Scene Perception in the Human Brain

A theory of hippocampal function: New developments

We develop further here the only quantitative theory of the storage of information in the hippocampal episodic memory system and its recall back to the neocortex. The theory is upgraded to account for a revolution in understanding of spatial representations in the primate, including human, hippocampus, that go beyond the place where the individual is located, to the location being viewed in a scene. This is fundamental to much primate episodic memory and navigation: functions supported in humans by pathways that build 'where' spatial view representations by feature combinations in a ventromedial visual cortical stream, separate from those for 'what' object and face information to the inferior temporal visual cortex, and for reward information from the orbitofrontal cortex. Key new computational developments include the capacity of the CA3 attractor network for storing whole charts of space; how the correlations inherent in self-organizing continuous spatial representations impact the storage capacity; how the CA3 network can combine continuous spatial and discrete object and reward representations; the roles of the rewards that reach the hippocampus in the later consolidation into long-term memory in part via cholinergic pathways from the orbitofrontal cortex; and new ways of analysing neocortical information storage using Potts networks.

Selective activations and functional connectivities to the sight of faces, scenes, body parts and tools in visual and non-visual cortical regions leading to the human hippocampus

Connectivity maps are now available for the 360 cortical regions in the Human Connectome Project Multimodal Parcellation atlas. Here we add function to these maps by measuring selective fMRI activations and functional connectivity increases to stationary visual stimuli of faces, scenes, body parts and tools from 956 HCP participants. Faces activate regions in the ventrolateral visual cortical stream (FFC), in the superior temporal sulcus (STS) visual stream for face and head motion; and inferior parietal visual (PGi) and somatosensory (PF) regions. Scenes activate ventromedial visual stream VMV and PHA regions in the parahippocampal scene area; medial (7m) and lateral parietal (PGp) regions; and the reward-related medial orbitofrontal cortex. Body parts activate the inferior temporal cortex object regions (TE1p, TE2p); but also visual motion regions (MT, MST, FST); and the inferior parietal visual (PGi, PGs) and somatosensory (PF) regions; and the unpleasant-related lateral orbitofrontal cortex. Tools activate an intermediate ventral stream area (VMV3, VVC, PHA3); visual motion regions (FST); somatosensory (1, 2); and auditory (A4, A5) cortical regions. The findings add function to cortical connectivity maps; and show how stationary visual stimuli activate other cortical regions related to their associations, including visual motion, somatosensory, auditory, semantic, and orbitofrontal cortex value-related, regions.

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.

Verbal semantic expertise is associated with reduced functional connectivity between left and right anterior temporal lobes

The left and right anterior temporal lobes (ATLs) encode semantic representations. They show graded hemispheric specialization in function, with the left ATL contributing preferentially to verbal semantic processing. We investigated the cognitive correlates of this organization, using resting-state functional connectivity as a measure of functional segregation between ATLs. We analyzed two independent resting-state fMRI datasets (n = 86 and n = 642) in which participants' verbal semantic expertise was measured using vocabulary tests. In both datasets, people with more advanced verbal semantic knowledge showed weaker functional connectivity between left and right ventral ATLs. This effect was highly specific. It was not observed for within-hemisphere connections between semantic regions (ventral ATL and inferior frontal gyrus (IFG), though it was found for left-right IFG connectivity in one dataset). Effects were not found for tasks probing semantic control, nonsemantic cognition, or face recognition. Our results suggest that hemispheric specialization in the ATLs is not an innate property but rather emerges as people develop highly detailed verbal semantic representations. We speculate that this effect is a consequence of the left ATL's greater connectivity with left-lateralized written word recognition regions, which causes it to preferentially represent meaning for advanced vocabulary acquired primarily through reading.

Theta and alpha oscillations in human hippocampus and medial parietal cortex support the formation of location-based representations

Our ability to navigate in a new environment depends on learning new locations. Mental representations of locations are quickly accessible during navigation and allow us to know where we are regardless of our current viewpoint. Recent functional magnetic resonance imaging (fMRI) research using pattern classification has shown that these location-based representations emerge in the retrosplenial cortex and parahippocampal gyrus, regions theorized to be critically involved in spatial navigation. However, little is currently known about the oscillatory dynamics that support the formation of location-based representations. We used magnetoencephalogram (MEG) recordings to investigate region-specific oscillatory activity in a task where participants could form location-based representations. Participants viewed videos showing that two perceptually distinct scenes (180° apart) belonged to the same location. This "overlap" video allowed participants to bind the two distinct scenes together into a more coherent location-based representation. Participants also viewed control "non-overlap" videos where two distinct scenes from two different locations were shown, where no location-based representation could be formed. In a post-video behavioral task, participants successfully matched the two viewpoints shown in the overlap videos, but not the non-overlap videos, indicating they successfully learned the locations in the overlap condition. Comparing oscillatory activity between the overlap and non-overlap videos, we found greater theta and alpha/beta power during the overlap relative to non-overlap videos, specifically at time-points when we expected scene integration to occur. These oscillations localized to regions in the medial parietal cortex (precuneus and retrosplenial cortex) and the medial temporal lobe, including the hippocampus. Therefore, we find that theta and alpha/beta oscillations in the hippocampus and medial parietal cortex are likely involved in the formation of location-based representations.

Visual Recognition Memory of Scenes Is Driven by Categorical, Not Sensory, Visual Representations

When we perceive a scene, our brain processes various types of visual information simultaneously, ranging from sensory features, such as line orientations and colors, to categorical features, such as objects and their arrangements. Whereas the role of sensory and categorical visual representations in predicting subsequent memory has been studied using isolated objects, their impact on memory for complex scenes remains largely unknown. To address this gap, we conducted an fMRI study in which female and male participants encoded pictures of familiar scenes (e.g., an airport picture) and later recalled them, while rating the vividness of their visual recall. Outside the scanner, participants had to distinguish each seen scene from three similar lures (e.g., three airport pictures). We modeled the sensory and categorical visual features of multiple scenes using both early and late layers of a deep convolutional neural network. Then, we applied representational similarity analysis to determine which brain regions represented stimuli in accordance with the sensory and categorical models. We found that categorical, but not sensory, representations predicted subsequent memory. In line with the previous result, only for the categorical model, the average recognition performance of each scene exhibited a positive correlation with the average visual dissimilarity between the item in question and its respective lures. These results strongly suggest that even in memory tests that ostensibly rely solely on visual cues (such as forced-choice visual recognition with similar distractors), memory decisions for scenes may be primarily influenced by categorical rather than sensory representations.

Dynamic effective connectivity in the cerebellar dorsal dentate nucleus and the cerebrum, cognitive impairment, and clinical correlates in patients with schizophrenia

BACKGROUND

Schizophrenia (SZ) is characterized by disconnected cerebral networks. Recent studies have shown that functional connectivity between the cerebellar dorsal dentate nucleus (dDN) and cerebrum is correlated with psychotic symptoms, and processing speed in SZ patients. Dynamic effective connectivity (dEC) is a reliable indicator of brain functional status. However, the dEC between the dDN and cerebrum in patients with SZ remains largely unknown.

METHODS

Resting-state functional MRI data, symptom severity, and cognitive performance were collected from 74 SZ patients and 53 healthy controls (HC). Granger causality analysis and sliding time window methods were used to calculate dDN-based dEC maps for all subjects, and k-means clustering was performed to obtain several dEC states. Finally, between-group differences in dynamic effective connectivity variability (dECV) and clinical correlations were obtained using two-sample t-tests and correlation analysis.

RESULTS

We detected four dEC states from the cerebrum to the right dDN (IN states) and three dEC states from the right dDN to the cerebrum (OUT states), with SZ group having fewer transitions in the OUT states. SZ group had increased dECV from the right dDN to the right middle frontal gyrus (MFG) and left lingual gyrus (LG). Correlations were found between the dECV from the right dDN to the right MFG and symptom severity and between the dECV from the right dDN to the left LG and working memory performance.

CONCLUSIONS

This study reveals a dynamic causal relationship between cerebellar dDN and the cerebrum in SZ and provides new evidence for the involvement of cerebellar neural circuits in neurocognitive functions in SZ.

Neural substrates of affective temperaments: An intersubject representational similarity analysis to resting-state functional magnetic resonance imaging in nonclinical subjects

Previous research has suggested that certain types of the affective temperament, including depressive, cyclothymic, hyperthymic, irritable, and anxious, are subclinical manifestations and precursors of mental disorders. However, the neural mechanisms that underlie these temperaments are not fully understood. The aim of this study was to identify the brain regions associated with different affective temperaments. We collected the resting-state functional magnetic resonance imaging (fMRI) data from 211 healthy adults and evaluated their affective temperaments using the Temperament Evaluation of Memphis, Pisa, Paris and San Diego Autoquestionnaire. We used intersubject representational similarity analysis to identify brain regions associated with each affective temperament. Brain regions associated with each affective temperament were detected. These regions included the prefrontal cortex, anterior cingulate cortex (ACC), precuneus, amygdala, thalami, hippocampus, and visual areas. The ACC, lingual gyri, and precuneus showed similar activity across several affective temperaments. The similarity in related brain regions was high among the cyclothymic, irritable, and anxious temperaments, and low between hyperthymic and the other affective temperaments. These findings may advance our understanding of the neural mechanisms underlying affective temperaments and their potential relationship to mental disorders and may have potential implications for personalized treatment strategies for mood disorders.

Two what, two where, visual cortical streams in humans

ROLLS, E. T. Two What, Two Where, Visual Cortical Streams in Humans. NEUROSCI BIOBEHAV REV 2024. Recent cortical connectivity investigations lead to new concepts about 'What' and 'Where' visual cortical streams in humans, and how they connect to other cortical systems. A ventrolateral 'What' visual stream leads to the inferior temporal visual cortex for object and face identity, and provides 'What' information to the hippocampal episodic memory system, the anterior temporal lobe semantic system, and the orbitofrontal cortex emotion system. A superior temporal sulcus (STS) 'What' visual stream utilising connectivity from the temporal and parietal visual cortex responds to moving objects and faces, and face expression, and connects to the orbitofrontal cortex for emotion and social behaviour. A ventromedial 'Where' visual stream builds feature combinations for scenes, and provides 'Where' inputs via the parahippocampal scene area to the hippocampal episodic memory system that are also useful for landmark-based navigation. The dorsal 'Where' visual pathway to the parietal cortex provides for actions in space, but also provides coordinate transforms to provide inputs to the parahippocampal scene area for self-motion update of locations in scenes in the dark or when the view is obscured.

Individual differences in internal models explain idiosyncrasies in scene perception

According to predictive processing theories, vision is facilitated by predictions derived from our internal models of what the world should look like. However, the contents of these models and how they vary across people remains unclear. Here, we use drawing as a behavioral readout of the contents of the internal models in individual participants. Participants were first asked to draw typical versions of scene categories, as descriptors of their internal models. These drawings were converted into standardized 3d renders, which we used as stimuli in subsequent scene categorization experiments. Across two experiments, participants' scene categorization was more accurate for renders tailored to their own drawings compared to renders based on others' drawings or copies of scene photographs, suggesting that scene perception is determined by a match with idiosyncratic internal models. Using a deep neural network to computationally evaluate similarities between scene renders, we further demonstrate that graded similarity to the render based on participants' own typical drawings (and thus to their internal model) predicts categorization performance across a range of candidate scenes. Together, our results showcase the potential of a new method for understanding individual differences - starting from participants' personal expectations about the structure of real-world scenes.

Developing cortex is functionally pluripotent: Evidence from blindness

How rigidly does innate architecture constrain function of developing cortex? What is the contribution of early experience? We review insights into these questions from visual cortex function in people born blind. In blindness, occipital cortices are active during auditory and tactile tasks. What 'cross-modal' plasticity tells us about cortical flexibility is debated. On the one hand, visual networks of blind people respond to higher cognitive information, such as sentence grammar, suggesting drastic repurposing. On the other, in line with 'metamodal' accounts, sighted and blind populations show shared domain preferences in ventral occipito-temporal cortex (vOTC), suggesting visual areas switch input modality but perform the same or similar perceptual functions (e.g., face recognition) in blindness. Here we bring these disparate literatures together, reviewing and synthesizing evidence that speaks to whether visual cortices have similar or different functions in blind and sighted people. Together, the evidence suggests that in blindness, visual cortices are incorporated into higher-cognitive (e.g., fronto-parietal) networks, which are a major source long-range input to the visual system. We propose the connectivity-constrained experience-dependent account. Functional development is constrained by innate anatomical connectivity, experience and behavioral needs. Infant cortex is pluripotent, the same anatomical constraints develop into different functional outcomes.

Preliminary Evidence for Global Properties in Human Listeners During Natural Auditory Scene Perception

Theories of auditory and visual scene analysis suggest the perception of scenes relies on the identification and segregation of objects within it, resembling a detail-oriented processing style. However, a more global process may occur while analyzing scenes, which has been evidenced in the visual domain. It is our understanding that a similar line of research has not been explored in the auditory domain; therefore, we evaluated the contributions of high-level global and low-level acoustic information to auditory scene perception. An additional aim was to increase the field's ecological validity by using and making available a new collection of high-quality auditory scenes. Participants rated scenes on 8 global properties (e.g., open vs. enclosed) and an acoustic analysis evaluated which low-level features predicted the ratings. We submitted the acoustic measures and average ratings of the global properties to separate exploratory factor analyses (EFAs). The EFA of the acoustic measures revealed a seven-factor structure explaining 57% of the variance in the data, while the EFA of the global property measures revealed a two-factor structure explaining 64% of the variance in the data. Regression analyses revealed each global property was predicted by at least one acoustic variable (R2 = 0.33-0.87). These findings were extended using deep neural network models where we examined correlations between human ratings of global properties and deep embeddings of two computational models: an object-based model and a scene-based model. The results support that participants' ratings are more strongly explained by a global analysis of the scene setting, though the relationship between scene perception and auditory perception is multifaceted, with differing correlation patterns evident between the two models. Taken together, our results provide evidence for the ability to perceive auditory scenes from a global perspective. Some of the acoustic measures predicted ratings of global scene perception, suggesting representations of auditory objects may be transformed through many stages of processing in the ventral auditory stream, similar to what has been proposed in the ventral visual stream. These findings and the open availability of our scene collection will make future studies on perception, attention, and memory for natural auditory scenes possible.

Efficient coding of natural images in the mouse visual cortex

How the activity of neurons gives rise to natural vision remains a matter of intense investigation. The mid-level visual areas along the ventral stream are selective to a common class of natural images-textures-but a circuit-level understanding of this selectivity and its link to perception remains unclear. We addressed these questions in mice, first showing that they can perceptually discriminate between textures and statistically simpler spectrally matched stimuli, and between texture types. Then, at the neural level, we found that the secondary visual area (LM) exhibited a higher degree of selectivity for textures compared to the primary visual area (V1). Furthermore, textures were represented in distinct neural activity subspaces whose relative distances were found to correlate with the statistical similarity of the images and the mice's ability to discriminate between them. Notably, these dependencies were more pronounced in LM, where the texture-related subspaces were smaller than in V1, resulting in superior stimulus decoding capabilities. Together, our results demonstrate texture vision in mice, finding a linking framework between stimulus statistics, neural representations, and perceptual sensitivity-a distinct hallmark of efficient coding computations.

Sex differences in functional connectivity and the predictive role of the connectome-based predictive model in Alzheimer's disease

Alzheimer's disease (AD) is a neurodegenerative disease characterized by cognitive decline. Sex differences in the progression of AD exist, but the neural mechanisms are not well understood. The purpose of the current study was to explore sex differences in brain functional connectivity (FC) at different stages of AD and their predictive ability on Montreal Cognitive Assessment (MoCA) scores using connectome-based predictive modeling (CPM). Resting-state functional magnetic resonance imaging was collected from 81 AD patients (44 females), 78 amnestic mild cognitive impairment patients (44 females), and 92 healthy controls (50 females). The FC analysis was conducted and the interaction effect between sex and group was investigated using two-factor variance analysis. The CPM was used to predict MoCA scores. There were sex-by-group interaction effects on FC between the left dorsolateral superior frontal gyrus and left middle temporal gyrus, left precuneus and right calcarine fissure surrounding cortex, left precuneus and left middle occipital gyrus, left middle temporal gyrus and left precentral gyrus, and between the left middle temporal gyrus and right cuneus. In the CPM, the positive network predictive model significantly predicted MoCA scores in both males and females. There were significant sex-by-group interaction effects on FC between the left precuneus and left middle occipital gyrus, and between the left middle temporal gyrus and right cuneus could predict MoCA scores in female patients. Our results suggest that there are sex differences in FC at different stages of AD. The sex-specific FC can further predict MoCA scores at individual level.

Integrative processing in artificial and biological vision predicts the perceived beauty of natural images

Previous research shows that the beauty of natural images is already determined during perceptual analysis. However, it is unclear which perceptual computations give rise to the perception of beauty. Here, we tested whether perceived beauty is predicted by spatial integration across an image, a perceptual computation that reduces processing demands by aggregating image parts into more efficient representations of the whole. We quantified integrative processing in an artificial deep neural network model, where the degree of integration was determined by the amount of deviation between activations for the whole image and its constituent parts. This quantification of integration predicted beauty ratings for natural images across four studies with different stimuli and designs. In a complementary functional magnetic resonance imaging study, we show that integrative processing in human visual cortex similarly predicts perceived beauty. Together, our results establish integration as a computational principle that facilitates perceptual analysis and thereby mediates the perception of beauty.

The Accuracy and Precision of Memory for Natural Scenes: A Walk in the Park

It is challenging to quantify the accuracy and precision of scene memory because it is unclear what 'space' scenes occupy (how can we quantify error when misremembering a natural scene?). To address this, we exploited the ecologically valid, metric space in which scenes occur and are represented: routes. In a delayed estimation task, participants briefly saw a target scene drawn from a video of an outdoor 'route loop', then used a continuous report wheel of the route to pinpoint the scene. Accuracy was high and unbiased, indicating there was no net boundary extension/contraction. Interestingly, precision was higher for routes that were more self-similar (as characterized by the half-life, in meters, of a route's Multiscale Structural Similarity index), consistent with previous work finding a 'similarity advantage' where memory precision is regulated according to task demands. Overall, scenes were remembered to within a few meters of their actual location.

Representational Dissimilarity of Faces and Places during a Working Memory Task is Associated with Subsequent Recognition Memory during Development

Nearly 50 years of research has focused on faces as a special visual category, especially during development. Yet it remains unclear how spatial patterns of neural similarity of faces and places relate to how information processing supports subsequent recognition of items from these categories. The current study uses representational similarity analysis and functional imaging data from 9- and 10-year-old youth during an emotional n-back task from the Adolescent Brain and Cognitive Development Study 3.0 data release to relate spatial patterns of neural similarity during working memory to subsequent out-of-scanner performance on a recognition memory task. Specifically, we examine how similarities in representations within face categories (neutral, happy, and fearful faces) and representations between visual categories (faces and places) relate to subsequent recognition memory of these visual categories. Although working memory performance was higher for faces than places, subsequent recognition memory was greater for places than faces. Representational similarity analysis revealed category-specific patterns in face-and place-sensitive brain regions (fusiform gyrus, parahippocampal gyrus) compared with a nonsensitive visual region (pericalcarine cortex). Similarity within face categories and dissimilarity between face and place categories in the parahippocampus was related to better recognition of places from the n-back task. Conversely, in the fusiform, similarity within face categories and their relative dissimilarity from places was associated with better recognition of new faces, but not old faces. These findings highlight how the representational distinctiveness of visual categories influence what information is subsequently prioritized in recognition memory during development.

Immersive scene representation in human visual cortex with ultra-wide angle neuroimaging

While humans experience the visual environment in a panoramic 220° view, traditional functional MRI setups are limited to display images like postcards in the central 10-15° of the visual field. Thus, it remains unknown how a scene is represented in the brain when perceived across the full visual field. Here, we developed a novel method for ultra-wide angle visual presentation and probed for signatures of immersive scene representation. To accomplish this, we bounced the projected image off angled-mirrors directly onto a custom-built curved screen, creating an unobstructed view of 175°. Scene images were created from custom-built virtual environments with a compatible wide field-of-view to avoid perceptual distortion. We found that immersive scene representation drives medial cortex with far-peripheral preferences, but surprisingly had little effect on classic scene regions. That is, scene regions showed relatively minimal modulation over dramatic changes of visual size. Further, we found that scene and face-selective regions maintain their content preferences even under conditions of central scotoma, when only the extreme far-peripheral visual field is stimulated. These results highlight that not all far-peripheral information is automatically integrated into the computations of scene regions, and that there are routes to high-level visual areas that do not require direct stimulation of the central visual field. Broadly, this work provides new clarifying evidence on content vs. peripheral preferences in scene representation, and opens new neuroimaging research avenues to understand immersive visual representation.

Scene-selectivity in CA1/subicular complex: Multivoxel pattern analysis at 7T

Prior univariate functional magnetic resonance imaging (fMRI) studies in humans suggest that the anteromedial subicular complex of the hippocampus is a hub for scene-based cognition. However, it is possible that univariate approaches were not sufficiently sensitive to detect scene-related activity in other subfields that have been implicated in spatial processing (e.g., CA1). Further, as connectivity-based functional gradients in the hippocampus do not respect classical subfield boundary definitions, category selectivity may be distributed across anatomical subfields. Region-of-interest approaches, therefore, may limit our ability to observe category selectivity across discrete subfield boundaries. To address these issues, we applied searchlight multivariate pattern analysis to 7T fMRI data of healthy adults who undertook a simultaneous visual odd-one-out discrimination task for scene and non-scene (including face) visual stimuli, hypothesising that scene classification would be possible in multiple hippocampal regions within, but not constrained to, anteromedial subicular complex and CA1. Indeed, we found that the scene-selective searchlight map overlapped not only with anteromedial subicular complex (distal subiculum, pre/para subiculum), but also inferior CA1, alongside posteromedial (including retrosplenial) and parahippocampal cortices. Probabilistic overlap maps revealed gradients of scene category selectivity, with the strongest overlap located in the medial hippocampus, converging with searchlight findings. This was contrasted with gradients of face category selectivity, which had stronger overlap in more lateral hippocampus, supporting ideas of parallel processing streams for these two categories. Our work helps to map the scene, in contrast to, face processing networks within, and connected to, the human hippocampus.

Mapping the functional and structural connectivity of the scene network

The recognition and perception of places has been linked to a network of scene-selective regions in the human brain. While previous studies have focussed on functional connectivity between scene-selective regions themselves, less is known about their connectivity with other cortical and subcortical regions in the brain. Here, we determine the functional and structural connectivity profile of the scene network. We used fMRI to examine functional connectivity between scene regions and across the whole brain during rest and movie-watching. Connectivity within the scene network revealed a bias between posterior and anterior scene regions implicated in perceptual and mnemonic aspects of scene perception respectively. Differences between posterior and anterior scene regions were also evident in the connectivity with cortical and subcortical regions across the brain. For example, the Occipital Place Area (OPA) and posterior Parahippocampal Place Area (PPA) showed greater connectivity with visual and dorsal attention networks, while anterior PPA and Retrosplenial Complex showed preferential connectivity with default mode and frontoparietal control networks and the hippocampus. We further measured the structural connectivity of the scene network using diffusion tractography. This indicated both similarities and differences with the functional connectivity, highlighting biases between posterior and anterior regions, but also between ventral and dorsal scene regions. Finally, we quantified the structural connectivity between the scene network and major white matter tracts throughout the brain. These findings provide a map of the functional and structural connectivity of scene-selective regions to each other and the rest of the brain.

Cultural Psychology: Beyond East and West

Research in cultural psychology over the last three decades has revealed the profound influence of culture on cognitive, emotional, and motivational processes shaping individuals into active agents. This article aims to show cultural psychology's promise in three key steps. First, we review four notable cultural dimensions believed to underlie cultural variations: independent versus interdependent self, individualism versus collectivism, tightness versus looseness of social norms, and relational mobility. Second, we examine how ecology and geography shape human activities and give rise to organized systems of cultural practices and meanings, called eco-cultural complexes. In turn, the eco-cultural complex of each zone is instrumental in shaping a wide range of psychological processes, revealing a psychological diversity that extends beyond the scope of the current East-West literature. Finally, we examine some of the non-Western cultural zones present today, including Arab, East Asian, Latin American, and South Asian zones, and discuss how they may have contributed, to varying degrees, to the formation of the contemporary Western cultural zone.

Cortical field maps across human sensory cortex

Cortical processing pathways for sensory information in the mammalian brain tend to be organized into topographical representations that encode various fundamental sensory dimensions. Numerous laboratories have now shown how these representations are organized into numerous cortical field maps (CMFs) across visual and auditory cortex, with each CFM supporting a specialized computation or set of computations that underlie the associated perceptual behaviors. An individual CFM is defined by two orthogonal topographical gradients that reflect two essential aspects of feature space for that sense. Multiple adjacent CFMs are then organized across visual and auditory cortex into macrostructural patterns termed cloverleaf clusters. CFMs within cloverleaf clusters are thought to share properties such as receptive field distribution, cortical magnification, and processing specialization. Recent measurements point to the likely existence of CFMs in the other senses, as well, with topographical representations of at least one sensory dimension demonstrated in somatosensory, gustatory, and possibly olfactory cortical pathways. Here we discuss the evidence for CFM and cloverleaf cluster organization across human sensory cortex as well as approaches used to identify such organizational patterns. Knowledge of how these topographical representations are organized across cortex provides us with insight into how our conscious perceptions are created from our basic sensory inputs. In addition, studying how these representations change during development, trauma, and disease serves as an important tool for developing improvements in clinical therapies and rehabilitation for sensory deficits.

Personal familiarity of faces, animals, objects, and scenes: Distinct perceptual and overlapping conceptual representations

While face, object, and scene recognition are often studied at a basic categorization level (e.g. "a face", "a car", "a kitchen"), we frequently recognise individual items of these categories as unique entities (e.g. "my mother", "my car", "my kitchen"). This recognition of individual identity is essential to appropriate behaviour in our world. However, relatively little is known about how we recognise individually familiar visual stimuli. Using event-related brain potentials, the present study examined whether and to what extent the underlying neural representations of personally familiar items are similar or different across different categories. In three experiments, we examined the recognition of personally highly familiar faces, animals, indoor scenes, and objects. We observed relatively distinct familiarity effects in an early time window (200-400 ms), with a clearly right-lateralized occipito-temporal scalp distribution for human faces and more bilateral and posterior distributions for other stimulus categories, presumably reflecting access to at least partly discrete visual long-term representations. In contrast, we found clearly overlapping familiarity effects in a later time window (starting 400 to 500 ms after stimulus onset), again with a mainly right occipito-temporal scalp distribution, for all stimulus categories. These later effects appear to reflect the sustained activation of conceptual properties relevant to any potential interaction. We conclude that familiarity for items from the various visual stimulus categories tested here is represented differently at the perceptual level, while relatively overlapping conceptual mechanisms allow for the preparation of impending potential interaction with the environment.

Alpha-frequency feedback to early visual cortex orchestrates coherent naturalistic vision

During naturalistic vision, the brain generates coherent percepts by integrating sensory inputs scattered across the visual field. Here, we asked whether this integration process is mediated by rhythmic cortical feedback. In electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) experiments, we experimentally manipulated integrative processing by changing the spatiotemporal coherence of naturalistic videos presented across visual hemifields. Our EEG data revealed that information about incoherent videos is coded in feedforward-related gamma activity while information about coherent videos is coded in feedback-related alpha activity, indicating that integration is indeed mediated by rhythmic activity. Our fMRI data identified scene-selective cortex and human middle temporal complex (hMT) as likely sources of this feedback. Analytically combining our EEG and fMRI data further revealed that feedback-related representations in the alpha band shape the earliest stages of visual processing in cortex. Together, our findings indicate that the construction of coherent visual experiences relies on cortical feedback rhythms that fully traverse the visual hierarchy.

Spatiotemporal cortical dynamics for visual scene processing as revealed by EEG decoding

The human visual system rapidly recognizes the categories and global properties of complex natural scenes. The present study investigated the spatiotemporal dynamics of neural signals involved in visual scene processing using electroencephalography (EEG) decoding. We recorded visual evoked potentials from 11 human observers for 232 natural scenes, each of which belonged to one of 13 natural scene categories (e.g., a bedroom or open country) and had three global properties (naturalness, openness, and roughness). We trained a deep convolutional classification model of the natural scene categories and global properties using EEGNet. Having confirmed that the model successfully classified natural scene categories and the three global properties, we applied Grad-CAM to the EEGNet model to visualize the EEG channels and time points that contributed to the classification. The analysis showed that EEG signals in the occipital electrodes at short latencies (approximately 80 ~ ms) contributed to the classifications, whereas those in the frontal electrodes at relatively long latencies (200 ~ ms) contributed to the classification of naturalness and the individual scene category. These results suggest that different global properties are encoded in different cortical areas and with different timings, and that the combination of the EEGNet model and Grad-CAM can be a tool to investigate both temporal and spatial distribution of natural scene processing in the human brain.

Inhibitory temporo-parietal effective connectivity is associated with explicit memory performance in older adults

Successful explicit memory encoding is associated with inferior temporal activations and medial parietal deactivations, which are attenuated in aging. Here we used dynamic causal modeling (DCM) of functional magnetic resonance imaging data to elucidate effective connectivity patterns between hippocampus, parahippocampal place area (PPA), and precuneus during encoding of novel visual scenes. In 117 young adults, DCM revealed pronounced activating input from the PPA to the hippocampus and inhibitory connectivity from the PPA to the precuneus during novelty processing, with both being enhanced during successful encoding. This pattern could be replicated in two cohorts (N = 141 and 148) of young and older adults. In both cohorts, older adults selectively exhibited attenuated inhibitory PPA-precuneus connectivity, which correlated negatively with memory performance. Our results provide insight into the network dynamics underlying explicit memory encoding and suggest that age-related differences in memory-related network activity are, at least partly, attributable to altered temporo-parietal neocortical connectivity.

Training biologically plausible recurrent neural networks on cognitive tasks with long-term dependencies

Training recurrent neural networks (RNNs) has become a go-to approach for generating and evaluating mechanistic neural hypotheses for cognition. The ease and efficiency of training RNNs with backpropagation through time and the availability of robustly supported deep learning libraries has made RNN modeling more approachable and accessible to neuroscience. Yet, a major technical hindrance remains. Cognitive processes such as working memory and decision making involve neural population dynamics over a long period of time within a behavioral trial and across trials. It is difficult to train RNNs to accomplish tasks where neural representations and dynamics have long temporal dependencies without gating mechanisms such as LSTMs or GRUs which currently lack experimental support and prohibit direct comparison between RNNs and biological neural circuits. We tackled this problem based on the idea of specialized skip-connections through time to support the emergence of task-relevant dynamics, and subsequently reinstitute biological plausibility by reverting to the original architecture. We show that this approach enables RNNs to successfully learn cognitive tasks that prove impractical if not impossible to learn using conventional methods. Over numerous tasks considered here, we achieve less training steps and shorter wall-clock times, particularly in tasks that require learning long-term dependencies via temporal integration over long timescales or maintaining a memory of past events in hidden-states. Our methods expand the range of experimental tasks that biologically plausible RNN models can learn, thereby supporting the development of theory for the emergent neural mechanisms of computations involving long-term dependencies.

Proximity to boundaries reveals spatial context representation in human hippocampal CA1

Recollection of real-world events is often accompanied by a sense of being in the place where the event transpired. Convergent evidence suggests the hippocampus plays a key role in supporting episodic memory by associating information with the time and place it was originally encountered. This representation is reinstated during memory retrieval. However, little is known about the roles of different subfields of the human hippocampus in this process. Research in humans and non-human animal models has suggested that spatial environmental boundaries have a powerful influence on spatial and episodic memory, as well as hippocampal representations of contexts and events. Here, we used high-resolution fMRI to investigate how boundaries influence hippocampal activity patterns during the recollection of objects encountered in different spatial contexts. During the encoding phase, participants viewed objects once in a naturalistic virtual reality task in which they passively explored two rooms in one of two houses. Following the encoding phase, participants were scanned while they recollected items in the absence of any spatial contextual information. Our behavioral results demonstrated that spatial context memory was enhanced for objects encountered near a boundary. Activity patterns in CA1 carried information about the spatial context associated with each of these boundary items. Exploratory analyses revealed that recollection performance was correlated with the fidelity of retrieved spatial context representations in anterior parahippocampal cortex and subiculum. Our results highlight the privileged role of boundaries in CA1 and suggest more generally a close relationship between memory for spatial contexts and representations in the hippocampus and parahippocampal region.

A map of spatial navigation for neuroscience

Spatial navigation has received much attention from neuroscientists, leading to the identification of key brain areas and the discovery of numerous spatially selective cells. Despite this progress, our understanding of how the pieces fit together to drive behavior is generally lacking. We argue that this is partly caused by insufficient communication between behavioral and neuroscientific researchers. This has led the latter to under-appreciate the relevance and complexity of spatial behavior, and to focus too narrowly on characterizing neural representations of space-disconnected from the computations these representations are meant to enable. We therefore propose a taxonomy of navigation processes in mammals that can serve as a common framework for structuring and facilitating interdisciplinary research in the field. Using the taxonomy as a guide, we review behavioral and neural studies of spatial navigation. In doing so, we validate the taxonomy and showcase its usefulness in identifying potential issues with common experimental approaches, designing experiments that adequately target particular behaviors, correctly interpreting neural activity, and pointing to new avenues of research.

Interactions between rodent visual and spatial systems during navigation

Many behaviours that are critical for animals to survive and thrive rely on spatial navigation. Spatial navigation, in turn, relies on internal representations about one's spatial location, one's orientation or heading direction and the distance to objects in the environment. Although the importance of vision in guiding such internal representations has long been recognized, emerging evidence suggests that spatial signals can also modulate neural responses in the central visual pathway. Here, we review the bidirectional influences between visual and navigational signals in the rodent brain. Specifically, we discuss reciprocal interactions between vision and the internal representations of spatial position, explore the effects of vision on representations of an animal's heading direction and vice versa, and examine how the visual and navigational systems work together to assess the relative distances of objects and other features. Throughout, we consider how technological advances and novel ethological paradigms that probe rodent visuo-spatial behaviours allow us to advance our understanding of how brain areas of the central visual pathway and the spatial systems interact and enable complex behaviours.

A Texture Statistics Encoding Model Reveals Hierarchical Feature Selectivity across Human Visual Cortex

Midlevel features, such as contour and texture, provide a computational link between low- and high-level visual representations. Although the nature of midlevel representations in the brain is not fully understood, past work has suggested a texture statistics model, called the P-S model (Portilla and Simoncelli, 2000), is a candidate for predicting neural responses in areas V1-V4 as well as human behavioral data. However, it is not currently known how well this model accounts for the responses of higher visual cortex to natural scene images. To examine this, we constructed single-voxel encoding models based on P-S statistics and fit the models to fMRI data from human subjects (both sexes) from the Natural Scenes Dataset (Allen et al., 2022). We demonstrate that the texture statistics encoding model can predict the held-out responses of individual voxels in early retinotopic areas and higher-level category-selective areas. The ability of the model to reliably predict signal in higher visual cortex suggests that the representation of texture statistics features is widespread throughout the brain. Furthermore, using variance partitioning analyses, we identify which features are most uniquely predictive of brain responses and show that the contributions of higher-order texture features increase from early areas to higher areas on the ventral and lateral surfaces. We also demonstrate that patterns of sensitivity to texture statistics can be used to recover broad organizational axes within visual cortex, including dimensions that capture semantic image content. These results provide a key step forward in characterizing how midlevel feature representations emerge hierarchically across the visual system.SIGNIFICANCE STATEMENT Intermediate visual features, like texture, play an important role in cortical computations and may contribute to tasks like object and scene recognition. Here, we used a texture model proposed in past work to construct encoding models that predict the responses of neural populations in human visual cortex (measured with fMRI) to natural scene stimuli. We show that responses of neural populations at multiple levels of the visual system can be predicted by this model, and that the model is able to reveal an increase in the complexity of feature representations from early retinotopic cortex to higher areas of ventral and lateral visual cortex. These results support the idea that texture-like representations may play a broad underlying role in visual processing.

Hippocampal spatial view cells for memory and navigation, and their underlying connectivity in humans

Hippocampal and parahippocampal gyrus spatial view neurons in primates respond to the spatial location being looked at. The representation is allocentric, in that the responses are to locations "out there" in the world, and are relatively invariant with respect to retinal position, eye position, head direction, and the place where the individual is located. The underlying connectivity in humans is from ventromedial visual cortical regions to the parahippocampal scene area, leading to the theory that spatial view cells are formed by combinations of overlapping feature inputs self-organized based on their closeness in space. Thus, although spatial view cells represent "where" for episodic memory and navigation, they are formed by ventral visual stream feature inputs in the parahippocampal gyrus in what is the parahippocampal scene area. A second "where" driver of spatial view cells are parietal inputs, which it is proposed provide the idiothetic update for spatial view cells, used for memory recall and navigation when the spatial view details are obscured. Inferior temporal object "what" inputs and orbitofrontal cortex reward inputs connect to the human hippocampal system, and in macaques can be associated in the hippocampus with spatial view cell "where" representations to implement episodic memory. Hippocampal spatial view cells also provide a basis for navigation to a series of viewed landmarks, with the orbitofrontal cortex reward inputs to the hippocampus providing the goals for navigation, which can then be implemented by hippocampal connectivity in humans to parietal cortex regions involved in visuomotor actions in space. The presence of foveate vision and the highly developed temporal lobe for object and scene processing in primates including humans provide a basis for hippocampal spatial view cells to be key to understanding episodic memory in the primate and human hippocampus, and the roles of this system in primate including human navigation.

The representational hierarchy in human and artificial visual systems in the presence of object-scene regularities

Human vision is still largely unexplained. Computer vision made impressive progress on this front, but it is still unclear to which extent artificial neural networks approximate human object vision at the behavioral and neural levels. Here, we investigated whether machine object vision mimics the representational hierarchy of human object vision with an experimental design that allows testing within-domain representations for animals and scenes, as well as across-domain representations reflecting their real-world contextual regularities such as animal-scene pairs that often co-occur in the visual environment. We found that DCNNs trained in object recognition acquire representations, in their late processing stage, that closely capture human conceptual judgements about the co-occurrence of animals and their typical scenes. Likewise, the DCNNs representational hierarchy shows surprising similarities with the representational transformations emerging in domain-specific ventrotemporal areas up to domain-general frontoparietal areas. Despite these remarkable similarities, the underlying information processing differs. The ability of neural networks to learn a human-like high-level conceptual representation of object-scene co-occurrence depends upon the amount of object-scene co-occurrence present in the image set thus highlighting the fundamental role of training history. Further, although mid/high-level DCNN layers represent the category division for animals and scenes as observed in VTC, its information content shows reduced domain-specific representational richness. To conclude, by testing within- and between-domain selectivity while manipulating contextual regularities we reveal unknown similarities and differences in the information processing strategies employed by human and artificial visual systems.

Angular Gyrus Responses Show Joint Statistical Dependence with Brain Regions Selective for Different Categories

Category selectivity is a fundamental principle of organization of perceptual brain regions. Human occipitotemporal cortex is subdivided into areas that respond preferentially to faces, bodies, artifacts, and scenes. However, observers need to combine information about objects from different categories to form a coherent understanding of the world. How is this multicategory information encoded in the brain? Studying the multivariate interactions between brain regions of male and female human subjects with fMRI and artificial neural networks, we found that the angular gyrus shows joint statistical dependence with multiple category-selective regions. Adjacent regions show effects for the combination of scenes and each other category, suggesting that scenes provide a context to combine information about the world. Additional analyses revealed a cortical map of areas that encode information across different subsets of categories, indicating that multicategory information is not encoded in a single centralized location, but in multiple distinct brain regions.SIGNIFICANCE STATEMENT Many cognitive tasks require combining information about entities from different categories. However, visual information about different categorical objects is processed by separate, specialized brain regions. How is the joint representation from multiple category-selective regions implemented in the brain? Using fMRI movie data and state-of-the-art multivariate statistical dependence based on artificial neural networks, we identified the angular gyrus encoding responses across face-, body-, artifact-, and scene-selective regions. Further, we showed a cortical map of areas that encode information across different subsets of categories. These findings suggest that multicategory information is not encoded in a single centralized location, but at multiple cortical sites which might contribute to distinct cognitive functions, offering insights to understand integration in a variety of domains.

Distinct neural mechanisms for heading retrieval and context recognition in the hippocampus during spatial reorientation

Reorientation, the process of regaining one's bearings after becoming lost, requires identification of a spatial context (context recognition) and recovery of heading direction within that context (heading retrieval). We previously showed that these processes rely on the use of features and geometry, respectively. Here, we examine reorientation behavior in a task that creates contextual ambiguity over a long timescale to demonstrate that mice learn to combine both featural and geometric cues to recover heading with experience. At the neural level, most CA1 neurons persistently align to geometry, and this alignment predicts heading behavior. However, a small subset of cells shows feature-sensitive place field remapping, which serves to predict context. Efficient heading retrieval and context recognition require integration of featural and geometric information in the active network through rate changes. These data illustrate how context recognition and heading retrieval are coded in CA1 and how these processes change with experience.

The human posterior parietal cortex: effective connectome, and its relation to function

The effective connectivity between 21 regions in the human posterior parietal cortex, and 360 cortical regions was measured in 171 Human Connectome Project (HCP) participants using the HCP atlas, and complemented with functional connectivity and diffusion tractography. Intraparietal areas LIP, VIP, MIP, and AIP have connectivity from early cortical visual regions, and to visuomotor regions such as the frontal eye fields, consistent with functions in eye saccades and tracking. Five superior parietal area 7 regions receive from similar areas and from the intraparietal areas, but also receive somatosensory inputs and connect with premotor areas including area 6, consistent with functions in performing actions to reach for, grasp, and manipulate objects. In the anterior inferior parietal cortex, PFop, PFt, and PFcm are mainly somatosensory, and PF in addition receives visuo-motor and visual object information, and is implicated in multimodal shape and body image representations. In the posterior inferior parietal cortex, PFm and PGs combine visuo-motor, visual object, and reward input and connect with the hippocampal system. PGi in addition provides a route to motion-related superior temporal sulcus regions involved in social interactions. PGp has connectivity with intraparietal regions involved in coordinate transforms and may be involved in idiothetic update of hippocampal visual scene representations.

A tripartite view of the posterior cingulate cortex

The posterior cingulate cortex (PCC) is one of the least understood regions of the cerebral cortex. By contrast, the anterior cingulate cortex has been the subject of intensive investigation in humans and model animal systems, leading to detailed behavioural and computational theoretical accounts of its function. The time is right for similar progress to be made in the PCC given its unique anatomical and physiological properties and demonstrably important contributions to higher cognitive functions and brain diseases. Here, we describe recent progress in understanding the PCC, with a focus on convergent findings across species and techniques that lay a foundation for establishing a formal theoretical account of its functions. Based on this converging evidence, we propose that the broader PCC region contains three major subregions - the dorsal PCC, ventral PCC and retrosplenial cortex - that respectively support the integration of executive, mnemonic and spatial processing systems. This tripartite subregional view reconciles inconsistencies in prior unitary theories of PCC function and offers promising new avenues for progress.

The human posterior cingulate, retrosplenial, and medial parietal cortex effective connectome, and implications for memory and navigation

The human posterior cingulate, retrosplenial, and medial parietal cortex are involved in memory and navigation. The functional anatomy underlying these cognitive functions was investigated by measuring the effective connectivity of these Posterior Cingulate Division (PCD) regions in the Human Connectome Project-MMP1 atlas in 171 HCP participants, and complemented with functional connectivity and diffusion tractography. First, the postero-ventral parts of the PCD (31pd, 31pv, 7m, d23ab, and v23ab) have effective connectivity with the temporal pole, inferior temporal visual cortex, cortex in the superior temporal sulcus implicated in auditory and semantic processing, with the reward-related vmPFC and pregenual anterior cingulate cortex, with the inferior parietal cortex, and with the hippocampal system. This connectivity implicates it in hippocampal episodic memory, providing routes for "what," reward and semantic schema-related information to access the hippocampus. Second, the antero-dorsal parts of the PCD (especially 31a and 23d, PCV, and also RSC) have connectivity with early visual cortical areas including those that represent spatial scenes, with the superior parietal cortex, with the pregenual anterior cingulate cortex, and with the hippocampal system. This connectivity implicates it in the "where" component for hippocampal episodic memory and for spatial navigation. The dorsal-transitional-visual (DVT) and ProStriate regions where the retrosplenial scene area is located have connectivity from early visual cortical areas to the parahippocampal scene area, providing a ventromedial route for spatial scene information to reach the hippocampus. These connectivities provide important routes for "what," reward, and "where" scene-related information for human hippocampal episodic memory and navigation. The midcingulate cortex provides a route from the anterior dorsal parts of the PCD and the supracallosal part of the anterior cingulate cortex to premotor regions.

Peripheral visual field loss and activities of daily living

PURPOSE OF REVIEW

Peripheral visual field (VF) loss affects 13% of the population over 65. Its effect on activities of daily living and higher order visual processing is as important as it is inadequately understood. The purpose of this review is to summarize available literature on the impact of peripheral vision loss on driving, reading, face recognition, scene recognition and scene navigation.

RECENT FINDINGS

In this review, glaucoma and retrochiasmal cortical damage are utilized as examples of peripheral field loss which typically spare central vision and have patterns respecting the horizontal and vertical meridians, respectively. In both glaucoma and retrochiasmal damage, peripheral field loss causes driving difficulty - especially with lane maintenance - leading to driving cessation, loss of independence, and depression. Likewise, peripheral field loss can lead to slower reading speeds and decreased enjoyment from reading, and anxiety. In glaucoma and retrochiasmal field loss, face processing is impaired which impacts social functioning. Finally, scene recognition and navigation are also adversely affected, impacting wayfinding and hazard detection leading to decreased independence as well as more frequent injury.

SUMMARY

Peripheral VF loss is an under-recognized cause of patient distress and disability. All peripheral field loss is not the same, differential patterns of loss affect parameters of activities of daily living (ADL) and visual processing in particular ways. Future research should aim to further characterize patterns of deranged ADL and visual processing, their correlation with types of field loss, and associated mechanisms.

Rethinking retrosplenial cortex: Perspectives and predictions

The last decade has produced exciting new ideas about retrosplenial cortex (RSC) and its role in integrating diverse inputs. Here, we review the diversity in forms of spatial and directional tuning of RSC activity, temporal organization of RSC activity, and features of RSC interconnectivity with other brain structures. We find that RSC anatomy and dynamics are more consistent with roles in multiple sensorimotor and cognitive processes than with any isolated function. However, two more generalized categories of function may best characterize roles for RSC in complex cognitive processes: (1) shifting and relating perspectives for spatial cognition and (2) prediction and error correction for current sensory states with internal representations of the environment. Both functions likely take advantage of RSC's capacity to encode conjunctions among sensory, motor, and spatial mapping information streams. Together, these functions provide the scaffold for intelligent actions, such as navigation, perspective taking, interaction with others, and error detection.

Reactivation of schema representation in lateral occipital cortex supports successful memory encoding

Schemas provide a scaffold onto which we can integrate new memories. Previous research has investigated the brain activity and connectivity underlying schema-related memory formation. However, how schemas are represented and reactivated in the brain, in order to enhance memory, remains unclear. To address this issue, we used an object–location spatial schema that was learned over multiple sessions, combined with similarity analyses of neural representations, to investigate the reactivation of schema representations of object–location memories when a new object–scene association is learned. In addition, we investigated how this reactivation affects subsequent memory performance under different strengths of schemas. We found that reactivation of a schema representation in the lateral occipital cortex (LOC) during object–scene encoding affected subsequent associative memory performance only in the schema-consistent condition and increased the functional connectivity between the LOC and the parahippocampal place area. Taken together, our findings provide new insight into how schema acts as a scaffold to support the integration of novel information into existing cortical networks and suggest a neural basis for schema-induced rapid cortical learning.

Environment Symmetry Drives a Multidirectional Code in Rat Retrosplenial Cortex

We investigated how environment symmetry shapes the neural processing of direction by recording directionally tuned retrosplenial neurons in male Lister hooded rats exploring multicompartment environments that had different levels of global rotational symmetry. Our hypothesis built on prior observations of twofold symmetry in the directional tuning curves of rats in a globally twofold-symmetric environment. To test whether environment symmetry was the relevant factor shaping the directional responses, here we deployed the same apparatus (two connected rectangular boxes) plus one with fourfold symmetry (a 2 × 2 array of connected square boxes) and one with onefold symmetry (a circular open-field arena). Consistent with our hypothesis we found many neurons with tuning curve symmetries that mirrored these environment symmetries, having twofold, fourfold, or onefold symmetric tuning, respectively. Some cells expressed this pattern only globally (across the whole environment), maintaining singular tuning curves in each subcompartment. However, others also expressed it locally within each subcompartment. Because multidirectionality has not been reported in naive rats in single environmental compartments, this suggests an experience-dependent effect of global environment symmetry on local firing symmetry. An intermingled population of directional neurons were classic head direction cells with globally referenced directional tuning. These cells were electrophysiologically distinct, with narrower tuning curves and a burstier firing pattern. Thus, retrosplenial directional neurons can simultaneously encode overall head direction and local head direction (relative to compartment layout). Furthermore, they can learn about global environment symmetry and express this locally. This may be important for the encoding of environment structure beyond immediate perceptual reach.SIGNIFICANCE STATEMENT We investigated how environment symmetry shapes the neural code for space by recording directionally tuned neurons from the retrosplenial cortex of rats exploring single- or multicompartment environments having onefold, twofold, or fourfold rotational symmetry. We found that many cells expressed a symmetry in their head direction tuning curves that matched the corresponding global environment symmetry, indicating plasticity of their directional tuning. They were also electrophysiologically distinct from canonical head directional cells. Notably, following exploration of the global space, many multidirectionally tuned neurons encoded global environment symmetry, even in local subcompartments. Our results suggest that multidirectional head direction codes contribute to the cognitive mapping of the complex structure of multicompartmented spaces.

Tackling the challenges of group network inference from intracranial EEG data

INTRODUCTION

Intracranial EEG (iEEG) data is a powerful way to map brain function, characterized by high temporal and spatial resolution, allowing the study of interactions among neuronal populations that orchestrate cognitive processing. However, the statistical inference and analysis of brain networks using iEEG data faces many challenges related to its sparse brain coverage, and its inhomogeneity across patients.

METHODS

We review these challenges and develop a methodological pipeline for estimation of network structure not obtainable from any single patient, illustrated on the inference of the interaction among visual streams using a dataset of 27 human iEEG recordings from a visual experiment employing visual scene stimuli. 100 ms sliding window and multiple band-pass filtered signals are used to provide temporal and spectral resolution. For the connectivity analysis we showcase two connectivity measures reflecting different types of interaction between regions of interest (ROI): Phase Locking Value as a symmetric measure of synchrony, and Directed Transfer Function-asymmetric measure describing causal interaction. For each two channels, initial uncorrected significance testing at p < 0.05 for every time-frequency point is carried out by comparison of the data-derived connectivity to a baseline surrogate-based null distribution, providing a binary time-frequency connectivity map. For each ROI pair, a connectivity density map is obtained by averaging across all pairs of channels spanning them, effectively agglomerating data across relevant channels and subjects. Finally, the difference of the mean map value after and before the stimulation is compared to the same statistic in surrogate data to assess link significance.

RESULTS

The analysis confirmed the function of the parieto-medial temporal pathway, mediating visuospatial information between dorsal and ventral visual streams during visual scene analysis. Moreover, we observed the anterior hippocampal connectivity with more posterior areas in the medial temporal lobe, and found the reciprocal information flow between early processing areas and medial place area.

DISCUSSION

To summarize, we developed an approach for estimating network connectivity, dealing with the challenge of sparse individual coverage of intracranial EEG electrodes. Its application provided new insights into the interaction between the dorsal and ventral visual streams, one of the iconic dualities in human cognition.

Scene-selective brain regions respond to embedded objects of a scene

Objects are fundamental to scene understanding. Scenes are defined by embedded objects and how we interact with them. Paradoxically, scene processing in the brain is typically discussed in contrast to object processing. Using the BOLD5000 dataset (Chang et al., 2019), we examined whether objects within a scene predicted the neural representation of scenes, as measured by functional magnetic resonance imaging in humans. Stimuli included 1,179 unique scenes across 18 semantic categories. Object composition of scenes were compared across scene exemplars in different semantic scene categories, and separately, in exemplars of the same scene category. Neural representations in scene- and object-preferring brain regions were significantly related to which objects were in a scene, with the effect at times stronger in the scene-preferring regions. The object model accounted for more variance when comparing scenes within the same semantic category to scenes from different categories. Here, we demonstrate the function of scene-preferring regions includes the processing of objects. This suggests visual processing regions may be better characterized by the processes, which are engaged when interacting with the stimulus kind, such as processing groups of objects in scenes, or processing a single object in our foreground, rather than the stimulus kind itself.

Ramp-shaped neural tuning supports graded population-level representation of the object-to-scene continuum

We can easily perceive the spatial scale depicted in a picture, regardless of whether it is a small space (e.g., a close-up view of a chair) or a much larger space (e.g., an entire class room). How does the human visual system encode this continuous dimension? Here, we investigated the underlying neural coding of depicted spatial scale, by examining the voxel tuning and topographic organization of brain responses. We created naturalistic yet carefully-controlled stimuli by constructing virtual indoor environments, and rendered a series of snapshots to smoothly sample between a close-up view of the central object and far-scale view of the full environment (object-to-scene continuum). Human brain responses were measured to each position using functional magnetic resonance imaging. We did not find evidence for a smooth topographic mapping for the object-to-scene continuum on the cortex. Instead, we observed large swaths of cortex with opposing ramp-shaped profiles, with highest responses to one end of the object-to-scene continuum or the other, and a small region showing a weak tuning to intermediate scale views. However, when we considered the population code of the entire ventral occipito-temporal cortex, we found smooth and linear representation of the object-to-scene continuum. Our results together suggest that depicted spatial scale information is encoded parametrically in large-scale population codes across the entire ventral occipito-temporal cortex.

Neural substrates of spatial processing and navigation in blindness: An activation likelihood estimation meta-analysis

Even though vision is considered the best suited sensory modality to acquire spatial information, blind individuals can form spatial representations to navigate and orient themselves efficiently in space. Consequently, many studies support the amodality hypothesis of spatial representations since sensory modalities other than vision contribute to the formation of spatial representations, independently of visual experience and imagery. However, given the high variability in abilities and deficits observed in blind populations, a clear consensus about the neural representations of space has yet to be established. To this end, we performed a meta-analysis of the literature on the neural correlates of spatial processing and navigation via sensory modalities other than vision, like touch and audition, in individuals with early and late onset blindness. An activation likelihood estimation (ALE) analysis of the neuroimaging literature revealed that early blind individuals and sighted controls activate the same neural networks in the processing of non-visual spatial information and navigation, including the posterior parietal cortex, frontal eye fields, insula, and the hippocampal complex. Furthermore, blind individuals also recruit primary and associative occipital areas involved in visuo-spatial processing via cross-modal plasticity mechanisms. The scarcity of studies involving late blind individuals did not allow us to establish a clear consensus about the neural substrates of spatial representations in this specific population. In conclusion, the results of our analysis on neuroimaging studies involving early blind individuals support the amodality hypothesis of spatial representations.

The hippocampus, ventromedial prefrontal cortex, and episodic and semantic memory

The human ventromedial prefrontal cortex (vmPFC)/anterior cingulate cortex is implicated in reward and emotion, but also in memory. It is shown how the human orbitofrontal cortex connecting with the vmPFC and anterior cingulate cortex provide a route to the hippocampus for reward and emotional value to be incorporated into episodic memory, enabling memory of where a reward was seen. It is proposed that this value component results in primarily episodic memories with some value component to be repeatedly recalled from the hippocampus so that they are more likely to become incorporated into neocortical semantic and autobiographical memories. The same orbitofrontal and anterior cingulate regions also connect in humans to the septal and basal forebrain cholinergic nuclei, thereby helping to consolidate memory, and helping to account for why damage to the vMPFC impairs memory. The human hippocampus and vmPFC thus contribute in complementary ways to forming episodic and semantic memories.

Multiple cortical visual streams in humans

The effective connectivity between 55 visual cortical regions and 360 cortical regions was measured in 171 HCP participants using the HCP-MMP atlas, and complemented with functional connectivity and diffusion tractography. A Ventrolateral Visual "What" Stream for object and face recognition projects hierarchically to the inferior temporal visual cortex, which projects to the orbitofrontal cortex for reward value and emotion, and to the hippocampal memory system. A Ventromedial Visual "Where" Stream for scene representations connects to the parahippocampal gyrus and hippocampus. An Inferior STS (superior temporal sulcus) cortex Semantic Stream receives from the Ventrolateral Visual Stream, from visual inferior parietal PGi, and from the ventromedial-prefrontal reward system and connects to language systems. A Dorsal Visual Stream connects via V2 and V3A to MT+ Complex regions (including MT and MST), which connect to intraparietal regions (including LIP, VIP and MIP) involved in visual motion and actions in space. It performs coordinate transforms for idiothetic update of Ventromedial Stream scene representations. A Superior STS cortex Semantic Stream receives visual inputs from the Inferior STS Visual Stream, PGi, and STV, and auditory inputs from A5, is activated by face expression, motion and vocalization, and is important in social behaviour, and connects to language systems.

Developmental changes in story-evoked responses in the neocortex and hippocampus

How does the representation of naturalistic life events change with age? Here, we analyzed fMRI data from 414 children and adolescents (5–19 years) as they watched a narrative movie. In addition to changes in the degree of inter-subject correlation (ISC) with age in sensory and medial parietal regions, we used a novel measure (between-group ISC) to reveal age-related shifts in the responses across the majority of the neocortex. Over the course of development, brain responses became more discretized into stable and coherent events and shifted earlier in time to anticipate upcoming perceived event transitions, measured behaviorally in an age-matched sample. However, hippocampal responses to event boundaries actually decreased with age, suggesting a shifting division of labor between episodic encoding processes and schematic event representations between the ages of 5 and 19.