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Center Initiatives:

The Temporal Dynamics of Learning Center (TDLC) aims to achieve an integrated understanding of the role of time and timing in learning, across multiple scales, brain systems, and social systems. The scientific goal of the center is therefore to understand the temporal dynamics of learning, and to apply this understanding to improve educational practice. This goal starts with basic science, because a coherent view of temporal dynamics relating to learning does not currently exist. In addition, it is difficult to predict which aspects of learning dynamics will prove the most relevant for improving education. Thus, we chose to identify as our Center Initiatives three broad but critical questions that logically parse the temporal dynamics of learning into its constituent components. The value of this approach is that answering the Initiative questions would, in itself, constitute a somewhat complete science of temporal dynamics of learning.

The selection of Initiatives is based on the idea that there are three sources of temporal dynamics for learning: (1) Dynamics in the external world (including sensory stimuli, interpersonal interactions, and rewards). Some of these dynamics are explicitly learned, for example sequence and order of speech sounds and other sensory inputs. Others influence learning, such as the relative timing between action and reward. (2) Dynamics intrinsic to the brain itself (e.g., cellular processes within neurons, or activity patterns in brain networks, such as oscillations) and dynamics that have been shaped by development and experience. These dynamics can influence how and what the brain learns. (3) Dynamics of the muscles and body. These are learned to enable appropriate movements, and also to allow active movement of sensors like eyes, fingertips, and the body, to sample the environment.

Thus, our three Center Research Initiatives are:

1. TEMPORAL DYNAMICS OF THE WORLD: How is temporal information about the world learned and how do the temporal dynamics of the world influence learning?
2. TEMPORAL DYNAMICS OF THE BRAIN: What are the temporal dynamics of brain cells, brain systems, and behavior? How do these dynamics change with learning, and how do they influence learning?
3. TEMPORAL DYNAMICS OF MOVEMENT AND EXPLORATION: What are the temporal structures for body movements and sampling the environment and how are they learned?

Each of these broad Center Research Initiatives are addressed by formulating specific research strands that represent concrete, approachable, answerable research questions on subtopics within the Initiative. The Center focuses on a few strands within each Initiative at any given time; over time, completion of multiple strands within each Initiative will allow meaningful answers to the Initiative questions to be formulated.

In order to address questions of such broad scope, we have created four research networks, each of which focuses on a different, major aspect of learning: The Sensorimotor Network, the Perceptual Expertise Network, the Interacting Memory Systems Network, and the Social Interaction Network. The Networks are the engines of our research, representing interdisciplinary research groups that include psychologists, neuroscientists, computational modelers, and roboticists. These groups are of a size such that the PIs and their trainees can all sit around a U-shaped table – no one is allowed to hang back! They form small communities that learn to understand each other's vocabularies and synchronize their research around issues that need to be attacked from multiple angles.

Hence the Research Initiatives and the Research Networks are interdigitated, with each network working on multiple initiatives, and each initiative being addressed by multiple networks. This leads to collaborations not only within, but between networks, leading to our Network of Research Networks model.

In addition to these Research Initiatives, Initiative 4, Education, Outreach, and Diversity, covers our work in educating our students, interacting with education professionals and the public, and increasing the diversity of our Center and the scientific community. The scientific goals of each initiative are inherently cross-disciplinary, and require coordinated research by all four research networks. A more detailed description of each initiative is included at the end of this page.

Center Research Initiatives:

1. TEMPORAL DYNAMICS OF THE WORLD : How is temporal information about the world learned, and how do the temporal dynamics of the world influence learning?

2. TEMPORAL DYNAMICS OF THE BRAIN : What are the temporal dynamics of brain cells, brain systems, and behavior? How do these dynamics change with learning, and how do they influence learning?

3. TEMPORAL DYNAMICS OF MOVEMENT AND EXPLORATION : What are the temporal structures for body movements and sampling the environment and how are they learned?


Theoretical Integration

Initiative 1: Temporal Dynamics of the World

How is temporal information about the world learned, and how do the temporal dynamics of the world influence learning?
(Initiative Coordinators: Dan Feldman and Paula Tallal)

The world around us is rich with temporal patterns, on time scales ranging from milliseconds to seconds to minutes and longer. These patterns convey critical information for sensation, communication, and survival. A fundamental aspect of learning is to implicitly or explicitly learn these behaviorally relevant temporal patterns to guide perception and behavior. For example, in speech perception, infants learn to parse a continually varying stream of speech into basic speech sounds (phonemes) by learning to recognize the millisecond-scale temporal pattern of frequencies that are characteristic of each phoneme. Organisms also robustly learn temporal order and sequences on longer time scales of milliseconds to seconds: for example, remembering the sequence of notes in a melody, digits in a phone number, or words and lines in a poem. In some situations, organisms explicitly learn the absolute time delay between events in the world, in order to generate temporally precise expectations and responses to predictable external events. On the longest time scales, episodic memory of past events can include the relative order and recency of these events on the time scale of days, months, and years.

In addition, this Initiative will explore how other temporal features of the world, including the relative timing of actions and rewards, can have a significant effect on learning, even though they are not explicitly learned. A well-known example is how the order and timing of study, testing, and review in the classroom can profoundly influence the duration of learning (spacing effects). Improving our understanding of these effects will provide insights that may improve teaching, learning, and memory retention.

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Initiative 2: Temporal Dynamics of the Brain

What are the temporal dynamics of brain cells, brain systems, and behavior? How do these dynamics change with learning, and how do they influence learning?
(Initiative Coordinators: Andrea Chiba and Isabel Gauthier)

The temporal dynamics of the external world inevitably coalesce with the dynamics of the brain. Aligning the dynamics in the external world with the intrinsic dynamics of the brain and its behavioral output is critical to successful learning. For years, theorists have asserted that the neural code can serve as an efficient representation of the sensory world. Whereas previous neurobiological research indicated that this representation occurred through the firing rate of neurons (rate coding), biophysical models have introduced the notion of spike-time dependent plasticity (STDP), where the timing of pre and post-synaptic neuronal spikes must be within a certain number of milliseconds of each other, and the efficacy of the synapse is enhanced if the pre-synaptic spike precedes the post-synaptic spike (and depressed if the pre-synaptic spike follows the post-synaptic spike). This suggests a method by which neurons might encode relations about the world around them by using precise temporal codes. Understanding how the intrinsic time scale of STDP at synapses governs sensory perceptual learning is likely to be of fundamental relevance to understanding how the dynamics of the brain influences learning in general. In earlier years, Center work demonstrated how STDP rules could be influenced by cortical dynamics. Thus, in this phase more emphasis is being placed on ensemble dynamics with an increasing effort to focus on integration between spike timing and ensemble dynamics.

It would be computationally efficient if each spike could be identified relative to its constituent process in representing the world. The hallmark of a cell assembly or neural ensemble is that its members show a higher probability of spiking together than with members of other ensembles, even in the absence of external inputs. Such identification may be provided by a temporal phase code in which spikes of neurons within an ensemble synchronize at/or on a particular frequency or through precise timing between the spikes. It has been demonstrated that the temporal window in which spike times of one neuron were best predicted from local neural ensemble activity or EEG activity is 10-30 Hz, indicating that ensembles may be synchronized at this timescale. This time window matches the time window for forms of synaptic plasticity, thus it is hypothesized as a critical timescale for information transfer and "storage" in cortical circuits. Understanding the question of how EEG frequencies or rates of modulation of EEG affect information processing will be important to understanding how information is represented across multiple systems in the brain.

The extent to which different brain systems are engaged during learning, as well as the extent to which behavioral expression is dependent on processing within a particular brain system remain critical issues in understanding the neural basis of perception, learning, and memory. Gaining such an understanding will rely heavily on assimilating knowledge regarding the temporal properties of information presentation, reinforcement contingencies, and behavioral demands that differentially engage and promote processing by constituent neural circuits. Given that information is often presented in a social context, it will also be important to determine the precise time windows relevant to factors such as reinforcement and responding between individuals.

How the temporal dynamics of perception link to the temporal dynamics of decisions and ultimately how these dynamics change with experience are important to understanding the temporal dynamics of brain systems and behavior. Such knowledge will also reveal how experience influences responses, modifying our ability to make rapid discriminations, accurate memory judgments and even changing emotional valence. Here, models can serve as theoretical building blocks in evaluating behavior and its underlying neurophysiology.

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Initiative 3: Temporal Dynamics of Movement and Exploration

What are the temporal structures for body movements and sampling the environment and how are they learned?
(Initiative Coordinators: Virginia de Sa and Emo Todorov) 

Biological motion can seldom rely on predetermined sequences of actions. Instead, the behavior of organisms is more like a dance with the environment, in which sensors, actuators, and internal representations are equal partners. In control theory, the laws that regulate this dance are known as "closed-loop control policies" (i.e. functions that specify the moment-to-moment mapping between sensory information, internal states, and the control signals sent to the organisms' actuators). Influential developmental psychologists such as Piaget and Vigotsky have long argued that these sensory-motor mappings provide the primordial conditions out of which high-level cognitive processes develop.

The goal of this initiative is to understand how humans learn sensory motor control laws and how these interact with perceptual and symbolic processes. Our main interest here is not just on learning of specific motor sequences (i.e., open-loop control) but on learning mappings that coordinate perception and action in real time (i.e., closed-loop control). We expect that the learning of such control laws will be different for different domains. For example, learning to walk or to ride a bicycle is likely to impose different temporal and computational constraints than learning to produce the gestures and facial expressions required in social interactions or learning to move our tongues to modulate sounds into recognizable words. Our goal, however, is to find common principles across domains and to formulate a general mathematical framework that shows how these principles apply to sensorimotor learning, perceptual learning, social interaction, and symbolic manipulation. Our approach relies on characterizing the statistics of human motion in multiple domains and at multiple time scales and understanding how these statistics emerge as solutions to real-time control problems.

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Initiative 4: Education, Outreach, and Diversity

(Initiative Coordinator: Gary Cottrell)

In this new instantiation of our Strategic and Implementation Plan, in the interests of redundancy reduction, we have integrated two previously separate initiatives (Integration of Research and Education, formerly Initiative 6, and Diversity, formerly Initiative 7) into one, as there was always considerable overlap between them. We have also given it a new label that is more in keeping with the actual content of this Initiative. Translational research was previously included in Initiative 6, and now has been incorporated directly into Initiatives 1-3 in the appropriate places, in order to maintain coherence between the basic science and the translational efforts that emerge from that science.

The goals of this Initiative include providing education and outreach to the public, education professionals, our fellow scientists, our trainees, and pre-college schools, including preschools, elementary schools, and high schools. They also include ensuring that our outreach and education efforts are inclusive, reflecting the diversity of ideas and the diversity of society.

Like the other initiatives, we have organized this one into separate strands that address our outreach to K-12 students and teachers, undergraduates, graduate students and postdocs, researchers, and the public at large. A few of the unique features of our approach in this initiative include 1) our partnership with UCSD's charter school, the Preuss School, that serves grades 6-12, sends nearly 100% of its graduates to college, and whose population is 72% underrepresented minorities; 2) our partnership with the successful educational technology company, Scientific Learning Corporation, which gives us access to thousands of teachers and school systems; 3) The Educator Network (TEN), which links education professionals with scientists, led by Dr. Doris Alvarez; and 4) our partnership with The Science Network, led by Roger Bingham, a web-based channel devoted to presenting unvarnished access to scientific discussions and presentations. These partnerships and others provide exciting opportunities to reach the educational community, the public, and to increase minority representation in the sciences.

While efforts at increasing the diversity of our center at multiple levels are included in nearly everything we do, some specific outreach to diverse communities are included as separate projects in this initiative.


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