DANA: Distributed numerical and adaptive modelling framework

Rougier, Nicolas P.; Fix, Jérémy

doi:10.3109/0954898x.2012.721573

Cited by 13 publications

(13 citation statements)

References 21 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This model is implemented in Python, and uses the DANA library for neuronal computation ( Rougier and Fix, 2012 ). Description of all the other model parameters is detailed in Table 1.…”

Section: Methodsand Materialsmentioning

confidence: 99%

A VTA GABAergic computational model of dissociated reward prediction error computation in classical conditioning

Kaushik¹,

Naudé²,

Bapi³

et al. 2020

Preprint

View full text Add to dashboard Cite

Classical Conditioning is a fundamental learning mechanism where the Ventral Striatum is generally thought to be the source of inhibition to Ventral Tegmental Area (VTA) Dopamine neurons when a reward is expected. However, recent evidences point to a new candidate in VTA GABA encoding expectation for computing the reward prediction error in the VTA. In this system-level computational model, the VTA GABA signal is hypothesised to be a combination of magnitude and timing computed in the Peduncolopontine and Ventral Striatum respectively. This dissociation enables the model to explain recent results wherein Ventral Striatum lesions affected the temporal expectation of the reward but the magnitude of the reward was intact. This model also exhibits other features in classical conditioning namely, progressively decreasing firing for early rewards closer to the actual reward, twin peaks of VTA dopamine during training and cancellation of US dopamine after training.

show abstract

“…This model is implemented in Python, and uses the DANA library for neuronal computation ( Rougier and Fix, 2012 ). Description of all the other model parameters is detailed in Table 1.…”

Section: Methodsand Materialsmentioning

confidence: 99%

A VTA GABAergic computational model of dissociated reward prediction error computation in classical conditioning

Kaushik¹,

Naudé²,

Bapi³

et al. 2020

Preprint

View full text Add to dashboard Cite

show abstract

“…To this end, we have developed a reduced bio-inspired distributed asynchronous model of the primitive mammal visual system, considering only motion event detection. This computational model is fed with natural image sequences, and is implemented as a large size distributed calculation [5] with thousands of computation units per structure.…”

Section: Methodsmentioning

confidence: 99%

“…The authors would like to thank Nicolas Rougier for his help with DANA [5] in the early development stages. This work is supported by the ANR/CONICYT KEOpS project, the Lorraine Region and the CORTINA associated team.…”

Section: Acknowledgementsmentioning

confidence: 99%

Impact of the Konio pathway in the thalamocortical visual system: a modeling study

2013

View full text Add to dashboard Cite

International audienceIn the early visual system, regarding the detection of a visual event, motion information is pre-processed in the Magnocellular pathway, while it has been shown that the Koniocellular pathway [1] also plays an important role, providing a global analysis about such a kind of information processing. However, the functional interplay between these two parallel pathways remains partially understood. Previous works have attacked this question by studying the signals produced by the corresponding ganglion cells [1] and their elaboration at further steps [2], rather than proposing to model the underlying mechanisms at a mesoscopic level, i.e., focusing on the functional aspects of such dual processing. Neurobiological studies dedicated to the thalamocortical stage of the early visual system provide knowledge on particular characteristics of the system, namely: 1) the variety of cell types in the retina [2], inducing different pathways, 2) the variety of thalamocortical projections through focused vs diffuse efferences to the cortex [3], from core vs matrix (specific vs non-specific) thalamic nuclei, and 3) the variety of kinds of connectivity between thalamic, cortical and collicular areas (i.e., feedforward, feedback, shortcuts, driver and modulator information flows [4]). To figure out the impact of these multi-scale characteristics, we propose here a systemic approach at the structure level. To this end, we have developed a reduced bio-inspired distributed asynchronous model of the primitive mammal visual system, considering only motion event detection. This computational model is fed with natural image sequences, and is implemented as a large size distributed calculation [5] with thousands of computation units per structure. Thanks to the dual analysis integrating local and larger image cues, we test the system for the detection of specific dynamical patterns (which could be interpreted as, e.g., threats or targets). Our simulations aim at showing that these multi-scale interactions help improving the speed and/or quality of such critical tasks, including target selection and tracking. We expect this approach to propose an innovative answer to the interplay issues quoted here, generalizable to other visuo-motor functions. This also provides a platform that could be used as a testbed for new hypotheses. Further information flows to be included could correspond to the Parvocellular pathway (and its related functions). Other structures such as the pulvinar, or higher cortical areas, would also allow us to explore even more developed mechanisms and behaviors [3,6]

show abstract

“…Our model uses the DANA library for neuronal representation and computation [28]. All the code for the model and parameters are open-source and available online at https://github.com/carreremax/basal-ganglia-ne.…”

Section: Our Modelmentioning

confidence: 99%

Modeling the sensory roles of noradrenaline in action selection

Carrere

Alexandre

2016

2016 Joint IEEE International Conference on Development and Learning and Epigenetic Robotics (ICDL-EpiRob)

View full text Add to dashboard Cite

Noradrenaline participates in the neuromodulation of brain activity to modify the trade-off between exploration and exploitation when sensory contingencies have changed. Accordingly, attentional models of noradrenaline acting on sensory representations have been proposed. In this paper, we explore another possible action of this neuromodulator in the decision making process and report simulation results that illustrate that its role is concerned with different aspects of sensory processing. This is made possible by the extension of a classical model of action selection, to render it able to detect and to adapt to sudden changes in sensory contingencies, which is a major characteristic of autonomous learning.

show abstract

DANA: Distributed numerical and adaptive modelling framework

Cited by 13 publications

References 21 publications

A VTA GABAergic computational model of dissociated reward prediction error computation in classical conditioning

A VTA GABAergic computational model of dissociated reward prediction error computation in classical conditioning

Impact of the Konio pathway in the thalamocortical visual system: a modeling study

Modeling the sensory roles of noradrenaline in action selection

Contact Info

Product

Resources

About