A novel somatosensory spatial navigation system outside the hippocampal formation

Spatially selective firing of place cells, grid cells, boundary vector/border cells and head direction cells constitutes the basic building blocks of a canonical spatial navigation system centered on the hippocampal-entorhinal complex. While head direction cells can be found throughout the brain, spatial tuning outside the hippocampal formation is often non-specific or conjunctive to other representations such as a reward. Although the precise mechanism of spatially selective firing activity is not understood, various studies show sensory inputs, particularly vision, heavily modulate spatial representation in the hippocampal-entorhinal circuit. To better understand the contribution of other sensory inputs in shaping spatial representation in the brain, we performed recording from the primary somatosensory cortex in foraging rats. To our surprise, we were able to detect the full complement of spatially selective firing patterns similar to that reported in the hippocampal-entorhinal network, namely, place cells, head direction cells, boundary vector/border cells, grid cells and conjunctive cells, in the somatosensory cortex. These newly identified somatosensory spatial cells form a spatial map outside the hippocampal formation and support the hypothesis that location information modulates body representation in the somatosensory cortex. Our findings provide transformative insights into our understanding of how spatial information is processed and integrated in the brain, as well as functional operations of the somatosensory cortex in the context of rehabilitation with brain-machine interfaces.Subject terms: Biological techniques, Cell biology     

Estimating Location without External Cues

The ability to determine one''s location is fundamental to spatial navigation. Here, it is shown that localization is theoretically possible without the use of external cues, and without knowledge of initial position or orientation. With only error-prone self-motion estimates as input, a fully disoriented agent can, in principle, determine its location in familiar spaces with 1-fold rotational symmetry. Surprisingly, localization does not require the sensing of any external cue, including the boundary. The combination of self-motion estimates and an internal map of the arena provide enough information for localization. This stands in conflict with the supposition that 2D arenas are analogous to open fields. Using a rodent error model, it is shown that the localization performance which can be achieved is enough to initiate and maintain stable firing patterns like those of grid cells, starting from full disorientation. Successful localization was achieved when the rotational asymmetry was due to the external boundary, an interior barrier or a void space within an arena. Optimal localization performance was found to depend on arena shape, arena size, local and global rotational asymmetry, and the structure of the path taken during localization. Since allothetic cues including visual and boundary contact cues were not present, localization necessarily relied on the fusion of idiothetic self-motion cues and memory of the boundary. Implications for spatial navigation mechanisms are discussed, including possible relationships with place field overdispersion and hippocampal reverse replay. Based on these results, experiments are suggested to identify if and where information fusion occurs in the mammalian spatial memory system.     

The neural mechanisms of long distance animal navigation

Animal navigation is a complex process involving the integration of many sources of specialized sensory information for navigation in near and far space. Our understanding of the neurobiological underpinnings of near-space navigation is well-developed, whereas the neural mechanisms of long-distance navigation are just beginning to be unraveled. One crucial question for future research is whether the near space concepts of place cells, head direction cells, and maps in the entorhinal cortex scale up to animals navigating over very long distances and whether they are related to the map and compass concepts of long-distance navigation.     

Independence of landmark and self-motion-guided navigation: a different role for grid cells

Recent interest in the neural bases of spatial navigation stems from the discovery of neuronal populations with strong, specific spatial signals. The regular firing field arrays of medial entorhinal grid cells suggest that they may provide place cells with distance information extracted from the animal''s self-motion, a notion we critically review by citing new contrary evidence. Next, we question the idea that grid cells provide a rigid distance metric. We also discuss evidence that normal navigation is possible using only landmarks, without self-motion signals. We then propose a model that supposes that information flow in the navigational system changes between light and dark conditions. We assume that the true map-like representation is hippocampal and argue that grid cells have a crucial navigational role only in the dark. In this view, their activity in the light is predominantly shaped by landmarks rather than self-motion information, and so follows place cell activity; in the dark, their activity is determined by self-motion cues and controls place cell activity. A corollary is that place cell activity in the light depends on non-grid cells in ventral medial entorhinal cortex. We conclude that analysing navigational system changes between landmark and no-landmark conditions will reveal key functional properties.     

A model of head direction and landmark coding in complex environments

Environmental information is required to stabilize estimates of head direction (HD) based on angular path integration. However, it is unclear how this happens in real-world (visually complex) environments. We present a computational model of how visual feedback can stabilize HD information in environments that contain multiple cues of varying stability and directional specificity. We show how combinations of feature-specific visual inputs can generate a stable unimodal landmark bearing signal, even in the presence of multiple cues and ambiguous directional specificity. This signal is associated with the retrosplenial HD signal (inherited from thalamic HD cells) and conveys feedback to the subcortical HD circuitry. The model predicts neurons with a unimodal encoding of the egocentric orientation of the array of landmarks, rather than any one particular landmark. The relationship between these abstract landmark bearing neurons and head direction cells is reminiscent of the relationship between place cells and grid cells. Their unimodal encoding is formed from visual inputs via a modified version of Oja’s Subspace Algorithm. The rule allows the landmark bearing signal to disconnect from directionally unstable or ephemeral cues, incorporate newly added stable cues, support orientation across many different environments (high memory capacity), and is consistent with recent empirical findings on bidirectional HD firing reported in the retrosplenial cortex. Our account of visual feedback for HD stabilization provides a novel perspective on neural mechanisms of spatial navigation within richer sensory environments, and makes experimentally testable predictions.     

A biologically inspired hierarchical goal directed navigation model

We propose an extended version of our previous goal directed navigation model based on forward planning of trajectories in a network of head direction cells, persistent spiking cells, grid cells, and place cells. In our original work the animat incrementally creates a place cell map by random exploration of a novel environment. After the exploration phase, the animat decides on its next movement direction towards a goal by probing linear look-ahead trajectories in several candidate directions while stationary and picking the one activating place cells representing the goal location. In this work we present several improvements over our previous model. We improve the range of linear look-ahead probes significantly by imposing a hierarchical structure on the place cell map consistent with the experimental findings of differences in the firing field size and spacing of grid cells recorded at different positions along the dorsal to ventral axis of entorhinal cortex. The new model represents the environment at different scales by populations of simulated hippocampal place cells with different firing field sizes. Among other advantages this model allows simultaneous constant duration linear look-ahead probes at different scales while significantly extending each probe range. The extension of the linear look-ahead probe range while keeping its duration constant also limits the degrading effects of noise accumulation in the network. We show the extended model’s performance using an animat in a large open field environment.     

Sea turtles, lobsters, and oceanic magnetic maps

Numerous marine animals can sense the Earth's magnetic field and use it as a cue in orientation and navigation. Two distinct types of information can potentially be extracted from the Earth's field. Directional or compass information enables animals to maintain a consistent heading in a particular direction such as north or south. In contrast, positional or map information can be used by animals to assess geographic location and, in some cases, to navigate to specific target areas. Marine animals exploit magnetic positional information in at least two different ways. For hatchling loggerhead sea turtles, regional magnetic fields function as open-sea navigational markers, eliciting changes in swimming direction at crucial points in the migratory route. Older sea turtles, as well as spiny lobsters, use magnetic information in a more complex way, exploiting it as a component of a classical navigational map, which permits an assessment of position relative to specific geographic destinations. These “magnetic maps” have not yet been fully characterized. They may be organized in several fundamentally different ways, some of which bear little resemblance to human maps, and they may also be used in conjunction with unconventional navigational strategies. Unraveling the nature of magnetic maps and exploring how they are used represents one of the most exciting frontiers of behavioral and sensory biology.     

Solving navigational uncertainty using grid cells on robots

To successfully navigate their habitats, many mammals use a combination of two mechanisms, path integration and calibration using landmarks, which together enable them to estimate their location and orientation, or pose. In large natural environments, both these mechanisms are characterized by uncertainty: the path integration process is subject to the accumulation of error, while landmark calibration is limited by perceptual ambiguity. It remains unclear how animals form coherent spatial representations in the presence of such uncertainty. Navigation research using robots has determined that uncertainty can be effectively addressed by maintaining multiple probabilistic estimates of a robot's pose. Here we show how conjunctive grid cells in dorsocaudal medial entorhinal cortex (dMEC) may maintain multiple estimates of pose using a brain-based robot navigation system known as RatSLAM. Based both on rodent spatially-responsive cells and functional engineering principles, the cells at the core of the RatSLAM computational model have similar characteristics to rodent grid cells, which we demonstrate by replicating the seminal Moser experiments. We apply the RatSLAM model to a new experimental paradigm designed to examine the responses of a robot or animal in the presence of perceptual ambiguity. Our computational approach enables us to observe short-term population coding of multiple location hypotheses, a phenomenon which would not be easily observable in rodent recordings. We present behavioral and neural evidence demonstrating that the conjunctive grid cells maintain and propagate multiple estimates of pose, enabling the correct pose estimate to be resolved over time even without uniquely identifying cues. While recent research has focused on the grid-like firing characteristics, accuracy and representational capacity of grid cells, our results identify a possible critical and unique role for conjunctive grid cells in filtering sensory uncertainty. We anticipate our study to be a starting point for animal experiments that test navigation in perceptually ambiguous environments.     

Limits of Feedback Control in Bacterial Chemotaxis

Inputs to signaling pathways can have complex statistics that depend on the environment and on the behavioral response to previous stimuli. Such behavioral feedback is particularly important in navigation. Successful navigation relies on proper coupling between sensors, which gather information during motion, and actuators, which control behavior. Because reorientation conditions future inputs, behavioral feedback can place sensors and actuators in an operational regime different from the resting state. How then can organisms maintain proper information transfer through the pathway while navigating diverse environments? In bacterial chemotaxis, robust performance is often attributed to the zero integral feedback control of the sensor, which guarantees that activity returns to resting state when the input remains constant. While this property provides sensitivity over a wide range of signal intensities, it remains unclear how other parameters such as adaptation rate and adapted activity affect chemotactic performance, especially when considering that the swimming behavior of the cell determines the input signal. We examine this issue using analytical models and simulations that incorporate recent experimental evidences about behavioral feedback and flagellar motor adaptation. By focusing on how sensory information carried by the response regulator is best utilized by the motor, we identify an operational regime that maximizes drift velocity along chemical concentration gradients for a wide range of environments and sensor adaptation rates. This optimal regime is outside the dynamic range of the motor response, but maximizes the contrast between run duration up and down gradients. In steep gradients, the feedback from chemotactic drift can push the system through a bifurcation. This creates a non-chemotactic state that traps cells unless the motor is allowed to adapt. Although motor adaptation helps, we find that as the strength of the feedback increases individual phenotypes cannot maintain the optimal operational regime in all environments, suggesting that diversity could be beneficial.     

Manipulating carabid beetle abundance alters prey removal rates in corn fields

Generalist natural enemies such as carabid beetles have the potential to maintain a variety of pests below outbreak levels in annual crops. To assess the relationship between carabid beetle abundance and field rates of prey removal, we created plots surrounded by different boundaries that selectively affected dispersal of edaphic arthropods, primarily carabids. Three treatments were established: (1) naturally occurring communities, (2) augmented communities using ingress boundaries, and (3) reduced communities using egress boundaries. Selective boundaries altered carabid communities with minimal habitat alteration and without use of insecticides. Three times during the growing season, a fixed number of onion fly pupae were placed in plots to evaluate the impact of carabid abundance on predation rates. A combination of vertebrate and invertebrate exclosures allowed us to evaluate prey removal by invertebrates alone. In comparison to the no boundary treatment, carabids increased 54.2% and decreased 83.1% in plots surrounded by ingress and egress boundaries respectively. Predation rates were positively correlated with carabid abundance (r² = 0.70, p < 0.0001). Significantly more pupae were removed from exclosures allowing access to invertebrates alone than from total exclosures, suggesting that invertebrates represented an important group of predators. Laboratory trials tested the feeding potential of the four most abundant carabid species and showed that they readily consumed onion fly pupae, supporting our hypothesis that carabids were the main predators in field tests. This study corroborates and extends previous observations of the importance of carabid beetles as generalist predators of insect pests in agricultural fields.     

解码大脑的空间方位认知

在过去的几十年间,与大脑空间方位认知功能相关的位置细胞、网格细胞、头朝向细胞和边界细胞陆续被发现,它们共同构成了大脑内部的导航定位系统。O'Keefe教授和Moser夫妇这三位科学家也正是由于发现了位置细胞和网格细胞,而共同获得了2014年的诺贝尔生理学或医学奖。     

Locating and navigation mechanism based on place-cell and grid-cell models

Extensive experiments on rats have shown that environmental cues play an important role in goal locating and navigation. Major studies about locating and navigation are carried out based only on place cells. Nevertheless, it is known that navigation may also rely on grid cells. Therefore, we model locating and navigation based on both, thus developing a novel grid-cell model, from which firing fields of grid cells can be obtained. We found a continuous-time dynamic system to describe learning and direction selection. In our simulation experiment, according to the results from physiology experiments, we successfully rebuild place fields of place cells and firing fields of grid cells. We analyzed the factors affecting the locating accuracy. Results show that the learning rate, firing threshold and cell number can influence the outcomes from various tasks. We used our system model to perform a goal navigation task and showed that paths that are changed for every run in one experiment converged to a stable one after several runs.     

Place cells, neocortex and spatial navigation: a short review

Hippocampal place cells are characterized by location-specific firing, that is each cell fires in a restricted region of the environment explored by the rat. In this review, we briefly examine the sensory information used by place cells to anchor their firing fields in space and show that, among the various sensory cues that can influence place cell activity, visual and motion-related cues are the most relevant. We then explore the contribution of several cortical areas to the generation of the place cell signal with an emphasis on the role of the visual cortex and parietal cortex. Finally, we address the functional significance of place cell activity and demonstrate the existence of a clear relationship between place cell positional activity and spatial navigation performance. We conclude that place cells, together with head direction cells, provide information useful for spatially guided movements, and thus provide a unique model of how spatial information is encoded in the brain.     

Genetic changes across language boundaries in Europe

By means of three different methods we investigated whether 59 allele frequencies and ten cranial variables show increased change at 29 language-family boundaries in Europe. The quadrat-variance method compares variances of map quadrats crossed by language-family boundaries to variances of quadrats that are not crossed. The rate-of-change method examines the directional derivative of surfaces of the variables perpendicular to a language-family boundary and compares these derivatives to the same quantities obtained by randomly placing the language boundaries on the map of Europe. The difference method tests whether these variables differ more across language-family boundaries than across randomly placed boundaries. These special data-analytic techniques had to be developed to avoid the problem of spatial autocorrelation of both language and biological data. All three methods indicate increased genetic change at language-family boundaries. Clearer and more pronounced results are obtained by the first two methods than by the difference method. Thirteen language-family boundaries show significant gene frequency change by at least one of the methods. Changes are more marked in gene frequencies than in cranial variables. Different allele frequencies mark the increased change at different language boundaries. A model, based on the known history of each language-family boundary, was constructed to predict whether given boundaries should exhibit increased genetic change. The model is in good agreement with the observed results.     

Models of place and grid cell firing and theta rhythmicity

Neuronal firing in the hippocampal formation (HF) of freely moving rodents shows striking examples of spatialorganization in the form of place, directional, boundary vector and grid cells. The firing of place and grid cells shows an intriguing form of temporal organization known as 'theta phase precession'. We review the mechanisms underlying theta phase precession of place cell firing, ranging from membrane potential oscillations to recurrent connectivity, and the relevant intra-cellular and extra-cellular data. We then consider the use of these models to explain the spatial structure of grid cell firing, and review the relevant intra-cellular and extra-cellular data. Finally, we consider the likely interaction between place cells, grid cells and boundary vector cells in estimating self-location as a compromise between path-integration and environmental information.     

Dynamic 3D Scene Depth Reconstruction via Optical Flow Field Rectification

In this paper, we propose a depth propagation scheme based on optical flow field rectification towards more accurate depth reconstruction. In depth reconstruction, the occlusions and low-textural regions easily result in optical flow field errors, which lead ambiguous depth value or holes without depth in the obtained depth map. In this work, a scheme is proposed to improve the precision of depth propagation and the quality of depth reconstruction for dynamic scene. The proposed scheme first adaptively detects the occlusive or low-textural regions, and the obtained vectors in optical flow field are rectified properly. Subsequently, we process the occluded and ambiguous vectors for more precise depth propagation. We further leverage the boundary enhancement filters as a post-processing to sharpen the object boundaries in obtained depth maps for better quality. Quantitative evaluations show that the proposed scheme can reconstruct depth map with higher accuracy and better quality compared with the state-of-the-art methods.     

Factors affecting plant species richness in field boundaries in the Mediterranean region

Field boundaries are expected to support the maintenance of biodiversity in agroecosystems, since they provide the habitat for a range of plant species. However, plant diversity in field boundaries has decreased substantially in recent decades. This pattern is generally linked with the intensification of agricultural land use at field and landscape level. Therefore, we aimed to test the effect of farming management (field and boundary management), boundary structure (width and habitat assemblage considering the Mediterranean grassland element), and landscape heterogeneity on plant species richness of field boundaries. Plants were recorded along 30 field boundaries next to organic fields and 30 next to conventional fields located in 15 agrarian localities of NE Iberian Peninsula along a gradient of landscape complexity. A total of 517 plant species were identified in the 60 field boundaries. We recorded 162 species (31%) catalogued as rare, very rare or extremely rare in the flora of the Catalan Countries. Our results showed the importance of landscape heterogeneity, field management and habitat assemblage, since they were found to be the most influential variables for plant species richness; whereas boundary width and boundary management were seen to contribute less to explaining plant diversity. Accordingly, agri-environmental schemes should be designed to promote organic farming and maintain the structure of the landscape mosaic in order to benefit plant diversity in field boundaries in the Mediterranean region.     

Where on earth can animals use a geomagnetic bi‐coordinate map for navigation?

Many animal taxa have been shown to possess the ability of true navigation. In this study we investigated the possibilities for geomagnetic bi‐coordinate map navigation in different regions of the earth by analysing angular differences between isolines of geomagnetic total intensity and inclination. In ‘no‐grid’ zones where isolines were running almost parallel, efficient geomagnetic bi‐coordinate navigation would probably not be feasible. These zones formed four distinct areas with a north‐south extension in the northern hemisphere, whereas the pattern in the southern hemisphere was more diffuse. On each side of these zones there was often a mirror effect where identical combinations of the geomagnetic parameters appeared. This may potentially cause problems for species migrating long distances east‐west across longitudes, since they may pass areas with identical geomagnetic coordinates. Migration routes assumed for four populations of migratory passerine birds were used to illustrate the possibilities of geomagnetic bi‐coordinate map navigation along different routes. We conclude that it is unlikely that animal navigation is universally based on a geomagnetic bi‐coordinate map mechanism only, and we predict that the relative importance of geomagnetic coordinate information differs between animals, areas and routes, depending on the different conditions for bi‐coordinate geomagnetic navigation in different regions of the earth.     

Navigating sensory conflict in dynamic environments using adaptive state estimation

Most conventional robots rely on controlling the location of the center of pressure to maintain balance, relying mainly on foot pressure sensors for information. By contrast, humans rely on sensory data from multiple sources, including proprioceptive, visual, and vestibular sources. Several models have been developed to explain how humans reconcile information from disparate sources to form a stable sense of balance. These models may be useful for developing robots that are able to maintain dynamic balance more readily using multiple sensory sources. Since these information sources may conflict, reliance by the nervous system on any one channel can lead to ambiguity in the system state. In humans, experiments that create conflicts between different sensory channels by moving the visual field or the support surface indicate that sensory information is adaptively reweighted. Unreliable information is rapidly down-weighted, then gradually up-weighted when it becomes valid again. Human balance can also be studied by building robots that model features of human bodies and testing them under similar experimental conditions. We implement a sensory reweighting model based on an adaptive Kalman filter in a bipedal robot, and subject it to sensory tests similar to those used on human subjects. Unlike other implementations of sensory reweighting in robots, our implementation includes vision, by using optic flow to calculate forward rotation using a camera (visual modality), as well as a three-axis gyro to represent the vestibular system (non-visual modality), and foot pressure sensors (proprioceptive modality). Our model estimates measurement noise in real time, which is then used to recompute the Kalman gain on each iteration, improving the ability of the robot to dynamically balance. We observe that we can duplicate many important features of postural sway in humans, including automatic sensory reweighting, effects, constant phase with respect to amplitude, and a temporal asymmetry in the reweighting gains.     

Boundary coding in the rat subiculum

The spatial mapping function of the hippocampal formation is likely derived from two sets of information: one based on the external environment and the other based on self-motion. Here, we further characterize ‘boundary vector cells’ (BVCs) in the rat subiculum, which code space relative to one type of cue in the external environment: boundaries. We find that the majority of cells with fields near the perimeter of a walled environment exhibit an additional firing field when an upright barrier is inserted into the walled environment in a manner predicted by the BVC model. We use this property of field repetition as a heuristic measure to define BVCs, and characterize their spatial and temporal properties. In further tests, we find that subicular BVCs typically treat drop edges similarly to walls, including exhibiting field repetition when additional drop-type boundaries are added to the testing environment. In other words, BVCs treat both kinds of edge as environmental boundaries, despite their dissimilar sensory properties. Finally, we also report the existence of ‘boundary-off cells’, a new class of boundary-coding cells. These cells fire everywhere except where a given BVC might fire.