Research-papers

Computational Neuroscience:

1. Indications of nonlinear deterministic and finite-dimensional structures in time series of brain electrical activity: Dependence on recording region and brain state
2. Visual Information Processing: Artificial Intelligence and the Sensorium of Sight
3. Extracting representations of cognition across neuroimaging studies improves brain decoding
4. Brain-computer interface technologies: from signal to action
5. Marr's Approach to Vision
6. Temporal epilepsy seizures monitoring and prediction using cross-correlation and chaos theory
7. Vision: A Computational Investigation into the Human Representation and Processing of Visual Information
8. A general method to generate artificial spike train populations matching recorded neurons
9. Neural synchrony in cortical networks: history, concept and current status
10. Sensitivity of Noisy Neurons to Coincident Inputs
11. Implementation of an Automatic EEG Feature Extraction with Gated Recurrent Neural Network for Emotion Recognition
12. Application of Game Theory to Neuronal Networks
13. The predictive mind: An introduction to Bayesian Brain Theory

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Algorithms:

1. Estimation of distribution algorithms
2. Quasi-Random Initial Population for Genetic Algorithms
3. A multi dynamics algorithm for global optimization
4. Introduction to Stochastic processes
5. Self-Improving Reactive Agents Based On Reinforcement Learning, Planning and Teaching
6. Influence maximization in social networks: Theories, methods and challenges
7. Learning to Discover Social Circles in Ego Networks
8. A Layer-Based Sequential Framework for Scene Generation with GANs
9. Interpolated Experience Replay for Improved Sample Efficiency of Model-Free Deep Reinforcement Learning Algorithms
10. Improving Friends Matching in Social Networks Using Graph Coloring
11. NodeRank: Finding infuential nodes in social networks based on interests
12. Social Network Analysis: WOM Marketing in Rural India
13. A community-based approach to identify the most influential nodes in social networks
14. Detecting influential nodes with topological structure via Graph Neural Network approach in social networks
15. Choosing Optimal Seed Nodes in Competitive Contagion

Others:

1. NANOTECHNOLOGY: ITS APPLICATION AND LIMITATION
2. The swimming neuron
3. The dystrophin–glycoprotein complex in brain development and disease
4. Applications of Game Theory for Cyber Security System: A Survey
5. Opportunities and challenges for machine learning in weather and climate modelling: hard, medium and soft AI
6. Tackling Climate Change with Machine Learning
7. Machine learning and artificial intelligence to aid climate change research and preparedness
8. Application of Game Theory to Neuronal Networks
9. LEARNING TO REINFORCEMENT LEARN
10. Adult neurogenesis acts as a neural regularizer
11. Neurogenesis Deep Learning

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Computational Psychiatry and Neurodegenerative diseases:

1. Computational Psychiatry and Computational Neurology: Seeking for Mechanistic Modeling in Cognitive Impairment and Dementia
2. Artificial Intelligence for Neurological Disorders
3. Under the Hood: Using Computational Psychiatry to Make Psychological Therapies More Mechanism-Focused
4. FROM REINFORCEMENT LEARNING MODELS OF THE BASAL GANGLIA TO THE PATHOPHYSIOLOGY OF PSYCHIATRIC AND NEUROLOGICAL DISORDERS
5. Dynamical systems in computational psychiatry: A toy-model to apprehend the dynamics of psychiatric symptoms
6. Multimodal multitask deep learning model for Alzheimer’s disease progression detection based on time series data
7. Functional network segregation is associated with attenuated tau spreading in Alzheimer’s disease
8. Improved multimodal biomarkers for Alzheimer’s disease and Mild Cognitive Impairment diagnosis - data from ADNI

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Psychology:

1. Research Designs
2. The Brain
3. Conditioning and Learning
4. Differential Effect of Reward and Punishment on Procedural Learning
5. Error-related psychophysiology and negative affect

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Neuromorphic computing:

1. Spiking neural networks, an introduction
2. Opportunities for neuromorphic computing algorithms and applications
3. Brian: a simulator for spiking neural networks in Python
4. Deep Spiking Convolutional Neural Network Trained with Unsupervised Spike Timing Dependent Plasticity
5. Action Potential Initiation in the Hodgkin-Huxley Model
6. Hodgkin-Huxley Models
7. Overview of Spiking Neural Network Learning Approaches and Their Computational Complexities
8. A QUANTITATIVE DESCRIPTION OF MEMBRANE CURRENT AND ITS APPLICATION TO CONDUCTION AND EXCITATION IN NERVE
9. The Hodgkin-Huxley theory of the action potential
10. Spike timing dependent plasticity: a consequence of more fundamental learning rules
11. Spike-Timing-Dependent Plasticity (STDP)
12. Spiking Neural Networks Hardware Implementations and Challenges: A Survey
13. Linear Leaky-Integrate-and-Fire Neuron Model Based Spiking Neural Networks and Its Mapping Relationship to Deep Neural Networks
14. Neuroplasticity
15. Neuromorphic deep spiking neural networks for seizure detection
16. Neuronal plasticity: historical roots and evolution of meaning
17. Spike encoding techniques for IoT time-varying signals benchmarked on a neuromorphic classification task
18. Neural Networks for Modeling Neural Spiking in S1 Cortex
19. A Neurocomputational Theory of How Rule-Guided Behaviors Become Automatic

Deep learning:

1. Dying ReLU and Initialization: Theory and Numerical Examples
2. Deep Neuro-Fuzzy System application trends, challenges, and future perspectives: a systematic survey