Ongoing dynamics in large-scale functional connectivity predict perception

Abstract

Most brain activity occurs in an ongoing manner not directly locked to external events or stimuli. Regional ongoing activity fluctuates in unison with some brain regions but not others, and the degree of long-range coupling is called functional connectivity, often measured with correlation. Strength and spatial distributions of functional connectivity dynamically change in an ongoing manner over seconds to minutes, even when the external environment is held constant. Direct evidence for any behavioral relevance of these continuous large-scale dynamics has been limited. Here, we investigated whether ongoing changes in baseline functional connectivity correlate with perception. In a continuous auditory detection task, participants perceived the target sound in roughly one-half of the trials. Very long (22-40 s) interstimulus intervals permitted investigation of baseline connectivity unaffected by preceding evoked responses. Using multivariate classification, we observed that functional connectivity before the target predicted whether it was heard or missed. Using graph theoretical measures, we characterized the difference in functional connectivity between states that lead to hits vs. misses. Before misses compared with hits and task-free rest, connectivity showed reduced modularity, a measure of integrity of modular network structure. This effect was strongest in the default mode and visual networks and caused by both reduced within-network connectivity and enhanced across-network connections before misses. The relation of behavior to prestimulus connectivity was dissociable from that of prestimulus activity amplitudes. In conclusion, moment to moment dynamic changes in baseline functional connectivity may shape subsequent behavioral performance. A highly modular network structure seems beneficial to perceptual efficiency.functional connectivity | brain networks | dynamics | graph theory | classification T he brain is highly active in a continuous manner, and much of neural activity is not directly locked to external events or stimuli. This continuous brain activity is spatiotemporally organized into a functional connectivity architecture that comprises several large-scale networks. Large-scale networks span different cerebral lobes and include subcortical structures (1). The regions comprised in such networks commonly coactivate together in response to task demands (2), but they also show correlated and spontaneous activity fluctuations when no changes occur in the external environment. The functional connectivity architecture ensuing from these activity cofluctuations largely persists across all mental states, including various tasks, resting wakefulness, and sleep, albeit showing some degree of modulation across these states (3, 4).Strength and spatial distributions of functional connectivity within this architecture are not, however, stationary across time. At the spatial level of large-scale networks, functional connectivity shows prominent changes over the range of seconds to minutes (5). These so-called in...

The prestimulus default mode network state predicts cognitive task performance levels on a mental rotation task

“…While the abovementioned studies show converging evidence for a beneficial role of a reduced DMN state before cognitive task onset, a number of other studies have recently shown a more variable role of the DMN for sensory tasks (Boly et al., 2007; Mayhew et al., 2013; Sadaghiani et al., 2009). These studies employed near‐threshold sensory tasks, on the one hand showing a lower prestimulus activation or connectivity predicted enhanced levels in detection performance (Boly et al., 2007), on the other hand showing a higher prestimulus DMN activation for more intense perception (e.g., more sensitive auditory stimulus detection, more extreme perception during thermal stimulation) of sensory stimuli (Mayhew et al., 2013; Sadaghiani et al., 2009, 2015). However, the tasks at hand relied primarily on processing in sensory areas, rather than higher‐order cognitive areas.…”

“…The DMN might therefore play different roles with regard to task performance when integrating sensory and higher‐order cognitive processes. In contrast to sensory tasks, cognitive tasks such as the match‐to‐sample mental rotation task employed in the current study might increase the need to distribute connections across different modules instead of relying on network integrity (Sadaghiani et al., 2015). It might be possible that within diverse DMN states, the brain benefits from a less integrated DMN (manifested in less functional connectivity within the network) in order to respond optimally to a changing environment.…”

“…This evidence for a baseline “preparedness” of task‐related brain regions was soon extended to a more global dimension by uncovering that large‐scale networks constitute different baseline states contributing to different task‐performance levels. More specifically, it has been proposed that spontaneous fluctuations in these networks during the period prior to task onset influence task performance to various degrees, introducing the idea that specific network states affect subsequent performance levels (Colas & Hsieh, 2014; Li, Yan, Bergquist, & Sinha, 2007; Mayhew, Ostwald, Porcaro, & Bagshaw, 2013; Rahnev, Bahdo, de Lange, & Lau, 2012; Sadaghiani, Hesselmann, & Kleinschmidt, 2009; Sadaghiani, Poline, Kleinschmidt, & D'Esposito, 2015; Soravia et al., 2016; Vanhaudenhuyse et al., 2011). …”

From connectome to cognition: The search for mechanism in human functional brain networks

“…In contrast, evidence of functionally relevant network dynamics emerging over relatively “fast” timescales was provided by Sadaghiani et al (Sadaghiani, Poline, Kleinschmidt, & D’Esposito, 2015). This was enabled by trial-wise FC estimation over pre-stimulus windows in an auditory detection task.…”

Spectral properties of the temporal evolution of brain network structure

“…6 Furthermore, the coordination of brain activity between disparate brain subnetworks is a dynamic and taskdependent process. [7][8][9][10] Temporal dynamic interactions within brain subnetworks play an important role in supporting brain information processing. 11,12 Fluctuations in brain systems involve a wide range of spatial and temporal scales.…”