Despite Bans, Many Still Text While Driving.  Radio Boston WBUR 90.0 FM
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Earl Miller receives the Kent State University Professional Achievement Award from KSU President Beverly Warren.

And delivers the Commencement Address:

 

Free access to our new paper:
Lundqvist, M., Rose, J., Herman, P., Brincat, S. L., Buschman, T. J., & Miller, E. K. (2016). Gamma and Beta Bursts Underlie Working Memory. Neuron.

Valid until May 26, 2016

Tsutsui et al shows how the prefrontal cortex integrates rule and category information for a behavioral decision.

Tsutsui, Ken-Ichiro, et al. “Representation of Functional Category in the Monkey Prefrontal Cortex and Its Rule-Dependent Use for Behavioral Selection.” The Journal of Neuroscience 36.10 (2016): 3038-3048.

Michael Halassa, Guoping Feng, and colleagues show that a genetic deficit  found in patients with ADHD produces (in mice) deficit in the thalamic reticular nucleus.  This adds to Halassa’s recent work (also in Nature) suggesting that  attention is focused when the prefrontal cortex acts on sensory cortex via the thalamus.  It adds a link to potential path to treatment.  Cool.

Thalamic reticular impairment underlies attention deficit in Ptchd1Y/− mice
Michael F. Wells, Ralf D. Wimmer, L. Ian Schmitt, Guoping Feng & Michael M. Halassa

Sustained activity has long been thought to be the neural substrate of working memory.  But the evidence is based on averaging neural activity across trials.  A closer examination reveals that something more complex is happening and supports a very different model of working memory.

Gamma and Beta Bursts Underlie Working Memory
Mikael Lundqvist, Jonas Rose, Pawel Herman, Scott L. Brincat, Timothy J. Buschman, Earl K. Miller
Neuron, published online March 17, 2016

Summary
Working memory is thought to result from sustained neuron spiking. However, computational models suggest complex dynamics with discrete oscillatory bursts. We analyzed local field potential (LFP) and spiking from the prefrontal cortex (PFC) of monkeys performing a working memory task. There were brief bursts of narrow-band gamma oscillations (45–100 Hz), varied in time and frequency, accompanying encoding and re-activation of sensory information. They appeared at a minority of recording sites associated with spiking reflecting the to-be-remembered items. Beta oscillations (20–35 Hz) also occurred in brief, variable bursts but reflected a default state interrupted by encoding and decoding. Only activity of neurons reflecting encoding/decoding correlated with changes in gamma burst rate. Thus, gamma bursts could gate access to, and prevent sensory interference with, working memory. This supports the hypothesis that working memory is manifested by discrete oscillatory dynamics and spiking, not sustained activity.

Increases in beta power associated with top-down attention.  Beta seemed unite visual cortex.  There was a more homogeneous pattern of beta correlation across the cortex during top-down vs bottom-up attention.

Bekisz, M., Bogdan, W., Ghazaryan, A., Waleszczyk, W. J., Kublik, E., & Wróbel, A. (2016). The Primary Visual Cortex Is Differentially Modulated by Stimulus-Driven and Top-Down Attention. PloS one, 11(1), e0145379.

Lunqvist, M., Rose, J., Herman, P, Brincat, S.L, Buschman, T.J., and Miller, E.K. (in press) Gamma and beta bursts underlie memory.  Neuron

We know how to party!

04 Feb 2016
February 4, 2016

Bose’s new beat

Miller Laboratory

CNET article on how the Bose Corporation is funding new technology and innovative research.  Including research by Earl Miller, a 2014 Bose Research Fellow. Bose’s New Beat

2014 Bose Research Fellow, Prof. Earl K. Miller

The viewpoint that single neurons are the functional units of the brain rests on the hypothesis that each neuron has a single function or “message”.  This notion has eroded under observations that cortical neurons do not seem to do one thing.  Instead, neurons often respond to diverse combinations of task relevant variables, and often a variety of different variables with no apparent single function.  Why would the brain evolve neurons with this “mixed selectivity”?  In short, they add computational power.  How?  Read this paper and we”ll tell you.

Why neurons mix: high dimensionality for higher cognition,
Stefano Fusi, Earl K Miller, Mattia Rigotti,
Current Opinion in Neurobiology, Volume 37, April 2016, Pages 66-74, ISSN 0959-4388, http://dx.doi.org/10.1016/j.conb.2016.01.010.