Distant from input: Evidence of regions within the default mode network supporting perceptually-decoupled and conceptually-guided cognition

Abstract

The default mode network supports a variety of mental operations such as semantic processing, episodic memory retrieval, mental time travel and mind-wandering, yet the commonalities between these functions remains unclear. One possibility is that this system supports cognition that is independent of the immediate environment; alternatively or additionally, it might support higher-order conceptual representations that draw together multiple features. We tested these accounts using a novel paradigm that separately manipulated the availability of perceptual information to guide decision-making and the representational complexity of this information. Using task based imaging we established regions that respond when cognition combines both stimulus independence with multi-modal information. These included left and right angular gyri and the left middle temporal gyrus. Although these sites were within the default mode network, they showed a stronger response to demanding memory judgements than to an easier perceptual task, contrary to the view that they support automatic aspects of cognition. In a subsequent analysis, we showed that these regions were located at the extreme end of a macroscale gradient, which describes gradual transitions from sensorimotor to transmodal cortex. This shift in the focus of neural activity towards transmodal, default mode, regions might reflect a process of where the functional distance from specific sensory enables conceptually rich and detailed cognitive states to be generated in the absence of input.

Targeting age‐related differences in brain and cognition with multimodal imaging and connectome topography profiling

“…As for the previous analysis, findings were corrected using an FDR procedure. Both gradients were discretized into 20 bins, following a recent approach to stratify task-based fMRI data using connectome topographies (Murphy et al, 2018). In the hippocampus, the first principal gradient of hippocampal connectivity runs from anterior to posterior regions across all subfields, with the former being more strongly connected to transmodal DMN than the posterior part (Vos de Wael et al, 2018).…”

“…In the hippocampus, the first principal gradient of hippocampal connectivity runs from anterior to posterior regions across all subfields, with the former being more strongly connected to transmodal DMN than the posterior part (Vos de Wael et al, 2018). Both gradients were discretized into 20 bins, following a recent approach to stratify task-based fMRI data using connectome topographies (Murphy et al, 2018). In brief, depending on its location on the original gradient map, each voxel was assigned a label between 0 and 100, where 0 represents the unimodal end and 100 the transmodal end.…”

BrainSpace: a toolbox for the analysis of macroscale gradients in neuroimaging and connectomics datasets

“…The ability to describe the brain wide neural activity in a single manifold offers the possibility to understand how the integrated nature of neural processing gives rise to function and dysfunction. Adopting a macroscale perspective on 50 cortical organization has already provided important insights into how cortexwide patterns relate to cortical dynamics and high level cognition (Sormaz et al, 2018;Murphy et al, 2018Murphy et al, , 2019Shine et al, 2019). Furthermore, several studies have leveraged gradients as an analytical framework to describe atypical macroscale organization across clinical conditions, 55 for example, by showing perturbations in functional connectome gradients in autism (Hong et al, 2019) and schizophrenia (Tian et al, 2019).…”

“…We also provide the evaluated FC and MPC gradients across these different spatial scales. Such gradients can be used to, for example stratify other imaging measures, including 380 functional activation and connectivity patters (Hong et al, 2019;Murphy et al, 2018), meta-analytical syntheses (Murphy et al, 2019;Margulies et al, 2016), cortical thickness measures or Amyloid-beta PET uptake data (Lowe et al, 2019).…”

Functional connectome contractions in temporal lobe epilepsy: microstructural underpinnings and associations to surgical outcome

“…26 Using a previously described approach, 26 the connectome gradient was computed using 100 subjects from the Human Connectome Project and subsequently surface registered to the 10k downsampled Conte69 template. As in previous connectome gradient profiling analyses, 27 we partitioned the gradient into 20 bins, ranging from unimodal regions (1 st bin) to higher-order/transmodal areas situated at the top of the processing hierarchy (20 th bin), and calculated mean vertex-wise connectivity distance at each bin. Patients and controls were compared using two-sample t-tests at each community and at each gradient bin, respectively.…”