No gender differences in egocentric and allocentric environmental transformation after compensating for male advantage by manipulating familiarity

The present study has two-fold aims: to investigate whether gender differences persist even when more time is given to acquire spatial information; to assess the gender effect when the retrieval phase requires recalling the pathway from the same or a different reference perspective (egocentric or allocentric). Specifically, we analyse the performance of men and women while learning a path from a map or by observing an experimenter in a real environment. We then asked them to reproduce the learned path using the same reference system (map learning vs. map retrieval or real environment learning vs. real environment retrieval) or using a different reference system (map learning vs. real environment retrieval or vice versa). The results showed that gender differences were not present in the retrieval phase when women have the necessary time to acquire spatial information. Moreover, using the egocentric coordinates (both in the learning and retrieval phase) proved easier than the other conditions, whereas learning through allocentric coordinates and then retrieving the environmental information using egocentric coordinates proved to be the most difficult. Results showed that by manipulating familiarity, gender differences disappear, or are attenuated in all conditions

Solving the detour problem in navigation: a model of prefrontal and hippocampal interactions.

Adapting behavior to accommodate changes in the environment is an important function of the nervous system. A universal problem for motile animals is the discovery that a learned route is blocked and a detour is required. Given the substantial neuroscience research on spatial navigation and decision-making it is surprising that so little is known about how the brain solves the detour problem. Here we review the limited number of relevant functional neuroimaging, single unit recording and lesion studies. We find that while the prefrontal cortex (PFC) consistently responds to detours, the hippocampus does not. Recent evidence suggests the hippocampus tracks information about the future path distance to the goal. Based on this evidence we postulate a conceptual model in which: Lateral PFC provides a prediction error signal about the change in the path, frontopolar and superior PFC support the re-formulation of the route plan as a novel subgoal and the hippocampus simulates the new path. More data will be required to validate this model and understand (1) how the system processes the different options; and (2) deals with situations where a new path becomes available (i.e., shortcuts)

Vector trace cells in the subiculum of the hippocampal formation

Successfully navigating in physical or semantic space requires a neural representation of allocentric (map-based) vectors to boundaries, objects and goals. Cognitive processes such as path-planning and imagination entail the recall of vector representations, but evidence of neuron-level memory for allocentric vectors has been lacking. Here, we describe a novel neuron type, vector trace cell (VTC), whose firing generates a new vector field when a cue is encountered and a ‘trace’ version of that field for hours after cue removal. VTCs are concentrated in subiculum, distal to CA1. Compared to non-trace cells, VTCs fire at further distances from cues and exhibit earlier-going shifts in preferred theta phase in response to newly introduced cues, which demonstrates a theta-linked neural substrate for memory encoding. VTCs suggest a vector-based model of computing spatial relationships between an agent and multiple spatial objects, or between different objects, freed from the constraints of direct perception of those objects

Vector trace cells in the subiculum of the hippocampal formation

Successfully navigating in physical or semantic space requires a neural representation of allocentric (map-based) vectors to boundaries, objects and goals. Cognitive processes such as path-planning and imagination entail the recall of vector representations, but evidence of neuron-level memory for allocentric vectors has been lacking. Here, we describe a novel neuron type, vector trace cell (VTC), whose firing generates a new vector field when a cue is encountered and a ‘trace’ version of that field for hours after cue removal. VTCs are concentrated in subiculum, distal to CA1. Compared to non-trace cells, VTCs fire at further distances from cues and exhibit earlier-going shifts in preferred theta phase in response to newly introduced cues, which demonstrates a theta-linked neural substrate for memory encoding. VTCs suggest a vector-based model of computing spatial relationships between an agent and multiple spatial objects, or between different objects, freed from the constraints of direct perception of those objects

A novel approach to human motion estimation with applications in human-robot safety

Assistive robotics has brought convenience especially to disabled and handicapped including the blinds. Mobile housekeeping robots such as floor cleaners are capable of local obstacle avoidance. However there is always a risk of hitting moving obstacles or blind human when they walk through the environment. In this article, a new decision mechanism is introduced for modelling path planning strategies adopted by blind travellers including wall-following, and taking shortcuts in indoor spaces e.g.; home, and office. A statistical path prediction method is used together with Fuzzy Cognitive Map FCM for prediction of entire paths from partial trajectories. Supplying knowledge from the presented model of spatial cognition and path planning to mobile robots can enhance their motion algorithms for better obstacle avoidance as well as safer service to users with visual impairment and blindness

Study of the applicability of cognitive path algorithms for 3D indoor navigation

C

Neural systems supporting navigation

Highlights: • Recent neuroimaging and electrophysiology studies have begun to shed light on the neural dynamics of navigation systems. • Computational models have advanced theories of how entorhinal grid cells and hippocampal place cells might serve navigation. • Hippocampus and entorhinal cortex provide complementary representations of routes and vectors for navigation. Much is known about how neural systems determine current spatial position and orientation in the environment. By contrast little is understood about how the brain represents future goal locations or computes the distance and direction to such goals. Recent electrophysiology, computational modelling and neuroimaging research have shed new light on how the spatial relationship to a goal may be determined and represented during navigation. This research suggests that the hippocampus may code the path to the goal while the entorhinal cortex represents the vector to the goal. It also reveals that the engagement of the hippocampus and entorhinal cortex varies across the different operational stages of navigation, such as during travel, route planning, and decision-making at waypoints