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<p>Integrating information from multiple sources is a crucial function of the brain.
Examples of such integration include multiple stimuli of different modalties, such
as visual and auditory, multiple stimuli of the same modality, such as auditory and
auditory, and integrating stimuli from the sensory organs (i.e. ears) with stimuli
delivered from brain-machine interfaces.</p><p>The overall aim of this body of work
is to empirically examine stimulus integration in these three domains to inform our
broader understanding of how and when the brain combines information from multiple
sources.</p><p>First, I examine visually-guided auditory, a problem with implications
for the general problem in learning of how the brain determines what lesson to learn
(and what lessons not to learn). For example, sound localization is a behavior that
is partially learned with the aid of vision. This process requires correctly matching
a visual location to that of a sound. This is an intrinsically circular problem when
sound location is itself uncertain and the visual scene is rife with possible visual
matches. Here, we develop a simple paradigm using visual guidance of sound localization
to gain insight into how the brain confronts this type of circularity. We tested two
competing hypotheses. 1: The brain guides sound location learning based on the synchrony
or simultaneity of auditory-visual stimuli, potentially involving a Hebbian associative
mechanism. 2: The brain uses a ‘guess and check’ heuristic in which visual feedback
that is obtained after an eye movement to a sound alters future performance, perhaps
by recruiting the brain’s reward-related circuitry. We assessed the effects of exposure
to visual stimuli spatially mismatched from sounds on performance of an interleaved
auditory-only saccade task. We found that when humans and monkeys were provided the
visual stimulus asynchronously with the sound but as feedback to an auditory-guided
saccade, they shifted their subsequent auditory-only performance toward the direction
of the visual cue by 1.3-1.7 degrees, or 22-28% of the original 6 degree visual-auditory
mismatch. In contrast when the visual stimulus was presented synchronously with the
sound but extinguished too quickly to provide this feedback, there was little change
in subsequent auditory-only performance. Our results suggest that the outcome of our
own actions is vital to localizing sounds correctly. Contrary to previous expectations,
visual calibration of auditory space does not appear to require visual-auditory associations
based on synchrony/simultaneity.</p><p>My next line of research examines how electrical
stimulation of the inferior colliculus influences perception of sounds in a nonhuman
primate. The central nucleus of the inferior colliculus is the major ascending relay
of auditory information before it reaches the forebrain, and thus an ideal target
for understanding low-level information processing prior to the forebrain, as almost
all auditory signals pass through the central nucleus of the inferior colliculus before
reaching the forebrain. Thus, the inferior colliculus is the ideal structure to examine
to understand the format of the inputs into the forebrain and, by extension, the processing
of auditory scenes that occurs in the brainstem. Therefore, the inferior colliculus
was an attractive target for understanding stimulus integration in the ascending auditory
pathway.</p><p>Moreover, understanding the relationship between the auditory selectivity
of neurons and their contribution to perception is critical to the design of effective
auditory brain prosthetics. These prosthetics seek to mimic natural activity patterns
to achieve desired perceptual outcomes. We measured the contribution of inferior colliculus
(IC) sites to perception using combined recording and electrical stimulation. Monkeys
performed a frequency-based discrimination task, reporting whether a probe sound was
higher or lower in frequency than a reference sound. Stimulation pulses were paired
with the probe sound on 50% of trials (0.5-80 µA, 100-300 Hz, n=172 IC locations in
3 rhesus monkeys). Electrical stimulation tended to bias the animals’ judgments in
a fashion that was coarsely but significantly correlated with the best frequency of
the stimulation site in comparison to the reference frequency employed in the task.
Although there was considerable variability in the effects of stimulation (including
impairments in performance and shifts in performance away from the direction predicted
based on the site’s response properties), the results indicate that stimulation of
the IC can evoke percepts correlated with the frequency tuning properties of the IC.
Consistent with the implications of recent human studies, the main avenue for improvement
for the auditory midbrain implant suggested by our findings is to increase the number
and spatial extent of electrodes, to increase the size of the region that can be electrically
activated and provide a greater range of evoked percepts.</p><p>My next line of research
employs a frequency-tagging approach to examine the extent to which multiple sound
sources are combined (or segregated) in the nonhuman primate inferior colliculus.
In the single-sound case, most inferior colliculus neurons respond and entrain to
sounds in a very broad region of space, and many are entirely spatially insensitive,
so it is unknown how the neurons will respond to a situation with more than one sound.
I use multiple AM stimuli of different frequencies, which the inferior colliculus
represents using a spike timing code. This allows me to measure spike timing in the
inferior colliculus to determine which sound source is responsible for neural activity
in an auditory scene containing multiple sounds. Using this approach, I find that
the same neurons that are tuned to broad regions of space in the single sound condition
become dramatically more selective in the dual sound condition, preferentially entraining
spikes to stimuli from a smaller region of space. I will examine the possibility that
there may be a conceptual linkage between this finding and the finding of receptive
field shifts in the visual system.</p><p>In chapter 5, I will comment on these findings
more generally, compare them to existing theoretical models, and discuss what these
results tell us about processing in the central nervous system in a multi-stimulus
situation. My results suggest that the brain is flexible in its processing and can
adapt its integration schema to fit the available cues and the demands of the task.</p>
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