ICLM Journal Club
This Week - 24 March 2017 (9:30 a.m., Gonda 2nd Floor Conference Room)
Speaker: Vishwa Goudar
Title: Modeling and Experimental Analysis of Sensory and Motor Timing within Recurrent Neural Networks
https://arxiv.org/abs/1701.00838
http://www.jneurosci.org/content/37/4/854
Much of the brain's computations are temporal in nature. Information commonly processed by the brain's circuits, such as a spoken word or a handwritten signature, is defined as much by how it unfolds in time as by its spatial structure at any given moment in time. Similarly, anticipating an upcoming event demands the ability to accurately tell time. While the neural mechanisms underlying spatiotemporal processing are not known, "state-space" models hypothesize that neural circuits encode temporal patterns in their dynamics as continuous neural trajectories. In this talk, I will describe two studies aimed at understanding neural basis of temporal processing. First, I will discuss a modeling study showing how a single recurrent neural network model can simultaneously encode time-varying sensory and motor patterns as continuous neural trajectories - specifically the network can perform a complex sensory-motor task in which spoken digits are transcribed into written digits. Crucially, this approach addresses the long-standing problem of temporal invariance: the network identifies the same stimulus played at different speeds. Second, I will describe a collaborative study with the Masmanidis lab, where we analyzed the neural encoding of anticipatory timing. Consistent with the notion of a "population clock", the striatum and cortex have been shown to encode elapsed time in their ongoing population-level dynamics. Our findings indicate that both the striatal and cortical networks encoded time, but striatal networks outperform the orbitofrontal cortex. These results are consistent with the hypothesis that temporal information is encoded in a widely distributed manner throughout multiple brain areas, but that the striatum may have a privileged role in timing because it has a more accurate “clock” as it integrates information across multiple cortical areas.
About Us
Introduction
The Integrative Center for Learning and Memory (ICLM) is a multidisciplinary center of UCLA labs devoted to understanding the neural basis of learning and memory and its disorders. This will require a unified approach across different levels of analysis, including;
1. Elucidating the molecular cellular and systems mechanisms that allow neurons and synapses to undergo the long-term changes that ultimately correspond to 'neural memories'.
2. Understanding how functional dynamics and computations emerge from complex circuits of neurons, and how plasticity governs these processes.
3. Describing the neural systems in which different forms of learning and memory take place, and how these systems interact to ultimately generate behavior and cognition.
History of ICLM
The Integrative Center for Learning and Memory formally LMP started in its current form in 1998, and has served as a platform for many interactions and collaborations within UCLA. A key event organized by the group is the weekly ICLM Journal Club. For more than 10 years, graduate students, postdocs, principal investigators, and invited speakers have presented on topics ranging from the molecular mechanisms of synaptic plasticity, through computational models of learning, to behavior and cognition. Dean Buonomano oversees the ICLM journal club with help of student/post doctoral organizers. For other events organized by ICLM go to http://www.iclm.ucla.edu/Events.html.
Current Organizers:
Walt Babiec (O'Dell Lab) & Helen Motanis (Buonomano Lab)
Current Faculty Advisor:
Past Organizers:
i) Anna Matynia(Aug 2004 - Jun 2008) (Silva Lab)
ii) Robert Brown (Aug 2008 - Jun 2009) (Balleine Lab)
iii) Balaji Jayaprakash (Aug 2008 - Nov 2011) (Silva Lab)
iv) Justin Shobe & Thomas Rogerson (Dec 2011 - June 2013) (Silva Lab)
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