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  • 13
    Nov 2015

    Long-range attention networks: circuit motifs underlying endogenously controlled stimulus selection


    Miller Lab
    Neuroscience

    Excellent review of how wide-spread brain areas use synchronized rhythms form networks for focusing attention.  Very comprehensive and thorough on both a maco and micro-circuit level.

    Womelsdorf, Thilo, and Stefan Everling. “Long-range attention networks: circuit motifs underlying endogenously controlled stimulus selection.” Trends in Neurosciences 38.11 (2015): 682-700.

  • 3
    Nov 2015

    A Large-Scale Circuit Mechanism for Hierarchical Dynamical Processing in the Primate Cortex


    Miller Lab
    Neuroscience

    Wang and colleagues present a model of the whole cortex (almost).  A gradient of synaptic excitation results in sensory areas show fast responses while cognitive areas show slow integrative activity.  Different temporal hierarchies/dynamics coexist in the same networks.

    A Large-Scale Circuit Mechanism for Hierarchical Dynamical Processing in the Primate Cortex
    Rishidev Chaudhuri, Kenneth Knoblauch, Marie-Alice Gariel,  Henry Kennedy, Xiao-Jing Wang
    Neuron, Volume 88, Issue 2, 21 October 2015, Pages 419–431

    In general, this fits pretty well with our recent study of actual neural dynamics across the cortex:
    Siegel, M., Buschman, T.J., and Miller, E.K. (2015) Cortical information flow during flexible sensorimotor decisions.  Science. 19 June 2015: 1352-1355.  View PDF

  • 3
    Nov 2015

    The Speed of Alpha-Band Oscillations Predicts the Temporal Resolution of Visual Perception


    Miller Lab
    Neuroscience

    Samaha and Postle report on the close relationship between alpha-band oscillations and human perception, including that individuals with higher alpha frequencies have vision with a finer temporal resolution.  Cool.

    Samaha, Jason, and Bradley R. Postle. “The Speed of Alpha-Band Oscillations Predicts the Temporal Resolution of Visual Perception.” Current Biology (2015).

  • 27
    Oct 2015

    Thalamic control of sensory selection in divided attention


    Miller Lab
    Neuroscience

    It is widely thought that the volitional focusing of attention on a sensory input depends on top-down influences from the prefrontal cortex (PFC) acting on sensory cortex.  However, much of the evidence for this is circumstantial.  Halassa et al now provide direct evidence using optogenetic manipulation in mice.  When they temporarily disrupted the PFC, mice had trouble focusing on a visual input in the face of an auditory distraction and vice-versa.  Moreover, they went on to show that the PFC acts on sensory cortex, not directly but, through the thalamic reticular nucleus (TRN).  Manipulation of thalamocortical circuits showed that behavior depended on PFC interactions with the thalamus, not on PFC interactions with sensory cortex.  Further, thalamic activity was correlated with behavioral performance and its manipulation was causal to performance.  This all suggests that attention is focused when the PFC acts on sensory cortex via the thalamus.

    Wimmer, R. D., Schmitt, L. I., Davidson, T. J., Nakajima, M., Deisseroth, K., & Halassa, M. M. (2015). Thalamic control of sensory selection in divided attention. Nature.

  • 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.

  • 13
    Oct 2015

    Neurocognitive Architecture of Working Memory


    Miller Lab
    Neuroscience

    Eriksson et al discuss working memory, not as an isolated function, but as an interaction between component processes such as attention, propsection, perception and long-term memory.

    Eriksson, Johan, et al. “Neurocognitive Architecture of Working Memory.”Neuron 88.1 (2015): 33-46.

  • 13
    Oct 2015

    From Behavior to Neural Dynamics: An Integrated Theory of Attention


    Miller Lab
    Neuroscience

    Tim Buschman and Sabine Kastner review work on visual attention and propose a new theory that ties together a wide range of observations.  Here’s an outline of the theory in their own words:

    1. Attention can either be (a) automatically grabbed by salient stimuli or (b) guided by task representations in frontal and parietal regions to specific spatial locations or features.
    2. The pattern-completion nature of sensory cortex sharpens the broad top-down attentional bias, restricting it to perceptually relevant representations. Interactions with bottom-up sensory drive will emphasize specific objects.
    3. Interneuron-mediated lateral inhibition normalizes activity and, thus, suppresses competing stimuli. This results in increased sensitivity and decreased noise correlations.
    4. Lateral inhibition also leads to the generation of high-frequency synchronous oscillations within a cortical region. Inter-areal synchronization follows as these local oscillations synchronize along with the propagation of a bottom-up sensory drive. Both forms of synchrony act to further boost selected representations.
    5. Further buildup of inhibition acts to “reset” the network, thereby restarting the process. This reset allows the network to avoid being captured by a single stimulus and allows a positive-only selection mechanism to move over time.

    Makes a lot of sense.
    Buschman, Timothy J., and Sabine Kastner. “From Behavior to Neural Dynamics: An Integrated Theory of Attention.” Neuron 88.1 (2015): 127-144.

  • 12
    Oct 2015

    Simple Learned Weighted Sums of Inferior Temporal Neuronal Firing Rates Accurately Predict Human Core Object Recognition Performance


    Miller Lab
    Neuroscience

    Jim DiCarlo and crew show how a weighted average of firing rates of neurons in inferior temporal cortex can explain performance on an object recognition task.

    Majaj, Najib J., et al. “Simple Learned Weighted Sums of Inferior Temporal Neuronal Firing Rates Accurately Predict Human Core Object Recognition Performance.” The Journal of Neuroscience 35.39 (2015): 13402-13418.

  • 12
    Oct 2015

    Single-cell coding of sensory, spatial and numerical magnitudes in primate prefrontal, premotor and cingulate motor cortices


    Miller Lab
    Neuroscience

    Eiselt and Nieder show that coding of numerical magnitudes is the prefrontal cortex but not the premotor or cingulate cortex.

    Eiselt, Anne-Kathrin, and Andreas Nieder. “Single-cell coding of sensory, spatial and numerical magnitudes in primate prefrontal, premotor and cingulate motor cortices.” Experimental brain research (2015): 1-14.

  • 8
    Oct 2015

    Plasticity in oscillatory coupling between hippocampus and cortex


    Miller Lab
    Neuroscience

    Review: Kei Igarashi argues that learning-related changes in synchrony between oscillatory activity in the cortex and hippocampus enhances neural communication and thus supports memory storage and recall.

     Igarashi, Kei M. “Plasticity in oscillatory coupling between hippocampus and cortex.” Current Opinion in Neurobiology 35 (2015): 163-168.

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