For the full list of publications and citations, please visit Mario Dipoppa's google scholar profile.

• Dipoppa M, Nogueira R*, Bugeon S*, Friedman Y, Reddy CB, Harris KD, Ringach DL, Miller KD, Carandini M⁺, Fusi S⁺ (2024), Adaptation shapes the representational geometry in mouse V1 to efficiently encode the environment, bioRxiv, 628035. *contributed equally, ⁺co-senior authors

• Tring E, Moosavi SA, Dipoppa M, Ringach DL (2024), Contrast gain control is a reparameterization of a population response curve, bioRxiv, 605608.

• Tring E, Dipoppa M, Ringach DL (2023), On the contrast response function of adapted neural populations, J. Neurophys., 131: 446–453.

• Tring E, Dipoppa M, Ringach DL (2023), A power law describes the magnitude of adaptation in neural populations of primary visual cortex, Nat. Comm., 14: 8366. 

• Di Santo S, Dipoppa M, Keller AJ, Roth MM, Scanziani M, Miller KD (2022), Unifying model for three forms of contextual modulation including feedback input from higher visual areas, bioRxiv, 493753. 

• Bugeon S, Duffield J, Dipoppa M, Prankerd I, Ritoux A, Nicolotsopoulos D, Orme D, Shinn M, Peng H, Forrest H, Viduolyte A, Reddy CB, Isogai Y, Carandini M, Harris KD (2022), A transcriptomic axis predicts state modulation of cortical interneurons, Nature, 607: 330-338. 

• Schmidt ERE, Zhao HT, Park JM, Dipoppa M*, Monsalve-Mercado MM*, Dahan JB, Rodgers CC, Lejeune A, Hillman EMC, Miller KD, Bruno RM, Polleux F (2021), A human-specific modifier of cortical circuit connectivity and function improves behavioral performance, Nature, 599: 640-644. *contributed equally

• Whiteway MR, Biderman D, Friedman Y, Dipoppa M, Buchanan EK, Wu A, Zhou J, Bonacchi N, Miska NJ, Noel J-P, Rodriguez E, Schartner M, Socha K, Urai AE, Salzman CD, Cunningham J, Paninski L (2021), Partitioning variability in animal behavioral videos using semi-supervised variational autoencoders, PLOS Comput. Bio., 17: e1009439.

• Keller AJ*, Dipoppa M*, Roth MM*, Caudill M*, Ingrosso A, Miller KD, Scanziani M (2020), A disinhibitory circuit for contextual modulation in primary visual cortex, Neuron, 108: 1-13. *co-first authors

• Minni S*, Ji-An L*, Moskovitz T, Lindsay G, Miller KD, Dipoppa M, Yang GR (2019), Understanding the functional and structural differences across excitatory and inhibitory neurons, bioRxiv, 680439. *co-first authors

• Dipoppa M, Ranson A, Krumin M, Pachitariu M, Carandini M, Harris KD (2018), Vision and locomotion shape the interactions between neuron types in mouse visual cortex, Neuron, 98: 602-615.

• Pachitariu M, Stringer C, Dipoppa M, Schröder S,  Rossi LF, Dalgleish H, Carandini M, Harris KD (2017), Suite2p: beyond 10,000 neurons with standard two-photon microscopy, bioRxiv, 061507. 

• Dipoppa M, Szwed M, Gutkin BS (2016), Controlling working memory operations by selective gating: role of oscillations and synchrony, Adv. Cogn. Psychol., 12: 209-232.

• Pérez-Schuster V, Kulkarni A, Nouvian M, Romano SA, Lygdas K, Jouary A, Dipoppa M, Pietri T, Haudrechy M, Candat V, Boulanger-Weill J, Hakim V, Sumbre G (2016), Sustained rhythmic brain activity underlies visual motion perception in zebrafish, Cell Reports, 17: 1098-1112. 

• Dipoppa M and Gutkin BS (2013), Flexible frequency control of cortical oscillations enables computations required for working memory, Proc. Natl. Acad. Sci. USA, 110: 12828-12833. 

• Dipoppa M and Gutkin BS (2013), Correlations in background activity control persistent state stability and allow execution of working memory tasks, Front. Comput. Neurosci. 7. 

• Dipoppa M, Krupa M, Torcini A, Gutkin BS (2012), Splay states in finite pulse-coupled networks of excitable neurons, SIAM J. Appl. Dyn. Syst. 11: 864–894. 

• Deslippe J, Dipoppa M, Prendergast D, Moutinho MV, Capaz RB, Louie SG (2009), Electron-Hole Interaction in Carbon Nanotubes: Novel Screening and Exciton Excitation Spectra, Nano Letters, 9: 1330-1334.