Special Issue information:

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The brain's adaptability has been assumed to be governed solely by the principle of neural plasticity via selectionism during development and later life through a Hebbian-style learning paradigm. However, the unknown player in the brain’s adaptability has been its precognitive consciousness. The lability of the informational structures composed of evanescent physical feelings enables the brain to unconsciously feel and adapt to the environment. This novel aspect of the brain’s plasticity makes it possible for new AI to be developed.

Artificial general intelligence (AGI) represents generalized human cognitive abilities achieved by Turing computations in weak AI technology. Strong Artificial Intelligence (SAI) represents mental abilities, conscious processes, and subjective functioning achieved by nonTuring computations in yet unspecified technology. The difference between AGI and SAI is that the latter can understand uncertainty to predict an unexpected event, giving it enormous altitude for mind-like action needed for various applications.

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This call for papers seeks new ways of fusing deep learning systems with attributes found in the multiscalar brain’s adaptability to forge ever-closer sentient  AI  systems.

Submission Date:  15 October 2023
Lead Editor:

Dr. Shantipriya Parida

Senior Scientist

Silo AI,  Helsinki, Finland

shantipriya.parida@silo.ai

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Observing a single ion channel to the live measuring of ion channel releases, binding marker molecules have dominated neuroscience with fixation and permeabilization. With the advent of various designs of neural probes and non-bonded physical markers, a time has arrived when state-of-the-art imaging techniques are being developed globally that deliver a live hologram of a single cell with minimal toxicity. This special issue is aimed to document technologies like scanning ion-conductance microscopy, STORM, scanning dielectric conductance microscopy, and other novel techniques for imaging dynamic cellular processes, We want to document realistic results closer to in vivo scenarios, for 2D and 3D cultured cellular studies of neurons and neural networks. We welcome submissions for all electromagnetic resonance-based wireless characterizations of neural networks covering all neural functions.

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Lead Editor: Dr. Anirban Bandyopadhyay

                      International Institute for materials Science, Japan