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      A cerebellar-thalamocortical pathway drives behavioral context-dependent movement initiation

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          Abstract

          <p id="d2318198e290">Executing learned motor behaviors often requires the transformation of sensory cues into patterns of motor commands that generate appropriately timed actions. The cerebellum and thalamus are two key areas involved in shaping cortical output and movement, but the contribution of a cerebellar-thalamocortical pathway to voluntary movement initiation remains poorly understood. Here, we investigated how an auditory “go cue” transforms thalamocortical activity patterns and how these changes relate to movement initiation. Population responses in dentate/interpositus-recipient regions of motor thalamus reflect a time-locked increase in activity immediately prior to movement initiation that is temporally uncoupled from the go cue, indicative of a fixed-latency feedforward motor timing signal. Blocking cerebellar or motor thalamic output suppresses movement initiation, while stimulation triggers movements in a behavioral context-dependent manner. Our findings show how cerebellar output, via the thalamus, shapes cortical activity patterns necessary for learned context-dependent movement initiation. </p><div class="fig panel" id="undfig1"> <a class="named-anchor" id="undfig1"> <!-- named anchor --> </a> <div class="figure-container so-text-align-c"> <img alt="" class="figure" src="/document_file/702ef17a-cff9-4fd3-aa2e-cb901a5598d6/PubMedCentral/image/fx1"/> </div> <div class="panel-content"/> </div><p id="d2318198e300"> <div class="list"> <a class="named-anchor" id="ulist0010"> <!-- named anchor --> </a> <ul class="so-custom-list" style="list-style-type: none"> <li id="u0010"> <div class="so-custom-list-label so-ol">•</div> <div class="so-custom-list-content so-ol"> <p id="p0010">DN/IPN thalamocortical activity conveys a reliable feedforward motor timing signal</p> </div> </li> <li id="u0015"> <div class="so-custom-list-label so-ol">•</div> <div class="so-custom-list-content so-ol"> <p id="p0015">Silencing DN/IPN or recipient regions of thalamus blocks movement initiation</p> </div> </li> <li id="u0020"> <div class="so-custom-list-label so-ol">•</div> <div class="so-custom-list-content so-ol"> <p id="p0020">Photostimulation of the DN/IPN thalamocortical pathway triggers movement</p> </div> </li> <li id="u0025"> <div class="so-custom-list-label so-ol">•</div> <div class="so-custom-list-content so-ol"> <p id="p0025">Thalamocortical activation drives behavioral context-dependent movement initiation</p> </div> </li> </ul> </div> </p><p class="first" id="d2318198e323">Dacre et al. show the contribution of a cerebellar-thalamocortical pathway to movement initiation. Using gain- and loss-of-function manipulations they demonstrate that output from dentate/interpositus nuclei, via the thalamus, shapes cortical activity dynamics necessary for learned behavioral context-dependent movement initiation. </p>

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          Fiji is a distribution of the popular open-source software ImageJ focused on biological-image analysis. Fiji uses modern software engineering practices to combine powerful software libraries with a broad range of scripting languages to enable rapid prototyping of image-processing algorithms. Fiji facilitates the transformation of new algorithms into ImageJ plugins that can be shared with end users through an integrated update system. We propose Fiji as a platform for productive collaboration between computer science and biology research communities.
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            Ultra-sensitive fluorescent proteins for imaging neuronal activity

            Summary Fluorescent calcium sensors are widely used to image neural activity. Using structure-based mutagenesis and neuron-based screening, we developed a family of ultra-sensitive protein calcium sensors (GCaMP6) that outperformed other sensors in cultured neurons and in zebrafish, flies, and mice in vivo. In layer 2/3 pyramidal neurons of the mouse visual cortex, GCaMP6 reliably detected single action potentials in neuronal somata and orientation-tuned synaptic calcium transients in individual dendritic spines. The orientation tuning of structurally persistent spines was largely stable over timescales of weeks. Orientation tuning averaged across spine populations predicted the tuning of their parent cell. Although the somata of GABAergic neurons showed little orientation tuning, their dendrites included highly tuned dendritic segments (5 - 40 micrometers long). GCaMP6 sensors thus provide new windows into the organization and dynamics of neural circuits over multiple spatial and temporal scales.
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              DeepLabCut: markerless pose estimation of user-defined body parts with deep learning

              Quantifying behavior is crucial for many applications in neuroscience. Videography provides easy methods for the observation and recording of animal behavior in diverse settings, yet extracting particular aspects of a behavior for further analysis can be highly time consuming. In motor control studies, humans or other animals are often marked with reflective markers to assist with computer-based tracking, but markers are intrusive, and the number and location of the markers must be determined a priori. Here we present an efficient method for markerless pose estimation based on transfer learning with deep neural networks that achieves excellent results with minimal training data. We demonstrate the versatility of this framework by tracking various body parts in multiple species across a broad collection of behaviors. Remarkably, even when only a small number of frames are labeled (~200), the algorithm achieves excellent tracking performance on test frames that is comparable to human accuracy.
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                Author and article information

                Journal
                Neuron
                Neuron
                Elsevier BV
                08966273
                June 2021
                June 2021
                Article
                10.1016/j.neuron.2021.05.016
                5511ed51-2cd4-4810-8ae2-50eab14096f0
                © 2021

                https://www.elsevier.com/tdm/userlicense/1.0/

                http://creativecommons.org/licenses/by/4.0/

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