The Department of Brain and Cognitive Sciences at MIT award Earl Miller the 2017 Award for Excellence in Graduate Teaching.

 

Earl Miller offers advice on how to avoid multitasking in the May 2018 issue of Redbook.

Life and Family – Redbook May 2018

Press release for our new paper:
A heavy working memory load may sink brainwave ‘synch’

The paper:
Pinotsis, D.A., Buschman, T.J. and Miller, E.K. (2018) Working Memory Load Modulates Neuronal Coupling. Cerebral Cortex.  https://doi.org/10.1093/cercor/bhy065  View PDF

Pinotsis, D.A., Buschman, T.J. and Miller, E.K. (2018) Working Memory Load Modulates Neuronal Coupling. Cerebral Cortex, 2018 https://doi.org/10.1093/cercor/bhy065

Abstract: There is a severe limitation in the number of items that can be held in working memory. However, the neurophysiological limits remain unknown. We asked whether the capacity limit might be explained by differences in neuronal coupling. We developed a theoretical model based on Predictive Coding and used it to analyze Cross Spectral Density data from the prefrontal cortex (PFC), frontal eye fields (FEF), and lateral intraparietal area (LIP). Monkeys performed a change detection task. The number of objects that had to be remembered (memory load) was varied (1–3 objects in the same visual hemifield). Changes in memory load changed the connectivity in the PFC–FEF–LIP network. Feedback (top-down) coupling broke down when the number of objects exceeded cognitive capacity. Thus, impaired behavioral performance coincided with a break-down of Prediction signals. This provides new insights into the neuronal underpinnings of cognitive capacity and how coupling in a distributed working memory network is affected by memory load.

An article in Science News about new ideas on the role of brain waves.  It also discuss three new papers from the Miller Lab.

Brain waves may focus attention and keep information flowing  Science New March 13, 2018

Here are the papers that are discussed:

Lundqvist, M., Herman, P. Warden, M.R., Brincat, S.L., and Miller, E.K. (2018) Gamma and beta bursts during working memory read-out suggest roles in its volitional control. Nature Communications. 9, 394   View PDF

Wutz, A., Loonis, R., Roy, J.E., Donoghue, J.A., and Miller, E.K. (2018)  Different levels of category abstraction by different dynamics in different prefrontal areas. Neuron 97: 1-11.  View PDF

Bastos, A.M., Loonis, R., Kornblith, S., Lundqvist, M., and Miller, E.K. (2018)  Laminar recordings in frontal cortex suggest distinct layers for maintenance and control of working memory.  Proceedings of the National Academy of Sciences.  View PDF

From Cortech Solutions.

Personal Highlights of the Plenary Sessions
Earl Miller: Rule+Rhythms=Cognition

 

Lundqvist, M., Herman, P. Warden, M.R., Brincat, S.L., and Miller, E.K. (2018) Gamma and beta bursts during working memory read-out suggest roles in its volitional control. Nature Communications. 9, Article number: 394 doi:10.1038/s41467-017-02791-8

Abstract:
Working memory (WM) activity is not as stationary or sustained as previously thought. There are brief bursts of gamma (~50–120 Hz) and beta (~20–35 Hz) oscillations, the former linked to stimulus information in spiking. We examined these dynamics in relation to readout and control mechanisms of WM. Monkeys held sequences of two objects in WM to match to subsequent sequences. Changes in beta and gamma bursting suggested their distinct roles. In anticipation of having to use an object for the match decision, there was an increase in gamma and spiking information about that object and reduced beta bursting. This readout signal was only seen before relevant test objects, and was related to premotor activity. When the objects were no longer needed, beta increased and gamma decreased together with object spiking information. Deviations from these dynamics predicted behavioral errors. Thus, beta could regulate gamma and the information in WM.

Wutz, A., Loonis, R., Roy, J.E., Donoghue, J.A., and Miller, E.K. (2018) Different levels of category abstraction by different dynamics in different prefrontal areas. Neuron  published online Jan 25 2018.

SUMMARY

Categories can be grouped by shared sensory attributes (i.e. cats) or by a more abstract rule (i.e. animals). We explored the neural basis of abstraction by recording from multi-electrode arrays in prefrontal cortex (PFC) while monkeys performed a dot-pattern categorization task. Category abstraction was varied by the degree of exemplar distortion from the prototype pattern. Different dynamics in different PFC regions processed different levels of category abstraction. Bottom-up dynamics (stimulus-locked gamma power and spiking) in ventral PFC processed more low-level abstractions whereas top-down dynamics (beta power and beta spike-LFP coherence) in dorsal PFC processed more high-level abstractions. Our results suggest a two-stage, rhythm-based model for abstracting categories.

Andre Bastos was selected at a Rising Star by the Association for Psychological Science.  Indeed, he is.  Congrats, Andre!

http://www.psychologicalscience.org/rising-stars/stars.cfm

Check out Andre’s latest paper:
Bastos, A.M., Loonis, R., Kornblith, S., Lundqvist, M., and Miller, E.K. (2018)  Laminar recordings in frontal cortex suggest distinct layers for maintenance and control of working memory.  Proceedings of the National Academy of Sciencesdoi:10.1073/pnas.1710323115   View PDF

High frequency waves (Davis on trumpet) carry sensory inputs from the back of the brain to the front. Low frequency waves (Mingus on bass) carry executive (top-down) information from the front to the back of the brain. The low frequencies control the expression of high frequencies. That’s how you choose what sensory inputs to hold in mind (working memory). (Image: Andre Bastos)

It makes sense because we all know that the bass should guide the lead instruments. Am I right?

Bastos, A.M., Loonis, R., Kornblith, S., Lundqvist, M., and Miller, E.K. (2018) Laminar recordings in frontal cortex suggest distinct layers for maintenance and control of working memory. Proceedings of the National Academy of Sciences. published ahead of print January 16, 2018, doi:10.1073/pnas.1710323115

Read MIT press release here.

 

This is the first of three papers that all lead to the same general conclusion:  Sensory (bottom-up) information is fed forward through cortex by gamma (>50 Hz) waves in superficial cortical layers. Executive (top-down) information is fed back through cortex by alpha/beta waves (4-22 Hz) in deep cortical layers. The beta waves in deep layers regulate superficial layer gamma in a push-pull fashion thereby allowing top-down information to control the flow of bottom-up sensory information. This allows volitional control over what we hold in mind.  Stayed tuned for the other two papers. They will appear in the next few weeks.

Bastos, A.M., Loonis, R., Kornblith, S., Lundqvist, M., and Miller, E.K. (2018) Laminar recordings in frontal cortex suggest distinct layers for maintenance and control of working memory. Proceedings of the National Academy of Sciences. published ahead of print January 16, 2018, doi:10.1073/pnas.1710323115

Read MIT press release here.

Gamma and beta bursts during working memory readout suggest roles in its volitional control
Lundqvist et al  Nature Communications, in press.

Laminar recordings in frontal cortex suggest distinct layers for maintenance and control of working memory
Bastos et al   PNAS, in press

Different levels of category abstraction by different dynamics in different prefrontal areas
Wutz et al   Neuron, in press

Stay tuned for what they are about and what they mean.  They add up to a new model of working memory.

New paper accepted:
“Laminar recordings in frontal cortex suggest distinct layers for maintenance and control of working memory”
Bastos, Loonis, Kornblith, Lundqvist, and Miller. PNAS, in press  
Coming soon. Stay tuned.

Intrinsic neuronal dynamics predict distinct functional roles during working memory
Dante Francisco Wasmuht, Eelke Spaak, Timothy J. Buschman, Earl K. Miller, Mark G. Stokes
doi: https://doi.org/10.1101/233171

Abstract
Working memory (WM) is characterized by the ability to maintain stable representations over time; however, neural activity associated with WM maintenance can be highly dynamic. We explore whether complex population coding dynamics during WM relate to the intrinsic temporal properties of single neurons in lateral prefrontal cortex (lPFC), the frontal eye fields (FEF) and lateral intraparietal cortex (LIP) of two monkeys (Macaca mulatta). We found that cells with short timescales carried memory information relatively early during memory encoding in lPFC; whereas long timescale cells played a greater role later during processing, dominating coding in the delay period. We also observed a link between functional connectivity at rest and intrinsic timescale in FEF and LIP. Our results indicate that individual differences in the temporal processing capacity predicts complex neuronal dynamics during WM; ranging from rapid dynamic encoding of stimuli to slower, but stable, maintenance of mnemonic information.

Enel et al use reservoir computing to understand how mixed selectivity dynamic in the prefrontal cortex support complex, flexible behavior.  Reservoir computing (like mixed selectivity) involves inputs fed to a dynamical system that learns only at the output stage.  They argue that this approach is good framework for understanding how cortical dynamics produce higher cognitive functions.

Enel, P., Procyk, E., Quilodran, R., & Dominey, P. F. (2016). Reservoir computing properties of neural dynamics in prefrontal cortexPLoS computational biology12(6), e1004967.

For more about mixed selectivity see:
Fusi, S., Miller, E.K., and Rigotti, M. (2016) Why neurons mix: High dimensionality for higher cognition.  Current Opinion in Neurobiology. 37:66-74  doi:10.1016/j.conb.2016.01.010. View PDF »

Rigotti, M., Barak, O., Warden, M.R., Wang, X., Daw, N.D., Miller, E.K., & Fusi, S. (2013) The importance of mixed selectivity in complex cognitive tasks. Nature, 497, 585-590, doi:10.1038/nature12160. View PDF »

Press release for our new paper in Neuron: Brain waves reflect different types of learning

Lindsay, G.W., Rigotti, M., Warden, M.R., Miller, E.K., and Fusi, S. (2017) Hebbian Learning in a Random Network Captures Selectivity Properties of Prefrontal CortexJournal of Neuroscience.  6 October 2017, 1222-17; DOI: https://doi.org/10.1523/JNEUROSCI.1222-17.2017   View PDF

A Meta-Analysis Suggests Different Neural Correlates for Implicit and Explicit Learning
Roman F. Loonis, Scott L. Brincat, Evan G. Antzoulatos, Earl K. Miller
Neuron, 96(2): p521-534, 2017.

Preview by Matthew Chafee and David Crowe:
Implicit and Explicit Learning Mechanisms Meet in Monkey Prefrontal Cortex

American Academy of Arts and Sciences. Induction Ceremony October 7, 2017.
The American Academy of Arts and Sciences is of the nation’s most prestigious honorary societies, the academy is also a leading center for independent policy research. Members contribute to academy publications, as well as studies of science and technology policy, energy and global security, social policy and American institutions, the humanities and culture, and education.

Review of the neural mechanisms behind persistent spiking activity and working memory.

Zylberberg, J., & Strowbridge, B. W. (2017). Mechanisms of persistent activity in cortical circuits: possible neural substrates for working memory. Annual Review of Neuroscience40.

There is little doubt that spiking during memory delays play a role in working memory.  But how persistent is the activity and how are the memories actually stored?  For another perspective see:
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 »

Gradual progression from sensory to task-related processing in cerebral cortex
Scott L. Brincat*, Markus Siegel*, Constantin von Nicolai, Earl K. Miller
doi: https://doi.org/10.1101/195602

Abstract

Somewhere along the cortical hierarchy, behaviorally relevant information is distilled from raw sensory inputs. We examined how this transformation progresses along multiple levels of the hierarchy by comparing neural representations in visual, temporal, parietal, and frontal cortices in monkeys categorizing across three visual domains (shape, motion direction, color). Representations in visual areas MT and V4 were tightly linked to external sensory inputs. In contrast, prefrontal cortex (PFC) largely represented the abstracted behavioral relevance of stimuli (task rule, motion category, color category). Intermediate-level areas — posterior inferotemporal (PIT), lateral intraparietal (LIP), and frontal eye fields (FEF) — exhibited mixed representations. While the distribution of sensory information across areas aligned well with classical functional divisions — MT carried stronger motion information, V4 and PIT carried stronger color and shape information — categorical abstraction did not, suggesting these areas may participate in different networks for stimulus-driven and cognitive functions. Paralleling these representational differences, the dimensionality of neural population activity decreased progressively from sensory to intermediate to frontal cortex. This shows how raw sensory representations are transformed into behaviorally relevant abstractions and suggests that the dimensionality of neural activity in higher cortical regions may be specific to their current task.

Come see Pavlov’s Dogz at Songbyrd DC on Sunday Nov 12 of the SFN meeting.

9:30pm Songbyrd DC  11/12/17
http://www.songbyrddc.com/shows/2017-11-12-pavlolvs-dogz

Pavlov’s Dogz are a roaming band of neuroscientist-musicians who get together at conference locations around the world to play shows.
Band members:
Tim Bussey
Brad Postle
Earl Miller
Paula Croxson
Charan Ranganath
Joel Voss
Daniela Schiller
Jess Grahn
Mick Rugg
Andy Lee

We show how limitations in cognitive capacity (how many thoughts you can think at the same time – very few) may be due to changes in rhythmic coupling between cortical areas.  More specifically, feedback coupling breaks down when capacity is exceeded.

Working Memory Load Modulates Neuronal Coupling  Dimitris A Pinotsis, Timothy J Buschman, Earl K Miller
doi: https://doi.org/10.1101/192336

 

New manuscript submitted to bioRxiv:

Neuronal rhythms orchestrate cell assembles to distinguish perceptual categories
Morteza Moazami Goudarzi, Jason Cromer, Jefferson Roy, Earl K. Miller
doi: https://doi.org/10.1101/191247

Abstract
Categories are reflected in the spiking activity of neurons. However, how neurons form ensembles for categories is unclear. To address this, we simultaneously recorded spiking and local field potential (LFP) activity in the lateral prefrontal cortex (lPFC) of monkeys performing a delayed match to category task with two independent category sets (Animals: Cats vs Dogs; Cars: Sports Cars vs Sedans). We found stimulus and category information in alpha and beta band oscillations. Different category distinctions engaged different frequencies. There was greater spike field coherence (SFC) in alpha (~8-14 Hz) for Cats and in beta (~16-22 Hz) for Dogs. Cars showed similar differences, albeit less pronounced: greater alpha SFC for Sedans and greater beta SFC for Sports Cars. Thus, oscillatory rhythms can help coordinate neurons into different ensembles. Engagement of different frequencies may help differentiate the categories.

Miller, Earl. “Earl K. Miller.” Neuron 95 (2017): 1237.
DOI: http://dx.doi.org/10.1016/j.neuron.2017.08.035

Earl Miller studies the neural basis of high-level cognitive functions. In an interview with Neuron, he discusses the need for a holistic approach to figure out the brain, how ideas don’t happen in a vacuum, and the challenge of convincing the public that science produces facts; he also shares an open invitation to see Pavlov’s Dogz.  View PDF