Miller Lab postdoc Mikael Lunqvist won a NARSAD Young Investigator Grant.  Congrats, Mikael!

Read Mikael’s recent paper to see what the fuss is all about:
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 »

Info about NARSAD grants:

Here’s Mikael:

Mikael Lundqvist

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Top 100 Neuroscience Blogs and Websites for Neuroscientists

Miller Lab Alumnus, Wael Asaad, shows that neurons in the prefrontal cortex can figure out which prior events get credit for the consequences of our actions.

Asaad, W. F., Lauro, P. M., Perge, J. A., & Eskandar, E. N. (2017). Prefrontal Neurons Encode a Solution to the Credit-Assignment ProblemJournal of Neuroscience37(29), 6995-7007.

12 Jul 2017
July 12, 2017

Welcome Meredith

Miller Laboratory

The Miller Lab welcomes new Lab Manager, Meredith Mahnke.  Glad to have you aboard.

You Asked: How Can I Use More of My Brain? Time, June 14, 2017


Neurons in the prefrontal cortex keeps track of elapsed time (even though time was not explicitly relevant) via sequential firing of neurons.  The overlap of sequences depended on the degree of similarity of the item being held in memory.  The time-keeping showed a Weber-fraction-like decrease in precision as time passed.

Compressed timeline of recent experience in monkey lPFC
Zoran Tiganj, Jason A Cromer, Jefferson E Roy, Earl K Miller, Marc W Howard

New result on bioRxiv:
Gamma and beta bursts during working memory read-out suggest roles in its volitional control
  Mikael Lundqvist, Pawel Herman, Melissa R Warden, Scott L Brincat, Earl K Miller


Working memory (WM) activity is not as stationary or sustained as previously thought. There are brief bursts of gamma (55 to 120 Hz) and beta (20 to 35 Hz) oscillations, the former linked to stimulus information in spiking. We examine these dynamics in relation to read-out from WM, which is still not well understood. Monkeys held a sequence of two objects and had to decide if they matched a subsequent sequence. Changes in the balance of beta/gamma suggested their role in WM control. In anticipation of having to use an object for the match decision, there was an increase in spiking information about that object along with an increase in gamma and a decrease in beta. When an object was no longer needed, beta increased and gamma as well as spiking information about that object decreased. Deviations from these dynamics predicted behavioral errors. Thus, turning up or down beta could regulate gamma and the information in working memory.

Still think that single neurons with specific functions rule the brain?  Let us persuade you otherwise.  We argue that cognitive control stems from dynamic, context-dependent population coding.

Stokes, M., Buschman, T.J., and Miller, E.K. (2017) Dynamic coding for flexible cognitive control.  The Wiley Handbook of Cognitive Control, The Wiley Handbook of Cognitive Control, Edited by Tobias Egner, John Wiley & Sons, 2017(Chichester, West Sussex, UK). View PDF

New Miller Lab paper:
Jia, N., Brincat, S.L., Salazar-Gomez, A., Panko, M., Guenther, F. and Miller, E.K. (2017) Decoding of intended saccade direction in an oculomotor brain-computer interface. Journal of Neural Engineering, 2017.

Objective. To date, invasive brain-computer interface (BCI) research has largely focused on replacing lost limb functions using signals from of hand/arm areas of motor cortex. However, the oculomotor system may be better suited to BCI applications involving rapid serial selection from spatial targets, such as choosing from a set of possible words displayed on a computer screen in an augmentative and alternative communication (AAC) application. Here we aimed to demonstrate the feasibility of a BCI utilizing the oculomotor system. Approach. We developed a chronic intracortical BCI in monkeys to decode intended saccadic eye movement direction using activity from multiple frontal cortical areas. Main results. Intended saccade direction could be decoded in real time with high accuracy, particularly at contralateral locations. Accurate decoding was evident even at the beginning of the BCI session; no extensive BCI experience was necessary. High-frequency (80-500 Hz) local field potential magnitude provided the best performance, even over spiking activity, thus simplifying future BCI applications. Most of the information came from the frontal and supplementary eye fields, with relatively little contribution from dorsolateral prefrontal cortex. Significance. Our results support the feasibility of high-accuracy intracortical oculomotor BCIs that require little or no practice to operate and may be ideally suited for point and click computer operation as used in most current AAC systems.

Antzoulatos, E. G., & Miller, E. K. (2016). Synchronous beta rhythms of frontoparietal networks support only behaviorally relevant representations. eLife, 5, e17822.

Categorization has been associated with distributed networks of the primate brain, including the prefrontal cortex (PFC) and posterior parietal cortex (PPC). Although category-selective spiking in PFC and PPC has been established, the frequency-dependent dynamic interactions of frontoparietal networks are largely unexplored. We trained monkeys to perform a delayed-match-to-spatial-category task while recording spikes and local field potentials from the PFC and PPC with multiple electrodes. We found category-selective beta- and delta-band synchrony between and within the areas. However, in addition to the categories, delta synchrony and spiking activity also reflected irrelevant stimulus dimensions. By contrast, beta synchrony only conveyed information about the task-relevant categories. Further, category-selective PFC neurons were synchronized with PPC beta oscillations, while neurons that carried irrelevant information were not. These results suggest that long-range beta-band synchrony could act as a filter that only supports neural representations of the variables relevant to the task at hand.

Why multitasking is BAD for your brain: Neuroscientist warns it wrecks productivity and causes mistakes

  • Earl Miller has advised that people should avoid multitasking altogether
  • Switching between tasks take more mental energy to get back on track
  • They advise removing distractions to overcome the brain’s thirst for new information and to block out time to focus on individual tasks

Read more

Stanley, D.A., Roy, J.E., Aoi, M.C., Kopell, N.J., and Miller, E.K. (2016) Low-beta oscillations turn up the gain during category judgments.  Cerebral Cortex. doi: 10.1093/cercor/bhw356  View PDF

Synchrony between local field potential (LFP) rhythms is thought to boost the signal of attended sensory inputs. Other cognitive functions could benefit from such gain control. One is categorization where decisions can be difficult if categories differ in subtle ways. Monkeys were trained to flexibly categorize smoothly varying morphed stimuli, using orthogonal boundaries to carve up the same stimulus space in 2 different ways. We found evidence for category-specific patterns of low-beta (16–20 Hz) synchrony in the lateral prefrontal cortex (PFC). This synchrony was stronger when a given category scheme was relevant. We also observed an overall increase in low-beta LFP synchrony for stimuli that were near the category boundary and thus more difficult to categorize. Beta category selectivity was evident in partial field–field coherence measurements, which measure local synchrony, but the boundary enhancement was not. Thus, it seemed that category selectivity relied on local interactions while boundary enhancement was a more global effect. The results suggest that beta synchrony helps form category ensembles and may reflect recruitment of additional cortical resources for categorizing challenging stimuli, thus serving as a form of gain control.

Now out from behind the paywall:

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