Easy rider: monkeys learn to drive a wheelchair to navigate through a complex maze

Landmark use by ghost crab (Ocypode quadrata) during wayfinding in a complex maze

Species of crab have been shown to spatially track and navigate to consequential locations through different processes, such as path integration and landmark orienting. Few investigations examine their ability to wayfind in complex environments, like mazes, with multiple intersections and how they may utilize specific features to benefit this process. Spatial learning potentially would lend a fitness advantage to animals living in complicated habitats, and ghost crab (Ocypode quadrata) is a semiterrestrial species that typically occupies extensive beach environments, which present many navigational challenges. Despite their potential, there are currently no studies that investigate forms of spatial cognition in these animals. To better diversify our knowledge of this trait, the current research exposed ghost crab to a maze with seven intersections. Animals were given multiple trials to learn the location of a reward destination to a specific criterion proficiency. In one condition several landmarks were distributed throughout the maze, and in another the environment was completely empty. Results showed that ghost crab in the landmark present group were able to learn the maze faster, they required significantly fewer trials to reach the learning criterion than those in the landmark absent group. However, only approximately half of the total sample met the learning criterion, indicating the maze was rather difficult. These findings are interpreted through theories of route learning that suggest animals may navigate by establishing landmark-turn associations. Such processes have implications for the cognitive ability of ghost crab, and spatial learning in this species may support the notion of convergent evolution for this trait.

The road towards understanding embodied decisions

Most current decision-making research focuses on classical economic scenarios, where choice offers are prespecified and where action dynamics play no role in the decision. However, our brains evolved to deal with different choice situations: "embodied decisions". As examples of embodied decisions, consider a lion that has to decide which gazelle to chase in the savannah or a person who has to select the next stone to jump on when crossing a river. Embodied decision settings raise novel questions, such as how people select from time-varying choice options and how they track the most relevant choice attributes; but they have long remained challenging to study empirically. Here, we summarize recent progress in the study of embodied decisions in sports analytics and experimental psychology. Furthermore, we introduce a formal methodology to identify the relevant dimensions of embodied choices (present and future affordances) and to map them into the attributes of classical economic decisions (probabilities and utilities), hence aligning them. Studying embodied decisions will greatly expand our understanding of what decision-making is.

Navigation strategy in macaque monkeys: An exploratory experiment in virtual reality

BACKGROUND

Spatial memory and navigation have been widely studied using animal models, most of them were performed with rodents and only few of them with non-human primates. Also, most of these studies were achieved in simple and small-scale mazes.

NEW METHOD

In order to test navigation strategy in macaque monkeys, we used a double-cross virtual maze in which they could freely move using a joystick and a procedure adapted from previous studies with rodents. The monkeys had first to learn several routes from a specific starting point to reach separate positions, each one containing distinct symbols, and then to associate each route with these symbols. After this phase, the monkeys had to reach these targets from a second starting point positioned at the other end of the maze, requiring the use an allocentric strategy. In order to evaluate monkey's strategy, we analyzed monkey's first choice as a function of the symbol presented.

RESULTS

The monkeys were able to learn routes and to associate routes with symbols but were not able to use an allocentric strategy. They also did not use the procedural strategy and seemed disoriented or adopted a stereotypical behavior.

COMPARISON WITH EXISTING METHOD(S)

Contrary to the few studies using small-scale environments, the monkeys seemed unable to solve the allocentric task. The studies using virtual mazes seemed not to specifically analyze monkey's navigation strategy.

CONCLUSIONS

Supplementary experiments will be necessary to explain the origin of the monkey's inability to use an allocentric strategy. Modified learning conditions could also incite the monkeys to develop an allocentric representation.

Brain-Machine Interfaces: From Basic Science to Neuroprostheses and Neurorehabilitation

Brain-machine interfaces (BMIs) combine methods, approaches, and concepts derived from neurophysiology, computer science, and engineering in an effort to establish real-time bidirectional links between living brains and artificial actuators. Although theoretical propositions and some proof of concept experiments on directly linking the brains with machines date back to the early 1960s, BMI research only took off in earnest at the end of the 1990s, when this approach became intimately linked to new neurophysiological methods for sampling large-scale brain activity. The classic goals of BMIs are 1) to unveil and utilize principles of operation and plastic properties of the distributed and dynamic circuits of the brain and 2) to create new therapies to restore mobility and sensations to severely disabled patients. Over the past decade, a wide range of BMI applications have emerged, which considerably expanded these original goals. BMI studies have shown neural control over the movements of robotic and virtual actuators that enact both upper and lower limb functions. Furthermore, BMIs have also incorporated ways to deliver sensory feedback, generated from external actuators, back to the brain. BMI research has been at the forefront of many neurophysiological discoveries, including the demonstration that, through continuous use, artificial tools can be assimilated by the primate brain's body schema. Work on BMIs has also led to the introduction of novel neurorehabilitation strategies. As a result of these efforts, long-term continuous BMI use has been recently implicated with the induction of partial neurological recovery in spinal cord injury patients.

Intelligence-Augmented Rat Cyborgs in Maze Solving

Cyborg intelligence is an emerging kind of intelligence paradigm. It aims to deeply integrate machine intelligence with biological intelligence by connecting machines and living beings via neural interfaces, enhancing strength by combining the biological cognition capability with the machine computational capability. Cyborg intelligence is considered to be a new way to augment living beings with machine intelligence. In this paper, we build rat cyborgs to demonstrate how they can expedite the maze escape task with integration of machine intelligence. We compare the performance of maze solving by computer, by individual rats, and by computer-aided rats (i.e. rat cyborgs). They were asked to find their way from a constant entrance to a constant exit in fourteen diverse mazes. Performance of maze solving was measured by steps, coverage rates, and time spent. The experimental results with six rats and their intelligence-augmented rat cyborgs show that rat cyborgs have the best performance in escaping from mazes. These results provide a proof-of-principle demonstration for cyborg intelligence. In addition, our novel cyborg intelligent system (rat cyborg) has great potential in various applications, such as search and rescue in complex terrains.

Precocious Alterations of Brain Oscillatory Activity in Alzheimer's Disease: A Window of Opportunity for Early Diagnosis and Treatment

Alzheimer's disease (AD) is the most common form of neurodegenerative dementia accounting for 50-80% of all age-related dementia. This pathology is characterized by the progressive and irreversible alteration of cognitive functions, such as memory, leading inexorably to the loss of autonomy for patients with AD. The pathology is linked with aging and occurs most commonly around 65 years old. Its prevalence (5% over 65 years of age and 20% after 80 years) constitutes an economic and social burden for AD patients and their family. At the present, there is still no cure for AD, actual treatments being moderately effective only in early stages of the pathology. A lot of efforts have been deployed with the aim of defining new AD biomarkers. Successful early detection of mild cognitive impairment (MCI) linked to AD requires the identification of biomarkers capable of distinguishing individuals with early stages of AD from other pathologies impacting cognition such as depression. In this article, we will review recent evidence suggesting that electroencephalographic (EEG) recordings, coupled with behavioral assessments, could be a useful approach and easily implementable for a precocious detection of AD.