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memory and its disorders

Our lab studies mechanisms of memory and memory disorders. We use a number of techniques and approaches that allow us to study memory from molecular mechanisms to the cells they affect, the circuits and neuroanatomy they modulate, all the way to behavioral studies in rodents and patients. For example, recently we have discovered the first mechanisms of memory allocation and memory linking and potential treatments for cognitive deficits associated with Neurofibromatosis type I, Tuberous Sclerosis, Noonan syndrome and HIV. Our field of study is Molecular and Cellular Cognition.



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Although mechanisms involved in encoding, storing and retrieving memory have attracted a great deal of attention, the processes that allocate individual memories to specific neurons within a network have remained elusive. Similarly, although the processes that connect and link information across time are critical for survival, they have also remained unexplored.

Recent findings from our laboratory, using methods, such as optogenetics and a new generation of head mounted fluorescent microscopes, unraveled the first insights into the mechanisms that modulate memory allocation in neuronetworks, and showed that they are critical to link memories across time.

We have shown that neurons compete to take part in memory traces and that the levels of the transcription factor CREB (cAMP-response element binding protein) determine the probability that a given neuron will be recruited into a given memory representation. Our electrophysiological studies showed that CREB-dependent transcription increases the excitability of neurons, and thus affects the probability that they will be recruited into a given memory.

We first proposed that a key function of memory allocation mechanisms is to link memories across time! Recently, our laboratory showed that one memory triggers CREB activation and subsequent increases in excitability in a subset of neurons of a network, so that another memory, even many hours later, can be allocated to some of the same neurons. Recall of the first memory triggers the activation of those neurons and therefore the reactivation and recall of the other memory. These results represent the first molecular, cellular and circuit mechanism underlying the linking of memories across time!

With the Poirazi lab, we have also published a biological model of memory linking across time in which linked memories are stored in clustered spines in overlapping neurons (PDF)

Our Memory Allocation and Linking discovery was highlighted by Scientific American as one of "13 Discoveries that Could Change Everything"


Key Publications:

Frank, A. C., S. Huang, M. Zhou, A. Gdalyahu, G. Kastellakis, T. K. Silva, E. Lu, X. Wen, P. Poirazi, J. T. Trachtenberg and A. J. Silva (2018). "Hotspots of dendritic spine turnover facilitate clustered spine addition and learning and memory." Nat Commun 9(1): 422.(link)

Lisman, John, Cooper, Katie, Segal, Megha, and Silva, Alcino J. Memory formation depends on both synapse specific modifications of synaptic strength and cell-specific increases in excitability.
Nature Neuroscience 2018

Alcino J Silva How the Brain Builds Memory Chains.
Scientific American July 2017

Denise J. Cai, Daniel Aharoni, Tristan Shuman, Justin Shobe, Jeremy Biane, Weilin Song, Brandon Wei, Michael Veshkini, Mimi La-Vu, Jerry Lou, Sergio Flores, Isaac Kim, Yoshitake Sano, Miou Zhou, Karsten Baumgaertel, Ayal Lavi, Masakazu Kamata, Mark Tuszynski, Mark Mayford, Peyman Golshani and Alcino J. Silva.
A shared neural ensemble links distinct contextual memories encoded close in time. Nature 534, 115–118 (02 June 2016) (PDF)

Kastellakis, G., Silva, AJ and Poirazi, P,
Linking memories across time via synapse clustering in nonlinear dendrites. Cell Reports, Volume 17, Issue 6, p1491–1504, 1 November 2016 (PDF)

Rogerson, T., B. Jayaprakash, D.J. Cai, Y. Sano, Y.S. Lee, Y. Zhou, P. Bekal, K. Deisseroth, and A.J. Silva,
Molecular and Cellular Mechanisms for Trapping and Activating Emotional Memories. PLoS One, 2016. 11(8): p. e0161655.(PDF)
Sano, Y, Shobe, JL, Zhou, M, Huang, S, Cai, DJ, Roth, BL, Kamata, M, and Silva, AJ.
CREB regulates memory allocation in the insular cortex. Current Biology 2014 (PDF). For a Scientist article on this research paper click here

Czajkowski, R, Jayaprakash, B, Wiltgen, B, Rogerson, T, Karlsson, MG, Barth, A, Trachtenberg, J, and Silva, AJ. E
ncoding and storage of spatial information in the retrosplenial cortex, PNAS Proc Natl Acad Sci U S A. 2014 (PDF)

Thomas Rogerson, Denise J. Cai, Adam Frank, Yoshitake Sano, Justin Shobe, Manuel F. Lopez-Aranda & Alcino J. Silva. S
ynaptic tagging during memory allocation. Nature Reviews Neuroscience 15, 157–169 (2014) PMID: 24496410 (PDF)

Silva, A. J., Y. Zhou, et al. (2009).
"Molecular and cellular approaches to memory allocation in neural circuits." Science 326(5951): 391-395.(PDF)

Zhou, Y., J. Won, et al. (2009). "
CREB regulates excitability and the allocation of memory to subsets of neurons in the amygdala." Nat Neurosci. (PDF)

Han, J. H., S. A. Kushner, et al. (2007). "
Neuronal competition and selection during memory formation." Science 316(5823): 457-460.(PDF).

Won, J. and A. J. Silva (2008). "
Molecular and cellular mechanisms of memory allocation in neuronetworks." Neurobiology of Learning and Memory 89(3): 285-292.

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Deficits in learning and memory can occur with aging, but little is known about what causes them. Studies in our laboratory demonstrated that just as humans and other animals, mice show age-related deficits in a variety of learning tests. Interestingly, cells in the brain become progressively less excitable with age, and previous studies suggested that this decrease in excitability could cause deficits in learning and memory.

Remarkably, our laboratory has shown that a change in a gene that increases the excitability of brain cells (the Kvb1.1 gene) improves long term potentiation as well as learning and memory specifically in aged mice.

We are engaged in a number of memory studies that will impact on how we understand and treat age-related cognitive decline, including studies of how the prefrontal cortex modulates the storage and retrieval of remote memory, and how memories are allocated in neuronetworks.

Recently, our laboratory showed that memory linking mechanisms are disrupted in the aging brain, and that increasing excitability in a subset of cells reverses these memory linking deficits. Two memories are said to be linked, when the recall of one triggers the recall of the other. Recently, our laboratory showed that one memory triggers CREB activation and subsequent increases in excitability in a subset of neurons of a network, so that another memory, even many hours later, can be allocated to some of the same neurons. Recall of the first memory triggers the activation of those neurons, and therefore the reactivation and recall of the other memory. Deficits in CREB and neuronal excitability associated with aging may underlie these impairments in memory linking. These results represent the first molecular, cellular and circuit mechanism underlying the linking of memories across time, and the first demonstration that memory linking is affected in the aging brain. It is possible that problems with memory linking may underly well-known source memory problems associated with aging.


Key Publications:

Denise J. Cai, Daniel Aharoni, Tristan Shuman, Justin Shobe, Jeremy Biane, Weilin Song, Brandon Wei, Michael Veshkini, Mimi La-Vu, Jerry Lou, Sergio Flores, Isaac Kim, Yoshitake Sano, Miou Zhou, Karsten Baumgaertel, Ayal Lavi, Masakazu Kamata, Mark Tuszynski, Mark Mayford, Peyman Golshani and Alcino J. Silva. A shared neural ensemble links distinct contextual memories encoded close in time. Nature 534, 115–118 (02 June 2016) (PDF)

Murphy, G., Shah, V.,. Hell, J.W., Silva, A.J. Investigation of age-related cognitive decline using mice as a model system: neurophysiological correlates. Am J Geriatr Psychiatry. 2006 Dec;14(12):1012-21. (PDF).

Murphy, G., Shah, V.,. Hell, J.W., Silva, A.J. Investigation of age-related cognitive decline using mice as a model system: behavioral correlates. Am J Geriatr Psychiatry. 2006 Dec;14(12):1004-11.(PDF).

Murphy GG, Fedorov NB, Giese KP, Ohno M, Friedman E, Chen R, Silva AJ. Increased neuronal excitability, synaptic plasticity, and learning in aged Kvbeta1.1 knockout mice. Curr Biol. 2004 Nov 9;14(21):1907-15.(PDF).

Giese, K.P., J.F. Storm, D. Reuter, N.B. Fedorov, L.-R. Shao, T. Leicher, O. Pongs, and A.J. Silva, Reduced K+ channel inactivation, spike broadening, and after-hyperpolarization in Kvß1.1-deficient mice with impaired learning. Learning and Memory, 1998. 5: p. 257-273 (link)




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Specific intellectual disabilities are the most common neurological complication of children with Neurofibromatosis type I (NF1) and Noonan Syndrome (NS). The inherent complexity of these cognitive deficits, and the complications of pursuing their study in patients, motivated us to study them in mice.

We have shown that these mice have very specific learning deficits that have striking similarities to the deficits in individuals with NF1 and NS.

Our biological studies of mice with NF1 and NS have yielded not only the mechanism for the learning deficits in these two disorders, but also a treatment . Studies in patients have suggested that there are similar deficits in patients to the ones we identified in mice, and therefore, it is possible that the treatments we developed may be effective in patients.

Currently, there is a large clinical trial involving multiple clinical centers around the world testing the efficacy of the treatment we developed for cognitive deficits associated with NF1.

Our studies of NF1 demonstrated that this GAP modulates GABA release during learning and that this in turn controls long term changes in synaptic function and consequently learning and memory. NF1 results in increases in inhibition that lead to deficits in plasticity and learning. In contrast, NS causes increases in basal excitatory synaptic transmission that occlude long term changes in synaptic function, and consequently cause deficits in learning and memory.

2013 general talk about NF1

Key Publications:

Rachel K. Jonas, EunJi Roh, Caroline A. Montojo, Laura A. Pacheco, Tena Rosser, Alcino J. Silva, Carrie E. Bearden. Risky Decision Making in Neurofibromatosis Type 1: An Exploratory Study. Biol Psychiatry Cogn Neurosci Neuroimaging. 2017 Mar;2(2):170-179

Oh, J.Y., Rhee, S., Silva, A.J., Lee, Y.S., and Kim, H.K. (2017). Noonan syndrome-associated SHP2 mutation differentially modulates the expression of postsynaptic receptors according to developmental maturation. Neurosci Lett 649, 41-47. PMID: 28366775

Gonçalves, J, Violante, IR, Sereno, J, Leitão, RA, Cai, Y, Abrunhosa, A Silva, AP Silva, AJ, and Castelo-Branco, M. Testing the excitation/inhibition imbalance hypothesis in a mouse model of the autism spectrum disorder: in viv neurospectroscopy and molecular evidence for regional phenotypes.
Molecular Autism (2017) 8:47, 2017

Petrella, L.I., Y. Cai, J.V. Sereno, S.I. Goncalves, A.J. Silva, and M. Castelo-Branco, Brain and behaviour phenotyping of a mouse model of neurofibromatosis type-1: an MRI/DTI study on social cognition.
Genes Brain Behav, 2016.

Bearden, C.E., G.S. Hellemann, T. Rosser, C. Montojo, R. Jonas, N. Enrique, L. Pacheco, S.A. Hussain, J.Y. Wu, J.S. Ho, J.J. McGough, C.A. Sugar, and A.J. Silva, A randomized placebo-controlled lovastatin trial for neurobehavioral function in neurofibromatosis I. Ann Clin Transl Neurol, 2016. 3(4): p. 266-79.(
PDF)

Tomson SN, Schreiner MJ, Narayan M, Rosser T, Enrique N, Silva AJ, Allen GI, Bookheimer SY, Bearden CE.Resting state functional MRI reveals abnormal network connectivity in neurofibromatosis 1. Hum Brain Mapp. 2015 Aug 25.PMID: 26304096

Korf B, Ahmadian R, Allanson J, Aoki Y, Bakker A, Wright EB, Denger B, Elgersma Y, Gelb BD, Gripp KW, Kerr B, Kontaridis M, Lazaro C, Linardic C, Lozano R, MacRae CA, Messiaen L, Mulero-Navarro S, Neel B, Plotkin S, Rauen KA, Roberts A, Silva AJ, Sittampalam SG, Zhang C, Schoyer L. The third international meeting on genetic disorders in the RAS/MAPK pathway: Towards a therapeutic approach.
Am J Med Genet A. 2015

Omrani A, van der Vaart T, Mientjes E, van Woerden GM, Hojjati MR, Li KW, Gutmann DH, Levelt CN, Smit AB, Silva AJ, Kushner SA, Elgersma Y. HCN channels are a novel therapeutic target for cognitive dysfunction in Neurofibromatosis type 1.
Mol Psychiatry. 2015; PMID: 25917366

Lee, Y-S, Ehninger, D, Zhou, M, Oh, J-Y, Butz, D, Araki, T, Nam, CI, Balaji, J, Sano, Y, Amin, A, Kim, H, Burger, C, Neel, BG, and Silva, AJ. Mechanism and treatment for the learning and memory deficits associated with mouse models of Noonan syndrome, Nature Neuroscience 17, 1736–1743 (2014); PMID: 25383899 (PDF) ) For a News and Views on this article, click here

Shilyansky C, Karlsgodt KH, Cummings DM, Sidiropoulou K, Hardt M, James AS, Ehninger D, Bearden CE, Poirazi P, Jentsch JD, Cannon TD, Levine MS, Silva AJ. Neurofibromin regulates corticostriatal inhibitory networks during working memory performance. Proc Natl Acad Sci U S A. 2010 Jul 12. PMID: 20624961 (
PDF)

Cui, Y, Costa, RM, Murphy, GG, Elgersma, Y, Zhu, Y, Gutmann, DH, Parada, LF, Mody, I, and Silva, AJ, Neurofibromin regulation of ERK signaling modulates GABA release and learning. Cell 2008 135(3) pp. 549 – 560. (PDF)

Krab, L.C., A. de Goede-Bolder, F.K. Aarsen, S.M. Pluijm, M.J. Bouman, J.N. van der Geest, M. Lequin, C.E. Catsman, W.F. Arts, S.A. Kushner, A.J. Silva, C.I. de Zeeuw, H.A. Moll, and Y. Elgersma, Effect of simvastatin on cognitive functioning in children with neurofibromatosis type 1: a randomized controlled trial. Jama, 2008. 300(3): p. 287-94. (
PDF)

Ehninger, D., S. Han, C. Shilyansky, Y. Zhou, W. Li, D.J. Kwiatkowski, V. Ramesh, and A.J. Silva, Reversal of learning deficits in a Tsc2(+/-) mouse model of tuberous sclerosis. Nat Med, 2008.(PDF)

Chen, A.P., M. Ohno, K.P. Giese, R. Kuhn, R.L. Chen, and A.J. Silva, Forebrain-specific knockout of B-raf kinase leads to deficits in hippocampal long-term potentiation, learning, and memory. J Neurosci Res, 2006. 83(1): p. 28-38.(PDF).

Kushner, S.A., Y. Elgersma, G.G. Murphy, D. Jaarsma, G.M. van Woerden, M.R. Hojjati, Y. Cui, J.C. LeBoutillier, D.F. Marrone, E.S. Choi, C.I. De Zeeuw, T.L. Petit, L. Pozzo-Miller, and A.J. Silva, Modulation of presynaptic plasticity and learning by the H-ras/extracellular signal-regulated kinase/synapsin I signaling pathway. J Neurosci, 2005. 25(42): p. 9721-34. (PDF)

Li, W., Y. Cui, S.A. Kushner, R.A. Brown, J.D. Jentsch, P.W. Frankland, T.D. Cannon, and A.J. Silva, The HMG-CoA reductase inhibitor lovastatin reverses the learning and attention deficits in a mouse model of neurofibromatosis type 1. Curr Biol, 2005. 15(21): p. 1961-7. (PDF)

Dhaka, A., R. Costa, H. Hu, D. Irvin, A. Patel, H. Kornblum, A. Silva, T. O'Dell, and J. Colicelli, The Ras Effector Rin1 Modulates the Formation of Aversive Memories. Journal of Neuroscience, 2003, 23(3):748-57.

Costa, R.M., N.B. Federov, J.H. Kogan, G.G. Murphy, J. Stern, M. Ohno, R. Kucherlapati, T. Jacks, and A.J. Silva, Mechanism for the learning deficits in a mouse model of neurofibromatosis type 1. Nature, 2002. 415(6871): p. 526-30.(PDF)

Ohno, M., P.W. Frankland, A.P. Chen, R.M. Costa, and A.J. Silva, Inducible, pharmacogenetic approaches to the study of learning and memory. Nature Neuroscience, 4, 1238-43, 2001.(PDF)

Giese, K., E. Friedman, J.-P. Telliez, N. Fedorov, W. Wines, L. Feig, and A.J. Silva, Hippocampus-dependent learning and memory is impaired in mice lacking the ras-guanine-nucleotide releasing factor 1(ras-GRF-1). Neuropharmacology, 2001. 41(16): p. 791-800.(PDF)

Costa, R.M., T. Yang, D.P. Huynh, S.M. Pulst, D.H. Viskochil, A.J. Silva, and C.I. Brannan, Learning deficits, but normal development and tumor predisposition, in mice lacking exon 23a of Nf1. [Comment In: Nat Genet. 2001 Apr;27(4):354-5 UI: 21175732]. Nature Genetics, 2001. 27(4): p. 399-405.(PDF)

Silva, A.J., P.W. Frankland, Z. Marowitz, E. Friedman, G. Lazlo, D. Cioffi, T. Jacks, and R. Bourtchuladze, A mouse model for the learning and memory deficits associated with neurofibromatosis type I. Nat Genet, 1997. 15(3): p. 281-4




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Most studies of brain injury, such as stroke, have traditionally focused on preventing neurodegeneration and death of affected brain cells. Comparatively little has been done to maximize and optimize the plasticity processes involved in repair and recovery after brain injury. Our laboratory is involved in a new initiative directed at leveraging brain plasticity in efforts to enhance repair and recovery following brain injury. In particular, in collaboration with the Carmichael, Shohami and Dobkins laboratories, we are using manipulations that enhance learning and memory to accelerate and optimize recovery after brain injury.

In the last 10 years, we and others have discovered multiple genetic and viral manipulations that dramatically enhance learning and memory. We have used information obtained from these studies in efforts to develop therapies to facilitate repair and recovery. For example, viral manipulations that enhance CREB function enhance motor recovery after stroke, while blocking CREB signaling prevents stroke recovery. CREB transfection enhances remapping of circuits disrupted by the stroke, and induces the formation of new connections within these circuits (PDF). Beyond the exciting clinical promise, these collaborative studies with the Carmichael lab showed that CREB is a central molecular node in the circuit responses after stroke that lead to recovery from motor deficits.

Key Publications:
Caracciolo, L., M. Marosi, J. Mazzitelli, S. Latifi, Y. Sano, L. Galvan, R. Kawaguchi, S. Holley, M. S. Levine, G. Coppola, C. Portera-Cailliau, A. J. Silva and S. T. Carmichael (2018). "CREB controls cortical circuit plasticity and functional recovery after stroke." Nat Commun 9(1): 2250 (PDF)
Miou Zhou Stuart Greenhill Shan Huang Tawnie K Silva Yoshitake Sano Shumin Wu Ying Cai Yoshiko Nagaoka Megha Sehgal Denise J Cai Yong-Seok Lee Kevin Fox Alcino J Silva. CCR5 is a suppressor for cortical plasticity and hippocampal learning and memory. DOI: http://dx.doi.org/10.7554/eLife.20985; Published December 20, 2016; Cite as eLife 2016;10.7554/eLife.209851. (PDF)
Kushner, S.A., Y. Elgersma, G.G. Murphy, D. Jaarsma, G.M. van Woerden, M.R. Hojjati, Y. Cui, J.C. LeBoutillier, D.F. Marrone, E.S. Choi, C.I. De Zeeuw, T.L. Petit, L. Pozzo-Miller, and A.J. Silva, Modulation of presynaptic plasticity and learning by the H-ras/extracellular signal-regulated kinase/synapsin I signaling pathway. J Neurosci, 2005. 25(42): p. 9721-34. (PDF)
Elgersma, Y., N. Fedorov, S. Ikonen, E. Choi, M. Elgersma, O. Carvalho, K. Giese, and A. Silva, Inhibitory autophosphorylation of CaMKII controls PSD association, plasticity and learning. Neuron, 2002. 36(3): p. 493-505.(PDF)
Murphy GG, Fedorov NB, Giese KP, Ohno M, Friedman E, Chen R, Silva AJ. Increased neuronal excitability, synaptic plasticity, and learning in aged Kvbeta1.1 knockout mice. Curr Biol. 2004 Nov 9;14(21):1907-15.(PDF)



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In our studies of the mechanistic underpinnings of extraordinary problem solving, we have studied different strains of mice with dramatic enhancements in learning and memory.

Understanding enhancements in learning and memory will be key to understanding extraordinary problem solving. Insights into extraordinary learning and memory will lead us a step closer to a mechanistic understanding of the biological processes responsible for historically creative achievements.

Insights into extraordinary cognition have also led us to treatments for cognitive deficits. For example, our efforts to identify memory enhancing mutations in mice led us to null mutations in CCR5, the receptor for HIV! In turn, this discovery led us to a brand new way to understand cognitive deficits associated with HIV and to a treatment for these cognitive deficits. Our work showed that stimulation of CCR5, a memory suppressor, by viral proteins may account for some of the cognitive deficits associated with HIV.


Key Publications:

Miou Zhou Stuart Greenhill Shan Huang Tawnie K Silva Yoshitake Sano Shumin Wu Ying Cai Yoshiko Nagaoka Megha Sehgal Denise J Cai Yong-Seok Lee Kevin Fox Alcino J Silva. CCR5 is a suppressor for cortical plasticity and hippocampal learning and memory. DOI: http://dx.doi.org/10.7554/eLife.20985; Published December 20, 2016; Cite as eLife 2016;10.7554/eLife.209851. (PDF)

Kaneko M, Cheetham CE, Lee Y-S, Silva AJ, Stryker MP, Fox K. Constitutively active H-ras accelerates multiple forms of plasticity in developing visual cortex. Proceedings of the National Academy of Sciences of the United States of America. 2010;107(44):19026-31. PubMed PMID: Medline:20937865. (Link)

Kushner, S.A., Y. Elgersma, G.G. Murphy, D. Jaarsma, G.M. van Woerden, M.R. Hojjati, Y. Cui, J.C. LeBoutillier, D.F. Marrone, E.S. Choi, C.I. De Zeeuw, T.L. Petit, L. Pozzo-Miller, and A.J. Silva, Modulation of presynaptic plasticity and learning by the H-ras/extracellular signal-regulated kinase/synapsin I signaling pathway. J Neurosci, 2005. 25(42): p. 9721-34. (
PDF)

Elgersma, Y., N. Fedorov, S. Ikonen, E. Choi, M. Elgersma, O. Carvalho, K. Giese, and A. Silva, Inhibitory autophosphorylation of CaMKII controls PSD association, plasticity and learning. Neuron, 2002. 36(3): p. 493-505.(PDF)

Murphy GG, Fedorov NB, Giese KP, Ohno M, Friedman E, Chen R, Silva AJ. Increased neuronal excitability, synaptic plasticity, and learning in aged Kvbeta1.1 knockout mice. Curr Biol. 2004 Nov 9;14(21):1907-15.(PDF)





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Our laboratory developed a framework and as set of algorithms to create maps (simplified abstractions) of causal information in research findings that can be used to integrate information and guide research planning. Based on this framework and algorithms, we developed a free web application that helps biologists keep track and interact with causal information in research papers (www.researchmaps.org).

Why researchmaps? In the last 20 years there has been a dramatic increase in the complexity of experiments and publications in Biology, including Neuroscience. This problem is specially severe in neuroscience, since in this field experiments often attempt to integrate across different sub-disciplines and levels of complexity, including, molecular, cellular, systems, behavioral, cognitive and clinical neuroscience. This discipline, for example, includes nearly two million research articles reporting approximately 20 million experiments.

We are looking for neuroscience students to helps us with our researchmaps project! This is a great opportunity for students interested in learning how neuroscientists integrate and plan experiments! Contact us!

For a recent Ray Kurzweil's newsletter article on our researchmaps work click here...

Alcino Silva talks about Researchmaps in a 2015 Current Biology interview


Key Publications:

- Matiasz, N. J., J. Wood, P. Doshi, W. Speier, B. Beckemeyer, W. Wang, W. Hsu and A. J. Silva (2018). "ResearchMaps.org for integrating and planning research." PLoS One 13(5): e0195271 (PDF)

- Matiasz, N.J., J. Wood, W. Wang, A.J. Silva, and W. Hsu, Computer-Aided Experiment Planning toward Causal Discovery in Neuroscience. Front Neuroinform, 2017. 11: p. 12.(PDF)

- Silva AJ, Müller KR. The need for novel informatics tools for integrating and planning research in molecular and cellular cognition. Learn Mem. 2015 Aug 18;22(9):494-8. PMID: 26286658 (PDF)

- Engineering the next revolution in neuroscience: the new science of experiment planning, 2013 by Alcino J. Silva, Anthony Landreth, John Bickle. Oxford Press, ISBN-13: 978-0199731756 ISBN-10: 0199731756 Edition: 1st. Book from Oxford Press 2013

- Landreth, A. and Silva, A.J. The Need for Research Maps to Navigate Published Work and Inform Experiment Planning. Neuron 2013 79 411-415 PMID: 23931992 (PDF)

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The figure above shows a researchmap representing results in a published paper (Costa et al., 2002). Each node in the graph has three items that describe the “What” of the item (top; e.g., name), as well as the “Where” (middle; spacial/source information that distinguishes the item) and the “When” (bottom; temporal information that defines the item) information that defines it. Nodes are connected by edges that characterize the nature of the causal relations represented, including excitatory (sharp edges), inhibitory (dull edge) and no relation (dotted line). Each edge also has a score that reflects the amount of evidence represented, and symbols that reflect the types of experiments carried out, including upward arrow for Positive Manipulations (that increase the probability of A and look at the impact on B), downward arrow for Negative Manipulations (that decrease the probability of A and look at the impact on B). Non-intervention (positive and negative) experiments simply track how A and B co-vary. Edges representing key hypothetical information mentioned in the paper do not have any weights or experiment symbols. Key edges for the main theses in the paper are highlighted in yellow in the map. This map was derived with a free web app that helps with the process of making research maps (www.researchmaps.org).

We have written a book on this subject with the very modest title of :) “Engineering the next revolution in neuroscience: the new science of experiment planning”. We have also written a Neuron (PDF) and a Learning and Memory (PDF) papers that summarize our ideas on this subject. For a recent Ray Kurzweil's newsletter article on our work click here...