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Computational model of axon guidance [article]

Rui Ponte Costa
2015 arXiv   pre-print
Inspired by this thesis Costa et al. [15] proposed a new multi-objective algorithm.  ...  Costa and Macedo proposed a two-dimensional simple multi-agent approach to model axon guidance [16] . This system modeled neurons and glial cells as agents and repulsive/attractive cues.  ... 
arXiv:1508.01537v1 fatcat:j47vv4ek2fbn3ffobbgjtx7gba

Dendritic cortical microcircuits approximate the backpropagation algorithm [article]

João Sacramento, Rui Ponte Costa, Yoshua Bengio, Walter Senn
2018 arXiv   pre-print
., 2016; Scellier and Bengio, 2017; Costa et al., 2017; Guerguiev et al., 2017) , how the brain could implement a backprop-like algorithm remains an open question.  ... 
arXiv:1810.11393v1 fatcat:jetulqdayrdrtnbh4ejzfqtusq

Developmental depression-facilitation shift controls excitation-inhibition balance [article]

David W. Jia, Rui Ponte Costa, Tim P. Vogels
2021 bioRxiv   pre-print
Costa, B. E. P. Mizusaki, P. J. Sjostrom, and M. C. W. van Rossum. Functional consequences of pre-and postsynaptic 392 expression of synaptic plasticity.  ... 
doi:10.1101/2021.02.23.431593 fatcat:3yxzs7r4wndzlktgfax4jz6iyy

Dendritic error backpropagation in deep cortical microcircuits [article]

João Sacramento and Rui Ponte Costa and Yoshua Bengio and Walter Senn
2017 arXiv   pre-print
., 2016; Costa et al., 2017; Guerguiev et al., 2017) , whether the brain implements a backprop-like algorithm remains unclear.  ... 
arXiv:1801.00062v1 fatcat:uruwi5mq3bgxdl7fgeokof55dm

Cerebro-cerebellar networks facilitate learning through feedback decoupling [article]

Ellen Boven, Joseph Pemberton, Paul Chadderton, Richard Apps, Rui Ponte Costa
2022 bioRxiv   pre-print
Behavioural feedback is critical for learning in the cerebral cortex. However, such feedback is often not readily available. How the cerebral cortex learns efficiently despite the sparse nature of feedback remains unclear. Inspired by recent deep learning algorithms, we introduce a systems-level computational model of cerebro-cerebellar interactions. In this model a cerebral recurrent network receives feedback predictions from a cerebellar network, thereby decoupling learning in cerebral
more » ... s from future feedback. When trained in a simple sensorimotor task the model shows faster learning and reduced dysmetria-like behaviours, in line with the widely observed functional impact of the cerebellum. Next, we demonstrate that these results generalise to more complex motor and cognitive tasks. Finally, the model makes several experimentally testable predictions regarding (1) cerebro-cerebellar task-specific representations over learning, (2) task-specific benefits of cerebellar predictions and (3) the differential impact of cerebellar and inferior olive lesions. Overall, our work offers a theoretical framework of cerebro-cerebellar networks as feedback decoupling machines.
doi:10.1101/2022.01.28.477827 fatcat:d6sw7m5igzd2plf4htnefp74qi

Computational roles of plastic probabilistic synapses

Milton Llera-Montero, João Sacramento, Rui Ponte Costa
2019 Current Opinion in Neurobiology  
machinery responsible for stochastic neurotransmitter release (Padamsey and Emptage, 2014; Costa et al., 30 2017b).  ...  However, exactly how much each component 60 is changed can have a dramatic impact on the synaptic transmission statistics (Costa et al., 2015).  ... 
doi:10.1016/j.conb.2018.09.002 pmid:30308457 fatcat:sm3p3anth5f7lkalb5xzlgdgry

Cortico-cerebellar networks as decoupling neural interfaces [article]

Joseph Pemberton and Ellen Boven and Richard Apps and Rui Ponte Costa
2021 arXiv   pre-print
The brain solves the credit assignment problem remarkably well. For credit to be assigned across neural networks they must, in principle, wait for specific neural computations to finish. How the brain deals with this inherent locking problem has remained unclear. Deep learning methods suffer from similar locking constraints both on the forward and feedback phase. Recently, decoupled neural interfaces (DNIs) were introduced as a solution to the forward and feedback locking problems in deep
more » ... ks. Here we propose that a specialised brain region, the cerebellum, helps the cerebral cortex solve similar locking problems akin to DNIs. To demonstrate the potential of this framework we introduce a systems-level model in which a recurrent cortical network receives online temporal feedback predictions from a cerebellar module. We test this cortico-cerebellar recurrent neural network (ccRNN) model on a number of sensorimotor (line and digit drawing) and cognitive tasks (pattern recognition and caption generation) that have been shown to be cerebellar-dependent. In all tasks, we observe that ccRNNs facilitates learning while reducing ataxia-like behaviours, consistent with classical experimental observations. Moreover, our model also explains recent behavioural and neuronal observations while making several testable predictions across multiple levels. Overall, our work offers a novel perspective on the cerebellum as a brain-wide decoupling machine for efficient credit assignment and opens a new avenue between deep learning and neuroscience.
arXiv:2110.11501v2 fatcat:wja2pqn275gnzdhxbeez2tgv4q

Functional consequences of pre- and postsynaptic expression of synaptic plasticity [article]

Rui Ponte Costa, Beatriz E. P. Mizusaki, P. Jesper Sjostrom, Mark C. W. van Rossum
2016 bioRxiv   pre-print
., Costa, R. P., Lalanne, T. & Sjostrom, P. J. Target-504 cell-specific short-term plasticity in local circuits.  ... 
doi:10.1101/075317 fatcat:dbphcghwzncwng5nujyhiwg5si

Cortical microcircuits as gated-recurrent neural networks [article]

Rui Ponte Costa, Yannis M. Assael, Brendan Shillingford, Nando de Freitas, Tim P. Vogels
2018 arXiv   pre-print
Senn et al., 2001; Pfister and Gerstner, 2006; Zenke et al., 2015; Costa et al., 2015 Costa et al., , 2017a at recurrent excitatory synapses.  ...  Slow memory decay in these networks may be controlled through short- (York and van Rossum, 2009; Costa et al., 2013 Costa et al., , 2017a and long-term synaptic plasticity (Abbott and Nelson, 2000;  ... 
arXiv:1711.02448v2 fatcat:2dyvlbg23ncz3nioqcjin73m5i

Pre- and postsynaptically expressed spiking-timing-dependent plasticity contribute differentially to neuronal learning [article]

Beatriz E. P. Mizusaki, Sally S. Y. Li, Rui Ponte Costa, P. Jesper Sjöström
2018 bioRxiv   pre-print
AbstractA plethora of experimental studies have shown that long-term plasticity can be expressed pre- or postsynaptically depending on a range of factors such as developmental stage, synapse type, and activity patterns. The functional consequences of this diversity are unknown. However, in models of neuronal learning, long-term synaptic plasticity is implemented as changes in connective weights. Whereas postsynaptic expression of plasticity predominantly affects synaptic response amplitude,
more » ... ynaptic expression alters both synaptic response amplitude and short-term dynamics. In other words, the consideration of long-term plasticity as a fixed change in amplitude corresponds more closely to post- than to presynaptic expression, which means theoretical outcomes based on this choice of implementation may have a postsynaptic bias. To explore the functional implications of the diversity of expression of long-term synaptic plasticity, we modelled spike-timing-dependent plasticity (STDP) such that it was expressed either pre- or postsynaptically, or both. We tested pair-based standard STDP models and a biologically tuned triplet STDP model, and investigated the outcome in a feed-forward setting, with two different learning schemes: either inputs were triggered at different latencies, or a subset of inputs were temporally correlated. Across different STDP models and learning paradigms, we found that presynaptic changes adjusted the speed of learning, while postsynaptic expression was better at regulating spike timing and frequency. When combining both expression loci, postsynaptic changes amplified the response range, while presynaptic plasticity maintained control over postsynaptic firing rates, potentially providing a form of activity homeostasis. Our findings highlight how the seemingly innocuous choice of implementing synaptic plasticity by direct weight modification may unwittingly introduce a postsynaptic bias in modelling outcomes. We conclude that pre- and postsynaptically expressed plasticity are not interchangeable, but enable complimentary functions.Author summaryDifferences between functional properties of pre- or postsynaptically expressed long-term plasticity have not yet been explored in much detail. In this paper, we used minimalist models of STDP with different expression loci, in search of fundamental functional consequences. Presynaptic expression acts mostly on neurotransmitter release, thereby altering short-term synaptic dynamics, whereas postsynaptic expression affects mainly synaptic gain. We compared cases where plasticity was expressed presynaptically, postsynaptically, or both. We found that postsynaptic plasticity was more effective at changing response times, while both pre- and postsynaptic plasticity were similarly capable of detecting correlated inputs. A model with biologically tuned expression of plasticity also achieved this separation over a range of frequencies without the need of external competitive mechanisms. Postsynaptic spiking frequency was not directly affected by presynaptic plasticity of short-term plasticity alone, however in combination with a postsynaptic component, it helped restrain positive feedback, contributing to activity homeostasis. In conclusion, expression locus may determine distinct coding schemes while also keeping activity within bounds. Our findings highlight the importance of correctly implementing expression of plasticity in modelling, since the locus of expression may affect functional outcomes in simulations.
doi:10.1101/450825 fatcat:tadejgz47zaojampxatkqofvrq

Target-cell-specific short-term plasticity in local circuits

Arne V. Blackman, Therese Abrahamsson, Rui Ponte Costa, Txomin Lalanne, P. Jesper Sjöström
2013 Frontiers in Synaptic Neuroscience  
However, connections from neocortical PCs to BCs tend to short-term depress slightly faster than those between PCs (Costa et al., 2013) .  ...  Revealing subtle differences at connections between excitatory neurons may thus require more refined experimental and theoretical techniques (Costa et al., 2013) .  ... 
doi:10.3389/fnsyn.2013.00011 pmid:24367330 pmcid:PMC3854841 fatcat:kazfmwr4zvbofnhew3uw6bm76i

Unified pre- and postsynaptic long-term plasticity enables reliable and flexible learning

Rui Ponte Costa, Robert C Froemke, P Jesper Sjöström, Mark CW van Rossum
2015 eLife  
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.
more » ... 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.
doi:10.7554/elife.09457 pmid:26308579 pmcid:PMC4584257 fatcat:3pkipgxphreflcuynxfzutsl3u

Synaptic Transmission Optimization Predicts Expression Loci of Long-Term Plasticity

Rui Ponte Costa, Zahid Padamsey, James A. D'Amour, Nigel J. Emptage, Robert C. Froemke, Tim P. Vogels
2017 Neuron  
Please contact Rui Ponte Costa at rui.costa@ with requests and inquiries.  ...  d KEY RESOURCES STAR+METHODS KEY RESOURCES TABLE CONTACT FOR REAGENT AND RESOURCE SHARING As Lead Contact, Rui Ponte Costa is responsible for all reagent and resource requests.  ... 
doi:10.1016/j.neuron.2017.09.021 pmid:28957667 pmcid:PMC5626823 fatcat:jkmy26em5nhbngzgqcuv6fdj4e

15 years of coronary intravascular ultrasound in percutaneous coronary intervention in Portugal

Rui Azevedo Guerreiro, Renato Fernandes, Rui Campante Teles, Pedro Canas da Silva, Hélder Pereira, Rui Cruz Ferreira, Marco Costa, Filipe Seixo, Pedro Farto e Abreu, João Luís Pipa, Luís Bernardes, Francisco Pereira Machado (+15 others)
2020 Revista Portuguesa de Cardiologia (English Edition)  
Coronary intravascular ultrasound (IVUS) is increasingly important in catheterization laboratories due to its positive prognostic impact. This study aims to characterize the use of IVUS in percutaneous coronary intervention (PCI) in Portugal. Methods: A retrospective observational study was performed based on the Portuguese Registry on Interventional Cardiology of the Portuguese Society of Cardiology. The clinical and angiographic profiles of patients who underwent PCI between 2002 and 2016,
more » ... percentage of IVUS use, and the coronary arteries assessed were characterized. Results: A total of 118706 PCIs were included, in which IVUS was used in 2266 (1.9%). Over time, use of IVUS changed from none in 2002 to generally increasing use from 2003 (0.1%) to 2016 (2.4%). The age of patients in whom coronary IVUS was used was similar to that of patients in whom IVUS was not used, but in the former group there were fewer male patients, and a higher prevalence of cardiovascular risk factors (hypertension, hypercholesterolemia and diabetes), previous myocardial infarction, previous PCI, multivessel coronary disease, C-type or bifurcated coronary lesions, and in-stent restenosis. IVUS was used in 54.8% of elective PCIs and in 19.15% of PCIs of the left main coronary artery. Conclusion: Coronary IVUS has been increasingly used in Portugal since 2003. It is used preferentially in elective PCIs, and in patients with higher cardiovascular risk, with more complex coronary lesions and lesions of the left main coronary artery.
doi:10.1016/j.repce.2020.01.002 fatcat:mvy5nbf2sjg2djysteyy2mttcq

Model-Based Inference of Synaptic Transmission

Ola Bykowska, Camille Gontier, Anne-Lene Sax, David W. Jia, Milton Llera Montero, Alex D. Bird, Conor Houghton, Jean-Pascal Pfister, Rui Ponte Costa
2019 Frontiers in Synaptic Neuroscience  
., 2014; Costa et al., 2017; Roelfsema and Holtmaat, 2018; Williams and Holtmaat, 2018; Llera-Montero et al., 2019) .  ...  Full probabilistic inference was done using MCMC sampling following Costa et al. (2013) (see main text for more details).  ... 
doi:10.3389/fnsyn.2019.00021 pmid:31481887 pmcid:PMC6710341 fatcat:gehsdzff7vdctjd7g3cg76fdne
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