The search for universal laws that help establish a relationship between dynamics and computation is driven by recent expansionist initiatives in biologically inspired computing. A general setting to understand both such dynamics and computation is a driven dynamical system that responds to a temporal input. Surprisingly, we find memory-loss a feature of driven systems to forget their internal states helps provide unambiguous answers to the following fundamental stability questions that have been unanswered for decades: what is necessary and sufficient so that slightly different inputs still lead to mostly similar responses? How does changing the driven system’s parameters affect stability? What is the mathematical definition of the edge-of...
When human psychological performance is viewed in terms of cognitive modules, our species displays r...
In theoretical biology, robustness refers to the ability of a biological system to function properly...
There is a widely accepted hypothesis that the maximum computational ability for a system is achieve...
The brain processes underlying cognitive tasks must be very robust. Disruptions such as the destruct...
Understanding the complex dynamics of the human brain is one of the most exciting challenges in mode...
This book offers a timely overview of theories and methods developed by an authoritative group of re...
Systems that exhibit complex behaviours are often found in a particular dynamical condition, poised ...
Cortical neurons are predominantly excitatory and highly interconnected. In spite of this, the corte...
Does biological computation happen at some sort of edge of chaos , a dynamical regime somewhere bet...
For fixed τn, there is a window of τi values for which oscillations exist. We examine the existence ...
A key challenge for neural modeling is to explain how a continuous stream of multimodal input from a...
In order for computation to emerge spontaneously and become an important factor in the dynamics of a...
The differential equations used to model biological neurons and the chemical kinetics involved in sy...
A diffusively driven instability has been hypothesised as a mechanism to drive spatial self-organisa...
How dynamical systems store and process information is a fundamental question that touches a remarka...
When human psychological performance is viewed in terms of cognitive modules, our species displays r...
In theoretical biology, robustness refers to the ability of a biological system to function properly...
There is a widely accepted hypothesis that the maximum computational ability for a system is achieve...
The brain processes underlying cognitive tasks must be very robust. Disruptions such as the destruct...
Understanding the complex dynamics of the human brain is one of the most exciting challenges in mode...
This book offers a timely overview of theories and methods developed by an authoritative group of re...
Systems that exhibit complex behaviours are often found in a particular dynamical condition, poised ...
Cortical neurons are predominantly excitatory and highly interconnected. In spite of this, the corte...
Does biological computation happen at some sort of edge of chaos , a dynamical regime somewhere bet...
For fixed τn, there is a window of τi values for which oscillations exist. We examine the existence ...
A key challenge for neural modeling is to explain how a continuous stream of multimodal input from a...
In order for computation to emerge spontaneously and become an important factor in the dynamics of a...
The differential equations used to model biological neurons and the chemical kinetics involved in sy...
A diffusively driven instability has been hypothesised as a mechanism to drive spatial self-organisa...
How dynamical systems store and process information is a fundamental question that touches a remarka...
When human psychological performance is viewed in terms of cognitive modules, our species displays r...
In theoretical biology, robustness refers to the ability of a biological system to function properly...
There is a widely accepted hypothesis that the maximum computational ability for a system is achieve...