From Brains to BRAINs: Neuroscience at the Cutting Edge

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

Transcript of From Brains to BRAINs: Neuroscience at the Cutting Edge

Page 1: From Brains to BRAINs: Neuroscience at the Cutting Edge

From Brains to BRAINS: Neuroscience at the Cutting Edge

John Borghi, PhD@JohnBorghi

@BoldSignalsPod

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Open

Connectome

Project

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McCabe, 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

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

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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, 773–778.

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

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

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

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Wickersham, I. R., Lyon, D. C., Barnard, R. J., Mori, T., Finke, S., Conzelmann, K. K., ... & Callaway, E. M. (2007). Monosynaptic restriction of

transsynaptic tracing from single, genetically targeted neurons. Neuron, 53(5), 639-647.

Transsynaptic Tracing

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

Expansion Microscopy

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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

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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

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

Golgi Stain

Brainbow

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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.

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Allen Cell Types Database

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Optogenetic actuators(e.g. channelrhodopsin)

Optogenetic sensors(e.g. Clomeleon, Mermaid)

Genetic Construct

inserted into virus

Virus is injected

into animal

Laser light is used to

Control activity of infected

neurons

Activity of infected

neurons is measured via

optic sensor

Optogenetics

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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.

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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

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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.

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

“Closed Loop” Optogenetics

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Transcranial Direct

Current Stimulation

foc.us tDCS v2

Ghostbusters (1984)

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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

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

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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

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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

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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.

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EyeWire

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The Human Brain Project

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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.

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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.

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

The Human Connectome

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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

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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

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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.

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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 Psychiatry

Shackman, 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.

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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

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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

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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

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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.

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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 event‐related fMRI. Human brain mapping, 26(4), 262-272.

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Sentiment Analysis by Emotient

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Clarity by Neurokky

Neuroscience Fiction

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Thanks!\

John Borghi, [email protected]

@JohnBorghi

Bold Signals [email protected]

@BoldSignalsPod