Lab publishes manuscript on novel spike sporting algorithm

In collaboration with the group of Tim Lei in the Department of Electrical Engineering at UC Denver, the group co-published a manuscript describing a novel spike sorting algorithm (Enhanced Growing Neural Gas, EGNG), which is computationally much less demanding than other existing algorithms. The lower demands on computing power will help with the development of small implantable stand-alone devices such as neural prosthesis.

Z. Mohammadi, J.M. Kincaid, S.H. Pun, A. Klug, C. Liu C, and T.C. Lei:
Computationally inexpensive enhanced growing neural gas algorithm for real-time adaptive neural spike clustering. Journal of Neural Engineering May 9. doi: 10.1088/1741-2552/ab208c, 2019.

https://iopscience.iop.org/article/10.1088/1741-2552/ab208c/pdf

Research grant to study central hearing loss is funded

A new multi-PI grant (multi-PI R01) was just funded by the NIH. This grant will help us study alterations in the sound localization pathway that occur during aging and which affect an individual’s ability to function in environments where many sound sources are active at the same time. The study is a combined human subjects - animal model study and the other two principal investigators are Melinda Anderson and Daniel Tollin, both from the University of Colorado School of Medicine.

Lab publishes manuscript on hearing impairments in Fragile x

In collaboration with the research groups of Dan Tollin, Molly Huntsman, and Nathaniel Greene at the University of Colorado Medical Campus, the group published a new manuscript describing binaural and hearing impairments in a Fragile X mouse model on Bioarchives, describing alterations in sound localization performance in Fragile X mice.

E.A. McCullagh, S. Poleg, N.T. Greene, M.M. Huntsman, D.J. Tollin, and A. Klug:
Auditory binaural and spatial hearing impairments in a Fragile X Syndrome mouse model.
BioRxiv, 648717, 2019.

https://www.biorxiv.org/content/biorxiv/early/2019/05/24/648717.full.pdf

Lab co-authors 3 papers presented at IEEE Conference in Neural Engineering

In collaboration with the group of Tim Lei at UC Denver’s Department of Electrical Engineering and the University of Macau, the lab co-authors three papers presented at the 2019 IEEE?EMBS Conference on Neural Engineering from 20-23 March 2019 in San Francisco. All three papers were peer-reviewed and accepted for presentation at the conference.

Z. Mohammadi, A. Klug, C. Liu, and T.C. Lei:
Data reduction for real-time enhanced growing neural gas spike sorting with multiple recording channels.
2019 9th International IEEE/EMBS Conference on Neural Engineering (NER), 1084-1087, 2019.

P.T. Ly, A. Lucas, C. Liu, A. Klug, and T.C. Lei:
A stereotaxic platform for small animals based on 3D computer vision and robotics.
2019 9th International IEEE/EMBS Conference on Neural Engineering (NER), 851-854, 2019.

B.Z. Li, S.H. Pun, W. Feng, M.I. Vai, A. Klug, and T.C. Lei:
A Spiking Neural Network Model Mimicking the Olfactory Cortex for Handwritten Digit Recognition.
2019 9th International IEEE/EMBS Conference on Neural Engineering (NER), 1167-1170, 2019.

Lab publishes manuscript on gerbil genome and transcriptome

In collaboration with BGI-Shenzhen, the Chinese Academy of Agricultural Sciences, and Ludwig Maximilians University Munich, the lab published a manuscript on the de novo assembly of the genome and transcriptome of the Mongolian gerbil on Bioarchives. Gerbils are one of the most important animal models for auditory research because their hearing spectrum, especially low frequency hearing spectrum, matches the spectrum of humans much closer than rats or mice. However, in the past, a major disadvantage of gerbils has been that their genome had not been sequenced, limiting our ability to use genetic tools. The main goal of the sequencing project is to overcome this disadvantage.

De novo assembly of the Mongolian gerbil genome and transcriptome:
Shifeng Cheng, Yuan Fu, Yaolei Zhang, Wenfei Xian, Hongli Wang, Benedikt Grothe, Xin Lu, Xun Xu, Achim Klug, Elizabeth A McCullagh. doi: https://doi.org/10.1101/522516

https://www.biorxiv.org/content/biorxiv/early/2019/01/24/522516.full.pdf