Sound Signals Many physical objects emit sounds when they are
excited (e.g. hit or rubbed). Sounds are just pressure waves
rippling through the air, but they carry a lot of information about
the objects that emitted them. (Example: what are these two
objects? Which one is heavier, object A or object B ?) The sound
(or signal) emitted by an object (or system) when hit is known as
the impulse response. Impulse responses of everyday objects can be
quite complex, but the sine wave is a fundamental ingredient of
these (or any) complex sounds (or signals). Many physical objects
emit sounds when they are excited (e.g. hit or rubbed). Sounds are
just pressure waves rippling through the air, but they carry a lot
of information about the objects that emitted them. (Example: what
are these two objects? Which one is heavier, object A or object B
?) The sound (or signal) emitted by an object (or system) when hit
is known as the impulse response. Impulse responses of everyday
objects can be quite complex, but the sine wave is a fundamental
ingredient of these (or any) complex sounds (or signals).
Slide 4
Vibrations of a Spring- Mass System Undamped 1. F = -ky (Hookes
Law) 2. F = m a (Newtons 2 nd ) 3. a = dv/dt = d 2 y/dt 2 -k y = m
d 2 y/dt 2 y(t) = y o cos(t k/m) Damped 4. ky r dy/dt = d 2 y/dt 2
y(t) = y o e (-rt/2m) cos(t k/m-(r/2m) 2 ) Undamped 1. F = -ky
(Hookes Law) 2. F = m a (Newtons 2 nd ) 3. a = dv/dt = d 2 y/dt 2
-k y = m d 2 y/dt 2 y(t) = y o cos(t k/m) Damped 4. ky r dy/dt = d
2 y/dt 2 y(t) = y o e (-rt/2m) cos(t k/m-(r/2m) 2 ) Dont worry
about the formulae! Just remember that mass-spring systems like to
vibrate at a rate proportional to the square-root of their
stiffness and inversely proportional to their weight.
http://auditoryneuroscience.com/acoustics/simple_harmonic_motion
Slide 5
Resonant Cavities In resonant cavities, lumps of air at the
entrance/exit of the cavity oscillate under the elastic forces
exercised by the air inside the cavity. The preferred resonance
frequency is inversely proportional to the square root of the
volume. (Large resonators => deeper sounds). In resonant
cavities, lumps of air at the entrance/exit of the cavity oscillate
under the elastic forces exercised by the air inside the cavity.
The preferred resonance frequency is inversely proportional to the
square root of the volume. (Large resonators => deeper
sounds).
Slide 6
The Ear Organ of Corti Cochela unrolled and sectioned
Slide 7
Modes of Vibration and Harmonic Complex Tones An ideal string
would maintain the triangular shape set up when the string is
plucked throughout the oscillation. Fourier analysis approximates
such vibrations as a sum (series) of sine waves. For large numbers
of sine waves (Fourier components) the approximation becomes very
good, for an infinite number of components it is exact. Natural
sounds are often made up of sine components that are harmonically
related i.e. their frequencies are all integer multiples of a
fundamental frequency. An ideal string would maintain the
triangular shape set up when the string is plucked throughout the
oscillation. Fourier analysis approximates such vibrations as a sum
(series) of sine waves. For large numbers of sine waves (Fourier
components) the approximation becomes very good, for an infinite
number of components it is exact. Natural sounds are often made up
of sine components that are harmonically related i.e. their
frequencies are all integer multiples of a fundamental frequency.
http://auditoryneuroscience.com/?q=acoustics/modes_of_vibration
Slide 8
Click Trains & the 30 Hz Transition At frequencies up to ca
30 Hz, each click in a click train is perceived as an isolated
event. At frequencies above ca 30 Hz, individual clicks fuse, and
one perceives a continuous hum with a strong pitch. At frequencies
up to ca 30 Hz, each click in a click train is perceived as an
isolated event. At frequencies above ca 30 Hz, individual clicks
fuse, and one perceives a continuous hum with a strong pitch. time
sound pressure
https://mustelid.physiol.ox.ac.uk/drupal/?q=pitch/click_train
Slide 9
The Impulse (or Click) The ideal click, or impulse, is an
infinitesimally short signal. The Fourier Transform encourages us
to think of this click as an infinite series of sine waves, which
have started at the beginning of time, continue until the end of
time, and all just happen to pile up at the one moment when the
click occurs.
Slide 10
Basilar Membrane Response to Clicks
http://auditoryneuroscience.com/ear/bm_motion_2
Slide 11
Why Click Trains Have Pitch If we represent each click in a
train by its Fourier Transform, then it becomes clear that certain
sine components will add (top) while others will cancel (bottom).
This results in a strong harmonic structure.
Slide 12
Basilar Membrane Response to Click Trains
auditoryneuroscience.com | The Ear
Slide 13
Cariani & Delgutte AN recordings Phase locking to Modulator
(Envelope) Phase locking to Carrier AN Phase Locking to Artificial
Single Formant Vowel Sounds
https://mustelid.physiol.ox.ac.uk/drupal/?q=ear/bm_motion_3
Slide 14
Vocal Folds in Action auditoryneuroscience.com |
Vocalizations
Slide 15
Articulation Articulators (lips, tongue, jaw, soft palate) move
to change resonance properties of the vocal tract.
auditoryneuroscience.com | Vocalizations Launch
SpectrogramSpectrogram
Slide 16
Harmonics & formants of a vowel Harmonics Formants
Slide 17
Formants Arise From Resonances in the Vocal Tract Speakers
change formant frequencies by making resonance cavities in their
mouth, nose and throat larger or smaller.
Slide 18
The Neurogram As a crude approximation, one might say that it
is the job of the ear to produce a spectrogram of the incoming
sounds, and that the brain interprets the spectrogram to identify
sounds. This figure shows histograms of auditory nerve fibre
discharges in response to a speech stimulus. Discharge rates depend
on the amount of sound energy near the neurons characteristic
frequency.
Slide 19
The discharges of cochlear nerve fibres to low- frequency
sounds are not random; they occur at particular times (phase
locking). Evans (1975) Phase Locking
https://mustelid.physiol.ox.ac.uk/drupal/?q=ear/phase_locking
Slide 20
Quantifying Phase-Locking Phase locking is usually measured as
a vector strength, also known as synchronicity index (SI). To
calculate this, a Period Histogram of the neural response is
normalized, and each bin of the histogram is thought of as a
vector. The SI is given by length of the vector sum for all bins.
Phase locking is usually measured as a vector strength, also known
as synchronicity index (SI). To calculate this, a Period Histogram
of the neural response is normalized, and each bin of the histogram
is thought of as a vector. The SI is given by length of the vector
sum for all bins.
Slide 21
Phase Locking Limits AN fibres are unable to phase lock to
signal fluctuations at rates faster than 3 kHz. This is due to
low-pass filtering in the hair cell receptors. AN fibres are unable
to phase lock to signal fluctuations at rates faster than 3 kHz.
This is due to low-pass filtering in the hair cell receptors. Hair
Cell Receptor PotentialsAN fibre Responses Synchrony Index
Frequency (kHz) 1000 Hz 2000 Hz 3000 Hz 4000 Hz
Slide 22
Frequency Coding The Place Theory stipulates that frequencies
are encoded by activity across the tonotopic array of fibers in the
AN, as well as in tonotopic nuclei along the lemniscal auditory
pathway. The Timing Theory posits that temporal information
conveyed through phase locking provides the dominant cue to
frequency information. Neither the Place nor the Timing Theory can
account for all psychophysical data The Place Theory stipulates
that frequencies are encoded by activity across the tonotopic array
of fibers in the AN, as well as in tonotopic nuclei along the
lemniscal auditory pathway. The Timing Theory posits that temporal
information conveyed through phase locking provides the dominant
cue to frequency information. Neither the Place nor the Timing
Theory can account for all psychophysical data
Slide 23
Missing Fundamental Sounds
http://auditoryneuroscience.com/topics/missing-fundamental
Slide 24
The Pitch of Complex Sounds (Examples)
Slide 25
The Periodicity of a Signal is the Major Determinant of its
Pitch Iterated rippled noise can be made more or less periodic by
increasing or decreasing the number of iterations. The less
periodic the signal, the weaker the pitch.
Slide 26
Sinusoidally Amplitude Modulated (SAM) Tones Example with
carrier frequency c:5000 Hz, modulator frequency f:400 Hz Make a
sinusoidally modulated tone by multiplying carrier with modulator:
sin(2 t c) (0.5 sin(2 t m) + 0.5) or by adding sine components of
frequencies c+ m, c - m 0.5 sin(2 t c) + 0.25 sin(2 t (c+m)) + 0.25
sin(2 t (c-m)) (!) The SAM tone has no energy at the modulation
frequency. Nevertheless the modulator influences the perceived
pitch. Example with carrier frequency c:5000 Hz, modulator
frequency f:400 Hz Make a sinusoidally modulated tone by
multiplying carrier with modulator: sin(2 t c) (0.5 sin(2 t m) +
0.5) or by adding sine components of frequencies c+ m, c - m 0.5
sin(2 t c) + 0.25 sin(2 t (c+m)) + 0.25 sin(2 t (c-m)) (!) The SAM
tone has no energy at the modulation frequency. Nevertheless the
modulator influences the perceived pitch.
Slide 27
AN Phase Locking to SAM Tones Medium SR fibers phase lock
better to amplitude modulation than high or low SR fibers. The
ability to phase lock to amplitude modulation declines with high
sound levels. Medium SR fibers phase lock better to amplitude
modulation than high or low SR fibers. The ability to phase lock to
amplitude modulation declines with high sound levels. Spontaneous
rate High MediumLow Sound level High Low
Slide 28
Spherical Bushy Stellate Globular Bushy Stellate Octopus
Fusiform Cell Types of the Cochlear Nucleus AVCN PVCN DCN
Slide 29
CN Phase Locking to Amplitude Modulations Certain cell types in
the CN (including Onset and some Chopper types) exhibit much
stronger phase locking to AM than is seen in their AN inputs.
Slide 30
Encoding of Envelope Modulations in the Midbrain Neurons in the
midbrain or above show much less phase locking to AM than neurons
in the brainstem. Transition from a timing to a rate code. Some
neurons have bandpass MTFs and exhibit best modulation frequencies
(BMFs). Topographic maps of BMF may exist within isofrequency
laminae of the ICc, (periodotopy). Neurons in the midbrain or above
show much less phase locking to AM than neurons in the brainstem.
Transition from a timing to a rate code. Some neurons have bandpass
MTFs and exhibit best modulation frequencies (BMFs). Topographic
maps of BMF may exist within isofrequency laminae of the ICc,
(periodotopy).
Slide 31
Periodotopic maps via fMRI Baumann et al Nat Neurosci 2011
described periodotopic maps in monkey IC obtained with fMRI. They
used stimuli from 0.5 Hz (infra-pitch) to 512 Hz (mid-range pitch).
Their sample size is quite small (3 animals false positive?) The
observed orientation of their periodotopic map (medio-dorsal to
latero- ventral for high to low) appears to differ from that
described by Schreiner & Langner (1988) in the cat
(predimonantly caudal to rostral) Baumann et al Nat Neurosci 2011
described periodotopic maps in monkey IC obtained with fMRI. They
used stimuli from 0.5 Hz (infra-pitch) to 512 Hz (mid-range pitch).
Their sample size is quite small (3 animals false positive?) The
observed orientation of their periodotopic map (medio-dorsal to
latero- ventral for high to low) appears to differ from that
described by Schreiner & Langner (1988) in the cat
(predimonantly caudal to rostral)
Slide 32
SAM tones should only activate the high frequency parts of the
tonotopically organized A1. However, activity (presumed to
correspond to the low pitch of these signals) is also seen in the
low frequency parts of A1. This activity is thought to be organized
in a concentric periodotopic map. However... SAM tones should only
activate the high frequency parts of the tonotopically organized
A1. However, activity (presumed to correspond to the low pitch of
these signals) is also seen in the low frequency parts of A1. This
activity is thought to be organized in a concentric periodotopic
map. However... Proposed Periodotopy in Gerbil A1
Slide 33
Periodotopy inconsistent in ferret cortex Nelken, Bizley,
Nodal, Ahmed, Schnupp, King (2008) J. Neurophysiol 99(4) SAM
toneshp Clickshp IRN animal 1 animal 2
Slide 34
A pitch area in primates? In marmoset, Pitch sensitive neurons
are most commonly found on the boundary between fields A1 and R.
Fig 2 of Bendor & Wang, Nature 2005
Slide 35
A pitch sensitive neuron in marmoset A1? Apparently pitch
sensitive neurons in marmoset A1. Fig 1 of Bendor & Wang,
Nature 2005 Apparently pitch sensitive neurons in marmoset A1. Fig
1 of Bendor & Wang, Nature 2005
Slide 36
Artificial Vowel Sounds
Slide 37
Bizley et al J Neurosci 2009 Responses to Artificial
Vowels
Slide 38
Pitch (Hz) Vowel type (timbre) Joint Sensitivity to Formants
and Pitch Bizley, Walker, Silverman, King & Schnupp - J
Neurosci 2009
Slide 39
Mapping cortical sensitivity to sound features Neural
sensitivity Timbre Nelken et al., J Neurophys, 2004 Bizley et al.,
J Neurosci, 2009
Slide 40
Summary Periodic Signals (click trains, harmonic complexes)
with periods between ca. 30-3000 Hz tend to have a strong pitch.
Aperiodic signals (noises, isolated clicks) have weak pitches or no
pitch at all. Speech sounds include periodic (vowels, voiced
consonants) and aperiodic (unvoiced consonants) sounds. There are
competing place and timing (temporal) theories of pitch. Place
theories depend on the representation of spectral peaks in
tonotopic parts of the auditory pathway. Some important features
(e.g. formants of speech sounds) are represented tonotopically, but
place cannot represent harmonic structure well. Timing theories
postulate that early stages of the auditory system measures spike
intervals in phase locked discharges. In midbrain and cortex pitch
appears to be represented through rate codes. Whether there are
periodotopic maps or specialized pitch areas in the central
auditory system is highly controversial. Periodic Signals (click
trains, harmonic complexes) with periods between ca. 30-3000 Hz
tend to have a strong pitch. Aperiodic signals (noises, isolated
clicks) have weak pitches or no pitch at all. Speech sounds include
periodic (vowels, voiced consonants) and aperiodic (unvoiced
consonants) sounds. There are competing place and timing (temporal)
theories of pitch. Place theories depend on the representation of
spectral peaks in tonotopic parts of the auditory pathway. Some
important features (e.g. formants of speech sounds) are represented
tonotopically, but place cannot represent harmonic structure well.
Timing theories postulate that early stages of the auditory system
measures spike intervals in phase locked discharges. In midbrain
and cortex pitch appears to be represented through rate codes.
Whether there are periodotopic maps or specialized pitch areas in
the central auditory system is highly controversial.