from brains to brains: neuroscience at the cutting edge

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From Brains to BRAINS: Neuroscience at the Cutting EdgeJohn Borghi, PhD@JohnBorghi@BoldSignalsPod

Open ConnectomeProjectMcCabe, D. P., & Castel, A. D. (2008). Seeing is believing: The effect of brain images on judgments of scientific reasoning.Cognition,107(1), 343-352.

Superfluous Neuroscience

Ariely, D., & Berns, G. S. (2010). Neuromarketing: the hope and hype of neuroimaging in business. Nature Reviews Neuroscience, 11(4), 284-292.

Noble, K. G., Houston, S. M., Brito, N. H., Bartsch, H., Kan, E., Kuperman, J. M., ... & Sowell, E. R. (2015). Family income, parental education and brain structure in children and adolescents. Nature Neuroscience, 18, 773778.

Adapted From: Brodmann K (1909). Vergleichende Lokalisationslehre der Grosshirnrinde.

Lafer-Sousa, R., Hermann, K.L., & Conway, B.R. (2015). Striking individual differences in color perception uncovered by the dress photograph. Current Biology.

Park, H. J., & Friston, K. (2013). Structural and functional brain networks: from connections to cognition.Science,342(6158), 1238411.

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Chen, F., Tillberg, P. W., & Boyden, E. S. (2015). Expansion microscopy. Science, 347(6221),543-548Expansion Microscopy

Chung, K., Wallace, J., Kim, S. Y., Kalyanasundaram, S., Andalman, A. S., Davidson, T. J., ... & Deisseroth, K. (2013). Structural and molecular interrogation of intact biological systems.Nature,497(7449), 332-337.CLARITY

Chung, K., Wallace, J., Kim, S. Y., Kalyanasundaram, S., Andalman, A. S., Davidson, T. J., ... & Deisseroth, K. (2013). Structural and molecular interrogation of intact biological systems.Nature,497(7449), 332-337.CLARITY

Lichtman, J. W., Livet, J., & Sanes, J. R. (2008). A technicolour approach to the connectome. Nature Reviews Neuroscience, 9(6), 417-422.Golgi StainBrainbow

Chung, K., Wallace, J., Kim, S. Y., Kalyanasundaram, S., Andalman, A. S., Davidson, T. J., ... & Deisseroth, K. (2013). Structural and molecular interrogation of intact biological systems.Nature,497(7449), 332-337.

Allen Cell Types Database Optogenetic actuators(e.g. channelrhodopsin)Optogenetic sensors(e.g. Clomeleon, Mermaid)Genetic Construct inserted into virusVirus is injectedinto animalLaser light is used to Control activity of infected neuronsActivity of infected neurons is measured via optic sensor

Optogenetics

Baratta, M. V., Nakamura, S., Dobelis, P., Pomrenze, M. B., Dolzani, S. D., & Cooper, D. C. (2012). Optogenetic control of genetically-targeted pyramidal neuron activity in prefrontal cortex. arXiv preprint arXiv:1204.0710.

Ramirez, S., Liu, X., Lin, P. A., Suh, J., Pignatelli, M., Redondo, R. L., ... & Tonegawa, S. (2013). Creating a false memory in the hippocampus.Science,341(6144), 387-391.Image: Evan Wondolowski of Collective Next

Tanaka, K. Z., Pevzner, A., Hamidi, A. B., Nakazawa, Y., Graham, J., & Wiltgen, B. J. (2014). Cortical Representations Are Reinstated by the Hippocampus during Memory Retrieval. Neuron, 84(2), 347-354.

Grosenick, L., Marshel, J. H., & Deisseroth, K. (2015). Closed-Loop and Activity-Guided Optogenetic Control. Neuron, 86(1), 106-139.Closed Loop Optogenetics

Transcranial DirectCurrent Stimulationfoc.us tDCS v2Ghostbusters (1984)

Grau, C., Ginhoux, R., Riera, A., Nguyen, T. L., Chauvat, H., Berg, M., ... & Ruffini, G. (2014). Conscious brain-to-brain communication in humans using non-invasive technologies.PloS one,9(8), e105225.Brain-to-Brain Communication

Park, H. J., & Friston, K. (2013). Structural and functional brain networks: from connections to cognition.Science,342(6158), 1238411.

Szigeti, B., Gleeson, P., Vella, M., Khayrulin, S., Palyanov, A., Hokanson, J., ... & Larson, S. (2014). OpenWorm: an open-science approach to modeling Caenorhabditis elegans.Frontiers in computational neuroscience,8.OpenWorm

Varshney, L. R., Chen, B. L., Paniagua, E., Hall, D. H., & Chklovskii, D. B. (2011). Structural properties of the Caenorhabditis elegans neuronal network. PLoS computational biology, 7(2), e1001066.

Robot Worms

Oh, S. W., Harris, J. A., Ng, L., Winslow, B., Cain, N., Mihalas, S., ... & Zeng, H. (2014). A mesoscale connectome of the mouse brain. Nature, 508(7495), 207-214.

EyeWire

The Human Brain Project

The Human Connectome

Hagmann, P., Cammoun, L., Gigandet, X., Meuli, R., Honey, C. J., Wedeen, V. J., & Sporns, O. (2008). Mapping the structural core of human cerebral cortex.PLoS biology,6(7), e159.

Irimia, A., Chambers, M. C., Torgerson, C. M., & Van Horn, J. D. (2012). Circular representation of human cortical networks for subject and population-level connectomic visualization.Neuroimage,60(2), 1340-1351.

Fornito, A., Zalesky, A., & Breakspear, M. (2015). The connectomics of brain disorders. Nature Reviews Neuroscience, 16(3), 159-172.The Human Connectome

Fox, C. J., Iaria, G., & Barton, J. J. (2009). Defining the face processing network: optimization of the functional localizer in fMRI.Human brain mapping,30(5), 1637-1651.The Face Processing Network

Glahn, D. C., Winkler, A. M., Kochunov, P., Almasy, L., Duggirala, R., Carless, M. A., ... & Blangero, J. (2010). Genetic control over the resting brain.Proceedings of the National Academy of Sciences,107(3), 1223-1228.The Default Mode Network

Brain Training Games

Kesler, S. R., Sheau, K., Koovakkattu, D., & Reiss, A. L. (2011). Changes in frontal-parietal activation and math skills performance following adaptive number sense training: Preliminary results from a pilot study.Neuropsychological rehabilitation,21(4), 433-454.Owen, A. M., Hampshire, A., Grahn, J. A., Stenton, R., Dajani, S., Burns, A. S., ... & Ballard, C. G. (2010). Putting brain training to the test.Nature,465(7299), 775-778.

Jones-Hagata, L. B., Ortega, B. N., Zaiko, Y. V., Roach, E. L., Korgaonkar, M. S., Grieve, S. M., ... & Etkin, A. (2015). Identification of a Common Neurobiological Substrate for Mental Illness. JAMA PsychiatryShackman, A. J., Salomons, T. V., Slagter, H. A., Fox, A. S., Winter, J. J., & Davidson, R. J. (2011). The integration of negative affect, pain and cognitive control in the cingulate cortex. Nature Reviews Neuroscience, 12(3), 154-167.

Kaplan, J. T., Man, K., & Greening, S. G. (2015). Multivariate cross-classification: applying machine learning techniques to characterize abstraction in neural representations.Frontiers in human neuroscience,9.Multi-Voxel Patten Analysis

Woo, C. W., Koban, L., Kross, E., Lindquist, M. A., Banich, M. T., Ruzic, L., ... & Wager, T. D. (2014). Separate neural representations for physical pain and social rejection.Nature communications,5.Eisenberger, N. I., Lieberman, M. D., & Williams, K. D. (2003). Does rejection hurt? An fMRI study of social exclusion.Science,302(5643), 290-292.Multi-Voxel Patten Analysis

Schoenmakers, S., Barth, M., Heskes, T., & van Gerven, M. (2013). Linear reconstruction of perceived images from human brain activity.NeuroImage,83, 951-961.Neural Decoding with MVPA

Cowen, A. S., Chun, M. M., & Kuhl, B. A. (2014). Neural portraits of perception: reconstructing face images from evoked brain activity.Neuroimage,94, 12-22.

fMRI and Lie Detection?Langleben, D. D., Loughead, J. W., Bilker, W. B., Ruparel, K., Childress, A. R., Busch, S. I., & Gur, R. C. (2005). Telling truth from lie in individual subjects with fast eventrelated fMRI.Human brain mapping,26(4), 262-272.

Sentiment Analysis by EmotientClarity by Neurokky

Neuroscience FictionThanks!\

John Borghi, PhDJohn.Borghi@Gmail.com@JohnBorghiBold Signals PodcastBoldSignalsi@Gmail.com@BoldSignalsPod