Understanding how structure maps to function in the brain in terms of large-scale networks is critical to elucidating the brain basis of mental phenomena and mental disorders. Given that this mapping is many-to-many, I argue that researchers need to shift to a multivariate brain and behavior characterization to fully unravel the contributions of brain processes to typical and atypical function.

It is taken for granted that the brain is composed of a set of networks. But what is a brain network? How should we characterize them? Adding to Anderson's (2014) persuasive anti-modular framework, I propose that (1) networks do not have a single, unique function; (2) networks are highly overlapping and not disjoint; and (3) tasks reconfigure networks found at rest.

In the précis to The Cognitive-Emotional Brain, I summarize a framework for understanding the organization of cognition and emotion in the brain. Here, I address six major themes that emerged in the commentaries: (1) emotional perception and automaticity; (2) the status of cognition and emotion: together or separate? (3) evolutionary implications for the understanding of emotion and cognition; (4) the diverse forms of cognitive-emotional integration; (5) dual process theories; and (6) functional diversity of brain regions/networks and cognitive ontologies. The central argument is, again, that cognition and emotion are so highly interactive, and indeed integrated, that these two elements blend into a new amalgam.

In The Cognitive-Emotional Brain (Pessoa 2013), I describe the many ways that emotion and cognition interact and are integrated in the brain. The book summarizes five areas of research that support this integrative view and makes four arguments to organize each area. (1) Based on rodent and human data, I propose that the amygdala's functions go beyond emotion as traditionally conceived. Furthermore, the processing of emotion-laden information is capacity limited, thus not independent of attention and awareness. (2) Cognitive-emotional interactions in the human prefrontal cortex (PFC) assume diverse forms and are not limited to mutual suppression. Particularly, the lateral PFC is a focal point for cognitive-emotional interactions. (3) Interactions between motivation and cognition can be seen across a range of perceptual and cognitive tasks. Motivation shapes behavior in specific ways – for example, by reducing response conflict or via selective effects on working memory. Traditional accounts, by contrast, typically describe motivation as a global activation independent of particular control demands. (4) Perception and cognition are directly influenced by information with affective or motivational content in powerful ways. A dual competition model outlines a framework for such interactions at the perceptual and executive levels. A specific neural architecture is proposed that embeds emotional and motivational signals into perception and cognition through multiple channels. (5) A network perspective should supplant the strategy of understanding the brain in terms of individual regions. More broadly, in a network view of brain architecture, “emotion” and “cognition” may be used as labels of certain behaviors, but will not map cleanly into compartmentalized pieces of the brain.

Lindquist et al. provide a convincing case against what they call the locationist account of emotion. Their quantitative approach elegantly illustrates the shortcomings of this still-entrenched viewpoint. Here, I discuss how a network perspective will advance our understanding of structure-function mappings in general, and the relationship between emotion and cognition in the brain.

Amorphous silicon carbide (a-SiC) thin films have been grown on aluminum nitride (AlN) intermediate layers on (100) Si substrates by RF magnetron sputtering technique. Profilometry, four-point probe method, Rutherford backscattering spectroscopy (RBS) and Fourier transform infrared (FTIR) were employed to characterize the as-deposited SiC thin films. Test structures have been developed to investigate the piezoresistive properties. These structures consist of SiC thin-film resistors on AlN/Si substrates defined by reactive ion etching (RIE) with Ti/Au pads formed by lift-off process. Gauge factor (GF) and temperature coefficient of resistance (TCR) measurements have been performed and demonstrated the potential of these resistors to be used as sensing elements in devices for high temperature application.

(1) The main issue with regard to modal and amodal completion is not which phenomena are cognitive, and which perceptual. At the level of the animal, both are visuo-cognitive. At the level of visual processing, however, we need to dissect the different functional effects of these kinds of completion. (2) Resonant binding between distributed cortical areas may play a role in perceptual completion, but evidence is needed.

The following points are discussed in response to the commentaries: (1) A taxonomy of perceptual completion phenomena should rely on both phenomenological and mechanistic criteria. (2) Certain forms of perceptual completion are caused by topographically organized neural processes – neural filling-in. (3) The bridge locus, understood as the final site of perceptual experience in the brain, should be replaced by the principle that each token percept has a neural substrate that is nomically sufficient for it, all else being equal. (4) Analytic isomorphism – the view that there must be a pictorial or spatial neural-perceptual isomorphism at the bridge locus – should be rejected. Although more abstract kinds of isomorphism are central to the neural-perceptual mapping, the perceptual cannot be exhaustively explained in terms of the neural, and therefore the explanation of perception cannot be reduced to uncovering neural-perceptual isomorphisms. (5) The task of vision is to guide action in the world, not to construct a detailed world-model in the head. (6) Neural filling-in facilitates the integration of information and thereby helps the animal find out about its environment. (7) Perceptual content needs to be understood at the level of the person or animal interacting in the world.

In visual science the term filling-in is used in different ways, which often leads to confusion. This target article presents a taxonomy of perceptual completion phenomena to organize and clarify theoretical and empirical discussion. Examples of boundary completion (illusory contours) and featural completion (color, brightness, motion, texture, and depth) are examined, and single-cell studies relevant to filling-in are reviewed and assessed. Filling-in issues must be understood in relation to theoretical issues about neural–perceptual isomorphism and linking propositions. Six main conclusions are drawn: (1) visual filling-in comprises a multitude of different perceptual completion phenomena; (2) certain forms of visual completion seem to involve spatially propagating neural activity (neural filling-in) and so, contrary to Dennett's (1991; 1992) recent discussion of filling-in, cannot be described as results of the brain's “ignoring an absence” or “jumping to a conclusion”; (3) in certain cases perceptual completion seems to have measurable effects that depend on neural signals representing a presence rather than ignoring an absence; (4) neural filling-in does not imply either “analytic isomorphism” or “Cartesian materialism,” and thus the notion of the bridge locus – a particular neural stage that forms the immediate substrate of perceptual experience – is problematic and should be abandoned; (5) to reject the representational conception of vision in favor of an “enactive” or “animate” conception reduces the importance of filling-in as a theoretical category in the explanation of vision; and (6) the evaluation of perceptual content should not be determined by “subpersonal” considerations about internal processing, but rather by considerations about the task of vision at the level of the animal or person interacting with the world.