https://doi.org/10.1186/1471-2202-9-S1-P2

Glaze, Christopher M

Troyer, Todd W

BMC Neuroscience

Christopher M Glaze

Todd W Troyer

Springer - Publisher Connector

BioMed CentralBMC Neuroscience
ssOpen AccePoster presentation
Temporal variability in a synfire chain model of birdsong
Christopher M Glaze1 and Todd W Troyer*2
Address: 1Program in Neuroscience and Cognitive Science, University of Maryland, College Park, MD 20742, USA and 2Biology Department, 
University of Texas, San Antonio, TX, 78249, USA
Email: Todd W Troyer* - todd.troyer@utsa.edu
* Corresponding author    
Introduction
Zebra finch songs are highly stereotyped, making them
especially well suited for in depth analysis of the neural
mechanisms underlying sequential behaviors. The acous-
tic structure of song is arranged into vocal units, known as
syllables, which are ordered into highly invariant
sequences called motifs. However, recordings in high-
level premotor nuclei during singing reveal spike bursts in
individual neurons with two notable timing properties:
first, burst times have millisecond precision, and second,
the times have no obvious relationship to the timing of
syllables or intersyllable gaps [1]. This has led to the hypo-
thesis that the representation for song is clock-like, and is
generated as neural activity propagates down a chain-like
network of neurons known as a synfire chain [2,3].
Recent results from our lab supports both clock-like regu-
lation and the syllable-based view of song organization.
We used a dynamic time warping to make fine-grained
measurements of song timing in several thousand songs
from 10 adult birds [4]. We found song length variability
that is driven by tempo changes shared across syllables,
rather than an accumulation of independent variance; this
yields positive correlations among the lengths of most syl-
lables and intersyllable gaps. This global variability sug-
gests that slow, modulatory effects have a strong influence
on timing across song representations. However, we also
found that syllables tended stretch and compress with
tempo proportionally less than gaps (syllables were less
"elastic"), contradicting the hypothesis of a uniform,
clock-like representation. Finally, we found that, after sub-
tracting the effects of song tempo, the residual lengths of
the same syllable sung in different motifs ("same ID" syl-
lables) were more strongly correlated than length devia-
tions in different syllables. Further timing analysis based
on spectral features revealed shared timing deviations
between same ID elements on the sub-syllabic time scales
[5]. In syllables with strong temporal cues, we could dem-
onstrate that shared same ID timing deviations were spe-
cific to segments as short as 10 msec, i.e. a given 10 msec
segment of song is correlated with the same 10 msec seg-
ment repeated over 1000 msec later, but is uncorrelated
with the adjacent 10 msec segment of song.
In sum, our behavioral analysis has shown: (1) timing is
dominated by tempo variations shared across syllables
and gaps; (2) syllables are less elastic than gaps with
respect to changes in song tempo; and (3) shared same ID
deviations across motifs are specific to 5–10 msec seg-
ments of song. Here we demonstrate that a simple synfire
chain model, subject to slow modulatory influences that
vary from song-to-song, account for these three aspects of
song timing. In the most simplified version of the model,
we consider a single integrate-and-fire type neuron at each
link in the chain. When threshold is reached, this triggers
a stereotyped burst of spikes leading to a post-synaptic
potential (PSP) in the next neuron. With this simplifica-
tion, analytic results can be obtained on the speed of
propagation over that link as a function of the shape of
the PSP and the parameters of the model. We show that
for most PSP shapes, the following conditions lead to
results 1–3 above: (a) motif repetition by repeated propa-
gation down a single chain of neurons; (b) modulation in
neural excitability (modeled as distance to threshold) that
changes from song-to-song and are spread nearly, but not
exactly, uniformly across all neurons in the chain; (c)
from Seventeenth Annual Computational Neuroscience Meeting: CNS*2008
Portland, OR, USA. 19–24 July 2008
Published: 11 July 2008
BMC Neuroscience 2008, 9(Suppl 1):P28 doi:10.1186/1471-2202-9-S1-P28
This abstract is available from: http://www.biomedcentral.com/1471-2202/9/S1/P28
© 2008 Glaze and Troyer; licensee BioMed Central Ltd. Page 1 of 2
(page number not for citation purposes)
BMC Neuroscience 2008, 9(Suppl 1):P28 http://www.biomedcentral.com/1471-2202/9/S1/P28Publish with BioMed Central   and  every 
scientist can read your work free of charge
"BioMed Central will be the most significant development for 
disseminating the results of biomedical research in our lifetime."
Sir Paul Nurse, Cancer Research UK
Your research papers will be:
available free of charge to the entire biomedical community
peer reviewed and published immediately upon acceptance
cited in PubMed and archived on PubMed Central 
yours — you keep the copyright
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weaker synaptic connections between links in the chain
that drive timing during inter-syllable gaps. Further tim-
ing results are explored by adding more realism to the
model (realistic numbers of neurons and connections,
background noise, feedback inhibition, etc.).
References
1. Hahnloser R, Kozhevnikov A, Fee M: An ultra-sparse code under-
lies the generation of neural sequences in a songbird.  Nature
419:65-70.
2. Fee M, Kozhevnikov A, Hahnloser R: Neural mechanisms of vocal
sequence generation in the songbird.  Ann N Y Acad Sc 2004,
1016:153-70.
3. Abeles M: Corticonics: Neural circuits of the cerebral cortex.
Cambridge University Press; 1991. 
4. Glaze C, Troyer T: Temporal structure in zebra finch song:
implications for motor coding.  J Neurosci 26:991-1005.
5. Glaze C, Troyer T: Behavioral measurements of a temporally
precise motor code for birdsong.  J Neurosci 2007, 27:7631-9.Page 2 of 2
(page number not for citation purposes)


Temporal variability in a synfire chain model of birdsong

Troyer Todd W

Glaze Christopher M

Directory of Open Access Journals

Digital Repository at the University of Maryland

BioMed CentralBMC NeurosciencessOpen AccePoster presentationTemporal variability in a synfire chain model of birdsongChristopher M Glaze1 and Todd W Troyer*2Address: 1Program in Neuroscience and Cognitive Science, University of Maryland, College Park, MD 20742, USA and 2Biology Department, University of Texas, San Antonio, TX, 78249, USAEmail: Todd W Troyer* - todd.troyer@utsa.edu* Corresponding author    IntroductionZebra finch songs are highly stereotyped, making themespecially well suited for in depth analysis of the neuralmechanisms underlying sequential behaviors. The acous-tic structure of song is arranged into vocal units, known assyllables, which are ordered into highly invariantsequences called motifs. However, recordings in high-level premotor nuclei during singing reveal spike bursts inindividual neurons with two notable timing properties:first, burst times have millisecond precision, and second,the times have no obvious relationship to the timing ofsyllables or intersyllable gaps [1]. This has led to the hypo-thesis that the representation for song is clock-like, and isgenerated as neural activity propagates down a chain-likenetwork of neurons known as a synfire chain [2,3].Recent results from our lab supports both clock-like regu-lation and the syllable-based view of song organization.We used a dynamic time warping to make fine-grainedmeasurements of song timing in several thousand songsfrom 10 adult birds [4]. We found song length variabilitythat is driven by tempo changes shared across syllables,rather than an accumulation of independent variance; thisyields positive correlations among the lengths of most syl-lables and intersyllable gaps. This global variability sug-gests that slow, modulatory effects have a strong influenceon timing across song representations. However, we alsofound that syllables tended stretch and compress withtempo proportionally less than gaps (syllables were less"elastic"), contradicting the hypothesis of a uniform,clock-like representation. Finally, we found that, after sub-tracting the effects of song tempo, the residual lengths ofthe same syllable sung in different motifs ("same ID" syl-lables) were more strongly correlated than length devia-tions in different syllables. Further timing analysis basedon spectral features revealed shared timing deviationsbetween same ID elements on the sub-syllabic time scales[5]. In syllables with strong temporal cues, we could dem-onstrate that shared same ID timing deviations were spe-cific to segments as short as 10 msec, i.e. a given 10 msecsegment of song is correlated with the same 10 msec seg-ment repeated over 1000 msec later, but is uncorrelatedwith the adjacent 10 msec segment of song.In sum, our behavioral analysis has shown: (1) timing isdominated by tempo variations shared across syllablesand gaps; (2) syllables are less elastic than gaps withrespect to changes in song tempo; and (3) shared same IDdeviations across motifs are specific to 5–10 msec seg-ments of song. Here we demonstrate that a simple synfirechain model, subject to slow modulatory influences thatvary from song-to-song, account for these three aspects ofsong timing. In the most simplified version of the model,we consider a single integrate-and-fire type neuron at eachlink in the chain. When threshold is reached, this triggersa stereotyped burst of spikes leading to a post-synapticpotential (PSP) in the next neuron. With this simplifica-tion, analytic results can be obtained on the speed ofpropagation over that link as a function of the shape ofthe PSP and the parameters of the model. We show thatfor most PSP shapes, the following conditions lead toresults 1–3 above: (a) motif repetition by repeated propa-gation down a single chain of neurons; (b) modulation inneural excitability (modeled as distance to threshold) thatchanges from song-to-song and are spread nearly, but notexactly, uniformly across all neurons in the chain; (c)from Seventeenth Annual Computational Neuroscience Meeting: CNS*2008Portland, OR, USA. 19–24 July 2008Published: 11 July 2008BMC Neuroscience 2008, 9(Suppl 1):P28 doi:10.1186/1471-2202-9-S1-P28This abstract is available from: http://www.biomedcentral.com/1471-2202/9/S1/P28© 2008 Glaze and Troyer; licensee BioMed Central Ltd. Page 1 of 2(page number not for citation purposes)BMC Neuroscience 2008, 9(Suppl 1):P28 http://www.biomedcentral.com/1471-2202/9/S1/P28Publish with BioMed Central   and  every scientist can read your work free of charge"BioMed Central will be the most significant development for disseminating the results of biomedical research in our lifetime."Sir Paul Nurse, Cancer Research UKYour research papers will be:available free of charge to the entire biomedical communitypeer reviewed and published immediately upon acceptancecited in PubMed and archived on PubMed Central yours — you keep the copyrightSubmit your manuscript here:http://www.biomedcentral.com/info/publishing_adv.aspBioMedcentralweaker synaptic connections between links in the chainthat drive timing during inter-syllable gaps. Further tim-ing results are explored by adding more realism to themodel (realistic numbers of neurons and connections,background noise, feedback inhibition, etc.).References1. Hahnloser R, Kozhevnikov A, Fee M: An ultra-sparse code under-lies the generation of neural sequences in a songbird.  Nature419:65-70.2. Fee M, Kozhevnikov A, Hahnloser R: Neural mechanisms of vocalsequence generation in the songbird.  Ann N Y Acad Sc 2004,1016:153-70.3. Abeles M: Corticonics: Neural circuits of the cerebral cortex.Cambridge University Press; 1991. 4. Glaze C, Troyer T: Temporal structure in zebra finch song:implications for motor coding.  J Neurosci 26:991-1005.5. Glaze C, Troyer T: Behavioral measurements of a temporallyprecise motor code for birdsong.  J Neurosci 2007, 27:7631-9.Page 2 of 2(page number not for citation purposes)

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