I am a postdoctoral researcher with Walter Senn at the University of Bern. We work on computational neuroscience. In broad terms we want to understand the neural basis of learning and memory using computer models and mathematical tools. We try to figure out how neuronal circuits adapt through synaptic plasticity and how this might explain our brain's ability to learn.

We have been working with Yoshua Bengio (U Montreal) and his group on these topics.

I have also been collaborating with Mark van Rossum (U Edinburgh) on synaptic plasticity rules and memory storage in neural networks.

From 2010 to 2015 I worked at GAIPS (U Lisboa), where I was a PhD student with Andreas Wichert, and later a research fellow with Francisco C Santos and Ana Paiva.


Cortical backprop
Dendritic error backpropagation in deep cortical microcircuits (2017).
With Rui P. Costa (U Bern & Oxford), Yoshua Bengio (U Montreal) and Walter Senn (U Bern). arXiv:1801.00062
[ abstract and pdf ]


Bengio Y, Scellier B, Bilaniuk O, Sacramento J, Senn W (2016). Feedforward Initialization for fast inference of deep generative networks is biologically plausible.
[ abstract and pdf ]
Senn W, Sacramento J (2015). Backward reasoning the formation rules.
Nature Neuroscience 18(12):1705-1706. News and Views on Lim et al. (2015).
[ abstract | pdf ]
Sacramento J, Wichert A, van Rossum MCW (2015). Energy efficient sparse connectivity from imbalanced synaptic plasticity rules.
PLOS Computational Biology 11(6):e1004265.
[ abstract and pdf ]
Rendeiro D, Sacramento J, Wichert A (2014). Taxonomical associative memory.
Cognitive Computation 6(1):45-65.
[ abstract | pdf ]
Sacramento J, Wichert A (2012). Binary Willshaw learning yields high synaptic capacity for long-term familiarity memory.
Biological Cybernetics, 106(2):123-133.
[ abstract | pdf ]
Sacramento J, Burnay F, Wichert A (2012). Regarding the temporal requirements of a hierarchical Willshaw network.
Neural Networks, 25:84-93.
[ abstract | pdf ]
Sacramento J, Wichert A (2011). Tree-like hierarchical associative memory structures.
Neural Networks, 24(2):143-147.
[ abstract | pdf ]
Conference presentations
Sacramento J, Bengio Y, Senn W (2017). Error backpropagation in cortical circuits.
5th Annual Humain Brain Project Summit, 17-20 October 2017, Glasgow, UK.
Selected for a young researcher talk.
Sacramento J, Senn W (2016). Learning based on error representations in apical dendrites of L5 pyramidal neurons.
Champalimaud Neuroscience Symposium, Lisbon, Portugal.
Selected for a talk.
Sacramento J, Senn W (2016). Dendritic functions in learning.
DENDRITES 2016, Heraklion, Crete.
Selected young researcher talk.
Sacramento J, Senn W (2016). Bayesian multisensory integration by dendrites.
COSYNE 2016, Salt Lake City, Utah, USA.
Selected for a talk.
Sacramento J, Wichert A, Santos FC, van Rossum MCW (2015). One-class learning in networks.
OCCAM 2015, Osnabrück, Germany.
Poster presentation.
Sacramento J, van Rossum MCW (2014). Imbalanced synaptic plasticity rules lead to energy efficient connectivity.
Neuroscience 2014, SfN's 44th annual meeting, Washington DC, USA.
Poster presentation.
[ abstract ]

Past invited talks

Learning with imbalanced plasticity and the information vs. efficiency dilemma (November 2013).
Invited talk, Institute for Adaptive and Neural Computation, School of Informatics, University of Edinburgh, UK.
Synaptic capacities for recognition memory (April 2012).
Invited talk, Institute for Adaptive and Neural Computation, School of Informatics, University of Edinburgh, UK.


In the past I served as a teaching assistant at the Department of Computer Science and Engineering of IST, where I lectured practical classes on computer programming and basic algorithms.