Competitive processes in the brain have the potential to account for a much larger range of behavioral functions than only attention and memory. Mather et al. successfully account for enhancing and impairing effects of arousal (and norepinephrine [NE]) on selective attention and memory in terms of neural competition, but still sometimes mix the brain metaphor with the “steam engine” metaphor. If competition is envisaged as mutual inhibition between neural nodes, there is no further need to borrow conservation laws from nineteenth-century physics and invoke limited resources to explain interference. Whereas arousal effects are thus predominantly analyzed in terms of neural processes, the source of arousal and emotion is discussed here only on a behavioral level. The analysis can be extended by also grounding arousal and affect in processes of neural competition.
Emotion research abounds in examples where modulatory influences of affect on attention and memory appear to be reciprocal, in that a similar, but not affectively laden, manipulation of attention or memory is able to elicit affect (e.g., Dreisbach & Fischer Reference Dreisbach and Fischer2012; Phaf & Rotteveel Reference Phaf and Rotteveel2005; Rotteveel & Phaf Reference Rotteveel and Phaf2007; Srinivasan & Hanif Reference Srinivasan and Hanif2010). Most relevant to the present discussion may be studies demonstrating distracter devaluation, and target appreciation, in attentional filtering tasks (Goolsby et al. Reference Goolsby, Shapiro, Silvert, Kiss, Fragopanagos, Taylor, Eimer, Nobre and Raymond2009; see also Raymond et al. Reference Raymond, Fenske and Tavassoli2003). The present authors explain target selection in attentional tasks by biased competition (Desimone & Duncan Reference Desimone and Duncan1995; Duncan Reference Duncan, Inui and McClelland1996; see also Phaf et al. Reference Phaf, Van der Heijden and Hudson1990), so the appreciation and devaluation may also follow from competitive processes. Phaf and Rotteveel (Reference Phaf and Rotteveel2012) have argued that affect is the consequence of competition (i.e., conflicting neural representations [cf. Murre et al. Reference Murre, Phaf and Wolters1992), and that negative affect arises when it is sustained, but positive affect when it is quickly resolved. Fluent, competition-less processing in itself is not sufficient to raise positive affect (but see Fazendeiro et al. Reference Fazendeiro, Chenier, Winkielman, Harmon-Jones and Winkielman2007). The common denominator in both positive and negative affect is the initial competition, which may thus correspond to arousal. The largely similar effects of positive and negative arousal (e.g., Sutherland & Mather, Reference Sutherland and Matherunder review) may thus result from this initial phase of competition.
Gamma and theta oscillations are involved but not well integrated by the authors in their competitive framework. Such integration, however, serendipitously emerged from our evolutionary simulations (Heerebout & Phaf Reference Heerebout and Phaf2010a; Reference Heerebout and Phaf2010b). Random variation combined with selection of the fittest individuals led to the development of both competition and oscillations in neural networks that controlled agents roaming an artificial environment. The fitness measure combined the amount of food gathered and the time the agent managed to escape from predators. The serendipitous emergence of oscillations coincided with a near doubling of fitness, indicating that they were very functional to the agents. In fact, the same feedback loops between excitatory and inhibitory nodes developed autonomously in the evolutionary simulations as were suggested in Mather et al. Heerebout and Phaf (Reference Heerebout and Phaf2010a) investigated the behavior of these agents and found that the function of oscillations was complementary to that of competition. Competition enables the selection of representations, and oscillations allow for a reset of winners (i.e., switching of representations).
Attentional flexibility is more functional with positive than with negative affect. When searching for food, it is highly adaptive to be able to quickly shift attention toward an approaching predator. When running from a predator, it is highly maladaptive to switch attention to some palatable food (i.e., “it is better to miss dinner than to be dinner”). We hypothesized that low-frequency, presumably theta, oscillations are evoked by competition, whereas high-frequency, presumably gamma, oscillations arise when the competition is solved. Similar to arousal (and NE), the former increase selectivity and narrow attentional focus, whereas the latter enhance switching between representations and attentional flexibility (Bauer et al. Reference Bauer, Cheadle, Parton, Müller and Usher2009; Heerebout et al. Reference Heerebout, Tap, Rotteveel and Phaf2013). Crucially, in this view, theta oscillations (i.e., resulting from competition) precede gamma oscillations and may thus be the most primary reflection of arousal. According to this framework, without competition there is no arousal, theta synchrony (i.e., negative affect), or eventual gamma synchrony (i.e., positive affect). Doubtlessly, the functioning of biological networks is more complex than in these simple models, which, however, provide a useful starting point for the integration of such disparate functions as attention, memory, arousal, affect, and neural oscillations.
Mather et al. attempt to break down the traditional distinction between hot emotional and cold cognitive processes by discussing emotional modulation of cognition. Not only, however, are there modulatory effects of arousal and emotion on attention and memory for neutral material, but also the elicitation of arousal and affect from the processing of neutral material can be observed (e.g., from novelty, conflict in classic Stroop [Phaf & Rotteveel Reference Phaf and Rotteveel2012]). The reverse modulation of emotion by cognition further strengthens such attempts at integration. With respect to neuronal organization, this must imply that specialized emotional and cognitive modules should not be distinguished, but that a more distributed picture of dynamic coalitions of multifunctional brain regions emerges (cf. Pessoa Reference Pessoa2008). Not only does neural competition seem an obvious candidate for the regulation of these processing streams, but also it can serve to account in an almost mechanical fashion for both emotional and cognitive sub-processes. Unfortunately, at the end, Mather and coauthors seem to qualify this role again by arguing that the GANE model does not require competition to be a fundamental mechanism, but that it applies to whatever priority mechanism is acting. If this refers to the resources from the steam engine metaphor, it is unclear how they can also account for the elicitation of arousal and affect. To paraphrase the beginning of the authors' conclusion: Competition is the core of what allows both our emotional and cognitive systems to function effectively.
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Competitive processes in the brain have the potential to account for a much larger range of behavioral functions than only attention and memory. Mather et al. successfully account for enhancing and impairing effects of arousal (and norepinephrine [NE]) on selective attention and memory in terms of neural competition, but still sometimes mix the brain metaphor with the “steam engine” metaphor. If competition is envisaged as mutual inhibition between neural nodes, there is no further need to borrow conservation laws from nineteenth-century physics and invoke limited resources to explain interference. Whereas arousal effects are thus predominantly analyzed in terms of neural processes, the source of arousal and emotion is discussed here only on a behavioral level. The analysis can be extended by also grounding arousal and affect in processes of neural competition.
Emotion research abounds in examples where modulatory influences of affect on attention and memory appear to be reciprocal, in that a similar, but not affectively laden, manipulation of attention or memory is able to elicit affect (e.g., Dreisbach & Fischer Reference Dreisbach and Fischer2012; Phaf & Rotteveel Reference Phaf and Rotteveel2005; Rotteveel & Phaf Reference Rotteveel and Phaf2007; Srinivasan & Hanif Reference Srinivasan and Hanif2010). Most relevant to the present discussion may be studies demonstrating distracter devaluation, and target appreciation, in attentional filtering tasks (Goolsby et al. Reference Goolsby, Shapiro, Silvert, Kiss, Fragopanagos, Taylor, Eimer, Nobre and Raymond2009; see also Raymond et al. Reference Raymond, Fenske and Tavassoli2003). The present authors explain target selection in attentional tasks by biased competition (Desimone & Duncan Reference Desimone and Duncan1995; Duncan Reference Duncan, Inui and McClelland1996; see also Phaf et al. Reference Phaf, Van der Heijden and Hudson1990), so the appreciation and devaluation may also follow from competitive processes. Phaf and Rotteveel (Reference Phaf and Rotteveel2012) have argued that affect is the consequence of competition (i.e., conflicting neural representations [cf. Murre et al. Reference Murre, Phaf and Wolters1992), and that negative affect arises when it is sustained, but positive affect when it is quickly resolved. Fluent, competition-less processing in itself is not sufficient to raise positive affect (but see Fazendeiro et al. Reference Fazendeiro, Chenier, Winkielman, Harmon-Jones and Winkielman2007). The common denominator in both positive and negative affect is the initial competition, which may thus correspond to arousal. The largely similar effects of positive and negative arousal (e.g., Sutherland & Mather, Reference Sutherland and Matherunder review) may thus result from this initial phase of competition.
Gamma and theta oscillations are involved but not well integrated by the authors in their competitive framework. Such integration, however, serendipitously emerged from our evolutionary simulations (Heerebout & Phaf Reference Heerebout and Phaf2010a; Reference Heerebout and Phaf2010b). Random variation combined with selection of the fittest individuals led to the development of both competition and oscillations in neural networks that controlled agents roaming an artificial environment. The fitness measure combined the amount of food gathered and the time the agent managed to escape from predators. The serendipitous emergence of oscillations coincided with a near doubling of fitness, indicating that they were very functional to the agents. In fact, the same feedback loops between excitatory and inhibitory nodes developed autonomously in the evolutionary simulations as were suggested in Mather et al. Heerebout and Phaf (Reference Heerebout and Phaf2010a) investigated the behavior of these agents and found that the function of oscillations was complementary to that of competition. Competition enables the selection of representations, and oscillations allow for a reset of winners (i.e., switching of representations).
Attentional flexibility is more functional with positive than with negative affect. When searching for food, it is highly adaptive to be able to quickly shift attention toward an approaching predator. When running from a predator, it is highly maladaptive to switch attention to some palatable food (i.e., “it is better to miss dinner than to be dinner”). We hypothesized that low-frequency, presumably theta, oscillations are evoked by competition, whereas high-frequency, presumably gamma, oscillations arise when the competition is solved. Similar to arousal (and NE), the former increase selectivity and narrow attentional focus, whereas the latter enhance switching between representations and attentional flexibility (Bauer et al. Reference Bauer, Cheadle, Parton, Müller and Usher2009; Heerebout et al. Reference Heerebout, Tap, Rotteveel and Phaf2013). Crucially, in this view, theta oscillations (i.e., resulting from competition) precede gamma oscillations and may thus be the most primary reflection of arousal. According to this framework, without competition there is no arousal, theta synchrony (i.e., negative affect), or eventual gamma synchrony (i.e., positive affect). Doubtlessly, the functioning of biological networks is more complex than in these simple models, which, however, provide a useful starting point for the integration of such disparate functions as attention, memory, arousal, affect, and neural oscillations.
Mather et al. attempt to break down the traditional distinction between hot emotional and cold cognitive processes by discussing emotional modulation of cognition. Not only, however, are there modulatory effects of arousal and emotion on attention and memory for neutral material, but also the elicitation of arousal and affect from the processing of neutral material can be observed (e.g., from novelty, conflict in classic Stroop [Phaf & Rotteveel Reference Phaf and Rotteveel2012]). The reverse modulation of emotion by cognition further strengthens such attempts at integration. With respect to neuronal organization, this must imply that specialized emotional and cognitive modules should not be distinguished, but that a more distributed picture of dynamic coalitions of multifunctional brain regions emerges (cf. Pessoa Reference Pessoa2008). Not only does neural competition seem an obvious candidate for the regulation of these processing streams, but also it can serve to account in an almost mechanical fashion for both emotional and cognitive sub-processes. Unfortunately, at the end, Mather and coauthors seem to qualify this role again by arguing that the GANE model does not require competition to be a fundamental mechanism, but that it applies to whatever priority mechanism is acting. If this refers to the resources from the steam engine metaphor, it is unclear how they can also account for the elicitation of arousal and affect. To paraphrase the beginning of the authors' conclusion: Competition is the core of what allows both our emotional and cognitive systems to function effectively.