FEDERATION OF EUROPEAN NEUROSCIENCE SOCIETIES
9th FENS Forum of Neuroscience
5-9 July 2014 – Milan, Italy
http://fens2014.neurosciences.asso.fr/
PRESS RELEASE
EMBARGOED UNTIL SUNDAY 6 JULY 2014, 11:15 CEST / 10:15 BST
THE 'OOPS' CENTRE:
COMPUTER MODELS CLARIFY HOW WE RECOGNISE AND PREDICT ERRORS
Scientists at Indiana University in the US are uncovering the brain mechanisms of how people
think ahead. A research team at the University's Department of Psychological and Brain
Sciences have been studying how people evaluate and predict consequences of their future
actions. Speaking today (Sunday 6 July) at the FENS Forum of Neuroscience, Dr Joshua
Brown described computer models which clarify how the brain anticipates, recognises,
evaluates, and avoids mistakes.
Dr Brown's research team study how people recognise unexpected results or errors, and how
they evaluate or predict outcomes. "The brain forms expectations about how things should work
out, and then compares against what actually happens — or fails to happen," said Dr Brown.
"We're building on that notion of simply recognising a mistake. We're examining how the brain
then predicts outcomes of actions we haven't yet taken — and how those brain areas help us
recognise and avoid future mistakes or risky situations," he noted.
Dr Brown and colleagues developed and tested a detailed computer simulation of brain regions
most involved as people unconsciously engage in monitoring and directing their behavioural
actions. The model has confirmed regions active during error recognition and prediction.
From this computer model combined with brain imaging, Dr Brown's team demonstrated that
error evaluation and prediction involves distinct regions of the brain within the medial prefrontal
cortex (mPFC), and especially within the anterior cingulate cortex (ACC). These regions
collectively learn to predict consequences and detect surprising events, both good and bad.
Prior studies showed activity in the ACC as or just after people detect their mistake, leading
some scientists to describe it as part of the brain's 'oops' centre. But the computer model
suggested and confirmed that the ACC also detects and tries to prevent possible future errors,
as an 'early warning system' helping us bypass risky situations. "Simulating varying situations
with these neural models helps us more accurately assess how specific brain areas may learn to
predict outcomes of our actions, and perceive future risk," said Dr Brown.
Their findings also suggest that ACC impairment can impact the brain's ability to accurately
assess upcoming risk. ACC dysfunction is already linked to several mental disorders. Underfunctioning is associated with autism and drug addiction, diminishing one's ability to predict
risks and consequences of actions. Over-activation is linked to obsessive compulsive disorder
(OCD), amplifying one's perception of impending risk. General ACC dysfunction in schizophrenia
involves predicting wrongly, and misunderstanding probability of various consequences.
Advances in computer modelling offer new perspectives for clinical research into these
disorders.
The team's sophisticated computer model was developed using existing data — including
neuroimaging, electrical brain activity recordings, and human behaviour analysis; as well as
internal electrical measurement (single-unit neurophysiology) in monkeys. "Once we developed
the model, we forced it to make predictions about brain activation patterns in various
experiments. Then we tested and confirmed these predictions with actual study data," said Dr
Brown. "Effectively, computer simulation helped us 'predict' the neural mechanisms of human
prediction."
The human data his team used derived from a series of experiments examining neural activity
while predicting and evaluating outcomes. Participants responded to cues on a computer screen,
making either one or two actions, and then predicting their action's result. Researchers
controlled the degree to which the actual outcomes differed from participants' predicted
outcomes.
In recent years, computer modelling has emerged as a valuable tool enhancing understanding
of the brain. "Our research demonstrates that computer models can boost research capability
and generate valuable findings," said Dr Brown. "By assembling disparate data with theory,
we're able to better test and demonstrate the accuracy of those theories." Dr Brown believes
that for conceptualising complex brain mechanisms, computational neural models offer a useful
way forward.
END
Abstract Reference R10209: Cognitive control as a process of prediction and evaluation
Symposia S08: The hedonistic brain: learning, predicting and decision making
Contact
FENS Press Office and all media enquiries:
Elaine Snell, Snell Communications Ltd, London UK (English language)
tel: +44 (0)20 7738 0424 or mobile +44 (0)7973 953 794
email: Elaine@snell-communications.net
Mauro Scanu (Italian language)
tel: +39 333 161 5477
email: press.office@fens.org
Dr Joshua Brown jwmbrown@indiana.edu
NOTES TO EDITORS
The 9th FENS Forum of Neuroscience, the largest basic neuroscience meeting in Europe,
organised by FENS and hosted by the The Società Italiana di Neuroscienze (SINS) (Italian
Society for Neuroscience) will attract an estimated 5,500 international delegates. The
Federation of European Neuroscience Societies (FENS), founded in 1998, aims to advance
research and education in neuroscience, representing neuroscience research in the European
Commission and other granting bodies. FENS represents 42 national and mono-disciplinary
neuroscience societies with close to 23,000 member scientists from 32 European countries.
http://fens2014.neurosciences.asso.fr/
Further Reading (Brown)
Distinct regions of anterior cingulate cortex signal prediction and outcome evaluation. A Jahn,
DE Nee, WH Alexander, JW Brown. NeuroImage. July 2014; Vol. 95: 80-89.
DOI: 10.1016/j.neuroimage.2014.03.050
Medial prefrontal cortex as an action-outcome predictor. WH Alexander, JW Brown. Nature
Neuroscience. 2011; 14(10): 1338-44.
DOI: 10.1016/j.neuron.2012.12.002
The neural basis of predicting the outcomes of imagined actions. A Jahn, DE Nee, JW Brown.
Frontiers in Decision Neuroscience. 2011; 5: 128.
DOI: 10.3389/fnins.2011.00128