Exploration-exploitation model of moth-inspired olfactory navigation.

Navigation of male moths towards females during the mating search offers a unique perspective on the exploration-exploitation (EE) model in decision-making. This study uses the EE model to explain male moth pheromone-driven flight paths. Wind tunnel measurements and three-dimensional tracking using infrared cameras have been leveraged to gain insights into male moth behaviour. During the experiments in the wind tunnel, disturbance to the airflow has been added and the effect of increased fluctuations on moth flights has been analysed, in the context of the proposed EE model. The exploration and exploitation phases are separated using a genetic algorithm to the experimentally obtained dataset of moth three-dimensional trajectories. First, the exploration-to-exploitation rate (EER) increases with distance from the source of the female pheromone is demonstrated, which can be explained in the context of the EE model. Furthermore, our findings reveal a compelling relationship between EER and increased flow fluctuations near the pheromone source. Using an olfactory navigation simulation and our moth-inspired navigation model, the phenomenon where male moths exhibit an enhanced EER as turbulence levels increase is explained. This research extends our understanding of optimal navigation strategies based on general biological EE models and supports the development of bioinspired navigation algorithms.

Distal but not local auditory information supports spatial representations by place cells.

Sound is an important navigational cue for mammals. During spatial navigation, hippocampal place cells encode spatial representations of the environment based on visual information, but to what extent audiospatial information can enable reliable place cell mapping is largely unknown. We assessed this by recording from CA1 place cells in the dark, under circumstances where reliable visual, tactile, or olfactory information was unavailable. Male rats were exposed to auditory cues of different frequencies that were delivered from local or distal spatial locations. We observed that distal, but not local cue presentation, enables and supports stable place fields, regardless of the sound frequency used. Our data suggest that a context dependency exists regarding the relevance of auditory information for place field mapping: whereas locally available auditory cues do not serve as a salient spatial basis for the anchoring of place fields, auditory cue localization supports spatial representations by place cells when available in the form of distal information. Furthermore, our results demonstrate that CA1 neurons can effectively use auditory stimuli to generate place fields, and that hippocampal pyramidal neurons are not solely dependent on visual cues for the generation of place field representations based on allocentric reference frames.

Inductive biases of neural network modularity in spatial navigation.

The brain may have evolved a modular architecture for daily tasks, with circuits featuring functionally specialized modules that match the task structure. We hypothesize that this architecture enables better learning and generalization than architectures with less specialized modules. To test this, we trained reinforcement learning agents with various neural architectures on a naturalistic navigation task. We found that the modular agent, with an architecture that segregates computations of state representation, value, and action into specialized modules, achieved better learning and generalization. Its learned state representation combines prediction and observation, weighted by their relative uncertainty, akin to recursive Bayesian estimation. This agent's behavior also resembles macaques' behavior more closely. Our results shed light on the possible rationale for the brain's modularity and suggest that artificial systems can use this insight from neuroscience to improve learning and generalization in natural tasks.

Modeling hippocampal spatial cells in rodents navigating in 3D environments.

Studies on the neural correlates of navigation in 3D environments are plagued by several issues that need to be solved. For example, experimental studies show markedly different place cell responses in rats and bats, both navigating in 3D environments. In this study, we focus on modelling the spatial cells in rodents in a 3D environment. We propose a deep autoencoder network to model the place and grid cells in a simulated agent navigating in a 3D environment. The input layer to the autoencoder network model is the HD layer, which encodes the agent's HD in terms of azimuth (θ) and pitch angles (ϕ). The output of this layer is given as input to the Path Integration (PI) layer, which computes displacement in all the preferred directions. The bottleneck layer of the autoencoder model encodes the spatial cell-like responses. Both grid cell and place cell-like responses are observed. The proposed model is verified using two experimental studies with two 3D environments. This model paves the way for a holistic approach using deep neural networks to model spatial cells in 3D navigation.

Parallel vector memories in the brain of a bee as foundation for flexible navigation.

Insects rely on path integration (vector-based navigation) and landmark guidance to perform sophisticated navigational feats, rivaling those seen in mammals. Bees in particular exhibit complex navigation behaviors including creating optimal routes and novel shortcuts between locations, an ability historically indicative of the presence of a cognitive map. A mammalian cognitive map has been widely accepted. However, in insects, the existence of a centralized cognitive map is highly contentious. Using a controlled laboratory assay that condenses foraging behaviors to short distances in walking bumblebees, we reveal that vectors learned during path integration can be transferred to long-term memory, that multiple such vectors can be stored in parallel, and that these vectors can be recalled at a familiar location and used for homeward navigation. These findings demonstrate that bees meet the two fundamental requirements of a vector-based analog of a decentralized cognitive map: Home vectors need to be stored in long-term memory and need to be recalled from remembered locations. Thus, our data demonstrate that bees possess the foundational elements for a vector-based map. By utilizing this relatively simple strategy for spatial organization, insects may achieve high-level navigation behaviors seen in vertebrates with the limited number of neurons in their brains, circumventing the computational requirements associated with the cognitive maps of mammals.

What Can Hippocampal Engrams Tell Us About Encoding Spatial Navigation?

The hippocampus is indispensable for episodic memories, but its particular role in the process is still unclear. This chapter briefly overviews past studies focusing on place cells and memory engrams, highlighting their potential roles in spatial navigation. Future work reconciling these two lines of studies would provide a comprehensive view of the specific contribution of the hippocampus and a better understanding of how memory engrams support memory.

Differential functions of the dorsal and intermediate regions of the hippocampus for optimal goal-directed navigation in VR space.

Goal-directed navigation requires the hippocampus to process spatial information in a value-dependent manner, but its underlying mechanism needs to be better understood. Here, we investigated whether the dorsal (dHP) and intermediate (iHP) regions of the hippocampus differentially function in processing place and its associated value information. Rats were trained in a place-preference task involving reward zones with different values in a visually rich virtual reality environment where two-dimensional navigation was possible. Rats learned to use distal visual scenes effectively to navigate to the reward zone associated with a higher reward. Inactivation of both dHP and iHP with muscimol altered the efficiency and precision of wayfinding behavior, but iHP inactivation induced more severe damage, including impaired place preference. Our findings suggest that the iHP is more critical for value-dependent navigation toward higher-value goal locations.

Human navigation strategies and their errors result from dynamic interactions of spatial uncertainties.

Goal-directed navigation requires continuously integrating uncertain self-motion and landmark cues into an internal sense of location and direction, concurrently planning future paths, and sequentially executing motor actions. Here, we provide a unified account of these processes with a computational model of probabilistic path planning in the framework of optimal feedback control under uncertainty. This model gives rise to diverse human navigational strategies previously believed to be distinct behaviors and predicts quantitatively both the errors and the variability of navigation across numerous experiments. This furthermore explains how sequential egocentric landmark observations form an uncertain allocentric cognitive map, how this internal map is used both in route planning and during execution of movements, and reconciles seemingly contradictory results about cue-integration behavior in navigation. Taken together, the present work provides a parsimonious explanation of how patterns of human goal-directed navigation behavior arise from the continuous and dynamic interactions of spatial uncertainties in perception, cognition, and action.

Spatial updating of gaze position in younger and older adults - A path integration-like process in eye movements.

Path integration (PI) is a navigation process that allows an organism to update its current location in reference to a starting point. PI can involve updating self-position continuously with respect to the starting point (continuous updating) or creating a map representation of the route which is then used to compute the homing vector (configural updating). One of the brain areas involved in PI, the entorhinal cortex, is modulated similarly by whole-body and eye movements, suggesting that if PI updates self-position, an analogous process may be used to update gaze position, and may undergo age-related changes. Here, we created an eyetracking version of a PI task in which younger and older participants followed routes with their eyes as guided by visual onsets; at the end of each route, participants were cued to return to the starting point or another enroute location. When only memory for the starting location was required for successful task performance, younger and older adults were generally not influenced by the number of locations, indicative of continuous updating. However, when participants could be cued to any enroute location, thereby requiring memory for the entire route, processing times increased, accuracy decreased, and overt revisits to enroute locations increased with the number of locations in a route, indicative of configural updating. Older participants showed evidence for similar updating strategies as younger participants, but they were less accurate and made more overt revisits to mid-route locations. These findings suggest that spatial updating mechanisms are generalizable across effector systems.

Executive function and spatial abilities in physically active children: an explorative study.

BACKGROUND: Regular physical activity has consistently shown promise in improving cognitive functioning among children. However, there is a shortage of comprehensive studies that delve into these benefits across various cognitive domains. This preliminary investigation aimed to discern potential disparities in cognitive performance between active and sedentary children, with a specific focus on inhibitory control, cognitive flexibility, and visuo-spatial working memory abilities. METHODS: The study employed a cross-sectional design encompassing 26 children (mean age 9.53 ± 2.20 years), categorized into two groups: Active and Sedentary. Executive functions were assessed using the NEPSY-II, while visuo-spatial working memory abilities were evaluated through the table version of the Radial Arm Maze (table-RAM) task. All outputs were analyzed with One-way ANOVAS or Kruskal-Wallis Tests to assess differences between Active and Sedentary children in both executive functioning and visuo-spatial working memory processes. RESULTS: The findings revealed that the Active group outperformed the sedentary group in inhibitory control (F1,23 = 4.99, p = 0.03*), cognitive flexibility (F1,23 = 5.77, p = 0.02*), spatial span (F1,23 = 4.40, p = 0.04*), and working memory errors (F1,23 = 8.59, p = 0.01**). Both spatial span and working memory errors are parameters closely associated with visuo-spatial working memory abilities. CONCLUSIONS: Although preliminary, these results offer evidence of a positive link between physical activity and cognitive functioning in children. This indicates the importance of promoting active behaviors, especially within educational environments.

Distance and grid-like codes support the navigation of abstract social space in the human brain.

People form impressions about others during daily social encounters and infer personality traits from others' behaviors. Such trait inference is thought to rely on two universal dimensions: competence and warmth. These two dimensions can be used to construct a 'social cognitive map' organizing massive information obtained from social encounters efficiently. Originating from spatial cognition, the neural codes supporting the representation and navigation of spatial cognitive maps have been widely studied. Recent studies suggest similar neural mechanism subserves the map-like architecture in social cognition as well. Here we investigated how spatial codes operate beyond the physical environment and support the representation and navigation of social cognitive map. We designed a social value space defined by two dimensions of competence and warmth. Behaviorally, participants were able to navigate to a learned location from random starting locations in this abstract social space. At the neural level, we identified the representation of distance in the precuneus, fusiform gyrus, and middle occipital gyrus. We also found partial evidence of grid-like representation patterns in the medial prefrontal cortex and entorhinal cortex. Moreover, the intensity of grid-like response scaled with the performance of navigating in social space and social avoidance trait scores. Our findings suggest a neurocognitive mechanism by which social information can be organized into a structured representation, namely cognitive map and its relevance to social well-being.

A recurrent network model of planning explains hippocampal replay and human behavior.

When faced with a novel situation, people often spend substantial periods of time contemplating possible futures. For such planning to be rational, the benefits to behavior must compensate for the time spent thinking. Here, we capture these features of behavior by developing a neural network model where planning itself is controlled by the prefrontal cortex. This model consists of a meta-reinforcement learning agent augmented with the ability to plan by sampling imagined action sequences from its own policy, which we call 'rollouts'. In a spatial navigation task, the agent learns to plan when it is beneficial, which provides a normative explanation for empirical variability in human thinking times. Additionally, the patterns of policy rollouts used by the artificial agent closely resemble patterns of rodent hippocampal replays. Our work provides a theory of how the brain could implement planning through prefrontal-hippocampal interactions, where hippocampal replays are triggered by-and adaptively affect-prefrontal dynamics.

Heart rate variability modulates memory function in a virtual task.

Heart rate variability (HRV) is considered one of the most relevant indicators of physical well-being and relevant biomarker for preventing cardiovascular risks. More recently, a growing amount of research has tracked an association between HRV and cognitive functions (i.e., attention). Research is still scarce on spatial orientation, a basic capability in our daily lives. It is also an important indicator of memory performance, and its malfunctioning working as an early sign of dementia. In this study, a total of 43 female students (M Age = 18.76; SD = 2.02) were measured in their lnRMSSD using the photoplethysmography technique with the Welltory smartphone app. They were also tested in their spatial memory with The Boxes Room, a virtual navigation test. Measures of physical activity were obtained with the International Physical Activity Questionnaire (IPAQ). Correlation analyses and repeated measures ANOVA were performed, comparing participants with high / low lnRMSSD in their spatial performance. Results showed that, at an equal level of physical activity, participants with a higher lnRMSSD were more effective in the early trials of The Boxes Room, being more precise in estimating the correct position of the stimuli. Moreover, a subsequent simple linear regression showed that a higher lnRMSSD was related to a smaller number of errors at the beginning of the spatial task. Overly, these results outline the relationship between HRV and navigation performance in early stages of processing, where the environment is still unknown and the situation is more demanding.

Mental navigation in the primate entorhinal cortex.

A cognitive map is a suitably structured representation that enables novel computations using previous experience; for example, planning a new route in a familiar space1. Work in mammals has found direct evidence for such representations in the presence of exogenous sensory inputs in both spatial2,3 and non-spatial domains4-10. Here we tested a foundational postulate of the original cognitive map theory1,11: that cognitive maps support endogenous computations without external input. We recorded from the entorhinal cortex of monkeys in a mental navigation task that required the monkeys to use a joystick to produce one-dimensional vectors between pairs of visual landmarks without seeing the intermediate landmarks. The ability of the monkeys to perform the task and generalize to new pairs indicated that they relied on a structured representation of the landmarks. Task-modulated neurons exhibited periodicity and ramping that matched the temporal structure of the landmarks and showed signatures of continuous attractor networks12,13. A continuous attractor network model of path integration14 augmented with a Hebbian-like learning mechanism provided an explanation of how the system could endogenously recall landmarks. The model also made an unexpected prediction that endogenous landmarks transiently slow path integration, reset the dynamics and thereby reduce variability. This prediction was borne out in a reanalysis of firing rate variability and behaviour. Our findings link the structured patterns of activity in the entorhinal cortex to the endogenous recruitment of a cognitive map during mental navigation.

Stochastic characterization of navigation strategies in an automated variant of the Barnes maze.

Animals can use a repertoire of strategies to navigate in an environment, and it remains an intriguing question how these strategies are selected based on the nature and familiarity of environments. To investigate this question, we developed a fully automated variant of the Barnes maze, characterized by 24 vestibules distributed along the periphery of a circular arena, and monitored the trajectories of mice over 15 days as they learned to navigate towards a goal vestibule from a random start vestibule. We show that the patterns of vestibule visits can be reproduced by the combination of three stochastic processes reminiscent of random, serial, and spatial strategies. The processes randomly selected vestibules based on either uniform (random) or biased (serial and spatial) probability distributions. They closely matched experimental data across a range of statistical distributions characterizing the length, distribution, step size, direction, and stereotypy of vestibule sequences, revealing a shift from random to spatial and serial strategies over time, with a strategy switch occurring approximately every six vestibule visits. Our study provides a novel apparatus and analysis toolset for tracking the repertoire of navigation strategies and demonstrates that a set of stochastic processes can largely account for exploration patterns in the Barnes maze.

Do Magnetic murmurs guide birds? A directional statistical investigation for influence of Earth's Magnetic field on bird navigation.

This paper delves into the intricate relationship between changes in Magnetic inclination and declination at specific geographical locations and the navigational decisions of migratory birds. Leveraging a dataset sourced from a prominent bird path tracking web resource, encompassing six distinct bird species' migratory trajectories, latitudes, longitudes, and observation timestamps, we meticulously analyzed the interplay between these avian movements and corresponding alterations in Magnetic inclination and declination. Employing a circular von Mises distribution assumption for the latitude and longitude distributions within each subdivision, we introduced a pioneering circular-circular regression model, accounting for von Mises error, to scrutinize our hypothesis. Our findings, predominantly supported by hypothesis tests conducted through circular-circular regression analysis, underscore the profound influence of Magnetic inclination and declination shifts on the dynamic adjustments observed in bird migration paths. Moreover, our meticulous examination revealed a consistent adherence to von Mises distribution across all bird directions. Notably, we unearthed compelling correlations between specific bird species, such as the Black Crowned Night Heron and Brown Pelican, exhibiting a noteworthy negative correlation with Magnetic inclination and a contrasting positive correlation with Magnetic declination. Similarly, the Pacific loon demonstrated a distinct negative correlation with Magnetic inclination and a positive association with Magnetic declination. Conversely, other avian counterparts showcased positive correlations with both Magnetic declination and inclination, further elucidating the nuanced dynamics between avian navigation and the Earth's magnetic field parameters.

Is there only one innate modular system for spatial navigation?

Spelke convincingly argues that we should posit six innate modular systems beyond the periphery (i.e., beyond low-level perception and motor control). I focus on the case of spatial navigation (Ch. 3) to claim that there remain powerful considerations in favor of positing additional innate, nonperipheral modules. This opens the door to stronger forms of nativism and nonperipheral modularism than Spelke's.

Hippocampal-dependent navigation in head-fixed mice using a floating real-world environment.

Head-fixation of mice enables high-resolution monitoring of neuronal activity coupled with precise control of environmental stimuli. Virtual reality can be used to emulate the visual experience of movement during head fixation, but a low inertia floating real-world environment (mobile homecage, MHC) has the potential to engage more sensory modalities and provide a richer experimental environment for complex behavioral tasks. However, it is not known whether mice react to this adapted environment in a similar manner to real environments, or whether the MHC can be used to implement validated, maze-based behavioral tasks. Here, we show that hippocampal place cell representations are intact in the MHC and that the system allows relatively long (20 min) whole-cell patch clamp recordings from dorsal CA1 pyramidal neurons, revealing sub-threshold membrane potential dynamics. Furthermore, mice learn the location of a liquid reward within an adapted T-maze guided by 2-dimensional spatial navigation cues and relearn the location when spatial contingencies are reversed. Bilateral infusions of scopolamine show that this learning is hippocampus-dependent and requires intact cholinergic signalling. Therefore, we characterize the MHC system as an experimental tool to study sub-threshold membrane potential dynamics that underpin complex navigation behaviors.

Wayfinding in pairs: comparing the planning and navigation performance of dyads and individuals in a real-world environment.

Navigation is essential to life, and it is cognitively complex, drawing on abilities such as prospective and situated planning, spatial memory, location recognition, and real-time decision-making. In many cases, day-to-day navigation is embedded in a social context where cognition and behavior are shaped by others, but the great majority of existing research in spatial cognition has focused on individuals. The two studies we report here contribute to our understanding of social wayfinding, assessing the performance of paired and individual navigators on a real-world wayfinding task in which they were instructed to minimize time and distance traveled. In the first study, we recruited 30 pairs of friends (familiar dyads); in the second, we recruited 30 solo participants (individuals). We compare the two studies to the results of an earlier study of 30 pairs of strangers (unfamiliar dyads). We draw out differences in performance with respect to spatial, social, and cognitive considerations. Of the three conditions, solo participants were least successful in reaching the destination accurately on their initial attempt. Friends traveled more efficiently than either strangers or individuals. Working with a partner also appeared to lend confidence to wayfinders: dyads of either familiarity type were more persistent than individuals in the navigation task, even after encountering challenges or making incorrect attempts. Route selection was additionally impacted by route complexity and unfamiliarity with the study area. Navigators explicitly used ease of remembering as a planning criterion, and the resulting differences in route complexity likely influenced success during enacted navigation.

Cumulative route improvements spontaneously emerge in artificial navigators even in the absence of sophisticated communication or thought.

Homing pigeons (Columba livia) navigate by solar and magnetic compass, and fly home in idiosyncratic but stable routes when repeatedly released from the same location. However, when experienced pigeons fly alongside naive counterparts, their path is altered. Over several generations of turnover (pairs in which the most experienced individual is replaced with a naive one), pigeons show cumulative improvements in efficiency. Here, I show that such cumulative route improvements can occur in a much simpler system by using agent-based simulation. Artificial agents are in silico entities that navigate with a minimal cognitive architecture of goal-direction (they know roughly where the goal is), social proximity (they seek proximity to others and align headings), route memory (they recall landmarks with increasing precision), and continuity (they avoid erratic turns). Agents' behaviour qualitatively matched that of pigeons, and quantitatively fitted to pigeon data. My results indicate that naive agents benefitted from being paired with experienced agents by following their previously established route. Importantly, experienced agents also benefitted from being paired with naive agents due to regression to the goal: naive agents were more likely to err towards the goal from the perspective of experienced agents' memorised paths. This subtly biased pairs in the goal direction, resulting in intergenerational improvements of route efficiency. No cumulative improvements were evident in control studies in which agents' goal-direction, social proximity, or memory were lesioned. These 3 factors are thus necessary and sufficient for cumulative route improvements to emerge, even in the absence of sophisticated communication or thought.