Rui Ponte Costa PhD

Rui P. Costa


Research Interests

Synaptic plasticity is believed to be the main principle underlying learning and memory storage, having a central impact on neural information processing. During my PhD I studied short and long-term plasticity under the supervision of Dr. Mark van Rossum (UoE) and Dr. Per Jesper Sjostrum (UCL, McGill).

Publications:
2015
  Unified pre- and postsynaptic long-term plasticity enables reliable and flexible learning
Costa, RP, Froemke, RC, Sjöström, PJ & Van Rossum, MCW 2015, 'Unified pre- and postsynaptic long-term plasticity enables reliable and flexible learning' eLIFE, vol 4. DOI: 10.7554/eLife.09457

Although it is well known that long-term synaptic plasticity can be expressed both pre- and postsynaptically, the functional consequences of this arrangement have remained elusive. We show that spike-timing-dependent plasticity with both pre- and postsynaptic expression develops receptive fields with reduced variability and improved discriminability compared to postsynaptic plasticity alone. These long-term modifications in receptive field statistics match recent sensory perception experiments. Moreover, learning with this form of plasticity leaves a hidden postsynaptic memory trace that enables fast relearning of previously stored information, providing a cellular substrate for memory savings. Our results reveal essential roles for presynaptic plasticity that are missed when only postsynaptic expression of long-term plasticity is considered, and suggest an experience-dependent distribution of pre- and postsynaptic strength changes.


General Information
Organisations: Edinburgh Neuroscience.
Authors: Costa, Rui P., Froemke, Robert C, Sjöström, Per Jesper & Van Rossum, M C W.
Number of pages: 24
Publication Date: 26 Aug 2015
Publication Information
Category: Article
Journal: eLIFE
Volume: 4
ISSN: 2050-084X
Original Language: English
DOIs: 10.7554/eLife.09457
2013
  Probabilistic inference of synaptic dynamics in neocortical microcircuits
Costa, RP, Sjöström, PJ & Van Rossum, M 2013, 'Probabilistic inference of synaptic dynamics in neocortical microcircuits' 22nd Annual Computational Neuroscience Meeting: CNS 2013, Paris, France, 13/07/13 - 18/07/13, .
Short-term synaptic plasticity (STP) is highly varied across brain area, cortical layer, cell type, and developmental stage (Reyes & Sakmann 1999). This variability is probably not coincidental and since synaptic dynamics shape neural computations, it suggests an important role of STP in neural information processing (Abbott & Regehr 2004). Therefore, an accurate description of STP is a key step towards a comprehensive understanding of neural systems. Many phenomenological STP models have been developed (Markram et al. 1998), but they have typically been fitted to experimental data using least-mean-square methods. With the Tsodyks-Markram model, we find that for typical synaptic dynamics such fitting procedures may give erratic outcomes. A Bayesian formulation based on a Markov Chain Monte Carlo method was introduced as a solution. This formulation provides the posterior distribution over the model parameters given the data statistics. We discovered that standard STP electrophysiology protocols yielded wide distributions over some model parameters. Based on this result we propose experimental protocols to more accurately determine model parameters. Next, the model parameters were inferred using experimental data from three different neocortical excitatory connection types: Pyramidal Cell-Pyramidal Cell (PC-PC), Pyramidal Cell-Basket Cell (PC-BC) and Pyramidal Cell-Martinotti Cell (PC-MC), (see Figure 1). This disclosed connection-specific distributions, which we used to classify synapses. This approach to determining connection-specific synaptic dynamics provides a more comprehensive representation of STP and unveils novel features from existing data.
General Information
Organisations: Institute for Adaptive and Neural Computation .
Authors: Costa, Rui P., Sjöström, Per Jesper & Van Rossum, Mark.
Publication Date: Jul 2013
Publication Information
Category: Poster
Original Language: English
  Probabilistic Inference Reveals Synapse-specific Synaptic Dynamics in Neocortical Microcircuits
Costa, RP, Sjostrom, PJ & van Rossum, MCW 2013, 'Probabilistic Inference Reveals Synapse-specific Synaptic Dynamics in Neocortical Microcircuits' Computational and Systems Neuroscience (Cosyne) 2013, Salt Lake City, Utah, United States, 28/02/13 - 5/03/13, .
Short-term synaptic plasticity is highly diverse and varies with brain area, cortical layer, cell type, and develop-mental stage. Since this form of plasticity shapes neural dynamics, its diversity suggests a specific and essential
role in neural information processing. Therefore, a correct identification of short-term plasticity is an important step towards understanding and modeling neural systems. Accurate phenomenological models have been developed, but they are usually fitted to experimental data using least-mean square methods. We demonstrate that, for typical synaptic dynamics, such fitting gives unreliable results. Instead, we introduce a Bayesian approach based on a Markov Chain Monte Carlo method, which provides the posterior distribution over the parameters of the model. We test the approach on simulated data. First we show that common protocols to measure short-term plasticity protocols yield broad distributions over some model parameters, i.e. with inaccurate estimates. Using this insight, we find a better experimental protocol for inferring the true synaptic parameters and show that our Bayesian formulation provides robust identification of changes in the model parameters. Next, we infer the model
parameters using experimental data from three different neocortical excitatory connection types, revealing novel synapse-specific distributions, while the approach yields more robust clustering results. Our approach to demar-cate synapse-specific synaptic dynamics is an important improvement on the state of the art and reveals novel features from existing data as well as guiding future experimental work.
General Information
Organisations: Institute for Adaptive and Neural Computation .
Authors: Costa, Rui Ponte, Sjostrom, Per Jesper & van Rossum, Mark C. W..
Publication Date: 2013
Publication Information
Category: Poster
Original Language: English
  How to train a neuron
Costa, RP, Watt, AJ & Sjöström, PJ 2013, 'How to train a neuron' eLIFE, vol 2. DOI: 10.7554/eLife.00491
A cellular learning rule known as spike-timing-dependent plasticity can form, reshape and erase the response preferences of visual cortex neurons.
General Information
Organisations: Neuroinformatics DTC.
Authors: Costa, Rui P., Watt, Alanna J & Sjöström, P Jesper.
Number of pages: 3
Publication Date: 22 Jan 2013
Publication Information
Category: Article
Journal: eLIFE
Volume: 2
ISSN: 2050-084X
Original Language: English
DOIs: 10.7554/eLife.00491
  Probabilistic Inference of Short-Term Synaptic Plasticity in Neocortical Microcircuits
Costa, RP, Sjöström, PJ & van Rossum, MCW 2013, 'Probabilistic Inference of Short-Term Synaptic Plasticity in Neocortical Microcircuits' Frontiers in Computational Neuroscience, vol 7, no. 75. DOI: 10.3389/fncom.2013.00075
Short-term synaptic plasticity is highly diverse across brain area, cortical layer, cell type, and developmental stage. Since short-term plasticity shapes neural dynamics, this diversity suggests a specific and essential role in neural information processing. Therefore, a correct characterization of short-term synaptic plasticity is an important step towards understanding and modeling neural systems. Phenomenological models have been developed, but they are usually fitted to experimental data using least-mean-square methods. We demonstrate that, for typical synaptic dynamics, such fitting may give unreliable results. As a solution, we introduce a Bayesian formulation, which yields the posterior distribution over the model parameters given the data. First, we show that common short-term plasticity protocols yield broad distributions over some model parameters. Using our result we propose a experimental protocol to more accurately determine synaptic dynamics parameters. Next, we infer the model parameters using experimental data from three different neocortical excitatory connection types. This reveals connection-specific distributions, which we use to classify synaptic dynamics. Our approach to demarcate connection-specific synaptic dynamics is an important improvement on the state of the art and reveals novel features from existing data.
General Information
Organisations: Institute for Adaptive and Neural Computation .
Authors: Costa, Rui P., Sjöström, P. Jesper & van Rossum, Mark C. W..
Publication Date: 2013
Publication Information
Category: Article
Journal: Frontiers in Computational Neuroscience
Volume: 7
Issue number: 75
ISSN: 1662-5188
Original Language: English
DOIs: 10.3389/fncom.2013.00075
  Target Cell-Specific Short-Term Plasticity in Local Circuits
Blackman, AV, Abrahamsson, T, Costa, RP, Lalanne, T & Sjöström, PJ 2013, 'Target Cell-Specific Short-Term Plasticity in Local Circuits' Frontiers in synaptic neuroscience, vol 5, no. 11. DOI: 10.3389/fnsyn.2013.00011
Short-term plasticity (STP) denotes changes in synaptic strength that last up to tens of seconds. It is generally thought that STP impacts information transfer across synaptic connections and may thereby provide neurons with, for example, the ability to detect input coherence, to maintain stability and to promote synchronization. STP is due to a combination of mechanisms, including vesicle depletion and calcium accumulation in synaptic terminals. Different forms of STP exist, depending on many factors, including synapse type. Recent evidence shows that synapse dependence holds true even for connections that originate from a single presynaptic cell, which implies that postsynaptic target cell type can determine synaptic short-term dynamics. This arrangement is surprising, since STP itself is chiefly due to presynaptic mechanisms. Target-specific synaptic dynamics in addition imply that STP is not a bug resulting from synapses fatiguing when driven too hard, but rather a feature that is selectively implemented in the brain for specific functional purposes. As an example, target-specific STP results in sequential somatic and dendritic inhibition in neocortical and hippocampal excitatory cells during high-frequency firing. Recent studies also show that the Elfn1 gene specifically controls STP at some synapse types. In addition, presynaptic NMDA receptors have been implicated in synapse-specific control of synaptic dynamics during high-frequency activity. We argue that synapse-specific STP deserves considerable further study, both experimentally and theoretically, since its function is not well known. We propose that synapse-specific STP has to be understood in the context of the local circuit, which requires combining different scientific disciplines ranging from molecular biology through electrophysiology to computer modeling.
General Information
Organisations: Neuroinformatics DTC.
Authors: Blackman, Arne V, Abrahamsson, Therese, Costa, Rui P., Lalanne, Txomin & Sjöström, Per Jesper.
Publication Date: 2013
Publication Information
Category: Article
Journal: Frontiers in synaptic neuroscience
Volume: 5
Issue number: 11
ISSN: 1663-3563
Original Language: English
DOIs: 10.3389/fnsyn.2013.00011
2012
  Presynaptic NMDA receptors differentially regulate release probability at neocortical excitatory synapses
Costa, RP, Buchanan, KA, Elgar, D, Blackman, AV, Oyrer, J, Van Rossum, M & Sjöström, PJ 2012, 'Presynaptic NMDA receptors differentially regulate release probability at neocortical excitatory synapses' Society for Neuroscience Annual Meeting 2012, New Orleans, 13/10/12 - 17/10/12, .
Classically, NMDA receptors are postsynaptic coincidence detectors in plasticity, but recent studies suggest that they also exist presynaptically (preNMDARs), where they have been implicated in regulating short-term plasticity. However, precisely how preNMDARs control release is poorly described.
We previously found that, in mouse visual cortex layer 5, preNMDARs control neurotransmitter release at connections from pyramidal cells (PCs) to other PCs, to somatostatin (SOM) interneurons (INs), and to a subset of non-basket-cell parvalbumin (PV) INs, while specifically leaving those to basket cells unaffected. Here, we combine computer modeling and 2-photon imaging to investigate the impact further. We tuned the Tsodyks-Markram short-term plasticity model to 30-Hz EPSP trains at these three excitatory synapses before and after preNMDAR blockade (200 µM D/L-AP5), and found that it consistently reduced baseline release probability (PC: 67±3%, n=7; SOM: 45±2%, n=9; PV: 71±5%, n=9; all: p<0.001). However, AP5 did not affect the time constants of depression (PC: p=0.63; SOM: p=0.38) or facilitation ( PC: p=0.15; SOM: p=0.65; PV: p=0.2), nor the facilitation constant (PC: p=0.15; SOM: p=0.67; PV: p=0.38). Onto PV, however, AP5 did increase the depression time constant (250% ± 10%, n=9; p<0.001). In keeping with reduced release probability, AP5 consistently increased failure rates at PC inputs to the three cell types (PCs: 268%±809% of baseline, n=9; p<0.001; SOM: 238%±715%, n=8; p<0.01; PV: 349%±242%, n=3; p<0.05).
The preNMDAR-mediated increase in baseline release probability may be linked to bouton calcium signals. To test this idea, we 2-photon imaged calcium in PC boutons. Although spike-evoked calcium transients were surprisingly unaffected by AP5 wash-in (100±11%, n=5, p=0.84 vs. controls), 5 of 12 boutons showed significant changes in basal calcium (63±4%, p<0.001), consistent with the model. We thus extended the model to include preNMDAR control of STP. This extension predicted a sigmoidal rate dependence of AP5 blockade -- with an 8.4Hz midpoint -- that we verified experimentally.
Our results suggest that preNMDARs specifically regulate release probability at a subset of synapses from PCs by locally controlling bouton resting calcium levels. PreNMDARs are thus well positioned to control the flow of information in the cortical microcircuit.
General Information
Organisations: Institute for Adaptive and Neural Computation .
Authors: Costa, Rui P., Buchanan, Katherine A., Elgar, Dale, Blackman, Arne V., Oyrer, Julia, Van Rossum, Mark & Sjöström, Per Jesper.
Publication Date: 14 Oct 2012
Publication Information
Category: Poster
Original Language: English
  Target-Specific Expression of Presynaptic NMDA Receptors in Neocortical Microcircuits
Buchanan, KA, Blackman, AV, Moreau, AW, Elgar, D, Costa, RP, Lalanne, T, Tudor Jones, AA, Oyrer, J & Sjostrom, PJ 2012, 'Target-Specific Expression of Presynaptic NMDA Receptors in Neocortical Microcircuits' Neuron, vol 75, no. 3, pp. 451-466. DOI: 10.1016/j.neuron.2012.06.017
Traditionally, NMDA receptors are located postsynaptically; yet, putatively presynaptic NMDA receptors (preNMDARs) have been reported. Although
implicated in controlling synaptic plasticity, their function is not well understood and their expression patterns are debated. We demonstrate that, in layer 5
of developing mouse visual cortex, preNMDARs specifically control synaptic transmission at pyramidal cell inputs to other pyramidal cells and to Martinotti
cells, while leaving those to basket cells unaffected. We also reveal a type of interneuron that mediates ascending inhibition. In agreement with synapse-specific expression, we find preNMDAR-mediated calcium signals in a subset of pyramidal cell terminals. A tuned network model predicts that preNMDARs specifically reroute information flow in local circuits during high-frequency firing, in particular by impacting frequency-dependent disynaptic inhibition mediated by Martinotti cells, a finding that we experimentally verify. We conclude that postsynaptic cell type determines presynaptic terminal molecular identity and that preNMDARs govern information processing in neocortical columns.
General Information
Organisations: Neuroinformatics DTC.
Authors: Buchanan, Katherine A., Blackman, Arne V., Moreau, Alexandre W., Elgar, Dale, Costa, Rui P., Lalanne, Txomin, Tudor Jones, Adam A., Oyrer, Julia & Sjostrom, P.Jesper.
Keywords: (#dtc-s0958979. )
Pages: 451-466
Publication Date: 1 Aug 2012
Publication Information
Category: Article
Journal: Neuron
Volume: 75
Issue number: 3
ISSN: 0896-6273
Original Language: English
DOIs: 10.1016/j.neuron.2012.06.017
2011
  The Impact of Synaptic Dynamics on the Structure of Plastic Networks
Costa, RP, Van Rossum, M & Sjöström, PJ 2011, 'The Impact of Synaptic Dynamics on the Structure of Plastic Networks' Workshop on Learning and Plasticity, Marseille, France, France, 7/11/11 - 11/11/11, .
General Information
Organisations: Institute for Adaptive and Neural Computation .
Authors: Costa, Rui P., Van Rossum, Mark & Sjöström, Per Jesper.
Publication Date: Nov 2011
Publication Information
Category: Poster
Original Language: English
  EPILAB: A MATLAB platform for multi-feature and multi-algorithm seizure prediction
Direito, B, Costa, RP, Feldwisch-Drentrup, H, Valderrama, M, Nikolopoulos, S, Schelter, B, Jachan, M, Teixeira, CA, Aires, L, Timmer, J, Le Van Quyen, M & Dourado, A 2011, EPILAB: A MATLAB platform for multi-feature and multi-algorithm seizure prediction. in I Osorio, HP Zaveri, MG Frei & S Arthurs (eds), Epilepsy: The intersection of neurosciences, mathematics and engineering. 1 edn, Taylor & Francis, pp. 417.
General Information
Organisations: Neuroinformatics DTC.
Authors: Direito, B, Costa, Rui P., Feldwisch-Drentrup, Hinnerk, Valderrama, M, Nikolopoulos, S, Schelter, B, Jachan, M, Teixeira, C A, Aires, Luis, Timmer, Jens, Le Van Quyen, M & Dourado, Antonio.
Number of pages: 428
Pages: 417
Publication Date: 2 May 2011
Publication Information
Category: Chapter
Original Language: English
  One cell to rule them all, and in the dendrites bind them
Costa, RP & Sjöström, PJ 2011, 'One cell to rule them all, and in the dendrites bind them' Frontiers in synaptic neuroscience, vol 3, no. 5. DOI: 10.3389/fnsyn.2011.00005
General Information
Organisations: Neuroinformatics DTC.
Authors: Costa, Rui P. & Sjöström, P. Jesper.
Publication Date: 2011
Publication Information
Category: Article
Journal: Frontiers in synaptic neuroscience
Volume: 3
Issue number: 5
ISSN: 1663-3563
Original Language: English
DOIs: 10.3389/fnsyn.2011.00005
2010
  A computational environment for long-term multi-feature and multi-algorithm seizure prediction
Teixeira, CA, Direito, B, Costa, RP, Valderrama, M, Feldwisch-Drentrup, H, Nikolopoulos, S, Le Van Quyen, M, Schelter, B & Dourado, A 2010, A computational environment for long-term multi-feature and multi-algorithm seizure prediction. in Engineering in Medicine and Biology Society (EMBS), 2010 Annual International Conference of the IEEE . vol. 2010, IEEE Computer Society, pp. 6341-4. DOI: 10.1109/IEMBS.2010.5627637
The daily life of epilepsy patients is constrained by the possibility of occurrence of seizures. Until now, seizures cannot be predicted with sufficient sensitivity and specificity. Most of the seizure prediction studies have been focused on a small number of patients, and frequently assuming unrealistic hypothesis. This paper adopts the view that for an appropriate development of reliable predictors one should consider long-term recordings and several features and algorithms integrated in one software tool. A computational environment, based on Matlab (®), is presented, aiming to be an innovative tool for seizure prediction. It results from the need of a powerful and flexible tool for long-term EEG/ECG analysis by multiple features and algorithms. After being extracted, features can be subjected to several reduction and selection methods, and then used for prediction. The predictions can be conducted based on optimized thresholds or by applying computational intelligence methods. One important aspect is the integrated evaluation of the seizure prediction characteristic of the developed predictors.
General Information
Organisations: Neuroinformatics DTC.
Authors: Teixeira, C A, Direito, B, Costa, Rui P., Valderrama, M, Feldwisch-Drentrup, H, Nikolopoulos, S, Le Van Quyen, M, Schelter, B & Dourado, A.
Keywords: (Algorithms, Electrocardiography, Electroencephalography, Humans, Seizures. )
Number of pages: 4
Pages: 6341-4
Publication Date: 2010
Publication Information
Category: Conference contribution
Original Language: English
DOIs: 10.1109/IEMBS.2010.5627637

Projects:
Short and long-term synaptic plasticity in excitatory and inhibitory neocortical networks (PhD)