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2 Janelia Publications

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    12/31/17 | A topographic axis of transcriptional identity in thalamus.
    Phillips JW, Schulman A, Hara E, Liu C, Shields BC, Korff W, Lemire A, Dudman JT, Nelson SB, Hantman AW
    bioRxiv. 2017 Dec 31:241315. doi: 10.1101/241315

    A fundamental goal in neuroscience is to uncover common principles by which different modalities of information are processed. In the mammalian brain, thalamus acts as the essential hub for forebrain circuits handling inputs from sensory, motor, limbic, and cognitive pathways. Whether thalamus imposes common transformations on each of these modalities is unknown. Molecular characterization offers a principled approach to revealing the organization of thalamus. Using near-comprehensive and projection-specific transcriptomic sequencing, we found that almost all thalamic nuclei fit into one of three profiles. These profiles lie on a single axis of genetic variance which is aligned with the mediolateral spatial axis of thalamus. Genes defining this axis of variance include receptors and ion channels, providing a systematic diversification of input/output transformations across the topography of thalamus. Single cell transcriptional profiling revealed graded heterogeneity within individual thalamic nuclei, demonstrating that a spectrum of cell types and potentially diverse input/output transforms exist within a given thalamic nucleus. Together, our data argue for an archetypal organization of pathways serving diverse input modalities, and provides a comprehensive organizational scheme for thalamus.

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    12/22/17 | Emergence of reward expectation signals in identified dopamine neurons.
    Coddington LT, Dudman JT
    bioRxiv. 2017 Dec 22:. doi: 10.1101/238881

    Coherent control of purposive actions emerges from the coordination of multiple brain circuits during learning. Dissociable brain circuits and cell-types are thought to preferentially participate in distinct learning mechanisms. For example, the activity of midbrain dopamine (mDA) neurons is proposed to primarily, or even exclusively, reflect reward prediction error signals in well-trained animals. To study the specific contribution of individual circuits requires observing changes before tight functional coordination is achieved. However, little is known about the detailed timing of the emergence of reward-related representations in dopaminergic neurons. Here we recorded activity of identified dopaminergic neurons as naive mice learned a novel stimulus-reward association. We found that at early stages of learning mDA neuron activity reflected both external (sensory) and internal (action initiation) causes of reward expectation. The increasingly precise correlation of action initiation with sensory stimuli rather than an evaluation of outcomes governed mDA neuron activity. Thus, our data demonstrate that mDA neuron activity early in learning does not reflect errors, but is more akin to a Hebbian learning signal - providing new insight into a critical computation in a highly conserved, essential learning circuit.

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