When networks walk a fine line: balance of excitation and inhibition in spinal motor circuits

Berg, Rune W.; Willumsen, Alex; Lindén, Henrik

doi:10.1016/j.cophys.2019.01.006

“…However, the strengths of synchronization here were relatively weak, thus supporting the view of vertebrate spinal cord interneurone networks as being sparse (Nielsen et al 2005;Radosevic et al 2019), itself consistent with the projection patterns of individual thoracic interneurons (Saywell et al 2011). The concurrent inhibition and excitation in the rat motoneurones here might be interpreted as an example of balanced excitation and inhibition, which has been proposed as a general principle in the organization of motor systems (Berg et al 2019). Our observations of peak/trough combinations could support this idea, so long as the peaks and troughs were really linked, i.e., if the same common inputs were responsible for both.…”

Section: Functional Considerationssupporting

confidence: 84%

Motoneurone synchronization for intercostal and abdominal muscles: interneurone influences in two different species

Road

¹

,

Almeida

²

,

Kirkwood

³

2020

Exp Brain Res

0

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The contribution of branched-axon monosynaptic inputs in the generation of short-term synchronization of motoneurones remains uncertain. Here, synchronization was measured for intercostal and abdominal motoneurones supplying the lower thorax and upper abdomen, mostly showing expiratory discharges. Synchronization in the anaesthetized cat, where the motoneurones receive a strong direct descending drive, is compared with that in anaesthetized or decerebrate rats, where the direct descending drive is much weaker. In the cat, some examples could be explained by branched-axon monosynaptic inputs, but many others could not, by virtue of peaks in cross-correlation histograms whose widths (relatively wide) and timing indicated common inputs with more complex linkages, e.g., disynaptic excitatory. In contrast, in the rat, correlations for pairs of internal intercostal nerves were dominated by very narrow peaks, indicative of branched-axon monosynaptic inputs. However, the presence of activity in both inspiration and expiration in many of the nerves allowed additional synchronization measurements between internal and external intercostal nerves. Time courses of synchronization for these often consisted of combinations of peaks and troughs, which have never been previously described for motoneurone synchronization and which we interpret as indicating combinations of inputs, excitation of one group of motoneurones being common with either excitation or inhibition of the other. Significant species differences in the circuits controlling the motoneurones are indicated, but in both cases, the roles of spinal interneurones are emphasised. The results demonstrate the potential of motoneurone synchronization for investigating inhibition and have important general implications for the interpretation of neural connectivity measurements by cross-correlation.

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“…The corresponding spike activity for the same data set containing the 4 inhibitory activity is shown in blue (Fig. 8c), where one inhibitory unit is concurrently active with excitation, while three are alternating, indicating the complexity of the population activity 39 . The verified synaptic connections give a connectivity probability of only 0.9% of inhibitory input, and even lower for the excitatory units (none detected).…”

Section: Resultsmentioning

confidence: 99%

Decoupling of timescales reveals sparse convergent CPG network in the adult spinal cord

Radosevic

¹

,

Willumsen

²

,

Petersen

³

et al. 2019

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During the generation of rhythmic movements, most spinal neurons receive an oscillatory synaptic drive. The neuronal architecture underlying this drive is unknown, and the corresponding network size and sparseness have not yet been addressed. If the input originates from a small central pattern generator (CPG) with dense divergent connectivity, it will induce correlated input to all receiving neurons, while sparse convergent wiring will induce a weak correlation, if any. Here, we use pairwise recordings of spinal neurons to measure synaptic correlations and thus infer the wiring architecture qualitatively. A strong correlation on a slow timescale implies functional relatedness and a common source, which will also cause correlation on fast timescale due to shared synaptic connections. However, we consistently find marginal coupling between slow and fast correlations regardless of neuronal identity. This suggests either sparse convergent connectivity or a CPG network with recurrent inhibition that actively decorrelates common input.

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“…Spinal inhibition has traditionally been associated with sculpting of the motor rhythm via reciprocal connections 2,12 or modulation of gain during motor control. 20 Nevertheless, since active decorrelation occurs in networks with a balance between excitation and inhibition, 23,24 and such concurrent E/I activity has been observed in spinal motor networks under certain circumstances, 51,52,53,39 it is quite possible that part of the low correlation could be explained by this mechanism. In our simulations of active decorrelation (Figs.…”

Section: Discussionmentioning

confidence: 99%

“…8c), where one inhibitory unit is concurrently active with excitation, while three are alternating, indicating the complexity of the population activity. 39 The verified synaptic connections give a connectivity probability of only 0.9% of inhibitory input, and even lower for the excitatory units (none detected). Similar low estimates (1%) has previously been obtained indirectly in the medulla respiratory system.…”

Section: Local Connectivity Is Sparsementioning

confidence: 98%

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Decoupling of timescales reveals sparse convergent CPG network in the adult spinal cord

Radosevic

¹

,

Willumsen

²

,

Petersen

³

et al. 2018

Preprint

Self Cite

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During the generation of rhythmic movements, most spinal neurons receive an oscillatory synaptic drive. The neuronal architecture underlying this drive is unknown, and the corresponding network size and sparseness have not yet been addressed. If the input originates from a small central pattern generator (CPG) with dense divergent connectivity, it will induce correlated input to all receiving neurons, while sparse convergent wiring will induce a weak correlation, if any. Here, we use pairwise recordings of spinal neurons to measure synaptic correlations and thus infer the wiring architecture qualitatively. A strong correlation on a slow timescale implies functional relatedness and a common source, which will also cause correlation on fast timescale due to shared synaptic connections. However, we consistently find marginal coupling between slow and fast correlations regardless of neuronal identity. This suggests either sparse convergent connectivity or a CPG network with recurrent inhibition that actively decorrelates common input.Movement is an essential part of our daily lives, and disorders of the motor system, such as spasticity, amyotrophic lateral sclerosis, and spinal cord injury are particularly debilitating for individuals. Simple rhythmic movements, such as walking and breathing, have constituted models for fundamental aspects of the motor system. In spite of extensive investigations, 1, 2, 3, 4, 5, 6 the connectivity of the network responsible for generating the motor activity remains unknown. A circuit component, known as a central pattern generator (CPG), is believed to transmit command signals to motoneurons and local premotor interneurons. 7,8,9,10 Although the size of the respiratory motor network, i.e. the preBötzinger complex, 1, 11 is well-known, the size and wiring of other CPG networks are not well understood. A feedforward organization is often proposed between groups of neurons or modules, which exhibit alternating rhythmic bursting 12 (Fig. 1a). Common drive modules are thought to be small, e.g., the preBötzinger complex has only 600 neurons, 1 which provides rhythmic drive for the rest of the network. The projection is also believed to diverge onto a much larger population of receiving neurons. 13,14,15 Thus, the receiving neurons would share the same connections via a dense divergent connectivity ( Fig. 1b). Since the transmission is communicated by action potentials, which are precise in time, a dense connectivity will manifest as a strong temporal correlation between synaptic potentials in the receiving neurons, and this correlation can be verified experimentally through pairwise recordings. If the drive network is not a small but rather a large population, however, the receiver neurons are likely to collect sparse convergent input without correlation (Fig. 1c). Hence, the assessment of correlation CPG connectivity from decoupled timescales Extensor network Flexor network extensor Common drive Common drive flexor IN IN MN MN MN e x o r e x te ns or knee MN Dense Common drive Sparse c b ...

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When networks walk a fine line: balance of excitation and inhibition in spinal motor circuits

Cited by 25 publications

References 58 publications

Motoneurone synchronization for intercostal and abdominal muscles: interneurone influences in two different species

Motoneurone synchronization for intercostal and abdominal muscles: interneurone influences in two different species

Decoupling of timescales reveals sparse convergent CPG network in the adult spinal cord

Decoupling of timescales reveals sparse convergent CPG network in the adult spinal cord

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