Movements, embodiment and the emergence of decisions. Insights from insect navigation

The self-in-the-world map emerged in the primate brain as a basis for Homo sapiens abilities

The brain in the genus Homo expanded rapidly during evolution, accelerated by a reciprocated interaction between neural, cognitive, and ecological niches (triadic niche construction, or TNC). This biologically costly expansion incubated latent cognitive capabilities that, with a quick and inexpensive rewiring of brain areas in a second phase of TNC, provided the basis for Homo sapiens specific abilities. The neural demands for perception of the human body in interaction with tools and the environment required highly integrated sensorimotor domains, inducing the parietal lobe expansion seen in humans. These newly expanded brain areas allowed connecting the sensations felt in the body to the actions in the world through the cognitive function of "projection". In this opinion article, we suggest that as a relationship of equivalence between body parts, tools and their external effects was established, mental mechanisms of self-objectification might have emerged as described previously, grounding notions of spatial organization, idealized objects, and their transformations, as well as socio-emotional states in the sensing agent through a self-in-the-world map. Therefore, human intelligence and its features such as symbolic thought, language, mentalizing, and complex technical and social behaviors could have stemmed from the explicit awareness of the causal relationship between the self and intentional modifications to the environment.

Scanning behaviour in ants: an interplay between random-rate processes and oscillators

At the start of a journey home or to a foraging site, ants often stop, interrupting their forward movement, turn on the spot a number of times, and fixate in different directions. These scanning bouts are thought to provide visual information for choosing a path to travel. The temporal organization of such scanning bouts has implications about the neural organisation of navigational behaviour. We examined (1) the temporal distribution of the start of such scanning bouts and (2) the dynamics of saccadic body turns and fixations that compose a scanning bout in Australian desert ants, Melophorus bagoti, as they came out of a walled channel onto open field at the start of their homeward journey. Ants were caught when they neared their nest and displaced to different locations to start their journey home again. The observed parameters were mostly similar across familiar and unfamiliar locations. The turning angles of saccadic body turning to the right or left showed some stereotypy, with a peak just under 45°. The direction of such saccades appears to be determined by a slow oscillatory process as described in other insect species. In timing, however, both the distribution of inter-scanning-bout intervals and individual fixation durations showed exponential characteristics, the signature for a random-rate or Poisson process. Neurobiologically, therefore, there must be some process that switches behaviour (starting a scanning bout or ending a fixation) with equal probability at every moment in time. We discuss how chance events in the ant brain that occasionally reach a threshold for triggering such behaviours can generate the results.

An intrinsic oscillator underlies visual navigation in ants

Many insects display lateral oscillations while moving, but how these oscillations are produced and participate in visual navigation remains unclear. Here, we show that visually navigating ants continuously display regular lateral oscillations coupled with variations of forward speed that strongly optimize the distance covered while simultaneously enabling them to scan left and right directions. This pattern of movement is produced endogenously and conserved across navigational contexts in two phylogenetically distant ant species. Moreover, the oscillations' amplitude can be modulated by both innate or learnt visual cues to adjust the exploration/exploitation balance to the current need. This lower-level motor pattern thus drastically reduces the degree of freedom needed for higher-level strategies to control behavior. The observed dynamical signature readily emerges from a simple neural circuit model of the insect's conserved pre-motor area known as the lateral accessory lobe, offering a surprisingly simple but effective neural control and endorsing oscillation as a core, ancestral way of moving in insects.

From representations to servomechanisms to oscillators: my journey in the study of cognition

The study of comparative cognition bloomed in the 1970s and 1980s with a focus on representations in the heads of animals that undergird what animals can achieve. Even in action-packed domains such as navigation and spatial cognition, a focus on representations prevailed. In the 1990s, I suggested a conception of navigation in terms of navigational servomechanisms. A servomechanism can be said to aim for a goal, with deviations from the goal-directed path registering as an error. The error drives action to reduce the error in a negative-feedback loop. This loop, with the action reducing the very signal that drove action in the first place, is key to defining a servomechanism. Even though actions are crucial components of servomechanisms, my focus was on the representational component that encodes signals and evaluates errors. Recently, I modified and amplified this view in claiming that, in navigation, servomechanisms operate by modulating the performance of oscillators, endogenous units that produce periodic action. The pattern is found from bacteria travelling micrometres to sea turtles travelling thousands of kilometres. This pattern of servomechanisms working with oscillators is found in other realms of cognition and of life. I think that oscillators provide an effective way to organise an organism's own activities while servomechanisms provide an effective means to adjust to the organism's environment, including that of its own body.

Insect-inspired AI for autonomous robots

Autonomous robots are expected to perform a wide range of sophisticated tasks in complex, unknown environments. However, available onboard computing capabilities and algorithms represent a considerable obstacle to reaching higher levels of autonomy, especially as robots get smaller and the end of Moore's law approaches. Here, we argue that inspiration from insect intelligence is a promising alternative to classic methods in robotics for the artificial intelligence (AI) needed for the autonomy of small, mobile robots. The advantage of insect intelligence stems from its resource efficiency (or parsimony) especially in terms of power and mass. First, we discuss the main aspects of insect intelligence underlying this parsimony: embodiment, sensory-motor coordination, and swarming. Then, we take stock of where insect-inspired AI stands as an alternative to other approaches to important robotic tasks such as navigation and identify open challenges on the road to its more widespread adoption. Last, we reflect on the types of processors that are suitable for implementing insect-inspired AI, from more traditional ones such as microcontrollers and field-programmable gate arrays to unconventional neuromorphic processors. We argue that even for neuromorphic processors, one should not simply apply existing AI algorithms but exploit insights from natural insect intelligence to get maximally efficient AI for robot autonomy.

Oscillators and servomechanisms in orientation and navigation, and sometimes in cognition

Navigational mechanisms have been characterized as servomechanisms. A navigational servomechanism specifies a goal state to strive for. Discrepancies between the perceived current state and the goal state specify error. Servomechanisms adjust the course of travel to reduce the error. I now add that navigational servomechanisms work with oscillators, periodic movements of effectors that drive locomotion. I illustrate this concept selectively over a vast range of scales of travel from micrometres in bacteria to thousands of kilometres in sea turtles. The servomechanisms differ in sophistication, with some interrupting forward motion occasionally or changing travel speed in kineses and others adjusting the direction of travel in taxes. I suggest that in other realms of life as well, especially in cognition, servomechanisms work with oscillators.

Embodiment in distributed information processing: "Solid" plants versus "liquid" ant colonies

Information processing is an essential part of biology, enabling coordination of intra-organismal processes such as development, environmental adaptation and inter-organismal communication. Whilst in animals with specialised brain tissue a substantial amount of information processing occurs in a centralised manner, most biological computing is distributed across multiple entities, such as cells in a tissue, roots in a root system or ants in a colony. Physical context, called embodiment, also affects the nature of biological computing. While plants and ant colonies both perform distributed computing, in plants the units occupy fixed positions while individual ants move around. This distinction, solid versus liquid brain computing, shapes the nature of computations. Here we compare information processing in plants and ant colonies, highlighting how similarities and differences originate in, as well as make use of, the differences in embodiment. We end with a discussion on how this embodiment perspective may inform the debate on plant cognition.