perceptual awareness. However, masking did significantly increase the median SRT for faces. In the manual responses, we found remarkable detection accuracy for faces and houses, even when participants indicated having no visual experience of the test images. These results provide evidence for the view that the saccadic bias to faces is initiated by coarse information used to categorize faces in the feedforward sweep but that, in most cases, additional processing is required to quickly reach the threshold for saccade initiation.

Distributed representations of behaviorally-relevant object dimensions in the human visual system

Object vision is commonly thought to involve a hierarchy of brain regions processing increasingly complex image features, with high-level visual cortex supporting object recognition and categorization. However, object vision supports diverse behavioral goals, suggesting basic limitations of this category-centric framework. To address these limitations, we mapped a series of behaviorally-relevant dimensions derived from a large-scale analysis of human similarity judgments directly onto the brain. Our results reveal broadly distributed representations of behaviorally-relevant information, demonstrating selectivity to a wide variety of novel dimensions while capturing known selectivities for visual features and categories. Behaviorally-relevant dimensions were superior to categories at predicting brain responses, yielding mixed selectivity in much of visual cortex and sparse selectivity in category-selective clusters. This framework reconciles seemingly disparate findings regarding regional specialization, explaining category selectivity as a special case of sparse response profiles among representational dimensions, suggesting a more expansive view on visual processing in the human brain.

Ventral temporal and posteromedial sulcal morphology in autism spectrum disorder

Two parallel research tracks link the morphology of small and shallow indentations, or sulci, of the cerebral cortex with functional features of the cortex and human cognition, respectively. The first track identified a relationship between the mid-fusiform sulcus (MFS) in ventral temporal cortex (VTC) and cognition in individuals with Autism Spectrum Disorder (ASD). The second track identified a new sulcus, the inframarginal sulcus (IFRMS), that serves as a tripartite landmark within the posteromedial cortex (PMC). As VTC and PMC are structurally and functionally different in ASD, here, we integrated these two tracks and tested if there are morphological differences in VTC and PMC sulci in a sample of young (5-17 years old) male participants (50 participants with ASD and 50 neurotypical controls). Our approach replicates and extends recent findings in four ways. First, regarding replication, the standard deviation (STD) of MFS cortical thickness (CT) was increased in ASD. Second, MFS length was shorter in ASD. Third, the CT STD effect extended to other VTC and to PMC sulci. Fourth, additional morphological features of VTC sulci (depth, surface area, gray matter volume) and PMC sulci (mean CT) were decreased in ASD, including putative tertiary sulci, which emerge last in gestation and continue to develop after birth. To our knowledge, this study is the most extensive comparison of the sulcal landscape (including putative tertiary sulci) in multiple cortical expanses between individuals with ASD and NTs based on manually defined sulci at the level of individual hemispheres, providing novel targets for future studies of neurodevelopmental disorders more broadly.

Characterizing the discriminability of visual categorical information in strongly connected voxels

Functional brain responses are strongly influenced by connectivity. Recently, we demonstrated a major example of this: category discriminability within occipitotemporal cortex (OTC) is enhanced for voxel sets that share strong functional connectivity to distal brain areas, relative to those that share lesser connectivity. That is, within OTC regions, sets of 'most-connected' voxels show improved multivoxel pattern discriminability for tool-, face-, and place stimuli relative to voxels with weaker connectivity to the wider brain. However, understanding whether these effects generalize to other domains (e.g. body perception network), and across different levels of the visual processing streams (e.g. dorsal as well as ventral stream areas) is an important extension of this work. Here, we show that this so-called connectivity-guided decoding (CGD) effect broadly generalizes across a wide range of categories (tools, faces, bodies, hands, places). This effect is robust across dorsal stream areas, but less consistent in earlier ventral stream areas. In the latter regions, category discriminability is generally very high, suggesting that extraction of category-relevant visual properties is less reliant on connectivity to downstream areas. Further, CGD effects are primarily expressed in a category-specific manner: For example, within the network of tool regions, discriminability of tool information is greater than non-tool information. The connectivity-guided decoding approach shown here provides a novel demonstration of the crucial relationship between wider brain connectivity and complex local-level functional responses at different levels of the visual processing streams. Further, this approach generates testable new hypotheses about the relationships between connectivity and local selectivity.

The effects of football juggling learning on executive function and brain functional connectivity

This study aimed to explore the relationship between motor skill learning and executive function (EF), with an emphasis on the potential effects of football juggling learning. A randomized controlled trial involving 111 participants aged 17-19 years was conducted. Participants were randomly assigned to either the football juggling learning (FJL) group or a control group. The FJL group underwent 70 sessions of football juggling learning, while the control group engaged in their normal daily activities without any exercise intervention during the same time frame. Both groups were assessed for EF performance and underwent functional magnetic resonance imaging (fMRI) scans before and after the experiment. The executive function test included three tasks, namely, inhibition, working memory, and shifting. The results showed significant improvement in inhibition and shifting in both groups, and the FJL group showed greater improvement in these aspects of EF compared to the control group. Additionally, in comparison to the control group, the FJL group exhibited increased functional connectivity within the frontal, temporal, and cerebellar regions from the pre-test to the post-test. Notably, enhanced functional connectivity between the right superior temporal gyrus (posterior division) and left cerebellum 6 was identified in the FJL group and was associated with improved EF performance induced by football juggling learning. These findings shed light on the potential causal relationship between motor skill learning, EF, and brain plasticity. Importantly, our study provides preliminary evidence supporting the use of motor skill learning, such as football juggling, as a potential avenue for cognitive enhancement.

Additive effects of emotional expression and stimulus size on the perception of genuine and artificial facial expressions: an ERP study

Seeing an angry individual in close physical proximity can not only result in a larger retinal representation of that individual and an enhanced resolution of emotional cues, but may also increase motivation for rapid visual processing and action preparation. The present study investigated the effects of stimulus size and emotional expression on the perception of happy, angry, non-expressive, and scrambled faces. We analyzed event-related potentials (ERPs) and behavioral responses of N = 40 participants who performed a naturalness classification task on real and artificially created facial expressions. While the emotion-related effects on accuracy for recognizing authentic expressions were modulated by stimulus size, ERPs showed only additive effects of stimulus size and emotional expression, with no significant interaction with size. This contrasts with previous research on emotional scenes and words. Effects of size were present in all included ERPs, whereas emotional expressions affected the N170, EPN, and LPC, irrespective of size. These results imply that the decoding of emotional valence in faces can occur even for small stimuli. Supra-additive effects in faces may necessitate larger size ranges or dynamic stimuli that increase arousal.

Visual mental imagery: Evidence for a heterarchical neural architecture

Theories of Visual Mental Imagery (VMI) emphasize the processes of retrieval, modification, and recombination of sensory information from long-term memory. Yet, only few studies have focused on the behavioral mechanisms and neural correlates supporting VMI of stimuli from different semantic domains. Therefore, we currently have a limited understanding of how the brain generates and maintains mental representations of colors, faces, shapes - to name a few. Such an undetermined scenario renders unclear the organizational structure of neural circuits supporting VMI, including the role of the early visual cortex. We aimed to fill this gap by reviewing the scientific literature of five semantic domains: visuospatial, face, colors, shapes, and letters imagery. Linking theory to evidence from over 60 different experimental designs, this review highlights three main points. First, there is no consistent activity in the early visual cortex across all VMI domains, contrary to the prediction of the dominant model. Second, there is consistent activity of the frontoparietal networks and the left hemisphere's fusiform gyrus during voluntary VMI irrespective of the semantic domain investigated. We propose that these structures are part of a domain-general VMI sub-network. Third, domain-specific information engages specific regions of the ventral and dorsal cortical visual pathways. These regions partly overlap with those found in visual perception studies (e.g., fusiform face area for faces imagery; lingual gyrus for color imagery). Altogether, the reviewed evidence suggests the existence of domain-general and domain-specific mechanisms of VMI selectively engaged by stimulus-specific properties (e.g., colors or faces). These mechanisms would be supported by an organizational structure mixing vertical and horizontal connections (heterarchy) between sub-networks for specific stimulus domains. Such a heterarchical organization of VMI makes different predictions from current models of VMI as reversed perception. Our conclusions set the stage for future research, which should aim to characterize the spatiotemporal dynamics and interactions among key regions of this architecture giving rise to visual mental images.

Sulcal variability in anterior lateral prefrontal cortex contributes to variability in reasoning performance among young adults

Identifying structure-function correspondences is a major goal among biologists, cognitive neuroscientists, and brain mappers. Recent studies have identified relationships between performance on cognitive tasks and the presence or absence of small, shallow indentations, or sulci, of the human brain. Building on the previous finding that the presence of the ventral para-intermediate frontal sulcus (pimfs-v) in the left anterior lateral prefrontal cortex (aLPFC) was related to reasoning task performance in children and adolescents, we tested whether this relationship extended to a different sample, age group, and reasoning task. As predicted, the presence of this aLPFC sulcus was also associated with higher reasoning scores in young adults (ages 22-36). These findings have not only direct developmental, but also evolutionary relevance-as recent work shows that the pimfs-v is exceedingly rare in chimpanzees. Thus, the pimfs-v is a key developmental, cognitive, and evolutionarily relevant feature that should be considered in future studies examining how the complex relationships among multiscale anatomical and functional features of the brain give rise to abstract thought.

THINGSplus: New norms and metadata for the THINGS database of 1854 object concepts and 26,107 natural object images

To study visual and semantic object representations, the need for well-curated object concepts and images has grown significantly over the past years. To address this, we have previously developed THINGS, a large-scale database of 1854 systematically sampled object concepts with 26,107 high-quality naturalistic images of these concepts. With THINGSplus, we significantly extend THINGS by adding concept- and image-specific norms and metadata for all 1854 concepts and one copyright-free image example per concept. Concept-specific norms were collected for the properties of real-world size, manmadeness, preciousness, liveliness, heaviness, naturalness, ability to move or be moved, graspability, holdability, pleasantness, and arousal. Further, we provide 53 superordinate categories as well as typicality ratings for all their members. Image-specific metadata includes a nameability measure, based on human-generated labels of the objects depicted in the 26,107 images. Finally, we identified one new public domain image per concept. Property (M = 0.97, SD = 0.03) and typicality ratings (M = 0.97, SD = 0.01) demonstrate excellent consistency, with the subsequently collected arousal ratings as the only exception (r = 0.69). Our property (M = 0.85, SD = 0.11) and typicality (r = 0.72, 0.74, 0.88) data correlated strongly with external norms, again with the lowest validity for arousal (M = 0.41, SD = 0.08). To summarize, THINGSplus provides a large-scale, externally validated extension to existing object norms and an important extension to THINGS, allowing detailed selection of stimuli and control variables for a wide range of research interested in visual object processing, language, and semantic memory.

The transition from vision to language: Distinct patterns of functional connectivity for subregions of the visual word form area

Reading entails transforming visual symbols to sound and meaning. This process depends on specialized circuitry in the visual cortex, the visual word form area (VWFA). Recent findings suggest that this text-selective cortex comprises at least two distinct subregions: the more posterior VWFA-1 is sensitive to visual features, while the more anterior VWFA-2 processes higher level language information. Here, we explore whether these two subregions also exhibit different patterns of functional connectivity. To this end, we capitalize on two complementary datasets: Using the Natural Scenes Dataset (NSD), we identify text-selective responses in high-quality 7T adult data (N = 8), and investigate functional connectivity patterns of VWFA-1 and VWFA-2 at the individual level. We then turn to the Healthy Brain Network (HBN) database to assess whether these patterns replicate in a large developmental sample (N = 224; age 6-20 years), and whether they relate to reading development. In both datasets, we find that VWFA-1 is primarily correlated with bilateral visual regions. In contrast, VWFA-2 is more strongly correlated with language regions in the frontal and lateral parietal lobes, particularly the bilateral inferior frontal gyrus. Critically, these patterns do not generalize to adjacent face-selective regions, suggesting a specific relationship between VWFA-2 and the frontal language network. No correlations were observed between functional connectivity and reading ability. Together, our findings support the distinction between subregions of the VWFA, and suggest that functional connectivity patterns in the ventral temporal cortex are consistent over a wide range of reading skills.

Curiosity: primate neural circuits for novelty and information seeking

For many years, neuroscientists have investigated the behavioural, computational and neurobiological mechanisms that support value-based decisions, revealing how humans and animals make choices to obtain rewards. However, many decisions are influenced by factors other than the value of physical rewards or second-order reinforcers (such as money). For instance, animals (including humans) frequently explore novel objects that have no intrinsic value solely because they are novel and they exhibit the desire to gain information to reduce their uncertainties about the future, even if this information cannot lead to reward or assist them in accomplishing upcoming tasks. In this Review, I discuss how circuits in the primate brain responsible for detecting, predicting and assessing novelty and uncertainty regulate behaviour and give rise to these behavioural components of curiosity. I also briefly discuss how curiosity-related behaviours arise during postnatal development and point out some important reasons for the persistence of curiosity across generations.

Getting LOST: A conceptual framework for supporting and enhancing spatial navigation in aging

Spatial navigation is more difficult and effortful for older than younger individuals, a shift which occurs for a variety of neurological, physical, and cognitive reasons associated with aging. Despite a large body of evidence documenting age-related deficits in spatial navigation, comparatively less research addresses how to facilitate more effective navigation behavior for older adults. Since navigation challenges arise for a variety of reasons in old age, a one-size-fits-all solution is unlikely to work. Here, we introduce a framework for the variety of spatial navigation challenges faced in aging, which we call LOST-Location, Orientation, Spatial mapping, and Transit. The LOST framework builds on evidence from the cognitive neuroscience of spatial navigation, which reveals distinct components underpinning human wayfinding. We evaluate research on navigational aids-devices and depictions-which help people find their way around; and we reflect on how navigation aids solve (or fail to solve) specific wayfinding difficulties faced by older adults. In summary, we emphasize a bespoke approach to improving spatial navigation in aging, which focuses on tailoring navigation solutions to specific navigation challenges. Our hope is that by providing precise support to older navigators, navigation opportunities can facilitate independence and exploration, while minimizing the danger of becoming lost. We conclude by delineating critical knowledge gaps in how to improve older adults' spatial navigation capacities that the novel LOST framework could guide to address. This article is categorized under: Psychology > Development and Aging Neuroscience > Cognition Neuroscience > Behavior.

Graspable foods and tools elicit similar responses in visual cortex

Extrastriatal visual cortex is known to exhibit distinct response profiles to complex stimuli of varying ecological importance (e.g., faces, scenes, and tools). The dominant interpretation of these effects is that they reflect activation of distinct "category-selective" brain regions specialized to represent these and other stimulus categories. We sought to explore an alternative perspective: that the response to these stimuli is determined less by whether they form distinct categories, and more by their relevance to different forms of natural behavior. In this regard, food is an interesting test case, since it is primarily distinguished from other objects by its edibility, not its appearance, and there is evidence of food-selectivity in human visual cortex. Food is also associated with a common behavior, eating, and food consumption typically also involves the manipulation of food, often with the hands. In this context, food items share many properties in common with tools: they are graspable objects that we manipulate in self-directed and stereotyped forms of action. Thus, food items may be preferentially represented in extrastriatal visual cortex in part because of these shared affordance properties, rather than because they reflect a wholly distinct kind of category. We conducted fMRI and behavioral experiments to test this hypothesis. We found that behaviorally graspable food items and tools were judged to be similar in their action-related properties, and that the location, magnitude, and patterns of neural responses for images of graspable food items were similar in profile to the responses for tool stimuli. Our findings suggest that food-selectivity may reflect the behavioral affordances of food items rather than a distinct form of category-selectivity.

Mechanisms underlying category learning in the human ventral occipito-temporal cortex

The human ventral occipito-temporal cortex (VOTC) has evolved into specialized regions that process specific categories, such as words, tools, and animals. The formation of these areas is driven by bottom-up visual and top-down nonvisual experiences. However, the specific mechanisms through which top-down nonvisual experiences modulate category-specific regions in the VOTC are still unknown. To address this question, we conducted a study in which participants were trained for approximately 13 h to associate three sets of novel meaningless figures with different top-down nonvisual features: the wordlike category with word features, the non-wordlike category with nonword features, and the visual familiarity condition with no nonvisual features. Pre- and post-training functional MRI (fMRI) experiments were used to measure brain activity during stimulus presentation. Our results revealed that training induced a categorical preference for the two training categories within the VOTC. Moreover, the locations of two training category-specific regions exhibited a notable overlap. Remarkably, within the overlapping category-specific region, training resulted in a dissociation in activation intensity and pattern between the two training categories. These findings provide important insights into how different nonvisual categorical information is encoded in the human VOTC.

Category-based attention facilitates memory search

We often need to decide whether the object we look at is also the object we look for. When we look for one specific object, this process can be facilitated by feature-based attention. However, when we look for many objects at the same time (e.g., the products on our shopping list) such a strategy may no longer be possible, as research has shown that we can actively prepare to detect only one or two objects at a time. Therefore, looking for multiple objects additionally requires long-term memory search, slowing down decision making. Interestingly, however, previous research has shown that distractor objects can be efficiently rejected during memory search when they are from a different category than the items in the memory set. Here, using EEG, we show that this efficiency is supported by top-down attention at the category level. In Experiment 1, human participants (both sexes) performed a memory search task on individually presented objects from different categories, most of which were distractors. We observed category-level attentional modulation of distractor processing from ∼150 ms after stimulus onset, expressed both as an evoked response modulation and as an increase in decoding accuracy of same-category distractors. In Experiment 2, memory search was performed on two concurrently presented objects. When both objects were distractors, spatial attention (indexed by the N2pc component) was directed to the object that was of the same category as the objects in the memory set. Together, these results demonstrate how top-down attention can facilitate memory search.Significance statement When we are in the supermarket, we repeatedly decide whether a product we look at (e.g., a banana) is on our memorized shopping list (e.g., apples, oranges, kiwis). This requires searching our memory, which takes time. However, when the product is of an entirely different category (e.g., dairy instead of fruit), the decision can be made quickly. Here, we used EEG to show that this between-category advantage in memory search tasks is supported by top-down attentional modulation of visual processing: The visual response evoked by distractor objects was modulated by category membership, and spatial attention was quickly directed to the location of within-category (vs. between-category) distractors. These results demonstrate a close link between attention and memory.

Functional and representational differences between bilateral inferior temporal numeral areas

The processing of numerals as visual objects is supported by an "Inferior Temporal Numeral Area" (ITNA) in the bilateral inferior temporal gyri (ITG). Extant findings suggest some degree of hemispheric asymmetry in how the bilateral ITNAs process numerals. Pollack and Price (2019) reported such a hemispheric asymmetry by which a region in the left ITG was sensitive to digits during a visual search for a digit among letters, and a homologous region in the right ITG that showed greater digit sensitivity in individuals with higher calculation skills. However, the ITG regions were localized with separate analyses without directly contrasting their digit sensitivities and relation to calculation skills. So, the extent of and reasons for these functional asymmetries remain unclear. Here we probe whether the functional and representational properties of the ITNAs are asymmetric by applying both univariate and multivariate region-of-interest analyses to Pollack and Price's (2019) data. Contrary to the implications of the original findings, digit sensitivity did not differ between ITNAs, and digit sensitivity in both left and right ITNAs was associated with calculation skills. Representational similarity analyses revealed that the overall representational geometries of digits in the ITNAs were also correlated, albeit weakly, but the representational contents of the ITNAs were largely inconclusive. Nonetheless, we found a right lateralization in engagement in alphanumeric categorization, and that the right ITNA showed greater discriminability between digits and letters. Greater right lateralization of digit sensitivity and digit discriminability in the left ITNA were also related to higher calculation skills. Our findings thus suggest that the ITNAs may not be functionally identical and should be directly contrasted in future work. Our study also highlights the importance of within-individual comparisons for understanding hemispheric asymmetries, and analyses of individual differences and multivariate features to uncover effects that would otherwise be obscured by averages.

Category-Selective Representation of Relationships in the Visual Cortex

Understanding social interaction requires processing social agents and their relationships. The latest results show that much of this process is visually solved: visual areas can represent multiple people encoding emergent information about their interaction that is not explained by the response to the individuals alone. A neural signature of this process is an increased response in visual areas, to face-to-face (seemingly interacting) people, relative to people presented as unrelated (back-to-back). This effect highlighted a network of visual areas for representing relational information. How is this network organized? Using functional MRI, we measured the brain activity of healthy female and male humans (N = 42), in response to images of two faces or two (head-blurred) bodies, facing toward or away from each other. Taking the facing > non-facing effect as a signature of relation perception, we found that relations between faces and between bodies were coded in distinct areas, mirroring the categorical representation of faces and bodies in the visual cortex. Additional analyses suggest the existence of a third network encoding relations between (nonsocial) objects. Finally, a separate occipitotemporal network showed the generalization of relational information across body, face, and nonsocial object dyads (multivariate pattern classification analysis), revealing shared properties of relations across categories. In sum, beyond single entities, the visual cortex encodes the relations that bind multiple entities into relationships; it does so in a category-selective fashion, thus respecting a general organizing principle of representation in high-level vision. Visual areas encoding visual relational information can reveal the processing of emergent properties of social (and nonsocial) interaction, which trigger inferential processes.

Both mOTS-words and pOTS-words prefer emoji stimuli over text stimuli during a reading task

The visual word form area in the occipitotemporal sulcus (OTS), here referred to as OTS-words, responds more strongly to text than other visual stimuli and is crucial for reading. We hypothesized, that this text preference may be driven by a preference for reading tasks, as in most prior fMRI studies only the text stimuli were readable. Hence, we performed three fMRI experiments (N=15) and systematically varied the participant's task and the stimulus, investigating mOTS-words and pOTS-words subregions. In experiment 1, we contrasted text stimuli with non-readable visual stimuli (faces, limbs, houses, objects). Experiment 2 utilized an fMRI adaptation paradigm, presenting compound words in text or emoji formats. In experiment 3, participants performed a reading or a color task on compound words in text or emoji format. Using experiment 1 data, we identified mOTS-words and pOTS-words by contrasting texts with non-readable stimuli. In experiment 2, pOTS-words, but not mOTS-words, showed fMRI adaptation for compound words in both text and emoji formats. In experiment 3, surprisingly, both subregions showed higher responses to compound words in emoji than text format. Moreover, mOTS-words showed higher responses during the reading than the color task and a task-stimulus interaction. Multivariate analyses revealed that distributed responses in pOTS-words encode the visual stimulus, while responses in mOTS-words encode both stimulus and task. Together, our findings suggest that the function of the OTS-words subregions goes beyond the specific visual processing of text and that these regions are flexibly recruited whenever semantic meaning needs to be assigned to visual input.

The Role of Agentive and Physical Forces in the Neural Representation of Motion Events

How does the brain represent information about motion events in relation to agentive and physical forces? In this study, we investigated the neural activity patterns associated with observing animated actions of agents (e.g., an agent hitting a chair) in comparison to similar movements of inanimate objects that were either shaped solely by the physics of the scene (e.g., gravity causing an object to fall down a hill and hit a chair) or initiated by agents (e.g., a visible agent causing an object to hit a chair). Using an fMRI-based multivariate pattern analysis (MVPA), this design allowed testing where in the brain the neural activity patterns associated with motion events change as a function of, or are invariant to, agentive versus physical forces behind them. A total of 29 human participants (nine male) participated in the study. Cross-decoding revealed a shared neural representation of animate and inanimate motion events that is invariant to agentive or physical forces in regions spanning frontoparietal and posterior temporal cortices. In contrast, the right lateral occipitotemporal cortex showed a higher sensitivity to agentive events, while the left dorsal premotor cortex was more sensitive to information about inanimate object events that were solely shaped by the physics of the scene.

Rethinking cortical recycling in ventral temporal cortex

High-level visual areas in ventral temporal cortex (VTC) support recognition of important categories, such as faces and words. Word-selective regions are left lateralized and emerge at the onset of reading instruction. Face-selective regions are right lateralized and have been documented in infancy. Prevailing theories suggest that face-selective regions become right lateralized due to competition with word-selective regions in the left hemisphere. However, recent longitudinal studies examining face- and word-selective responses in childhood do not provide support for this theory. Instead, there is evidence that word representations recycle cortex previously involved in processing other stimuli, such as limbs. These findings call for more longitudinal investigations of cortical recycling and a new era of work that links visual experience and behavior with neural responses.

Visual Functions Are Associated with Biomarker Changes in Alzheimer's Disease

Background

While various biomarkers of Alzheimer's disease (AD) have been associated with general cognitive function, their association to visual-perceptive function across the AD spectrum warrant more attention due to its significant impact on quality of life. Thus, this study explores how AD biomarkers are associated with decline in this cognitive domain.

Objective

To explore associations between various fluid and imaging biomarkers and visual-based cognitive assessments in participants across the AD spectrum.

Methods

Data from participants (N = 1,460) in the Alzheimer's Disease Neuroimaging Initiative were analyzed, including fluid and imaging biomarkers. Along with the Mini-Mental State Examination (MMSE), three specific visual-based cognitive tests were investigated: Trail Making Test (TMT) A and TMT B, and the Boston Naming Test (BNT). Locally estimated scatterplot smoothing curves and Pearson correlation coefficients were used to examine associations.

Results

MMSE showed the strongest correlations with most biomarkers, followed by TMT-B. The p-tau181/Aβ1-42 ratio, along with the volume of the hippocampus and entorhinal cortex, had the strongest associations among the biomarkers.

Conclusions

Several biomarkers are associated with visual processing across the disease spectrum, emphasizing their potential in assessing disease severity and contributing to progression models of visual function and cognition.

Longitudinal development of category representations in ventral temporal cortex predicts word and face recognition

Regions in ventral temporal cortex that are involved in visual recognition of categories like words and faces undergo differential development during childhood. However, categories are also represented in distributed responses across high-level visual cortex. How distributed category representations develop and if this development relates to behavioral changes in recognition remains largely unknown. Here, we used functional magnetic resonance imaging to longitudinally measure the development of distributed responses across ventral temporal cortex to 10 categories in school-age children over several years. Our results reveal both strengthening and weakening of category representations with age, which was mainly driven by changes across category-selective voxels. Representations became particularly more distinct for words in the left hemisphere and for faces bilaterally. Critically, distinctiveness for words and faces across category-selective voxels in left and right lateral ventral temporal cortex, respectively, predicted individual children's word and face recognition performance. These results suggest that the development of distributed representations in ventral temporal cortex has behavioral ramifications and advance our understanding of prolonged cortical development during childhood.

The Representation of Observed Actions at the Subordinate, Basic, and Superordinate Level

Actions can be planned and recognized at different hierarchical levels, ranging from very specific (e.g., to swim backstroke) to very broad (e.g., locomotion). Understanding the corresponding neural representation is an important prerequisite to reveal how our brain flexibly assigns meaning to the world around us. To address this question, we conducted an event-related fMRI study in male and female human participants in which we examined distinct representations of observed actions at the subordinate, basic and superordinate level. Using multiple regression representational similarity analysis (RSA) in predefined regions of interest, we found that the three different taxonomic levels were best captured by patterns of activations in bilateral lateral occipitotemporal cortex (LOTC), showing the highest similarity with the basic level model. A whole-brain multiple regression RSA revealed that information unique to the basic level was captured by patterns of activation in dorsal and ventral portions of the LOTC and in parietal regions. By contrast, the unique information for the subordinate level was limited to bilateral occipitotemporal cortex, while no single cluster was obtained that captured unique information for the superordinate level. The behaviorally established action space was best captured by patterns of activation in the LOTC and superior parietal cortex, and the corresponding neural patterns of activation showed the highest similarity with patterns of activation corresponding to the basic level model. Together, our results suggest that occipitotemporal cortex shows a preference for the basic level model, with flexible access across the subordinate and the basic level.SIGNIFICANCE STATEMENT The human brain captures information at varying levels of abstraction. It is debated which brain regions host representations across different hierarchical levels, with some studies emphasizing parietal and premotor regions, while other studies highlight the role of the lateral occipitotemporal cortex (LOTC). To shed light on this debate, here we examined the representation of observed actions at the three taxonomic levels suggested by Rosch et al. (1976) Our results highlight the role of the LOTC, which hosts a shared representation across the subordinate and the basic level, with the highest similarity with the basic level model. These results shed new light on the hierarchical organization of observed actions and provide insights into the neural basis underlying the basic level advantage.

Cross-movie prediction of individualized functional topography

Participant-specific, functionally defined brain areas are usually mapped with functional localizers and estimated by making contrasts between responses to single categories of input. Naturalistic stimuli engage multiple brain systems in parallel, provide more ecologically plausible estimates of real-world statistics, and are friendly to special populations. The current study shows that cortical functional topographies in individual participants can be estimated with high fidelity from naturalistic stimuli. Importantly, we demonstrate that robust, individualized estimates can be obtained even when participants watched different movies, were scanned with different parameters/scanners, and were sampled from different institutes across the world. Our results create a foundation for future studies that allow researchers to estimate a broad range of functional topographies based on naturalistic movies and a normative database, making it possible to integrate high-level cognitive functions across datasets from laboratories worldwide.

Multi-voxel neuro-reinforcement changes resting-state functional connectivity: A pilot study

Background

Multi-voxel neuro-reinforcement has been shown to selectively reduce amygdala reactivity in response to feared stimuli, but the precise mechanisms supporting these effects are still unknown. The current pilot study seeks to identify potential intermediaries of change using functional brain connectivity at rest.

Methods

Individuals (N = 11) diagnosed with at least two animal subtype specific phobias took part in a double-blind multi-voxel neuro-reinforcement clinical trial targeting one of two phobic animals, with the untargeted animal as placebo control. Changes in whole-brain resting state functional connectivity from pre-treatment to post-treatment were measured using group ICA. These changes were tested to see if they predicted the previously observed decreases in amygdala reactivity in response to images of target phobic animals.

Results

A common functional connectivity network overlapping with the visual network was identified in resting state data pre-treatment and post-treatment. Significant increases in functional connectivity in this network from pre-treatment to post-treatment were found in higher level visual and cognitive processing regions of the brain. Increases in functional connectivity in these regions also significantly predicted decreases in task-based amygdala reactivity to targeted phobic animals following multi-voxel neuro-reinforcement. Specifically, greater increases of functional connectivity pre-treatment to post-treatment were associated with greater decreases of amygdala reactivity to target phobic stimuli pre-treatment to post-treatment.

Conclusions

These findings provide preliminary evidence that multi-voxel neuro-reinforcement can induce persisting functional connectivity changes in the brain. Moreover, these changes in functional connectivity were not limited to the direct area of neuro-reinforcement, suggesting neuro-reinforcement may change how the targeted region interacts with other brain regions. Identification of these brain regions represent a first step towards explaining the underlying mechanisms of change in previous multi-voxel neuro-reinforcement studies. Future research should seek to replicate these effects in a larger sample size to further assess their role in the effects observed from multi-voxel neuro-reinforcement.

A personalized cortical atlas for functional regions of interest

Advances in functional MRI (fMRI) allow mapping an individual's brain function in vivo. Task fMRI can localize domain-specific regions of cognitive processing or functional regions of interest (fROIs) within an individual. Moreover, data from resting state (no task) fMRI can be used to define an individual's connectome, which can characterize that individual's functional organization via connectivity-based parcellations. However, can connectivity-based parcellations alone predict an individual's fROIs? Here, we describe an approach to compute individualized rs-fROIs (i.e., regions that correspond to given fROI constructed using only resting state data) for motor control, working memory, high-level vision, and language comprehension. The rs-fROIs were computed and validated using a large sample of young adults (n = 1,018) with resting state and task fMRI from the Human Connectome Project. First, resting state parcellations were defined across a sequence of resolutions from broadscale to fine-grained networks in a training group of 500 individuals. Second, 21 rs-fROIs were defined from the training group by identifying the rs network that most closely matched task-defined fROIs across all individuals. Third, the selectivity of rs-fROIs was investigated in a training set of the remaining 518 individuals. All computed rs-fROIs were indeed selective for their preferred category. Critically, the rs-fROIs had higher selectivity than probabilistic atlas parcels for nearly all fROIs. In conclusion, we present a potential approach to define selective fROIs on an individual-level circumventing the need for multiple task-based localizers.NEW & NOTEWORTHY We compute individualized resting state parcels that identify an individual's own functional regions of interest (fROIs) for high-level vision, language comprehension, motor control, and working memory, using only their functional connectome. This approach demonstrates a rapid and powerful alternative for finding a large set of fROIs in an individual, using only their unique connectivity pattern, which does not require the costly acquisition of multiple fMRI localizer tasks.

Architecture of the brain's visual system enhances network stability and performance through layers, delays, and feedback

In the visual system of primates, image information propagates across successive cortical areas, and there is also local feedback within an area and long-range feedback across areas. Recent findings suggest that the resulting temporal dynamics of neural activity are crucial in several vision tasks. In contrast, artificial neural network models of vision are typically feedforward and do not capitalize on the benefits of temporal dynamics, partly due to concerns about stability and computational costs. In this study, we focus on recurrent networks with feedback connections for visual tasks with static input corresponding to a single fixation. We demonstrate mathematically that a network's dynamics can be stabilized by four key features of biological networks: layer-ordered structure, temporal delays between layers, longer distance feedback across layers, and nonlinear neuronal responses. Conversely, when feedback has a fixed distance, one can omit delays in feedforward connections to achieve more efficient artificial implementations. We also evaluated the effect of feedback connections on object detection and classification performance using standard benchmarks, specifically the COCO and CIFAR10 datasets. Our findings indicate that feedback connections improved the detection of small objects, and classification performance became more robust to noise. We found that performance increased with the temporal dynamics, not unlike what is observed in core vision of primates. These results suggest that delays and layered organization are crucial features for stability and performance in both biological and artificial recurrent neural networks.

Brain Representation of Animal and Non-Animal Images in Patients with Mild Cognitive Impairment and Alzheimer's Disease

Background

In early Alzheimer's disease (AD), high-level visual functions and processing speed are impacted. Few functional magnetic resonance imaging (fMRI) studies have investigated high-level visual deficits in AD, yet none have explored brain activity patterns during rapid animal/non-animal categorization tasks.

Objective

To address this, we utilized the previously known Integrated Cognitive Assessment (ICA) to collect fMRI data and compare healthy controls (HC) to individuals with mild cognitive impairment (MCI) and mild AD.

Methods

The ICA encompasses a rapid visual categorization task that involves distinguishing between animals and non-animals within natural scenes. To comprehensively explore variations in brain activity levels and patterns, we conducted both univariate and multivariate analyses of fMRI data.

Results

The ICA task elicited activation across a range of brain regions, encompassing the temporal, parietal, occipital, and frontal lobes. Univariate analysis, which compared responses to animal versus non-animal stimuli, showed no significant differences in the regions of interest (ROIs) across all groups, with the exception of the left anterior supramarginal gyrus in the HC group. In contrast, multivariate analysis revealed that in both HC and MCI groups, several regions could differentiate between animals and non-animals based on distinct patterns of activity. Notably, such differentiation was absent within the mild AD group.

Conclusions

Our study highlights the ICA task's potential as a valuable cognitive assessment tool designed for MCI and AD. Additionally, our use of fMRI pattern analysis provides valuable insights into the complex changes in brain function associated with AD. This approach holds promise for enhancing our understanding of the disease's progression.

Mapping the evolution of regional brain network efficiency and its association with cognitive abilities during the first twenty-eight months of life

Human brain undergoes rapid growth during the first few years of life. While previous research has employed graph theory to study early brain development, it has mostly focused on the topological attributes of the whole brain. However, examining regional graph-theory features may provide unique insights into the development of cognitive abilities. Utilizing a large and longitudinal rsfMRI dataset from the UNC/UMN Baby Connectome Project, we investigated the developmental trajectories of regional efficiency and evaluated the relationships between these changes and cognitive abilities using Mullen Scales of Early Learning during the first twenty-eight months of life. Our results revealed a complex and spatiotemporally heterogeneous development pattern of regional global and local efficiency during this age period. Furthermore, we found that the trajectories of the regional global efficiency at the left temporal occipital fusiform and bilateral occipital fusiform gyri were positively associated with cognitive abilities, including visual reception, expressive language, receptive language, and early learning composite scores (P < 0.05, FDR corrected). However, these associations were weakened with age. These findings offered new insights into the regional developmental features of brain topologies and their associations with cognition and provided evidence of ongoing optimization of brain networks at both whole-brain and regional levels.

High-dimensional topographic organization of visual features in the primate temporal lobe

The inferotemporal cortex supports our supreme object recognition ability. Numerous studies have been conducted to elucidate the functional organization of this brain area, but there are still important questions that remain unanswered, including how this organization differs between humans and non-human primates. Here, we use deep neural networks trained on object categorization to construct a 25-dimensional space of visual features, and systematically measure the spatial organization of feature preference in both male monkey brains and human brains using fMRI. These feature maps allow us to predict the selectivity of a previously unknown region in monkey brains, which is corroborated by additional fMRI and electrophysiology experiments. These maps also enable quantitative analyses of the topographic organization of the temporal lobe, demonstrating the existence of a pair of orthogonal gradients that differ in spatial scale and revealing significant differences in the functional organization of high-level visual areas between monkey and human brains.

Adding Meaning to Memories: How Parietal Cortex Combines Semantic Content with Episodic Experience

Neuroimaging studies of human memory have consistently found that univariate responses in parietal cortex track episodic experience with stimuli (whether stimuli are 'old' or 'new'). More recently, pattern-based fMRI studies have shown that parietal cortex also carries information about the semantic content of remembered experiences. However, it is not well understood how memory-based and content-based signals are integrated within parietal cortex. Here, in humans (males and females), we used voxel-wise encoding models and a recognition memory task to predict the fMRI activity patterns evoked by complex natural scene images based on (1) the episodic history and (2) the semantic content of each image. Models were generated and compared across distinct subregions of parietal cortex and for occipitotemporal cortex. We show that parietal and occipitotemporal regions each encode memory and content information, but they differ in how they combine this information. Among parietal subregions, angular gyrus was characterized by robust and overlapping effects of memory and content. Moreover, subject-specific semantic tuning functions revealed that successful recognition shifted the amplitude of tuning functions in angular gyrus but did not change the selectivity of tuning. In other words, effects of memory and content were additive in angular gyrus. This pattern of data contrasted with occipitotemporal cortex where memory and content effects were interactive: memory effects were preferentially expressed by voxels tuned to the content of a remembered image. Collectively, these findings provide unique insight into how parietal cortex combines information about episodic memory and semantic content.SIGNIFICANCE STATEMENT Neuroimaging studies of human memory have identified multiple brain regions that not only carry information about "whether" a visual stimulus is successfully recognized but also "what" the content of that stimulus includes. However, a fundamental and open question concerns how the brain integrates these two types of information (memory and content). Here, using a powerful combination of fMRI analysis methods, we show that parietal cortex, particularly the angular gyrus, robustly combines memory- and content-related information, but these two forms of information are represented via additive, independent signals. In contrast, memory effects in high-level visual cortex critically depend on (and interact with) content representations. Together, these findings reveal multiple and distinct ways in which the brain combines memory- and content-related information.

Visual Representations: Insights from Neural Decoding

Patterns of brain activity contain meaningful information about the perceived world. Recent decades have welcomed a new era in neural analyses, with computational techniques from machine learning applied to neural data to decode information represented in the brain. In this article, we review how decoding approaches have advanced our understanding of visual representations and discuss efforts to characterize both the complexity and the behavioral relevance of these representations. We outline the current consensus regarding the spatiotemporal structure of visual representations and review recent findings that suggest that visual representations are at once robust to perturbations, yet sensitive to different mental states. Beyond representations of the physical world, recent decoding work has shone a light on how the brain instantiates internally generated states, for example, during imagery and prediction. Going forward, decoding has remarkable potential to assess the functional relevance of visual representations for human behavior, reveal how representations change across development and during aging, and uncover their presentation in various mental disorders.

Perception and Memory in the Ventral Visual Stream and Medial Temporal Lobe

Perception and memory are traditionally thought of as separate cognitive functions, supported by distinct brain regions. The canonical perspective is that perceptual processing of visual information is supported by the ventral visual stream, whereas long-term declarative memory is supported by the medial temporal lobe. However, this modular framework cannot account for the increasingly large body of evidence that reveals a role for early visual areas in long-term recognition memory and a role for medial temporal lobe structures in high-level perceptual processing. In this article, we review relevant research conducted in humans, nonhuman primates, and rodents. We conclude that the evidence is largely inconsistent with theoretical proposals that draw sharp functional boundaries between perceptual and memory systems in the brain. Instead, the weight of the empirical findings is best captured by a representational-hierarchical model that emphasizes differences in content, rather than in cognitive processes within the ventral visual stream and medial temporal lobe.

Neural and behavioral signatures of the multidimensionality of manipulable object processing

Understanding how we recognize objects requires unravelling the variables that govern the way we think about objects and the neural organization of object representations. A tenable hypothesis is that the organization of object knowledge follows key object-related dimensions. Here, we explored, behaviorally and neurally, the multidimensionality of object processing. We focused on within-domain object information as a proxy for the decisions we typically engage in our daily lives - e.g., identifying a hammer in the context of other tools. We extracted object-related dimensions from subjective human judgments on a set of manipulable objects. We show that the extracted dimensions are cognitively interpretable and relevant - i.e., participants are able to consistently label them, and these dimensions can guide object categorization; and are important for the neural organization of knowledge - i.e., they predict neural signals elicited by manipulable objects. This shows that multidimensionality is a hallmark of the organization of manipulable object knowledge.

A large-scale fMRI dataset for the visual processing of naturalistic scenes

One ultimate goal of visual neuroscience is to understand how the brain processes visual stimuli encountered in the natural environment. Achieving this goal requires records of brain responses under massive amounts of naturalistic stimuli. Although the scientific community has put a lot of effort into collecting large-scale functional magnetic resonance imaging (fMRI) data under naturalistic stimuli, more naturalistic fMRI datasets are still urgently needed. We present here the Natural Object Dataset (NOD), a large-scale fMRI dataset containing responses to 57,120 naturalistic images from 30 participants. NOD strives for a balance between sampling variation between individuals and sampling variation between stimuli. This enables NOD to be utilized not only for determining whether an observation is generalizable across many individuals, but also for testing whether a response pattern is generalized to a variety of naturalistic stimuli. We anticipate that the NOD together with existing naturalistic neuroimaging datasets will serve as a new impetus for our understanding of the visual processing of naturalistic stimuli.

Distinct ventral stream and prefrontal cortex representational dynamics during sustained conscious visual perception

Instances of sustained stationary sensory input are ubiquitous. However, previous work focused almost exclusively on transient onset responses. This presents a critical challenge for neural theories of consciousness, which should account for the full temporal extent of experience. To address this question, we use intracranial recordings from ten human patients with epilepsy to view diverse images of multiple durations. We reveal that, in sensory regions, despite dramatic changes in activation magnitude, the distributed representation of categories and exemplars remains sustained and stable. In contrast, in frontoparietal regions, we find transient content representation at stimulus onset. Our results highlight the connection between the anatomical and temporal correlates of experience. To the extent perception is sustained, it may rely on sensory representations and to the extent perception is discrete, centered on perceptual updating, it may rely on frontoparietal representations.

Similar object shape representation encoded in the inferolateral occipitotemporal cortex of sighted and early blind people

We can sense an object's shape by vision or touch. Previous studies suggested that the inferolateral occipitotemporal cortex (ILOTC) implements supramodal shape representations as it responds more to seeing or touching objects than shapeless textures. However, such activation in the anterior portion of the ventral visual pathway could be due to the conceptual representation of an object or visual imagery triggered by touching an object. We addressed these possibilities by directly comparing shape and conceptual representations of objects in early blind (who lack visual experience/imagery) and sighted participants. We found that bilateral ILOTC in both groups showed stronger activation during a shape verification task than during a conceptual verification task made on the names of the same manmade objects. Moreover, the distributed activity in the ILOTC encoded shape similarity but not conceptual association among objects. Besides the ILOTC, we also found shape representation in both groups' bilateral ventral premotor cortices and intraparietal sulcus (IPS), a frontoparietal circuit relating to object grasping and haptic processing. In contrast, the conceptual verification task activated both groups' left perisylvian brain network relating to language processing and, interestingly, the cuneus in early blind participants only. The ILOTC had stronger functional connectivity to the frontoparietal circuit than to the left perisylvian network, forming a modular structure specialized in shape representation. Our results conclusively support that the ILOTC selectively implements shape representation independently of visual experience, and this unique functionality likely comes from its privileged connection to the frontoparietal haptic circuit.

Material category of visual objects computed from specular image structure

Recognizing materials and their properties visually is vital for successful interactions with our environment, from avoiding slippery floors to handling fragile objects. Yet there is no simple mapping of retinal image intensities to physical properties. Here, we investigated what image information drives material perception by collecting human psychophysical judgements about complex glossy objects. Variations in specular image structure-produced either by manipulating reflectance properties or visual features directly-caused categorical shifts in material appearance, suggesting that specular reflections provide diagnostic information about a wide range of material classes. Perceived material category appeared to mediate cues for surface gloss, providing evidence against a purely feedforward view of neural processing. Our results suggest that the image structure that triggers our perception of surface gloss plays a direct role in visual categorization, and that the perception and neural processing of stimulus properties should be studied in the context of recognition, not in isolation.