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Multifactorial motor behavior assessment for real-time evaluation of emerging therapeutics to treat neurologic impairments

  • Riazul Islam
    ,
  • ,
  • Ben Felmlee
    ,
  • Tori Riccelli
    ,
  • Jodi Silvernail
    ,
  • Suelen Lucio Boschen
*Corresponding author for this work
Research Output:
Contribution to journal
Article
Research
Peer-review

Open access

Publication Information

Output type

Research Output:
Contribution to journal
Article
Research
Peer-review

Original language

English

Article number

16503

Journal (Volume, Issue Number)

Scientific Reports (Volume 9, Issue 1)

Publication milestones

  • Published - 01/12/2019

Publication status

Published - 01/12/2019

Publication IDs

  • Scopus: 85074835185
  • PubMed: 31712725

Abstract

Integrating multiple assessment parameters of motor behavior is critical for understanding neural activity dynamics during motor control in both intact and dysfunctional nervous systems. Here, we described a novel approach (termed Multifactorial Behavioral Assessment (MfBA)) to integrate, in real-time, electrophysiological and biomechanical properties of rodent spinal sensorimotor network activity with behavioral aspects of motor task performance. Specifically, the MfBA simultaneously records limb kinematics, multi-directional forces and electrophysiological metrics, such as high-fidelity chronic intramuscular electromyography synchronized in time to spinal stimulation in order to characterize spinal cord functional motor evoked potentials (fMEPs). Additionally, we designed the MfBA to incorporate a body weight support system to allow bipedal and quadrupedal stepping on a treadmill and in an open field environment to assess function in rodent models of neurologic disorders that impact motor activity. This novel approach was validated using, a neurologically intact cohort, a cohort with unilateral Parkinsonian motor deficits due to midbrain lesioning, and a cohort with complete hind limb paralysis due to T8 spinal cord transection. In the SCI cohort, lumbosacral epidural electrical stimulation (EES) was applied, with and without administration of the serotonergic agonist Quipazine, to enable hind limb motor functions following paralysis. The results presented herein demonstrate the MfBA is capable of integrating multiple metrics of motor activity in order to characterize relationships between EES inputs that modulate mono- and polysynaptic outputs from spinal circuitry which in turn, can be used to elucidate underlying electrophysiologic mechanisms of motor behavior. These results also demonstrate that proposed MfBA is an effective tool to integrate biomechanical and electrophysiology metrics, synchronized to therapeutic inputs such as EES or pharmacology, during body weight supported treadmill or open field motor activities, to target a high range of variations in motor behavior as a result of neurological deficit at the different levels of CNS.

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