Papers

Welcome to the References wiki!

• These are selected papers I am currently reading. It would be updated when I finish reading/give up or find out/replace with new relevant references, hopefully.

1. Predictive coding

• Predictive coding in the visual cortex: a functional interpretation of some extra-classical receptive-field effects
• • an original paper on predictive coding in V1 RFs
• The free-energy principle: a unified brain theory?
• • a more general predictive scheme in brain activity
• The hippocampus as a predictive map
• • one of the newest publication from Deepmind on prediction
• Primary Visual Cortex Represents the Difference Between Past and Present
• • early results in visual cortex with predictive bahavior

2. Cortical structure and circuits

• General Cortical and Special Prefrontal Connections: Principles from Structure to Function
• • anatomy, looking at the structure underlying computation, are extremely powerful and crucial
• Distributed Hierarchical Processing in the Primate Cerebral Cortex
• Whose cortical column would that be?
• A Canonical Microcircuit for Neocortex
• • important hypothesis for canonical microcircuits

3. Visual system

• Local Diversity and Fine-Scale Organization of Receptive Fields in Mouse Visual Cortex
• • an important reference for V1 mapping, dynamics, and local organization
• Highly Selective Receptive Fields in Mouse Visual Cortex
• • important cell typing and RF properties
• Traveling Waves in Visual Cortex
• • how do global effects like traveling waves relate to local computation in columns
• Six principles of visual cortical dynamics
• • reviewing some known principles in visual cortex activities

4. Models

Network models

• Inhibitory Plasticity Balances Excitation and Inhibition in Sensory Pathways and Memory Networks
• • I am currently implementing the results in this paper
• Rich-Club Organization in Effective Connectivity among Cortical Neurons
• • rank of functional connectivity in cortex, which is important to investigate in population coding

Dynamical systems

• Self-Tuned Critical Anti-Hebbian Networks
• • influential theoretical paper that generalizes dynamics of anti-hebbian networks and links to critical dynamics
• The Dynamic Brain: From Spiking Neurons to Neural Masses and Cortical Fields
• • long review on various response models, linking discrete networks and field models
• Is there chaos in the brain? II. Experimental evidence and related models
• • nonlinear dynamic approach in neuroscience
• Synaptic input sequence discrimination on behavioral timescales mediated by reaction-diffusion chemistry in dendrites
• • a link from microscopic biophysics to macroscopic behavior

5. Machine learning

• Why does deep and cheap learning work so well?
• • theoretical paper that verifies ability of deep learning by locality, symmetry, and "flatness" theories
• Deep Predictive Coding Networks for Video Prediction and Unsupervised Learning
• • the only deep learning project that finally includes predictive coding
• Opening the Black Box of Deep Neural Networks via Information
• • fascinating paper that applies information-bottleneck method to machine learning, revealing a noval way to verify representation and phase transition during learning process
• Neuroscience-Inspired Artificial Intelligence
• • current review and opinion from Deepmind

6. Biophysics and systems bio

• Perspectives on theory at the interface of physics and biology
• • Dr. Bialek's review and opinion in biophysics
• Physical limits to magnetogenetics
• • Dr. Meister's debunk for another paper that claims to bioengineer magnetogenetics
• Broken Detailed Balance of Filament Dynamics in Active Networks
• • Application of statistics physics in biomolecule dynamics
• Probabilistic models of individual and collective animal behavior
• • Application of statistics physics in collective behavior

7. Information theory

• Information processing in living systems
• • Dr. Bialek's review and opinion in information theory in biology
• Sparse low-order interaction network underlies a highly correlated and learnable neural population code
• • functional investigation of sparse and weakly correlated population neural codes
• Local information transfer as a spatiotemporal filter for complex systems
• • a nice method to characterise spatiotemporal dynamics via information theory
• A universal tradeoff between power, precision and speed in physical communication
• • optimization/trade-off/physical limit paper, this time considering power consumption

8. Statistic mechanics

• Thermodynamics of information
• • linking information measurements and the physical correspondents is extremely fundamental
• Statistical physics of self-replication
• • origin of life in statistical physics term
• The thermodynamics of prediction
• • prediction in thermodynamics term, Landauer's principle and physical bounds revisited
• Learning in Neural Networks Based on a Generalized Fluctuation Theorem

9. Techs

• Whole-brain calcium imaging with cellular resolution in freely behaving Caenorhabditis elegans
• Advances in light microscopy for neuroscience
• • reviewing recent advances in neural recording through optical methods
• Nanotools for Neuroscience and Brain Activity Mapping
• Physical principles for scalable neural recording
• • a nice paper that estimates physical limits for bioengineering goals, guiding developments and optimization

10. Others

• Selectionist and evolutionary approaches to brain function: a critical appraisal
• • in terms of "neural Darwinism", how can we really compare evolution in species and dynamics in neuroscience
• Evaluating cell reprogramming, differentiation and conversion technologies in neuroscience
• Consciousness as a State of Matter
• Scalar Timing in Memory
• Why do we age?
• • ageing and time perception has long been one of the final frontiers for me
• Bee Foraging in Uncertain Environments Using Predictive Hebbian Learning
• • nothing in neuroscience makes sense except in the light of animal behavior
• Musical rhythm spectra from Bach to Joplin obey a 1/f power law
• • mysterious structure of musics and how they reveal mechanisms of perception are fascinating