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| 001 | 909576 | ||
| 005 | 20230123110647.0 | ||
| 024 | 7 | _ | |a 10.1016/j.tics.2022.07.001 |2 doi |
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| 100 | 1 | _ | |a Paquola, Casey |0 P:(DE-Juel1)187055 |b 0 |e Corresponding author |u fzj |
| 245 | _ | _ | |a Closing the mechanistic gap: the value of microarchitecture in understanding cognitive networks |
| 260 | _ | _ | |a Amsterdam [u.a.] |c 2022 |b Elsevier Science |
| 336 | 7 | _ | |a article |2 DRIVER |
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| 520 | _ | _ | |a Cognitive neuroscience aims to provide biologically relevant accounts of cognition. Contemporary research linking spatial patterns of neural activity to psychological constructs describes 'where' hypothesised functions occur, but not 'how' these regions contribute to cognition. Technological, empirical, and conceptual advances allow this mechanistic gap to be closed by embedding patterns of functional activity in macro- and microscale descriptions of brain organisation. Recent work on the default mode network (DMN) and the multiple demand network (MDN), for example, highlights a microarchitectural landscape that may explain how activity in these networks integrates varied information, thus providing an anatomical foundation that will help to explain how these networks contribute to many different cognitive states. This perspective highlights emerging insights into how microarchitecture can constrain network accounts of human cognition |
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| 700 | 1 | _ | |a Amunts, Katrin |0 P:(DE-Juel1)131631 |b 1 |u fzj |
| 700 | 1 | _ | |a Evans, Alan |0 P:(DE-HGF)0 |b 2 |
| 700 | 1 | _ | |a Smallwood, Jonathan |0 P:(DE-HGF)0 |b 3 |
| 700 | 1 | _ | |a Bernhardt, Boris |0 P:(DE-HGF)0 |b 4 |e Corresponding author |
| 773 | _ | _ | |a 10.1016/j.tics.2022.07.001 |g p. S1364661322001589 |0 PERI:(DE-600)2010989-1 |n 10 |p 873-886 |t Trends in cognitive sciences |v 26 |y 2022 |x 1364-6613 |
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