Our edited books
Sensory adaptation
Adibi M, Zoccolan D & Clifford CWG eds.
Lausanne: Frontiers Media (2021)
What can simple brains teach us about how vision works.
Zoccolan D, Cox DD, Benucci A, Reid RC, eds
Lausanne: Frontiers Media. doi: 10.3389/978-2-88919-678-4 (2015)
Selected articles
Truly dorsal: nonlinear integration of motion signals is required to account for the responses of pattern cells in rat visual cortex
Matteucci G, Bellacosa Marotti R, Zattera B, Zoccolan D (2023)
bioRxiv: doi:
Prune and distill: similar reformatting of image information along rat visual cortex and deep neural networks
Muratore P, Tafazoli S, Piasini E, Laio A, Zoccolan D (2022)
Adv. Neural Info. Processing Systems (NeurIPS): 35
Editorial: Sensory Adaptation
Adibi M, Zoccolan D & Clifford CWG (2021)
Front. Syst. Neurosci.: 15: 809000
Rat sensitivity to multipoint statistics is predicted by efficient coding of natural scenes
Caramellino R*, Piasini E*, Buccellato A, Carboncino A, Balasubramanian V & Zoccolan D (2021)
eLife: 2021; 10:e72081
Rats spontaneously perceive global motion direction of drifting plaids
Matteucci G*, Zattera B*, Bellacosa Marotti R, & Zoccolan D (2021)
Plos Comp. Biol.: 17(9): e1009415
Temporal stability of stimulus representation increases along rodent visual cortical hierarchies
Piasini E*, Soltuzu L*, Muratore P, Caramellino R, Vinken K, Op De Beeck H, Balasubramanian V & Zoccolan D (2021)
Nature Comm.: 12, 4448
A machine learning framework to optimize optic nerve electrical stimulation for vision restoration
Romeni S, Zoccolan D & Micera S (2021)
Patterns: 2(7), 100286
A general-purpose mechanism of visual feature association in visual word identification and beyond.
Vidal Y, Viviani E, Zoccolan D & Crepaldi D (2021)
Curr. Biol.: 31(6), 1261-1267
A template-matching algorithm for laminar identification of cortical recording sites from evoked response potentials.
Matteucci G*, Riggi M* & Zoccolan D (2020)
J. Neurophys.: 124, 102-114
Unsupervised experience with temporal continuity of the visual environment is causally involved in the development of V1 complex cells.
Matteucci G & Zoccolan D (2020)
Science Adv.: 6(22), eaba3742
A passive, camera-based head-tracking system for real-time, three-dimensional estimation of head position and orientation in rodents.
Vanzella W*, Grion N*, Bertolini D*, Perissinotto A, Gigante M & Zoccolan D (2019)
J. Neurophys. : 122, 2220-2242
Nonlinear processing of shape information in rat lateral extrastriate cortex.
Matteucci G, Bellacosa Marotti R, Riggi M, Rosselli FB & Zoccolan D (2019)
J. Neurosci. : 39, 1649-1670
Characterization of visual object representations in rat primary visual cortex.
Vascon S*, Parin Y*, Annavini E*, D’Andola M, Zoccolan D & Pelillo M (2019)
ECCV 2018, Lect. Notes Comp. Science: 11131, 577-586
Intrinsic dimension of data representations in deep neural networks.
Ansuini A, Laio A, Macke J & Zoccolan D (2019)
Adv. Neural Info. Processing Systems (NeurIPS): 32
Accuracy of rats in discriminating visual objects is explained by the complexity of their perceptual strategy.
Djurdjevic V*, Ansuini A*, Bertolini D, Macke JH & Zoccolan D (2018)
Curr. Biol. : 28(7), 1005-1015
Supralinear and supramodal integration of visual and tactile signals in rats: psychophysics and neuronal mechanisms.
Nikbakht N, Tafreshiha A, Zoccolan D & Diamond ME (2018)
Neuron : 97, 626-639
Methodological approaches to the behavioral investigation of visual perception in rodents.
Zoccolan D & Di Filippo A (2018)
Handbook of object novelty recognition.: Volume 27, 2018, Pages 69-101
Emergence of transformation-tolerant representations of visual objects in rat lateral extrastriate cortex.
Tafazoli S*, Safaai H*, De Franceschi G, Rosselli FB, Vanzella W, Riggi M, Buffolo F, Panzeri S & Zoccolan D (2017)
eLife: 6:e22794
Editorial: What can simple brains teach us about how vision works.
Zoccolan D, Cox DD & Benucci A (2015)
Front. Neural Circuits: doi: 10.3389/fncir.2015.00051
Invariant visual object recognition and shape processing in rats.
Zoccolan D (2015)
Behav. Brain. Res. : 285, 10-33
Object similarity affects the perceptual strategy underlying invariant visual object recognition in rats.
Rosselli FB*, Alemi A*, Ansuini A & Zoccolan D (2015)
Front. Neural Circuits : 9(10). doi: 10.3389/fncir.2015.00010
Shape similarity, better than semantic membership, accounts for the structure of visual object representations in a population of monkey inferotemporal neurons.
Baldassi C*, Alemi-Neissi A*, Pagan M*, DiCarlo JJ, Zecchina R & Zoccolan D (2013)
PLoS Comput. Biol.: 9(8): e1003167
Multifeatural shape processing in rats engaged in invariant visual object recognition.
Alemi-Neissi A*, Rosselli BF* & Zoccolan D (2013)
J. Neurosci. : 33, 5939-5956
How does the brain solve visual object recognition?
DiCarlo JJ, Zoccolan D & Rust NC (2012)
Neuron : 73, 415-434
Transformation-tolerant object recognition in rats revealed by visual priming.
Tafazoli S*, Di Filippo A* & Zoccolan D (2012)
J. Neurosci. : 32, 21-34
A self-calibrating, camera-based eye tracker for the recording of rodent eye movement.
Zoccolan D, Graham JB & Cox DD (2010)
Front. Neurosci. : 4:193
What response properties do individual neurons need to underlie object recognition in clutter?
Li N, Cox DD, Zoccolan D & DiCarlo JJ (2009)
J. Neurophys. : 102, 360-376
A rodent model for the study of invariant visual object recognition.
Zoccolan D*, Oertelt N*, DiCarlo JJ & Cox DD (2009)
Proc. Natl. Acad. Sci. USA : 106, 8748-53
Trade-off between object selectivity and tolerance in monkey inferotemporal cortex.
Zoccolan D, Kouh M, Poggio T & DiCarlo JJ (2007)
J. Neurosci. : 27, 12292-12307
Multiple object response normalization in monkey inferotemporal cortex.
Zoccolan D*, Cox DD* & DiCarlo JJ (2005)
J. Neurosci. : 25, 8150-64