Opinion
Reworking the language network

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Highlights

  • A central question in cognitive science concerns whether human language requires specialized computational machinery or whether it can be solved by more general-purpose mental operations; in recent years, fMRI data have been used to argue for both sides of this debate.

  • The systems that support language processing might be better described at the level of interactive networks, not individual brain regions.

  • Many different criteria have been used to identify a ‘language network’ and variations in these definitions may contribute to some of the apparent disagreements in the field.

  • Measuring the dynamic properties of neural networks can reveal ‘core’ and ‘peripheral’ components of a network; the cross-time structure of the language network provides a new tool for thinking about functional specificity.

Prior investigations of functional specialization have focused on the response profiles of particular brain regions. Given the growing emphasis on regional covariation, we propose to reframe these questions in terms of brain ‘networks’ (collections of regions jointly engaged by some mental process). Despite the challenges that investigations of the language network face, a network approach may prove useful in understanding the cognitive architecture of language. We propose that a language network plausibly includes a functionally specialized ‘core’ (brain regions that coactivate with each other during language processing) and a domain-general ‘periphery’ (a set of brain regions that may coactivate with the language core regions at some times but with other specialized systems at other times, depending on task demands). Framing the debate around network properties such as this may prove to be a more fruitful way to advance our understanding of the neurobiology of language.

Section snippets

In search of the language organ

Many deeply important questions in cognition hinge on whether two mental processes rely on the same pool of cognitive and neural resources. Is processing faces distinct from processing other classes of visual objects? Do we use the same mechanisms to extract meaning from words versus pictures? Does resolving linguistic ambiguity draw on the same resources as other demanding tasks? This is one class of question where functional MRI (fMRI) can inform and constrain cognitive theories (cf. [1]; see

Scaling up the notion of functional specialization: from nodes to networks

What does it mean for a collection of brain regions to be functionally specialized for some mental process x? There are at least three ways to approach this question.

One strategy is to focus on the functional profiles of the individual nodes. For example, a network may be functionally specialized for mental process x if all of its nodes are functionally specialized for x (e.g., Figure 1A). Alternatively, perhaps the presence of at least one functionally specialized node is sufficient to qualify

The language network of interest

We turn now to our primary topic; namely, the language network. To ask questions about the nodes, edges, or dynamics of the language network, as described above, we need to define the language network. Immediately, we have a problem: what is language? That is, whatever task (or task comparison) one might choose to define the language network will require assumptions about what putative operations comprise language. One could rightly question whether it even makes sense to ask about a language

Is the language network functionally specialized?

The extent to which language – including its many components (like speech perception, letter/word recognition, articulation, and syntactic processing; Box 2) – relies on functionally specialized versus domain-general cognitive and neural machinery has been long debated. One important take-away message from the preceding section is that, under many definitions, the language network includes both relatively functionally specialized brain regions 24, 28, 29, 30 and brain regions better thought of

Concluding remarks

For many years, we – both as the individual scientists coauthoring this opinion article and as two representative researchers of the neurobiology of language – have been trying to understand the cognitive and neural architecture of language using regionally specific fMRI responses. Much of this work has been framed as a debate about the functional specificity of regions recruited during language processing, and we have contributed to each side of this debate. One of us has argued that there is

Acknowledgments

The authors thank Danielle Bassett, Ted Gibson, Nancy Kanwisher, and Sarah Solomon for comments on drafts of this manuscript. They were supported by the Eunice Kennedy Shriver NICHD R00 award HD-057522 to E.F. and NIH R01 DC009209 to S.L.T-S.

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