As we should expect, fMRI shows many local regions of the brain involved in specific cognitive activities, such as recognizing a face or understanding language. Less expected is the complementary discovery of a constant pattern of frontal and parietal lobe activity associated with many different kinds of cognitive demand. This same “multiple-demand” or MD pattern is seen in tasks tapping stimulus discrimination, working and episodic memory, response inhibition, language, problem-solving, arithmetic and much more (see here). The MD network, we propose, constructs attentional control structures for complex behaviour of all kinds.

With fMRI, the MD network can be precisely defined in the brains of individual people. Often, MD regions are immediately adjacent to regions with quite different functional properties, e.g. specific involvement in language. With identification of specific MD regions in individual brains, we aim for detailed investigation of their functional properties and contributions to attentional control.

References:
Duncan, 2010
Fedorenko et al.,2012

Once MD regions are defined, their physiological properties can be examined using a range of complementary methods. With fMRI, for example, detailed representations of task events can be studied using multivoxel pattern analysis or MVPA (Kriegeskorte). Our results show broad coding of many different kinds of task information, including relevant stimuli, responses and rules. In our group at the University of Oxford, neurophysiological recordings in behaving monkeys allow MD activity to be examined at the level of activity in single cells and cell populations. In lateral frontal cortex, for example, neurons show high speed adaptation to code the specific information and events of current behaviour; explaining why, in fMRI, activity in the same regions is seen for many different kinds of task. Collaborations with clinical groups in several institutions worldwide are allowing us to conduct similar studies in human patients with implanted brain electrodes. With these methods we track how MD regions construct the contents of an attentional episode, and track neural dynamics as the pattern of activity for one step of a task completes and makes way for the next.

The components of the MD system are anatomically distinct, yet in fMRI, their activity is largely similar. Using a range of methods, we are asking how different MD regions interact in behavioural control. With fMRI, for example, we are examining the common proposal of a processing hierarchy in prefrontal cortex, with most anterior regions involved in the highest levels of control.

References:
Woolgar, 2011, J Neurosci
Sigala, 2008

Well-known tests of “fluid intelligence” – usually involving novel problem-solving – are of interest for their broad ability to predict success in many kinds of laboratory and real-world tasks. In fMRI, fluid intelligence tests show strong activity in the MD system, and in neurological cases, we find that impaired fluid intelligence is predicted by MD lesions. These tests, we propose, measure a fundamental aspect of MD activity, solving complex problems through division into simpler, more tractable episodes.

To develop this hypothesis, we are examining a bizarre form of error termed goal neglect. In goal neglect, a person knows and can describe task rules, yet these rules have no apparent influence on behaviour. Extreme cases are well known from the literature on frontal lobe damage, but when tasks are novel and complex, neglect is seen also in the normal population. Importantly, it is linked closely to fluid intelligence, and in behavioural experiments we are linking neglect to attentional control.

Fluid intelligence declines strongly in old age. Using MRI, we are asking how cognitive decline links to changed structure and function within and outside the MD system (camCAM, Henson).

References:
Duncan et al., 2008
Woolgar 2010

Many clinical tests are used to measure executive control deficits in frontal lobe patients. Because fluid intelligence is correlated with all kinds of test, and because it is impaired after MD lesions, we are asking how far different clinical deficits are explained by fluid intelligence loss.

The results show an intriguing picture. For some common tests, such as Wisconsin Card Sorting and Trail Making, deficits in frontal lobe patients are entirely explained by fluid intelligence. Since much of the frontal lobe lies outside the MD system, however, we should not expect this for all tests. Confirming this prediction, some aspects of executive control (e.g. social cognition, complex multi-tasking) show deficits separate from fluid intelligence. In some cases, the evidence suggests link to damage outside the MD system, especially the most anterior parts of the frontal lobe.

In a wide range of neurological and psychiatric conditions, impairments in attentional control cripple return to everyday life. Their assessment, however, is notoriously uncertain. Our methods suggest a new approach to defining distinct aspects of clinical deficit, and with Tom Manly, we are investigating their utility in patient assessment and management.

References:
Roca at el 2010

In several new lines of work, we are examining the potential for training to overcome attentional limitations. A variety of attentional impairments follow damage to the brain, including both lateralized and global deficits. Using sophisticated cognitive assessment, we are searching for clinical improvements through training attentional capacity and control (Manly, Astle).

More broadly, low fluid intelligence impacts achievements in many aspects of daily life. To address such difficulties, we are exploring methods for improved division of tasks into simple, manageable parts. As this work develops, we shall search for applications in a range of settings, including neurological conditions, healthy aging and cognitive development (Gathercole).

References:
Duncan and Manly, 2012

John Duncan: Programme leader

Andrew Bell: Senior investigator scientist
Apoorva Bhandari: Research student
Francesca Biondo: Research assistant
Christiane Brenner: Visiting student
Ben Crittenden: Research student
Yaara Erez: Postdoctoral fellow
Miki Kadohisa: Investigator scientist
Makoto Kusunoki: Senior investigator scientist
Diana Kyriazis: Research assistant
Danny Mitchell: Investigator scientist
Marieke Mur: Postdoctoral fellow
Polly Peers: Visiting scientist