You are here

SYSTEM FOR AUTOMATED NONINVASIVE MONITORING OF MOUSE SLEEP AND BEHAVIOR

Award Information
Agency: Department of Health and Human Services
Branch: National Institutes of Health
Contract: 2R44NS083218-03
Agency Tracking Number: R44NS083218
Amount: $994,664.00
Phase: Phase II
Program: SBIR
Solicitation Topic Code: 105
Solicitation Number: PA14-071
Timeline
Solicitation Year: 2014
Award Year: 2015
Award Start Date (Proposal Award Date): 2015-08-01
Award End Date (Contract End Date): 2018-04-30
Small Business Information
501 RIDGE RD
Lexington, KY 40503-1229
United States
DUNS: 964938455
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 MICHAEL LHAMON
 (859) 271-7521
 michael.lhamon@sigsoln.com
Business Contact
 KEVIN DONOHUE
Phone: (859) 257-4004
Email: kevin.donohue@sigsoln.com
Research Institution
N/A
Abstract

DESCRIPTION provided by applicant The basic functions of sleep are still unknown Abnormal sleep patterns can manifest as a variety of disorders sleep apnea parasomnias REM rapid eye movement sleep behavioral disorder RBD narcolepsy many of which are influenced by heredity There is an increasing focus on characterizing mouse behaviors for genetic and drug studies However discovering the genes responsible for sleep and related disorders requires time consuming large scale behavioral screening of phenotypes to correlate observed traits with genetics Behavioral monitoring of mice is usually limited to actigraphic measurements such as video tracking wheel running and photoelectric beam breaking Although many of these methods are noninvasive and have potential for high throughput HT application they monitor mainly locomotor activity without providing information about sleep wake state and sleep architecture which are important for investigating sleep disorders While EEG can be used to accurately determine sleep wake state it is invasive and resource intensive surgery recovery etc which limits its application in large scale genetic studies wih rodents Signal Solutions LLC has developed a sensor cage environment for noninvasive behavioral monitoring that is being used by prominent research groups to identify genes responsible for different traits related to sleep and circadian rhythms The specific aims of this work are to further improve the capabilities of the piezo system to noninvasively Discriminate sleep wake state sleep wake REM NREM and behavior within wake e g quiet vs active high activity feeding grooming to a level comparable to EEG EMG by classifying piezo signal features with added low cost video features Incorporate real time feedback stimulation for behavior modification Integrate electronics and with new multimodal sensing into a compact system for testing in research laboratories Develop low cost device for automatic animal welfare monitoring The envisioned end product is a sensor cage and software interface for HT monitoring of sleep wake state and behavior in small animals to identify genetic factors responsible for sleep circadian disorders as well as behavioral effects of pharmacological manipulation sensory stimulation or neural injury e g traumatic brain injury epilepsy This system will be particularly advantageous for prescreening potentially interesting phenotypes and reserving invasive EEG analysis for further confirmation Medical targets of interest are sleep circadian disorders sleep apnea obesity diabetes REM NREM sleep deprivation and stress among others Potential clients include academic research labs as well as industrial labs interested in behavioral monitoring on a large scale e g drug screening PUBLIC HEALTH RELEVANCE Discovery of genes that play a role in sleep and circadian rhythm disorders requires extensive screening of behavior usually in mice preferably with invasive and resource intensive brain signal EEG recordings to score sleep stage REM NREM and wake behavior The goal of this research is to develop and validate a methodology for using a noninvasive pressure sensitive piezoelectric andquot piezoandquot sensor platform to distinguish different stages of sleep and behavior without the need for EEG making large scale behavioral screening feasible and limit the need for EEG verification to only the most interesting phenotypes thus identified

* Information listed above is at the time of submission. *

US Flag An Official Website of the United States Government