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Using the well mapped connectome of the nematode Caenorhabditis Elegans (C. Elegans) [1], I created a program that can be started three hundred and two times where each program inherits the attributes one of each of the worms 302 neurons and uses interprocess communications to connect the programs together in a manner similar to that of synaptic co...
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We approach the C. elegans connectome as an information processing network that receives input from about 90 sensory neurons, processes that information through a highly recurrent network of about 80 interneurons, and it produces a coordinated output from about 120 motor neurons that control the nematode’s muscles. We focus on the feedforward flow...
Graph spectral analysis can yield meaningful embeddings of graphs by providing insight into distributed features not directly accessible in nodal domain. Recent efforts in graph signal processing have proposed new decompositions-for example, based on wavelets and Slepians-that can be applied to filter signals defined on the graph. In this work, we...
We analyse the neural dynamics and its relation with the emergent behaviour of a robotic vehicle that is controlled by a neural network numerical simulation based on the nervous system of the nematode Caenorhabditis elegans. The robot interacts with the environment through a sensor, that transmits the information to sensory neurons, while motor neu...
Detailed anatomical maps of individual organs and entire animals have served as invaluable entry points for ensuing dissection of their evolution, development, and function. The pharynx of the nematode Caenorhabditis elegans is a simple neuromuscular organ with a self-contained, autonomously acting nervous system, composed of 20 neurons that fall i...
Determining the fundamental architectural design of complex nervous systems will lead to significant medical and technological advances. Yet it remains unclear how nervous systems evolved highly efficient networks with near optimal sharing of pathways that yet produce multiple distinct behaviors to reach the organism’s goals. To determine this, the...
Citations
... This, however, has not discouraged advancements in this area. The EV3 robot built using the connectome of C Elegans has resulted in similar behaviors of the worm being observed in the LEGO robot (Busbice, 2014). The patterns of behavior, here, emerges from the relatively smaller connectome. ...
With the advent of Machine Learning models in the current global markets, questions pertaining to artificial mental states and Artificial General Intelligence (AGI) come to the forefront. The current study seeks to find support for possible mental states by subjecting three different Machine Learning models – GPT 3.5 (Generative Pre-Trained Transformer), Bard, and GPT 3 – Ada to psychological tests concerning Theory of Mind (ToM). To discern another’s mental state one must be capable of distinguishing oneself as an entity separate from the other. The three models were presented with the Strange Story Task and the Theory of Mind Scale. The idea of artificial ToM by observation and prediction has been posited. As hypothesized, GPT 3.5 significantly outperformed GPT 3 (Ada) and failed to outperform Bard. Further implications and limitations have been discussed.
... In this work we use a robotic vehicle that is controlled by a neural network numerical simulation based on the C. elegans connectome (Busbice, 2014b). In the simulation the neurons have the same firing threshold, and as a consequence have identical dynamics as isolated units. ...
... The control of the robots was implemented in a custom numerical simulation using the Python 3 programming language, and is based on the original program developed by Busbice (2014b) and the version implemented in the GoPiGo robot (Industries, 2020a). ...
... In this way the program allows for the whole set of neural signals and the actions of the robot to be sampled once per second, setting the upper bound to the frequency of every individual signal to be ω = 0.5Hz. This is directly related to the physical scale of the robot and how fast it can execute the commands received (Busbice, 2014b). If the parameter for the motor control is set too low, then the motors cannot execute the actions, as they have a physical limitation on the time scale at which they can turn and reverse. ...
We analyze the neural dynamics and their relation with the emergent actions of a robotic vehicle that is controlled by a neural network numerical simulation based on the nervous system of the nematode Caenorhabditis elegans. The robot interacts with the environment through a sensor that transmits the information to sensory neurons, while motor neurons outputs are connected to wheels. This is enough to allow emergent robot actions in complex environments, such as avoiding collisions with obstacles. Working with robotic models makes it possible to simultaneously keep track of the dynamics of all the neurons and also register the actions of the robot in the environment in real time, while avoiding the complex technicalities of simulating a real environment. This allowed us to identify several relevant features of the neural dynamics associated with the emergent actions of the robot, some of which have already been observed in biological worms. These results suggest that some basic aspects of behaviors observed in living beings are determined by the underlying structure of the associated neural network.
... Such technologies are already being tested, and several large scale initiatives mapping the brain connectome are underway (see Seung, 2012). Further progress has been made in the reconstruction of non-human minds: first, the whole nervous system of the nematode C. elegans was mapped and subsequently released in 2019 (Cook et al., 2019), and robots simulating the C. elegans nervous system are capable of autonomous motion (Busbice, 2014;Neiva & Goiveia, 2017). Second, the Blue Brain project recently digitized the whole cortex of a mouse (Reimann et al., 2019), and digitized parts of rat brains fire similarly to their biological counterparts (Markram et al., 2015). ...
Mind upload, making a digital copy of one's brain, is a part of the transhumanistic dream of eternal life and the end of suffering. It is also perceived as a viable route toward artificial general intelligence (AGI). However, AI safety research has alerted to one major risk in creating AGI by mind upload: namely, that mind upload technology could appeal primarily to callous and selfish individuals who then abuse this technology for their personal gain—and, potentially, at a considerable cost to the welfare of humankind. Therefore, it is important to understand whether people's acceptance of mind upload is associated with pathological and/or antisocial traits. To this end, the present research examined whether individual differences in Dark Triad traits predict attitudes toward mind upload in a sample of 1007 English-speaking adults. A pre-registered structural equation model revealed that Machiavellianism (but not psychopathy) was associated with favorable views about mind upload, both directly and indirectly through utilitarian moral attitudes. These results therefore substantiate the concerns voiced by AI safety researchers—namely, that mind upload technology could be adopted disproportionately by individuals with an antisocial personality.
... Such technologies are already being tested, and several large scale initiatives mapping the brain connectome are underway (see Seung, 2012). Further progress has been made in the reconstruction of non-human minds: First, the whole nervous system of the nematode C. Elegans was mapped and subsequently released in 2019 (Cook et al., 2019), and robots simulating the C. Elegans nervous system are capable of autonomous motion (Busbice, 2014;Neiva, 2017). Second, the Blue Brain project recently digitized the whole cortex of a mouse (Reimann et al, 2019), and digitized parts of rat brains fire similarly to their biological counterparts (Markram et al., 2015). ...
Mind upload, making a digital copy of one’s brain, is a part of the transhumanistic dream of eternal life and the end of suffering. It is also perceived as a viable route toward artificial general intelligence (AGI). However, AI safety research has alerted to one major risk in creating AGI by mind upload: namely, that mind upload technology could appeal primarily to callous and selfish individuals who then abuse this technology for their personal gain—and, potentially, at a considerable cost to the welfare of humankind. Therefore, it is important to understand whether people’s acceptance of mind upload is associated with pathological and/or antisocial traits. To this end, the present research examined whether individual differences in Dark Triad traits predict attitudes toward mind upload in a sample of 1007 English-speaking adults. A pre-registered structural equation model revealed that Machiavellianism (but not psychopathy) was associated with favourable views about mind upload, both directly and indirectly through utilitarian moral attitudes. These results therefore substantiate the concerns voiced by AI safety researchers—namely, that mind upload technology could be adopted disproportionately by individuals with an antisocial personality.
... In this work we use a robot vehicle that is controlled by a neural network numerical simulation based on the C. elegans connectome 30 . This allows us to analyse the neural dynamics that emerges through the connectome, and at the same time to study the interplay between the neural dynamics and the actions of the robot. ...
... For the experiments we use robots based on the design originally presented by T. Busbice 30 . The robots are vehicles with one distance sensor and two wheels, which allow them to sense the environment and move on the ground. ...
... On the other hand, the neural simulation that controls the robot has elementary dynamical units, and uses the biological information of the connectome for their interaction. With this stripped down approach T. Busbice showed that the robot presents emergent behaviours, which allow it to spontaneously navigate and avoid obstacles 30,31 . Thus, the robotic model constitutes an excellent platform to study the interplay between the connectome and emergent behaviours. ...
We analyse the neural dynamics and its relation with the emergent behaviour of a robotic vehicle that is controlled by a neural network numerical simulation based on the nervous system of the nematode Caenorhabditis elegans. The robot interacts with the environment through a sensor, that transmits the information to sensory neurons, while motor neurons outputs are connected to wheels. This is enough to allow robot movement in complex environments, avoiding collisions with obstacles. Working with a robotic model makes it possible to keep track simultaneously of the detailed microscopic dynamics of all the neurons and also register the actions of the robot in the environment in real time. This allowed us to study the interplay between connectome and complex behaviors. We found that some basic features of the global neural dynamics and their correlation with behaviour observed in the worm appear spontaneously in the robot, suggesting they are just an emergent property of the connectome.
... Another interesting project is [29]. In this project the nematode 2 C.Elegans is represented by an EV3 and the connectome 3 of the worm is implemented as software. ...
The German education system is on the verge of raising a generation of digital illiterates. We are in desperate need of up-to-date and motivating teaching content and tools for computer science education to make prevailing topics such as artificial intelligence more accessible to the general public.
The underlying work seeks to tackle these problems. It depicts the current state of research of the interdisciplinary field of educational sciences and machine learning still in its infancy and proposes new learning objectives for teaching machine learning in high school classrooms. In the scope of this work, a state-of-the-art visual programming environment is developed, including an interface for solving tasks created specifically for the use of machine learning with LEGO MINDSTORMS EV3 to match current trends and efforts in computer science education. This thesis is completed by gathering practical insights through diverse workshops. The results of these workshops make a strong case for the underlying work being effective in giving a well rounded introduction to the world of machine learning.
... Недавно стало известно о первом «воплощении» коннектома нематоды: на основании нейронных связей C. Elegance из конструктора «Лего» был сконструирован робот EV3, способный адекватно (подобно нематоде) реагировать на ограниченный набор внешних раздражителей [35]. [193], включая вычисление временной задержки между активацией зон, которая с большой достоверностью определяется по ЭЭГ, и построение сетей Байеса. ...
... Все «поведение» робота реализуется на основании воспроизведения коннектома нематоды (рис. 2).Рис 2. Схема сенсорного и моторного потоков информации робота EV3[35].Нематода C. Elegans -единственный на сегодняшний день организм, для которого известна структура всей нервной системы и получен коннектом. Однако это не позволило исследователям ответить на все вопросы и понять, как работает даже такая относительно простая нервная система. ...
The review is devoted to researches in the relatively new field of neuroscience--connectomics. The theoretical and applied aspects of connectom studying are observed. The concept of connectom is defined as well as its attributes such as connectivity. The review describes the basic modern methods of the connectom investigation, existing data on the connectom structure in normal and pathological conditions, as well as prospects for the development of a new field of knowledge--connectomics.
