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Thalamic control of sensory selection in divided attention

Nature volume 526, pages 705709 (29 October 2015) | Download Citation


How the brain selects appropriate sensory inputs and suppresses distractors is unknown. Given the well-established role of the prefrontal cortex (PFC) in executive function1, its interactions with sensory cortical areas during attention have been hypothesized to control sensory selection2,3,4,5. To test this idea and, more generally, dissect the circuits underlying sensory selection, we developed a cross-modal divided-attention task in mice that allowed genetic access to this cognitive process. By optogenetically perturbing PFC function in a temporally precise window, the ability of mice to select appropriately between conflicting visual and auditory stimuli was diminished. Equivalent sensory thalamocortical manipulations showed that behaviour was causally dependent on PFC interactions with the sensory thalamus, not sensory cortex. Consistent with this notion, we found neurons of the visual thalamic reticular nucleus (visTRN) to exhibit PFC-dependent changes in firing rate predictive of the modality selected. visTRN activity was causal to performance as confirmed by bidirectional optogenetic manipulations of this subnetwork. Using a combination of electrophysiology and intracellular chloride photometry, we demonstrated that visTRN dynamically controls visual thalamic gain through feedforward inhibition. Our experiments introduce a new subcortical model of sensory selection, in which the PFC biases thalamic reticular subnetworks to control thalamic sensory gain, selecting appropriate inputs for further processing.

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We thank J. A. Movshon, W. Ma, R. W. Tsien, G. Fishell and D. Rinberg for helpful comments on the manuscript and G. J. Augustine for providing us with the SuperClomeleon construct and for helpful discussion around its use. The work was supported by the Swiss National Science Foundation (P2LAP3 151786) to R.D.W. and the Simons Foundation, the Sloan Foundation, the Brain and Behavior Research Foundation and the US National Institutes of Health (R00 NS078115) to M.M.H; M.M.H. is additionally supported by the Feldstein Medical Foundation, a Klingenstein-Simons Fellowship and a Biobehavioral Research Award for Innovative New Scientists (BRAINS) R01 (R01 MH107680) from the National Institute of Mental Health.

Author information

Author notes

    • Ralf D. Wimmer
    •  & L. Ian Schmitt

    These authors contributed equally to this work.


  1. New York University Neuroscience Institute, Department of Neuroscience and Physiology, New York University Langone Medical Center, New York, New York 10016, USA

    • Ralf D. Wimmer
    • , L. Ian Schmitt
    • , Miho Nakajima
    •  & Michael M. Halassa
  2. Department of Bioengineering, Stanford University, Stanford, California 94305, USA

    • Thomas J. Davidson
    •  & Karl Deisseroth
  3. Cracking the Neural Code Program, Stanford University, Stanford, California 94305, USA

    • Karl Deisseroth
  4. Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, California 94305, USA

    • Karl Deisseroth
  5. Department of Psychiatry, New York University Langone Medical Center, New York, New York 10016, USA

    • Michael M. Halassa
  6. Center for Neural Science, New York University, New York, New York 10003, USA

    • Michael M. Halassa


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M.M.H. conceived and designed all aspects of the study. R.D.W. devised the training paradigm for the cross-modal task and L.I.S. performed all associated programming. R.D.W. collected electrophysiological data. T.J.D. provided fibre photometry training, advice and rig designs; L.I.S. extended the method to FRET-based photometry, built the rig and collected data. R.D.W. analysed behavioural data and L.I.S. analysed psychophysical, electrophysiological and photometry data. M.N. generated the retrograde lentiviruses in-house, performed SuperClomeleon cloning into an AAV backbone and acquired confocal images. K.D. provided support for fibre photometry training. M.M.H. supervised the experiment, directed the analysis and wrote the manuscript. All authors read the final version of the manuscript.

Competing interests

The authors declare no competing financial interests.

Corresponding author

Correspondence to Michael M. Halassa.

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  1. 1.

    Supplementary Information

    This file contains a Supplementary Discussion and additional references.


  1. 1.

    Example trials of cross-modal performance

    Three trials are shown; the first is ‘attend to vision’ (left selection) the second is ‘attend to audition’ (left selection), and the third is ‘attend to vision’ (right selection). All trials are shown in normal speed and in slow-motion. The video illustrates the mechanics of the task and the impact of context (cueing) on selection.

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