Stimulus-Specific Adaptations in the Gaze Control System of the Barn Owl

Abstract

Abrupt orientation to novel stimuli is a critical, memory-dependent task performed by the brain. In the present study, we examined two gaze control centers of the barn owl: the optic tectum (OT) and the arcopallium gaze fields (AGFs). Responses of neurons to long sequences of dichotic sound bursts comprised of two sounds differing in the probability of appearance were analyzed. We report that auditory neurons in the OT and in the AGFs tend to respond stronger to rarely presented sounds (novel sounds) than to the same sounds when presented frequently. This history-dependent phenomenon, known as stimulus-specific adaptation (SSA), was demonstrated for rare sound frequencies, binaural localization cues [interaural time difference (ITD) and level difference (ILD)] and sound amplitudes. The manifestation of SSA in such a variety of independent acoustic features, in the midbrain and in the forebrain, supports the notion that SSA is involved in sensory memory and novelty detection. To track the origin of SSA, we analyzed responses of neurons in the external nucleus of the inferior colliculus (ICX; the source of auditory input to the OT) to similar sequences of sound bursts. Neurons in the ICX responded stronger to rare sound frequencies, but did not respond differently to rare ITDs, ILDs, or sound amplitudes. We hypothesize that part of the SSA reported here is computed in high-level networks, giving rise to novelty signals that modulate tectal responses in a context-dependent manner.

Full text

Behavioral/Systems/Cognitive
Stimulus-Specific Adaptations in the Gaze Control System of
the Barn Owl
Amit Reches and Yoram Gutfreund
Department of Physiology and Biophysics, The Ruth and Bruce Rappaport Faculty of Medicine, The Technion, Haifa 31096, Israel
Abrupt orientation to novel stimuli is a critical, memory-dependent task performed by the brain. In the present study, we examined two
gaze control centers of the barn owl: the optic tectum (OT) and the arcopallium gaze fields (AGFs). Responses of neurons to long
sequences of dichotic sound bursts comprised of two sounds differing in the probability of appearance were analyzed. We report that
auditory neurons in the OT and in the AGFs tend to respond stronger to rarely presented sounds (novel sounds) than to the same sounds
when presented frequently. This history-dependent phenomenon, known as stimulus-specific adaptation (SSA), was demonstrated for
rare sound frequencies, binaural localization cues [interaural time difference (ITD) and level difference (ILD)] and sound amplitudes.
The manifestation of SSA in such a variety of independent acoustic features, in the midbrain and in the forebrain, supports the notion that
SSA is involved in sensory memory and novelty detection. To track the origin of SSA, we analyzed responses of neurons in the external
nucleus of the inferior colliculus (ICX; the source of auditory input to the OT) to similar sequences of sound bursts. Neurons in the ICX
responded stronger to rare sound frequencies, but did not respond differently to rare ITDs, ILDs, or sound amplitudes. We hypothesize
that part of the SSA reported here is computed in high-level networks, giving rise to novelty signals that modulate tectal responses in a
context-dependent manner.
Key words: auditory localization; novelty detection; attention; optic tectum; superior colliculus; saliency map
Introduction
In natural environments, a critical task of the brain is to abruptly
detect and attend to novel stimuli (Ranganath and Rainer, 2003).
Indeed, signals that are novel in time and space are perceptually
privileged and give rise to psychophysical effects such as pop-outs
(Diliberto et al., 2000), attentional capture (Tiitinen et al., 1994),
and enhanced autonomic responses (Weisbard and Graham,
1971; Bala and Takahashi, 2000).
Stimulus-specific adaptation (SSA) is a phenomenon at the
single-neuron level proposed as a neurocorrelate for novelty
detection (Ulanovsky et al., 2003). In SSA, the response of a
neuron to a stimulus is decreased when the same stimulus is
repeatedly presented. As a result, the stimulus when it is rare
elicits a stronger response than when it is frequent (Sobotka
and Ringo, 1994; Ulanovsky et al., 2004; Perez-Gonzalez et al.,
2005; Katz et al., 2006). Previous studies emphasized the ap-
pearance of SSA in cortical circuitry linking it with auditory
memory and recognition of acoustic objects (Nelken, 2004).
Here, we study auditory SSA in the midbrain and forebrain
gaze control circuitry of the barn owl.
Gaze control circuitry is believed to be intimately linked
with the control of spatial attention to salient stimuli (Cor-
betta, 1998; Moore et al., 2003). Therefore, it is of special
interest to characterize SSA effects in gaze control centers such
as the superior colliculus or the frontal eye fields (FEFs). The
superior colliculus in mammals, or its avian homolog the optic
tectum (OT), is a midbrain structure involved in orienting
gaze toward salient stimuli (Sparks, 1986; Wagner, 1993). The
FEFs are a direct gaze control center located in the frontal
cortex of monkeys (Bruce and Goldberg, 1985). The avian
equivalent forebrain circuit of the FEFs can be found in the
arcopallium gaze fields (AGFs) (Cohen and Knudsen, 1995), a
region controlling gaze changes that, like the FEFs, projects to
the OT and to premotor areas in the brainstem (Knudsen et
al., 1995; Knudsen and Knudsen, 1996b).
To study SSA we analyzed extracellular responses to se-
quences of dichotically presented acoustic stimuli. Sequences
were comprised of two sounds differing in the probability of
appearance (one rare and the other frequent) and in a single
acoustic feature, which could be either sound frequency, in-
teraural time difference (ITD), interaural level difference
(ILD), or average binaural sound intensity (ABSI). We found
significant SSA effects in both the OT and the AGFs for all
sound features tested (ITD, ILD, ABSI, and frequency in the
OT; ITD and frequency in the AGFs). However, SSA for fre-
quency differed from SSA for ITD, ILD, and ABSI in that the
latter were not observed in the external nucleus of the inferior
colliculus (ICX), whereas SSA for frequency was evident in the
ICX and OT. We hypothesize that SSA for ITD, ILD, and ABSI
are computed in high-level circuitry in the OT or forebrain,
possibly giving rise to novelty signals that modulate auditory
responses in a context-dependent manner.
Received Aug. 20, 2007; revised Dec. 5, 2007; accepted Dec. 26, 2007.
Thiswork wassupported bya Bikuragrant fromthe IsraelScience Foundationand bythe JoelElkes grantfrom the
National Psychobiology Institute in Israel (founded by the E. Smith family). We thank Prof. Eli Nelken for advice and
careful reading of this manuscript and Felix Milman for technical support.
Correspondence should be addressed to Yoram Gutfreund, Department of Physiology and Biophysics, The Bruce
Rappaport Medical School, The Technion, Haifa 31096, Israel. E-mail: yoramg@tx.technion.ac.il.
DOI:10.1523/JNEUROSCI.3785-07.2008
Copyright © 2008 Society for Neuroscience 0270-6474/08/281523-11$15.00/0
The Journal of Neuroscience, February 6, 2008 •28(6):1523–1533 • 1523

Materials and Methods
For this study, four barn owls (Tyto alba) were used. All owls were
hatched in captivity, and raised and kept in a large flying cage. The owls
were provided for in accordance with the guidelines of the Technion
Institutional Animal Care and Use Committee.
Electrophysiological measures. Owls were prepared for repeated electro-
physiological experiments in a single surgical procedure. A craniotomy
was performed and a recording chamber was cemented to the skull. At
the beginning of each recording session, the owl underwent anesthesia
using halothane (2%) and nitrous oxide in oxygen (4:5). Once anesthe-
tized, the animal was positioned in a stereotaxic apparatus at the center of
a sound attenuating chamber lined with acoustic foam to suppress ech-
oes. The head was bolted to the stereotaxic apparatus and aligned using
retinal landmarks [as described by Gold and Knudsen (2000)]. Within
the chamber, the bird was maintained on a fixed mixture of nitrous oxide
and oxygen (4:5). A glass-coated tungsten microelectrode (⬃1M⍀; Al-
pha Omega, Nazareth, Israel) was driven into the recording chamber
using a motorized manipulator (SM-191; Narishige, Tokyo, Japan). A
Tucker-Davis Technologies (Alachua, FL) System3 and an online spike
sorter (MSD; Alpha Omega) were used to record and isolate action po-
tentials from single neurons or a small cluster of neurons (multiunit
recording). Multiunit recordings were obtained by manually setting a
threshold consistently selecting the largest unit waveforms in the re-
corded site. Single units were isolated using a template-based sorting.
The spike sorter presents a histogram of the squared errors between the
template and the detected spike. We required the histogram to have a
sharp, well distinguished peak, signifying the presence of a homogeneous
group of spike shapes similar to the template. We also verified that the
interspike-interval histogram showed a refractory period of at least 3 ms.
Based on the above criteria, data from single units was obtained in the
AGFs and OT. In the ICX all recordings were multiunit. Data points
obtained from single neurons are marked specifically in the appropriate
figures. We did not observe any qualitative difference between single and
multiunit results. Therefore, single and multiunit recordings were ana-
lyzed together. At the end of each recording session the chamber was
treated with chloramphenicol 5% ointment and closed. The owl was then
returned to its home flying cage.
Targeting of nuclei. The identification of the recording sites was based
on stereotaxic coordinates and on expected physiological properties. The
OT was recognized by characteristic bursting activity and spatially re-
stricted visual receptive fields (Knudsen, 1982). Position within the OT
was determined based on the location of the visual receptive field (RF).
To target the auditory AGFs, we first obtained the position in the OT
corresponding to the visual RF of zero azimuth and zero elevation (di-
rectly in front). From this position, the electrode was advanced 2 mm
rostrally, 0.4 mm laterally, and 3 mm dorsally [as described by Cohen and
Knudsen (1995)]. Electrolytic lesions (⫹5
␮
A for 30 s) were performed at
the end of two experiments. Both cases confirmed the recording posi-
tions to be well within the boundaries of the AGFs. The ICX was targeted
stereotaxically by positioning the electrode 2 mm caudal and 2.5 mm
medial from the tectal representation of 0
o
azimuth and ⫹10
o
elevation
(relative to the visual axes). The electrode was then moved laterally and
rostrally in steps of ⬃300
␮
m to sample additional sites from the ICX. In
previous studies, anatomical reconstructions of recording sites have con-
firmed the correspondence of these stereotaxic coordinates with the ICX
(Brainard and Knudsen, 1993; Gold and Knudsen, 2000).
Auditory stimulation. Computer-generated signals were transduced by
a pair of matched miniature earphones (ED-1914; Knowles, Itasca, IL).
The earphones were placed in the center of the ear canal ⬃5 mm from the
tympanic membrane. The amplitude and phase spectra of the earphones
Figure1. Exampleof anITDtuning curve.A,Raster plotshowingresponses ofatectal unitto
sounds with different ITD values. Stimulus duration was 50 ms (horizontal bar) starting at time
0 (vertical line). B, The average response per trial as a function of the ITD value. The best ITD
value is designated by the black vertical line. Two ITD values of equal distances (⫾10
␮
s) from
the best ITD (gray arrows) were selected to test for SSA in this neuron.
Figure 2. Auditory stimuli used in the study. A, The oddball stimulus. Sequences of sounds
were comprised of two sounds: stimulus 1 was presented frequently (with a probability of 0.85)
and stimulus 2 was presented rarely. In the second block, the roles were reversed: stimulus 1
wasrareand stimulus2 wascommon.B, Theconstant orderstimulus. Longsequencesof sounds
werecomprisedof 10repetitionsof stimulus1alternating with10repetitions ofstimulus2. The
response to the first stimulus in a sequence of 10 (rare, gray circle) was compared with the
response to the last stimulus in the sequence (common, black circle).
Figure 3. Example of a single AGF site response to an ITD oddball stimulus. A, Dot raster
showing 40 responses to stimulus 1 (ITD, ⫺80
␮
s). The bottom 20 rows show responses to the
rarely presented sound (embedded in a sequence of sounds with an ITD of ⫺100
␮
s). The top
20 rows show randomly picked responses to the same sound presented frequently. B, The
average response to stimulus 1 and stimulus 2 when common (black bars) are compared with
the average response to the same stimuli when rare (gray bars). Error bars represent SE. C,D,
Poststimulus time responses to stimulus 1 (C) and to stimulus 2 (D) are shown (lines are
smoothed for display). Gray lines designate responses to the rare presentation; black lines
designate responses to the common presentation. The shaded area indicates the onset and
duration of sound stimulation. The arrowhead in Dpoints to an inhibitory window not visible in
the average response to rare stimuli.
1524 •J. Neurosci., February 6, 2008 •28(6):1523–1533 Reches and Gutfreund •Specific Adaptation in the Barn Owl

were equalized within ⫾2dBand⫾2
␮
s between 2 and 12 kHz by
computer adjustment of the stimulus waveform. Acoustic stimuli con-
sisted of bursts of either broadband (3–12 kHz) or narrowband noise (1
kHz bandwidth; finite impulse response filter, order ⫽70) with rise/fall
times of 5 ms, presented at an interstimulus interval of 1 s. Sound levels
were controlled by two independent attenuators (PA5; Tucker-Davis
Technologies) and are reported as ABSI relative to a fixed sound-pressure
level. Unit responses to an acoustic stimulus were quantified as the num-
ber of spikes in a given time window after stimulus onset minus the
number of spikes during the same amount of time immediately before
stimulus onset (baseline activity). Tuning curves were generated by vary-
ing a single parameter (ITD, ILD, central frequency, or ABSI) while
holding all other parameters constant. The value of the tested parameter
was varied randomly in stimulus sets that were repeated 10 –20 times.
The width of tuning curves was defined as the range over which responses
were ⬎50% of the maximal response; best ITD, ILD, or frequency was the
midpoint of this range.
Measurements of stimulus-specific adaptation. For each test, two sound
stimuli were selected that differed in a single acoustic feature (ITD, ILD,
central frequency, or ABSI). The values of the specific features were se-
lected to be equally distant from both sides of the best value (for an
example of selecting ITD values, see Fig. 1). This selection procedure
ensured that the neural responses to the two stimuli were approximately
similar. In all cases the selected values were within the tuning curves of
the units. In the ABSI test one stimulus was 10 –15 dB above units thresh-
old and the second was 30 dB louder than the
first. In all cases sound duration was 200 ms
long, the interstimulus interval (onset to onset)
was 1 s and the ABSI (excluding the experiments
in which ABSI-specific adaptation was tested)
was 20 –30 dB above the threshold of the unit.
Two stimulation paradigms were used as fol-
lows. (1) In the oddball design, the two selected
stimuli were presented in a probabilistic manner
(Fig. 2A). One of the stimuli was defined as the
rare stimulus and the other as the common
stimulus (frequent). Each experimental block
consisted of 150 stimuli, the probability of oc-
currence of the common stimulus was 85% and
of the rare stimulus was 15%. In the next exper-
imental block, the roles of the frequent and rare
stimuli were reversed. Neural responses to a
stimulus when rare were compared with the re-
sponses to the same stimulus when frequent. (2)
In the constant order (CO) design, stimuli pre-
sentation consisted of a long sequence of stimuli
[600 repetitions; 1 s interstimulus interval (ISI)]
alternating between the two selected stimuli ev-
ery 10 repetitions (Fig. 2B). The first presenta-
tion of a stimulus within a series of 10 repeti-
tions was regarded as the rare stimulus, because
of precedence of a repetitive presentation of the
other stimulus. The last presentation within a
series of 10 was regarded as the common stimu-
lus, because of preceding repetitive presenta-
tions of the identical stimulus.
Data analysis. For each stimulus in a se-
quence, the response was measured as the num-
ber of spikes in a 200 ms time window starting at
the onset of the stimulus minus the spike count
in the 200 ms preceding the stimulus. In the
oddball design, the responses to frequent stimuli
and the responses to rare stimuli were averaged,
yielding, for each test, four averaged values:
stimulus 1 frequent (S
1
f), stimulus 1 rare (S
1
r),
stimulus 2 frequent (S
2
f), and stimulus 2 rare
(S
2
r). To quantify the SSA effect, we used the
indices defined by Ulanovsky et al. (2003). The
stimulus index (SI) is the normalized difference
between the response to the rare appearance
versus the response to the common appearance of the same stimulus,
defined as follows:
SI ⫽Sir⫺Sif
Sir⫹Sif.
To quantify the tendency of the neuron to respond to a rare stimulus,
independent of the stimulus itself, we used the neuron index (NI), de-
fined as follows:
NI ⫽
共S1r⫺S1f兲⫹共S2r⫺S2f兲
S1r⫹S1f⫹S2r⫹S2f.
Positive values of NI imply a tendency to respond stronger to the rare
appearances of the stimuli.
In the constant order design, we averaged the responses to all first
presentations (S
i
r) and to all last presentations (S
i
f) of a stimulus within
a series of 10 repetitions (n⫽30) (Fig. 2 B). Stimulus and neuron indices
were computed as described above. To avoid bias caused by onset effects,
the responses to the first 20 stimuli were omitted from the analysis.
To determine the latency of the response, we used the spike-train
analysis procedure used by Hanes et al. (1995). The algorithm identifies
the point in time where the interspike intervals are shorter than expected,
based on the notion that the interspike intervals of the spontaneous
Figure 4. Summary of ITD oddball tests from all recording sites in the AGFs. A–C, Results are separated to ITD gaps smaller
than 30
␮
s(A), between 40 and 60
␮
s(B), and larger than 60
␮
s(C). The left column presents the scatterplots of SI
1
versus SI
2
.
Gray points designate recordings from verified single units. The dashed lines mark the first quadrant, where both SIs are positive.
The number of points above and below the diagonal line are shown in the bottom right corner. The middle column presents the
histogramsofthe NIsdistribution.The blackvertical line marksthe zero axis(NI, 0).Theright columnshowsthe populationPSTHs
normalized and averaged across all sites. Gray lines designate the population response to the rare stimulus and black lines
designate the population response to the common stimulus. The bar in the top plot represents the duration of stimulation.
Reches and Gutfreund •Specific Adaptation in the Barn Owl J. Neurosci., February 6, 2008 •28(6):1523–1533 • 1525

activity can be viewed as a homogenous Poisson process. The latency for
each spike train was identified separately and averaged over all trials.
To obtain the population average response, single-test poststimulus
time histograms (PSTHs) with 2 ms wide bins were normalized to their
maximum and averaged across the entire population. Population PSTHs
were smoothed for display purposes (see Figs. 4, 6, 7, 9, 10, 12, 14).
Quantitative analysis was performed on unsmoothed data.
Results
SSA in the AGFs
SSA was studied using the oddball stimulus paradigm (see Mate-
rials and Methods). An example of one recording site in the AGFs
is shown in Figure 3. Here, a sequence of 150 sound stimuli was
presented from which the ITD value of 127 randomly selected
stimuli was ⫺80
␮
s in block 1 and ⫺100
␮
s in block 2 (frequent
presentations). The remaining 23 stimuli had ITD values of ⫺100
and ⫺80
␮
s in blocks 1 and 2, respectively (rare presentations).
Both ITD values were within the response range of the recorded
site, eliciting significant responses. The average response for an
ITD of ⫺80
␮
s was slightly larger than for ⫺100
␮
s (Fig. 3B).
Nevertheless, for both ITDs, the average response to the rare
presentation was significantly stronger than the response to the
same ITD when frequent (Fig. 3A,B) (one-tailed ttest, p⬍0.001
for both stimuli). Note that it is not only the average spike rate
that is larger in responses to rare stimuli, but also the response
profile is different, as can be seen in the poststimulus time histo-
gram in Figure 3, Cand D. For example, an inhibitory window,
which is apparent in the common responses (Fig. 3D, black line,
arrow), is absent in the rare responses (Fig. 3D, gray line). The
slight differences between the spontaneous firing rates of the rare
and common responses, which can be seen in Figure 3, Cand D
(see also Fig. 5C,D), are caused by small fluctuations in the base-
line activity that occurred on a time scale of several minutes. In
most cases (97%), these differences did not reach a significant
level (ttest, p⬍0.05).
A summary of the results from all sites (n⫽43) measured in
the AGFs is shown in Figure 4. For each test, two SIs and a single
NI were calculated (see Materials and Methods). Tests were di-
vided into three categories according to the difference between
ITD values of the two stimuli: smaller than 30
␮
s (Fig. 4A), be-
tween 40 and 60
␮
s (Fig. 4 B), and larger than 60
␮
s (Fig. 4C). The
left column in Figure 4 presents the scatterplots of SI
1
versus SI
2
for all tests. A point appearing in the first quadrant (within the
two dotted lines) implies stronger responses to the rare appear-
ance of both stimuli. However, as pointed by Ulanovsky et al.
(2003), any point above the diagonal line implies SSA: if the
response to stimulus 1 when rare is stronger than the response to
the same stimulus when common (SI
1
⬎0) and the adaptation is
only activity dependent, it is expected that the response to stim-
ulus 2 when rare will be smaller than when common (SI
2
⬍0) by
an amount that is equal to SI
1
(i.e., the point is expected to be on
the diagonal). In all three cases (Fig. 4A–C), a large number of
points were within the first quadrant and the majority of points
were significantly above the diagonal lines (sign test; p⬍0.005)
indicating the widespread presence of SSA. The distributions of
the neural indices for the different conditions are presented in the
middle column of Figure 4. Evidently, a tendency to respond
stronger to rare stimuli (positive NI) appeared in all three condi-
tions (one-tailed ttest, p⬍0.0001). The averaged PSTH of the
normalized responses to rare stimuli (Fig. 4, right column, gray
line) is compared with the average PSTH of the responses to the
frequent stimuli (black line). The preferred response to rare pre-
sentations was apparent in all cases. The difference between the
average rare and common responses increased systematically
with the increase in the gap between the ITD values of the two
stimuli.
To examine whether SSA in the AGFs can be elicited by a
different acoustic feature rather than ITD, we measured re-
sponses to frequency oddball stimulation. Here the stimulus was
a narrow noise band (1 kHz bandwidth); stimulus 1 differed from
stimulus 2 only by the center frequency (CF) (see Materials and
Methods). A frequency gap of 2 kHz between the two center
frequencies was used in these experiments. An example from a
single recording site in the AGFs is shown in Figure 5. In this
example, the center frequencies of stimulus 1 and 2 were 2 and 4
kHz, respectively. In both cases, the responses elicited by rarely
presented stimuli were significantly larger than those elicited by
common stimuli (Fig. 5A,B). This effect was most dramatic for a
stimulus of 2 kHz in which a common stimulus induced an aver-
age inhibitory response followed by a late excitatory response
whereas the rare stimulus induced a clear excitatory response
throughout the duration of the stimulus (Fig. 5C).
The results from 40 sites tested for a center frequency gap of 2
kHz are summarized in Figure 6. Similarly to the ITD tests, the
majority of sites were significantly above the diagonal line (sign
test, p⬍0.001) (Fig. 6A). The NIs distribution was positively
biased (ttest, p⬍10
⫺5
) (Fig. 6B), and the population PSTH of
responses to the rare stimuli was above the population PSTH of
responses to the common stimuli (Fig. 6C). Thus, we conclude
that SSA in the AGFs can be induced by frequency changes as well
as by ITD changes. The best frequency of the population of neu-
rons used in this analysis ranged between 3 and 8 kHz. Therefore,
a difference of 2 kHz corresponded to a normalized frequency
difference [defined as ⌬f⫽(f
2
⫺f
1
)/( f
2
⫻f
1
)
1/2
) of 0.71– 0.25.
We did not attempt smaller frequency differences in the AGFs.
The majority of the analyzed population of responses was
Figure 5. Example of a single AGF site response to a frequency oddball test. A, Dot raster
showing 40 responses to stimulus 1 (CF, 2 kHz). The bottom 20 rows show responses to the
rarely presented sound (embedded in a sequence of sounds with a CF of 4 kHz). The top 20 rows
show randomly picked responses to the same sound (CF, 2 kHz) frequently presented. B, The
average response to stimulus 1 and stimulus 2 when common (black bars) are compared with
the average response to the same stimuli when rare (gray bars). Error bars represent SE. C,D,
Poststimulus time responses to stimulus 1 (C) and to stimulus 2 (D) are shown (lines are
smoothed for display). Gray lines designate responses to the rare presentation; black lines
designate responses to the frequent presentation. The shaded area indicates the onset and
duration of sound stimulation.
1526 •J. Neurosci., February 6, 2008 •28(6):1523–1533 Reches and Gutfreund •Specific Adaptation in the Barn Owl

obtained from multiunit recordings (Figs. 4, 6, black dots).
Therefore, we analyzed and displayed single-unit data separately
to verify that the SSA reported above is not a particular outcome
of the multiunit recordings. Figure 7Ashows the population av-
erage PSTHs of responses to rare and com-
mon frequencies recorded only from well
isolated single units (see Materials and
Methods) (n⫽17). Figure 7Bshows the
single-unit responses to rare and common
ITDs (n⫽19). In both cases the average
response to rare stimuli was larger than the
average response to common stimuli and
the distribution of the NIs (insets) was pos-
itively biased (ttest, p⬍10
⫺4
). The stim-
ulus indices calculated from these single
units (Figs. 4, 6, left column, gray dots)
were evenly distributed among the multi-
unit data (black dots). Thus, we conclude
that SSA in the AGFs is expressed in single
as well as multiunit recordings. Recordings
from single units in the OT (n⫽13)
yielded a similar agreement between multiunit and single-unit
data (data not shown).
SSA in the OT
Next we characterized the responses of neurons in the OT to the
oddball stimulus, testing either frequency or ITD changes. The
scatterplots of SI
1
versus SI
2
, obtained from all recording sites in
the OT where an oddball ITD test was performed (n⫽74) and
from all sites in the OT where an oddball frequency test was
performed (n⫽29), are shown in Figure 8, Aand B, respectively.
Both these acoustic features gave rise to SSA effects in the major-
ity of neurons (sign test, p⬍10
⫺4
). Thus, we conclude that SSA
of ITD and of frequency is expressed in the neural responses of
tectal neurons, as was shown in AGF neurons (Figs. 4, 6).
The appearance of a rare stimulus in the oddball design is
probabilistic, resembling the arrival of stimuli in nature. It is
possible that this feature of the oddball design is essential to elicit
the SSA effects recorded above. To test this hypothesis we used a
CO stimulation design (see Materials and Methods) (Fig. 2B)as
opposed to the stochastic oddball stimulus. The results of the CO
frequency tests in the OT are summarized in Figure 9. CF values
of the two stimuli were separated by a gap of either 660 Hz (Fig.
9A), 1330 Hz (Fig. 9B), or 2000 Hz (Fig. 9C). The bandwidth of
the stimuli was maintained at 1 kHz, implying a substantial over-
lap between the frequency bands at the small gap of 660 Hz. For
frequency gaps of 2000 Hz and 1330 Hz, the average response to
the first stimulus in a sequence of 10 identical stimuli was signif-
icantly stronger than the average response to the last stimulus in
the sequence (ttest, p⬍0.05) (Fig. 9B,C), indicating the ten-
dency of tectal neurons to specifically adapt to the stimulus fre-
quency. A frequency gap of 660 Hz did not achieve a significant
difference. Note the rapid adaptation in all three conditions,
reaching approximately the steady-state level after one novel
stimulus (Fig. 9, left column).
To compare the time course of adaptation with that presented
in the probabilistic stimulation we normalized and averaged the
neural responses to three groups of stimuli in the oddball test: (1)
frequent stimuli that directly preceded a rare event and (2, 3) the
two consecutive frequent stimuli that immediately followed a
rare event. The average response to the first stimulus after a single
display of a rare ITD (Fig. 8A, inset) or a rare frequency (Fig. 8B,
inset) was significantly stronger than the average response to the
subsequent stimulus (second stimulus after the rare event; ttest,
p⬍0.01). The average response to this second stimulus, however,
in both ITD and frequency tests was not significantly different
from the average response to the stimulus directly preceding a
Figure 6. Summary of frequency oddball tests from all sites recorded in the AGFs. Results are shown for frequency gaps of 2
kHz. A, Scatterplot of SI
1
versus SI
2
. Gray points designate recordings from verified single units. B, Histogram showing the
distribution of NIs. C, PSTHs of the averaged normalized response to a rare stimulus (gray line) and to a frequent stimulus (black
line). The format is as in Figure 4.
Figure 7. Results from verified single-unit recordings in the AGFs. A, Normalized and aver-
aged PSTHs of single unit responses to the frequency oddball test with frequency gaps of 2 kHz.
B,Normalizedand averagedPSTHs of single-unitresponses totheITD oddballtest withITDgaps
of 20 – 60
␮
s. The average response to the rare stimulus is designated by the gray line and the
averageresponseto thecommonstimulus isdesignated by theblack line.Thebar intheleft plot
represents the duration of stimulation. The insets depict the histograms of the NIs distribution
calculated from the population of single units. The black vertical line marks the zero axis (NI, 0).
Both distributions significantly deviate from zero (ttest, *p⬍10
⫺4
).
Figure 8. Summary of results from oddball tests in the OT. A, Scatterplot of SI
1
versus SI
2.
of
ITD oddball tests with 20 –40
␮
s gaps between the ITD of stimulus 1 and stimulus 2. B, Scat-
terplot of SI
1
versus SI
2
obtained from frequency oddball tests with a 2 kHz gap between the
center frequency of stimulus 1 and stimulus 2. The number of points above and below the
diagonal line are shown in the bottom right corner. The dashed lines mark the first quadrant
where both SIs are positive. All points represent multiunit recordings. The insets show the
population average response to the stimulus that directly preceded a rare event (left bar) and to
the first and second stimuli that immediately followed a rare event (middle bar and right bar,
respectively). The gap in the histograms represents the position of the rare event in the se-
quence. The error bars designate the SE.
Reches and Gutfreund •Specific Adaptation in the Barn Owl J. Neurosci., February 6, 2008 •28(6):1523–1533 • 1527

rare event. These results suggest that the ad-
aptation occurred on a fast time scale, sim-
ilar to the adaptation observed in the con-
stant order tests, and that a single different
event in the sequence was sufficient to ini-
tiate a recovery from SSA. The degree of the
effect was substantially smaller than in the
constant order tests (Figs. 9, 10), where
the recovery was initiated by a sequence of
10 preceding events.
To quantify the size of the SSA effect, we
calculated two indices similar to the oddball
paradigm (see Materials and Methods).
Scatterplots of the SIs (Fig. 9, center col-
umn) and histograms of the NIs (inset)
were consistent with response averages –
the two larger frequency gaps obtained an
NI distribution significantly shifted toward
positive values (ttest, p⬍0.01 and p⬍
0.001 for 1330 Hz and 2000 Hz, respec-
tively), whereas a frequency difference of
660 Hz did not achieve a significant devia-
tion from zero. It is evident from the PSTHs
depicted in the right column that the differ-
ence between the responses to frequent and
rare stimuli increased systematically with
the increase in frequency gap.
Figure 10 shows the results from the ex-
periments in which only the ITD value was
interchanged between the two parts of the
frozen sequence. The ITD gap was either 20
␮
s (Fig. 10A)or40
␮
s (Fig. 10B). It can be
seen that the average response to the first
stimulus in a sequence was significantly
stronger than the average response to the
last stimulus (ttest, p⬍0.0005). This result
is also demonstrated by the positive distri-
bution of the neural indices (ttest, p⬍
0.00005) (Fig. 10, middle column) and by
the differences in the average response pro-
files shown in Figure 10 (right column).
Both 20 and 40
␮
s disparities elicited stron-
ger average responses to rare stimuli. Simi-
lar to the frequency domain, a tendency for a stronger SSA effect
with increased ITD disparity was apparent. In summary, we did
not observe any qualitative differences between the adaptation in
the oddball design and the adaptation in the CO design. In the
following further characterization of SSA in the midbrain path-
way, we used the CO design exclusively.
SSA of ITD and frequency in the ICX
To track the origin of the SSA that appeared in the OT, we re-
corded from the primary source of auditory input to the OT, the
ICX (Knudsen and Knudsen, 1983). Stimulus-specific adapta-
tion to frequency was evident in ICX neurons (Fig. 11). All three
frequency gaps tested revealed a significant difference between
the average response to the first stimulus compared with the
average response to the last stimulus (ttest, p⬍0.05, 0.01, and
0.001 for frequency difference of 660, 1330, and 2000 Hz, respec-
tively). Similar to the results obtained in the OT, SSA effects were
larger for wider frequency gaps (Fig. 11B). Thus, frequency-
specific adaptation in the OT can largely be explained by adapta-
tion occurring at earlier stations along the pathway. This, how-
ever, was not the case for ITD-specific adaptation. In the sampled
group of neurons from the ICX (Fig. 12), no ITD SSA effect was
observed as is indicated by the constant average response (Fig. 12,
left column), by the distribution of neuron indices, which was not
significantly different from zero (Fig. 12, middle column) ( p⬎
0.05), and by the overlapping average PSTHs (Fig. 12, right col-
umn). The lack of ITD SSA in the ICX was apparent even when
increasing the gap between the ITD values of the two stimuli from
20
␮
s (Fig. 12A)to40
␮
s (Fig. 12B). Results acquired in the ICX
using the oddball paradigm (data not shown) agreed with the
above results, namely ITD SSA was not visible in the ICX.
SSA of sound intensity and ILD in the midbrain
If SSA in the OT is a basis for novelty detection, we would expect
that the phenomenon will be manifested in a wide range of acous-
tic features. To test this hypothesis we characterized the general-
ity of SSA in the midbrain by testing the CO stimulus design with
yet two additional acoustic features: the ABSI and the ILD. In the
first test (Fig. 13A), the two stimuli differed only in the ABSI. The
left side of the bar chart in Figure 13Ashows the average re-
Figure9. Summaryof theresults fromfrequencyconstant ordertests inthe OT.Resultsfrom testswith frequencygapsof 660,
1330, and 2000 Hz are shown in A,B, and Crespectively. Histograms in the left column show the population response (normal-
ized and averaged across all recording sites) to the constant order sequence of 20 stimuli. The first 10 bars present responses to
the stimuli with the lower CF (relative to the best frequency) and the last 10 bars present responses to the higher CF. Error bars
indicate SEs. The SIs scatterplots are shown in the middle column. The number of points above and below the diagonal line are
shown in the bottom right corner. Gray points designate recordings from single units. Insets depict the NI distributions. The
abscissa of the NI histogram is between ⫺0.2 and 0.55 in all histograms. The right column shows the population PSTHs,
normalized and averaged. Gray lines designate the population response to the rare stimulus and black lines designate the
population response to the common stimulus. The bar in the top plot represents the duration of stimulation.
1528 •J. Neurosci., February 6, 2008 •28(6):1523–1533 Reches and Gutfreund •Specific Adaptation in the Barn Owl

sponses to the weak stimulus (10 –15 dB above threshold),
whereas the right side of the histogram shows the average re-
sponses to the loud stimulus (30 dB above the weak stimulus).
The average response to the first stimulus in a block was signifi-
cantly stronger than the response to the last stimulus for both
loud and weak sounds (Fig. 13A,C)(ttest, p⬍10
⫺6
), and the
distribution of the neural indices was significantly biased to pos-
itive values (Fig. 13B)(ttest p⬍10
⫺8
). Thus, tectal neurons
undergo specific adaptation to the intensity of the sound. Inter-
estingly, this result was not visible in neurons from the ICX. The
mean NI was not significantly different from zero, and the re-
sponses to the first sound in a sequence of 10 identical stimuli
were not significantly different from the responses to the last
sound in the sequence (Fig. 13D–F). Therefore, ABSI SSA ap-
peared in the OT and not in the ICX.
In the second test, the two stimuli differed only in ILD. The
results of this test were qualitatively similar to the results obtained
for ABSI and ITD tests, namely an SSA effect was evident in the
OT and not in the preceding auditory sta-
tion, the ICX. The average response to the
first stimulus in a block was significantly
stronger than the response to the last stim-
ulus for both contralateral-ear-leading and
ipsilateral-ear-leading sounds (Fig. 13G,I)
(ttest, p⬍0.005), and both NIs and SIs
were significantly biased toward positive
values (Fig. 13H)(ttest, p⬍10
⫺5
; sign
test, p⬍10
⫺4
). In the ICX, however, rare
and frequent stimuli elicited identical re-
sponses and the mean NI was not signifi-
cantly different from zero (Fig. 13J–L).
A summary of the mean NIs measured
in the three different brain structures (OT,
ICX, and AGFs) is shown in Figure 14. In
the OT, all four acoustic features (ITD,
ILD, ABSI, and frequency) elicited signifi-
cant SSAs. At the same parameter gaps that
elicited clear SSAs in the OT, SSAs were not
present in the ICX. Frequency was an ex-
ceptional feature: only SSA for frequency
was manifested both in the OT and the
ICX. In the forebrain AGFs, both ITD and
frequency elicited SSAs. We did not test for
ABSI or ILD SSAs in the forebrain.
A close look at the onsets of the average
responses permits the inspection of the relative population delays
of responses to rare versus common stimuli. Figure 15Ashows
the onsets (first 40 ms) of the population average responses in the
OT for ABSI, frequency, ILD, and ITD tests. The bottom gray line
is the difference between the responses to rare (top gray line) and
common (black line) stimuli. All curves were smoothed with a
sliding average window of 6 ms. The time of onset was estimated
as the point where the curve crossed the threshold, defined as
30% of the peak plus 1.5 times the SD of the spontaneous activity.
It is evident that for all four acoustic parameters tested, the aver-
age population responses to the rare and to the common stimuli
initially overlapped. The difference between the responses initi-
ated several ms after the onset of the population responses (Fig.
15A, compare gray and black ticks). This short delay in the initi-
ation of the difference may reflect a circumstance where SSA
occurs only in a subpopulation of neurons in the OT with long
response latencies. To check this possibility, we correlated the
response latency with the SI for each stimulus condition. In all
conditions the SI did not increase significantly with the response
latency of the neurons (ANOVA Ftest, p⬎0.05). Three examples
are shown in Figure 15B: the 2 kHz frequency gap, 40
␮
s ITD gap,
and 30 dB ABSI gap. Our results suggest that the enhancing effect
of SSA is not initiated together with response onset, but shortly
afterward (⬃5 ms).
Discussion
Stimulus-specific adaptation in the auditory system
Adaptation is a ubiquitous property of neurons in the auditory
system. Most types of adaptations described in the literature de-
pend on the activation history of the neuron more than on spe-
cific features of the stimulus (Calford and Semple, 1995; Brosch
and Schreiner, 1997; McAlpine et al., 2000; Ingham and McAlp-
ine, 2004; Furukawa et al., 2005; Wehr and Zador, 2005; Gut-
freund and Knudsen, 2006). A different, higher-level adaptation
is SSA, an adaptation to the history of the stimulus rather than to
the activity of the neuron (Ulanovsky et al., 2003, 2004). Neurons
Figure10. Summaryof resultsfrom ITDconstantorder testsin OT.Resultsfrom constantorder tests presentedwith anITD gap
of 20
␮
s are shown in Aand results from tests with an ITD gap of 40
␮
s are shown in B. The format is as in Figure 8.
Figure 11. Summary of results from frequency constant order tests in the ICX. A, The popu-
lation response (normalized and averaged) to the constant order sequence with a frequency
gap of 2 kHz. The first 10 bars present responses to the stimuli with the lower CF (relative to the
bestfrequency)and thelast10 barspresentresponses tothehigher CF.Errorbars indicateSE.B,
The NIs are shown versus the frequency gap used in the test. The line connects the average
points at each frequency gap.
Reches and Gutfreund •Specific Adaptation in the Barn Owl J. Neurosci., February 6, 2008 •28(6):1523–1533 • 1529

that adapt to specific features of the stimu-
lus integrate sensory information to create
a model of the world, responding stronger
to novel features in the environment. The
computations to achieve such stimulus-
specific responses require a network to
compare between current and past stimu-
lus conditions (Abbott et al., 1997; Eytan et
al., 2003).
In the auditory system, SSA has been
described in the auditory cortex (Ul-
anovsky et al., 2003, 2004) and in the infe-
rior colliculus (IC) (Malone and Semple,
2001). However, the stimulus protocol
used to elicit SSA in the cortex and in the IC
differed substantially, obscuring direct
comparison between the two phenomena.
Moreover, Malone and Semple (2001)
showed that the auditory response of many
neurons in the IC cannot be predicted sim-
ply by the cell’s discharge history. This,
however, does not necessarily imply SSA as
defined here because the adaptation may
be determined by processes other than dis-
charge rates (e.g., spike timing, subthresh-
old activity, etc.). The stimulus protocol
and analysis used by Ulanovsky et al.
(2003) avoids this difficulty by using bidi-
rectional comparison; adaptation is con-
sidered specific to the stimulus if the re-
sponses to both stimulus 1 and 2, when rare, are stronger than the
responses to the same stimuli when common, a state that cannot
be achieved if the activity alone determines the adaptation. Here
we used the same analysis used by Ulanovsky et al. (2003) to
measure SSA directly. The adaptation we report in the OT and
AGFs resembles the SSA in the auditory cortex in several aspects:
in the cortex, adaptation develops over a time scale of seconds,
comparable with the time scale we report here (Figs. 9 –11, 13).
Moreover, in the cortex the adaptation is extremely specific to the
frequency of the stimulus; a very small frequency gap, compared
with the tuning width of the neurons, was sufficient to induce a
significant SSA. In the present work, although we did not system-
atically check the level of specificity, we show that ITD gaps of 20
␮
s, which are finer than the response range of typical neurons in
the OT, elicited SSA effects (Fig. 10 A). Another striking similarity
is the abrupt appearance of SSA in the pathway. Neurons in the
medial geniculate nucleus, which provide inputs to the auditory
cortex, did not exhibit SSA (Ulanovsky et al., 2003). Similarly,
neurons in the ICX, the source of auditory information to the OT,
did not show SSA for ITD, ILD and ABSI (Figs. 12, 13). An
exception to this was the frequency SSA, which was observed in
ICX neurons. Interestingly, SSA to frequency was recently re-
ported in a sub population of IC neurons in rats (Perez-Gonzalez
et al., 2005).
Implication of SSA in the localization pathway
The SSA in the OT was found to be relatively invariant to the
feature tested: in all cases (ITD, ILD, ABSI, and frequency) the
adaptation was stimulus specific, developed rapidly (1 trial) (Figs.
9, 10, 13) and the adaptation memory was at least 1 s long (we did
not attempt other ISIs). This similarity is especially striking tak-
ing into account that the four features are represented and com-
puted in marginally different ways: ITD and ILD, the two primary
binaural localization cues, are processed in parallel in two sepa-
rate and independent brainstem pathways that converge in the
lateral shell of the central nucleus of the inferior colliculus
(ICCls) (Takahashi et al., 1984; Takahashi and Konishi, 1988;
Adolphs, 1993; Albeck and Konishi, 1995) to induce selectivity to
spatial locations, which is then further refined along the pathway
to the ICX and on to the OT (Moiseff and Konishi, 1983; Pena
and Konishi, 2001). Frequency separation is maintained in both
ascending auditory pathways from the cochlea up to the level of
the ICCls where information across frequency-specific channels
is combined (Euston and Takahashi, 2002). Sound-level infor-
mation is presumably manifested in the response levels of the
ascending pathways. The fact that all four independent acoustic
features showed a qualitatively similar pattern of adaptation sug-
gests that SSA is an important property in the neural representa-
tion of the auditory scene. Possibly, this property underlies the
owl’s ability to attend and orient abruptly to novel events. We
hypothesize that similar auditory SSA exists in the superior col-
liculus of mammalian species. However, to our knowledge this
has not been studied. Interestingly, we also found strong spatial
SSA in the OT for visual stimuli (data not shown), suggesting that
SSA in the OT is a multisensory phenomenon.
Mechanisms of SSA
Several types of adaptation mechanisms have been described,
including synaptic depression (Wehr and Zador, 2005), delayed
inhibition (Schmidt and Perkel, 1998; Tan et al., 2004; Wehr and
Zador, 2005), and intrinsic cellular properties such as voltage- or
calcium- dependent potassium currents (Gollisch and Herz,
2004). Any mechanism of adaptation can be involved in generat-
ing SSA provided that the two stimuli activate separate paths to
the recorded neuron and that the adaptation acts at a level where
the activation is significantly separated (Eytan et al., 2003). Pre-
Figure 12. Summary of results from ITD constant order tests in the ICX. A, Results from tests with ITD gaps of 20
␮
s. B, Results
from tests with ITD gaps of 40
␮
s. Histograms in the left column show the population response (normalized and averaged across
all recording sites) to the constant order sequence of 20 stimuli. The first 10 bars present responses to the stimuli with ITD values
left of the best ITD and the last 10 bars present responses to ITD values right of the best ITD. Error bars indicate SEs. The NI
distributionandthe SIsscatterplots(insets) areshown in themiddle column.Thenumber ofpoints above andbelow thediagonal
lineareshown inthe toprightand bottomleft cornersofthe scatterplots,respectively. Rightcolumnshows thepopulation PSTHs,
normalized and averaged. Gray lines designate the population response to the rare stimulus and black lines designate the
population response to the common stimulus. The bar in the top plot represents the duration of stimulation.
1530 •J. Neurosci., February 6, 2008 •28(6):1523–1533 Reches and Gutfreund •Specific Adaptation in the Barn Owl

vious studies in barn owls have reported adaptation effects in the
afferent auditory pathway to the OT (Wagner et al., 2002; Spitzer
et al., 2004; Gutfreund and Knudsen, 2006). However, in all of
these cases, the adaptation was relatively short lasting, incapable
of accounting for the 1 s ISI used in the current study.
A key observation in this work was the
qualitative difference between the OT and
its main source of auditory input, calling
for at least two separate sites of adaptation
to account for the SSA effects. Adaptation
acting at frequency-specific lower levels of
the auditory pathway could explain fre-
quency SSA but is unlikely to explain ITD,
ILD, or ABSI SSA. One possibility is that
the adaptation mechanism of the latter is a
short term synaptic depression acting at
ICX-OT synapses, similar to depression at
thalamocortical synapses proposed to un-
derlie SSA in the cortex (Katz et al., 2006).
However, the observation shown in Figure
15 that the SSA in the OT, on average, tends
to develop several milliseconds after the
onset of response suggests that the SSA is
happening not at the direct pathway to the
tectal neurons, but involves an additional
level of processing either internal in the OT
or external arriving from other parts of the
brain.
Origin of SSA
Among the indirect pathways to the OT,
the extensively studied isthmotectal loop
has been suggested to be involved in spatial
attention (Marin et al., 2005). Nucleus
isthmi, the homolog of the mammalian nu-
cleus parabigeminalis (Diamond et al.,
1992), receives auditory and visual affer-
ents from tectal neurons, and send cholin-
ergic projections back to the tectum (Mac-
zko et al., 2006). This may constitute a
winner-take-all network that enhances the
sensitivity of tectal neurons to the location
of the most salient stimulus (Marin et al.,
2005; Wang et al., 2006; Knudsen, 2007).
Adaptation in the isthmotectal loop has not
been reported so far. In principle, because
of the high spatial precision, such adapta-
tion may induce tectal SSA in ITD and ILD,
two cues that are topographically repre-
sented in the OT. This mechanism, how-
ever, cannot account for SSA of nonspatial
parameters such as intensity.
An additional indirect auditory pathway
to the OT is conveyed through the AGFs
(Cohen et al., 1998). This forebrain nucleus
has been shown to be involved in auditory
working memory (Knudsen and Knudsen,
1996a), a vital feature for specific adapta-
tion of the time scales presented here.
Moreover, a recent study has shown that
focal electrical microstimulation in the
AGFs enhances tectal auditory responses in
a space-specific manner (Winkowski and
Knudsen, 2006). Such top-down effects have been suggested to be
involved in control of spatial attention in mammals and birds
(Moore and Fallah, 2004; Winkowski and Knudsen, 2006). These
findings raise the possibility that SSA originates in forebrain net-
works, giving rise to top-down signals that enhance responses to
Figure 13. Results of additional acoustic features in the OT and ICX. A, Population average response to a constant order
sequence. The first 10 bars show the average responses to a sequence of sounds with low ABSI, the second 10 bars show the
responses to a sequence of sounds with a higher ABSI (30 dB relative to the ABSI of the low sound). B, Scatterplot of SI
1
versus SI
2
of the same neurons as in A. The gray points designate recordings from single units. The inset shows the distribution of the NIs.
Theabscissaof theNIhistogram isbetween⫺0.2 and0.55 in allhistograms. C, Thepopulation PSTHs,normalizedand averaged,
are shown for the rare stimulus (gray line) and for the frequent stimulus (black line). The responses to the low-intensity sound
andtothe high-intensitysoundare shownseparatelyin thetopand bottomplots,respectively. D–F,Resultsfrom neuronsinthe
ICX tested under the same stimulus conditions as in A–C.D, The population response to the constant order sequence. E, NI distribution
and scatterplot of SIs. F, Population PSTH responses to rare (gray line) and frequent (black line) sound intensities. Responses to both low
and high intensities are averaged together. G, Population response to a constant order sequence in which the ILD of the first 10 stimuli
differed by 15 dB (toward contra lateral ear louder) from the ILD displayed in the second 10 stimuli. H, The scatterplot of SIs and the
distributionofthe NIsof allILD tests.The graypointsdesignate recordingsfrom singleunits. I,The averageresponse torare(gray line)and
frequent(blackline) stimulusareshown separatelyforthe loudercontralateralear (topplot)and thelouderipsilateral ear(bottomplot).
J–L, Results from neurons in the ICX under the same stimulus conditions as in G–I.
Reches and Gutfreund •Specific Adaptation in the Barn Owl J. Neurosci., February 6, 2008 •28(6):1523–1533 • 1531

rare stimuli in the OT. In agreement with this model, a similar
stimulation paradigm used in the OT revealed frequency and ITD
SSA in the AGFs (Figs. 3– 6). Interestingly, the AGFs project to
the isthmi pars parvocellularis (Knudsen et al., 1995), a connec-
tion that may enable forebrain control of tectal sensitivity
through the isthmotectal system. The involvement of the fore-
brain and nucleus isthmi in the generation of SSA is yet to be
validated in future experimental work.
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