Collaborative Research: Development of song culture in zebra finches - vocal and sensory
changes over generations
PIs:
City College of New York: Ofer Tchernichovski & Lucas Parra
Weill Medical College of Cornell University: Henning Voss
Baylor College of Medicine: Santosh Helekar
Project Summary
Culture consists of traits inherited epigenetically through social learning. Oscine songbirds exhibit song
learning and provide biologically tractable models of culture: members of a species show individual
variation in song and geographically separated groups have local song dialects. How does song culture
develop over multiple generations? In zebra finches, birds kept isolated during the sensitive period for
song learning develop an abnormal isolate song. Interestingly, in an isolated colony founded by an
isolate, wild-type songs emerge within 3-4 generations, due to biased imitation that gradually
transforms the isolate song into a normal, species-typical song. In the proposed research we would like
to study both vocal and sensory changes that take place during the cumulative cultural transition. We
will combine continuous analysis of vocal changes with non-invasive fMRI brain imaging to investigate
how auditory selectivity to songs develops in males and in females, and how it drives cultural changes.
The non-invasive fMRI will allow repeated measurements of auditory selectivity side by side with
measurements of vocal changes during individual development and over generations as culture
emerges de novo in controlled environments. Of particular interest is the role of imitation biases in
males, and that of female auditory/perceptual selectivity in driving cultural changes. We will confirm that
the BOLD response changes measured above are due to changes in neuronal activity and not primarily
due to hemodynamic and vascular factors by measuring the local cerebral blood flow with arterial spin
labeling, and separately recording local field potential responses in parallel experiments.
Our research could potentially bridge between studies of vocal and sensory changes (which are often
studied in reduced preparations) and field ethology studies of cultural changes in vocal communication.
This project will contribute to the training of postdoctoral scholars and graduate students. It will provide
scientific education and research training to minority undergraduate students at CCNY. We will also
involve a few Bronx high school students in the research. We will disseminate our findings through
electronic and print media. .
1
Objectives
This proposal is based on two recent findings: the first is that the transition from an isolate song into a
wild type song can be studied in a controlled laboratory environment [1], where vocal changes leading
to wild-type culture can be measured and analyzed continuously in different social conditions. The
second finding is that non-invasive fMRI imaging can capture auditory selectivity to song stimuli in
awake mildly sedated birds [2-4]. In males, such selectivity depends on early exposure to songs. In
females, however, auditory selectivity to songs develops even without exposure to songs, suggesting
that females might have an important role in guiding the development of song culture. To examine the
role of imitation biases and song-selectivity in the emergence of song culture we address the following
objectives:
Objective 1: We will examine how song culture emerges during one generation by performing
continuous measurements of social interactions and of vocal changes in controlled
environments:
A
B
♀
♀
In an arena configuration of one tutor (center) and 10 pupils we observed a wide variety of imitation,
with one or two pupils imitating perfectly, one or two imitating nothing, and the rest of the bird with
partial imitation (Tchernichovski et al 2001).





The separation between the birds will allow us to record relatively clean song development from
each bird using directional microphones (so that only one pupil can sing in the microphone
direction)
The separation between the birds will allow us to use automatic video tracking of each bird,
continuously over development. This will allow us to quantify how much each pupil communicate
with the tutor and with other pupils. In configuration B, we replace two pupils by adult females and
visually separate some pupils from the females (black bars). This will allow us to examine the effect
of females presence on tutor behavior and on the neighboring pupils
We will perform these experiments both with wild-type tutor and with isolate tutor – to obtain the first
generation of progress toward wt songs (which is the strongest effect).
During song development we will perform fMRI in three age groups 40, 60, 90, and will compare the
progression of imitation and social interactions in each bird with fMRI results.
Experiments will be repeated to test for possible (unlikely) effect of the fMRI on song development –
it is unlikely since social and live training will usually override that of passive playbacks. However,
we will test the birds with song syllables – not entire songs, to further reduce the chance of effect.
2
Objectives 2: We will examine the developmental time course of auditory selectivity to song in
males and in females, testing for experience-dependent effects.
We will investigate whether there are consistent differences in males as opposed to females in
developmental time course of auditory response maturation between isolates and birds raised in a
semi-natural colony. This is a necessary first step in studying the role of sensory processes in the
evolution of a song dialect. We will record song development males and test for coupling between song
development and changes in auditory response selectivity in those males, and in their female audience.
In previous fMRI studies with 3T scanner we found that blood oxygenation level-dependent (BOLD)
responses to vocal stimuli show stimulus-dependent selectivity in adult colony males but not in isolate
males. Here, using a stronger magnet (a new 7T scanner) we hope to obtain higher definition brain
images and measure both general song selectivity (songs vs. calls) and fine-grained song selectivity
(comparing wild type songs, isolate songs and familiar colony songs). Under Objective 1 We will ask
the following questions:
i) When during song development do general and fine-grained song selectivities emerge in
males? Time course of song selectivity development will be compared across colony raised
males and isolates. Does individual variability in the progression of song imitation (similarity
to tutor’s songs) correlate with the development of song selectivity, as assessed by fMRI?
Are there consistent differences in BOLD responses of juveniles and adult males across wildtype and isolate songs? How responses to the bird’s own song develop in isolates versus
colony raised males?
ii) When during development do general and fine-grained song selectivities emerge, and how
do they progress in females? Does the timing and magnitude of selectivity depend on the
environment (colony vs. isolation)?
iii) Assess the possible effect of repeated measurements of BOLD responses to vocal sounds
on vocal development and on auditory selectivity. In case of adverse effects we will adjust
the research plan.
iv) We will confirm that the BOLD response changes measured above are due to changes in neuronal
activity and not primarily due to hemodynamic and vascular factors by measuring the local cerebral
blood flow with arterial spin labeling (ASL), and separately recording local field potential (LFP)
responses in parallel experiments.
Objective 3: We propose to test the following two hypotheses: a) Progressive maturation of
auditory response selectivity across generations in males anticipates the de novo evolution of
song culture, and b) The innately mature and normal response selectivity in females facilitates
its maturation in their male companions through social interaction.
Under this objective we will study how male and female song-selectivity changes during
development across generations, over the course of evolution of a new song culture. Using similar
methods as in Objective 1 we will examine the development of general and fine-grained song selectivity
across generations in two environments. In the first “deprived environment”, a juvenile bird will imitate
the song on an isolate tutor one-to-one, continuing recursively (using the pupil of one generation as the
tutor of the next generation) across 3-5 generations until wild-type song emerges. In the second “social
environment” same tutoring will take place, starting from a pair of male and female isolates, continuing
recursively with 4 birds in each chamber (male + female tutors and male + female pupils). In these birds
we will ask the following questions:
i) When during development in each generation and across generations general and fine-grained
song selectivities emerge, and how do they progress in males in relation to the evolution of a
new song culture? Does the presence of female change the rate of vocal and sensory
changes?
3
ii)
Does the development of female song selectivity affect the imitation of song by males across
generations?
For this study the birds will be raised, isolated and tutored at CCNY in the Tchernichovski laboratory.
fMRI scanning will be conducted at WMC under the direction of Henning Voss. LFP recordings will be
carried out in the Tchernichovski laboratory in collaboration with Santosh Helekar. fMRI analysis will be
carried out jointly by Henning Voss at WMC and Santosh Helekar at BCM. Lucas Parra at CCNY will
develop statistical methods and models to perform combined analysis of multi-generational LFP, fMRI
and song data.
Background and Significance
Many species of oscine songbirds show elaborate vocal communication with remarkable ability of
juvenile birds to develop their song repertoire by imitating songs of adult individuals. Except for tropical
species, females usually do not sing, but song preferences of females can affect male singing behavior
indirectly by sexual selection, such that males with songs that females prefer will reproduce more,
followed by epigenetic transmission of their songs to their offspring. In addition, females can affect song
structure directly by behaviorally guiding song development of juvenile males (West & King, Nelson &
Marler). At the population level, the cultural transmission of songs gives rise to local song dialects.
Those dialects can remain stable for many years, and song-dialects are expressed not only at the vocal
level but also at the perceptual level, as females prefer local dialect songs upon other dialects ().
Although our knowledge about song culture stems from field studies, understanding the role of song
imitation and female preferences in the development of song culture requires research in controlled
environments that allow us to examine how song culture come about in an “island colony” established
by an isolate founder. Songbirds raised in isolation (isolates) develop abnormal songs that differ from
wild-type song of the species (Fig 1 a-b). In a recent study (Feher et al 2009) we found that species
specific (wild-type) song culture can emerge de novo within 3-4 generations: we raised a juvenile zebra
finch with an isolate tutor in a sound proof chamber. When adult, we used that pupil as the tutor of
another pupil, continuing recursively across tutoring-generations. The outcome was a gradual
modification, across generations, of the isolate song toward a wild-type song structure. The pupils did
not invent new syllables. Instead, they modified the abnormal isolate syllables and made them more
species typical in each generation (Fig. 2). The approximation of wild-type song in such impoverished
environment indicates that even in an isolate bird who sings abnormal song there is some hidden
“knowledge” of the wild-type song structure, but it takes a few recursions to emerge. In that sense, the
wild-type song culture is a multi-generational phenotype – it is encoded in the founder, but takes a few
recursions to emerge. However, the outcome is slightly different when a similar experiment is done in a
seminatural colony. Here, a gradual transition toward a wild-type song across generations occurred as
well, but birds show some “creativity”, with new syllable types invented and then incorporated into the
songs.
Figure 1c-e presents a cartoon illustration of how feedback might affect song development at
different levels: In an isolate we have only a single level of feedback from the bird’s own song. In a oneto-one tutoring environment we have an additional input from the tutor, and in a colony setting we also
have feedback from females and from siblings. Taken together, song development is shaped by input
and feedback at different levels, but also by imitation is biased. Here, we propose to study the
establishment of song culture by combining two approaches: First, until now we only looked at the
outcome of song development in each generation. We now add to this a dynamic investigation of vocal
changes during development and across generations, as song culture is established. Second, we are
going to combine the vocal measurements with brain imaging that would allow us to assess – both in
males and in females – how auditory response patterns to songs are shaped by experience across
generations. Although the second aim is complicated, and somewhat risky, we show preliminary results
(see XX) that establish the feasibility of using fMRI imaging to gain important knowledge about how
experience can shape specific responses to songs. In this section we present a short review about the
current knowledge about the development of auditory responses to songs, with emphasis on sensorymotor feedback during development:
4
d
c
isolate
e
One-to-one
tutoring
♀♀
♀
Colony
Figure 1: isolate songs versus wild type songs. c-e in isolates we have only one level of
input feedbac from bird’s own song. The tutor (d) add an additional layer of input and
females (c) can add a third one…
What can be gained by combined sensory and vocal measurements? At the level of the individual
animal, we expect that singing skills and sensory tuning should develop concurrently, so that as
auditory responses (and perception) become sensitive to subtle vocal transitions, a better singing
performance can be achieved, which in turn further . But of course, sensory-motor feedback cannot
explain the development of song culture, which requires no external input: Figure 2 presents the
convergence from isolate songs into wild-type songs across a few generations
5
isolate
F1
F2
At the population level, we expect to see similar effect at longer time scales. Since zebra finches are
Figure 2: Biased imitation across generations giving rise to wild type song…
6
Song development and song culture: Songbirds are used to study vocal learning, vocal
perception and production. There are interesting parallels between auditory and vocal pathways in the
songbird and human brain [5], and between song development and speech development [6]. Among
songbirds used in neurobiological research, zebra finches have been the most extensively studied
species. In striking analogy with human speech acquisition, zebra finches require an extended critical
period of tutor-dependent learning for the acquisition of song [7, 8]. Each adult male zebra finch
produces a learned song that is stereotyped but spectrally and temporally distinct [9]. The learning of
song involves tutoring by adult conspecific birds, and requires auditory feedback [10]. As in human
speech, two stages of vocal development have been recognized, namely early sensory and late
sensorimotor phase (reviewed in [11]). It is hypothesized that an auditory template of the tutor song is
memorized by a young bird during the sensory learning phase [12]. This stored template is then used
by the pupil to compare it with the sensory representation of its own evolving vocal output until a closely
matched stable copy of the tutor song is acquired [13]. The exact nature and location of the auditory
template of the tutor song are unclear. Recent experiments have suggested that it might reside in the
secondary auditory area NCM [14], but we do not know much about it, nor when and how it becomes
accessible to the premotor song system.
Development of auditory responses in the forebrain: Auditory responses to song have been
recorded in the primary auditory area in the caudal telencephalic region termed as field L, in the higher
auditory areas NCM and CM, as well as in forebrain nuclei related to the production and acquisition of
song: HVC, LMAN, area X of the lobus parolfactorius, and nucleus interfacialis (Nif) [15-22].
The song system nuclei show song-specific auditory responses with remarkably similar properties
and selectivity, with greater responsiveness to BOS compared to conspecific song and to conspecific
compared to heterospecific song [23]. Most neurons within HVC show a global synchronous response
to BOS [24]. The temporal pattern of song appears to be encoded by combination-sensitive neurons
that are activated by temporal sequences of multiple syllables, and structures within the song control
pathway appear to be tuned to specific patterns within songs [18-20]. Song-selectivity of auditory
neurons in the song nuclei emerges gradually and in parallel with song motor learning [22, 25-28]. The
responsiveness to the bird's own song (BOS) is stronger than for the tutor’s song even during early
song development [29-31], even when BOS is an abnormal song produced by denervation of the syrinx
[29], suggesting that song selectivity might be induced by auditory feedback during vocalization.
Selectivity for conspecific song is also seen in the NCM [32]. Song learning experience has a profound
effect on the responsiveness of NCM neurons to song stimuli [33]. Similarities in response selectivity
seen in the song nuclei also extend to neurons in NCM and CM [34, 35], suggesting that essentially a
similar type of perceptually relevant information regarding song is accessed by higher auditory areas,
premotor song control nuclei and song learning nuclei.
How then do these areas make use of this information in a differential manner to perform their
distinct functions? One possibility is that these structures might be differentially responsive during
different phases of song development. To find out if this is true we need to compare the responsiveness
of these areas simultaneously and at multiple times during development using a global analytical
approach.
fMRI-BOLD responses to song stimuli: Recently, fMRI based on the blood-oxygenation-leveldependent (BOLD) effect has been developed for songbirds [2, 36]. fMRI as a non-invasive procedure
allows for longitudinal within-subject studies, and it does not interfere with subsequent extra- or
intracellular recordings. In humans, fMRI is presently the most important neuroimaging technique. The
BOLD effect is indirectly related to neuronal activity because increased local energy demand increases
capillary blood flow and reduces deoxyhemoglobin levels [37]. Observations in monkeys show that
BOLD amplitude increases approximately linearly with the LFP and to a lesser extent with single and
multiple unit activity. LFPs have been shown to be better correlated than neuronal spiking activity with
BOLD effect. Therefore, LFP recordings can complement fMRI by revealing the neural activations
underlying the BOLD response, in addition to elucidating millisecond scale temporal information. fMRI
images in turn provide high resolution 3-dimensional spatial information.
Preliminary Studies
Studies Relevant to Both Objectives of the Project
7
Cultural evolution of song in zebra finches
Ofer, please add stuff here
fMRI studies in awake birds
Our group performed a series of fMRI and event related potential recording experiments in zebra
finches over the past three years. We overcame technical hurdles of fMRI in small animals on 3.0 T
MRI scanners, involving custom-made radiofrequency (RF) coils [38, 39] and techniques to improve the
image quality for echo-planar imaging [40-42]. This knowledge can be transferred readily to the
proposed experiments on a 7.0 T animal MRI scanner. A paper describing the first set of results of
these experiments has been published in PNAS [2] and two additional papers are under review [43, 44].
Our group works cohesively. We presented our results in several conferences including ISMRM (2006
and 2007), SFN (2006 - 2008), Cold Spring Harbor Workshop (2007), and the IBRO World Congress,
Melbourne (2007).
Figure 2: Differential topography of activation of auditory areas show stimulus specific
responses. (A) Averaged functional activations depending on stimulus (rows) and sagittal slice
position (columns). The slice numbers as corresponding to Figure 1A are given at the bottom. (B)
Comparison of averaged activation for different stimuli. Positive changes from stimulus 1 to stimulus 2
are shown in red, negative changes in blue. For example, the stimulation with BOS yields more
posterior (red area, arrow) and less anterior (blue) activation than the stimulation with TONE. (C)
Differences in BOLD response between primary and secondary auditory areas for stimulation with
TUT. The clusters presumably correspond to activations in field L (green) and other areas including
NCM (red).
right
left
3
5
We detected highly significant BOLD responses
to songs in auditory brain areas (Figure 1), shown
by, the maximum intensity projection of significantly
active voxels for the whole brain and by the BOLD
response time series. Figure 2A shows parasagittal
slices with averaged activation clusters. Slices 4 and
5 are from the medial part, and slices 2 and 7 are
most lateral. As shown, activation is mostly medial,
centered around auditory nuclei field L and NCM.
7
2
X med
X lat
1 0
1 1
1 2
1 3
CM
L
9
8
NCM
Stim
750 ms
Figure 3: Local field potential responses to
auditory stimuli. Bilateral local field potentials in
an adult male to a conspecific song motif. Traces
8
shown are stimulus onset time-locked averages
of 256 traces. X med and X lat represent area X
medial and lateral portions, respectively.
Stimulus-dependent differentiation of sensory BOLD response topography in auditory areas
We found strong differences in the distribution of the voxels activated in response to different stimuli.
Interestingly, the largest contiguous area of activation was seen with tutor song (TUT) stimulus and the
smallest with the unfamiliar conspecific song (CON) stimulus. Figure 2B shows differential profiles for
all possible pairs of stimuli in the two medial slices. TUT showed activation that is much more
pronounced throughout the activated region when compared with TONE, and greater amount of
activation in the central and rostral field L portions when compared with BOS. An example for clustering
in the mediocaudal region is given in Figure 2C (See Voss et al., 2007 [2] for details).
Discrimination between stimuli in the forebrain as a whole
In normal colony birds, the response has been quantified by measuring the time-averaged BOLD
A
B
C
Figure 4: Social interactions and song tutoring can shape stimulus-specific patterns of BOLD
activation in the forebrain. A) Sound playbacks trigger strong, and non-selective BOLD responses in
isolate birds. We see activation in both posterior (NCM, field L and CM cluster) and anterior (probably
area X) of the forebrain. In birds who learned songs during development (box-trained and live tutored)
we see only posterior forebrain activation, with strong differences (discrimination) across stimuli (n=6
birds per group). (B) Quantification of anterior forebrain (C) Quantification of the posterior auditory
cluster. Note that isolates show similar responses across sounds, whereas trained birds show strong
NCM response to songs, and weak response to other sounds.
response amplitude [2]. The medial parts of the brain show differential selectivity with respect to the
stimulus. Stimulus discrimination was strong in the medial part of the brain (a single factor ANOVA test
across the stimuli, p=0.0006) but non significant (p=0.5) in the lateral slices. Responses to TONE
stimulation were significantly smaller than responses to CON or BOS stimulation.
Neural responses in auditory areas and the anterior forebrain region are similar to BOLD responses
We have conducted in vivo chronic LFP recordings in NCM, field L, CM and area X in 4 adult birds
(Figure 3), showing faithfully reflected stimulus features in LFP responses. Similar observations have
been made by others with regard to NCM multiunit responses in acute preparations [14, 45, 46]. The
responses suggest right-sided lateralization and are much smaller in area X than in the posterior
auditory structures, consistent with the fMRI findings below.
Testing for possible effect of Diazepam on bioelectrical responses
9
To test for possible effect of mild sedation with Diazepam, which is necessary for the fMRI studies,
we compared auditory evoked surface and LFP responses with and without Diazepam. There was no
significant difference in the amplitude or time course, and only slight alterations in shape, between
responses before and after sedation (see supplementary figures in Voss et al. [2]).
Song tutoring over development can shape the selectivity of auditory responses
To study the impact of tutoring on the neural representation of auditory stimuli we have compared
BOLD responses in box-trained, live-tutored and untutored adults. The untutored birds were
acoustically isolated from other birds and each other during the sensitive period for song learning. The
other birds were trained either by playbacks (in isolation) or by live tutors in a colony. We found
remarkably widespread and indiscriminate activation of the forebrain in the untutored birds in response
to songs, calls and pure tone (Figure 4), with greater spread of activity in auditory areas; but in addition,
the song learning area was also activated. In
Right
Left
contrast, activity in box-tutored birds was
significantly restricted and highly selective, with
little activation of the anterior forebrain (AFP).
NCM field
Box trained birds showed only a single cluster,
AEP surface
centered at field L and NCM. In live-tutored birds
responses were even more restricted and no
consistent activation of AFP could be detected.
Stim marker
Both area and magnitude of AFP BOLD
750 ms
response were significantly higher in isolates Figure 5: Comparison of NCM LFP and surface
compared to trained birds. In isolates, AFP AEP. Traces shown are representative averages of
responded to a variety of sounds (Figure 4A and 256 trials from a >150 day-old adult zebra finch. The
B). We find it remarkable that several minutes of stimulus marker is a square pulse indicating the
song playbacks over the entire song duration of the conspecific song motif stimulus used.
development were sufficient to nearly eliminate
AFP activation. Since AFP has a central role in song imitation, our results could be interpreted as
“gating by learning”; namely, that the decreased sensitivity of AFP to sounds might be the neuronal
mechanism of closing the sensitive period for song learning.
BOLD responses do not mirror spiking activity [47] but correlate well with evoked potentials and with
LFPs, reflecting the overall input and postsynaptic potentials across thousands of neurons.
Simultaneous measurements of surface auditory evoked potentials (AEP) and LFP in NCM (Figure 5)
verified that a significant portion of the AEP stems from an area that shows BOLD activation. Taken
together, the above findings suggest that developmental tutoring might cause selective redistribution,
restriction, and fine tuning of auditory representation in the forebrain.
Tracking the development of auditory responses
We have performed chronic LFP recordings in 9 young males during song development (age 58 to
86 days). The electrodes have remained in place in a usable condition for more than 6 weeks. We
tested if AFP activation occurs in tutored juvenile birds. Figure 6 shows that on an average there is
significant activation of the most lateral part of area X in 39 – 56 day-old male zebra finches trained with
a live tutor. LFP recordings show larger area X responses in 58 – 60 day old juvenile birds trained with
live tutors compared to live-tutored adults (101 – 1095 day old, Figure 7). The mean power of the area
X responses is 3 - 4 fold greater in juveniles (n = 6) compared to adults (n = 7, p < 0.023, left; p <
0.034, right, Student’s unpaired t test) (Figure 8A). The mean power of NCM responses on the other
hand is 6 – 7 folds greater in adults than in juveniles (Figure 8B). Recordings in juveniles conducted at
5 successive time points during development show a marked decrease in the mean power of area X
responses after the first time point (Figure 8C; one way ANOVA p < 0.002, F = 13.17, left; p < 0.01, F =
8.09, right). In contrast, the mean power of the NCM response shows a (not significant) trend towards
an increase at the last two time points (Figure 8D). Thus it appears that males undergo a distinct
pattern of maturational changes in their auditory responses to song during development.
In the first objective of the present project we will be tracking these maturational changes in greater
detail in with fMRI and LFP recordings, and correlating them with the trajectory of development of the
song output of each bird. In the second objective we will be determining the progression, if any, of these
sensory changes in anticipation of the progressive approximation towards normal pattern of song over 3
– 5 generations.
10
Research Design and Methods
11
WT
WT
ISO
ISO
12
Call2
Call1
Con2
Con1
Tone
The facilities and expertise needed for the experiments proposed here are distributed across our three
laboratories at Baylor College of Medicine (BCM), Weill Medical College of Cornell University (WMC)
and City College of New York (CCNY). For this project zebra finches are being raised at CCNY, and
cared for according to IACUC committee animal protocol review guidelines and recommendations.
Procedures and Timeline: Based on
the variability observed in our preliminary
Anterior forebrain
Auditory area
activation
activation
results we set the sample size to 10 birds
per subgroup. We will test 14 experimental
subgroups: 10 in Objective 1 and 4 in
Objective 2, and therefore we anticipate
that a total of 120 birds will be used in this
project. The Tchernichovski Lab will
dedicate 10 training boxes to this project,
adding up to about 40 developmental
experiments per year.
All fMRI scanning will be done at WMC
by Dr. Voss or his postdoctoral associate
with help from Dr. Helekar or a graduate
forebrain
student in Dr. Tchernichovski’s laboratory.
Birds will be transported to WMC from
CCNY individually in a sound-proof box by
eye
the experimenter.
lateral
medial
Figure 6: AFP activation in juvenile tutored
birds. Averaged functional BOLD activation maps
(color, p < 0.005) in 5 juvenile birds (day 39-56 post
hatch). Stimuli: 2 different conspecific songs, 2
different calls, and a control tone.
Left
Right
Adult
4
Left
Juvenile
Right
5
X
X
2
NCM
NCM
Stim
Stim
750 ms
750 ms
Figure 7: LFP traces in adult and juvenile male birds. Conspecific song motif responses in a livetutored 3 year-old adult and a 59 day-old juvenile male in training with a live tutor. Birds were recorded
in the awake state. Recordings are bilateral from X and NCM. Traces are stimulus time-locked
averages of >250 stimulus trials. Note the larger amplitude of the area X responses in the juvenile bird.
13
Transportation will be done by taxicab, as in our pilot project over the last three years. fMRI and LFP
recordings will be done in different sets of birds under similar conditions. LFP recordings will be done at
A
Juveniles
Adults
C
NCM
800
Mean Power ( m V 2)
700
600
500
NCM (right)
400
NCM (left)
300
200
100
da
ys
99
/1
05
da
ys
86
da
ys
76
da
ys
69
59
da
ys
0
Age (days)
B
Juveniles
Adults
D
Area X
800
Mean Power (mV2)
700
600
Area X (right)
500
Area X (left)
400
300
200
100
da
ys
da
ys
99
/1
05
86
da
ys
76
da
ys
69
59
da
ys
0
Age (days)
Figure 8: Comparison of responses in juveniles and adults, and maturation of area X and
NCM responses. A. Mean power (± SEM) of area X responses in 58 – 60 day old juveniles and 101
– 1095 day-old adults. The responses were evoked by a conspecific song motif stimulus as in Figure
10. B. Mean power (± SEM) of the NCM response under the same stimulus conditions as in A. C.
Mean power (± SEM) of area X responses at five different developmental time points. The responses
were evoked by a conspecific song motif stimulus as in Figure 11. D. Mean power (± SEM) of the
NCM response at the same time points and under the same stimulus conditions as in C above.
CCNY by a graduate student in collaboration with Dr. Helekar. Drs. Voss and Helekar will analyze the
fMRI data at WMC and BCM, respectively. Dr. Parra at CCNY will develop statistical methods and
models to analyze multi-generational song, fMRI and LFP data.
Under ideal conditions we would perform both fMRI and LFP in the same location. However, this is
not possible due to the distribution of equipment, skills and expertise. The principal investigators of this
project have been collaborating for 3 years now, including co-mentoring of a PhD student and
publishing together. The PIs will continue their joint leadership of this project, sharing equal
responsibilities for carrying out the work. Each PI will be administratively, technically, and scientifically
responsible for the conduct of his own research and that of the project personnel in his laboratory. The
PI’s will make efficient use of their primary expertise, namely: Dr. Tchernichovski will supervise raising
and tutoring of birds for the de novo establishment of a song culture, and continuous sound recordings
and real-time analysis during song development. fMRI imaging will be conducted by Dr. Voss at WMC.
The LFP recordings and fMRI data analysis will be conducted in collaboration with Dr. Helekar. Dr.
14
Parra will be in charge of developing statistical methods. The project will be carried out over 4 years.
The first objective will be completed by the end of year 2. Objective 2 will be addressed over the last
three years of the project.
The data generated by this project will be presented scientific meetings, and published in peerreviewed journals. Procedures, software and materials developed will be freely shared with all
interested researchers, students and teachers for research and education.
OBJECTIVE 1
We will test the hypothesis that maturation of auditory responses to vocal stimuli during
development is experience-dependent in male zebra finches but not in females.
We will perform high resolution brain fMRI on sedated zebra finches at several time points during
song development in these two groups of birds. We will test for changes in the spatial extent and
configuration of the blood oxygenation level-dependent (BOLD) response in all song and auditory nuclei
of the forebrain. We will attempt to judge the influence of developmental vascular changes on the BOLD
response by measuring the local cerebral blood flow with arterial spin labeling (ASL). To measure
changes in the time course of activation we will perform local field potential recordings (LFP) from the
same nuclei at corresponding developmental time points in separate sets of birds belong the two
groups. Based on our preliminary studies we have already identified the auditory areas caudal medial
nidopallium (NCM), field L and caudal mesopallium (CM) and the song learning nucleus area X as
potential sites of recording. We will use a common set of conspecific as well as heterospecific vocal
stimuli to elicit auditory responses in all birds studied with fMRI and LFPs. We will develop common
standardized measures for quantitative comparison of BOLD and LFP responses at different time
points, such as the variability of the amplitude, time course and spatial spread across stimuli and across
birds.
We will investigate whether there are consistent differences in males as opposed to females in
developmental time course of auditory response maturation between isolates and birds raised in a
semi-natural colony. This is a necessary first step in studying the role of sensory processes in the
evolution of a song dialect. This investigation will be performed in a single generation under two
environments: birds raised in a semi-natural colony, as opposed to birds raised singly in sound isolation
chambers. In previous fMRI studies with 3T scanner we found that blood oxygenation level-dependent
(BOLD) responses to vocal stimuli show stimulus-dependent selectivity in adult colony males but not in
isolate males. The pattern of response selectivity in females was similar to that in colony males. Here,
using a 7T scanner, we hope to obtain higher definition brain images to study to what extent
developmental changes in sensory responses to vocalizations contribute to the de novo evolution of a
song dialect. We will examine general song selectivity (songs vs. calls) and fine-grained song selectivity
(comparing wild type songs, isolate songs and familiar colony songs). Under Objective 1 We will ask
the following questions:
i) When during song development do general and fine-grained song selectivities emerge, and how
do they progress in males? Does individual variability in the progression of song imitation correlate with
the development of song preferences?
ii) When during development do general and fine-grained song selectivities emerge, and how do
they progress in females? Does the timing and magnitude of selectivity depend on the environment
(colony vs. isolation)?
fMRI procedure: We will develop and use RF coils and methods designed to perform fMRI scanning
in juvenile birds. We will perform high resolution brain fMRI on trained and isolated zebra finches during
development, and test for changes of the spatial extent and spatial configuration of the blood
oxygenation level-dependent (BOLD) response. All MRI scanning will be done in awake birds mildly
sedated with Diazepam (60 µl, 1.66 mg/ml in normal saline, i.m.), and restrained in soft plastic tubes.
The stimulation paradigm used in all experiments is given under Procedures. Wild type songs, isolate
songs, familiar colony songs and calls will be used as stimuli………………………….
LFP procedure: We will perform LFP recordings with chronically implanted electrodes following
similar stimulation procedure and at similar time points as in the scanning experiments described
above. Electrodes will be implanted 72 hours before the first presentation of the stimulus and recording
of its response. These experiments will also tell us whether the changes in BOLD response do indeed
mirror changes in neural activity, rather than other parameters such as tissue perfusion, blood flow and
15
oxygenation of the hemoglobin, which are also likely to change during development. Measuring the
BOLD response and the LFP response under similar conditions, and quantifying the correlation
between the two, enables us to assess whether both change in similar ways with development. If nonneuronal parameters are responsible for the changes we see over development then we would not see
corresponding correlated changes in LFP. Moreover, if the non-neuronal parameters change simply
during the course of brain development then we would see these changes in both tutored birds and
isolates. Alternatively, neural changes will be dependent on auditory experience, and would be reflected
in differences between tutored birds and isolates. Bilateral LFP responses will be recorded in the
auditory areas NCM, field L and CM, and the song learning nucleus area X. As shown in the preliminary
studies, these areas show strong BOLD responses to auditory stimuli. fMRI would also reveal any
activity that might be evident in limbic or other structures at any stage during development. If there is
consistent activation of the song nucleus HVC in the awake mildly sedated state, then we will also
perform LFP recordings from this nucleus. We will use a high resolution anatomical MRI scan and the
new MRI atlas [48] to pin-point the location of the tip of the LFP electrode on the zebra finch stereotaxic
atlas. The anatomical location of the tip will be kept constant across birds. The chronic LFP recordings
will be done, as described below, under fully alert unrestrained conditions as well as after mild sedation
and restraint, as in the fMRI scanning procedure.
Testing for developmental vascular changes: To separate neurophysiological changes as visible in
the BOLD response from vascular changes, we will perform arterial spin labeling (ASL) imaging at all
time points and in all groups of birds to measure regional cerebral blood flow (rCBF). An ASL pulse
sequence is now provided within our agreement with Bruker Biospin. From forepaw-stimulation
experiments in rats it is known that the BOLD response is tightly correlated with rCBF, but the activated
BOLD areas may be larger than areas with increased rCBF [49]. Whereas we cannot measure the
cerebral metabolic rate of oxygen directly here (which would be the ultimate goal), we will relate the
changes in relative BOLD response intensity during ontogeny to the accompanying changes in rCBF.
Accuracy of song imitation: To assess the progress and success of vocal imitation, the vocalizations
of experimental birds will be recorded at the same time points at which neural measurements are
performed. The similarity between the bird’s song at each of these points and the tutor’s song (in the
tutored groups) will be measured using Sound Analysis, as described elsewhere [50]. Imitation success
will be correlated with the neural findings.
Data analysis and anticipated results
Cultural Evolution
Ofer, please add here
fMRI and LFP Changes
We will measure the mean peak amplitude and mean area of significant BOLD activation. We will
also compare the location(s) of the centroid(s) of maximum activation and the spatial configuration of
activation, and perform cluster analyses on the BOLD response time traces to analyze sub-structures of
activated areas. For LFP responses we will measure the root mean square (RMS) amplitude and
duration of the responses elicited at each location or area. The shape of the responses will be
compared in a pair-wise manner using cross-correlation analysis. For BOLD and LFP responses these
parameters will be computed from the stimulus time-locked averaged traces. To make left-right
comparisons, left-right ratio of each quantified parameter under each condition will be used as a
determinant of the extent of lateralization.
Both short and long term time-dependent changes would be noteworthy from the standpoint of
response plasticity and sensory learning during development. For LFP responses we will measure the
RMS amplitude/power and duration, and compare shapes by cross-correlation. Each BOLD and
bioelectrical response parameter will be plotted with respect to time during development. This will allow
us to observe the time course of changes due to learning of song, and correlate any sharp
transformations of responses with steps in song learning at corresponding time points.
Based in part by observations in our preliminary studies we hope to confirm the following: a) There
would be an initial over-activation of NCM/field L/CM region in response to TUT in terms of mean peak
amplitude/power and area of significant activation in the early stages of song learning. b) There would
be a similar robust activation of the area X at these early stages. c) Both types of activity would show a
progressive reduction over the course of song learning either as a gradual decrement or a sharp fall at
the time of the closure of the sensitive period. d) The emergence of auditory representation of the
16
tutor’s song would be captured by consistency in some measure of the LFP response (such as the
consistency of the shape of the response ascertained by cross-correlation analysis) and of the BOLD
response (such as a fixed discrete pattern of significant activation in NCM). This, if true, would support
the long-standing notion in the birdsong field that the establishment of a fixed auditory representation of
the tutor’s song precedes vocal development. e) A general decrease in sensitivity and an increase in
selectivity of the NCM/field L/CM response to non-vocal control sound combined with deactivation of X
might also be observed, with contrasting findings in isolates. f) Accuracy of imitation varies among
individuals, and we expect to see such variability among our tutored birds. We expect to find a
correlation between imitation success and the observed changes in auditory responses. Specifically, we
expect better tuning and maturation (as described above) of activation of auditory areas and of area X
in birds achieving good imitation.
We will weigh our results against the possibility that observed ontogenic changes are caused by
changes in neuro-vascular coupling by measuring changes of regional cerebral blood flow (rCBF) using
arterial spin labeling (ASL) in response to stimulation with a vocal sound. For constant neuro-vascular
coupling we would not expect a significant change of the BOLD/rCBF ratio. If we observe significant
changes during certain phases of development, we will include this information into the interpretation of
our results. In addition, we will generate correlation maps between the BOLD and rCBF signals and
monitor local changes during development. To keep experimental efforts feasible, ASL experiments will
be performed on only one stimulus (a standard female call) per bird, and the analysis will be restricted
to primary and secondary auditory areas.
OBJECTIVE 2
We propose to test the following two hypotheses: a) Progressive maturation of auditory
response selectivity across generations in males anticipates the de novo evolution of song
culture, and b) The innately mature and normal response selectivity in females facilitates its
maturation in their male companions through social interaction.
Under this objective we will study how male and female song-selectivity changes during
development across generations, over the course of evolution of a new song culture. Using similar
methods as in Objective 1 we will examine the development of general and fine-grained song selectivity
across generations in two environments. In the first “deprived environment”, a juvenile bird will imitate
the song on an isolate tutor one-to-one, continuing recursively (using the pupil of one generation as the
tutor of the next generation) across 3-5 generations until wild-type song emerges. In the second “social
environment” same tutoring will take place, starting from a pair of male and female isolates, continuing
recursively with 4 birds in each chamber (male + female tutors and male + female pupils). In these birds
we will ask the following questions:
iii) When during development in each generation and across generations general and fine-grained
song selectivities emerge, and how do they progress in males in relation to the evolution of a
new song culture? Does the presence of female change the rate of vocal and sensory
changes?
iv) Does the development of female song selectivity affect the imitation of song by males across
generations?
Bird’s vocalizations produced during song learning will be continuously recorded and analyzed in
real time using a modified version of the Sound Analysis system developed in the Tchernichovski
laboratory [50, 51]. In each of the two experimental groups (box-trained and isolates) we will perform an
initial fMRI scan for the tutor’s song and a non-vocal sound at day 41. We recognize that there are
individual differences in the pace of song development. We therefore propose to scan the birds,
subsequently, both at pre-specified time points in development (once weekly scans until day 90) and at
time points corresponding to shifts in vocal patterns. While we might not be able to determine whether
any particular sensory change precedes a vocal shift or vice versa, the LFP and fMRI measurements at
pre-specified time points, independent of vocal changes, would allow us to plot developmental
trajectories of auditory responses and compare those trajectories with the trajectories of vocal changes
that are being continuously recorded. In this way we would be able to determine if any of the major
events in song development such as the emergence of syllable types, formation of song motifs, and
crystallization, are preceded or succeeded by significant changes in auditory responses. Once such
correlations are discovered, causal relationship between the two events could be tested in a
subsequent project. In separate groups of birds we will perform LFP recordings at corresponding time
points……………………………..
17
Data analysis and anticipated results
Cultural Evolution
Ofer, please add here
fMRI and LFP Changes
We will investigate any changes in the BOLD parameters side by side with the developing vocalized
precursors for the tutor’s song components (or for the crystallized song in isolates). To confirm that
these changes also occur at the same time in the underlying bioelectrical response, we will perform
measurements on LFPs as in Objective 1…………………
Problems and Alternative Strategies
Based on our experience, we do not anticipate any serious technical problems with the fMRI
experiments. Regarding in vivo electrophysiology, we have already performed preliminary experiments
using the proposed methods in adult and juvenile birds. We propose to record LFPs only after 40 days
post-hatch because of the difficulty of implanting chronic electrodes due to the softness and immaturity
of the skull at earlier ages. If we encounter difficulty in conducting chronic recordings before 60 days
post-hatch, then we will perform acute LFP recordings at these earlier time points in restrained birds
using standard procedures. We have successfully performed chronic epidural surface
electroencephalographic and LFP recordings around 45 – 55 days of age.
Regarding difficulties in comparing differences in activation between different salient stimuli with a
global measure such as fMRI, we have already demonstrated that we can measure response selectivity
and differential topography using fMRI in our recent PNAS paper. In addition, we are using both fMRI
and LFP recordings. With LFP, response selectivity is evident in the amplitude and shape of the
waveform elicited by each stimulus. …………….
Procedures
Protocol for stimulation: All stimuli (digitally normalized to RMS amplitude) used will be delivered at
~70 dB sound pressure level (exceeding the 7T scanner background noise of ~65 dB). Furthermore, we
will construct a sound isolation box to reduce the background noise. The stimulation protocol will be as
described in Voss et al., 2007 [2]. The same stimuli will be used for the LFP recordings, in which we will
also present stimuli at the normal sound intensity of vocalizations, i.e. ~70 dB sound pressure level, in
the presence of a pre-recorded background noise (~65 dB) to simulate the scanning conditions. As far
as possible, stimuli of comparable durations will be chosen, and parameters such as degree of
familiarity and saliency will be kept uniform across all birds.
MRI scanning procedure: (Henning, please add here)
Images will be acquired on a 7T animal MRI scanner (Bruker BioSpec) with parallel acquisition
hardware. We will use a variety of MRI pulse sequences to acquire anatomical and functional (BOLD
and rCBF) images of the brain, starting with EPI. All necessary pulse sequences are provided with our
scanner. The choice of scanning parameters will be guided by our experience on a 3T MRI scanner and
by literature values from songbird fMRI experiments on 7T MRI scanners. Final optimized parameters
will be determined in pilot experiments. As far as possible, this optimization will be performed on
phantoms. Each scanning sessions will take about 1 hr per bird. In addition, we will image anatomical
changes with high-resolution contrast-enhanced anatomical imaging [52], and diffusion tensor imaging
(DTI) [53] in excised brains at representative time points.
MRI postprocessing: The images will be despiked and motion corrected using AFNI and further
processed using in-house software written in MATLAB, and ParaVision: Data will be smoothed slicewise with a 2D Gaussian filter, detrended, and temporally smoothed. Statistical significance of the
BOLD and rCBF response will be defined voxel-wise with general linear modeling, including motion
parameters derived from the motion correction as nuisance parameter, and then corrected for multiple
testing using Gaussian random field theory. The relative strength of the BOLD effect and rCBF changes
will be measured in the significantly activated areas by the percentage of signal variability in response
to stimulation against overall signal intensity. The relative BOLD signal will be related to the relative
rCBF signal by comparing the BOLD/rCBF ratio, averaged over all significant voxels in the brain, for all
time points. In addition, correlation maps between BOLD and rCBF will be computed to estimate
possible local changes of neuro-vascular coupling. We will also measure the volume of activation in
selected regions. Non-isotropic shifts in anatomy during development will be analyzed by examining
18
changes in the shape of activated regions within the brain. All the statistical parametric maps (SPMs)
will finally be registered to a brain template for the corresponding developmental time point, and group
statistics will be performed, using standard n-way ANOVA tests for groups of birds, stimuli, and time
points. The anatomical resolution on the new 7T animal scanner that we will use will be higher than in
our present experiment. More importantly, we expect spatial distortions of the functional data versus the
anatomy to be reduced, and we will be able to overlay the functional activations to the anatomies of
individual brains at each time point. Color fiber direction maps from DTI images will provide additional
information about location of fiber tracts and song nuclei which may not be evident from the anatomical
images alone.
Procedure for in vivo electrophysiology: The chronic depth electrodes will be implanted bilaterally
under general anesthesia (xylazine - 50 mg/kg body weight and ketamine - 25 mg/kg body weight,
intramuscular). The LFP Teflon-coated blunt tungsten electrodes with an impedance of 100 – 500 KΩ
will be inserted into holes made in the skull at pre-specified stereotaxic coordinates (uniform across all
birds) in NCM, field L, CM and area X specified by the Nixdorf and Bischof stereotaxic atlas (Nixdorf, B.
and Bischof, H.–J. (1979) unpublished, Bielefeld) aligned with a MRI atlas ([48], and using a high
resolution anatomical MRI scan. Two bilateral gold-plated pin reference electrodes will be implanted
over the cerebellum at stereotaxic coordinates AP – -2.0, Lat – 1.3. The active and reference electrodes
will be connected to the lead wires with specially designed clamp connectors. The leads will be
connected to a 16-channel differential amplifier (AM-Systems, Inc). Digitally normalized stimuli will be
delivered at 70 dB maximum sound pressure levels. Recordings will be conducted while the bird is
awake or mildly sedated with diazepam and restrained in a soft plastic tube inside a sound-attenuated
box. The signals will be low-pass filtered at 10 kHz, digitized at 5 kHz, and analyzed with MATLABbased programs developed by us. Auditory evoked LFPs will be obtained by stimulus time-locked
averaging of >250 artifact-free epochs.
Raising and training of zebra Finches:
Ofer, please add here
Brain histology: To determine the location of electrodes we will mark their locations by passing an
electrolytic lesion current under deep terminal xylazine/ketamine general anesthesia. We will then
perfuse and remove the brain to perform histology on cryosections using standard procedures. Coronal
or sagittal sections will be stained with Nissl’s stain or with cytochrome C oxidase stain (see Braun et al.
[54]). Cytochrome C oxidase histology will also be carried out in a few separate birds at ages
corresponding to the fMRI scanning time points in development, to track developmental anatomical
changes in auditory and song structures. This will enable us to properly interpret the locations and
spatial extents of BOLD activation patterns at those time points.
Analysis of birdsong:
Ofer, please add here
Statistical Analysis
Lucas, please add here
Broader Impact
Educational Significance: This project provides a unique opportunity for students and postdoctoral
fellows to engage in multidisciplinary research in animals, involving behavioral analysis, in vivo
electrophysiology and functional magnetic resonance imaging. We will use this innovative multipronged
and quantitative analytical approach to recruit students and postdoctoral researchers in our
laboratories. The Tchernichovski laboratory provides research opportunities for graduate and
undergraduate students from CCNY, City University of New York (CUNY). CCNY is a designated
Research Center in Minority Institution (RCMI) and is dedicated to supporting and promoting the
scientific careers of minority students. Its campus is located in Harlem, New York, and the college has a
large proportion of minority students. Graduate students from the Speech-Language-Hearing
Department of CUNY also have an opportunity to conduct research in the lab, as Dr. Tchernichovski is
a faculty member of that program as well as Biology. This allows students with a background in human
clinical research (speech pathology) to conduct research on an animal model of vocal learning. Dr.
Tchernichovski teaches an Animal Behavior course to both graduates and undergraduates at CCNY.
The course includes a section on mechanisms of learning in songbirds. A number of students have
sought to conduct research in the lab (for independent study credits) after being introduced to the
subject of birdsong neurobiology in the course. The graduate student in the Tchernichovski lab that will
be involved with the present project will be trained to combine behavioral analysis with imaging. She/he
19
will be mentored by Dr. Tchernichovski, and will interact with other systems neuroscience faculty in our
neuroscience group. She/he will participate in our weekly neuroscience seminars, and present her work
at Society for Neuroscience annual meetings. She/he will also visit the Voss lab on a regular basis, and
learn fMRI scanning and analysis from Dr. Voss.
The Voss laboratory is integrated into an imaging core facility that provides research opportunities
and support for graduate students and residents from the WMC and affiliated research institutions
interested in biomedical imaging. Dr. Voss is in charge of animal magnetic resonance imaging, and will
be involved in training students and postdoctoral researchers involved in this research.
The Helekar laboratory has provided research internships to undergraduate students of University of
Houston, University of Texas at Austin and Rice University, as well as research assistantships to
science graduates interested in academic careers in science and medicine. BCM Neuroscience
graduate students have the opportunity to conduct research rotations and doctoral thesis research in
his laboratory. The laboratory has conducted short-term (1 - 3 months) research training for high
school, undergraduate and medical students. He has held a laboratory teaching activity on songbird
models of speech for Speech Pathology graduate students of University of Houston. Being an adjunct
faculty member of the Biology Department of Texas A & M University, Dr. Helekar serves on the thesis
committee of a graduate student studying songbird molecular neurobiology.
Training minority students – The Tchernichovski laboratory has already trained a minority PhD
student and several undergraduate students. For this project, CCNY will allocate resources to provide
at least one undergraduate minority student with a stipend for participation in it. The student will be
taught the behavioral data collection and analysis methods used in the lab, and apply them under the
supervision of a PhD student and Dr. Tchernichovski. Currently, WMC boasts a record of graduating
over 400 minority physicians with numbers still rising. In addition, 18% (among the highest in the nation)
of its student body consists of underrepresented minorities. From this pool, Dr. Voss will try to attract
medical students and postdoctoral fellows to work with him on the present project. Students at BCM
and universities in the Houston area have a substantial minority representation, and Dr. Helekar will try
to recruit students from this pool as undergraduate, graduate and postgraduate researchers in the
laboratory.
Extending across disciplines – Dr. Tchernichovski is a member of both the CUNY Neuroscience
program, and the CUNY Speech and Hearing programs. We plan to continue sharing students across
these disciplines to relate our findings more firmly to those of speech pathology and speech
development in human infants. With more than 20 current user groups, the imaging core facility that
houses Dr. Voss’ lab will serve, as before, a pool of users from the basic and cognitive neurosciences
and various medical specialties, ensuring a continuous exchange of ideas across disciplines. The
imaging core is at present rapidly expanding, with a new 7.0 T animal MRI scanner and a second 3.0 T
human MRI scanner, attracting new groups from various institutions, including biologists from
Rockefeller University. Dr. Helekar’s laboratory will continue to offer as before opportunities for
research to clinical residents and fellows, as well as for collaborative projects on songbird models of
speech and learning disorders for clinical researchers in the BCM Neurology, Otolaryngology and
Psychiatry departments.
Dissemination of Research Findings: Our (Tchernichovski, Voss and Helekar) research involving
fMRI was featured on the NOVA Science Now program of the Public Broadcasting Service
(http://www.pbs.org/wgbh/nova/sciencenow/0304/01.html) and the Science Friday news report of
National
Public
Radio
(http://www.sciencefriday.com/news/072407/finch072407.html).
Dr.
Tchernichovski continues to answer questions from students and interested readers regarding our work
on the NOVA Science Now website. Our work also appeared in the German weekly newspaper “Die
Zeit” (http://www.zeit.de/2008/41/N-Stottervoegel). We will continue to disseminate the findings of our
project through local, national and international media in this manner. We will also explain our work and
our results to the general public through our respective institutional websites.
Community Outreach: The Tchernichovski lab has participated, and will continue to participate in a
program with a local middle school which pairs middle school students with a graduate student mentor
over the course of the school year for a science fair project. The goal of the program is to introduce the
middle school students to scientific research and methods and promote interest in science. Dr. Voss
gives an annual lecture within an NIH sponsored summer school for high school students interested in
neuroscience. Dr. Helekar has given and plans to give talks to high school students who are members
20
of the National Science Honor Society about careers in science, his own experiences as a
neuroscientist, and songbird research related to the present proposal. Two students have used his help
and the resources in his laboratory to develop their science fair projects in the past. He will continue to
carry out such activities in the community.
Overall Future Plans: Our overall plan for the future for our research to have a broader impact is
therefore as follows: Procedures, software and materials developed under the present project will be
freely shared with all interested researchers, students and teachers for research and educational
purposes. All three investigators will strive: 1) To train graduate students through laboratory research
rotations and doctoral thesis work, 2) To provide scientific and research training to undergraduate
students and opportunities for independent summer research, 3) To serve on the thesis committees of
graduate students, 4) To disseminate our work through electronic and print media, and 5) To give
science lectures, and provide practical science education and student research experience to middle
school and high school students in the community.
Postdoctoral Mentoring/Training
The graduate student in the Helekar laboratory will receive a well-rounded training and experience
in songbird neurophysiology. He/she will be trained to perform animal surgery and implant local field
potential recording (LFP) electrodes in the brain. He/she will be taught to raise and tutor songbirds,
perform song and LFP recordings, and to carry out statistical analysis of data. He/she will also gain
experience in functional magnetic resonance imaging (fMRI) in songbirds, and analyze fMRI data.
He/she will have to present his/her work at a weekly lab meeting, and participate in a weekly journal
club that requires each person to present a research paper about once every two months for general
discussion. He/she will have to attend a departmental neuroscience seminar every week. He/she will
also have opportunities to attend an annual departmental Neuroscience retreat and a Society for
Neuroscience annual meeting to present his/her work. This will enable him/her to interact with scientists
in his/her area, as well as with those working in other areas of research on the brain.
The postdoctoral fellow in the Voss laboratory will have the opportunity to interact with several
neuroscience and preclinical research groups with various backgrounds that use the imaging core
facility. He/she will have the opportunity to present at domestic scientific conferences, and to attend
scientific meetings and presentations at WMC and its two affiliated institutions, including Rockefeller
University. WMC offers regular grant preparation, scientific publishing, and mentoring workshops. The
postdoc program at WMC offers regular career pathway seminars. We will also ask the postdoc to
present a lecture about functional MRI within our biomedical imaging teaching program and to present
progress reports within our internal lab meetings.
References
1. Feher, O., et al., De novo establishment of wild-type song culture in the zebra finch. Nature, 2009.
459(7246): p. 564-8.
2. Voss, H.U., et al., Functional MRI of the zebra finch brain during song stimulation suggests a
lateralized response topography. Proc Natl Acad Sci U S A, 2007. 104(25): p. 10667-72.
3. Maul, K.K., et al., Early song-tutoring experience is required to shape auditory responses in zebra
finch males but not in females. in review, 2009.
4. Voss, H.U., D. Salgado-Commissariat, and S.A. Helekar, Altered BOLD response to conspecific
song in zebra finches with stuttered syllables. in review, 2009.
5. Haesler, S., et al., FoxP2 expression in avian vocal learners and non-learners. J Neurosci, 2004.
24(13): p. 3164-75.
6. Doupe, A. and P. Kuhl, Birdsong and human speech: common themes and mechanisms. Annu Rev
Neurosci, 1999. 22: p. 567-631.
7. Immelmann, K., Song development in the zebra finch and other estrilid finches, in Bird
Vocalizations, R.A. Hinde, Editor. 1969, Cambridge University Press: Cambridge. p. 61-77.
8. Doupe, A.J. and P.K. Kuhl, Birdsong and human speech: common themes and mechanisms. Annu
Rev Neurosci, 1999. 22: p. 567-631.
9. Sossinka, R. and J. Bohner, Song types in the zebra finch Poephilia guttata castanotis. Zietschrift
für Tierpsychologie, 1980. 53: p. 123-132.
10. Brainard, M.S. and A.J. Doupe, Interruption of a basal ganglia-forebrain circuit prevents plasticity of
learned vocalizations. Nature, 2000. 404(6779): p. 762-6.
21
11. Terpstra, N.J., et al., Localized brain activation specific to auditory memory in a female songbird. J
Comp Neurol, 2006. 494(5): p. 784-91.
12. Konishi, M. and F. Nottebohm, Experimental studies in the ontogeny of avian vocalizations., in Bird
Vocalizations, R.A. Hinde, Editor. 1969, Cambridge University Press: Cambridge. p. 29-48.
13. Tchernichovski, O., et al., Dynamics of the vocal imitation process: how a zebra finch learns its
song. Science, 2001. 291(5513): p. 2564-9.
14. Phan, M.L., C.L. Pytte, and D.S. Vicario, Early auditory experience generates long-lasting
memories that may subserve vocal learning in songbirds. Proc Natl Acad Sci U S A, 2006. 103(4):
p. 1088-93.
15. Bonke, B., D. Bonke, and H. Scheich, Connectivity of the auditory forebrain nuclei in the guinea
fowl (Numida meleagris). Cell Tissue Res, 1979. 200(1): p. 101-21.
16. Muller, C. and H. Leppelsack, Feature extraction and tonotopic organization in the avian auditory
forebrain. Exp Brain Res, 1985. 59(3): p. 587-99.
17. Williams, H. and F. Nottebohm, Auditory responses in avian vocal motor neurons: a motor theory
for song perception in birds. Science, 1985. 229(4710): p. 279-82.
18. Margoliash, D., Preference for autogenous song by auditory neurons in a song system nucleus of
the white-crowned sparrow. J Neurosci, 1986. 6(6): p. 1643-61.
19. Doupe, A. and M. Konishi, Song-selective auditory circuits in the vocal control system of the zebra
finch. Proc Natl Acad Sci U S A, 1991. 88(24): p. 11339-43.
20. Margoliash, D. and E. Fortune, Temporal and harmonic combination-sensitive neurons in the zebra
finch's HVc. J Neurosci, 1992. 12(11): p. 4309-26.
21. Vicario, D. and K. Yohay, Song-selective auditory input to a forebrain vocal control nucleus in the
zebra finch. J Neurobiol, 1993. 24(4): p. 488-505.
22. Doupe, A., Song- and order-selective neurons in the songbird anterior forebrain and their
emergence during vocal development. J Neurosci, 1997. 17(3): p. 1147-67.
23. Margoliash, D., Functional organization of forebrain pathways for song production and perception. J
Neurobiol, 1997. 33(5): p. 671-93.
24. Sutter, M. and D. Margoliash, Global synchronous response to autogenous song in zebra finch
HVc. J Neurophysiol, 1994. 72(5): p. 2105-23.
25. Doupe, A. and M. Solis, Song- and order-selective neurons develop in the songbird anterior
forebrain during vocal learning. J Neurobiol, 1997. 33(5): p. 694-709.
26. Solis, M. and A. Doupe, Anterior forebrain neurons develop selectivity by an intermediate stage of
birdsong learning. J Neurosci, 1997. 17(16): p. 6447-62.
27. Volman, S., Development of neural selectivity for birdsong during vocal learning. J Neurosci, 1993.
13(11): p. 4737-47.
28. Amin, N., A. Doupe, and F.E. Theunissen, Development of selectivity for natural sounds in the
songbird auditory forebrain. J Neurophysiol, 2007. 97(5): p. 3517-31.
29. Solis, M.M. and A.J. Doupe, Compromised neural selectivity for song in birds with impaired
sensorimotor learning. Neuron, 2000. 25(1): p. 109-21.
30. Solis, M.M. and A.J. Doupe, Anterior forebrain neurons develop selectivity by an intermediate stage
of birdsong learning. J Neurosci, 1997. 17(16): p. 6447-62.
31. Solis, M. and A. Doupe, Compromised neural selectivity for song in birds with impaired
sensorimotor learning [see comments]. Neuron, 2000. 25(1): p. 109-21.
32. Stripling, R., S. Volman, and D. Clayton, Response modulation in the zebra finch neostriatum:
relationship to nuclear gene regulation. J Neurosci, 1997. 17(10): p. 3883-93.
33. Bolhuis, J.J., et al., Localized neuronal activation in the zebra finch brain is related to the strength of
song learning. Proc Natl Acad Sci U S A, 2000. 97(5): p. 2282-5.
34. Theunissen, F.E. and S.S. Shaevitz, Auditory processing of vocal sounds in birds. Curr Opin
Neurobiol, 2006. 16(4): p. 400-7.
35. Stripling, R., A.A. Kruse, and D.F. Clayton, Development of song responses in the zebra finch
caudomedial neostriatum: role of genomic and electrophysiological activities. J Neurobiol, 2001.
48(3): p. 163-80.
36. Van Meir, V., et al., Spatiotemporal properties of the BOLD response in the songbirds' auditory
circuit during a variety of listening tasks. Neuroimage, 2005. 25(4): p. 1242-55.
37. Logothetis, N.K. and B.A. Wandell, Interpreting the BOLD signal. Annu Rev Physiol, 2004. 66: p.
735-69.
22
38. Ballon, D. and H.U. Voss. High-Pass Two-Dimensional Ladder Network Resonators. in Proc.of the
13th Scientific Meeting of ISMRM. 2005.
39. Voss, H.U. and D.J. Ballon, High-pass two-dimensional ladder network resonators for magnetic
resonance imaging. IEEE Trans Biomed Eng, 2006. 53(12 Pt 2): p. 2590-3.
40. Voss, H.U., et al. Diffusion tensor imaging at 3T with strongly reduced geometric and intensity
distortions. in Proc Intl Soc Mag Reson Med. 2005.
41. Voss, H.U., et al. Correction of Spatial and Intensity Distortions in Functional Magnetic Resonance
Imaging. in Proc Intl Soc Mag Reson Med. 2005.
42. Voss, H.U., et al. Functional MRI of the songbird zebra finch at 3 Tesla. in Proc Intl Soc Mag Reson
Med 2006.
43. Voss, H.U., D. Salgado-Commissariat, and S.A. Helekar, Altered Bold Sensitivity To Conspecific
Song In Zebra Finches With Stuttered Syllables. Submitted preprint, 2008.
44. Maul, K.K., et al., Early song-tutoring experience is required to shape auditory responses in zebra
finch males but not in females. Submitted preprint, 2008.
45. Chew, S.J., et al., Decrements in auditory responses to a repeated conspecific song are longlasting and require two periods of protein synthesis in the songbird forebrain. Proc Natl Acad Sci U
S A, 1995. 92(8): p. 3406-10.
46. Terleph, T.A., C.V. Mello, and D.S. Vicario, Auditory topography and temporal response dynamics
of canary caudal telencephalon. J Neurobiol, 2006. 66(3): p. 281-92.
47. Logothetis, N.K., et al., Neurophysiological investigation of the basis of the fMRI signal. Nature,
2001. 412(6843): p. 150-7.
48. Poirier, C., et al., A three-dimensional MRI atlas of the zebra finch brain in stereotaxic coordinates.
Neuroimage, 2008. 41(1): p. 1-6.
49. Shen, Q., H. Ren, and T.Q. Duong, CBF, BOLD, CBV, and CMRO(2) fMRI signal temporal
dynamics at 500-msec resolution. J Magn Reson Imaging, 2008. 27(3): p. 599-606.
50. Tchernichovski, O., et al., A procedure for an automated measurement of song similarity. Anim
Behav, 2000. 59: p. 1167-1176.
51. Deregnaucourt, S., et al., How sleep affects the developmental learning of bird song. Nature, 2005.
433(7027): p. 710-6.
52. Bath, K.G., et al., Quantitative intact specimen magnetic resonance microscopy at 3.0 Tesla,
Magnetic Resonance Imaging. in press, 2009.
53. De Groof, G., et al., In vivo diffusion tensor imaging (DTI) of brain subdivisions and vocal pathways
in songbirds. Neuroimage, 2006. 29(3): p. 754-63.
54. Braun, K., et al., Distribution of parvalbumin, cytochrome oxidase activity and 14C-2-deoxyglucose
uptake in the brain of the zebra finch I. Auditory and vocal motor systems. Cell Tissue Res, 1985.
240: p. 101-115.
23