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  • 19
    Feb 2018

    Network dimensionality underlies flexible representation of cognitive information


    Miller Lab
    Neuroscience

    Interesting new work from Ito and Cole showing how network connectivity patterns is associated with representational flexibility.

    Ito, T., & Cole, M. W. (2018). Network dimensionality underlies flexible representation of cognitive information. bioRxiv, 262626.

  • 29
    Sep 2017

    Disruption of Conscious Access in Schizophrenia


    Miller Lab
    Neuroscience

    Due to a disruption of top-down attentional amplification.

    Berkovitch, L., Dehaene, S., & Gaillard, R. (2017). Disruption of Conscious Access in Schizophrenia. Trends in Cognitive Sciences.

  • 12
    Apr 2017

    When is it time to abandon the notion of feature detectors and adopt the cell assembly as the unit of cognition?


    Miller Lab
    Neuroscience

    Well said, Howard Eichenbaum.  Could agree more.  The time is nigh.

    Eichenbaum, H. (2017). Barlow versus Hebb: When is it time to abandon the notion of feature detectors and adopt the cell assembly as the unit of cognition?. Neuroscience Letters.

  • 23
    Aug 2016

    A Putative Multiple-Demand System in the Macaque Brain


    Miller Lab
    Neuroscience

    The multidemand network is a set of frontoparietal areas in humans that are recruited for a wide range of cognitive-demanding tasks.  Mitchell et al use FMRI connectivity analysis to identify a putative homolog in monkeys.

    Mitchell, Daniel J., et al. “A Putative Multiple-Demand System in the Macaque Brain.” The Journal of Neuroscience 36.33 (2016): 8574-8585.

  • 2
    Aug 2016

    Prefrontal neurons expand their representation of space by increase in dimensionality and decrease in noise correlation


    Miller Lab
    Neuroscience

    For much of the history of modern neuroscience, it has been a assumed that the neuron is the functional unit of the brain.  But now there is increasing evidence that ensembles of neurons, not individuals, are the functional units.  One line of evidence is that many neurons in higher cortical areas have “mixed selectivity” , responses to diverse combinations of variables; they don’t signal one “message”.  Thus, their activity only makes sense when simultaneously considering the activity of other neurons.  In fact, we (Rigotti et al., 2013; Fusi et al., 2016) have shown that mixed selectivity gives the brain the computational horsepower needed for complex behavior.

    In this paper, Dehaqani et al show that simultaneously recorded prefrontal cortex neurons have high-dimensional, mixed-selectivity, representations and convey more information as a population than even individuals.  This was especially true for parts of visual space that were weakly encoded by single neurons.  Less-informative neurons were recruited into ensemble to fully encode visual space.

    Prefrontal neurons expand their representation of space by increase in dimensionality and decrease in noise correlation.  Mohammad-Reza Dehaqani, Abdol-Hossein Vahabie, Mohammadbagher Parsa, Behrad Noudoost, Alireza Soltani
    doi: http://dx.doi.org/10.1101/065581

    Further reading:
    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 »

    Yuste, Rafael. “From the neuron doctrine to neural networks.” Nature Reviews Neuroscience 16.8 (2015): 487-497.

  • 4
    Feb 2016

    Why neurons mix: high dimensionality for higher cognition


    Miller Lab
    Miller Laboratory, Neuroscience

    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, http://dx.doi.org/10.1016/j.conb.2016.01.010.

  • 21
    Oct 2015

    Rhythms for Cognition: Communication through Coherence


    Miller Lab
    Neuroscience

    Pascal Fries walks us through the latest in the communication through coherence theory.

    Fries, Pascal. “Rhythms for Cognition: Communication through Coherence.”Neuron 88.1 (2015): 220-235.

  • 10
    Sep 2015

    Doping the Mind: Dopaminergic Modulation of Prefrontal Cortical Cognition


    Miller Lab
    Neuroscience

    Ranganath and Jacob walk us through the role that prefrontal cortex dopamine plays in cognition.

    Ranganath, Ajit, and Simon N. Jacob. “Doping the Mind Dopaminergic Modulation of Prefrontal Cortical Cognition.” The Neuroscientist (2015): 1073858415602850.

  • 2
    Jun 2015

    The Challenge of Understanding the Brain: Where We Stand in 2015


    Miller Lab
    Neuroscience

    One person’s (John Lisman) take on the state of the art of neuroscience in 2015.
    The Challenge of Understanding the Brain: Where We Stand in 2015

  • 2
    Jun 2015

    Flexible Coding of Task Rules in Frontoparietal Cortex: An Adaptive System for Flexible Cognitive Control


    Miller Lab
    Neuroscience

    Woolgar et al show preferential engagement of human frontoparietal networks with an increase in the complexity of task rules.  Plus, the frontoparietal cortex adjusts representations to make rules that are more behavioral confusable easier to discriminate.

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