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Events for April 24, 2023
Mon, Apr 24, 2023 @ 11:00 AM - 12:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Assal Habibi, Associate Research Professor of Psychology, Brain and Creativity Institute, University of Southern California
Talk Title: The Brain\'s Crescendo; How Music Training Impacts Child Development
Abstract: In a multi-year longitudinal study, we have been investigating the effects of a group-based music training program on the development of children, beginning at age 6, using behavioral, neuroimaging, and electrophysiological measures. The target group of children have been participating in the Youth Orchestra of Los Angeles (YOLA) program. This music program is based on the Venezuelan system of musical training known as El-Sistema and offers free music instruction 6-“7 hours weekly to children from underprivileged and under-resourced areas of Los Angeles. The children in the music program have been compared with two groups of children, one involved in a community-based sports program, and another not enrolled in any systematic afterschool training. During this talk, I will share some of the behavioral and neuroimaging results from this study. Over the course of 5 years, we have observed that children in the music group had better performance than comparison groups in musically relevant auditory skills (pitch and rhythm discrimination) and showed an accelerated maturity of auditory processing as measured by cortical auditory evoked potentials. We also observed that children in the music group showed a different rate of cortical thickness maturation between the right and left posterior superior temporal gyrus and higher fractional anisotropy in the corpus callosum, specifically in the crossing pathways connecting superior frontal, sensory, and motor segments. For nonmusical skills, children with music training, compared with children without music training, showed stronger neural activation during a cognitive inhibition task in brain regions involved in response inhibition and decision-making (bilateral pre-SMA/SMA, ACC, IFG). Finally, we observed that parents of children involved in music training, after four years, rated their children higher on the emotional stability personality trait and lower on aggression and on hyperactivity compared to children not involved in music activities despite no differences in these measures before children\'s entry into the program. Considering a general reduction in art education specifically in the communities where there is limited access to art exposure in general, and specifically to music education, the findings from this study is providing compelling answers to the ongoing discussion about music\'s role in the education curriculum.
Biography: Assal Habibi is an Associate Research Professor of Psychology at the Brain and Creativity Institute at the University of Southern California. Her research takes a broad perspective on understanding the influence of arts and specifically music on health and development, focusing on how biological dispositions and learning experiences shape the brain and development of cognitive, emotional and social abilities during childhood and adolescence. She is an expert on the use of electrophysiologic and neuroimaging methods to investigate human brain function and has used longitudinal and cross-sectional designs to investigate how implementing music training programs within the school curricula impacts the learning and academic achievement of children from under-resourced communities. Her research program has been supported by federal agencies and private foundations including the NIH, NEA and the GRoW @ Annenberg Foundation and her findings have been published in peer reviewed journals including Cerebral Cortex, Music Perception, Neuroimage and PLoS ONE. Currently, she is the lead investigator of a multi-year study, in collaboration with the Los Angeles Philharmonic and their Youth Orchestra program (YOLA), investigating the effects of early childhood music education on the development of brain function and structure as well as learning skills, cognitive, emotional, and social abilities. Dr. Habibi is a classically trained pianist and has many years of musical teaching experience with children, a longstanding personal passion.
Host: Dr. Karim Jerbi, email@example.com and Dr. Richard M. Leahy, firstname.lastname@example.org
More Information: MoBI-Seminar-Habibi-042423.pdf
Audiences: Everyone Is Invited
Contact: Mayumi Thrasher
Mon, Apr 24, 2023 @ 02:00 PM - 04:00 PM
Thomas Lord Department of Computer Science
PHD Thesis Defense - Christopher Denniston
Title: Active Sensing In Robotic Deployment
Committee Members: Prof. Gaurav S. Sukhatme (Chair), Prof. Jesse Thomason, Prof. David A. Caron
Date/Time: April 24th, 2-4pm
Location: RTH 306 or on Zoom https://usc.zoom.us/j/2869134593
Robots have the potential to greatly increase our ability to measure complex environmental phenomena, such as harmful algae blooms, which can harm humans and animals alike in drinking water. Such phenomena require study and measurement at a scale that is beyond what can be accomplished by robots that plan to completely cover the area. Despite this, many sensing robots still are deployed with non-active behaviors, such as fixed back-and-forth patterns. The lack of deployment of active sensing systems in practice is due to difficulties with problems encountered in the real world. We identify and address solutions for three main issues which plague complex real robotic active sensing deployments.
First, active sensing systems are difficult to use, with complex deployment-time decisions that affect the efficiency of sensing. We describe systems that eschew these decisions, allowing for efficient and automatic deployment. We find that these systems provide a non-technical deployment procedure and outperform hand-tuned behaviors.
Second, active sensing robots tend to perform a survey that maximizes some general goal and requires the user to interpret the collected data. We propose a system that, instead, plans for the specific user task of collecting physical samples at limited, unknown locations. We demonstrate that planning for this specific task while sensing allows for more efficiency in the active sensing behavior.
Finally, existing models for active sensing do not accurately model the interaction of the sensed signal and obstacles in the environment. We propose two novel modeling techniques which allow active sensing of signals which have complex interactions with obstacles, such as electromagnetic waves. Both outperform traditional modeling techniques and enable scalable active sensing to a large number of measurements on a real robot. Additionally, we find that they allow the robot to actively place signal-emitting devices while sensing the signals from these placed devices.
Audiences: Everyone Is Invited
Contact: Asiroh Cham