Papers by Alexey Leukhin
Blended Cognition (Book), 2019
In this paper we present a new computational bio-inspired approach. We use the three-dimensional... more In this paper we present a new computational bio-inspired approach. We use the three-dimensional model of emotions created by the Hugo Lövheim “cube of emotions” and validated it via neurosimulation in NEST. We present a computational model that bridges psycho-emotional states with computational processes as the extension of the model “cube of emotions.” Results of the neurosimulationindicatetheincremental influence ofdopamine over computational resources used for the computation of a simulation of a psycho-emotional state as well as noradrenaline modulation of the dopamine system, whereas in contrast serotonin decreases the computational resources used to calculate the simulation of apsycho-emotionalstate.Theseresultsindicatetheoverallcorrectnessoftheneuromimetic approaches of artificial cognition that not only are feasible but also offer new and unique ways of designing computing architectures with special performing potential.
This work aims at demonstrating that the neuromodulatory mechanisms that control the emotional st... more This work aims at demonstrating that the neuromodulatory mechanisms that control the emotional states of mammals (specifically rat's brains) can be represented and re-implemented in a computational model processed by a machine. In particular we specifically focus on two neurotransmitters, sero-tonin and dopamine, starting from their fundamental role in basic cognitive processes. In our specific implementation, we represent the simulation of the 'disgust-like' state based on the three dimensional neuromodulatory model of affects or emotions, according to the 'cube of emotions' where dopamine controls attention and serotonin is the key for inhibition. These functional mechanisms can be transferred into an artificial cognitive system: inhibition, for example, can elicit a blocking behaviour that, depending on its intensity and duration, can push the system to a general emotional state. Therefore, the main goal of this paper is to implement such a mechanism in a computational system to make it capable of managing a " failure " scenario in the complex set of inbound parameters appropriate for social environment useful for highlighting memories, decision making, resources evaluation, and other cognitive processes. We have simulated 1000 milliseconds of the sero-tonin and dopamine systems using NEST Neural Simulation Tool with the rat brain as the model to artificially reproduce this mechanism on a compu
In this paper, we present a novel approach to model
and re-implement the noradrenaline influence ... more In this paper, we present a novel approach to model
and re-implement the noradrenaline influence in a bio-plausible
manner suitable for the modelling of emotions in a computational
system. We have upgraded our previous bio-inspired architecture
NEUCOGAR (Neuromodulating Cognitive Architecture) to capture
a key aspect of cognitive processes: novelty detection and its
evaluation. With our model, we can computationally implement
a bioinspired cognitive architecture that uses neuromodulation
as a mechanism to identify signals, as well as to evaluate them
according to their novelty, taking into account the noradrenaline
concentration dynamics. At the same time, the values thus generated
are stored in the system using the same neurotransmitters
model
In this work we propose the following hypothesis: the neuromodulatory mechanisms that control the... more In this work we propose the following hypothesis: the neuromodulatory mechanisms that control the emotional states of mammals can be translated and re-implemented in a computer by controlling the computational performance of a hosted computational system. In our specific implementation, we represent the simulation of the 'fear-like' state based on the three dimensional neuromodulatory model of affects, in this paper 'affects' refer to the basic emotional inborn states, inherited from works of Hugo Lövheim. Whilst dopamine controls attention, serotonin is the key for inhibition, and fear is a elicitator for inhibitory and protective processes. This inhibition can promote [in a cognitive system] to blocking behaviour which can be labelled as 'depression'. Therefore, our interest is how to reimplement biomimet-ically both action-regulators without the computational system to resulting in a 'failed' scenario. We have simulated 1000 ms of the dopamine system using NEST Neural Simulation Tool with the rat brain as the model. The results of the simulation experiments are reported with an evaluation to demonstrate the cor-rectness of our hypothesis.
In this paper we present the following hypothesis: the neuromodulatory
mechanisms that control th... more In this paper we present the following hypothesis: the neuromodulatory
mechanisms that control the emotional states of mammals could be translated and
re-implemented in a computer by means of controlling the computational performance
of a hosted computational system. In our specific implementation we represent
the simulation of the fear-like state based on the three dimensional
neuromodulatory model of affects (here the basic emotional inborn states) that we
have inherited from works of Hugo Lövheim. We have managed to simulate
1000 ms of work of the dopamine system using NEST Neural Simulation Tool and
the rat brain as the model. We also present the results of that simulation and
evaluate them to validate the overall correctness of our hypothesis.
Conference Presentations by Alexey Leukhin
—In this paper, we present a novel approach to model and re-implement the noradrenaline influence... more —In this paper, we present a novel approach to model and re-implement the noradrenaline influence in a bio-plausible manner suitable for the modelling of emotions in a computational system. We have upgraded our previous bio-inspired architecture NEUCOGAR (Neuromodulating Cognitive Architecture) to capture a key aspect of cognitive processes: novelty detection and its evaluation. With our model, we can computationally implement a bioinspired cognitive architecture that uses neuromodulation as a mechanism to identify signals, as well as to evaluate them according to their novelty, taking into account the noradrenaline concentration dynamics. At the same time, the values thus generated are stored in the system using the same neurotransmitters model.
Drafts by Alexey Leukhin
arXiv, 2022
This work is dedicated to the review and perspective of the new direction that we call "Neuropunk... more This work is dedicated to the review and perspective of the new direction that we call "Neuropunk revolution" resembling the cultural phenomenon of cyberpunk. This new phenomenon has its foundations in advances in neuromorphic technologies including memristive and bio-plausible simulations, BCI, and neurointerfaces as well as unconventional approaches to AI and computing in general. We present the review of the current state-of-the-art and our vision of near future development of scientific approaches and future technologies. We call the "Neuropunk revolution" the set of trends that in our view provide the necessary background for the new generation of approaches technologies to integrate the cybernetic objects with biological tissues in close loop system as well as robotic systems inspired by the biological processes again integrated with biological objects. We see bio-plausible simulations implemented by digital computers or spiking networks memristive hardware as promising bridge or middleware between digital and (neuro)biological domains.
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Papers by Alexey Leukhin
and re-implement the noradrenaline influence in a bio-plausible
manner suitable for the modelling of emotions in a computational
system. We have upgraded our previous bio-inspired architecture
NEUCOGAR (Neuromodulating Cognitive Architecture) to capture
a key aspect of cognitive processes: novelty detection and its
evaluation. With our model, we can computationally implement
a bioinspired cognitive architecture that uses neuromodulation
as a mechanism to identify signals, as well as to evaluate them
according to their novelty, taking into account the noradrenaline
concentration dynamics. At the same time, the values thus generated
are stored in the system using the same neurotransmitters
model
mechanisms that control the emotional states of mammals could be translated and
re-implemented in a computer by means of controlling the computational performance
of a hosted computational system. In our specific implementation we represent
the simulation of the fear-like state based on the three dimensional
neuromodulatory model of affects (here the basic emotional inborn states) that we
have inherited from works of Hugo Lövheim. We have managed to simulate
1000 ms of work of the dopamine system using NEST Neural Simulation Tool and
the rat brain as the model. We also present the results of that simulation and
evaluate them to validate the overall correctness of our hypothesis.
Conference Presentations by Alexey Leukhin
Drafts by Alexey Leukhin
and re-implement the noradrenaline influence in a bio-plausible
manner suitable for the modelling of emotions in a computational
system. We have upgraded our previous bio-inspired architecture
NEUCOGAR (Neuromodulating Cognitive Architecture) to capture
a key aspect of cognitive processes: novelty detection and its
evaluation. With our model, we can computationally implement
a bioinspired cognitive architecture that uses neuromodulation
as a mechanism to identify signals, as well as to evaluate them
according to their novelty, taking into account the noradrenaline
concentration dynamics. At the same time, the values thus generated
are stored in the system using the same neurotransmitters
model
mechanisms that control the emotional states of mammals could be translated and
re-implemented in a computer by means of controlling the computational performance
of a hosted computational system. In our specific implementation we represent
the simulation of the fear-like state based on the three dimensional
neuromodulatory model of affects (here the basic emotional inborn states) that we
have inherited from works of Hugo Lövheim. We have managed to simulate
1000 ms of work of the dopamine system using NEST Neural Simulation Tool and
the rat brain as the model. We also present the results of that simulation and
evaluate them to validate the overall correctness of our hypothesis.