This one's for you enjoy:
It is often that Iquote Stephen Foskett probably to the annoyance of many who see his commentthat “Brainchip taking Ai everywhere” as far too over the top and a ludicrousattempt at generating hype around Brainchip and AKIDA technology.
However the moreyou do your own research you will find that increasingly every rock you turnover has some new application for Ai in particular the brain inspired Spikingconvolutional neural network developed by Brainchip and called ALIDAtechnology. Just a short while ago I was looking for some updated information on tinnitus as a family member suffers from this condition and when extreme has difficulty with sleeping. For those who do not know tinnitus a serious condition world wide and in its extreme form is responsible for a significant number of suicides each year.
Well to my surpriseI found that just in January, 2021 a paper was published which has had successin using spiking neural networks to identify what range of noise can in anyindividual case operate to effectively cancel out the tinnitus sound inaffected patients. It has been known that the sound of running water will in some people cancel out the sound of their tinnitus. The spiking neural network being used is brain inspired. Interesting term so looking at the References I found that Simon Thorpe and company were cited. Looking at the authors I noticed the name Nikola K.Kasabov and Auckland University.
Well those in theknow and there are many of you out there know that one of the researchersincluding Mr. Kasabov worked at Auckland University and were involved in the BrainchipAERO e-nose project.
So not a lot of speculatingneeded here I would have thought but I have reproduced below thefollowing: Mayo Clinic for World wide figures on tinnitus, Extract from the Tinnitus paper and an extract confirming the link between Kasabov and Brainchip previously.
So just to annoy I sayagain Brainchip taking Ai everywhere and now to the huge addressable market forthe treatment of tinnitus world wide.
My opinion onlyDYOR.
Tinnitus is when youexperience ringing or other noises in one or both of your ears. The noise youhear when you have tinnitus isn't caused by an external sound,and other people usually can't hear it. Tinnitus is a common problem.It affects about 15% to 20% of people, and is especially common inolder adults.4 Feb 2021
Tinnitus -Symptoms and causes - Mayo Clinic
Prediction of Acoustic Residual Inhibition of TinnitusUsing a Brain-Inspired Spiking Neural Network Model
Philip J. Sanders 1,2,3 , Zohreh G. Doborjeh 1,2,3 , Maryam G. Doborjeh 4 , Nikola K. Kasabov 5,6,7 and Grant D. Searchfield 1,2,3,* ,†
Citation: Sanders, P.J.; Doborjeh, Z.G.; Doborjeh, M.G.; Kasabov, N.K.; Searchfield, G.D. Prediction of Acoustic Residual Inhibition of Tinnitus Using a Brain-Inspired Spiking Neural Network Model. Brain Sci. 2021, 11, 52. https:// doi.org/10.3390/brainsci11010052Received: 3 December 2020 Accepted: 2 January 2021
Published: 5 January 2021 Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. Copyright: © 2021 by the authors. LicenseeMDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). 1 Section of Audiology,
TheUniversity of Auckland, Auckland 1023, New Zealand;
[email protected] (P.J.S.);
[email protected] (Z.G.D.) 2 Eisdell Moore Centre, Auckland 1023, New Zealand 3 Centre for Brain Research, The University of Auckland, Auckland1023, New Zealand 4 Information Technology and Software Engineering Department, Auckland University of Technology, Auckland 1010, New Zealand;
[email protected] 5 School of Engineering, Computer and Mathematical Sciences, Auckland Universityof Technology, Auckland 1010, New Zealand;
[email protected] 6 Intelligent Systems Research Centre, Ulster University, Derry/Londonderry BT48 7JL, UK 7 Auckland Bioengineering Institute, The University of Auckland, Auckland 1010, New Zealand * Correspondence:
[email protected] † Brain Research New Zealand—Rangahau Roro Aotearoa, New Zealand.
Abstract: Auditory Residual Inhibition (ARI) is a temporary suppression of tinnitus that occurs in some people following the presentation of masking sounds. Differences in neural response to ARI stimuli may enable classification of tinnitus and a tailored approach to intervention in the future. In an exploratory study, we investigated the use of a brain-inspired artificial neural network to examine the effects of ARI on electroencephalographic function, as well as the predictive ability of the model. Ten tinnitus patients underwent two auditory stimulation conditions (constant and amplitude modulated broadband noise) at two time points and were then characterised as responders or non-responders, based on whether they experienced ARI or not. Using a spiking neural network model, we evaluated concurrent neural patterns generated across space and time from features of electroencephalographic data, capturing the neural dynamic changes before and after stimulation. Results indicated that the model may be used to predict the effect of auditory stimulation on tinnitus on an individual basis. This approach may aid in the development of predictive models for treatment selection. Keywords: residual inhibition; amplitude modulated; tinnitus; spiking neural network; prediction; individualised treatment
Reference:
43. Masquelier, T.; Guyonneau, R.; Thorpe, S.J. Competitive STDP-Based Spike Pattern Learning. Neural Comput. 2009, 21, 1259–1276
2020 Application of a brain-inspired spiking neural network for odor data classification
Anup Vanarse Edith Cowan University, [email protected] Josafath Israel Espinosa-Ramos Adam Osseiran Edith Cowan University, [email protected] Alexander Rassau Edith Cowan University, [email protected] Nikola Kasabov
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