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  • 18
    Jan 2018

    Miller Lab postdoc Andre Bastos selected as an APS Rising Star.


    Miller Lab
    In The News, Miller Laboratory

    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 Sciences. doi:10.1073/pnas.1710323115   View PDF

  • 16
    Jan 2018

    Our new model of working memory as illustrated by Charles Mingus and Miles Davis


    Miller Lab
    Miller Laboratory, Neuroscience
    Our new model of working memory as illustrated by Charles Mingus and Miles Davis

    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.

     

  • 16
    Jan 2018

    New paper: Laminar recordings in frontal cortex suggest distinct layers for maintenance and control of working memory


    Miller Lab
    Miller Laboratory

    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.

  • 3
    Jan 2018

    Three new papers in press


    Miller Lab
    Miller Laboratory, Neuroscience

    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.

  • 20
    Dec 2017

    New paper accepted: “Laminar recordings in frontal cortex suggest distinct layers for maintenance and control of working memory”


    Miller Lab
    Miller Laboratory, Neuroscience

    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.

  • 14
    Dec 2017

    New results: Intrinsic neuronal dynamics predict distinct functional roles during working memory


    Miller Lab
    Miller Laboratory, Neuroscience

    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.

  • 8
    Nov 2017

    Reservoir Computing Properties of Neural Dynamics in Prefrontal Cortex


    Miller Lab
    Miller Laboratory, Neuroscience

    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 cortex. PLoS computational biology, 12(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 »

  • 11
    Oct 2017

    Press release: Brain waves reflect different types of learning


    Miller Lab
    In The News, Miller Laboratory

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

  • 11
    Oct 2017

    New Paper: Hebbian Learning in a Random Network Captures Selectivity Properties of Prefrontal Cortex


    Miller Lab
    Miller Laboratory, Neuroscience

    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 Cortex. Journal of Neuroscience.  6 October 2017, 1222-17; DOI: https://doi.org/10.1523/JNEUROSCI.1222-17.2017   View PDF

  • 11
    Oct 2017

    New paper: A Meta-Analysis Suggests Different Neural Correlates for Implicit and Explicit Learning


    Miller Lab
    Miller Laboratory, Neuroscience

    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

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