2017-08 system neurosci

papers in Aug

Abrol, A., Damaraju, E., Miller, R. L., Stephen, J. M., Claus, E. D., Mayer, A. R., & Calhoun, V. D. (2017). Replicability of time-varying connectivity patterns in large resting state fMRI samples. bioRxiv, 172866. http://doi.org/10.1101/172866

Adams, D. L., Economides, J. R., & Horton, J. C. (2017). Incomitance and Eye Dominance in Intermittent ExotropiaIncomitance in Exotropia. Investigative Ophthalmology & Visual Science, 58(10), 4049–4055. http://doi.org/10.1167/iovs.17-22155

  • Agetsuma, M., Hamm, J. P., Tao, K., Fujisawa, S., & Yuste, R. (2017). Parvalbumin-Positive Interneurons Regulate Neuronal Ensembles in Visual Cortex. Cerebral Cortex (New York, N.Y. : 1991), 1–15. http://doi.org/10.1093/cercor/bhx169

  • Aghayee, S., Winkowski, D. E., Bowen, Z., Marshall, E. E., Harrington, M. J., Kanold, P. O., & Losert, W. (2017). Particle Tracking Facilitates Real Time Capable Motion Correction in 2D or 3D Two-Photon Imaging of Neuronal Activity. Frontiers in Neural Circuits, 11, 295. http://doi.org/10.3389/fncir.2017.00056

  • Akbarinia, A., & Parraga, C. A. (2017). Feedback and Surround Modulated Boundary Detection. International Journal of Computer Vision, 33(5), 1–14. http://doi.org/10.1007/s11263-017-1035-5

Albright, T. D. (2017). Why eyewitnesses fail. Proceedings of the National Academy of Sciences, 114(30), 7758–7764. http://doi.org/10.1073/pnas.1706891114

  • Andersen, N., Krauth, N., & Nabavi, S. (2017). Hebbian plasticity in vivo : relevance and induction. Current Opinion in Neurobiology, 45, 188–192. http://doi.org/10.1016/j.conb.2017.06.001

  • Angelucci, A., Bijanzadeh, M., Nurminen, L., Federer, F., Merlin, S., & Bressloff, P. C. (2017). Circuits and Mechanisms for Surround Modulation in Visual Cortex. Annual Review of Neuroscience, 40(1), 425–451. http://doi.org/10.1146/annurev-neuro-072116-031418

Arcaro, M. J., & Livingstone, M. S. (2017a). A hierarchical, retinotopic proto-organization of the primate visual system at birth. eLife, 6, e26196. http://doi.org/10.7554/eLife.26196

** Arcaro, M. J., & Livingstone, M. S. (2017b). Retinotopic Organization of Scene Areas in Macaque Inferior Temporal Cortex. The Journal of Neuroscience : the Official Journal of the Society for Neuroscience, 37(31), 7373–7389. http://doi.org/10.1523/JNEUROSCI.0569-17.2017

Arriaga, M., & Han, E. B. (2017). Dedicated hippocampal inhibitory networks for locomotion and immobility. – PubMed – NCBI. Journal of Neuroscience, 1076–17. http://doi.org/10.1523/JNEUROSCI.1076-17.2017

Avitan, L., Pujic, Z., Mölter, J., Van De Poll, M., Sun, B., Teng, H., et al. (2017). Spontaneous Activity in the Zebrafish Tectum Reorganizes over Development and Is Influenced by Visual Experience. Current Biology, 0(0). http://doi.org/10.1016/j.cub.2017.06.056

Barak, O. (2017). Recurrent neural networks as versatile tools of neuroscience research. Current Opinion in Neurobiology, 46, 1–6. http://doi.org/10.1016/j.conb.2017.06.003

Barker, A. J., Helmbrecht, T. O., Grob, A. A., & Baier, H. (2017). Detection of whole-field luminance changes by superficial interneurons in the zebrafish tectum. bioRxiv, 178970. http://doi.org/10.1101/178970

  • Benichoux, V., Brown, A. D., Anbuhl, K. L., & Tollin, D. J. (2017). Representation of Multidimensional Stimuli: Quantifying the Most Informative Stimulus Dimension from Neural Responses. Journal of Neuroscience, 37(31), 7332–7346. http://doi.org/10.1523/JNEUROSCI.0318-17.2017

  • Bijanzadeh, M., Nurminen, L., Merlin, S., & Angelucci, A. (2017). Distinct Laminar Processing of Local and Global Context in Primate Primary Visual Cortex. bioRxiv, 171793. http://doi.org/10.1101/171793

  • Bloodgood, D. W., Sugam, J. A., Holmes, A., & Kash, T. L. (2017). Fear extinction requires infralimbic cortex projections to the basolateral amygdala. bioRxiv, 172791.

Bone, A., & Houck, K. (2017). Adverse Drug Reactions: The benefits of data mining. eLife, 6, e30280. http://doi.org/10.7554/eLife.30280

Bonner, M. F., & Epstein, R. A. (2017). Computational mechanisms underlying cortical responses to the affordance properties of visual scenes. bioRxiv, 177329. http://doi.org/10.1101/177329

  • Braem, S., De Houwer, J., Demanet, J., Yuen, K. S. L., Kalisch, R., & Brass, M. (2017). Pattern Analyses Reveal Separate Experience-Based Fear Memories in the Human Right Amygdala. Journal of Neuroscience, 37(34), 8116–8130. http://doi.org/10.1523/JNEUROSCI.0908-17.2017

Braun, A., Urai, A. E., & Donner, T. H. (2017). Confidence-dependent accumulation of past decision variables biases perceptual choice. bioRxiv, 172049. http://doi.org/10.1101/172049

Bray, N. (2017). Motor systems: Mice get manual. Nature Reviews. Neuroscience, 18(9), 512–512. http://doi.org/10.1038/nrn.2017.108

  • Bullock, K. R., Pieper, F., Sachs, A. J., & Martinez-Trujillo, J. C. (2017). Visual and presaccadic activity in area 8Ar of the macaque monkey lateral prefrontal cortex. Journal of Neurophysiology, 118(1), 15–28. http://doi.org/10.1152/jn.00278.2016

  • Chaffiol, A., Ishii, M., Cao, Y., & Mangel, S. C. (2017). Dopamine Regulation of GABAA Receptors Contributes to Light/Dark Modulation of the ON-Cone Bipolar Cell Receptive Field Surround in the Retina. Current Biology, 0(0). http://doi.org/10.1016/j.cub.2017.07.063

    ** Chamberland, S., Yang, H. H., Pan, M. M., Evans, S. W., Guan, S., Chavarha, M., et al. (2017). Fast two-photon imaging of subcellular voltage dynamics in neuronal tissue with genetically encoded indicators. eLife, 6, e25690. http://doi.org/10.7554/eLife.25690

  • Chan, K. Y., Jang, M. J., Yoo, B. B., Greenbaum, A., Ravi, N., Wu, W.-L., et al. (2017). Engineered AAVs for efficient noninvasive gene delivery to the central and peripheral nervous systems. Nature Neuroscience, 20(8), 1172–1179. http://doi.org/10.1038/nn.4593

  • Chen, C.-Y., Sonnenberg, L., Weller, S., Witschel, T., & Hafed, Z. M. (2017). Spatial vision by macaque midbrain. bioRxiv, 171645. http://doi.org/10.1101/171645

  • Clarke, L. E., & Liddelow, S. A. (2017). Neurobiology: Diversity reaches the stars. Nature, 548(7668), 396–397. http://doi.org/10.1038/548396a

  • Cohen, J. D., Bolstad, M., & Lee, A. K. (2017). Experience-dependent shaping of hippocampal CA1 intracellular activity in novel and familiar environments. eLife, 6, e23040. http://doi.org/10.7554/eLife.23040

Contreras, E. J. B., Chekhov, S., Tarnowsky, J., Sun, J., McNaughton, B. L., & Mohajerani, M. H. (2017). A high-performance, inexpensive setup for simultaneous multi-site recording of electrophysiological signals and wide-field optical imaging of the mouse cortex. bioRxiv, 177188. http://doi.org/10.1101/177188

  • Cortese, A., Amano, K., Koizumi, A., Lau, H., & Kawato, M. (2017). Decoded fMRI neurofeedback can induce bidirectional confidence changes within single participants. NeuroImage, 149, 323–337. http://doi.org/10.1016/j.neuroimage.2017.01.069

  • Cuthill, I. C., Allen, W. L., Arbuckle, K., Caspers, B., Chaplin, G., Hauber, M. E., et al. (2017). The biology of color. Science (New York, N.Y.), 357(6350), eaan0221. http://doi.org/10.1126/science.aan0221

  • Danielson, N. B., Turi, G. F., Ladow, M., Chavlis, S., Petrantonakis, P. C., Poirazi, P., & Losonczy, A. (2017). In Vivo Imaging of Dentate Gyrus Mossy Cells in Behaving Mice. Neuron, 93(3), 552–559.e4. http://doi.org/10.1016/j.neuron.2016.12.019

    ** David, S. V. (2017). Cognition: Neurons couple up to make decisions. Nature. http://doi.org/10.1038/nature23100

Del Vechio Koike, B., Farias, K. S., Billwiller, F., Almeida-Filho, D., Libourel, P.-A., Tiran-Cappello, A., et al. (2017). Electrophysiological Evidence That the Retrosplenial Cortex Displays a Strong and Specific Activation Phased with Hippocampal Theta during Paradoxical (REM) Sleep. Journal of Neuroscience, 37(33), 8003–8013. http://doi.org/10.1523/JNEUROSCI.0026-17.2017

  • Dillon, M. R., Persichetti, A. S., Spelke, E. S., & Dilks, D. D. (2017). Places in the Brain: Bridging Layout and Object Geometry in Scene-Selective Cortex. – PubMed – NCBI. Cerebral Cortex, 1–10. http://doi.org/10.1093/cercor/bhx139

Driscoll, L. N., Pettit, N. L., Minderer, M., Chettih, S. N., & Harvey, C. D. (2017). Dynamic Reorganization of Neuronal Activity Patterns in Parietal Cortex. – PubMed – NCBI. Cell. http://doi.org/10.1016/j.cell.2017.07.021

Edwards, G., Vetter, P., McGruer, F., Petro, L. S., & Muckli, L. (2017). Predictive feedback to V1 dynamically updates with sensory input. bioRxiv, 180539. http://doi.org/10.1101/180539

Elsayed, G. F., & Cunningham, J. P. (2017). Structure in neural population recordings: an expected byproduct of simpler phenomena? Nature Neuroscience, 20(9), 1310–1318. http://doi.org/10.1038/nn.4617

Ester, E. F., Sprague, T. C., & Serences, J. T. (2017). Category learning biases sensory representations in visual cortex. bioRxiv, 170845. http://doi.org/10.1101/170845

Fernandez-Leon, J. A., Hansen, B. J., & Dragoi, V. (2017a). Representation of Rapid Image Sequences in V4 Networks. Cerebral Cortex (New York, N.Y. : 1991), 1–10. http://doi.org/10.1093/cercor/bhx146

Förster, D., Dal Maschio, M., Laurell, E., & Baier, H. (2017). An optogenetic toolbox for unbiased discovery of functionally connected cells in neural circuits. – PubMed – NCBI. Nature Communications, 8(1), 81. http://doi.org/10.1038/s41467-017-00160-z

Friedrich, J., Yang, W., Soudry, D., Mu, Y., Ahrens, M. B., Yuste, R., et al. (2017). Multi-scale approaches for high-speed imaging and analysis of large neural populations. PLoS Computational Biology, 13(8), e1005685. http://doi.org/10.1371/journal.pcbi.1005685

Gallego, J. A., Perich, M. G., Naufel, S. N., Ethier, C., Solla, S. A., & Miller, L. E. (2017). Multiple tasks viewed from the neural manifold: Stable control of varied behavior. bioRxiv, 176081. http://doi.org/10.1101/176081

** Goddard, E., Solomon, S. G., & Carlson, T. A. (2017). Dynamic population codes of multiplexed stimulus features in primate area MT. Journal of Neurophysiology, 118(1), 203–218. http://doi.org/10.1152/jn.00954.2016

  • Goldman, M. S., & Fee, M. S. (2017). Computational training for the next generation of neuroscientists. Current Opinion in Neurobiology, 46, 25–30. http://doi.org/10.1016/j.conb.2017.06.007

Gomez, J. L., Bonaventura, J., Lesniak, W., Mathews, W. B., Sysa-Shah, P., Rodriguez, L. A., et al. (2017). Chemogenetics revealed: DREADD occupancy and activation via converted clozapine. Science (New York, N.Y.), 357(6350), 503–507. http://doi.org/10.1126/science.aan2475

Gordon, E. M., Laumann, T. O., Gilmore, A. W., Newbold, D. J., Greene, D. J., Berg, J. J., et al. (2017). Precision Functional Mapping of Individual Human Brains. Neuron, 0(0), 249–258. http://doi.org/10.1016/j.neuron.2017.07.011

Green, A. A., Kim, J., Ma, D., Silver, P. A., Collins, J. J., & Yin, P. (2017). Complex cellular logic computation using ribocomputing devices. Nature, 12(7665), 381–121. http://doi.org/10.1038/nature23271

Grilli, J., Barabás, G., Michalska-Smith, M. J., & Allesina, S. (2017). Higher-order interactions stabilize dynamics in competitive network models. Nature, 75, 1527. http://doi.org/10.1038/nature23273

Gulbinaite, R., İlhan, B., & VanRullen, R. (2017). The Triple-Flash Illusion Reveals a Driving Role of Alpha-Band Reverberations in Visual Perception. Journal of Neuroscience, 37(30), 7219–7230. http://doi.org/10.1523/JNEUROSCI.3929-16.2017

Gutnisky, D. A., Yu, J., Hires, S. A., To, M.-S., Bale, M. R., Svoboda, K., & Golomb, D. (2017). Mechanisms underlying a thalamocortical transformation during active tactile sensation. PLoS Computational Biology, 13(6), e1005576. http://doi.org/10.1371/journal.pcbi.1005576

  • Hallum, L. E., Shooner, C., Kumbhani, R. D., Kelly, J. G., García-Marín, V., Majaj, N. J., et al. (2017). Altered Balance of Receptive Field Excitation and Suppression in Visual Cortex of Amblyopic Macaque Monkeys. Journal of Neuroscience, 37(34), 8216–8226. http://doi.org/10.1523/JNEUROSCI.0449-17.2017

Hashimotodani, Y., Nasrallah, K., Jensen, K. R., Chávez, A. E., Carrera, D., & Castillo, P. E. (2017). LTP at Hilar Mossy Cell-Dentate Granule Cell Synapses Modulates Dentate Gyrus Output by Increasing Excitation/Inhibition Balance. Neuron, 95(4), 928–943.e3. http://doi.org/10.1016/j.neuron.2017.07.028

*** Hasse, J. M., & Briggs, F. (2017). Corticogeniculate feedback sharpens the temporal precision and spatial resolution of visual signals in the ferret. Proceedings of the National Academy of Sciences of the United States of America, 114(30), E6222–E6230. http://doi.org/10.1073/pnas.1704524114

Helfrich, R. F., Huang, M., Wilson, G., & Knight, R. T. (2017). Prefrontal cortex modulates posterior alpha oscillations during top-down guided visual perception. Proceedings of the National Academy of Sciences of the United States of America, 114(35), 9457–9462. http://doi.org/10.1073/pnas.1705965114

Huang, C., & Doiron, B. (2017). Once upon a (slow) time in the land of recurrent neuronal networks…. Current Opinion in Neurobiology, 46, 31–38. http://doi.org/10.1016/j.conb.2017.07.003

** Huk, A. C., Katz, L. N., & Yates, J. L. (2017). The Role of the Lateral Intraparietal Area in (the Study of) Decision Making. Doi.org, 40(1), 349–372. http://doi.org/10.1146/annurev-neuro-072116-031508

Hyman, J. M., Holroyd, C. B., & Seamans, J. K. (2017). A Novel Neural Prediction Error Found in Anterior Cingulate Cortex Ensembles. Neuron, 0(0). http://doi.org/10.1016/j.neuron.2017.06.021

Iacaruso, M. F., Gasler, I. T., & Hofer, S. B. (2017). Synaptic organization of visual space in primary visual cortex. Nature, 547(7664), 449–452. http://doi.org/10.1038/nature23019

Inada, K., Tsuchimoto, Y., & Kazama, H. (2017). Origins of Cell-Type-Specific Olfactory Processing in the Drosophila Mushroom Body Circuit. Neuron, 95(2), 357–367.e4. http://doi.org/10.1016/j.neuron.2017.06.039

  • Is population activity more than the sum of its parts? (2017b). Is population activity more than the sum of its parts?, 20(9), 1196–1198. http://doi.org/10.1038/nn.4627

Ismakov, R., Barak, O., Jeffery, K., & Derdikman, D. (2017). Grid Cells Encode Local Positional Information. Current Biology, 0(0). http://doi.org/10.1016/j.cub.2017.06.034

  • Ito, S., Feldheim, D. A., & Litke, A. M. (2017). Segregation of Visual Response Properties in the Mouse Superior Colliculus and Their Modulation during Locomotion. Journal of Neuroscience, 37(35), 8428–8443. http://doi.org/10.1523/JNEUROSCI.3689-16.2017

  • Jenks, K. R., Kim, T., Pastuzyn, E. D., Okuno, H., Taibi, A. V., Bito, H., et al. (2017). Arc restores juvenile plasticity in adult mouse visual cortex. Proceedings of the National Academy of Sciences of the United States of America, 114(34), 9182–9187. http://doi.org/10.1073/pnas.1700866114

Jercog, D., Roxin, A., Barthó, P., Luczak, A., Compte, A., & la Rocha, de, J. (2017). UP-DOWN cortical dynamics reflect state transitions in a bistable network. eLife, 6, e22425. http://doi.org/10.7554/eLife.22425

Jorstad, N. L., Wilken, M. S., Grimes, W. N., Wohl, S. G., VandenBosch, L. S., Yoshimatsu, T., et al. (2017). Stimulation of functional neuronal regeneration from Müller glia in adult mice. Nature. http://doi.org/10.1038/nature23283

Kaiser, D., Moeskops, M. M., & Cichy, R. M. (2017). Typical real-world locations impact the time course of object coding. bioRxiv, 177493. http://doi.org/10.1101/177493

Kato, H. K., Asinof, S. K., & Isaacson, J. S. (2017). Network-Level Control of Frequency Tuning in Auditory Cortex. Neuron, 1–17. http://doi.org/10.1016/j.neuron.2017.06.019

** Kim, H. R., Angelaki, D. E., & DeAngelis, G. C. (2017). Gain Modulation as a Mechanism for Coding Depth from Motion Parallax in Macaque Area MT. Journal of Neuroscience, 37(34), 8180–8197. http://doi.org/10.1523/JNEUROSCI.0393-17.2017

  • Kim, W. B., & Cho, J.-H. (2017). Encoding of Discriminative Fear Memory by Input-Specific LTP in the Amygdala. Neuron. http://doi.org/10.1016/j.neuron.2017.08.004

Kirschen, G. W., Shen, J., Tian, M., Schroeder, B., Wang, J., Man, G., et al. (2017). Active Dentate Granule Cells Encode Experience to Promote the Addition of Adult-Born Hippocampal Neurons. – PubMed – NCBI. Journal of Neuroscience, 37(18), 4661–4678. http://doi.org/10.1523/JNEUROSCI.3417-16.2017

Knudsen, E. I., Schwarz, J. S., Knudsen, P. F., & Sridharan, D. (2017). Space-Specific Deficits in Visual Orientation Discrimination Caused by Lesions in the Midbrain Stimulus Selection Network. Current Biology, 0(0). http://doi.org/10.1016/j.cub.2017.06.011

Kuramoto, E., Iwai, H., Yamanaka, A., Ohno, S., Seki, H., Tanaka, Y. R., et al. (2017). Dorsal and Ventral Parts of Thalamic Nucleus Submedius Project to Different Areas of Rat Orbitofrontal Cortex: A Single Neuron‐Tracing Study Using Virus Vectors. Journal of Comparative Neurology. http://doi.org/10.1002/cne.12646

Kwon, S. E., Tsytsarev, V., Erzurumlu, R. S., & O’Connor, D. H. (2017a). Organization of orientation-specific whisker deflection responses in layer 2/3 of mouse somatosensory cortex. Neuroscience. http://doi.org/10.1016/j.neuroscience.2017.07.067

Kwon, T., Sakamoto, M., Peterka, D. S., & Yuste, R. (2017b). Attenuation of Synaptic Potentials in Dendritic Spines. CellReports, 20(5), 1100–1110. http://doi.org/10.1016/j.celrep.2017.07.012

La Camera, G., Bouret, S., & Richmond, B. J. (2017). Contributions of different prefrontal cortical regions to abstract rule acquisition and reversal in monkeys. bioRxiv, 180893. http://doi.org/10.1101/180893

Ledoux, L.-P., Morency, F. C., Cousineau, M., Houde, J.-C., Whittingstall, K., & Descoteaux, M. (2017). Fiberweb: Diffusion Visualization and Processing in the Browser. Frontiers in Neuroinformatics, 11, 816. http://doi.org/10.3389/fninf.2017.00054

  • Leszczynski, M., Fell, J., Jensen, O., & Axmacher, N. (2017). Alpha activity in the ventral and dorsal visual stream controls information flow during working memory. bioRxiv, 180166. http://doi.org/10.1101/180166

Li, X., Cao, V. Y., Zhang, W., Mastwal, S. S., Liu, Q., Otte, S., & Wang, K. H. (2017a). Skin suturing and cortical surface viral infusion improves imaging of neuronal ensemble activity with head-mounted miniature microscopes. Journal of Neuroscience Methods. http://doi.org/10.1016/j.jneumeth.2017.08.016

Li, Y., Gong, H., Yang, X., Yuan, J., Jiang, T., Li, X., et al. (2017b). TDat: An Efficient Platform for Processing Petabyte-Scale Whole-Brain Volumetric Images. Frontiers in Neural Circuits, 11, 2033. http://doi.org/10.3389/fncir.2017.00051

Liu, J. K., Schreyer, H. M., Onken, A., Rozenblit, F., Khani, M. H., Krishnamoorthy, V., et al. (2017a). Inference of neuronal functional circuitry with spike-triggered non-negative matrix factorization. Nature Communications, 8(1), 149. http://doi.org/10.1038/s41467-017-00156-9

Liu, K., Kim, J., Kim, D. W., Zhang, Y. S., Bao, H., Denaxa, M., et al. (2017b). Lhx6-positive GABA-releasing neurons of the zona incerta promote sleep. Nature, 538, 51. http://doi.org/10.1038/nature23663

Livneh, Y., Ramesh, R. N., Burgess, C. R., Levandowski, K. M., Madara, J. C., Fenselau, H., et al. (2017). Homeostatic circuits selectively gate food cue responses in insular cortex. Nature, 546(7660), 611–616. http://doi.org/10.1038/nature22375

Lowet, E., Roberts, M. J., Peter, A., Gips, B., & De Weerd, P. (2017). A quantitative theory of gamma synchronization in macaque V1. eLife, 6, e26642. http://doi.org/10.7554/eLife.26642

** Majaj, N. J., & Pelli, D. G. (2017). Deep learning: Using machine learning to study biological vision. bioRxiv, 178152. http://doi.org/10.1101/178152

  • Majima, K., Sukhanov, P., Horikawa, T., & Kamitani, Y. (2017). Position Information Encoded by Population Activity in Hierarchical Visual Areas. Eneuro, 4(2), ENEURO.0268–16.2017. http://doi.org/10.1523/ENEURO.0268-16.2017

  • Manita, S., Miyakawa, H., Kitamura, K., & Murayama, M. (2017). Dendritic Spikes in Sensory Perception. Frontiers in Cellular Neuroscience, 11, 26. http://doi.org/10.3389/fncel.2017.00029

Mann, K., Gallen, C. L., & Clandinin, T. R. (2017). Whole-Brain Calcium Imaging Reveals an Intrinsic Functional Network in Drosophila. Current Biology, 0(0), 2389–2396.e4. http://doi.org/10.1016/j.cub.2017.06.076

Meyer, R., Ladenbauer, J., & Obermayer, K. (2017). The Influence of Mexican Hat Recurrent Connectivity on Noise Correlations and Stimulus Encoding. Frontiers in Computational Neuroscience, 11, 2072. http://doi.org/10.3389/fncom.2017.00034

  • Minami, S., & Amano, K. (2017). Illusory Jitter Perceived at the Frequency of Alpha Oscillations. Current Biology, 0(0), 2344–2351.e4. http://doi.org/10.1016/j.cub.2017.06.033

Mokri, Y., Salazar, R. F., Goodell, B., Baker, J., Gray, C. M., & Yen, S.-C. (2017). Sorting Overlapping Spike Waveforms from Electrode and Tetrode Recordings. Frontiers in Neuroinformatics, 11, 129. http://doi.org/10.3389/fninf.2017.00053

Murty, N. A. R., & Arun, S. R. (2017). Effect of silhouetting and inversion on view invariance in the monkey inferotemporal cortex. Journal of Neurophysiology, 118(1), 353–362. http://doi.org/10.1152/jn.00008.2017

  • Navratil, O., Duris, K., Juran, V., Neuman, E., Svoboda, K., & Smrcka, M. (2017). Middle cerebral artery aneurysms with intracerebral hematoma-the impact of side and volume on final outcome. Acta Neurochirurgica, 159(3), 543–547. http://doi.org/10.1007/s00701-016-3070-3

    *** Nöbauer, T., Skocek, O., Pernía-Andrade, A. J., Weilguny, L., Traub, F. M., Molodtsov, M. I., & Vaziri, A. (2017). Video rate volumetric Ca(2+) imaging across cortex using seeded iterative demixing (SID) microscopy. Nature Methods, 14(8), 811–818. http://doi.org/10.1038/nmeth.4341

Ohshiro, T., Angelaki, D. E., & DeAngelis, G. C. (2017). A Neural Signature of Divisive Normalization at the Level of Multisensory Integration in Primate Cortex. Neuron, 95(2), 399–411.e8. http://doi.org/10.1016/j.neuron.2017.06.043

Orsborn, A. L., & Pesaran, B. (2017). Parsing learning in networks using brain–machine interfaces. Current Opinion in Neurobiology, 46, 76–83. http://doi.org/10.1016/j.conb.2017.08.002

Orsini, C. A., Hernandez, C. M., Singhal, S., Kelly, K. B., Frazier, C. J., Bizon, J. L., & Setlow, B. (2017). Optogenetic inhibition reveals distinct roles for basolateral amygdala activity at discrete timepoints during risky decision making. bioRxiv, 180885. http://doi.org/10.1101/180885

Peters, A. J., Lee, J., Hedrick, N. G., O’Neil, K., & Komiyama, T. (2017a). Reorganization of corticospinal output during motor learning. Nature Neuroscience, 57, 329. http://doi.org/10.1038/nn.4596

  • Peters, A. J., Liu, H., & Komiyama, T. (2017b). Learning in the Rodent Motor Cortex. Annual Review of Neuroscience, 40(1), 77–97. http://doi.org/10.1146/annurev-neuro-072116-031407

  • Ponce, C. R., Lomber, S. G., & Livingstone, M. S. (2017). Posterior Inferotemporal Cortex Cells Use Multiple Input Pathways for Shape Encoding. The Journal of Neuroscience : the Official Journal of the Society for Neuroscience, 37(19), 5019–5034. http://doi.org/10.1523/JNEUROSCI.2674-16.2017

Qiu, L. R., Fernandes, D. J., Szulc, K. U., Dazai, J., Nieman, B. J., Turnbull, D. H., et al. (2017). Mouse MRI shows brain areas larger in males emerge earlier than those larger in females. bioRxiv, 172841. http://doi.org/10.1101/172841

  • Ramachandran, S., Meyer, T., & Olson, C. R. (2017). Prediction suppression and surprise enhancement in monkey inferotemporal cortex. Journal of Neurophysiology, 118(1), 374–382. http://doi.org/10.1152/jn.00136.2017

Reimann, M. W., Horlemann, A.-L., Ramaswamy, S., Muller, E. B., & Markram, H. (2017). Morphological Diversity Strongly Constrains Synaptic Connectivity and Plasticity. – PubMed – NCBI. Cerebral Cortex, 1–16. http://doi.org/10.1093/cercor/bhx150

Rennó-Costa, C., & Tort, A. B. L. (2017). Place and Grid Cells in a Loop: Implications for Memory Function and Spatial Coding. Journal of Neuroscience, 37(34), 8062–8076. http://doi.org/10.1523/JNEUROSCI.3490-16.2017

Rens, G. (2017). Advantages of Using the Dorsolateral versus the Dorsomedial Visual Stream for Decoding Hand Movements. Journal of Neuroscience, 37(35), 8312–8314. http://doi.org/10.1523/JNEUROSCI.1461-17.2017

Robinson, A. K., Venkatesh, P., Boring, M. J., Tarr, M. J., Grover, P., & Behrmann, M. (2017). Very high density EEG elucidates spatiotemporal aspects of early visual processing. bioRxiv, 172353. http://doi.org/10.1101/172353

  • Rose, T., & Hübener, M. (2017). Neurobiology: Synapses get together for vision. Nature, 547(7664), 408–410. http://doi.org/10.1038/nature23098

Roseboom, W., Fountas, Z., Nikiforou, K., Bhowmik, D., Shanahan, M., & Seth, A. K. (2017). A functioning model of human time perception. bioRxiv, 172387. http://doi.org/10.1101/172387

  • Runyan, C. A., Piasini, E., Panzeri, S., & Harvey, C. D. (2017). Distinct timescales of population coding across cortex. Nature, 86, 1916. http://doi.org/10.1038/nature23020

Saal, H. P., Delhaye, B. P., Rayhaun, B. C., & Bensmaia, S. J. (2017). Simulating tactile signals from the whole hand with millisecond precision. Proceedings of the National Academy of Sciences of the United States of America, 114(28), E5693–E5702. http://doi.org/10.1073/pnas.1704856114

Sabharwal, J., Seilheimer, R. L., Tao, X., Cowan, C. S., Frankfort, B. J., & Wu, S. M. (2017). Elevated IOP alters the space-time profiles in the center and surround of both ON and OFF RGCs in mouse. Proceedings of the National Academy of Sciences of the United States of America, 114(33), 8859–8864. http://doi.org/10.1073/pnas.1706994114

  • Sani, I., Santandrea, E., Morrone, M. C., & Chelazzi, L. (2017). Temporally evolving gain mechanisms of attention in macaque area V4. Journal of Neurophysiology, 118(2), 964–985. http://doi.org/10.1152/jn.00522.2016

Schmidt-Hieber, C., Toleikyte, G., Aitchison, L., Roth, A., Clark, B. A., Branco, T., & Häusser, M. (2017). Active dendritic integration as a mechanism for robust and precise grid cell firing. Nature Neuroscience, 20(8), 1114–1121. http://doi.org/10.1038/nn.4582

** Scholl, B., Pattadkal, J. J., & Priebe, N. J. (2017). Binocular Disparity Selectivity Weakened after Monocular Deprivation in Mouse V1. The Journal of Neuroscience : the Official Journal of the Society for Neuroscience, 37(27), 6517–6526. http://doi.org/10.1523/JNEUROSCI.1193-16.2017

Scott, B. B., Constantinople, C. M., Akrami, A., Hanks, T. D., Brody, C. D., & Tank, D. W. (2017). Fronto-parietal Cortical Circuits Encode Accumulated Evidence with a Diversity of Timescales. Neuron, 0(0). http://doi.org/10.1016/j.neuron.2017.06.013

Shi, J., Wen, H., Zhang, Y., Han, K., & Liu, Z. (2017). Deep Recurrent Neural Network Reveals a Hierarchy of Process Memory during Dynamic Natural Vision. bioRxiv, 177196. http://doi.org/10.1101/177196

Shilatifard, A. (2017). Cas9 endonuclease and off-target activity. Science (New York, N.Y.), 357(6350), 467–469. http://doi.org/10.1126/science.357.6350.467-q

*** Shiozaki, H. M., & Kazama, H. (2017). Parallel encoding of recent visual experience and self-motion during navigation in Drosophila. Nature Neuroscience, 503, 262. http://doi.org/10.1038/nn.4628

Stern, P. (2017a). DREADD not the designer compound. Science (New York, N.Y.), 357(6350), 467–469. http://doi.org/10.1126/science.357.6350.467-l

Stern, P. (2017b). The disappearance of fine motor control. Science (New York, N.Y.), 357(6349), 366–367. http://doi.org/10.1126/science.357.6349.366-f

*** Stokes, P. A., & Purdon, P. L. (2017). A study of problems encountered in Granger causality analysis from a neuroscience perspective. Proceedings of the National Academy of Sciences of the United States of America, 369, 201704663. http://doi.org/10.1073/pnas.1704663114

Sumser, A., Mease, R. A., Sakmann, B., & Groh, A. (2017). Organization and somatotopy of corticothalamic projections from L5B in mouse barrel cortex. Proceedings of the National Academy of Sciences of the United States of America, 114(33), 8853–8858. http://doi.org/10.1073/pnas.1704302114

Sun, Y., Nern, A., Franconville, R., Dana, H., Schreiter, E. R., Looger, L. L., et al. (2017). Neural signatures of dynamic stimulus selection in Drosophila. Nature Publishing Group, 20(8), 1104–1113. http://doi.org/10.1038/nn.4581

** Tajima, S., Koida, K., Tajima, C. I., Suzuki, H., Aihara, K., & Komatsu, H. (2017). Task-dependent recurrent dynamics in visual cortex. eLife, 6. http://doi.org/10.7554/eLife.26868

** Tamura, K., Takeda, M., Setsuie, R., Tsubota, T., Hirabayashi, T., Miyamoto, K., & Miyashita, Y. (2017). Conversion of object identity to object-general semantic value in the primate temporal cortex. Science (New York, N.Y.), 357(6352), 687–692. http://doi.org/10.1126/science.aan4800

** Tootell, R. B. H., & Nasr, S. (2017). Columnar Segregation of Magnocellular and Parvocellular Streams in Human Extrastriate Cortex. Journal of Neuroscience, 37(33), 8014–8032. http://doi.org/10.1523/JNEUROSCI.0690-17.2017

Totty, M. S., Chesney, L. A., Geist, P. A., & Datta, S. (2017). Sleep-Dependent Oscillatory Synchronization: A Role in Fear Memory Consolidation. Frontiers in Neural Circuits, 11, 572. http://doi.org/10.3389/fncir.2017.00049

  • Tsytsarev, V., Arakawa, H., Zhao, S., Chédotal, A., & Erzurumlu, R. S. (2017). Behavioral Consequences of a Bifacial Map in the Mouse Somatosensory Cortex. Journal of Neuroscience, 37(30), 7209–7218. http://doi.org/10.1523/JNEUROSCI.0598-17.2017

  • Vanni, M. P., Chan, A. W., Balbi, M., Silasi, G., & Murphy, T. H. (2017a). Mesoscale Mapping of Mouse Cortex Reveals Frequency-Dependent Cycling between Distinct Macroscale Functional Modules. Journal of Neuroscience, 37(31), 7513–7533. http://doi.org/10.1523/JNEUROSCI.3560-16.2017

  • Voigt, F. F., Emaury, F., Bethge, P., Waldburger, D., Link, S. M., Carta, S., et al. (2017). Multiphoton in vivo imaging with a femtosecond semiconductor disk laser. Biomedical Optics Express, 8(7), 3213–3231. http://doi.org/10.1364/BOE.8.003213

  • Waadt, R., Krebs, M., Kudla, J., & Schumacher, K. (2017). Multiparameter imaging of calcium and abscisic acid and high‐resolution quantitative calcium measurements using R‐GECO1‐mTurquoise in Arabidopsis. New Phytologist, 216(1), 303–320. http://doi.org/10.1111/nph.14706

Wang, Y., Han, X., Xi, W., Li, J., Roe, A. W., Lu, P., & Qian, J. (2017). Bright AIE Nanoparticles with F127 Encapsulation for Deep-Tissue Three-Photon Intravital Brain Angiography. – PubMed – NCBI. Advanced Healthcare Materials, 384, 1700685. http://doi.org/10.1002/adhm.201700685

Wenzel, M., Hamm, J. P., Peterka, D. S., & Yuste, R. (2017). Reliable and Elastic Propagation of Cortical Seizures In Vivo. CellReports, 19(13), 2681–2693. http://doi.org/10.1016/j.celrep.2017.05.090

  • White, B. J., Kan, J. Y., Levy, R., Itti, L., & Munoz, D. P. (2017). Superior colliculus encodes visual saliency before the primary visual cortex. Proceedings of the National Academy of Sciences of the United States of America, 114(35), 9451–9456. http://doi.org/10.1073/pnas.1701003114

  • Yates, J. L., Park, I. M., Katz, L. N., Pillow, J. W., & Huk, A. C. (2017). Functional dissection of signal and noise in MT and LIP during decision-making. Nature Neuroscience, 20(9), 1285–1292. http://doi.org/10.1038/nn.4611

  • Zhang, C., Kolodkin, A. L., Wong, R. O., & James, R. E. (2017). Establishing Wiring Specificity in Visual System Circuits: From the Retina to the Brain. Annual Review of Neuroscience, 40(1), 395–424. http://doi.org/10.1146/annurev-neuro-072116-031607


2017-07 system neurosci (checked)

Papers * Akbarinia, A., & Parraga, C. A. (2017). Feedback and Surround Modulated Boundary Detection. International Journal of Computer Vision, 33(5), 1–14. http://doi.org/10.1007/s11263-017-1035-5

Albright, T. D. (2017). Why eyewitnesses fail. Proceedings of the National Academy of Sciences, 114(30), 7758–7764. http://doi.org/10.1073/pnas.1706891114

Andersen, N., Krauth, N., & Nabavi, S. (2017). Hebbian plasticity in vivo : relevance and induction. Current Opinion in Neurobiology, 45, 188–192. http://doi.org/10.1016/j.conb.2017.06.001

Arcaro, M. J., & Livingstone, M. S. (2017). A hierarchical, retinotopic proto-organization of the primate visual system at birth. eLife, 6, e26196. http://doi.org/10.7554/eLife.26196

Barak, O. (2017). Recurrent neural networks as versatile tools of neuroscience research. Current Opinion in Neurobiology, 46, 1–6. http://doi.org/10.1016/j.conb.2017.06.003

  • Bullock, K. R., Pieper, F., Sachs, A. J., & Martinez-Trujillo, J. C. (2017). Visual and presaccadic activity in area 8Ar of the macaque monkey lateral prefrontal cortex. Journal of Neurophysiology, 118(1), 15–28. http://doi.org/10.1152/jn.00278.2016

  • Chamberland, S., Yang, H. H., Pan, M. M., Evans, S. W., Guan, S., Chavarha, M., et al. (2017). Fast two-photon imaging of subcellular voltage dynamics in neuronal tissue with genetically encoded indicators. eLife, 6, e25690. http://doi.org/10.7554/eLife.25690

  • Chan, K. Y., Jang, M. J., Yoo, B. B., Greenbaum, A., Ravi, N., Wu, W.-L., et al. (2017). Engineered AAVs for efficient noninvasive gene delivery to the central and peripheral nervous systems. Nature Neuroscience, 20(8), 1172–1179. http://doi.org/10.1038/nn.4593

  • Cohen, J. D., Bolstad, M., & Lee, A. K. (2017). Experience-dependent shaping of hippocampal CA1 intracellular activity in novel and familiar environments. eLife, 6, e23040. http://doi.org/10.7554/eLife.23040

  • Danielson, N. B., Turi, G. F., Ladow, M., Chavlis, S., Petrantonakis, P. C., Poirazi, P., & Losonczy, A. (2017). In Vivo Imaging of Dentate Gyrus Mossy Cells in Behaving Mice. Neuron, 93(3), 552–559.e4. http://doi.org/10.1016/j.neuron.2016.12.019

  • David, S. V. (2017). Cognition: Neurons couple up to make decisions. Nature. http://doi.org/10.1038/nature23100

** Goddard, E., Solomon, S. G., & Carlson, T. A. (2017). Dynamic population codes of multiplexed stimulus features in primate area MT. Journal of Neurophysiology, 118(1), 203–218. http://doi.org/10.1152/jn.00954.2016

Goldman, M. S., & Fee, M. S. (2017). Computational training for the next generation of neuroscientists. Current Opinion in Neurobiology, 46, 25–30. http://doi.org/10.1016/j.conb.2017.06.007

Gordon, E. M., Laumann, T. O., Gilmore, A. W., Newbold, D. J., Greene, D. J., Berg, J. J., et al. (2017). Precision Functional Mapping of Individual Human Brains. Neuron, 0(0), 249–258. http://doi.org/10.1016/j.neuron.2017.07.011

Green, A. A., Kim, J., Ma, D., Silver, P. A., Collins, J. J., & Yin, P. (2017). Complex cellular logic computation using ribocomputing devices. Nature, 12, 381. http://doi.org/10.1038/nature23271

  • Grilli, J., Barabás, G., Michalska-Smith, M. J., & Allesina, S. (2017). Higher-order interactions stabilize dynamics in competitive network models. Nature, 75, 1527. http://doi.org/10.1038/nature23273

Gulbinaite, R., İlhan, B., & VanRullen, R. (2017). The Triple-Flash Illusion Reveals a Driving Role of Alpha-Band Reverberations in Visual Perception. Journal of Neuroscience, 37(30), 7219–7230. http://doi.org/10.1523/JNEUROSCI.3929-16.2017

** Hasse, J. M., & Briggs, F. (2017). Corticogeniculate feedback sharpens the temporal precision and spatial resolution of visual signals in the ferret. Proceedings of the National Academy of Sciences of the United States of America, 114(30), E6222–E6230. http://doi.org/10.1073/pnas.1704524114

Huang, C., & Doiron, B. (2017). Once upon a (slow) time in the land of recurrent neuronal networks…. Current Opinion in Neurobiology, 46, 31–38. http://doi.org/10.1016/j.conb.2017.07.003

Hyman, J. M., Holroyd, C. B., & Seamans, J. K. (2017). A Novel Neural Prediction Error Found in Anterior Cingulate Cortex Ensembles. Neuron, 0(0). http://doi.org/10.1016/j.neuron.2017.06.021

*** Iacaruso, M. F., Gasler, I. T., & Hofer, S. B. (2017). Synaptic organization of visual space in primary visual cortex. Nature, 547(7664), 449–452. http://doi.org/10.1038/nature23019

Inada, K., Tsuchimoto, Y., & Kazama, H. (2017). Origins of Cell-Type-Specific Olfactory Processing in the Drosophila Mushroom Body Circuit. Neuron, 95(2), 357–367.e4. http://doi.org/10.1016/j.neuron.2017.06.039

  • Ismakov, R., Barak, O., Jeffery, K., & Derdikman, D. (2017). Grid Cells Encode Local Positional Information. Current Biology, 0(0). http://doi.org/10.1016/j.cub.2017.06.034

Jorstad, N. L., Wilken, M. S., Grimes, W. N., Wohl, S. G., VandenBosch, L. S., Yoshimatsu, T., et al. (2017). Stimulation of functional neuronal regeneration from Müller glia in adult mice. Nature. http://doi.org/10.1038/nature23283

Kato, H. K., Asinof, S. K., & Isaacson, J. S. (2017). Network-Level Control of Frequency Tuning in Auditory Cortex. Neuron, 1–17. http://doi.org/10.1016/j.neuron.2017.06.019

Knudsen, E. I., Schwarz, J. S., Knudsen, P. F., & Sridharan, D. (2017). Space-Specific Deficits in Visual Orientation Discrimination Caused by Lesions in the Midbrain Stimulus Selection Network. Current Biology, 0(0). http://doi.org/10.1016/j.cub.2017.06.011

Li, Y., Gong, H., Yang, X., Yuan, J., Jiang, T., Li, X., et al. (2017). TDat: An Efficient Platform for Processing Petabyte-Scale Whole-Brain Volumetric Images. Frontiers in Neural Circuits, 11, 2033. http://doi.org/10.3389/fncir.2017.00051

Livneh, Y., Ramesh, R. N., Burgess, C. R., Levandowski, K. M., Madara, J. C., Fenselau, H., et al. (2017). Homeostatic circuits selectively gate food cue responses in insular cortex. Nature, 546(7660), 611–616. http://doi.org/10.1038/nature22375

  • Mann, K., Gallen, C. L., & Clandinin, T. R. (2017). Whole-Brain Calcium Imaging Reveals an Intrinsic Functional Network in Drosophila. Current Biology, 0(0). http://doi.org/10.1016/j.cub.2017.06.076

Minami, S., & Amano, K. (2017). Illusory Jitter Perceived at the Frequency of Alpha Oscillations. Current Biology, 0(0). http://doi.org/10.1016/j.cub.2017.06.033

Murty, N. A. R., & Arun, S. R. (2017). Effect of silhouetting and inversion on view invariance in the monkey inferotemporal cortex. Journal of Neurophysiology, 118(1), 353–362. http://doi.org/10.1152/jn.00008.2017

  • Ohshiro, T., Angelaki, D. E., & DeAngelis, G. C. (2017). A Neural Signature of Divisive Normalization at the Level of Multisensory Integration in Primate Cortex. Neuron, 95(2), 399–411.e8. http://doi.org/10.1016/j.neuron.2017.06.043

  • Peters, A. J., Lee, J., Hedrick, N. G., O’Neil, K., & Komiyama, T. (2017). Reorganization of corticospinal output during motor learning. Nature Neuroscience, 57, 329. http://doi.org/10.1038/nn.4596

Ponce, C. R., Lomber, S. G., & Livingstone, M. S. (2017). Posterior Inferotemporal Cortex Cells Use Multiple Input Pathways for Shape Encoding. The Journal of Neuroscience : the Official Journal of the Society for Neuroscience, 37(19), 5019–5034. http://doi.org/10.1523/JNEUROSCI.2674-16.2017

Ramachandran, S., Meyer, T., & Olson, C. R. (2017). Prediction suppression and surprise enhancement in monkey inferotemporal cortex. Journal of Neurophysiology, 118(1), 374–382. http://doi.org/10.1152/jn.00136.2017

*** Rose, T., & Hübener, M. (2017). Neurobiology: Synapses get together for vision. Nature, 547(7664), 408–410. http://doi.org/10.1038/nature23098

  • Runyan, C. A., Piasini, E., Panzeri, S., & Harvey, C. D. (2017). Distinct timescales of population coding across cortex. Nature, 86, 1916. http://doi.org/10.1038/nature23020

Saal, H. P., Delhaye, B. P., Rayhaun, B. C., & Bensmaia, S. J. (2017). Simulating tactile signals from the whole hand with millisecond precision. Proceedings of the National Academy of Sciences of the United States of America, 114(28), E5693–E5702. http://doi.org/10.1073/pnas.1704856114

  • Schmidt-Hieber, C., Toleikyte, G., Aitchison, L., Roth, A., Clark, B. A., Branco, T., & Häusser, M. (2017). Active dendritic integration as a mechanism for robust and precise grid cell firing. Nature Neuroscience, 20(8), 1114–1121. http://doi.org/10.1038/nn.4582

  • Scholl, B., Pattadkal, J. J., & Priebe, N. J. (2017). Binocular Disparity Selectivity Weakened after Monocular Deprivation in Mouse V1. The Journal of Neuroscience : the Official Journal of the Society for Neuroscience, 37(27), 6517–6526. http://doi.org/10.1523/JNEUROSCI.1193-16.2017

  • Scott, B. B., Constantinople, C. M., Akrami, A., Hanks, T. D., Brody, C. D., & Tank, D. W. (2017). Fronto-parietal Cortical Circuits Encode Accumulated Evidence with a Diversity of Timescales. Neuron, 0(0). http://doi.org/10.1016/j.neuron.2017.06.013

Sedigh-Sarvestani, M., Vigeland, L., Fernandez-Lamo, I., Taylor, M. M., Palmer, L. A., & Contreras, D. (2017). Intracellular, In Vivo, Dynamics of Thalamocortical Synapses in Visual Cortex. The Journal of Neuroscience : the Official Journal of the Society for Neuroscience, 37(21), 5250–5262. http://doi.org/10.1523/JNEUROSCI.3370-16.2017

Stern, P. (2017). The disappearance of fine motor control. Science (New York, N.Y.), 357(6349), 366–367. http://doi.org/10.1126/science.357.6349.366-f

*** Tajima, S., Koida, K., Tajima, C. I., Suzuki, H., Aihara, K., & Komatsu, H. (2017). Task-dependent recurrent dynamics in visual cortex. eLife, 6. http://doi.org/10.7554/eLife.26868

Totty, M. S., Chesney, L. A., Geist, P. A., & Datta, S. (2017). Sleep-Dependent Oscillatory Synchronization: A Role in Fear Memory Consolidation. Frontiers in Neural Circuits, 11, 572. http://doi.org/10.3389/fncir.2017.00049

Tsytsarev, V., Arakawa, H., Zhao, S., Chédotal, A., & Erzurumlu, R. S. (2017). Behavioral Consequences of a Bifacial Map in the Mouse Somatosensory Cortex. Journal of Neuroscience, 37(30), 7209–7218. http://doi.org/10.1523/JNEUROSCI.0598-17.2017

Vanni, M. P., Chan, A. W., Balbi, M., Silasi, G., & Murphy, T. H. (2017). Mesoscale mapping of mouse cortex reveals frequency-dependent cycling between distinct macroscale functional modules. Journal of Neuroscience, 3560–16. http://doi.org/10.1523/JNEUROSCI.3560-16.2017

  • Voigt, F. F., Emaury, F., Bethge, P., Waldburger, D., Link, S. M., Carta, S., et al. (2017). Multiphoton in vivo imaging with a femtosecond semiconductor disk laser. Biomedical Optics Express, 8(7), 3213–3231. http://doi.org/10.1364/BOE.8.003213

** Wenzel, M., Hamm, J. P., Peterka, D. S., & Yuste, R. (2017). Reliable and Elastic Propagation of Cortical Seizures In Vivo. CellReports, 19(13), 2681–2693. http://doi.org/10.1016/j.celrep.2017.05.090


2017-06 system neurosci

  • Blum, R. (Ed.). (2017). An R-CaMP1.07 reporter mouse for
    cell-type-specific expression of a sensitive red fluorescent calcium
    indicator. PLoS ONE, 12(6), e0179460.
    http://doi.org/10.1371/journal.pone.0179460

    • Butler, R., Bernier, P.-M., Lefebvre, J., Gilbert, G., &
      Whittingstall, K. (2017). Decorrelated Input Dissociates Narrow Band γ
      Power and BOLD in Human Visual Cortex. Journal of Neuroscience,
      37(22), 5408–5418. http://doi.org/10.1523/JNEUROSCI.3938-16.2017

Cho, J. R., Treweek, J. B., Robinson, J. E., Xiao, C., Bremner, L. R.,
Greenbaum, A., & Gradinaru, V. (2017). Dorsal Raphe Dopamine Neurons
Modulate Arousal and Promote Wakefulness by Salient Stimuli. Neuron,
0(0). http://doi.org/10.1016/j.neuron.2017.05.020

** Fang, Q., & Tao, H. W. (2017). Direction selectivity starts early.
Nature Neuroscience, 20(7), 899–901. http://doi.org/10.1038/nn.4585

Fernando, B., & Gould, S. (2017). Discriminatively Learned
Hierarchical Rank Pooling Networks. International Journal of Computer
Vision, 2(3), 1–21. http://doi.org/10.1007/s11263-017-1030-x

  • Gal, E., London, M., Globerson, A., Ramaswamy, S., Reimann, M. W.,
    Muller, E., et al. (2017). Rich cell-type-specific network topology in
    neocortical microcircuitry. Nature Neuroscience, 20(7), 1004–1013.
    http://doi.org/10.1038/nn.4576

Gong, M., Jia, K., & Li, S. (2017). Perceptual Competition Promotes
Suppression of Reward Salience in Behavioral Selection and Neural
Representation. Journal of Neuroscience, 37(26), 6242–6252.
http://doi.org/10.1523/JNEUROSCI.0217-17.2017

** Gulati, S., Cao, V. Y., & Otte, S. (2017). Multi-layer Cortical
Ca2+ Imaging in Freely Moving Mice with Prism Probes and Miniaturized
Fluorescence Microscopy. Journal of Visualized Experiments, (124).
http://doi.org/10.3791/55579

  • Guo, W., Clause, A. R., Barth-Maron, A., & Polley, D. B. (2017). A
    Corticothalamic Circuit for Dynamic Switching between Feature
    Detection and Discrimination. Neuron.
    http://doi.org/10.1016/j.neuron.2017.05.019

He, C. X., Cantu, D. A., Mantri, S. S., Zeiger, W. A., Goel, A., &
Portera-Cailliau, C. (2017). Tactile defensiveness and impaired
adaptation of neuronal activity in the Fmr1 knockout mouse model of
autism. – PubMed – NCBI. Journal of Neuroscience, 0651–17.
http://doi.org/10.1523/JNEUROSCI.0651-17.2017

** Hillier, D., Fiscella, M., Drinnenberg, A., Trenholm, S., Rompani,
S. B., Raics, Z., et al. (2017). Causal evidence for retina-dependent
and -independent visual motion computations in mouse cortex. Nature
Neuroscience, 20(7), 960–968. http://doi.org/10.1038/nn.4566

  • Kamigaki, T., & Dan, Y. (2017). Delay activity of specific
    prefrontal interneuron subtypes modulates memory-guided behavior.
    Nature Neuroscience, 20(6), 854–863. http://doi.org/10.1038/nn.4554

*** Klink, P. C., Dagnino, B., Gariel-Mathis, M.-A., & Roelfsema, P.
R. (2017). Distinct Feedforward and Feedback Effects of
Microstimulation in Visual Cortex Reveal Neural Mechanisms of Texture
Segregation. Neuron, 0(0). http://doi.org/10.1016/j.neuron.2017.05.033

  • Levine, J. N., Chen, H., Gu, Y., & Cang, J. (2017). Environmental
    Enrichment Rescues Binocular Matching of Orientation Preference in the
    Mouse Visual Cortex. Journal of Neuroscience, 37(24), 5822–5833.
    http://doi.org/10.1523/JNEUROSCI.3534-16.2017

** Liu, Y. J., Hashemi-Nezhad, M., & Lyon, D. C. (2017). Differences
in orientation tuning between pinwheel and domain neurons in primary
visual cortex depend on contrast and size. Neurophotonics, 4(3),
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2016年最も好きな論文

この記事は,今年読んだ一番好きな論文 Advent Calendar 2016への投稿です. 下記の論文について紹介します.絵を描く時間をわすれており,結果としてわかりにくくなってしまった. Rust, N. C., & DiCarlo, J. J. (2010). Selectivity and tolerance (“invariance”) both increase as visual information propagates from cortical area V4 to IT. The Journal of Neuroscience : the Official Journal of the Society for Neuroscience, 30(39), 12978–12995. http://doi.org/10.1523/JNEUROSCI.0179-10.2010

概要

全然今年発表された論文じゃないんですが真面目に読んだのは今年だし面白かったので解説します.近年,視覚皮質を模したモデルを用いたCNNが注目を集めていて深い階層が効果を発揮する根拠の一つとしてたまに挙げられる論文の一つです.ざっくりいうと,

低次から高次の視覚野にかけてみている物体の脳内表現が一般化 (抽象化といってもいい)されてく ということを示した論文です.以前 (というか今も) の神経科学の論文では各領野から神経細胞の特性をひとつひとつ取り出してV1にはこういう細胞が多くてV4にはこんな特性を持つ細胞がある〜といった論旨の論文がまだまだ根強いのですがこの研究ではある領野の細胞集団のデータをつかってパターン認識を行うという手法を用いているのが特徴です.こういったアプローチの研究も近年増えてきています.著者らは神経科学に機械学習手法をもちこんだ結果を次々と発表していて,注目されているグループです.

intro

視覚に関わるニューロンの受容野

視覚研究ガチ勢には怒られそうな雑解説をします. 下記はノーベル賞も受賞したHubel, Wiesel 氏らによるネコ初期視覚野ニューロンの受容野の同定を示した実験の動画です.

動画LINK

上の動画の前半では初期視覚野の単純型細胞とよばれる細胞の視覚刺激への応答を計測しています.この細胞はある向きで中心が暗く,周辺が明るいバーが担当している領域にあったときにスパイクをたくさん発します.このように,視覚野の特に初期のニューロンはそれぞれ視野のある一部分を担当して,その領域の方位・空間周波数をよみだすフィルターになっていて,フーリエ変換のような計算が脳内で行われているとされています.これらの細胞の応答を集めると逆フーリエ変換ができ,つまり初期視覚野は画像の圧縮表現を行っていると言えます.(詳しくは 大澤先生@阪大のサイトなどをご覧下さい) 近年ではこのような細胞の担当する範囲とその応答特性まで含めて “受容野” と呼ぶことが多いです.

高次の視覚野ニューロンの特性とinvariance (不変性)

それでは高次の視覚野のニューロンはどんな情報を表現しているのかというと,より 抽象的特定の形 に対して強く応答するニューロンがあると言われています.さらにそういったニューロンの多くは,同じ顔の視覚刺激ならば向き・大きさ・表示する場所などが変わっても同じような応答をすることが知られていました.このように視覚刺激の大きさや場所などのパラメータをかえて呈示しても細胞の応答が変化しないことを指して invariance と呼びます.つまりこれらの細胞は初期視覚野のように画像特性を表現しているのではなくより抽象的に「目の前に顔(や特定のオブジェクト)があるかどうか」を表現しているのです.上述したV1の単純型細胞は受容野内でも適切な場所に黒いエッジがないと応答しないのにくらべると,かなり抽象化した表現がされていることが推察されます.

この論文のポイント

これまでの研究の問題点

というストーリーが長い間教科書的には説明されていたのですが,実際により高次視覚野になるにつれて size, position などについての invariance を獲得しているかどうかは統一的・定量的に検証されされていませんでした.IT野の細胞といっても特定の顔にしか応答しない細胞もあれば色々な物体に応答する細胞もあり,多くの細胞の選択性はそれほど高くないのです.また複数の領野で同じ刺激をつかって検証するのは実験的にも大変ですし,多くの論文では「この領野にはこんな細胞が多かった」という程度で終わっている場合が殆どでした.

新しい点

この研究では機械学習の手法であるSVM (線形カーネル) を用いて,上記問題の解決に取り組みました.細胞一つ一つの特性の分布からでなく,各領野細胞の特性をまとめて特徴量として脳活動からそのとき見ていた物体の分類をしようという考えで,つまり細胞一つ一つではなく,集団での表現をみようという考えです.もし invariance が高次視覚野で集団表現されているとすれば,呈示場所 や画像サイズを変更した同様の画像セットを同じクラスとして分類できるはずです.

手法と結果

記録

記録実験自体は単純なもので,まずたくさん物体画像を用意し,そのサイズや呈示する場所を変えて何度もサルに見せます.その際にサルの視覚野V4・ITに神経細胞の応答を測るために電極を刺入しておきます.このようにして計測している細胞がどのような視覚刺激を見たときにどれくらいスパイクを発生するかを記録します.この手法で200個くらいの神経細胞の特性 (どの画像,場所・サイズに対してどのくらいスパイクを発生するか)を調べます.

(サルのイラスト以外はいらすとやさんより)

解析方法および結果

このとき細胞集団の活動からどの画像がでていたか当てることができるか?ということで機械学習の手法を用います.この正解率でV4/ITの情報表現を探ります. まず上の実験での各細胞の応答の強さを特徴ベクトルとしてSVMに学習させます.ある画像を表示した際の応答は,n (記録した細胞数) 次元の空間の一点として表されますので,この空間上にどの画像が画面にでていたかの境界線を定義するということです .

この際に,オブジェクト画像のサイズや表示する場所を変えても弁別ができるとしたら,その細胞集団は表示されている画像の特性ではなくその “物体” そのものを表現していると言えないでしょうか? この論文の大きな結果は,中期視覚野V4細胞の活動データで作ったSVMは刺激画像の場所・大きさがかわったデータを含めると大きく正解率が下がるのに対し,高次視覚野であるIT細胞群のSVMは正解率があまり下がらないということを示したことです.特に画像を表示する場所についてV4と比べ強い invariance を示しており,これはこれまでの研究で示されていた個々のIT野細胞の特徴と一致する結果となりました. [模式図: 本文 fig 7c. ]

最後に

細胞一つ一つでみると微妙な差だったり単なる分布の差だったりした invarianceを,機械学習の手法をもちこんで細胞群をまとめて直接比較するというのが非常に面白いと感じました.上で紹介した解析はこの論文のごく一部で,さらに個々の細胞レベルでの解析もあり,またスクランブル画像 (低次特徴量を保持しつつ画像全体の構造をシャッフルした画像)に対する応答を調べたりもしています.神経科学や機械学習に興味のある方は是非一読ください.


MATLABのPCAとK-meansを試してみる (スパイクソ−ティングもどき)

MATLABのPCAとかの使い方をおさらいしておきたかったのでなにか良い例ないかなとおもったらここにスパイクソーティングはPCAがよく使われてると書かれてたので簡単に試してみた.

疑似スパイクデータ生成は真面目にモデルとか実装するの面倒だったので適当にガボール関数つくってノイズを加えた.ためしに3つユニットを混ぜてみたけっか.

スクリーンショット 2015-08-26 20.30.33

異常な簡単さ.実際のスパイクソーティングは多chだったりテンプレートマッチングとかしたりしてもっと難しいので各自論文チェックしましょう.


日記 (2015-06-14)

バイク洗車 + チェーン清掃など

バイクを洗車.土曜に洗車して,雨降りそうで悲しくなったがなんとかもってよかった.ホイールとか「おまえそんな色してたのか…」てくらい汚れてた.サッパリ.
集合住宅住みだと水道とかなくて洗車しづらいのよね.
日曜はバイクでどっか以降と思ったが前日に夜更かし論文読みしたので寝坊して断念.良い天気だったのに.

Vitaの積みゲー消化

  • イース セルセタの樹海
  • アンチャーテッド 地図無き冒険の始まり

ほぼラスダンで詰んでたのをクリア.両方面白かった.
イースは7みたいにラスボスはパーティ全員使用とかなくて助かった反面すこしラスボスの攻撃がワンパすぎてすこし物足りなかった.1週目からハードでやったけど丁度良い難易度だった.全般的に回復アイテムにほとんど制限なかったので少し7よりはぬるめ.


エアクリ交換

DSC_0037

SVたんのエアクリーナを交換.写真何枚かとったけどいまどきSV400Sのメンテ記事なんて必要としているオーナはおるいまい.
ちなみにシート外してタンクはずして+ドライバでネジ4つ外してつけかえるだけ.タンクはずせばああこれね,とすぐわかると思う.

効果は上々.あきらかにアイドリングが安定してるし,スムーズに加速する感覚がある.アクセル回すのが楽しい.
車検前にかえとけばもう少しスムーズに通ったんじゃなかろうか.次はエンジンプラグ交換する予定.