0000000000054057
AUTHOR
Roland Strauss
A spiking network for body size learning inspired by the fruit fly
The concept of peripersonal space is an interesting research topics for psychologists, neurobiologists and for robotic applications. A living being can learn the representation of its own body to take the correct behavioral decision when interacting with the world. To transfer these important learning mechanisms on bio-robots, simple and efficient solutions can be found in the insect world. In this paper a neural-based model for body-size learning is proposed taking into account the results obtained in experiments with fruit flies. Simulations and experimental results on a roving platform are reported and compared with the biological counterpart.
Modelling Spatial Memory
Among the different capabilities of animals, the formation of spatial memories is crucial for their life. Living beings able to move, constantly need to orient themselves in the environment to reach a target that might be not always visible. This chapter investigates the process of spatial memory formation as an essential ingredient for orientation in open and unstructured environments. Neural centres devoted to spatial memory and path integration were deeply investigated both in rats and different insect species like ants, bees and fruit flies. In this chapter a neural-inspired model for the formation of a spatial working memory is discussed considering some key elements of the insect neur…
Higher Brain Centers for Intelligent Motor Control in Insects
The higher control of orientation, walking and gap climbing behavior in the fruit fly Drosophila is studied by neurogenetic means. An insect brain model is presented for the control of object approaches. The model comprises learning abilities of flies at two different time scales. A short-term orientation memory allows for the continued approach of objects that disappeared from sight. Flies can come back to the still invisible object even after a detour to a distracter object. A long-term memory allows for the storage of experience with particular types of objects in order to trigger avoidance behavior in the future instead of the default approach behavior. Moreover, we provide evidence tha…
Motor-skill learning in an insect inspired neuro-computational control system
In nature, insects show impressive adaptation and learning capabilities. The proposed computational model takes inspiration from specific structures of the insect brain: after proposing key hypotheses on the direct involvement of the mushroom bodies (MBs) and on their neural organization, we developed a new architecture for motor learning to be applied in insect-like walking robots. The proposed model is a nonlinear control system based on spiking neurons. MBs are modeled as a nonlinear recurrent spiking neural network (SNN) with novel characteristics, able to memorize time evolutions of key parameters of the neural motor controller, so that existing motor primitives can be improved. The ad…
The visual orientation memory of Drosophila requires Foraging (PKG) upstream of Ignorant (RSK2) in ring neurons of the central complex
Orientation and navigation in a complex environment requires path planning and recall to exert goal-driven behavior. Walking Drosophila flies possess a visual orientation memory for attractive targets which is localized in the central complex of the adult brain. Here we show that this type of working memory requires the cGMP-dependent protein kinase encoded by the foraging gene in just one type of ellipsoid-body ring neurons. Moreover, genetic and epistatic interaction studies provide evidence that Foraging functions upstream of the Ignorant Ribosomal-S6 Kinase 2, thus revealing a novel neuronal signaling pathway necessary for this type of memory in Drosophila.
Neurobiological Models of the Central Complex and the Mushroom Bodies
This study reviews the actual knowledge on functions of the central complex (CX) and the mushroom bodies (MBs) in a genetic model insect, the fly Drosophila melanogaster. Ongoing research of UNIMAINZ and respective data are included. Reference is made to other insects, where respective functions are not yet studied in Drosophila. Neuroanatomical information is reported with regard to the general flow of information in these central brain neuropils. Particular projection systems and circuits are taken into account where this can be linked to functions. Models are developed.
Glial and neuronal expression of polyglutamine proteins induce behavioral changes and aggregate formation inDrosophila
Patients with polyglutamine expansion diseases, like Huntington's disease or several spinocerebellar ataxias, first present with neurological symptoms that can occur in the absence of neurodegeneration. Behavioral symptoms thus appear to be caused by neuronal dysfunction, rather than cell death. Pathogenesis in polyglutamine expansion diseases is largely viewed as a cell-autonomous process in neurons. It is likely, however, that this process is influenced by changes in glial physiology and, at least in the case of DRPLA glial inclusions and glial cell death, seems to be an important part in the pathogenesis. To investigate these aspects in a Drosophila model system, we expressed polyglutami…
A Fly-Inspired Mushroom Bodies Model for Sensory-Motor Control Through Sequence and Subsequence Learning
Classification and sequence learning are relevant capabilities used by living beings to extract complex information from the environment for behavioral control. The insect world is full of examples where the presentation time of specific stimuli shapes the behavioral response. On the basis of previously developed neural models, inspired by Drosophila melanogaster, a new architecture for classification and sequence learning is here presented under the perspective of the Neural Reuse theory. Classification of relevant input stimuli is performed through resonant neurons, activated by the complex dynamics generated in a lattice of recurrent spiking neurons modeling the insect Mushroom Bodies n…
Visual Working Memory Requires Permissive and Instructive NO/cGMP Signaling at Presynapses in the Drosophila Central Brain.
The gaseous second messenger nitric oxide (NO) has been shown to regulate memory formation by activating retrograde signaling cascades from post- to presynapse that involve cyclic guanosine monophosphate (cGMP) production to induce synaptic plasticity and transcriptional changes. In this study, we analyzed the role of NO in the formation of a visual working memory that lasts only a few seconds. This memory is encoded in a subset of ring neurons that form the ellipsoid body in the Drosophila brain. Using genetic and pharmacological manipulations, we show that NO signaling is required for cGMP-mediated CREB activation, leading to the expression of competence factors like the synaptic homer pr…
Modeling the insect mushroom bodies: application to a delayed match-to-sample task.
Despite their small brains, insects show advanced capabilities in learning and task solving. Flies, honeybees and ants are becoming a reference point in neuroscience and a main source of inspiration for autonomous robot design issues and control algorithms. In particular, honeybees demonstrate to be able to autonomously abstract complex associations and apply them in tasks involving different sensory modalities within the insect brain. Mushroom Bodies (MBs) are worthy of primary attention for understanding memory and learning functions in insects. In fact, even if their main role regards olfactory conditioning, they are involved in many behavioral achievements and learning capabilities, as …
Modelling the insect Mushroom Bodies: Application to sequence learning
Learning and reproducing temporal sequences is a fundamental ability used by living beings to adapt behaviour repertoire to environmental constraints. This paper is focused on the description of a model based on spiking neurons, able to learn and autonomously generate a sequence of events. The neural architecture is inspired by the insect Mushroom Bodies (MBs) that are a crucial centre for multimodal sensory integration and behaviour modulation. The sequence learning capability coexists, within the insect brain computational model, with all the other features already addressed like attention, expectation, learning classification and others. This is a clear example that a unique neural struc…
Serum Response Factor-Mediated Gene Regulation in a Drosophila Visual Working Memory
Summary Background Navigation through the environment requires a working memory for the chosen target and path integration facilitating an approach when the target becomes temporarily hidden. We have previously shown that this visual orientation memory resides in the ellipsoid body, which is part of the central complex in the Drosophila brain. Former analysis of foraging and ignorant mutants have revealed that a hierarchical PKG and RSKII kinase signaling cascade in a subset of the ellipsoid-body ring neurons is required for this type of working memory in flies. Results Here we show that mutants in the ellipsoid body open ( ebo ) gene, which encodes the actin-binding protein Exportin 6, e…
Roving Robots Gain from an Orientation Algorithm of Fruit Flies and Predict a Fly Decision-Making Algorithm
Simple organisms like bacteria are directly influenced by momentary changes in concentration or strength of sensory signals. In noisy sensory gradients frequent zigzagging reduces the performance of the cell or organism. Drosophila melanogaster flies significantly deviate from a direct response to sensory input when orienting in gradients. A dynamical model has been derived which reproduces fly behaviour. Here we report on an emergent property of the model. Implemented in a robot, the algorithm is sustaining decisions between visual targets. The behaviour was consequently found in wild-type flies, which stay with a once-chosen visual target for considerable longer times than mutant flies wi…
The central control of oriented locomotion in insects - towards a neurobiological model
A neurobiological model for the higher control of oriented locomotion in insects is developed here. It is based on studies in a genetic model insect, the fruit fly Drosophila melangaster. Reference is made to other insects, where respective functions are not yet studied in Drosophila. Flies can walk swiftly with up to 16 steps per second, each leg, on almost any substrate and in any orientation to the gravity vector. To bring about this astounding maneuverability and agility the central complex within the insect brain derives directional commands for the leg coordination centers in the thoracic nervous system. Neuroanatomical information is taken into account with regard to the general flow…
An insect brain computational model inspired by Drosophila melanogaster: architecture description
The fruit fly Drosophila melanogaster is an extremely interesting insect because it shows a wealth of complex behaviors, despite its small brain. Nowadays genetic techniques allow to knock out the function of defined parts or genes in the Drosophila brain. Together with specific mutants which show similar defects in those parts or genes, hypothesis about the functions of every single brain part can be drawn. Following these experiments, a computational model of the fly Drosophila has been designed with a view to its robotic implementation.
Software/Hardware Issues in Modelling Insect Brain Architecture
The concept of cognitive abilities is commonly associated to humans and animals like mammals, birds and others. Nevertheless, in the last years several research groups have intensified the studies on insects that posses a much simpler brain structure even if they are able to show interesting memory and learning capabilities. In this paper a survey on some key results obtained in a joint research activity among Engineers and Neurogeneticians is reported. They were focussed toward the design and implementation of a model of the insect brain inspired by the Drosophila melanogaster. Particular attention was paid to the main neural centers the Mushroom Bodies and the Central Complex. Moreover a …
Learning spatio-temporal behavioural sequences
Living beings are able to adapt their behaviour repertoire to environmental constraints. Among the capabilities needed for such improvement, the ability to store and retrieve temporal sequences is of particular importance. This chapter focuses on the description of an architecture based on spiking neurons, able to learn and autonomously generate a sequence of generic objects or events. The neural architecture is inspired by the insect mushroom bodies already taken into account in the previous chapters as a crucial centre for multimodal sensory integration and behaviour modulation in insects. Sequence learning is only one among a variety of functionalities that coexist within the insect brai…
A Systematic Nomenclature for the Insect Brain
SummaryDespite the importance of the insect nervous system for functional and developmental neuroscience, descriptions of insect brains have suffered from a lack of uniform nomenclature. Ambiguous definitions of brain regions and fiber bundles have contributed to the variation of names used to describe the same structure. The lack of clearly determined neuropil boundaries has made it difficult to document precise locations of neuronal projections for connectomics study. To address such issues, a consortium of neurobiologists studying arthropod brains, the Insect Brain Name Working Group, has established the present hierarchical nomenclature system, using the brain of Drosophila melanogaster…
Implementation of a Drosophila-inspired orientation model on the Eye-Ris platform
A behavioral model, recently derived from experiments on fruit-flies, was implemented, with successful comparative experiments on orientation control in real robots. This model has been firstly implemented in a standard CNN structure, using an algorithm based on classical, space-invariant templates. Subsequently, the Eye-Ris platform was utilised for the implementation of the whole strategy, at the aim to constitute a stand alone smart sensor for orientation control in bio-inspired robotic platforms. The Eye-Ris vl.2 is a visual system, made by Anafocus, that employs a fully-parallel mixed-signal array sensor-processor chip. Some experiments are reported using a commercial roving platform, …
A computational model for motor learning in insects
The aim of this paper is to propose a computational model, inspired by Drosophila melanogaster, able to handle problems related to motor learning. The role of the Mushroom Bodies and the Central Complex in solving this problem is analyzed and plausible biologically inspired models are proposed. The designed computational models have been evaluated in simulation using a dynamic structure inspired by the fruit fly. The obtained results open the way to new neurobiological experiments focused to better understand the underlined mechanisms involved, to verify the feasibility of the hypotheses formulated and the significance of the obtained results.
Serotonin modulates a depression-like state in Drosophila responsive to lithium treatment
Major depressive disorder (MDD) affects millions of patients; however, the pathophysiology is poorly understood. Rodent models have been developed using chronic mild stress or unavoidable punishment (learned helplessness) to induce features of depression, like general inactivity and anhedonia. Here we report a three-day vibration-stress protocol for Drosophila that reduces voluntary behavioural activity. As in many MDD patients, lithium-chloride treatment can suppress this depression-like state in flies. The behavioural changes correlate with reduced serotonin (5-HT) release at the mushroom body (MB) and can be relieved by feeding the antidepressant 5-hydroxy-L-tryptophan or sucrose, which …
Controlling and learning motor functions
Effective and adaptive motor functions are important for living beings and developing computational and learning mechanisms for roving robots is a crucial aspect in biorobotics. In this chapter we report a new architecture for motor learning to be applied in insect-like walking robots. The proposed model is based on the MB structure previously introduced able to memorize time evolutions of key parameters of the neural motor controller to improve existing motor primitives. The adopted control scheme enables the structure to efficiently cope with goal-oriented behavioural motor tasks. The problem of body-size evaluation is also considered and a model for the parallax-based estimation is provi…
Non-linear neuro-inspired circuits and systems: Processing and learning issues
In this chapter the main elements useful for the design and realization of the neural architectures reported in the following chapters will be presented. Considering spiking and non-spiking neurons, the models used for implementing each of them, the synaptic models, the basic learning and plasticity algorithms and the network architectures will be introduced and analysed. The key elements that led to their selection and application in the developed neuro-inspired systems will be discussed briefly.
Analysis of a spatial orientation memory in Drosophila.
Flexible goal-driven orientation requires that the position of a target be stored, especially in case the target moves out of sight. The capability to retain, recall and integrate such positional information into guiding behaviour has been summarized under the term spatial working memory. This kind of memory contains specific details of the presence that are not necessarily part of a long-term memory. Neurophysiological studies in primates indicate that sustained activity of neurons encodes the sensory information even though the object is no longer present. Furthermore they suggest that dopamine transmits the respective input to the prefrontal cortex, and simultaneous suppression by GABA s…
Visual learning in Drosophila: Application on a roving robot and comparisons
Visual learning is an important aspect of fly life. Flies are able to extract visual cues from objects, like colors, vertical and horizontal distributedness, and others, that can be used for learning to associate a meaning to specific features (i.e. a reward or a punishment). Interesting biological experiments show trained stationary flying flies avoiding flying towards specific visual objects, appearing on the surrounding environment. Wild-type flies effectively learn to avoid those objects but this is not the case for the learning mutant rutabaga defective in the cyclic AMP dependent pathway for plasticity. A bio-inspired architecture has been proposed to model the fly behavior and experi…
Drosophila Full-Length Amyloid Precursor Protein is Required for Visual Working Memory and Prevents Age-Related Memory Impairment
Summary The β-amyloid precursor protein (APP) plays a central role in the etiology of Alzheimer's disease (AD). However, its normal physiological functions are still unclear. APP is cleaved by various secretases whereby sequential processing by the β- and γ-secretases produces the β-amyloid peptide that is accumulating in plaques that typify AD. In addition, this produces secreted N-terminal sAPPβ fragments and the APP intracellular domain (AICD). Alternative cleavage by α-secretase results in slightly longer secreted sAPPα fragments and the identical AICD. Whereas the AICD has been connected with transcriptional regulation, sAPPα fragments have been suggested to have a neurotrophic and neu…
The Insect Mushroom Bodies: a Paradigm of Neural Reuse
This paper is devoted to discuss the implementation of models,which are inspired by the fly Drosophila melanogaster and able to handle open problems in the field of robotics such as attention, expectation and sequence learning. The role of the Mushroom Bodies (MBs) in solving these tasks is analyzed in detail and a unifying plausible biologically inspired model is proposed. The developed neural structure is able to show different capabilities in line with the paradigm of neural reuse. The same neural circuit can be exploited to accomplish multiple tasks showing interesting capabilities such as attention, expectation and delayed match-to-sample. The simulation results here reported suggest a…
Drosophila-inspired visual orientation model on the Eye-Ris platform: Experiments on a roving robot
Behavioral experiments on fruit flies had shown that they are attracted by near objects and they prefer front-to-back motion. In this paper a visual orientation model is implemented on the Eye-Ris vision system and tested using a roving platform. Robotic experiments are used to collect statistical data regarding the system behaviour: followed trajectories, dwelling time, distribution of gaze direction and others strictly resembling the biological experimental setup on the flies. The statistical analysis has been performed in different scenarios where the robot faces with different object distribution in the arena. The acquired data has been used to validate the proposed model making a compa…
Integrative Biomimetics of Autonomous Hexapedal Locomotion
Despite substantial advances in many different fields of neurorobotics in general, and biomimetic robots in particular, a key challenge is the integration of concepts: to collate and combine research on disparate and conceptually disjunct research areas in the neurosciences and engineering sciences. We claim that the development of suitable robotic integration platforms is of particular relevance to make such integration of concepts work in practice. Here, we provide an example for a hexapod robotic integration platform for autonomous locomotion. In a sequence of six focus sections dealing with aspects of intelligent, embodied motor control in insects and multipedal robots-ranging from comp…
Exploiting Imperfections in Perception-Action Learning
In this paper a some examples of simulations and experiments performed in the last few years in the field of bio-inspired robotics are reviewed and revisited, deepening their characteristics and emphasising the role of imperfections that could be the main actors guiding their success in real environment. Our cases of study rely on both geetic and behavioral experiments on the fruit fly, from which models, simulations and robotic experiments were performed.
Biological investigation of neural circuits in the insect brain
Watching insects thoughtfully one cannot but adore their behavioural capabilities. They have developed amazing reproductive, foraging and orientation strategies and at the same time they followed the evolutionary path of miniaturization and sparseness. Both features together turn them into a role model for autonomous robots. Despite their tiny brains, fruit flies (Drosophila) can orient, walk on uneven terrain, in any orientation to gravity, can fly in adverse winds, find partners, places for egg laying, food and shelter. Drosophila melanogaster is the model animal for geneticists and cutting-edge tools are being continuously developed to study the underpinnings of their behavioural capabil…
Drosophila Acquires a Long-Lasting Body-Size Memory from Visual Feedback
Summary Grasping an object or crossing a trench requires the integration of information on the operating distance of our limbs with precise distance estimation. The reach of our hands and step size of our legs are learned by the visual feedback we get during our actions. This implicit knowledge of our peripersonal space is first acquired during infancy but will be continuously updated throughout our whole life [ 1 ]. In contrast, body size of holometabolous insects does not change after metamorphosis; nevertheless, they do have to learn their body reaches at least once. The body size of Drosophila imagines can vary by about 15% depending on environmental factors like food quality and temper…
A spiking network for spatial memory formation: Towards a fly-inspired ellipsoid body model
Neural centers devoted to spatial memory and path integration were largely studied in rats and in different insect species like ants and bees. In this paper a neural-based model for the formation of a spatial working memory is proposed mirroring some peculiarities of the Drosophila central brain and in particular the ellipsoid body. Simulation results are reported opening the way to applications on roving platforms.
A Mushroom Bodies inspired spiking network for classification and sequence learning
Sequence learning is a complex capability shown by living beings, able to extract information from the environment. Looking into the insect world, there are several examples where the presentation time of specific stimuli is considered to select the proper behavioural response. On the basis of previously developed neural models for sequence learning, inspired by the Drosophila melanogaster, a new formalization of key brain structures involved in the process is here provided. The input classification is performed through resonant neurons, stimulated by the complex dynamics generated in a lattice of recurrent spiking neurons modelling the Mushroom Bodies neuropile in the insect brain. The net…
Mushroom bodies enhance initial motor activity in Drosophila.
The central body (or central complex, CCX) and the mushroom bodies (MBs) are brain structures in most insect phyla that have been shown to influence aspects of locomotion. The CCX regulates motor coordination and enhances activity while MBs have, thus far, been shown to suppress motor activity levels measured over time intervals ranging from hours to weeks. In this report, we investigate MB involvement in motor behavior during the initial stages (15 minutes) of walking in Buridan's paradigm. We measured aspects of walking in flies that had MB lesions induced by mutations in six different genes and by chemical ablation. All tested flies were later examined histologically to assess MB neuroan…
Towards Neural Reusable Neuro-inspired Systems
This chapter presents an overview of some key aspects of the neuro-inspired modelling previously discussed, under the new perspective of the neural reuse theory. Here it is envisaged that the excellent capabilities shown by insects with their small neuron number and relatively low brain complexity, as compared to vertebrates, could be justified if some key neural structures are re-used for different behavioural needs. The chapter recalls some examples, found in the literature for addressing specific topics and reformulates them in relation to the neural reuse theory.
A screen for constituents of motor control and decision making in Drosophila reveals visual distance-estimation neurons
AbstractClimbing over chasms larger than step size is vital to fruit flies, since foraging and mating are achieved while walking. Flies avoid futile climbing attempts by processing parallax-motion vision to estimate gap width. To identify neuronal substrates of climbing control, we screened a large collection of fly lines with temporarily inactivated neuronal populations in a novel high-throughput assay described here. The observed climbing phenotypes were classified; lines in each group are reported. Selected lines were further analysed by high-resolution video cinematography. One striking class of flies attempts to climb chasms of unsurmountable width; expression analysis guided us to C2 …
Motor learning and body size within an insect brain computational model
Nowadays modeling insect brains is also an important source of inspiration to develop learning architectures and control algorithms for applications on autonomous walking robots. Within the insect brain two important neuropiles received a lot of attention: the mushroom bodies (MBs) and the central complex (CX). Recent research activities considered the MBs as a unique architecture where different behavioural functions can be found. MBs are well known in bees and flies for their role in performing associative learning and memory in odor conditioning experiments [4]. They are also involved in the processing of multiple sensory modalities including visual tasks [3], different forms of learning…