Formation Of Cognitive Maps Research Articles

Pre-protocol of the Virtual Spatial Configuration Task (VSCT): A Novel Virtual Reality-Based Tool for Assessing Cognitive Map Formation Abilities

This study proposes the validation of the Virtual Spatial Configuration Task (VSCT), a novel task designed to evaluate cognitive map formation abilities in participants. Addressing a notable gap in spatial cognition research, particularly in the assessment of higher-level spatial abilities in 3D environments, the VSCT offers a virtual reality (VR) approach that allows users to explore and recall spatial relationships between landmarks. This task is particularly innovative for populations with impaired mobility, as it simplifies navigation by restricting movement to rotational exploration, thus improving accessibility and reducing motion sickness. Furthermore, the VSCT could serve a dual purpose: assessing spatial orientation skills while also providing a platform for training and improving these skills post-injury. The potential applications of this tool extend to neurorehabilitation and other therapeutic interventions, offering an engaging, immersive method for enhancing spatial abilities.

The medial and lateral orbitofrontal cortex jointly represent the cognitive map of task space

A cognitive map is an internal model of the world’s causal structure, crucial for adaptive behaviors. The orbitofrontal cortex (OFC) is central node to decision-making and cognitive map representation. However, it remains unclear how the medial OFC (mOFC) and lateral OFC (lOFC) contribute to the formation of cognitive maps in humans. By performing a multi-step sequential task and multivariate analyses of functional magnetic resonance imaging (fMRI) data, we found that the mOFC and lOFC play complementary but dissociable roles in this process. Specifically, the mOFC represents all hidden task state components. The lOFC and dorsolateral prefrontal cortex (dlPFC) encode abstract rules governing structure knowledge across task states. Furthermore, the two orbitofrontal subregions are functionally connected to share state-hidden information for constructing a representation of the task structure. Collectively, these findings provide an account that can increase our understanding of how the brain constructs abstract cognitive maps in a task-relevant space.

Curiosity shapes spatial exploration and cognitive map formation in humans

AbstractCognitive maps are thought to arise, at least in part, from our intrinsic curiosity to explore unknown places. However, it remains untested how curiosity shapes aspects of spatial exploration in humans. Combining a virtual reality task with indices of exploration complexity, we found that pre-exploration curiosity states predicted how much individuals spatially explored environments, whereas markers of visual exploration determined post-exploration feelings of interest. Moreover, individual differences in curiosity traits, particularly Stress Tolerance, modulated the relationship between curiosity and spatial exploration, suggesting the capacity to cope with uncertainty enhances the curiosity-exploration link. Furthermore, both curiosity and spatial exploration predicted how precisely participants could recall spatial-relational details of the environment, as measured by a sketch map task. These results provide new evidence for a link between curiosity and exploratory behaviour, and how curiosity might shape cognitive map formation.

Brain–computer interface for simultaneous dual‐region spatial coding in hippocampal and somatosensory cortex of freely behaving rats

AbstractDecoding of spatial information from place cells is currently limited to individual brain regions, severely constraining the understanding of the brain's spatial navigation mechanisms. In this study, synchronized detection of dual‐brain region spatial encoding was conducted using brain–computer interface (BCI). Therefore, an implantable microelectrode array (MEA) was developed tailored for the simultaneous detection of neuronal activities in the CA1 of the hippocampus and the Barrel Cortex (BC) of the somatosensory cortex in rats as BCI. The MEA was improved by modifying the nanocomposite PtNP/PEDOT:PSS to improve their electrical properties (reducing impedance from 1.82 ± 0.17 MΩ to 3.4 ± 0.3 kΩ), facilitating neural recordings in freely behaving rats. The neural activities were obtained from the CA1 and the BC simultaneously and validated the existence of place cells in both brain regions. This study highlighted the potential of PtNP/PEDOT:PSS‐modified MEA as BCI in concurrently detecting neural activity associated with spatial encoding in two brain regions, offering novel perspectives on the processing of tactile stimuli and the formation of cognitive maps for navigation.

Decomposing geographical judgments into spatial, temporal and linguistic components

When mentally exploring maps representing large-scale environments (e.g., countries or continents), humans are assumed to mainly rely on spatial information derived from direct perceptual experience (e.g., prior visual experience with the geographical map itself). In the present study, we rather tested whether also temporal and linguistic information could account for the way humans explore and ultimately represent this type of maps. We quantified temporal distance as the minimum time needed to travel by train across Italian cities, while linguistic distance was retrieved from natural language through cognitively plausible AI models based on non-spatial associative learning mechanisms (i.e., distributional semantic models). In a first experiment, we show that temporal and linguistic distances capture with high-confidence real geographical distances. Next, in a second behavioral experiment, we show that linguistic information can account for human performance over and above real spatial information (which plays the major role in explaining participants’ performance) in a task in which participants have to judge the distance between cities (while temporal information was found to be not relevant). These findings indicate that, when exploring maps representing large-scale environments, humans do take advantage of both perceptual and linguistic information, suggesting in turn that the formation of cognitive maps possibly relies on a strict interplay between spatial and non-spatial learning principles.

COGNITIVE MAPS OF A CITY AS A SOCIO-PSYCHOLOGICAL FACTOR OF INDIVIDUAL PERCEPTION OF URBAN SPACES

The article considers the role of cognitive maps in the perception of urban space and their influence on social interaction and self-identification of city dwellers. The author analyses how mental ideas about a city are formed under the influence of personal experience, cultural and social factors. The relationship between cognitive maps and urban planning is investigated, and ways to optimise the urban environment based on understanding the mental maps of residents are proposed. In particular, the theoretical foundations of cognitive map formation are reviewed, including the works of Kevin Lynch, Edward Tolman, and other leading researchers who have laid the foundation for understanding the processes of mental mapping of urban spaces. The author of the article studies how personal experience, cultural and social contexts contribute to the creation of unique cognitive maps that reflect individual perception of a city.

The well-worn route revisited: Striatal and hippocampal system contributions to familiar route navigation.

Classic research has shown a division in the neuroanatomical structures that support flexible (e.g., short-cutting) and habitual (e.g., familiar route following) navigational behavior, with hippocampal-caudate systems associated with the former and putamen systems with the latter. There is, however, disagreement about whether the neural structures involved in navigation process particular forms of spatial information, such as associations between constellations of cues forming a cognitive map, versus single landmark-action associations, or alternatively, perform particular reinforcement learning algorithms that allow the use of different spatial strategies, so-called model-based (flexible) or model-free (habitual) forms of learning. We sought to test these theories by asking participants (N = 24) to navigate within a virtual environment through a previously learned, 9-junction route with distinctive landmarks at each junction while undergoing functional magnetic resonance imaging (fMRI). In a series of probe trials, we distinguished knowledge of individual landmark-action associations along the route versus knowledge of the correct sequence of landmark-action associations, either by having absent landmarks, or "out-of-sequence" landmarks. Under a map-based perspective, sequence knowledge would not require hippocampal systems, because there are no constellations of cues available for cognitive map formation. Within a learning-based model, however, responding based on knowledge of sequence would require hippocampal systems because prior context has to be utilized. We found that hippocampal-caudate systems were more active in probes requiring sequence knowledge, supporting the learning-based model. However, we also found greater putamen activation in probes where navigation based purely on sequence memory could be planned, supporting models of putamen function that emphasize its role in action sequencing.

Analysis of hippocampal local field potentials by diffusion mapped delay coordinates

Spatial navigation through novel spaces and to known goal locations recruits multiple integrated structures in the mammalian brain. Within this extended network, the hippocampus enables formation and retrieval of cognitive spatial maps and contributes to decision making at choice points. Exploration and navigation to known goal locations produce synchronous activity of hippocampal neurons resulting in rhythmic oscillation events in local networks. Power of specific oscillatory frequencies and numbers of these events recorded in local field potentials correlate with distinct cognitive aspects of spatial navigation. Typically, oscillatory power in brain circuits is analyzed with Fourier transforms or short-time Fourier methods, which involve assumptions about the signal that are likely not true and fail to succinctly capture potentially informative features. To avoid such assumptions, we applied a method that combines manifold discovery techniques with dynamical systems theory, namely diffusion maps and Takens’ time-delay embedding theory, that avoids limitations seen in traditional methods. This method, called diffusion mapped delay coordinates (DMDC), when applied to hippocampal signals recorded from juvenile rats freely navigating a Y-maze, replicates some outcomes seen with standard approaches and identifies age differences in dynamic states that traditional analyses are unable to detect. Thus, DMDC may serve as a suitable complement to more traditional analyses of LFPs recorded from behaving subjects that may enhance information yield.

ЦИФРОВЫЕ ТЕХНОЛОГИИ УПРАВЛЕНИЯ БИОТЕХНОЛОГИЧЕСКИМИ ПРОЦЕССАМИ НА ОСНОВЕ КОГНИТИВНОГО МОДЕЛИРОВАНИЯ (НА ПРИМЕРЕ ЗАЩИТЫ НАСАЖДЕНИЙ ЯБЛОНИ ОТ ЯБЛОННОЙ ПЛОДОЖОРКИ)

The necessity of developing digital technologies for managing biotechnological processes in long-term agrocenoses based on cognitive modeling is substantiated. Methodological approaches to the construction of effective management tools for biotechnological processes based on the logical concept of the triad (organization, management, efficiency) in a dynamic cycle have been developed. An algorithm for the formation of digital technologies for managing biotechnological processes is proposed, including: the formation of multifunctional databases and data banks and digital applications, cognitive modeling of system relationships and the formation of cognitive maps, the development of a system architecture of a prototype program, approbation and verification of the adequacy of a digital application. An algorithm has been developed for constructing cognitive models for the formation of management tools for biotechnological processes in long-term agrocenoses, including clarification of goal setting and local tasks; the distribution of functional relationships between the structural components of the agrocenosis using methods of correlation and regression analysis; economic and statistical characteristics of systemic relationships in reproductive processes by functional areas of influence using correlation matrices and discriminant analysis; verification of the results of optimization of parameters of functional stability and technological and economic efficiency of production and technological processes. A cognitive process management map is constructed using the example of protecting fruit plantations from pests. A flowchart of an algorithm for building a digital control program for biotechnological processes for protecting fruit plantations is proposed using the example of an apple moth, which provides for the development of a technology for importing data from a weather station to determine the sum of effective temperatures and determine the start of processing depending on the stage of development of the pest; neural network technologies for detecting a harmful object; a module for automated selection of a protection system. Key words: DIGITAL TECHNOLOGIES, MANAGEMENT, BIOTECHNOLOGICAL PROCESSES, PLANT PROTECTION, COGNITIVE MODELING, ALGORITHM, MODEL

Sex and menstrual cycle influence human spatial navigation strategies and performance

Which facets of human spatial navigation do sex and menstrual cycle influence? To answer this question, a cross-sectional online study of reproductive age women and men was conducted in which participants were asked to demonstrate and self-report their spatial navigation skills and strategies. Participants self-reported their sex and current menstrual phase [early follicular (EF), late follicular/periovulatory (PO), and mid/late luteal (ML)], and completed a series of questionnaires and tasks measuring self-reported navigation strategy use, topographical memory, cognitive map formation, face recognition, and path integration. We found that sex influenced self-reported use of cognitive map- and scene-based strategies, face recognition, and path integration. Menstrual phase moderated the influence of sex: compared to men, women had better face recognition and worse path integration, but only during the PO phase; PO women were also better at path integration in the presence of a landmark compared to EF + ML women and men. These findings provide evidence that human spatial navigation varies with the menstrual cycle and suggest that sensitivity of the entorhinal cortex and longitudinal axis of the hippocampus to differential hormonal effects may account for this variation.

Route sequence knowledge supports the formation of cognitive maps.

In this study, we examined the extent to which knowledge about the sequence of places encountered during route learning supports the formation of a metric cognitive map. In a between subjects design, participants learned a route until they could navigate it independently without error whilst also learning information about either the identity of places along the route (Recognition Learning condition) or the sequence of places along the route (Sequence Learning condition). In a follow-up Reconstruction of Order Task, we confirmed that participants in the Sequence Learning condition had more accurate route sequence knowledge than those in the Recognition Learning condition, despite requiring the same overall number of trials to learn the route. Participants then completed a Pointing Task to assess the quality of their cognitive map of the environment. Both groups performed above chance level, showing incidental encoding of metric information, but the Sequence Learning group produced significantly lower pointing errors than the Recognition Learning group. Further, we found that route distance between pairs of places was a strong predictor of pointing error in both groups, whilst Euclidean distance between places was a significant, but weak, predictor only for the Sequence Learning condition. The results of this study demonstrate that discrete route sequence knowledge directly supports the formation of metric cognitive maps. We consider how the results are best explained by interactions between striatal route representations and hippocampal metric representations, centered around the sequence of places acting as a scaffold for the encoding of metric information.

Cognitive map formation in the blind is enhanced by three-dimensional tactile information

For blind individuals, tactile maps are useful tools to form cognitive maps through touch. However, they still experience challenges in cognitive map formation and independent navigation. Three-dimensional (3D) tactile information is thus increasingly being considered to convey enriched spatial information, but it remains unclear if it can facilitate cognitive map formation compared to traditional two-dimensional (2D) tactile information. Consequently, the present study investigated the impact of the type of sensory input (tactile 2D vs. tactile 3D vs. a visual control condition) on cognitive map formation. To do so, early blind (EB, n = 13), late blind (LB, n = 12), and sighted control (SC, n = 14) participants were tasked to learn the layouts of mazes produced with different sensory information (tactile 2D vs. tactile 3D vs. visual control) and to infer routes from memory. Results show that EB manifested stronger cognitive map formation with 3D mazes, LB performed equally well with 2D and 3D tactile mazes, and SC manifested equivalent cognitive map formation with visual and 3D tactile mazes but were negatively impacted by 2D tactile mazes. 3D tactile maps therefore have the potential to improve spatial learning for EB and newly blind individuals through a reduction of cognitive overload. Installation of 3D tactile maps in public spaces should be considered to promote universal accessibility and reduce blind individuals’ wayfinding deficits related to the inaccessibility of spatial information through non-visual means.

Neural network based formation of cognitive maps of semantic spaces and the putative emergence of abstract concepts

How do we make sense of the input from our sensory organs, and put the perceived information into context of our past experiences? The hippocampal-entorhinal complex plays a major role in the organization of memory and thought. The formation of and navigation in cognitive maps of arbitrary mental spaces via place and grid cells can serve as a representation of memories and experiences and their relations to each other. The multi-scale successor representation is proposed to be the mathematical principle underlying place and grid cell computations. Here, we present a neural network, which learns a cognitive map of a semantic space based on 32 different animal species encoded as feature vectors. The neural network successfully learns the similarities between different animal species, and constructs a cognitive map of ‘animal space’ based on the principle of successor representations with an accuracy of around 30% which is near to the theoretical maximum regarding the fact that all animal species have more than one possible successor, i.e. nearest neighbor in feature space. Furthermore, a hierarchical structure, i.e. different scales of cognitive maps, can be modeled based on multi-scale successor representations. We find that, in fine-grained cognitive maps, the animal vectors are evenly distributed in feature space. In contrast, in coarse-grained maps, animal vectors are highly clustered according to their biological class, i.e. amphibians, mammals and insects. This could be a putative mechanism enabling the emergence of new, abstract semantic concepts. Finally, even completely new or incomplete input can be represented by interpolation of the representations from the cognitive map with remarkable high accuracy of up to 95%. We conclude that the successor representation can serve as a weighted pointer to past memories and experiences, and may therefore be a crucial building block to include prior knowledge, and to derive context knowledge from novel input. Thus, our model provides a new tool to complement contemporary deep learning approaches on the road towards artificial general intelligence.

Optimal Quadratic Binding for Relational Reasoning in Vector Symbolic Neural Architectures.

Binding operation is fundamental to many cognitive processes, such as cognitive map formation, relational reasoning, and language comprehension. In these processes, two different modalities, such as location and objects, events and their contextual cues, and words and their roles, need to be bound together, but little is known about the underlying neural mechanisms. Previous work has introduced a binding model based on quadratic functions of bound pairs, followed by vector summation of multiple pairs. Based on this framework, we address the following questions: Which classes of quadratic matrices are optimal for decoding relational structures? And what is the resultant accuracy? We introduce a new class of binding matrices based on a matrix representation of octonion algebra, an eight-dimensional extension of complex numbers. We show that these matrices enable a more accurate unbinding than previously known methods when a small number of pairs are present. Moreover, numerical optimization of a binding operator converges to this octonion binding. We also show that when there are a large number of bound pairs, however, a random quadratic binding performs, as well as the octonion and previously proposed binding methods. This study thus provides new insight into potential neural mechanisms of binding operations in the brain.

Listening to the Voice of People with Vision Impairment

Extensive research developed assistive technologies (ATs) to improve mobility for people with vision impairment (PVI). However, a limited number of PVI rely on ATs for mobility. One of the factors contributing to the limited reliability and low acceptance of ATs is the developers’ failure to consider PVI mobility traits from the target group’s perspective. Many developers and researchers proposed solutions based on their knowledge and experiences, where PVI have been excluded from several studies except for limited involvement in testing phases. Accordingly, this study aims to bridge this gap by providing comprehensive information on PVIs’ behaviors, challenges, and requirements for safe and independent outdoor mobility. Therefore, a total of 15 participants with vision impairment were involved in semi-structured interviews and two observation sessions. One key finding highlights the need for AT that complements the conventional cane and overcomes its limitations, not substituting the cane. Moreover, the proposed AT should address instant mobility and future needs simultaneously. Overall, the study contributes to providing comprehensive knowledge on PVI safe and independent mobility traits, which assist AT developers to explore the potential barriers and facilitators of the adoption of ATs among PVIs and leads to develop effective and reliable ATs that meet their needs. For future work, the researchers will develop an AT that complements the conventional cane, supports instant mobility, and enhances cognitive map formation.

Cognitive map formation through tactile map navigation in visually impaired and sighted persons

The human brain can form cognitive maps of a spatial environment, which can support wayfinding. In this study, we investigated cognitive map formation of an environment presented in the tactile modality, in visually impaired and sighted persons. In addition, we assessed the acquisition of route and survey knowledge. Ten persons with a visual impairment (PVIs) and ten sighted control participants learned a tactile map of a city-like environment. The map included five marked locations associated with different items. Participants subsequently estimated distances between item pairs, performed a direction pointing task, reproduced routes between items and recalled item locations. In addition, we conducted questionnaires to assess general navigational abilities and the use of route or survey strategies. Overall, participants in both groups performed well on the spatial tasks. Our results did not show differences in performance between PVIs and sighted persons, indicating that both groups formed an equally accurate cognitive map. Furthermore, we found that the groups generally used similar navigational strategies, which correlated with performance on some of the tasks, and acquired similar and accurate route and survey knowledge. We therefore suggest that PVIs are able to employ a route as well as survey strategy if they have the opportunity to access route-like as well as map-like information such as on a tactile map.

Neural network based successor representations to form cognitive maps of space and language

How does the mind organize thoughts? The hippocampal-entorhinal complex is thought to support domain-general representation and processing of structural knowledge of arbitrary state, feature and concept spaces. In particular, it enables the formation of cognitive maps, and navigation on these maps, thereby broadly contributing to cognition. It has been proposed that the concept of multi-scale successor representations provides an explanation of the underlying computations performed by place and grid cells. Here, we present a neural network based approach to learn such representations, and its application to different scenarios: a spatial exploration task based on supervised learning, a spatial navigation task based on reinforcement learning, and a non-spatial task where linguistic constructions have to be inferred by observing sample sentences. In all scenarios, the neural network correctly learns and approximates the underlying structure by building successor representations. Furthermore, the resulting neural firing patterns are strikingly similar to experimentally observed place and grid cell firing patterns. We conclude that cognitive maps and neural network-based successor representations of structured knowledge provide a promising way to overcome some of the short comings of deep learning towards artificial general intelligence.

Neurophysiological Evidence for Cognitive Map Formation during Sequence Learning.

Humans deftly parse statistics from sequences. Some theories posit that humans learn these statistics by forming cognitive maps, or underlying representations of the latent space which links items in the sequence. Here, an item in the sequence is a node, and the probability of transitioning between two items is an edge. Sequences can then be generated from walks through the latent space, with different spaces giving rise to different sequence statistics. Individual or group differences in sequence learning can be modeled by changing the time scale over which estimates of transition probabilities are built, or in other words, by changing the amount of temporal discounting. Latent space models with temporal discounting bear a resemblance to models of navigation through Euclidean spaces. However, few explicit links have been made between predictions from Euclidean spatial navigation and neural activity during human sequence learning. Here, we use a combination of behavioral modeling and intracranial encephalography (iEEG) recordings to investigate how neural activity might support the formation of space-like cognitive maps through temporal discounting during sequence learning. Specifically, we acquire human reaction times from a sequential reaction time task, to which we fit a model that formulates the amount of temporal discounting as a single free parameter. From the parameter, we calculate each individual’s estimate of the latent space. We find that neural activity reflects these estimates mostly in the temporal lobe, including areas involved in spatial navigation. Similar to spatial navigation, we find that low-dimensional representations of neural activity allow for easy separation of important features, such as modules, in the latent space. Lastly, we take advantage of the high temporal resolution of iEEG data to determine the time scale on which latent spaces are learned. We find that learning typically happens within the first 500 trials, and is modulated by the underlying latent space and the amount of temporal discounting characteristic of each participant. Ultimately, this work provides important links between behavioral models of sequence learning and neural activity during the same behavior, and contextualizes these results within a broader framework of domain general cognitive maps.

Methodological approaches to digitalization of biotechnological processes in industrial viticulture

Factors affecting the stability and efficiency of reproduction processes in industrial viticulture have been identified. Destructive changes in the elements of grape agrocenosis in the conditions of changing climatic factors and chemical-technogenic intensification of production are determined. A generalizing characteristic of the biologization of intensification processes in industrial viticulture is given. It is established that the strategic appearance of promising technologies in viticulture is determined by modern methods of process biologization and their management based on digital technologies. The functional content of digitalization of management of biotechnological processes in grape agrocenoses is identified. An algorithm for the formation of digital technologies for managing biotechnological processes is proposed, including: the formation of multifunctional databases and data banks on technology elements, the formation of digital applications, the formation of an empirical database and geocoded collection of information on technological operations, cognitive modeling of system relationships and the formation of cognitive maps that determine the influence of external and internal environmental factors on functional areas of influence, the development of a system program prototype architectures, approbation and verification of the adequacy of digital technologies. An assessment of the effectiveness of the use of digital technologies in the management of biotechnological processes in viticulture is given.

Parallel processing of sensory cue and spatial information in the dentate gyrus.

SUMMARYDuring exploration, animals form an internal map of an environment by combining information about landmarks and the animal’s movement, a process that depends on the hippocampus. The dentate gyrus (DG) is the first stage of the hippocampal circuit where self-motion (“where”) and sensory cue information (“what”) are integrated, but it remains unknown how DG neurons encode this information during cognitive map formation. Using two-photon calcium imaging in mice running on a treadmill along with online cue manipulation, we identify robust sensory cue responses in DG granule cells. Cue cell responses are stable, stimulus-specific, and accompanied by inhibition of nearby neurons. This demonstrates the existence of “cue cells” in addition to better characterized “place cells” in the DG. We hypothesize that the DG supports parallel channels of spatial and non-spatial information that contribute distinctly to downstream computations and affect roles of the DG in spatial navigation and episodic memory.