The Science of LearningBreaking NewsD b 2010December 2010

Joan Straumanis

Current SLC Portfolio2004 Cohort

CELEST: Center for Cognitive d Ed ti l N i

2006 Cohort

SILC: Spatial Intelligence and L i C t (T l U)and Educational Neuroscience  

(Boston U) http://celest.bu.edu

Learning Center (Temple U) http://spatiallearning.org

TDLC: Temporal Dynamics of LIFE: Learning in Informal and 

Formal Environments (U of Washington) http://www.life‐slc.org

TDLC: Temporal Dynamics of Learning Center (UC‐San Diego) http://tdlc.ucsd.edu

slc.org

PSLC: Pittsburgh Science of Learning Center (Carnegie‐Mellon U)

VL2: Visual Language and Learning Center (Gallaudet U) Mellon U) 

http://www.learnlab.org( )http://vl2.gallaudet.edu

Definition of Robust Learning:

• Retained for a long time

• Effective preparation for further learning or practicepractice

f l• Transfers to novel situations

To Increase Learning:

Enlist brain’s motivational & reward systems; compete  effectively with other rewards

Manage sleep to consolidate memoryMultimodal input Ensure engagement (“Active Learning”) Ensure engagement ( Active Learning )Manage timing of practice, reinforcement 

(Assistance Dilemma) Provide plenty of social interaction!  

What we’ve learned about STEM learningSTEM learning…

(a synthesis) 

Expert explanation……….is not as effective as

Peer explanation …which is not as effective as

Self explanation which is not as effective as Self explanation…..which is not as effective as

Teaching another…even when that other is a Teaching another…even when that other is acomputer‐generated avatar

Findings about Social Interaction:

• Babies need it to learn language• Teaching another is powerful so• Teaching another is powerful…so• Team/group learning is effective• “Mere belief in the social” works!• But so does teaching a computer avatar!!

Social Dynamics of Learning:of Learning: Human, Robot, VidVideo

UW MEG Brain Imaging Center LIFE reported the first in the world MEG recordings of awake infants engaged in a cognitive task (Imada Kuhlcognitive task (Imada, Kuhl et al., 2006).

Magnetic fields generated by neuronal activity in the brain are recordedoutside the brain by magnetometers.

8Ribbon-Cutting on May 24, 2010

International collaboration with Helsinki University of Technology and Elekta Oy –all 6 SLCs in Helsinki in Dec., 2009

Science at CELEST• Focus:  Brain mechanisms of learning during planning, 

exploring, communicating & remembering• Approach: Integration of modeling & experimentation• Cross‐Cutting Research Themes: processing bottlenecks , 

dynamic coding functional connections neural plasticitydynamic coding, functional connections, neural plasticity, neuromorphic engineering

• Examples: Links between gamma oscillations, plasticity & learning to study phase coding in working memory, illuminating cognitive bottlenecks; biologically inspired microprocessingusingmemristorsusing memristors

The DARPA SyNAPSE Project

A National Science FoundationScience of Learning Center

Center of Excellence for Learning in Education, Science, and Technology

The DARPA SyNAPSE Project

Hardware goalsSystems of Neuromorphic Adaptive Plastic Scalable Electronics

106 “neurons”/cm2

1020 “synapses”/cm2

~100 milliwatts/cm2

10,000 chips, 1000 wattsstuffed in a shoeboxTo date: Wrong hardware!

Brain-like computations with CELEST i ki i hBrain like computations withco-located DATA STORAGE,SIGNAL TRANSMISSION, and LEARNING are inefficient in di it l t

CELEST is working with Industrial partners HRL Labs and Hewlett-Packard to devisenext-generation computing hardware.digital computers

1010 neurons1014 synapses

next generation computing hardware.

Such machines MUST LEARN, because they will not be fully “programmable”.

Blue Gene 1 GW, thousands

of racks

Brain20 W1.3Kg

Phase‐Coding of Objects in Working MemoryWhat are the fundamental constraints on working memory capacity?

This analysis was directly inspired by CELEST interactions between members of the Hasselmo and Miller labs.Koene, R. & Hasselmo, M. (2007). Cerebral Cortex, 17, 1766–1781.

Spikes associated with the first and secondSpikes associated with the first and seconditems occur at different phases within local field potentials that cycle at approximately 32 Hz i h f l f kin the prefrontal cortex of monkeys performing a working memory task.

11Siegel, Warden, and Miller (2009) Proc. Nat. Acad. Sci.

TDLC:Time matters for processing…

“say”yFreq

uency

“stay”

F

100 ms

Ti ( illi d )Time (milliseconds)

These wave forms are identicalidentical except for the artificially inserted gap and a compensating shrinkage of the waveform.

Facial Expression during problem solving. Littlewort, Phan Reilly and Bartlett (3 2)Phan, Reilly, and Bartlett,  (3.2)

Facial Expression during problem solving.Littlewort, Phan, Reilly, and Bartlett,  (3.2)

Initiative 6- Translational Research Initiative 6- Translational Research