Search

Transcranial direct current stimulation (tDCS) and transcranial random noise stimulation (tRNS) have been claimed to produce many remarkable enhancements in perception, cognition, learning and numerous clinical conditions. The physiological basis of the claims for tDCS rests on the finding that 1 mA of unilateral anodal stimulation increases cortical excitation and 1 mA of cathodal produces inhibition. Here we show that these classic excitatory and inhibitory effects do not hold for the bilateral stimulation or 2 mA intensity conditions favoured in cognitive enhancement experiments. This is important because many, including some of the most salient claims are based on experiments using 2 mA bilateral stimulation. The claims for tRNS are also based on unilateral stimulation. Here we show that, again the classic excitatory effects of unilateral tRNS do not extend to the bilateral stimulation preferred in enhancement experiments. Further, we show that the effects of unilateral tRNS do not hold when one merely doubles the stimulation duration. We are forced to two conclusions: (i) that even if all the data on TES enhancements are true, the physiological explanations on which the claims are based are at best not established but at worst false, and (ii) that we cannot explain, scientifically at least, how so many experiments can have obtained data consistent with physiological effects that may not exist.

The cognitive deficits associated with Parkinson’s disease vary across individuals and change across time, with implications for prognosis and treatment. Key outstanding challenges are to define the distinct behavioural characteristics of this disorder and develop diagnostic paradigms that can assess these sensitively in individuals. In a previous study, we measured different aspects of attentional control in Parkinson’s disease using an established fMRI switching paradigm. We observed no deficits for the aspects of attention the task was designed to examine; instead those with Parkinson’s disease learnt the operational requirements of the task more slowly. We hypothesized that a subset of people with early-to-mid stage Parkinson’s might be impaired when encoding rules for performing new tasks. Here, we directly test this hypothesis and investigate whether deficits in instruction-based learning represent a characteristic of Parkinson’s Disease. Seventeen participants with Parkinson’s disease (8 male; mean age: 61.2 years), 18 older adults (8 male; mean age: 61.3 years) and 20 younger adults (10 males; mean age: 26.7 years) undertook a simple instruction-based learning paradigm in the MRI scanner. They sorted sequences of coloured shapes according to binary discrimination rules that were updated at two-minute intervals. Unlike common reinforcement learning tasks, the rules were unambiguous, being explicitly presented; consequently, there was no requirement to monitor feedback or estimate contingencies. Despite its simplicity, a third of the Parkinson’s group, but only one older adult, showed marked increases in errors, 4 SD greater than the worst performing young adult. The pattern of errors was consistent, reflecting a tendency to misbind discrimination rules. The misbinding behaviour was coupled with reduced frontal, parietal and anterior caudate activity when rules were being encoded, but not when attention was initially oriented to the instruction slides or when discrimination trials were performed. Concomitantly, Magnetic Resonance Spectroscopy showed reduced gamma-Aminobutyric acid levels within the mid-dorsolateral prefrontal cortices of individuals who made misbinding errors. These results demonstrate, for the first time, that a subset of early-to-mid stage people with Parkinson’s show substantial deficits when binding new task rules in working memory. Given the ubiquity of instruction-based learning, these deficits are likely to impede daily living. They will also confound clinical assessment of other cognitive processes. Future work should determine the value of instruction-based learning as a sensitive early marker of cognitive decline and as a measure of responsiveness to therapy in Parkinson's disease., Parkin et al. show that a subset of people with Parkinson’s misbind binary discrimination rules in working memory during an instruction-based learning task. These errors were coupled with reduced frontal, parietal and anterior caudate activity when rules were being encoded, as well as reduced GABA levels within the mid-dorsolateral prefrontal cortices., Graphical Abstract Graphical Abstract

The development of the use of transcranial magnetic stimulation (TMS) in the study of psychological functions has entered a new phase of sophistication. This is largely due to an increasing physiological knowledge of its effects and to its being used in combination with other experimental techniques. This review presents the current state of our understanding of the mechanisms of TMS in the context of designing and interpreting psychological experiments. We discuss the major conceptual advances in behavioral studies using TMS. There are meaningful physiological and technical achievements to review, as well as a wealth of new perceptual and cognitive experiments. In doing so we summarize the different uses and challenges of TMS in mental chronometry, perception, awareness, learning, and memory.

Menu-based ‘nudges’ hold promise as effective ways to encourage a shift away from ruminant meat and towards more environmentally friendly plant-based options when dining out. One example of a menu-based nudge is including an inferior ‘decoy’ option to existing items on menus. Decoys have been shown to influence decision-making in other domains (e.g. Lichters, Bengart, Sarstedt, & Vogt, 2017), but have yet to be used to promote sustainable food choices. Two online randomized controlled trials tested whether the addition of higher priced ‘decoy’ vegetarian options to menus influenced the number of diners choosing a ‘target’ vegetarian option. Adjusted Generalized Estimating Equations on data from four menu conditions showed no main effect of intervention group in study 1 (decoy absent vs. decoy present; odds ratio (OR) 1.08 (95% Confidence Interval (CI) 0.45 to 2.57). Replicating the trial in study 2 across seven menu conditions and testing a more expensive decoy also showed no main effect of the intervention (decoy absent vs. decoy present; OR 0.68 (95% CI 0.41 to 1.12). Further analyses revealed that our price-based decoy strategy (a £30% price increase) did not significantly influence the numbers who chose the inferior decoy dish, potentially due to the fact that dish choices were purely hypothetical. Further research is now needed to clarify which attributes of a dish (e.g. taste, portion size, signature ingredients etc.) are optimal candidates for use as decoys and testing these in real world choice contexts.

Having investigated the influence of acute physical exhaustion on decision-making in world-class elite athletes in Parkin et al. (2017), here a similar method is applied to subelite athletes. These subelite athletes were enrolled on a Team GB talent development program and were undergoing training for possible Olympic competition in 4-8 years. They differ from elite athletes examined previously according to expertise and age. While considered elite (Swann et al., 2015), the subelite athletes had approximately 8 years fewer sporting experience and were yet to obtain sustained success on the international stage. Additionally, the average age of the subelite sample is 20 years; thus, they are still undergoing the behavioral, cognitive, and neuronal changes that occur during the transition from late adolescence to young adulthood (Blakemore and Robbins, 2012). Previous work has used broad definitions of elite status in sport, and as such overlooked different categories within the spectrum of elite athletes (Swann et al., 2015). Therefore it is important to consider subelite athletes as a discrete point on the developmental trajectory of elite sporting expertise.This work aims to investigate the influence of physical pressure on key indicators of decision-making in subelite athletes. It forms part of a wider project examining decision-making across different stages of the developmental trajectory in elite sport. In doing so, it aims to examine how to apply and develop psychological insights useful to an elite sporting environment.32 subelite athletes (18 males, mean age: 20 years) participated in the study. Performance across three categories of decision-making was assessed under conditions of low and high physical pressure. Decision-making under risk was measured with performance of the Cambridge Gambling Task (CGT; Rogers et al., 1999), decision-making under uncertainty with the Balloon Analogue Risk Task (BART; Lejuez et al., 2002), and fast reactive responses and inhibition via the Stop Signal Reaction Time Task (SSRT; Logan, 1994). Physical exhaustion was induced via intervals of maximal exertion exercise on a wattbike.Under pressure subelite athletes showed increased risk taking for both decisions where probability outcomes were explicit (on the CGT), and those where probability outcomes were unknown (on the BART). Despite making quicker decisions under pressure, with fewer errors, on the CGT, subelite athletes showed a reduced ability to optimally adjust betting behavior according to reward and loss contingencies. Fast reactive responses to perceptual stimuli and response inhibition did not change as a result of physical pressure. Individual responses to pressure showed a negative correlation in that a decrease in reaction times on the SSRT Task under pressure was associated with an increase in risk taking on the BART. When assessing the applicability of results based on group averages to individual athletes, 17% of the sample showed an "average" response (within 1 SD of the mean) to pressure across all three decision-making tasks.Indicators of decision-making in a sample of subelite athletes are influenced by physical pressure, with a shift toward increased indiscriminate risk taking. The influence that physical pressure has on decision-making was different to that observed in world-class elite athletes; this highlights the importance of distinguishing between athletes at the elite level (Swann et al., 2015). The application of this work to a novel subgroup of elite athletes, including the implementation of a decision-making taxonomy, is discussed.

Having investigated the decision making of world class elite and subelite athletes (see Parkin and Walsh, 2017; Parkin et al., 2017), here the abilities of those at the earliest stage of entry to elite sport are examined. Junior elite athletes have undergone initial national selection and are younger than athletes examined previously (mean age 13 years). Decision making under mental pressure is explored in this sample. During performance an athlete encounters a wide array of mental pressures; these include the psychological impact of errors, negative feedback, and requirements for sustained attention in a dynamic environment (Anshel and Wells, 2000; Mellalieu et al., 2009). Such factors increase the cognitive demands of the athletes, inducing distracting anxiety-related thoughts known as rumination (Beilock and Gray, 2007). Mental pressure has been shown to reduce performance of decision-making tasks where reward and loss contingencies are explicit, with a shift toward increased risk taking (Pabst et al., 2013; Starcke et al., 2011). Mental pressure has been shown to be detrimental to decision-making speed in comparison to physical stress, highlighting the importance of considering a range of different pressures encountered by athletes (Hepler, 2015).To investigate the influence of mental pressure on key indicators of decision making in junior elite athletes. This chapter concludes a wider project examining decision making across developmental stages in elite sport. The work further explores how psychological insights can be applied in an elite sporting environment and in particular tailored to the requirements of junior athletes.Seventeen junior elite athletes (10 males, mean age: 13.80 years) enrolled on a national youth athletic development program participated in the study. Performance across three categories of decision making was assessed under conditions of low and high mental pressure. Decision making under risk was measured via the Cambridge Gambling Task (CGT; Rogers et al., 1999), decision making under uncertainty via the Balloon Analogue Risk Task (BART; Lejuez et al., 2002), and fast reactive responses to perceptual stimuli via the Visual Search Task (Treisman, 1982). Mental pressure was induced with the addition of a concurrent verbal memory task, used to increase cognitive load and mimic the distracting effects of anxiety-related rumination.In junior elite athletes, fast reactive responses to perceptual stimuli (on the Visual Search Task) were slower under conditions of mental pressure. For decision making under risk there was an interaction of mental pressure and gender on the amount of points gambled, under pressure there was a higher level of risk taking in male athletes compared to females. There was no influence of mental pressure on decision making under uncertainity. There were no significant correlations in the degree to which individual's responses changed under pressure across the three measures of decision making. When assessing the applicability of results based on group averages there were no junior elite athletes who showed an "average" response (within 1SD of the mean) to mental pressure across all the three decision-making tasks.Mental pressure affects decision making in a sample of junior elite athletes, with a slowing of response times, and modulations to performance of decision making under risk that have a high requirement for working memory. In relation to sport, these findings suggest that novel situations that place high cognitive demands on the athlete may be particularly influenced by mental pressure. The application of this work in junior elite athletes included the feedback of individual results and the implementation of a decision-making taxonomy.

The cognitive skills required during sport are highly demanding; accurate decisions based on the processing of dynamic environments are made in a fraction of a second (Walsh, 2014). Optimal decision-making abilities are crucial for success in sporting competition (Bar-Eli et al., 2011; Kaya, 2014). Moreover, for the elite athlete, decision making is required under conditions of intense mental and physical pressure (Anshel and Wells, 2000), yet much of the work in this area has largely ignored the highly stressful context in which athletes operate. A number of studies have shown that conditions of elevated pressure influence athletes' decision quality (Kinrade et al., 2015; Smith et al., 2016), response times (Hepler, 2015; Smith et al., 2016) and risk taking (Pighin et al., 2015). However, almost all of this work has been undertaken in nonelite athletes and participants who do not routinely operate under conditions of high stress. Thus, there is very little known about the influence of pressure on decision making in elite athletes.This study investigated the influence of physical performance pressure on decision making in a sample of world-class elite athletes. This allowed an examination of whether findings from the previous work in nonelite athletes extend to those who routinely operate under conditions of high stress. How this work could be applied to improve insight and understanding of decision making among sport professionals is examined. We sought to introduce a categorization of decision making useful to practitioners in sport: gunslingers, poker players, and chickens.Twenty-three elite athletes who compete and have frequent success at an international level (including six Olympic medal winners) performed tasks relating to three categories of decision making under conditions of low and high physical pressure. Decision making under risk was measured with performance on the Cambridge Gambling Task (CGT; Rogers et al., 1999), decision making under uncertainty with the Balloon Analogue Risk Task (BART; Lejuez et al., 2002), and fast reactive responses and interference with the Stroop Task (Stroop, 1935). Performance pressures of physical exhaustion was induced via an exercise protocol consisting of intervals of maximal exertion undertaken on a watt bike.At a group level, under physical pressure elite athletes were faster to respond to control trials on the Stroop Task and to simple probabilistic choices on the CGT. Physical pressure was also found to increase risk taking for decisions where probability outcomes were explicit (on the CGT), but did not affect risk taking when probability outcomes were unknown (on the BART). There were no significant correlations in the degree to which individuals' responses changed under pressure across the three tasks, suggesting that elite athletes did not show consistent responses to physical pressure across measures of decision making. When assessing the applicability of results based on group averages to individual athletes, none of the sample showed an "average" response (within 1 SD of the mean) to pressure across all three decision-making tasks.There are three points of conclusion. First, an immediate scientific point that highlights a failure of transfer of work reported from nonelite athletes to elite athletes in the area of decision making under pressure. Second, a practical conclusion with respect to the application of this work to the elite sporting environment, which highlights the limitations of statistical approaches based on group averages and thus the beneficial use of individualized profiling in feedback sessions. Third, the application of this work in a sports setting is described, in particular the development and implementation of a decision-making taxonomy as a framework to conceptualize and communicate psychological skills among elite sporting professionals.

Slowing is a common feature of ageing, yet a direct relationship between neural slowing and brain atrophy is yet to be established in healthy humans. We combine magnetoencephalographic (MEG) measures of neural processing speed with magnetic resonance imaging (MRI) measures of white and grey matter in a large population-derived cohort to investigate the relationship between age-related structural differences and visual evoked field (VEF) and auditory evoked field (AEF) delay across two different tasks. Here we use a novel technique to show that VEFs exhibit a constant delay, whereas AEFs exhibit delay that accumulates over time. White-matter (WM) microstructure in the optic radiation partially mediates visual delay, suggesting increased transmission time, whereas grey matter (GM) in auditory cortex partially mediates auditory delay, suggesting less efficient local processing. Our results demonstrate that age has dissociable effects on neural processing speed, and that these effects relate to different types of brain atrophy., Neural processing speed slows with age, but the relationship between this slowing and brain atrophy is unknown. Here, authors show that age-related functional brain differences in auditory and visual processing are partly due to structural differences in the distinct brain regions underlying these processes.

The comment by Ashton, Lee, and Visser (2014) seeks to find fault in the recent article ‘Fractionating Human Intelligence’ ( Hampshire, Highfield, Parkin, & Owen, 2012 ). However, several of their key points are misleading and, more importantly, they fail completely to acknowledge the main novel contribution of the original article. More specifically, their comment focuses entirely on the behavioural data and makes no attempt to consider the relationship between the neuroimaging and behavioural results ( Hampshire et.al, 2012 ). This is a major oversight, because the main point of the original article was an alternative perspective on the nature of Intelligence that considered how the factors of human ability reflect the manner in which the human brain is organised into specialised functional systems. Moreover, their argument for disregarding the imaging analyses is demonstrably weak. Here, we argue, that data from individual differences analyses and brain imaging analyses are complementary and must be considered together, because, whilst they relate to the same underlying cognitive systems, they have quite different properties. The weaknesses when analysing one set of data are complemented by the strengths when analysing the other. Consequently, by combining the two, it is possible to further constrain our understanding of the architecture of human cognition.

Background: Having investigated the influence of acute physical exhaustion on decision-making in world-class elite athletes in Parkin et al. (2017) , here a similar method is applied to subelite athletes. These subelite athletes were enrolled on a Team GB talent development program and were undergoing training for possible Olympic competition in 4–8 years. They differ from elite athletes examined previously according to expertise and age. While considered elite ( Swann et al., 2015 ), the subelite athletes had approximately 8 years fewer sporting experience and were yet to obtain sustained success on the international stage. Additionally, the average age of the subelite sample is 20 years; thus, they are still undergoing the behavioral, cognitive, and neuronal changes that occur during the transition from late adolescence to young adulthood ( Blakemore and Robbins, 2012 ). Previous work has used broad definitions of elite status in sport, and as such overlooked different categories within the spectrum of elite athletes ( Swann et al., 2015 ). Therefore it is important to consider subelite athletes as a discrete point on the developmental trajectory of elite sporting expertise. Objective: This work aims to investigate the influence of physical pressure on key indicators of decision-making in subelite athletes. It forms part of a wider project examining decision-making across different stages of the developmental trajectory in elite sport. In doing so, it aims to examine how to apply and develop psychological insights useful to an elite sporting environment. Methods: 32 subelite athletes (18 males, mean age: 20 years) participated in the study. Performance across three categories of decision-making was assessed under conditions of low and high physical pressure. Decision-making under risk was measured with performance of the Cambridge Gambling Task (CGT; Rogers et al., 1999 ), decision-making under uncertainty with the Balloon Analogue Risk Task (BART; Lejuez et al., 2002 ), and fast reactive responses and inhibition via the Stop Signal Reaction Time Task (SSRT; Logan, 1994 ). Physical exhaustion was induced via intervals of maximal exertion exercise on a wattbike. Results: Under pressure subelite athletes showed increased risk taking for both decisions where probability outcomes were explicit (on the CGT), and those where probability outcomes were unknown (on the BART). Despite making quicker decisions under pressure, with fewer errors, on the CGT, subelite athletes showed a reduced ability to optimally adjust betting behavior according to reward and loss contingencies. Fast reactive responses to perceptual stimuli and response inhibition did not change as a result of physical pressure. Individual responses to pressure showed a negative correlation in that a decrease in reaction times on the SSRT Task under pressure was associated with an increase in risk taking on the BART. When assessing the applicability of results based on group averages to individual athletes, 17% of the sample showed an “average” response (within 1 SD of the mean) to pressure across all three decision-making tasks. Conclusion: Indicators of decision-making in a sample of subelite athletes are influenced by physical pressure, with a shift toward increased indiscriminate risk taking. The influence that physical pressure has on decision-making was different to that observed in world-class elite athletes; this highlights the importance of distinguishing between athletes at the elite level ( Swann et al., 2015 ). The application of this work to a novel subgroup of elite athletes, including the implementation of a decision-making taxonomy, is discussed.

Background: Having investigated the decision making of world class elite and subelite athletes (see Parkin and Walsh, 2017 , Parkin et al., 2017 ), here the abilities of those at the earliest stage of entry to elite sport are examined. Junior elite athletes have undergone initial national selection and are younger than athletes examined previously (mean age 13 years). Decision making under mental pressure is explored in this sample. During performance an athlete encounters a wide array of mental pressures; these include the psychological impact of errors, negative feedback, and requirements for sustained attention in a dynamic environment ( Anshel and Wells, 2000 , Mellalieu et al., 2009 ). Such factors increase the cognitive demands of the athletes, inducing distracting anxiety-related thoughts known as rumination ( Beilock and Gray, 2007 ). Mental pressure has been shown to reduce performance of decision-making tasks where reward and loss contingencies are explicit, with a shift toward increased risk taking ( Pabst et al., 2013 , Starcke et al., 2011 ). Mental pressure has been shown to be detrimental to decision-making speed in comparison to physical stress, highlighting the importance of considering a range of different pressures encountered by athletes ( Hepler, 2015 ). Objective: To investigate the influence of mental pressure on key indicators of decision making in junior elite athletes. This chapter concludes a wider project examining decision making across developmental stages in elite sport. The work further explores how psychological insights can be applied in an elite sporting environment and in particular tailored to the requirements of junior athletes. Methods: Seventeen junior elite athletes (10 males, mean age: 13.80 years) enrolled on a national youth athletic development program participated in the study. Performance across three categories of decision making was assessed under conditions of low and high mental pressure. Decision making under risk was measured via the Cambridge Gambling Task (CGT; Rogers et al., 1999 ), decision making under uncertainty via the Balloon Analogue Risk Task (BART; Lejuez et al., 2002 ), and fast reactive responses to perceptual stimuli via the Visual Search Task ( Treisman, 1982 ). Mental pressure was induced with the addition of a concurrent verbal memory task, used to increase cognitive load and mimic the distracting effects of anxiety-related rumination. Results: In junior elite athletes, fast reactive responses to perceptual stimuli (on the Visual Search Task) were slower under conditions of mental pressure. For decision making under risk there was an interaction of mental pressure and gender on the amount of points gambled, under pressure there was a higher level of risk taking in male athletes compared to females. There was no influence of mental pressure on decision making under uncertainity. There were no significant correlations in the degree to which individual's responses changed under pressure across the three measures of decision making. When assessing the applicability of results based on group averages there were no junior elite athletes who showed an “average” response (within 1SD of the mean) to mental pressure across all the three decision-making tasks. Conclusion: Mental pressure affects decision making in a sample of junior elite athletes, with a slowing of response times, and modulations to performance of decision making under risk that have a high requirement for working memory. In relation to sport, these findings suggest that novel situations that place high cognitive demands on the athlete may be particularly influenced by mental pressure. The application of this work in junior elite athletes included the feedback of individual results and the implementation of a decision-making taxonomy.

A prominent hypothesis states that specialized neural modules within the human lateral frontopolar cortices (LFPCs) support “relational integration” (RI), the solving of complex problems using inter-related rules. However, it has been proposed that LFPC activity during RI could reflect the recruitment of additional “domain-general” resources when processing more difficult problems in general as opposed to RI specifically. Moreover, theoretical research with computational models has demonstrated that RI may be supported by dynamic processes that occur throughout distributed networks of brain regions as opposed to within a discrete computational module. Here, we present fMRI findings from a novel deductive reasoning paradigm that controls for general difficulty while manipulating RI demands. In accordance with the domain-general perspective, we observe an increase in frontoparietal activation during challenging problems in general as opposed to RI specifically. Nonetheless, when examining frontoparietal activity using analyses of phase synchrony and psychophysiological interactions, we observe increased network connectivity during RI alone. Moreover, dynamic causal modeling with Bayesian model selection identifies the LFPC as the effective connectivity source. Based on these results, we propose that during RI an increase in network connectivity and a decrease in network metastability allows rules that are coded throughout working memory systems to be dynamically bound. This change in connectivity state is top-down propagated via a hierarchical system of domain-general networks with the LFPC at the apex. In this manner, the functional network perspective reconciles key propositions of the globalist, modular, and computational accounts of RI within a single unified framework.

The use of non-invasive brain stimulation is widespread in studies of human cognitive neuroscience. This has led to some genuine advances in understanding perception and cognition, and has raised some hopes of applying the knowledge in clinical contexts. There are now several forms of stimulation, the ability to combine these with other methods, and ethical questions that are special to brain stimulation. In this Primer, we aim to give the users of these methods a starting point and perspective from which to view the key questions and usefulness of the different forms of non-invasive brain stimulation. We have done so by taking a critical view of recent highlights in the literature, selected case studies to illustrate the elements necessary and sufficient for good experiments, and pointed to questions and findings that can only be addressed using interference methods.

It is now well established that some patients who are diagnosed as being in a vegetative state or a minimally conscious state show reliable signs of volition that may only be detected by measuring neural responses. A pertinent question is whether these patients are also capable of logical thought. Here, we validate an fMRI paradigm that can detect the neural fingerprint of reasoning processes and moreover, can confirm whether a participant derives logical answers. We demonstrate the efficacy of this approach in a physically non-communicative patient who had been shown to engage in mental imagery in response to simple auditory instructions. Our results demonstrate that this individual retains a remarkable capacity for higher cognition, engaging in the reasoning task and deducing logical answers. We suggest that this approach is suitable for detecting residual reasoning ability using neural responses and could readily be adapted to assess other aspects of cognition., Highlights ► Hampshire et al. develop a paradigm for assessing reasoning ability using fMRI alone. ► Inferior frontal sulcus activation is used as a marker of engagement in reasoning. ► Visual and pre-motor activation is used to detect logically correct answers. ► An overtly non-responsive patient is able to solve grammatical reasoning problems. ► Frontal lobe sub-regions activate at distinct stages of the reasoning task.

SUMMARY What makes one person more intellectually able than another? Can the entire distribution of human intelligence be accounted for by just one general factor? Is intelligence supported by a single neural system? Here, we provide a perspective on human intelligence that takes into account how general abilities or ‘‘factors’’ reflect the functional organization of the brain. By comparing factor models of individual differences in performance with factor models of brain functional organization, we demonstrate that different components of intelligence have their analogs in distinct brain networks. Using simulations based on neuroimaging data, we show that the higher-order factor ‘‘g’’ is accounted for by cognitive tasks corecruiting multiple networks. Finally, we confirm the independence of these components of intelligence by dissociating them using questionnaire variables. We propose that intelligence is an emergent property of anatomically distinct cognitive systems, each of which has its own capacity.

Ashton and colleagues concede in their response (Ashton, Lee, & Visser, in this issue), that neuroimaging methods provide a relatively unambiguous measure of the levels to which cognitive tasks co-recruit dif- ferent functional brain networks (task mixing). It is also evident from their response that they now accept that task mixing differs from the blended models of the classic literature. However, they still have not grasped how the neuroimaging data can help to constrain models of the neural basis of higher order ‘g’. Specifically, they claim that our analyses are invalid as we assume that functional networks have uncorrelated capacities. They use the simple analogy of a set of exercises that recruit multiple muscle groups to varying extents and highlight the fact that individual differences in strength may correlate across muscle groups. Contrary to their claim, we did not assume in the original article (Hampshire, High- field, Parkin, & Owen, 2012) that functional networks had uncorrelated capacities; instead, the analyses were specifically designed to estimate the scale of those correlations, which we referred to as spatially ‘diffuse’ factors