I Know My Neighbour: Individual Recognition in Octopus vulgaris

Background: Little is known about individual recognition (IR) in octopuses, although they have been abundantly studied for their sophisticated behaviour and learning capacities. Indeed, the ability of octopuses to recognise conspecifics is suggested by a number of clues emerging from both laboratory studies (where they appear to form and maintain dominance hierarchies) and field observations (octopuses of neighbouring dens display little agonism between each other). To fill this gap in knowledge, we investigated the behaviour of 24 size-matched pairs of Octopus vulgaris in laboratory conditions. Methodology/Principal Findings: The experimental design was composed of 3 phases: Phase 1 (acclimatization): 12 ‘‘sightallowed’’ (and 12 ‘‘isolated’’) pairs were maintained for 3 days in contiguous tanks separated by a transparent (and opaque) partition to allow (and block) the vision of the conspecific; Phase 2 (cohabitation): members of each pair (both sight-allowed and isolated) were transferred into an experimental tank and were allowed to interact for 15 min every day for 3 consecutive days; Phase 3 (test): each pair (both sight-allowed and isolated) was subject to a switch of an octopus to form pairs composed of either familiar (‘‘sham switches’’) or unfamiliar conspecifics (‘‘real switches’’). Longer latencies (i.e. the time elapsed from the first interaction) and fewer physical contacts in the familiar pairs as opposed to the unfamiliar pairs were used as proxies for recognition. Conclusions: Octopuses appear able to recognise conspecifics and to remember the individual previously met for at leas

Functional Clustering Drives Encoding Improvement in a Developing Brain Network during Awake Visual Learning

Sensory experience drives dramatic structural and functional plasticity in developing neurons. However, for single-neuron plasticity to optimally improve whole-network encoding of sensory information, changes must be coordinated between neurons to ensure a full range of stimuli is efficiently represented. Using two-photon calcium imaging to monitor evoked activity in over 100 neurons simultaneously, we investigate network-level changes in the developing Xenopus laevis tectum during visual training with motion stimuli. Training causes stimulus-specific changes in neuronal responses and interactions, resulting in improved population encoding. This plasticity is spatially structured, increasing tuning curve similarity and interactions among nearby neurons, and decreasing interactions among distant neurons. Training does not improve encoding by single clusters of similarly responding neurons, but improves encoding across clusters, indicating coordinated plasticity across the network. NMDA receptor blockade prevents coordinated plasticity, reduces clustering, and abolishes whole-network encoding improvement. We conclude that NMDA receptors support experience-dependent network self-organization, allowing efficient population coding of a diverse range of stimuli.Canadian Institutes of Health Researc

Design, fabrication and control of soft robots

Conventionally, engineers have employed rigid materials to fabricate precise, predictable robotic systems, which are easily modelled as rigid members connected at discrete joints. Natural systems, however, often match or exceed the performance of robotic systems with deformable bodies. Cephalopods, for example, achieve amazing feats of manipulation and locomotion without a skeleton; even vertebrates such as humans achieve dynamic gaits by storing elastic energy in their compliant bones and soft tissues. Inspired by nature, engineers have begun to explore the design and control of soft-bodied robots composed of compliant materials. This Review discusses recent developments in the emerging field of soft robotics.National Science Foundation (U.S.) (Grant IIS-1226883

Entrained rhythmic activities of neuronal ensembles as perceptual memory of time interval

The ability to process temporal information is fundamental to sensory perception, cognitive processing and motor behaviour of all living organisms, from amoebae to humans(1-4). Neural circuit mechanisms based on neuronal and synaptic properties have been shown to process temporal information over the range of tens of microseconds to hundreds of milliseconds(5-7). How neural circuits process temporal information in the range of seconds to minutes is much less understood. Studies of working memory in monkeys and rats have shown that neurons in the prefrontal cortex(8-10), the parietal cortex(9,11) and the thalamus(12) exhibit ramping activities that linearly correlate with the lapse of time until the end of a specific time interval of several seconds that the animal is trained to memorize. Many organisms can also memorize the time interval of rhythmic sensory stimuli in the timescale of seconds and can coordinate motor behaviour accordingly, for example, by keeping the rhythm after exposure to the beat of music. Here we report a form of rhythmic activity among specific neuronal ensembles in the zebrafish optic tectum, which retains the memory of the time interval ( in the order of seconds) of repetitive sensory stimuli for a duration of up to similar to 20 s. After repetitive visual conditioning stimulation ( CS) of zebrafish larvae, we observed rhythmic post-CS activities among specific tectal neuronal ensembles, with a regular interval that closely matched the CS. Visuomotor behaviour of the zebrafish larvae also showed regular post- CS repetitions at the entrained time interval that correlated with rhythmic neuronal ensemble activities in the tectum. Thus, rhythmic activities among specific neuronal ensembles may act as an adjustable 'metronome' for time intervals in the order of seconds, and serve as a mechanism for the short- term perceptual memory of rhythmic sensory experience

The world according to zebrafish: How neural circuits generate behaviour

Understanding how the brain functions is one of the most ambitious current scientific goals. This challenge will only be accomplish by a multidisciplinary approach involving genetics, molecular biology, optics, ethology, neurobiology and mathematics and using tractable model systems. The zebrafish larva is a transparent genetically tractable small vertebrate, ideal for the combination state-of-the- art imaging techniques (e.g. two-photon scanning microscopy, single-plane illumination microscopy, spatial light modulator microscopy and lightfield microscopy), bioluminiscence and optogenetics to monitor and manipulate neuronal activity from single specific neurons up to the entire brain, in an intact behaving organism. Furthermore, the zebrafish model offers large and increasing collection of mutant and transgenic lines modelling human brain diseases. With these advantages in hand, the zebrafish larva became in the recent years, a novel animal model to study neuronal circuits and behaviour, taking us closer than ever before to understand how the brain controls behaviour

Nonsomatotopic Organization of the Higher Motor Centers in Octopus

Hyperredundant limbs with a virtually unlimited number of degrees of freedom (DOFs) pose a challenge for both biological and computational systems of motor control. In the flexible arms of the octopus, simplification strategies have evolved to reduce the number of controlled DOFs [1–3]. Motor control in the octopus nervous system is hierarchically organized [4, 5]. A relatively small central brain integrates a huge amount of visual and tactile information from the large optic lobes and the peripheral nervous system of the arms [6–9] and issues commands to lower motor centers controlling the elaborated neuromuscular system of the arms. This unique organization raises new questions on the organization of the octopus brain and whether and how it represents the rich movement repertoire. We developed a method of brain microstimulation in freely behaving animals and stimulated the higher motor centers—the basal lobes—thus inducing discrete and complex sets of movements. As stimulation strength increased, complex movements were recruited from basic components shared by different types of movement. We found no stimulation site where movements of a single arm or body part could be elicited. Discrete and complex components have no central topographical organization but are distributed over wide regions

Design and Development of a Soft Actuator for a Robot Inspired by the Octopus Arm

The octopus provides roboticists with a good example of a completely compliant structure that can however reach good levels of stiffness and then exert forces on its environment. With no rigid structures, the octopus can deform its body and fit small apertures, its arms can bend in all directions and they can even elongate. The peculiar muscular Structure of the octopus arm, named muscular hydrostat, acts in fact as a modifiable skeleton, providing stiffness when and where needed. A key point in imitating this muscular structure is that the muscular hydrostat creates a sort of antagonistic mechanism between different muscle fibres. As a consequence, the arm movements are given by a combination of contractions of part of the muscles and passive stretching of the other muscles. On one side, this reduces the contraction requirements for the single muscle; on the other side, the contractile structure must be compliant and passively stretchable. The contractile units proposed here are built with EAP (Electro-Active Polymer) technology, with a particular geometry that increases the contraction range and force, by using soft materials. Contraction tests on prototypes of the contracting units show a very good similarity with a theoretical model and support the starting hypothesis on the possibility of building a robotic octopus-like arm based on an artificial muscular hydrostat