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Detect and analyze the 3-D head movement patterns in marmoset monkeys using wireless tracking system
Description
Head movement is a natural orienting behavior for sensing environmental events around us. Head movement is particularly important for identifying through the sense of hearing the location of an out-of-sight, rear-approaching target to avoid danger or threat. This research aims to design a portable device for detecting the head movement patterns of common marmoset monkeys in laboratory environments. Marmoset is a new-world primate species and has become increasingly popular for neuroscience research. Understanding the unique patterns of their head movements will improve its values as a new primate model for uncovering the neurobiology of natural orienting behavior. Due to their relatively small head size (5 cm in diameter) and body weight (300-500 g), the device has to meet several unique design requirements with respect to accuracy and workability. A head-mount wireless tracking system was implemented based on inertial sensors that are capable of detecting motion in the Yaw, Pitch and Roll axes. The sensors were connected to the encoding station, which transmits wirelessly the 3-axis movement data to the decoding station at the sampling rate of ~175 Hz. The decoding station relays this information to the computer for real-time display and analysis. Different tracking systems, based on the accelerometer and Inertial Measurement Unit is implemented to track the head movement pattern of the marmoset head. Using these systems, translational and rotational information of head movement are collected, and the data analysis focuses on the rotational head movement in body-constrained marmosets. Three stimulus conditions were tested: 1) Alert, 2) Idle 3) Sound only. The head movement patterns were examined when the house light was turned on and off for each stimulus. Angular velocity, angular displacement and angular acceleration were analyzed in all three axes.
Fast and large head turns were observed in the Yaw axis in response to the alert stimuli and not much in the idle and sound-only stimulus conditions. Contrasting changes in speed and range of head movement were found between light-on and light-off situations. The mean peak angular displacement was 95 degrees (light on) and 55 (light off) and the mean peak angular velocity was 650 degrees/ second (light on) and 400 degrees/second (light off), respectively, in response to the alert stimuli. These results suggest that the marmoset monkeys may engage in different modes of orienting behaviors with respect to the availability of visual cues and thus the necessity of head movement. This study provides a useful tool for future studies in understanding the interplay among visual, auditory and vestibular systems during nature behavior.
Fast and large head turns were observed in the Yaw axis in response to the alert stimuli and not much in the idle and sound-only stimulus conditions. Contrasting changes in speed and range of head movement were found between light-on and light-off situations. The mean peak angular displacement was 95 degrees (light on) and 55 (light off) and the mean peak angular velocity was 650 degrees/ second (light on) and 400 degrees/second (light off), respectively, in response to the alert stimuli. These results suggest that the marmoset monkeys may engage in different modes of orienting behaviors with respect to the availability of visual cues and thus the necessity of head movement. This study provides a useful tool for future studies in understanding the interplay among visual, auditory and vestibular systems during nature behavior.
ContributorsPandey, Swarnima (Author) / Zhou, Yi (Thesis advisor) / Tillery, Stephen H (Thesis advisor) / Buneo, Christpher A (Committee member) / Arizona State University (Publisher)
Created2015
Description
Sound localization can be difficult in a reverberant environment. Fortunately listeners can utilize various perceptual compensatory mechanisms to increase the reliability of sound localization when provided with ambiguous physical evidence. For example, the directional information of echoes can be perceptually suppressed by the direct sound to achieve a single, fused auditory event in a process called the precedence effect (Litovsky et al., 1999). Visual cues also influence sound localization through a phenomenon known as the ventriloquist effect. It is classically demonstrated by a puppeteer who speaks without visible lip movements while moving the mouth of a puppet synchronously with his/her speech (Gelder and Bertelson, 2003). If the ventriloquist is successful, sound will be “captured” by vision and be perceived to be originating at the location of the puppet. This thesis investigates the influence of vision on the spatial localization of audio-visual stimuli. Participants seated in a sound-attenuated room indicated their perceived locations of either ISI or level-difference stimuli in free field conditions. Two types of stereophonic phantom sound sources, created by modulating the inter-stimulus time interval (ISI) or level difference between two loudspeakers, were used as auditory stimuli. The results showed that the light cues influenced auditory spatial perception to a greater extent for the ISI stimuli than the level difference stimuli. A binaural signal analysis further revealed that the greater visual bias for the ISI phantom sound sources was correlated with the increasingly ambiguous binaural cues of the ISI signals. This finding suggests that when sound localization cues are unreliable, perceptual decisions become increasingly biased towards vision for finding a sound source. These results support the cue saliency theory underlying cross-modal bias and extend this theory to include stereophonic phantom sound sources.
ContributorsMontagne, Christopher (Author) / Zhou, Yi (Thesis advisor) / Buneo, Christopher A (Thesis advisor) / Yost, William A. (Committee member) / Arizona State University (Publisher)
Created2015
Description
This study consisted of several related projects on dynamic spatial hearing by both human and robot listeners. The first experiment investigated the maximum number of sound sources that human listeners could localize at the same time. Speech stimuli were presented simultaneously from different loudspeakers at multiple time intervals. The maximum of perceived sound sources was close to four. The second experiment asked whether the amplitude modulation of multiple static sound sources could lead to the perception of auditory motion. On the horizontal and vertical planes, four independent noise sound sources with 60° spacing were amplitude modulated with consecutively larger phase delay. At lower modulation rates, motion could be perceived by human listeners in both cases. The third experiment asked whether several sources at static positions could serve as "acoustic landmarks" to improve the localization of other sources. Four continuous speech sound sources were placed on the horizontal plane with 90° spacing and served as the landmarks. The task was to localize a noise that was played for only three seconds when the listener was passively rotated in a chair in the middle of the loudspeaker array. The human listeners were better able to localize the sound sources with landmarks than without. The other experiments were with the aid of an acoustic manikin in an attempt to fuse binaural recording and motion data to localize sounds sources. A dummy head with recording devices was mounted on top of a rotating chair and motion data was collected. The fourth experiment showed that an Extended Kalman Filter could be used to localize sound sources in a recursive manner. The fifth experiment demonstrated the use of a fitting method for separating multiple sounds sources.
ContributorsZhong, Xuan (Author) / Yost, William (Thesis advisor) / Zhou, Yi (Committee member) / Dorman, Michael (Committee member) / Helms Tillery, Stephen (Committee member) / Arizona State University (Publisher)
Created2015
Description
Head movement is known to have the benefit of improving the accuracy of sound localization for humans and animals. Marmoset is a small bodied New World monkey species and it has become an emerging model for studying the auditory functions. This thesis aims to detect the horizontal and vertical rotation of head movement in marmoset monkeys.
Experiments were conducted in a sound-attenuated acoustic chamber. Head movement of marmoset monkey was studied under various auditory and visual stimulation conditions. With increasing complexity, these conditions are (1) idle, (2) sound-alone, (3) sound and visual signals, and (4) alert signal by opening and closing of the chamber door. All of these conditions were tested with either house light on or off. Infra-red camera with a frame rate of 90 Hz was used to capture of the head movement of monkeys. To assist the signal detection, two circular markers were attached to the top of monkey head. The data analysis used an image-based marker detection scheme. Images were processed using the Computation Vision Toolbox in Matlab. The markers and their positions were detected using blob detection techniques. Based on the frame-by-frame information of marker positions, the angular position, velocity and acceleration were extracted in horizontal and vertical planes. Adaptive Otsu Thresholding, Kalman filtering and bound setting for marker properties were used to overcome a number of challenges encountered during this analysis, such as finding image segmentation threshold, continuously tracking markers during large head movement, and false alarm detection.
The results show that the blob detection method together with Kalman filtering yielded better performances than other image based techniques like optical flow and SURF features .The median of the maximal head turn in the horizontal plane was in the range of 20 to 70 degrees and the median of the maximal velocity in horizontal plane was in the range of a few hundreds of degrees per second. In comparison, the natural alert signal - door opening and closing - evoked the faster head turns than other stimulus conditions. These results suggest that behaviorally relevant stimulus such as alert signals evoke faster head-turn responses in marmoset monkeys.
Experiments were conducted in a sound-attenuated acoustic chamber. Head movement of marmoset monkey was studied under various auditory and visual stimulation conditions. With increasing complexity, these conditions are (1) idle, (2) sound-alone, (3) sound and visual signals, and (4) alert signal by opening and closing of the chamber door. All of these conditions were tested with either house light on or off. Infra-red camera with a frame rate of 90 Hz was used to capture of the head movement of monkeys. To assist the signal detection, two circular markers were attached to the top of monkey head. The data analysis used an image-based marker detection scheme. Images were processed using the Computation Vision Toolbox in Matlab. The markers and their positions were detected using blob detection techniques. Based on the frame-by-frame information of marker positions, the angular position, velocity and acceleration were extracted in horizontal and vertical planes. Adaptive Otsu Thresholding, Kalman filtering and bound setting for marker properties were used to overcome a number of challenges encountered during this analysis, such as finding image segmentation threshold, continuously tracking markers during large head movement, and false alarm detection.
The results show that the blob detection method together with Kalman filtering yielded better performances than other image based techniques like optical flow and SURF features .The median of the maximal head turn in the horizontal plane was in the range of 20 to 70 degrees and the median of the maximal velocity in horizontal plane was in the range of a few hundreds of degrees per second. In comparison, the natural alert signal - door opening and closing - evoked the faster head turns than other stimulus conditions. These results suggest that behaviorally relevant stimulus such as alert signals evoke faster head-turn responses in marmoset monkeys.
ContributorsSimhadri, Sravanthi (Author) / Zhou, Yi (Thesis advisor) / Turaga, Pavan (Thesis advisor) / Berisha, Visar (Committee member) / Arizona State University (Publisher)
Created2014
Description
Spatial awareness (i.e., the sense of the space that we are in) involves the integration of auditory, visual, vestibular, and proprioceptive sensory information of environmental events. Hearing impairment has negative effects on spatial awareness and can result in deficits in communication and the overall aesthetic experience of life, especially in noisy or reverberant environments. This deficit occurs as hearing impairment reduces the signal strength needed for auditory spatial processing and changes how auditory information is combined with other sensory inputs (e.g., vision). The influence of multisensory processing on spatial awareness in listeners with normal, and impaired hearing is not assessed in clinical evaluations, and patients’ everyday sensory experiences are currently not directly measurable. This dissertation investigated the role of vision in auditory localization in listeners with normal, and impaired hearing in a naturalistic stimulus setting, using natural gaze orienting responses. Experiments examined two behavioral outcomes—response accuracy and response time—based on eye movement in response to simultaneously presented auditory and visual stimuli. The first set of experiments examined the effects of stimulus spatial saliency on response accuracy and response time and the extent of visual dominance in both metrics in auditory localization. The results indicate that vision can significantly influence both the speed and accuracy of auditory localization, especially when auditory stimuli are more ambiguous. The influence of vision is shown for both normal hearing- and hearing-impaired listeners. The second set of experiments examined the effect of frontal visual stimulation on localizing an auditory target presented from in front of or behind a listener. The results show domain-specific effects of visual capture on both response time and response accuracy. These results support previous findings that auditory-visual interactions are not limited by the spatial rule of proximity. These results further suggest the strong influence of vision on both the processing and the decision-making stages of sound source localization for both listeners with normal, and impaired hearing.
ContributorsClayton, Colton (Author) / Zhou, Yi (Thesis advisor) / Azuma, Tamiko (Committee member) / Daliri, Ayoub (Committee member) / Arizona State University (Publisher)
Created2021
Description
This study focuses on the properties of binaural beats (BBs) compared to Monaural beats (MBs) and their steady-state response at the level of the Superior Olivary Complex (SOC). An auditory nerve stimulator was used to simulate the response of the SOC. The simulator was fed either BBs or MBs stimuli to compare the SOC response. This was done for different frequencies at twenty, forty, and sixty hertz for comparison of the SOC response envelopes. A correlation between the SOC response envelopes for both types of beats and the waveform resulting from adding two tones together was completed. The highest correlation for BBs was found to be forty hertz and for MBs it was sixty hertz. A Fast Fourier Transform (FFT) was also completed on the stimulus envelope and the SOC response envelopes. The FFT was able to show that within the BBs presentation the envelopes of the original stimuli showed no difference frequency. However, the difference frequency was present in the binaural SOC response envelope. For the MBs, the difference frequency was present within the stimulus and the monaural SOC response envelope.
ContributorsCrawford, Taylor Janay (Author) / Brewer, Gene (Thesis advisor) / Zhou, Yi (Committee member) / Azuma, Tamiko (Committee member) / Arizona State University (Publisher)
Created2021
Description
Neuron models that behave like their biological counterparts are essential for computational neuroscience.Reduced neuron models, which abstract away biological mechanisms in the interest of speed and interpretability, have received much attention due to their utility in large scale simulations of the brain, but little care has been taken to ensure that these models exhibit behaviors that closely resemble real neurons.
In order to improve the verisimilitude of these reduced neuron models, I developed an optimizer that uses genetic algorithms to align model behaviors with those observed in experiments.
I verified that this optimizer was able to recover model parameters given only observed physiological data; however, I also found that reduced models nonetheless had limited ability to reproduce all observed behaviors, and that this varied by cell type and desired behavior.
These challenges can partly be surmounted by carefully designing the set of physiological features that guide the optimization. In summary, we found evidence that reduced neuron model optimization had the potential to produce reduced neuron models for only a limited range of neuron types.
In order to improve the verisimilitude of these reduced neuron models, I developed an optimizer that uses genetic algorithms to align model behaviors with those observed in experiments.
I verified that this optimizer was able to recover model parameters given only observed physiological data; however, I also found that reduced models nonetheless had limited ability to reproduce all observed behaviors, and that this varied by cell type and desired behavior.
These challenges can partly be surmounted by carefully designing the set of physiological features that guide the optimization. In summary, we found evidence that reduced neuron model optimization had the potential to produce reduced neuron models for only a limited range of neuron types.
ContributorsJarvis, Russell Jarrod (Author) / Crook, Sharon M (Thesis advisor) / Gerkin, Richard C (Thesis advisor) / Zhou, Yi (Committee member) / Abbas, James J (Committee member) / Arizona State University (Publisher)
Created2020
Description
It is increasingly common to see machine learning techniques applied in conjunction with computational modeling for data-driven research in neuroscience. Such applications include using machine learning for model development, particularly for optimization of parameters based on electrophysiological constraints. Alternatively, machine learning can be used to validate and enhance techniques for experimental data analysis or to analyze model simulation data in large-scale modeling studies, which is the approach I apply here. I use simulations of biophysically-realistic cortical neuron models to supplement a common feature-based technique for analysis of electrophysiological signals. I leverage these simulated electrophysiological signals to perform feature selection that provides an improved method for neuron-type classification. Additionally, I validate an unsupervised approach that extends this improved feature selection to discover signatures associated with neuron morphologies - performing in vivo histology in effect. The result is a simulation-based discovery of the underlying synaptic conditions responsible for patterns of extracellular signatures that can be applied to understand both simulation and experimental data. I also use unsupervised learning techniques to identify common channel mechanisms underlying electrophysiological behaviors of cortical neuron models. This work relies on an open-source database containing a large number of computational models for cortical neurons. I perform a quantitative data-driven analysis of these previously published ion channel and neuron models that uses information shared across models as opposed to information limited to individual models. The result is simulation-based discovery of model sub-types at two spatial scales which map functional relationships between activation/inactivation properties of channel family model sub-types to electrophysiological properties of cortical neuron model sub-types. Further, the combination of unsupervised learning techniques and parameter visualizations serve to integrate characterizations of model electrophysiological behavior across scales.
ContributorsHaynes, Reuben (Author) / Crook, Sharon M (Thesis advisor) / Gerkin, Richard C (Committee member) / Zhou, Yi (Committee member) / Baer, Steven (Committee member) / Armbruster, Hans D (Committee member) / Arizona State University (Publisher)
Created2020
Description
Much evidence has shown that first language (L1) plays an important role in the formation of L2 phonological system during second language (L2) learning process. This combines with the fact that different L1s have distinct phonological patterns to indicate the diverse L2 speech learning outcomes for speakers from different L1 backgrounds. This dissertation hypothesizes that phonological distances between accented speech and speakers' L1 speech are also correlated with perceived accentedness, and the correlations are negative for some phonological properties. Moreover, contrastive phonological distinctions between L1s and L2 will manifest themselves in the accented speech produced by speaker from these L1s. To test the hypotheses, this study comes up with a computational model to analyze the accented speech properties in both segmental (short-term speech measurements on short-segment or phoneme level) and suprasegmental (long-term speech measurements on word, long-segment, or sentence level) feature space. The benefit of using a computational model is that it enables quantitative analysis of L1's effect on accent in terms of different phonological properties. The core parts of this computational model are feature extraction schemes to extract pronunciation and prosody representation of accented speech based on existing techniques in speech processing field. Correlation analysis on both segmental and suprasegmental feature space is conducted to look into the relationship between acoustic measurements related to L1s and perceived accentedness across several L1s. Multiple regression analysis is employed to investigate how the L1's effect impacts the perception of foreign accent, and how accented speech produced by speakers from different L1s behaves distinctly on segmental and suprasegmental feature spaces. Results unveil the potential application of the methodology in this study to provide quantitative analysis of accented speech, and extend current studies in L2 speech learning theory to large scale. Practically, this study further shows that the computational model proposed in this study can benefit automatic accentedness evaluation system by adding features related to speakers' L1s.
ContributorsTu, Ming (Author) / Berisha, Visar (Thesis advisor) / Liss, Julie M (Committee member) / Zhou, Yi (Committee member) / Arizona State University (Publisher)
Created2018
Description
Auditory scene analysis (ASA) is the process through which listeners parse and organize their acoustic environment into relevant auditory objects. ASA functions by exploiting natural regularities in the structure of auditory information. The current study investigates spectral envelope and its contribution to the perception of changes in pitch and loudness. Experiment 1 constructs a perceptual continuum of twelve f0- and intensity-matched vowel phonemes (i.e. a pure timbre manipulation) and reveals spectral envelope as a primary organizational dimension. The extremes of this dimension are i (as in “bee”) and Ʌ (“bun”). Experiment 2 measures the strength of the relationship between produced f0 and the previously observed phonetic-pitch continuum at three different levels of phonemic constraint. Scat performances and, to a lesser extent, recorded interviews were found to exhibit changes in accordance with the natural regularity; specifically, f0 changes were correlated with the phoneme pitch-height continuum. The more constrained case of lyrical singing did not exhibit the natural regularity. Experiment 3 investigates participant ratings of pitch and loudness as stimuli vary in f0, intensity, and the phonetic-pitch continuum. Psychophysical functions derived from the results reveal that moving from i to Ʌ is equivalent to a .38 semitone decrease in f0 and a .75 dB decrease in intensity. Experiment 4 examines the potentially functional aspect of the pitch, loudness, and spectral envelope relationship. Detection thresholds of stimuli in which all three dimensions change congruently (f0 increase, intensity increase, Ʌ to i) or incongruently (no f0 change, intensity increase, i to Ʌ) are compared using an objective version of the method of limits. Congruent changes did not provide a detection benefit over incongruent changes; however, when the contribution of phoneme change was removed, congruent changes did offer a slight detection benefit, as in previous research. While this relationship does not offer a detection benefit at threshold, there is a natural regularity for humans to produce phonemes at higher f0s according to their relative position on the pitch height continuum. Likewise, humans have a bias to detect pitch and loudness changes in phoneme sweeps in accordance with the natural regularity.
ContributorsPatten, K. Jakob (Author) / Mcbeath, Michael K (Thesis advisor) / Amazeen, Eric L (Committee member) / Glenberg, Arthur W (Committee member) / Zhou, Yi (Committee member) / Arizona State University (Publisher)
Created2017