Table of contents
- Computational Neuroscience on Coursera, recommended, Beginner difficulty
- The Fundamentals of Neuroscience on Harvard & edX, Neuroscience intro, has no prerequisities but Biology and Chemistry can be helpful
- Introduction to Neuroscience on MIT OCW, emphasis on structure and function of human brain, text based (no video)
- Medical Neuroscience on Coursera, Advanced difficulty
- Neuroscience: Exploring the Brain [$] (4th Edition), Mark F. Bear, Barry W. Connors, Michael A. Paradiso, last updated 2015
Overview of memory model with likely future changes:
- Protein synthesis possibly plays a role
- The role of protein synthesis in memory consolidation: Progress amid decades of debate, scientific paper from 2008
- Protein synthesis is associated with high-speed dynamics and broad-band stability of functional hubs in the brain, scientific paper from 2017
- Memory formation possibly happens due to engram competition
- Competition between engrams influences fear memory formation and recall, scientific paper from 2016
"Does human brain work like a computer or not?" has a somewhat complicated answer. And with certainty, it's not possible to answer it with current knowledge. It's also good to mention that Artificial Neural Networks are inspired by Biological Neural Networks. Therefore they could simulate them, although with current technology it's still very inefficient.
Robert Epstein's post explains, why looking at the brain as a computer is wrong. We recommend to read the following counterarguments from Perengras (followed by Golder's review of both), Shallit and Graziosi.
- Chapter 2-4 of Cognitive Psychology: A Student's Handbook [$] (7th edition), Michael W. Eysenck, Mark T. Keane, last updated 2015
Other useful resources
- Chapter 8 of Cognitive Psychology: A Student's Handbook [$] (7th edition), Michael W. Eysenck, Mark T. Keane, last updated 2015
- Chapter 24-25 of Neuroscience: Exploring the Brain [$] (4th Edition), Mark F. Bear, Barry W. Connors, Michael A. Paradiso, last updated 2015
- Implicit learning and consciousness: A graded, dynamic perspective, Axel Cleeremans, from 2001, followed by Connecting Conscious and Unconscious Processing from 2014
- Theories of Memory and Aging: A Look at the Past and a Glimpse of the Future, Denise C. Park, Sara B. Festini, 2016
Other useful resources
- Atkinson–Shiffrin memory model
- Baddeley's model of working memory
- Mental representation of knowledge, recommended book Computer-Based Diagnostics and Systematic Analysis of Knowledge [$], possible to obtain free sample about Mental representation
- Episodic memory
- Autobiographical memory
- Implicit and explicit processes, scientific paper from 2008, 260+ citations
- Dual process theory
- Artificial grammar learning
- Chapter 17 of Cognitive Psychology: A Student's Handbook [$] (7th edition), Michael W. Eysenck, Mark T. Keane, last updated 2015
- Prefrontal cortex and flexible cognitive control: Rules without symbols, Nicolas P. Rougier, 2005, 300+ citations
Other useful resources
- Prefrontal cortex
- Assessment of executive functions, Raymond C. K. Chan, scientific paper from 2007, 900+ citations
- Problem solving
- Insight
- Decision-making (Judgement)
- Probability judgements
- Bayesian probability
- Framing
- Heuristics
- Chapter 2-5 of Neuroscience: Exploring the Brain [$] (4th Edition), Mark F. Bear, Barry W. Connors, Michael A. Paradiso, last updated 2015
Other useful resources
- Anatomy and histology of a neuron, follow up schematic
- Membrane potential
- Action potential
- Neurotransmission
- Afferent (sensory) neurons
- Neurotransmitter
- Excitatory postsynaptic potential
- Inhibitory postsynaptic potential
- Ionotropic effect
- Metabotropic receptor
- Microcircuits neuroscience to understand pathophysiology, scientific paper from 2017
- Nernst equation
Lebedev and Lutsky (1972) pioneered the concept of modeling the dynamics of neurons by equations with delay. Researchers agree that it is not necessary to introduce delay in explicit form into equations that describe the neuron. In examining the fundamental role of delays in neuron modeling, Hodgkin and Huxley (1939) achieved the effect of delay through the use of a chain of ordinary differential equations. A model always reflects the interpretation of a phenomenon. The neuron is a complex formation, and it is difficult to expect the monotony of representations. Mathematical models of neurons can be divided into two classes: static and dynamic. – Citation (simplified) from The Model of a Single Neuron, Serguey Kashchenko, last updated 2015.
- Chapter 2-5 of Neuroscience: Exploring the Brain [$] (4th Edition), Mark F. Bear, Barry W. Connors, Michael A. Paradiso, last updated 2015
- Chapter 1-2 of Dynamical Systems in Neuroscience: The Geometry of Excitability and Bursting [$], Eugene M. Izhikevich, last updated 2010
- Chapter 6 of Biophysics of Computation: Information Processing in Single Neurons [$], Christof Koch, last updated 2004
Other useful resources
- Ionic conductivity, Fundamental questions relating to ion conduction in disordered solids, doi, Jeppe C Dyre, 2009, 200+ citations
- Leaky Integrate-and-Fire Model, Emin Orhan, 2012 followed by Gerstner's web
- Quadratic Integrate and Fire, Chaotic solutions in the quadratic integrate-and-fire neuron with adaptation, Gang Zheng and Arnaud Tonnelier, 2009, 11 citations
- Hodgkin–Huxley model, 1952, 20k citations, simplified: A brief historical perspective: Hodgkin and Huxley, Christof J Schwiening, 2009, 40+ citations
- Cable theory, Electric current flow in excitable cells, JJB Jack, D Noble, RW Tsien, 1975, 2k citations, followed by Cable theory for dendritic neurons
- Simple Model of Spiking Neurons (Izhikevich's model), pdf
- Perceptron
- Blue Brain Project, creating a digital reconstruction of the brain by reverse-engineering mammalian brain circuitry
Neural coding is a neuroscience-related field concerned with characterizing the relationship between the stimulus and the individual or ensemble neuronal responses and the relationship among the electrical activity of the neurons in the ensemble.
- Principles of Neural Coding [$], Rodrigo Quian Quiroga, Stefano Panzeri, last updated 2013
Other useful resources
- Rate coding, describing that as the intensity of a stimulus increases, the frequency or rate of action potentials ("spike firing") increases
- Spike-count rate, counting the number of spikes that appear during a trial and dividing by the duration of trial
- Neural encoding to decoding
- Temporal coding
- Population coding
- Sparse coding
- Tuning Curves, Neuronal Variability, and Sensory Coding, Daniel A Butts, 2006, 160+ citations
- Small-world brain networks, Danielle Smith Bassett, Ed Bullmore, 2006, 1500+ citations
- On the computational architecture of the neocortex and The role of cortico-cortical loops, D. Mumford, 1991-1992, 800+ citations
Neuroanatomy is the study of the anatomy and stereotyped organization of nervous systems. In contrast to animals with radial symmetry, whose nervous system consists of a distributed network of cells, animals with bilateral symmetry have segregated, defined nervous systems.
- Chapter 2-5 of Neuroscience: Exploring the Brain [$] (4th Edition), Mark F. Bear, Barry W. Connors, Michael A. Paradiso, last updated 2015
Other useful resources
- Cell staining
- Histochemistry
- Genetically encoded markers
- Non-invasive brain imaging (Magnetic resonance imaging)
- Viral-based and Dye-based methods
- Connectomics
- Computational neuroanatomy
- Model systems
- Caenorhabditis elegans connectome
- Network control principles predict neuron function in the Caenorhabditis elegans connectome, Gang Yan et al., 2016
- Drosophila melanogaster connectome → Virtual Fly Brain
- Caenorhabditis elegans connectome
Behavioral Science involves the systematic analysis and investigation of human and animal behavior through the study of the past, controlled and naturalistic observation of the present, and disciplined scientific experimentation.
- Chapter 2 of Mechanisms of Memory [$] (2nd Edition), J. David Sweatt, last updated 2009
- Behavioral Game Design, John Hopson, 2001
Other useful resources
- Behaviorism
- Etology
- Functional analytic psychotherapy
- Imprinting
- Appetitive/consumatory behavior
- Classical conditioning also known as Pavlov's research
- Rescorla–Wagner model
- Stimulus–response model
- Operant conditioning also known as Instrumental conditioning
- Forward conditioning (trace and delay conditioning)
- Fear conditioning
- Eyeblink conditioning
- Match-to-sample task
- Chapter 23-25 of Neuroscience: Exploring the Brain [$] (4th Edition), Mark F. Bear, Barry W. Connors, Michael A. Paradiso, last updated 2015
- The molecular biology of memory storage: a dialogue between genes and synapses, Eric R. Kandel, 2001, 3000+ citations
- Molecular mechanisms of fear learning and memory, Joshua P. Johansen, 2011, 600+ citations
- Behavioural neuroscience: The circuit of fear, Pankaj Sah, R. Frederick Westbrook, 2008, 60 citations
Other useful resources
- Chapter 9-10 of Neuroscience: Exploring the Brain [$] (4th Edition), Mark F. Bear, Barry W. Connors, Michael A. Paradiso, last updated 2015
- Chapter 3 of Computational Maps in the Visual Cortex [$] (1st Edition), Risto Miikkulainen, James A. Bednar, Yoonsuck Choe, last updated 2010
- What the Frog's Eye Tells the Frog's Brain (doi), Jerome Lettvin et al., 1959, 2300+ citations
Other useful resources
- Retina
- Lateral geniculate nucleus
- Primary visual cortex (V1)
- Descriptive Models of Receptive Fields
- Gabor filter
- Learning in primary visual cortex
- Effects of perceptual learning on primary visual cortex activity in humans, Gilles Pourtois et al., 2007, 120 citations+
- RF-LISSOM Model, simplified version
- Chapter 10 of Neuroscience: Exploring the Brain [$] (4th Edition), Mark F. Bear, Barry W. Connors, Michael A. Paradiso, last updated 2015
Other useful resources
- Secondary visual cortex (V2), prestriate cortex
- Visual area V4 or Colour centre
- Middle temporal gyrus
- Fusiform face area
- Inferior temporal gyrus
- Posterior parietal cortex
- Two-streams hypothesis
- Separate visual pathways for perception and action, Melvyn Goodale, David Milner, 1992, 2500+ citations
- Working memory in the occipital cortex
- Stimulating occipital cortex enhances visual working memory consolidation, Tal Makovski, 2014, 5+ citations
- Binding problem
- Hierarchical models of object recognition in cortex (doi), Maximilian Riesenhuber and Tomaso Poggio, 1999, 2800+ citations
Low-level motor control is the process by which humans and animals use their brain/cognition to activate and coordinate the muscles and limbs involved in the performance of a motor skill. Fundamentally, it is the integration of sensory information, both about the world and the current state of the body, to determine the appropriate set of muscle forces and joint activations to generate some desired movement or action. This process requires cooperative interaction between the central nervous system and the musculoskeletal system and is thus a problem of information processing, coordination, mechanics, physics, and cognition. Successful motor control is crucial to interacting with the world, not only determining action capabilities but regulating balance and stability as well. – Citation from Motor Control
- Chapter 12-14 of Neuroscience: Exploring the Brain [$] (4th Edition), Mark F. Bear, Barry W. Connors, Michael A. Paradiso, last updated 2015
- From swimming to walking with a salamander robot driven by a spinal cord model, Ijspeert AJ et al., 2007, 700+ citations
- Evidence for fast, low-level motor resonance to action observation: An MEG study, Hein T. van Schie, 2008, 30+ citations
Other useful resources
- Majority of human fingers and toes are replaceable and theoretically redundant. From 5 toes per a leg, Homo Sapiens would be able to move without all of them, although toes play a role in the effectivity of movement. Speaking about fingers, three are necessary for object manipulation if at least one is in the opposition.
- Organization of the motor system
- Reflexes
- Central pattern generators
- Motor program
- The oculomotor system
- Saccades, quick, simultaneous movement of both eyes between two or more phases of fixation in the same direction
- Hexapod robots, biologically inspired by Hexapoda locomotion (movement of insects with six legs)
- Lamprey robots, based on the model of the lamprey spiral cord
- Lamprey robot from the Biorob Lab of Auke Ispeert at EPFL (YouTube video)
- Wake structures behind a swimming robotic lamprey with a passively flexible tail, Megan C. Leftwich et al., 2012, 40+ citations
- Chapter 13-14 of Neuroscience: Exploring the Brain [$] (4th Edition), Mark F. Bear, Barry W. Connors, Michael A. Paradiso, last updated 2015
- Vision. A Computational Investigation into the Human Representation and Processing of Visual Information [$], David Marr, last updated 2010
Other useful resources
- Proprioception
- Motor cortex
- Premotor cortex
- Supplementary motor area
- Cerebellum
- Basal ganglia
- On the role of the hippocampus in learning and memory in the rat, Leonard E. Jarrard, 1993, 1000+ citations
Spatial cognition is a branch of cognitive psychology that studies how people or animals acquire and use knowledge about their environment to determine where they are.
- Part 1 in the book The Neurobiology of Spatial Behaviour [$], K. J. Jeffery, last updated 2003
Other useful resources
- Subjective vs. objective space (simplified version)
- Place cell
- Grid cell
- Head direction cells
- Different types of mazes
- The Classic maze
- The T-maze and The Multiple T-maze
- The Y-maze
- The Radial Arm Maze
- The Morris Water Maze
- Episodic-like memory
- Handbook of Spatial Cognition [$] (1st Edition), David Waller, last updated 2012
- Part 1, Chapter 7: Article Comparative approaches to human navigation [$], Elizabeth S. Spelke, 30+ citations, in the book The Neurobiology of Spatial Behaviour [$], K. J. Jeffery, last updated 2003
Other useful resources
- Chapter 24-25 of Neuroscience: Exploring the Brain [$] (4th Edition), Mark F. Bear, Barry W. Connors, Michael A. Paradiso, last updated 2015
- The Hippocampus Book [$] (1st Edition), Per Andersen, Richard Morris, David Amaral, Tim Bliss, John O'Keefe, last updated 2006
- Microstructure of a spatial map in the entorhinal cortex, Torkel Hafting, Marianne Fyhn, Sturla Molden, May-Britt Moser & Edvard I. Moser, 2005, 2100+ citations
- Path integration and the neural basis of the ‘Cognitive Map.’, Bruce L. Mcnaughton, 2006, 1100+ citations
- A spin glass model of path integration in rat medial entorhinal cortex, Mark C. Fuhs and David S. Touretzky, 2006, 400+ citations
- Catastrophic Forgetting in Connectionist Networks, Robert M French, 2006, 140+ citations
- A unified model of spatial and episodic memory, Edmund T. Rolls, Simon M. Stringer and Thomas P. Trappenberg, 2002, 90+ citations
Other useful resources
- Hippocampus anatomy
- Episodic Memory Models
- Catastrophic interference
- Recursive Dual-Net: A New Universal Network for Supercomputers of the Next Generation, Yamin Li, Shietung Peng, Wanming Chu, 2009, 15+ citations
- Memory consolidation
- Hippocampal pointers
- Head direction cells models
- Place cell models
- Grid cell models
Source: Informatics and Cognitive Sciences syllabus inspired the structure of headlines in this text.