Integrative neuroscience

Integrative neuroscience brings together biological, psychological and clinical models of the human brain within neuroscience. It encourages a freer exchange of information across disciplines and across scales of focus (from the single neuron to whole brain systems). It emphasises how most of the brain's processes are inter-related within andacross scales, as well as across disciplines. It also explores thevirtues of integrating data into quality-controlled databases.

This integrative approach focuses on the brain as an adaptive system. It is concerned with how all the components of the brain are coordinated, and the principles that guide this coordination. A key organizing principle is the importance of our need to avoid potential danger or threat, and maximize safety and reward. In humans, we see this principle operating in regard to responses driven by external information, as well as internally-generated goals. As such, Integrative Neuroscience aims for a unified understanding of brain function across timescales. It draws on information from different measurement sources (including both brain and body measures) to test these unifying principles.

'Integrative Neuroscience' was first described in Gordon (Ed) (2000).

Motivation

Since the ‘decade of the brain’ there has been an explosion of insights into the brain and their application in most areas of medicine. With this explosion, the need for integration of data across studies, modalities and levels of understanding is increasingly recognized. A concrete exemplar of the value of large-scale data sharing has been provided by the Human Brain Project [http://www.nimh.nih.gov/research-funding/scientific-meetings/recurring-meetings/human-brain-project/index.shtml] .

The importance of large-scale integration of brain information for new approaches to medicine has been recognized [http://www.nature.com/neuro/journal/v7/n5/full/nn0504-426.html Nature Neuroscience 2004] . Rather than relying mainly on symptom information, a combination of brain and gene information may ultimately be required for understanding what treatment is best suited to which individual person.

It provides an framework for linking the great diversity of specializations within contemporary neuroscience, including
* Molecular neuroscience — genetic and cellular aspects of brain function
* Neuroanatomy — connections, networks, neurotransmitter systems
* Behavioral neuroscience — the overt consequences of neural activity
* Systems neuroscience — description of sensory and motors systems
* Developmental neuroscience — structural and functional changes during maturation
* Cognitive neuroscience — channels and stages of sensory processing, including memory
* Computational neuroscience — simulation and emulation of neuronal and brain function
* Clinical observations — evidence that can be gleaned from brain dysfunctionThis diversity is inevitable, yet has arguably created a void: neglect of the "primary" role of the nervous system in enabling the animal to survive and prosper. Integrative neuroscience aims to fill this perceived void.

Evolutionary basis

Integrative Neuroscience draws on the important context of our evolutionary history Charles Darwin.

References

Reflist

"Integrative Neuroscience", E. Gordon ed., Harwood (2000) ISBN 90-5823-054-6 (hb) ISBN 90-5823-055-4

"Integrative psychophysiology", Gordon E (2001). International Journal of Psychophysiology, 42, 95 - 108

"Integrative neuroscience: the role of a standardised database",Gordon E Cooper N, Rennie C, Hermens D & Williams (2005). Clinical EEG and Neuroscience, 36, 64 - 75

"Integrating genomics and neuromarkers for the era of brain-related personalized medicine", Gordon E. (2007). Personalized Medicine, 4, 201 - 215