Miller Lab alum Andreas Nieder and crew show how dopamine receptors in the prefrontal cortex regulate access to working memory and its protection from interference.

Jacob, Simon N., Maximilian Stalter, and Andreas Nieder. “Cell-type-specific modulation of targets and distractors by dopamine D1 receptors in primate prefrontal cortex.” Nature Communications (2016): 13218.

Earl Miller wins 2016 Goldman-Rakic Prize for Outstanding Achievement in Cognitive Neuroscience.

Watch a video here:

The Goldman-Rakic Prize for Outstanding Achievement in Cognitive Neuroscience
The Goldman-Rakic Prize was created by Constance and Stephen Lieber in memory of Dr. Patricia Goldman-Rakic, a neuroscientist renowned for discoveries about the brain’s frontal lobe, who died in an automobile accident in 2003.

Earl K. Miller, Ph.D., Picower Professor of Neuroscience, Massachusetts Institute of Technology

Building on Pat Goldman-Rakic’s groundbreaking studies, Dr. Miller’s work in primates has broken new ground in the understanding of cognition. Using innovative experimental and theoretical approaches to study the neural basis of high-level cognitive functions, his laboratory has provided insights into how categories, concepts, and rules are learned, how attention is focused, and how the brain coordinates thought and action. The laboratory has innovated techniques for studying the activity of many neurons in multiple brain areas simultaneously, providing insight into how different brain structures interact and collaborate. This work has established a foundation upon which to construct more detailed, mechanistic accounts of how executive control is implemented in the brain and its dysfunction in diseases such as autism, schizophrenia and attention deficit disorder, and has led to new approaches relevant to severe mental illnesses in children and adults.

MIT press release:

BBRF press release:

Watch Award video:

Earl K. Miller’s Commencement Address at Kent State 5-14-16

Kent State Professional Achievement Award:

Digital Lives – The Science Behind Multitasking:

As we learn about items in our environment, their neural representations become increasingly enriched with our acquired knowledge. But there is little understanding of how network dynamics and neural processing related to external information changes as it becomes laden with “internal” memories. We sampled spiking and local field potential activity simultaneously from multiple sites in the lateral prefrontal cortex (PFC) and the hippocampus (HPC)—regions critical for sensory associations—of monkeys performing an object paired-associate learning task. We found that in the PFC, evoked potentials to, and neural information about, external sensory stimulation decreased while induced beta-band (∼11–27 Hz) oscillatory power and synchrony associated with “top-down” or internal processing increased. By contrast, the HPC showed little evidence of learning-related changes in either spiking activity or network dynamics. The results suggest that during associative learning, PFC networks shift their resources from external to internal processing.

Brincat, S.L. and Miller, E.K (2016) Prefrontal networks shift from external to internal modes during learning  Journal of Neuroscience. 36(37): 9739-9754, 2016 doi: 10.1523/JNEUROSCI.0274-16.2016. View PDF

Earl Miller is quoted in the New York Times:
What Could I Possibly Learn From a Mentor Half My Age? Plenty (New York Times, Sept 11, 2016)

“But part of the problem was me — a person in her mid-50s trying to learn something new. Earl Miller, a neuroscience professor at the Picower Institute for Learning and Memory at the Massachusetts Institute of Technology, explained why progress might be slow.

As you age, your dendrites — the antennas by which neurons receive information from other neurons — begin to shrink, he said. This is especially noticeable in the prefrontal cortex, which handles higher-order brain functions like focusing, staying on task and forming long-term memories.

The decline in these areas begins in your 40s and 50s and worsens from there, he said. This can make it tougher to focus. There’s also more of a limit to how many thoughts people can carry in their heads simultaneously.

“Your mind’s bandwidth is smaller,” he said. “You learn at a slower rate because less information is getting in.”

<But it’s not all bad news>

That sounds depressing. Isn’t there any mental upside to getting older?

Yes, there is, Professor Miller said. Older people tend to be more disciplined and diligent, he said, which can compensate for learning deficits. Based on their greater experience in the world, they are also very good at putting ideas and thoughts into categories — the very basis of knowledge and wisdom.

It’s true: “The older brain is a wiser brain,” he said. But it can also get into a rut because of its lack of plasticity.

The brain is like a muscle that benefits from mental exercises such as learning new things. The more you put your brain through its paces, the easier it will be to learn the next thing. “It’s always important to keep yourself cognitively engaged,” Professor Miller said.

Miller Lab Alumnus Andreas Nieder tells you everything you need to know about the brain substrates of the sense of number:

Nieder, Andreas. “The neuronal code for number.” Nature Reviews Neuroscience (2016).



Stokes and Spaak review our recent work on single-trial analysis of working memory “delay” activity.   This showed that the classic profile of sustained activity as the memory substrate is an artifact of averaging across trials.  The assumption is that averaging cancels out noise.  Instead, it may be covering up important details of the dynamics of neural activity.

Read more here:
The Importance of Single-Trial Analyses in Cognitive Neuroscience
Mark Stokes and Eelke Spaak
Trends in Cognitive Sciences

The original paper:
Lunqvist, M., Rose, J., Herman, P, Brincat, S.L, Buschman, T.J., and Miller, E.K. (2016) Gamma and beta bursts underlie working memory.  Neuron, published online March 17, 2016. View PDF »

A wonderful tribute to a dear friend

Suzanne Corkin, Who Helped Pinpoint Nature of Memory, Dies at 79

That is all

Despite Bans, Many Still Text While Driving.  Radio Boston WBUR 90.0 FM
Listen here

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

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

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.

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,

Multitasking doesn’t work: Why focus isn’t just hocus-pocus.

Earl Miller answers questions about the why and why bad of multitasking. (1/27/16)

Earl Miller is scheduled to discuss the myth of multitasking on NBC’s TODAY show tomorrow morning (1/27/16).  Tune in (but only if it is not a distraction).

Miller Lab alumnus David Freedman is a winner of the 2016 Troland Research Award from the National Academy of Sciences.  Way to go, Dave!  Well deserved.

Miller Lab alumnus Melissa Warden is a winner of a 2015 NIH New Innovator Award.

We couldn’t be prouder of her if she were a Little Lebowski Urban Achiever.

Video of Earl Miller for the 2015 Professional Achievement Award from the Kent State University Alumni Association.

2015 Kent State Alumni Awards

And makes his hometown newspaper:
On the Move – The Cleveland Plain Dealer 9-23-15

Advance copy of our new paper:
Kornblith, S. Buschman, T.J., and Miller, E.K. (2015) Stimulus Load and Oscillatory Activity in Higher Cortex.  Cerebral Cortex.  doi: 10.1093/cercor/bhv182   Journal link

Exploring and exploiting a rich visual environment requires perceiving, attending, and remembering multiple objects simultaneously. Recent studies have suggested that this mental “juggling” of multiple objects may depend on oscillatory neural dynamics. We recorded local field potentials from the lateral intraparietal area, frontal eye fields, and lateral prefrontal cortex while monkeys maintained variable numbers of visual stimuli in working memory. Behavior suggested independent processing of stimuli in each hemifield. During stimulus presentation, higher-frequency power (50–100 Hz) increased with the number of stimuli (load) in the contralateral hemifield, whereas lower-frequency power (8–50 Hz) decreased with the total number of stimuli in both hemifields. During the memory delay, lower-frequency power increased with contralateral load. Load effects on higher frequencies during stimulus encoding and lower frequencies during the memory delay were stronger when neural activity also signaled the location of the stimuli. Like power, higher-frequency synchrony increased with load, but beta synchrony (16–30 Hz) showed the opposite effect, increasing when power decreased (stimulus presentation) and decreasing when power increased (memory delay). Our results suggest roles for lower-frequency oscillations in top-down processing and higher-frequency oscillations in bottom-up processing.

Micheli et al find that during sustained attention, successful near-threshold visual detection is predicted by increased phase synchrony between the frontal and temporal/parietal cortex.  They suggest that beta coherent states in the prefrontal cortex regulate top-down expectancy and coupling with posterior cortex facilitates the gating of that information.

Evidence for the role of beta in top-down selection continues to mount.

Micheli, Cristiano, et al. “Inferior-frontal cortex phase synchronizes with the temporal-parietal junction prior to successful change detection.” NeuroImage (2015).

Siegel, M., Buschman, T.J., and Miller, E.K. (2015) Cortical information flow during flexible sensorimotor decisions.  Science19 June 2015: 1352-1355.

During flexible behavior, multiple brain regions encode sensory inputs, the current task, and choices.  It remains unclear how these signals evolve. We simultaneously recorded neuronal activity from six cortical regions (MT, V4, IT, LIP, PFC and FEF) of monkeys reporting the color or motion of stimuli. Following a transient bottom-up sweep, there was a top-down flow of sustained task information from frontoparietal to visual cortex.  Sensory information flowed from visual to parietal and prefrontal cortex. Choice signals developed simultaneously in frontoparietal regions and travelled to FEF and sensory cortex. This suggests that flexible sensorimotor choices emerge in a frontoparietal network from the integration of opposite flows of sensory and task information.

From the MIT News Office:
Uncovering a dynamic cortex
Neuroscientists show that multiple cortical regions are needed to process information.