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  • 11
    Sep 2018

    A Flexible Model of Working Memory


    Miller Lab
    Miller Laboratory, Neuroscience

    Bouchacourt and Buschman describe a two-layer model of working memory. A sensory layer feeds into an unstructured layer of neurons with random connections (i.e., “mixed-selectivity” type neurons).  It is flexible but interference between representations results in a capacity limit.  Sounds like working memory to me.

    Bouchacourt, F., & Buschman, T. J. (2018). A Flexible Model of Working Memory. bioRxiv, 407700.

    More about mixed-selectivity:
    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
    Sep 2018

    Andre Bastos receives a K99 Award


    Miller Lab
    In The News, Miller Laboratory
    Andre Bastos receives a K99 Award

    Congrats to Miller Lab postdoc Andre Bastos for being awarded a prestigious K99 Award from the National Institutes of Health.

  • 4
    Sep 2018

    Phase-coding memories in mind


    Miller Lab
    Neuroscience

    Nice summary of phase coding models of working memory by Hakim and Vogel, including a recent paper by Bahramisharif et al.

    Hakim, N., & Vogel, E. K. (2018). Phase-coding memories in mind. PLoS biology, 16(8), e3000012.

    Bahramisharif, A., Jensen, O., Jacobs, J., & Lisman, J. (2018). Serial representation of items during working memory maintenance at letter-selective cortical sites. PLoS biology, 16(8), e2003805.

  • 29
    Aug 2018

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


    Miller Lab
    Miller Laboratory

    Wasmuht, D. F., Spaak, E., Buschman, T. J., Miller, E. K., & Stokes, M. G. (2018). Intrinsic neuronal dynamics predict distinct functional roles during working memory. Nature Communications.

    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 find that cells with short timescales carry memory information relatively early during memory encoding in lPFC; whereas long-timescale cells play a greater role later during processing, dominating coding in the delay period. We also observe a link between functional connectivity at rest and the intrinsic timescale in FEF and LIP. Our results indicate that individual differences in the temporal processing capacity predict complex neuronal dynamics during WM, ranging from rapid dynamic encoding of stimuli to slower, but stable, maintenance of mnemonic information.

  • 28
    Aug 2018

    Attention is rhythmic!


    Miller Lab
    Neuroscience

    Two new, exciting papers in Neuron that “put the last nail(s) in the coffin of sustained attention.”  They present compelling evidence that sustained attention is not sustained at all but fluctuates with theta rhythms and alpha/beta rhythms. This provides yet more evidence that the brain works by rhythmic switching between representations.

    Ian C. Fiebelkorn, Mark A. Pinsk, Sabine Kastner
    A Dynamic Interplay within the Frontoparietal Network Underlies Rhythmic Spatial Attention
    Neuron, Volume 99, Issue 4, 22 August 2018, Pages 842-853.e8

    Randolph F. Helfrich, Ian C. Fiebelkorn, Sara M. Szczepanski, Jack J. Lin, Josef Parvizi, Robert T. Knight, Sabine Kastner
    Neural Mechanisms of Sustained Attention Are Rhythmic
    Neuron, Volume 99, Issue 4, 22 August 2018, Pages 854-865.e5

    An excellent Preview by Rufin VanRullen: Attention Cycles

    For further reading:
    Buschman, T.J. and Miller, E.K. (2009) Serial, covert, shifts of attention during visual search are reflected by the frontal eye fields and correlated with population oscillations. Neuron, 63: 386-396. View PDF »

    Buschman,T.J. and Miller, E.K. (2010) Shifting the Spotlight of Attention: Evidence for Discrete Computations in Cognition. Frontiers in Human Neuroscience. 4(194): 1-9. View PDF »

  • 14
    Aug 2018

    Phase-Locked Stimulation during Cortical Beta Oscillations Produces Bidirectional Synaptic Plasticity in Awake Monkeys


    Miller Lab
    Neuroscience

    Beta rhythms play a role in synaptic plasticity.

    Zanos, S., Rembado, I., Chen, D., & Fetz, E. E. (2018). Phase-Locked Stimulation during Cortical Beta Oscillations Produces Bidirectional Synaptic Plasticity in Awake Monkeys. Current Biology.

  • 14
    Aug 2018

    Structuring of Abstract Working Memory Content by Fronto-parietal Synchrony in Primate Cortex


    Miller Lab
    Neuroscience

    Super-cool paper by Andreas Nieder and crew.  Frontal-parietal beta synchrony encodes the most recent numerical input.  Theta synchrony distinguishes between different numerosities held in working memory.  The spiking of mixed-selectivity neurons multiplexed both task-relevant and irrelevant stimuli but they were separated in different phases of theta oscillations.  Powerful support that neural oscillations functionally organize spiking activty.

    Jacob, S. N., Hähnke, D., & Nieder, A. (2018). Structuring of Abstract Working Memory Content by Fronto-parietal Synchrony in Primate Cortex. Neuron, 99(3), 588-597.

  • 11
    Aug 2018

    Blog: Does persistent spiking hold memories “in mind” (i.e., working memory)?


    Miller Lab
    In The News, Miller Laboratory

    Our dual Perspectives “debate” paper re: Does persistent spiking hold memories “in mind” (i.e., working memory):
    Paper and link to opposing paper: Working Memory: Delay Activity, Yes! Persistent Activity? Maybe Not

    Press release: To understand working memory, scientists must resolve this debate

    Our two cents:
    Surprised this became a debate.  All we are saying is that if you look at delay activity more closely (on single trials) it’s bursty. Something else (synaptic weight changes) could be helping. Adding synaptic mechanisms saves energy and confers functional advantages.
    Lundqvist, M., Rose, J., Herman, P., Brincat, S. L., Buschman, T. J., & Miller, E. K. (2016). Gamma and beta bursts underlie working memory. Neuron, 90(1), 152-164.

    And it leaves room for network rhythms that may underlie executive control of working memory.
    Bastos, A. M., Loonis, R., Kornblith, S., Lundqvist, M., & 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, 201710323.

    Lundqvist, M., Herman, P., Warden, M. R., Brincat, S. L., & Miller, E. K. (2018). Gamma and beta bursts during working memory readout suggest roles in its volitional control. Nature Communications, 9(1), 394.

    Yuri Buzsaki pointed out that his lab reported that in PFC working memories are maintained by internally generated cell assembly sequences. The few persistently firing neurons were interneurons.
    Fujisawa S, Amarasingham A, Harrison MT, Buzsáki G.
    Nat Neurosci. 2008.

    Also, the idea that synaptic weight changes help maintain working memories is not altogether new.  Goldman-Rakic suggested such a mechanism.  Her lab found that sparse firing in the PFC produces temporary changes in synaptic weights.  Importantly, if neurons firing too fast, inhibitory mechanisms kick in and you don’t get the weight changes. See:

    Wang, Y., Markram, H., Goodman, P.H., Berger, T.K., Ma, J., and Goldman-Rakic, P.S. (2006). Heterogeneity in the pyramidal network of the medial prefrontal cortex. Nat. Neurosci. 9, 534–542.

    But, hey, don’t take our word for it:  Look at memory delay activity on single trials and tell us what *you* see.

  • 31
    Jul 2018

    Adaptive coding in the human brain: Distinct object features are encoded by overlapping voxels in frontoparietal cortex


    Miller Lab
    Neuroscience

    More evidence for mixed-selectivity in the cortex.  This time with voxels in the human brain.

    Jackson, J., & Woolgar, A. (2018). Adaptive coding in the human brain: Distinct object features are encoded by overlapping voxels in frontoparietal cortex. Cortex.

    Read more about mixed selectivity:
    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 »

    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 »

  • 3
    Jul 2018

    Coordinated prefrontal–hippocampal activity and navigation strategy-related prefrontal firing during spatial memory formation


    Miller Lab
    Neuroscience

    Enhanced prefrontal-hippocampal spike-LFP coupling during learning of a spatial strategy (but not other strategies).

    Negrón-Oyarzo, I., Espinosa, N., Aguilar, M., Fuenzalida, M., Aboitiz, F., & Fuentealba, P. (2018). Coordinated prefrontal–hippocampal activity and navigation strategy-related prefrontal firing during spatial memory formation. Proceedings of the National Academy of Sciences, 201720117.

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