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This paper provides a conceptual roadmap for the use of hormonal bioinspired models in a broad range of AI, neuroengineering, or computational systems. The functional signaling nature of hormones provides an example of a reliable multidimensional information management system that can solve parallel multitasks. Two existing examples of hormonal computing bioinspired possibilities are shortly reviewed, and two novel approaches are introduced, with a special emphasis on what researchers propose as hormonal computing for neurorehabilitation in patients with complete spinal cord injuries. They extend the use of epidural electrical stimulation (EES) by applying sequential stimulations to limbs through prostheses. The prostheses include various limb models and are connected to a neurostimulation bus called the central pattern generator (CPG). The CPG bus utilizes hormonal computing principles to coordinate the stimulation of the spinal cord and muscles.
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The effect of inhibitory management is usually underestimated in artificial control systems, using biological analogy. According to our hypothesis, the muscle hypertonus could be effectively compensated via stimulation by bio-plausible patterns. We proposed an approach for the compensatory stimulation device as implementation of previously presented architecture of the neurointerface, where (1) the neuroport is implemented as a DAC and stimulator, (2) neuroterminal is used for neurosimulation of a set of oscillator motifs on one-board computer. In the set of experiments with five volunteers, we measured the efficacy of motor neuron inhibition via the antagonist muscle or nerve stimulation registering muscle force with and without antagonist stimulation. For the agonist activation, we used both voluntary activity and electrical stimulation. In the case of stimulation of both the agonist and the antagonist muscles and nerves, we experimented with delays between muscle stimulation in the range of 0-20 ms. We registered the subjective discomfort rate. We did not identify any significant difference between the antagonist muscle and nerve stimulation in both voluntary activity and electrical stimulation of cases showing agonist activity. We determined the most effective delay between the stimulation of the agonist and the antagonist muscles and nerves as 10-20 ms.
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Existing methods of neurorehabilitation include invasive or non-invasive stimulators that are usually simple digital generators with manually set parameters like pulse width, period, burst duration, and frequency of stimulation series. An obvious lack of adaptation capability of stimulators, as well as poor biocompatibility and high power consumption of prosthetic devices, highlights the need for medical usage of neuromorphic systems including memristive devices. The latter are electrical devices providing a wide range of complex synaptic functionality within a single element. In this study, we propose the memristive schematic capable of self-learning according to bio-plausible spike-timing-dependant plasticity to organize the electrical activity of the walking pattern generated by the central pattern generator.
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Familial hemiplegic migraine type 3 (FHM3) is caused by gain-of-function mutations in the SCN1A gene that encodes the α1 subunit of voltage-gated NaV1.1 sodium channels. The high level of expression of NaV1.1 channels in peripheral trigeminal neurons may lead to abnormal nociceptive signaling thus contributing to migraine pain. NaV1.1 dysfunction is relevant also for other neurological disorders, foremost epilepsy and stroke that are comorbid with migraine. Here we used computer modeling to test the functional role of FHM3-mutated NaV1.1 channels in mechanisms of trigeminal pain. The activation of Aδ-fibers was studied for two algogens, ATP and 5-HT, operating through P2X3 and 5-HT3 receptors, respectively, at trigeminal nerve terminals. In WT Aδ-fibers of meningeal afferents, NaV1.1 channels efficiently participate in spike generation induced by ATP and 5-HT supported by NaV1.6 channels. Of the various FHM3 mutations tested, the L263V missense mutation, with a longer activation state and lower activation voltage, resulted in the most pronounced spiking activity. In contrast, mutations that result in a loss of NaV1.1 function largely reduced firing of trigeminal nerve fibers. The combined activation of P2X3 and 5-HT3 receptors and branching of nerve fibers resulted in very prolonged and high-frequency spiking activity in the mutants compared to WT. We identified, in silico, key determinants of long-lasting nociceptive activity in FHM3-mutated Aδ-fibers that naturally express P2X3 and 5-HT3 receptors and suggest mutant-specific correction options. Modeled trigeminal nerve firing was significantly higher for FHM3 mutations, compared to WT, suggesting that pronounced nociceptive signaling may contribute to migraine pain.
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Extracellular ATP and serotonin (5-HT) are powerful triggers of nociceptive firing in the meninges, a process supporting headache and whose cellular mechanisms are incompletely understood. The current study aimed to develop, with the neurosimulator NEURON, a novel approach to explore in silico the molecular determinants of the long-lasting, pulsatile nature of migraine attacks. The present model included ATP and 5-HT release, ATP diffusion and hydrolysis, 5-HT uptake, differential activation of ATP P2X or 5-HT3 receptors, and receptor subtype-specific desensitization. The model also tested the role of branched meningeal fibers with multiple release sites. Spike generation and propagation were simulated using variable contribution by potassium and sodium channels in a multi-compartment fiber environment. Multiple factors appeared important to ensure prolonged nociceptive firing potentially relevant to long-lasting pain. Crucial roles were observed in: (i) co-expression of ATP P2X2 and P2X3 receptor subunits; (ii) intrinsic activation/inactivation properties of sodium Nav1.8 channels; and (iii) temporal and spatial distribution of ATP/5-HT release sites along the branches of trigeminal nerve fibers. Based on these factors we could obtain either persistent activation of nociceptive firing or its periodic bursting mimicking the pulsating nature of pain. In summary, our model proposes a novel tool for the exploration of peripheral nociception to test the contribution of clinically relevant factors to headache including migraine pain.
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Here we provide a perspective concept of neurohybrid memristive chip based on the combination of living neural networks cultivated in microfluidic/microelectrode system, metal-oxide memristive devices or arrays integrated with mixed-signal CMOS layer to control the analog memristive circuits, process the decoded information, and arrange a feedback stimulation of biological culture as parts of a bidirectional neurointerface. Our main focus is on the state-of-the-art approaches for cultivation and spatial ordering of the network of dissociated hippocampal neuron cells, fabrication of a large-scale cross-bar array of memristive devices tailored using device engineering, resistive state programming, or non-linear dynamics, as well as hardware implementation of spiking neural networks (SNNs) based on the arrays of memristive devices and integrated CMOS electronics. The concept represents an example of a brain-on-chip system belonging to a more general class of memristive neurohybrid systems for a new-generation robotics, artificial intelligence, and personalized medicine, discussed in the framework of the proposed roadmap for the next decade period.
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The slime mould Physarum polycephalum has been used in developing unconventional computing devices for in which the slime mould played a role of a sensing, actuating, and computing device. These devices treated the slime mould as an active living substrate, yet it is a self-consistent living creature which evolved over millions of years and occupied most parts of the world, but in any case, that living entity did not own true cognition, just automated biochemical mechanisms. To "rehabilitate" slime mould from the rank of a purely living electronics element to a "creature of thoughts" we are analyzing the cognitive potential of P. polycephalum. We base our theory of minimal cognition of the slime mould on a bottom-up approach, from the biological and biophysical nature of the slime mould and its regulatory systems using frameworks such as Lyon's biogenic cognition, Muller, di Primio-Lengelers modifiable pathways, Bateson's "patterns that connect" framework, Maturana's autopoietic network, or proto-consciousness and Morgan's Canon.