23 problems in systems neuroscience

  title={23 problems in systems neuroscience},
  author={Jan Leonard van Hemmen and Terrence J. Sejnowski},
Part I How have brains evolved? 1. Shall we ever understand the fly's brain? 2. Can we understand the action of brain in natural environments? 3. Hemisphere dominance of brain function-which functions are lateralized and why? Part II How is the cerebral cortex organized? 4. What is the function of the thalamus? 5. What is a neuronal map, how does it arise, and what is it good for? 6. What is fed back? Part III How do neurons interact? 7. How Can the Brain be so Fast? 8. What is the Neural Code… 

Towards the Idea of Molecular Brains

It is thought that the discovery of neuron-like r-protein networks in the ribosome may provide the molecular basis for designing future computers with organic processors.

The Brain's concepts: the role of the Sensory-motor system in conceptual knowledge

It is proposed that the sensory-motor system has the right kind of structure to characterise both sensory- motor and more abstract concepts, and it is argued against this position using neuroscientific evidence, results from neural computation, and results about the nature of concepts from cognitive linguistics.

Dynamical neural networks: Modeling low-level vision at short latencies

This work proposes a simple implementation of Sparse Spike Coding using greedy inference mechanisms but also how the system may adapt in a unsupervised fashion and shows simple applications in the field of image processing as a quantitative method to evaluate these different cortical models.

Toward a Theory of Information Processing in Auditory Cortex

This chapter discusses cortical function in the context of a comprehensive, neurally grounded theory of hearing and the various aspects of neural information processing that are needed for adequate explanations of auditory function.

Auditory Cortical Contrast Enhancing by Global Winner-Take-All Inhibitory Interactions

Evidence is presented for the existence of GABAA-mediated inhibition in primary auditory cortex within a circular map of sound periodicity representation in AI, where functionally inhibitory projections of similar effect from any location throughout the whole map could underlie the proposed competitive “winner-take-all” algorithm to support object segregation.

Brain Computation Is Organized via Power-of-Two-Based Permutation Logic

It is shown that this power-of-two-based permutation logic is widely used in cortical and subcortical circuits across animal species and is conserved for the processing of a variety of cognitive modalities including appetitive, emotional and social information.

Why Are Computational Neuroscience and Systems Biology So Separate?

This review reconstructs the history of the two disciplines and shows that this may explain why they grew up apart, and speculation about how the relationship between the two fields may evolve in the near future is speculated.

Nonlinear mixed selectivity supports reliable neural computation

It is shown that the conjunctive coding of multiple stimulus features, commonly known as nonlinear mixed selectivity, may be used by the brain to support reliable information transmission using unreliable neurons, and that NMS requires as little as half the metabolic energy required by pure selectivity to achieve the same level of transmission reliability.



How Can the Brain Be So Fast

The author sought different ways that permits a proper reduction to biophysical approximations of neurons, but it can be extremely delicate numerically how they can be applied to neurons over short time period.

Are Neurons Adapted for Specific Computations? Examples from Temporal Coding in the Auditory System

To make the case that neurons may be adapted for particular tasks, the example of temporal coding cells in the vertebrate auditory system is used because their function is well known and allows us to tie physiological and morphological observations to function.

How Does Our Visual System Achieve Shift and Size Invariance

The question of shift and size invariance in the primate visual system is discussed and a more detailed analysis of computational models is given, including the dynamic routing circuit model and invariant feature networks, such as the neocognitron.

What Is the Neural Code? 143 C. van Vreeswijk

  • What Is the Neural Code? 143 C. van Vreeswijk

Misha Tsodylzs, and Amiram Grinvald 10 What Is the Other 85 Percent of V 1 Doing? 182 Bruno A. Olshausen and David J. Field PART IV What Can Brains Compute? 11

  • Which Computation Runs in Visual Cortical Columns? 2 1 5 Steven W

I l l How Do Neurons Interact?

  • I l l How Do Neurons Interact?