Flexible cue anchoring strategies enable stable head direction coding in both sighted and blind animals

Vision plays a crucial role in instructing the brain's spatial navigation systems. However, little is known about how vision loss affects the neuronal encoding of spatial information. Here, recording from head direction (HD) cells in the anterior dorsal nucleus of the thalamus in mice, we find stable and robust HD tuning in blind animals. In contrast, placing sighted animals in darkness significantly impairs HD cell tuning. We find that blind mice use olfactory cues to maintain stable HD tuning and that prior visual experience leads to refined HD cell tuning in blind adult mice compared to congenitally blind animals. Finally, in the absence of both visual and olfactory cues, the HD attractor network remains intact but the preferred firing direction of HD cells continuously drifts over time. We thus demonstrate remarkable flexibility in how the brain uses diverse sensory information to generate a stable directional representation of space.

A Positioning Method Based on Place Cells and Head-Direction Cells for Inertial/Visual Brain-Inspired Navigation System

Mammals rely on vision and self-motion information in nature to distinguish directions and navigate accurately and stably. Inspired by the mammalian brain neurons to represent the spatial environment, the brain-inspired positioning method based on multi-sensors’ input is proposed to solve the problem of accurate navigation in the absence of satellite signals. In the research related to the application of brain-inspired engineering, it is not common to fuse various sensor information to improve positioning accuracy and decode navigation parameters from the encoded information of the brain-inspired model. Therefore, this paper establishes the head-direction cell model and the place cell model with application potential based on continuous attractor neural networks (CANNs) to encode visual and inertial input information, and then decodes the direction and position according to the population neuron firing response. The experimental results confirm that the brain-inspired navigation model integrates a variety of information, outputs more accurate and stable navigation parameters, and generates motion paths. The proposed model promotes the effective development of brain-inspired navigation research.

A structured scaffold underlies activity in the hippocampus

Place cells are believed to organize memory across space and time, inspiring the idea of the cognitive map. Yet unlike the structured activity in the associated grid and head-direction cells, they remain an enigma: their responses have been difficult to predict and are complex enough to be statistically well-described by a random process. Here we report one step toward the ultimate goal of understanding place cells well enough to predict their fields. Within a theoretical framework in which place fields are derived as a conjunction of external cues with internal grid cell inputs, we predict that even apparently random place cell responses should reflect the structure of their grid inputs and that this structure can be unmasked if probed in sufficiently large neural populations and large environments. To test the theory, we design experiments in long, locally featureless spaces to demonstrate that structured scaffolds undergird place cell responses. Our findings, together with other theoretical and experimental results, suggest that place cells build memories of external inputs by attaching them to a largely prespecified grid scaffold.

Global and Local Head Direction Coding in the Human Brain

Orientation-specific head direction (HD) cells increase their firing rate to indicate one’s facing direction in the environment. Rodent studies suggest HD cells in distinct areas of thalamus and retrosplenial cortex (RSC) code either for global (relative to the wider environment) or local (e.g., room-specific) reference frames. To investigate whether similar neuroanatomical dissociations exist in humans, we reanalysed functional magnetic resonance imaging data in which participants learned the orientation of unique images in separate local environments relative to distinct global landmarks (Shine, Valdés-Herrera, Hegarty, & Wolbers, 2016). The environment layout meant that we could establish two separate multivariate analysis models in which the HD on individual trials was coded relative either to global (North, South, East, West) or local (Front, Back, Right, Left) reference frames. Examining the data first in key regions of interest (ROI) for HD coding, we replicated our previous results and found that global HD was decodable in the thalamus and precuneus; the RSC, however, was sensitive only to local HD. Extending recent findings in both humans and rodents, V1 was sensitive to both HD reference frames. Additional small volume-corrected searchlight analyses supported the ROI results and indicated that the anatomical locus of the thalamic global HD coding was located in the medial thalamus, bordering the anterior thalamus, a region critical for global HD coding in rodents. Our findings elucidate further the putative neural basis of HD coding in humans, and suggest that distinct brain regions code for different frames of reference in HD.Significance statementHead direction (HD) cells provide a neural signal as to one’s orientation in the environment. HD can be coded relative to global or local (e.g., room-specific) reference frames, with studies suggesting that distinct areas of thalamus and retrosplenial cortex (RSC) code for this information. We reanalysed fMRI data where human participants associated images with global HDs before undergoing scanning. The design enabled us to examine both global and local HD coding. Supporting previous findings, global HD was decodable in thalamus, however the RSC coded only for local HD. We found evidence also for both reference frames in V1. These findings elucidate the putative neural basis of HD coding in humans, with distinct brain regions coding for different HD reference frames.

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 New Paradigm for the Study of Cognitive Flexibility in Children and Adolescents: The “Virtual House Locomotor Maze” (VHLM)

Classical neuropsychological assessments are designed to explore cognitive brain functions using paper-and-pencil or digital tests. The purpose of this study was to design and to test a new protocol named the “Virtual House Locomotor Maze” (VHLM) for studying inhibitory control as well as mental flexibility using a visuo-spatial locomotor memory test. The VHLM is a simple maze including six houses using the technology of the Virtual Carpet Paradigm™. Ten typical development children (TD) were enrolled in this study. The participants were instructed to reach a target house as quickly as possible and to bear in mind the experimental instructions. We examined their planning and replanning abilities to take the shortest path to reach a target house. In order to study the cognitive processes during navigation, we implemented a spatio-temporal index based on the measure of kinematics behaviors (i.e., trajectories, tangential velocity and head direction). Replanning was tested by first repeating a path chosen by the subject to reach a given house. After learning this path, it was blocked imposing that the subject inhibited the learned trajectory and designed a new trajectory to reach the same house. We measured the latency of the departure after the presentation of each house and the initial direction of the trajectory. The results suggest that several strategies are used by the subjects for replanning and our measures could be used as an index of impulsivity.

Functional network topography of the medial entorhinal cortex

SummaryThe medial entorhinal cortex (MEC) creates a map of local space, based on the firing patterns of grid, head direction (HD), border, and object-vector (OV) cells. How these cell types are organized anatomically is debated. In-depth analysis of this question requires collection of precise anatomical and activity data across large populations of neurons during unrestrained behavior, which neither electrophysiological nor previous imaging methods fully afford. Here we examined the topographic arrangement of spatially modulated neurons in MEC and adjacent parasubiculum using miniaturized, portable two-photon microscopes, which allow mice to roam freely in open fields. Grid cells exhibited low levels of co-occurrence with OV cells and clustered anatomically, while border, HD and OV cells tended to intermingle. These data suggest that grid-cell networks might be largely distinct from those of border, HD and OV cells and that grid cells exhibit strong coupling among themselves but weaker links to other cell types.Highlights- Grid and object vector cells show low levels of regional co-occurrence- Grid cells exhibit the strongest tendency to cluster among all spatial cell types- Grid cells stay separate from border, head direction and object vector cells- The territories of grid, head direction and border cells remain stable over weeks

Population dynamics of the thalamic head direction system during drift and reorientation

The head direction (HD) system is classically modeled as a ring attractor network1,2 which ensures a stable representation of the animal’s head direction. This unidimensional description popularized the view of the HD system as the brain’s internal compass3,4. However, unlike a globally consistent magnetic compass, the orientation of the HD system is dynamic, depends on local cues and exhibits remapping across familiar environments5. Such a system requires mechanisms to remember and align to familiar landmarks, which may not be well described within the classic 1-dimensional framework. To search for these mechanisms, we performed large population recordings of mouse thalamic HD cells using calcium imaging, during controlled manipulations of a visual landmark in a familiar environment. First, we find that realignment of the system was associated with a continuous rotation of the HD network representation. The speed and angular distance of this rotation was predicted by a 2nd dimension to the ring attractor which we refer to as network gain, i.e. the instantaneous population firing rate. Moreover, the 360-degree azimuthal profile of network gain, during darkness, maintained a ‘memory trace’ of a previously displayed visual landmark. In a 2nd experiment, brief presentations of a rotated landmark revealed an attraction of the network back to its initial orientation, suggesting a time-dependent mechanism underlying the formation of these network gain memory traces. Finally, in a 3rd experiment, continuous rotation of a visual landmark induced a similar rotation of the HD representation which persisted following removal of the landmark, demonstrating that HD network orientation is subject to experience-dependent recalibration. Together, these results provide new mechanistic insights into how the neural compass flexibly adapts to environmental cues to maintain a reliable representation of the head direction.