Local Axonal Conduction Shapes the Spatiotemporal Properties of Neural Sequences

Abstract

Highlights d Simultaneous recording of sequentially active premotor neurons during singing d Models suggest that network delays impact song-related population activity d Ultraslow axonal conduction within HVC generates substantial network delays d Local axonal delays shape spatial patterns of activity within a neural circuit

Addition of new neurons and the emergence of a local neural circuit for precise timing

“…There is strong evidence that the sequential bursting of HVC RA neurons is generated within HVC [9,[18][19][20][21]. Moreover, HVC RA neurons most likely form a feedforward synaptic chain network (Fig 1) [9,21,22].…”

“…There is strong evidence that the sequential bursting of HVC RA neurons is generated within HVC [ 9 , 18 – 21 ]. Moreover, HVC RA neurons most likely form a feedforward synaptic chain network ( Fig 1 ) [ 9 , 21 , 22 ]. The feedforward network supports propagation of bursting activity of HVC RA neurons, and each HVC RA neuron bursts once at a precise time, as observed experimentally [ 8 , 9 ].…”

“…The synaptic chain network grows by gradual recruitment of neurons into the network. However, our model incorporates more biologically realistic features, including explicit incorporation of HVC INT neurons rather than simplifying the inhibitory actions as idealized global inhibition between HVC RA neurons; implementation of axonal delays between HVC RA neurons, which has shown to be substantial and is important for determining the connectivity structure of the synaptic chain network [ 21 ]; and spatial structure of HVC RA connectivity, which has been recently measured in the zebra finch [ 20 ]. Most importantly, the maturation dynamics of HVC RA neurons is modeled.…”

“…We also show that our model creates the observed spatial distribution profile for the connections between HVC RA neurons [ 20 ]. With a wide delay distribution between these connections, as observed by experiments [ 21 ], our model produces a robust polychronous chain network with continuous and precise time representation, which is recently proposed to be the structure of the synaptic chain network in HVC [ 21 ]. The previous models of chain growth neglected synaptic delays and produced synfire chains [ 28 , 29 ], in which a postsynaptic neuron receives synchronous inputs, and the presynaptic neurons that provide these inputs fire synchronously as well [ 37 ].…”

“…In a polychronous chain network, the inputs also arrive synchronously at the postsynaptic neuron. However, the presynaptic neurons fire asynchronously due to the distributed axonal delays [ 21 , 38 ]. Our model additionally predicts that HVC RA neurons in the growing chain network receive less forward inhibition from the HVC RA neurons that drive them, which was not predicted by the previous models due to the omission of HVC INT neurons [ 28 , 29 ].…”