Central Pattern Generators


Essential behaviours such as walking or breathing are rhythmic, that is, characterised by repetitive activation of muscles in a specific temporal sequence. A basic version of the underlying neural activity is generated in the central nervous system by networks called central pattern generators (CPGs). CPGs can produce these patterns even in the absence of inputs that carry specific timing information. The core rhythmic activity can be based on intrinsic oscillatory properties of pacemaker neurons or emerge from the synaptic connectivity of nonoscillatory neurons. In both cases, other neurons are recruited into this rhythmic activity to generate a whole pattern. Neuronal and synaptic properties underlying the precise temporal patterning of sequential bursting activity are shaped by neuromodulators to generate different versions of motor patterns. The circuitry controlling rhythmic behaviours of a whole animal is organised in modules that control different body parts and can be coordinated in different ways to generate different behaviours.

Key Concepts

  • Essentially all rhythmic motor behaviours are based on CPGs.
  • CPGs can produce patterned activity in the absence of patterned input.
  • Rhythm generation can be based on intrinsically rhythmic neurons or network interactions.
  • The speed, strength and specific temporal sequence in which CPG neurons fire arise from complex interactions of synaptic and intrinsic neuronal properties governed by diverse types of ion channels.
  • CPG activity is modified by sensory feedback to adapt the motor pattern to changing environmental parameters.
  • CPGs can be activated and reshaped by neuromodulators that adjust neuronal excitability by modifying or suppressing existing ionic currents or adding new currents and changing the properties of synapses.
  • Neuromodulation provides flexibility of motor pattern generation to adjust output to changing behavioural demands.
  • The central networks controlling rhythmic behaviours are inherently modular and allow different coordination of body parts for different behaviours or different versions of the same behaviour.

Keywords: fictive motor pattern; pacemaker; half‐centre oscillator; neuromodulation; unit oscillator

Figure 1. The basic version of rhythmic neural activity underlying repetitive motor behaviours is generated in the central nervous system by central pattern generators (CPGs). (a) Originally, rhythmic motor patterns were thought to arise from chains of reflexes (left panels). In this model, contraction of a muscle, for example, one that controls flexion of a leg joint, leads to proprioceptor signalling that activates the antagonistic extensor muscle through reflex pathways (red). The resulting extension then reflexively activates the flexor again and so forth. It is now clear that such motor patterns are actually based on CPG networks (right panels) that can produce rhythmic activity in the absence of timing information from sensory feedback, for example, through mutually inhibitory connections between neurons controlling different agonists. SN: sensory neuron; MN: motor neuron; eIN: excitatory interneuron, iIN: inhibitory interneuron. (b) Fictive behaviours, that is, activity patterns recorded in the isolated central nervous system that resemble the motor output of the intact animal, are the ultimate proof of the existence of a CPG. A preparation of the rodent brain stem and spinal cord will spontaneously express rhythmic motor activity in electrophysiological recordings of the phrenic nerve, which would lead to inspiratory movements of the diaphragm in the intact animal. When properly pharmacologically activated, this preparation will also show walking‐like motor activity in recordings of ventral roots in the lumbar spinal cord.
Figure 2. Mechanisms underlying rhythm generation. Rhythmic neuron activity in the intact network (left) and after synaptic isolation (right). (a) Rhythm generation can be based on endogenous oscillatory properties of a neuron (red). This neuron continues to burst in synaptic isolation, while an electrically coupled member of the ‘pacemaker group’ (pink) and a follower neuron (green) fall silent or are tonically active. (b) In half‐centre oscillations or other network‐based rhythm generation, bursting activity is usually not based on intrinsic oscillatory properties of neurons but emerges purely from synaptic network interactions. In synaptic isolation, all network neurons therefore fall silent or are tonically active. (c) In some cases, stable and regular rhythm generation may strongly depend on network interactions such as half‐centre oscillations despite the presence of intrinsic bursting properties. In such cases, synaptically isolated neurons may burst endogenously, but at slow frequencies and with irregular periods.
Figure 3. Common membrane properties of CPG neurons. (a) Endogenous oscillations (pacemaker properties). Current inputs can reset rhythmic activity, either by advancing or delaying the next burst. (b) Spike frequency adaptation is the waning of spike frequency during constant depolarizing input. (c) Postinhibitory rebound is the ability to produce activity as a result of prior inhibition. It is often accompanied by a sag potential, that is, an escape from ongoing inhibition. The delay to the onset of the rebound burst can be increased by fast potassium currents such as IA. (d) Plateau potentials are relatively long‐lasting firing responses to sufficiently large but short depolarisations. They can either self‐terminate or end in response to brief hyperpolarizing input.
Figure 4. Neuromodulation of CPGs. (a) Sources of neuromodulation include modulatory projection neurons that release neuromodulators (colours) in a paracrine manner into the local brain area containing the CPG. Projection neurons often co‐release two or more transmitters/modulators. Neuromodulators can also be released by CPG neurons (intrinsic modulation) or reach the CPG as neurohormones (arrows) via the circulatory system or cerebrospinal fluid. (b) Divergent neuromodulatory actions at the cellular level and the resulting changes in network activity, as found for biogenic amine neuromodulators in the pyloric network of the crustacean stomatogastric nervous system. All neurons express receptors (GPCRs) to both modulators (1 and 2, corresponding colours). However, each modulator targets multiple ion channels in a cell type‐specific manner. The effects on neuronal excitability are therefore different across different neurons and different modulators (small network diagrams, colours correspond to target ion channels) and result in different network activity patterns. (c) Cellular convergence and network divergence, as found for a number of neuropeptide modulators in the pyloric network. Each modulator (3, 4 and 5, corresponding colours) targets the same ion channel (red). However, not every receptor is expressed in all neurons. Therefore, each modulator affects a different subset of neurons, resulting in different network activity patterns.
Figure 5. Modular organisation of motor patterns. (a) Unit pattern generators controlling different body parts have to be coordinated to produce meaningful behaviour. Coordination can be achieved through local connectivity or descending commands in the central nervous system or through sensory feedback. Sensory feedback from one body part can directly affect a unit pattern generator controlling a different one or rely on mechanical coupling between two parts. (b) In walking animals, each leg joint has to be controlled by coordinating flexion and extension movements. All joints within one leg have to be coordinated to achieve stepping movements in the proper sequence for stance and swing. All legs have to be coordinated to produce meaningful gaits.


Bartos M, Manor Y, Nadim F, et al. (1999) Coordination of fast and slow rhythmic neuronal circuits. Journal of Neuroscience 19 (15): 6650–6660.

Borgmann A and Buschges A (2015) Insect motor control: methodological advances, descending control and inter‐leg coordination on the move. Current Opinion in Neurobiology 33C: 8–15.

Bose A, Manor Y and Nadim F (2004) The activity phase of postsynaptic neurons in a simplified rhythmic network. Journal of Computational Neuroscience 17 (2): 245–261.

Brown TG (1911) The intrinsic factors in the act of progression in the mammal. Proceedings of the Royal Society B: Biological Sciences 84 (572): 308–319.

Bucher D, Taylor AL and Marder E (2006) Central pattern generating neurons simultaneously express fast and slow rhythmic activities in the stomatogastric ganglion. Journal of Neurophysiology 95 (6): 3617–3632.

Bucher D and Marder E (2013) SnapShot: Neuromodulation. Cell 155 (2): 482–482 e481.

Buschges A, Akay T, Gabriel JP, et al. (2008) Organizing network action for locomotion: insights from studying insect walking. Brain Research Reviews 57 (1): 162–171.

Cymbalyuk GS, Gaudry Q, Masino MA, et al. (2002) Bursting in leech heart interneurons: cell‐autonomous and network‐based mechanisms. Journal of Neuroscience 22 (24): 10580–10592.

Deliagina TG, Zelenin PV, Fagerstedt P, et al. (2000) Activity of reticulospinal neurons during locomotion in the freely behaving lamprey. Journal of Neurophysiology 83 (2): 853–863.

Diaz‐Rios M and Miller MW (2006) Target‐specific regulation of synaptic efficacy in the feeding central pattern generator of Aplysia: potential substrates for behavioral plasticity? Biological Bulletin 210 (3): 215–229.

Dickinson PS (1995) Interactions among neural networks for behavior. Current Opinion in Neurobiology 5 (6): 792–798.

Dickinson PS (2006) Neuromodulation of central pattern generators in invertebrates and vertebrates. Current Opinion in Neurobiology 16 (6): 604–614.

Feldman JL, Del Negro CA and Gray PA (2013) Understanding the rhythm of breathing: so near, yet so far. Annual Review of Physiology 75: 423–452.

Gariepy JF, Missaghi K and Dubuc R (2010) The interactions between locomotion and respiration. Progress in Brain Research 187: 173–188.

Grillner S (2003) The motor infrastructure: from ion channels to neuronal networks. Nature Reviews. Neuroscience 4 (7): 573–586.

Grillner S, Hellgren J, Menard A, et al. (2005) Mechanisms for selection of basic motor programs—roles for the striatum and pallidum. Trends in Neurosciences 28 (7): 364–370.

Grillner S (2006) Biological pattern generation: the cellular and computational logic of networks in motion. Neuron 52 (5): 751–766.

Grillner S and Manira AE (2015) The intrinsic operation of the networks that make us locomote. Current Opinion in Neurobiology 31: 244–249.

Harris‐Warrick RM, Coniglio LM, Levini RM, et al. (1995) Dopamine modulation of two subthreshold currents produces phase shifts in activity of an identified motoneuron. Journal of Neurophysiology 74 (4): 1404–1420.

Harris‐Warrick RM (2010) General principles of rhythmogenesis in central pattern generator networks. Progress in Brain Research 187: 213–222.

Harris‐Warrick RM (2011) Neuromodulation and flexibility in Central Pattern Generator networks. Current Opinion in Neurobiology 21 (5): 685–692.

Izhikevich EM, Desai NS, Walcott EC, et al. (2003) Bursts as a unit of neural information: selective communication via resonance. Trends in Neurosciences 26 (3): 161–167.

Jones SR, Mulloney B, Kaper TJ, et al. (2003) Coordination of cellular pattern‐generating circuits that control limb movements: the sources of stable differences in intersegmental phases. Journal of Neuroscience 23 (8): 3457–3468.

Jordan LM, Liu J, Hedlund PB, et al. (2008) Descending command systems for the initiation of locomotion in mammals. Brain Research Reviews 57 (1): 183–191.

Katz PS and Frost WN (1996) Intrinsic neuromodulation: altering neuronal circuits from within. Trends in Neurosciences 19 (2): 54–61.

Kiehn O (2011) Development and functional organization of spinal locomotor circuits. Current Opinion in Neurobiology 21 (1): 100–109.

Kristan WB Jr, Calabrese RL and Friesen WO (2005) Neuronal control of leech behavior. Progress in Neurobiology 76 (5): 279–327.

Kupfermann I and Weiss KR (2001) Motor program selection in simple model systems. Current Opinion in Neurobiology 11 (6): 673–677.

Li WC, Sautois B, Roberts A, et al. (2007) Reconfiguration of a vertebrate motor network: specific neuron recruitment and context‐dependent synaptic plasticity. Journal of Neuroscience 27 (45): 12267–12276.

Marder E and Calabrese RL (1996) Principles of rhythmic motor pattern generation. Physiological Reviews 76 (3): 687–717.

Marder E and Bucher D (2001) Central pattern generators and the control of rhythmic movements. Current Biology 11 (23): R986–996.

Marder E, Bucher D, Schulz DJ, et al. (2005) Invertebrate central pattern generation moves along. Current Biology 15 (17): R685–699.

Marder E and Goaillard JM (2006) Variability, compensation and homeostasis in neuron and network function. Nature Reviews. Neuroscience 7 (7): 563–574.

Marder E and Bucher D (2007) Understanding circuit dynamics using the stomatogastric nervous system of lobsters and crabs. Annual Review of Physiology 69: 291–316.

Marder E (2012) Neuromodulation of neuronal circuits: back to the future. Neuron 76 (1): 1–11.

Nadim F and Manor Y (2000) The role of short‐term synaptic dynamics in motor control. Current Opinion in Neurobiology 10 (6): 683–690.

Nadim F, Zhao S, Zhou L, et al. (2011) Inhibitory feedback promotes stability in an oscillatory network. Journal of Neural Engineering 8 (6): 065001.

Nadim F and Bucher D (2014) Neuromodulation of neurons and synapses. Current Opinion in Neurobiology 29C: 48–56.

Nusbaum MP and Blitz DM (2012) Neuropeptide modulation of microcircuits. Current Opinion in Neurobiology 22 (4): 592–601.

Pearson KG (2004) Generating the walking gait: role of sensory feedback. Progress in Brain Research 143: 123–129.

Roeder KD, Tozian L and Weiant EA (1960) Endogenous nerve activity and behaviour in the mantis and cockroach. Journal of Insect Physiology 4 (1): 45–48.

Rubin JE, Hayes JA, Mendenhall JL, et al. (2009) Calcium‐activated nonspecific cation current and synaptic depression promote network‐dependent burst oscillations. Proceedings of the National Academy of Sciences of the United States of America 106 (8): 2939–2944.

Selverston AI (2010) Invertebrate central pattern generator circuits. Philosophical Transactions of the Royal Society, B: Biological Sciences 365 (1551): 2329–2345.

Sherrington CS (1910) Flexion‐reflex of the limb, crossed extension‐reflex, and reflex stepping and standing. Journal of Physiology 40 (1–2): 28–121.

Stein W, Smarandache CR, Nickmann M, et al. (2006) Functional consequences of activity‐dependent synaptic enhancement at a crustacean neuromuscular junction. Journal of Experimental Biology 209 (Pt 7): 1285–1300.

Tseng HA, Martinez D and Nadim F (2014) The frequency preference of neurons and synapses in a recurrent oscillatory network. Journal of Neuroscience 34 (38): 12933–12945.

Wilson DM (1961) The central nervous control of flight in a locust. Journal of Experimental Biology 38: 471–490.

Wood DE, Manor Y, Nadim F, et al. (2004) Intercircuit control via rhythmic regulation of projection neuron activity. Journal of Neuroscience 24 (34): 7455–7463.

Wyart C, Del Bene F, Warp E, et al. (2009) Optogenetic dissection of a behavioural module in the vertebrate spinal cord. Nature 461 (7262): 407–410.

Yu X, Nguyen B and Friesen WO (1999) Sensory feedback can coordinate the swimming activity of the leech. Journal of Neuroscience 19 (11): 4634–4643.

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Bucher, Dirk, Haspel, Gal, Golowasch, Jorge, and Nadim, Farzan(Dec 2015) Central Pattern Generators. In: eLS. John Wiley & Sons Ltd, Chichester. http://www.els.net [doi: 10.1002/9780470015902.a0000032.pub2]