PMID- 24319408
OWN - NLM
STAT- PubMed-not-MEDLINE
DCOM- 20131209
LR  - 20211021
IS  - 1662-4548 (Print)
IS  - 1662-453X (Electronic)
IS  - 1662-453X (Linking)
VI  - 7
DP  - 2013
TI  - Real-time biomimetic Central Pattern Generators in an FPGA for hybrid 
      experiments.
PG  - 215
LID - 10.3389/fnins.2013.00215 [doi]
LID - 215
AB  - This investigation of the leech heartbeat neural network system led to the 
      development of a low resources, real-time, biomimetic digital hardware for use in 
      hybrid experiments. The leech heartbeat neural network is one of the simplest 
      central pattern generators (CPG). In biology, CPG provide the rhythmic bursts of 
      spikes that form the basis for all muscle contraction orders (heartbeat) and 
      locomotion (walking, running, etc.). The leech neural network system was 
      previously investigated and this CPG formalized in the Hodgkin-Huxley neural 
      model (HH), the most complex devised to date. However, the resources required for 
      a neural model are proportional to its complexity. In response to this issue, 
      this article describes a biomimetic implementation of a network of 240 CPGs in an 
      FPGA (Field Programmable Gate Array), using a simple model (Izhikevich) and 
      proposes a new synapse model: activity-dependent depression synapse. The network 
      implementation architecture operates on a single computation core. This digital 
      system works in real-time, requires few resources, and has the same bursting 
      activity behavior as the complex model. The implementation of this CPG was 
      initially validated by comparing it with a simulation of the complex model. Its 
      activity was then matched with pharmacological data from the rat spinal cord 
      activity. This digital system opens the way for future hybrid experiments and 
      represents an important step toward hybridization of biological tissue and 
      artificial neural networks. This CPG network is also likely to be useful for 
      mimicking the locomotion activity of various animals and developing hybrid 
      experiments for neuroprosthesis development.
FAU - Ambroise, Matthieu
AU  - Ambroise M
AD  - Laboratoire IMS, UMR Centre National de la Recherche Scientifique, University of 
      Bordeaux Talence, France.
FAU - Levi, Timothee
AU  - Levi T
FAU - Joucla, Sebastien
AU  - Joucla S
FAU - Yvert, Blaise
AU  - Yvert B
FAU - Saighi, Sylvain
AU  - Saighi S
LA  - eng
PT  - Journal Article
DEP - 20131121
PL  - Switzerland
TA  - Front Neurosci
JT  - Frontiers in neuroscience
JID - 101478481
PMC - PMC3836270
OTO - NOTNLM
OT  - FPGA
OT  - biomimetic
OT  - central pattern generator
OT  - digital hardware
OT  - neuron model
OT  - spiking neural networks
EDAT- 2013/12/10 06:00
MHDA- 2013/12/10 06:01
PMCR- 2013/01/01
CRDT- 2013/12/10 06:00
PHST- 2013/08/06 00:00 [received]
PHST- 2013/10/29 00:00 [accepted]
PHST- 2013/12/10 06:00 [entrez]
PHST- 2013/12/10 06:00 [pubmed]
PHST- 2013/12/10 06:01 [medline]
PHST- 2013/01/01 00:00 [pmc-release]
AID - 10.3389/fnins.2013.00215 [doi]
PST - epublish
SO  - Front Neurosci. 2013 Nov 21;7:215. doi: 10.3389/fnins.2013.00215. eCollection 
      2013.