Selected publications:
- Li N., Daie K., Svoboda K., Druckmann S. (2016) Robust neuronal dynamics in premotor cortex during motor planning. Nature
- Druckmann, S. and Chklovskii, D. (2012) Neuronal circuits underlying persistent representations despite time varying activity, Current Biology
- Druckmann S. and Chklovskii, D. (2010) Over-complete representations on recurrent neural networks can support persistent percepts, NIPS
Preprints
Daie K, Svoboda K, Druckmann S (2019) Targeted photostimulation uncovers circuit motifs supporting short-term memory, BioRxiv (link to pdf)
Wei Z, Chen, TW, Daie K, Svoboda K, Druckmann S (2019) A comparison of neuronal population dynamics measured with calcium imaging and electrophysiology, BioRxiv (link to pdf)
Daie K, Svoboda K, Druckmann S (2019) Targeted photostimulation uncovers circuit motifs supporting short-term memory, BioRxiv (link to pdf)
Wei Z, Chen, TW, Daie K, Svoboda K, Druckmann S (2019) A comparison of neuronal population dynamics measured with calcium imaging and electrophysiology, BioRxiv (link to pdf)
Full list of publications (chronological)
- Stavisky SD, Willett FR, Wilson GH, Murphy BA, Rezaii P, Avansino DT, Memberg WD, Miller JP, Kirsch RF, Hochberg LR, Ajiboye AB, Druckmann S, Shenoy KV, Henderson JM (2019) Neural ensemble dynamics in dorsal motor cortex during speech in people with paralysis. eLife
- Wan Y, Wei Z, Looger LL, Koyama M, Druckmann S*, Keller PJ* (2019) Single-Cell Reconstruction of Emerging Population Activity in an Entire Developing Circuit. Cell. *Co-senior authors
- Kazemipour A, Novak O, Flickinger D, Marvin JS, Abdelfattah AS, King J, Borden PM, Kim JJ, Al-Abdullatif SH, Deal PE, Miller EW, Schreiter ER, Druckmann S, Svoboda K, Looger LL, Podgorski K. (2019) Kilohertz frame-rate two-photon tomography. Nature Methods
- Wei Z, Inagaki H, Li N, Svoboda K, Druckmann S. (2019) An orderly single-trial organization of population dynamics in premotor cortex predicts behavioral variability. Nature Communications
- Ranganathan GN, Apostolides PF, Harnett MT, Xu NL, Druckmann S, Magee JC. (2018) Active dendritic integration and mixed neocortical network representations during an adaptive sensing behavior. Nature Neuroscience
- Kwon O, Feng L, Druckmann S, Kim J. (2018) Schaffer Collateral Inputs to CA1 Excitatory and Inhibitory Neurons Follow Different Connectivity Rules. J Neuroscience
- Guo ZV, Inagaki HK, Daie K, Druckmann S, Gerfen CR, Svoboda K. (2017) Maintenance of persistent activity in a frontal thalamocortical loop. Nature
- Turner-Evans D, Wegener S, Rouault H, Franconville R, Wolff T, Seelig JD, Druckmann S, Jayaraman V. (2017) Angular velocity integration in a fly heading circuit. eLife
- Kim SS, Rouault H, Druckmann S* , Jayaraman V.* (2017) Ring attractor dynamics in the Drosophila central brain. Science; *:co-corresponding authors
- Li, N., Daie, K., Svoboda, K., Druckmann S. (2016) Robust neuronal dynamics in premotor cortex during motor planning. Nature
- Schulze A, Gomez-Marin A, Rajendran VG, Lott G, Musy M, Ahammad P, Deogade A, Sharpe J, Riedl J, Jarriault D, Trautman ET, Werner C, Venkadesan M, Druckmann S., Jayaraman V, Louis M (2015) Dynamical feature extraction at the sensory periphery guides chemotaxis, eLife
- Rah, J. C., L. Feng, Druckmann S., H. Lee and J. Kim (2015). From a meso- to micro-scale connectome: array tomography and mGRASP. Frontiers in Neuroanatomy
- Druckmann S., Feng L, Lee B, Yook C, Zhao T, Magee JC, Kim J. (2014), Structured synaptic connectivity between hippocampal regions. Neuron
- Yook C., Druckmann S., Kim, J. (2013) Mapping mammalian synaptic connectivity, Cellular and Molecular Life Sciences
- Druckmann, S. and Chklovskii, D. (2012) Neuronal circuits underlying persistent representations despite time varying activity, Current Biology
- Druckmann, S., Hu, T., and Chklovskii, D. (2012) A mechanistic model of early sensory processing based on subtracting sparse representations, NIPS
- Druckmann, S., Hill S., Schuermann F., Markarm H., and Segev, I. (2012) Heirarchical structure of cortical interneuron electrical diversity revealed by automated statistical analysis, Cerebral Cortex
- Druckmann, S., Berger, T.K., Hill S., Schuermann F., Markarm H., and Segev, I. (2011) Effective Stimuli for Faithful Neuron Models, PLoS Computational Biology
- Druckmann, S. and Chklovskii, D. (2010) Over-complete representations on recurrent neural networks can support persistent percepts, NIPS
- Druckmann, S., Berger, T.K., Hill S., Schuermann F., Markarm H., and Segev, I. (2008) Evaluating automated parameter constraining procedures of neuron models by experimental and surrogate data, Biological Cybernetics
- Druckmann, S., Banitt, Y., Gidon, A., Schuermann, F., Markram, H., and Segev, I. (2007) A novel multiple objective optimization framework for constraining conductance-based neuron models by experimental data. Frontiers in Neuroscience
Book chapters
1. Druckmann, S., (2014) Automated Parameter Constraining of Single-Neuron Models, in H. Cuntz, M. Remme, B. Torben-Nielsen (eds.), The Computing Dendrite: From Structure to Function. Springer New York
2. Druckmann S., (2014) Evolutionary Algorithms, in D. Jaeger, R. Jung (eds.) Encyclopedia of Computational Neuroscience. Springer New York
3. Druckmann S., Gidon, A., Segev, I. (2013) Computational Neuroscience: Capturing the Essence, in G. Galizia, Lledo, P. (eds.) Neurosciences-From Molecule to Behavior: a university textbook, Springer Berlin, 671-694