Learning sculpts the spontaneous activity of the resting human brain

Abstract

The brain is not a passive sensory-motor analyzer driven by environmental stimuli, but actively maintains ongoing representations that may be involved in the coding of expected sensory stimuli, prospective motor responses, and prior experience. Spontaneous cortical activity has been proposed to play an important part in maintaining these ongoing, internal representations, although its functional role is not well understood. One spontaneous signal being intensely investigated in the human brain is the interregional temporal correlation of the blood-oxygen level-dependent (BOLD) signal recorded at rest by functional MRI (functional connectivity-by-MRI, fcMRI, or BOLD connectivity). This signal is intrinsic and coherent within a number of distributed networks whose topography closely resembles that of functional networks recruited during tasks. While it is apparent that fcMRI networks reflect anatomical connectivity, it is less clear whether they have any dynamic functional importance. Here, we demonstrate that visual perceptual learning, an example of adult neural plasticity, modifies the resting covariance structure of spontaneous activity between networks engaged by the task. Specifically, after intense training on a shape-identification task constrained to one visual quadrant, resting BOLD functional connectivity and directed mutual interaction between trained visual cortex and frontalparietal areas involved in the control of spatial attention were significantly modified. Critically, these changes correlated with the degree of perceptual learning. We conclude that functional connectivity serves a dynamic role in brain function, supporting the consolidation of previous experience.fMRI ͉ functional connectivity ͉ perceptual learning ͉ resting state S pontaneous neural activity utilizes the majority of the brain's energy budget, but its function remains mysterious (1-8). At the level of single neurons, embedded in the local circuitry of a cortical area, spontaneous activity has been shown to emulate the pattern of activity evoked by the neuron's optimal stimulus, suggesting that at least at this level of description, spontaneous activity is likely to reflect the history of coactivation within local networks (9). At the level of distributed cortical systems, spontaneous activity measured by blood-oxygen level-dependent (BOLD) functional MRI (fMRI) exhibits covariance structures (or functional connectivity) at ultraslow frequencies (Ͻ0.1 Hz) that are stable across a wide range of behavioral states (anesthesia, task performance, resting wakefulness, and sleep) (10, 11). The topography of BOLD functional connectivity is compatible with both the underlying structural connectivity of the cortex and the functional anatomy of systems engaged by a broad range of tasks (12-16).Studies have suggested that BOLD functional connectivity is largely a physiological marker of anatomical connections or a correlate of intrinsic vascular dynamics without functional or behavioral significance (17). This hypothesis is consistent with t...

Strategy‐based reasoning training modulates cortical thickness and resting‐state functional connectivity in adults with chronic traumatic brain injury

“…First, rsFC is based upon the underlying structural connectivity, and therefore reflects the functional anatomy of brain systems (Damoiseaux et al., 2006). On the other hand, rsFC is also sculpted by the repeated history of coordinated activation between brain regions during experience‐driven activities (Lewis et al., 2009). Our rsFC findings (Figure 6) further support the latter aspect of rsFC by demonstrating training‐related changes in rsFC of injured brain.…”

“…Although there are a variety of differences among training regimes, the prominent changes we observed in between‐network connectivity over within‐network connectivity following training are consistent with the findings of Lewis et al. (2009). R DFPC and R APFC were the most heavily involved in connectivity changes for the SMART group.…”

“…Quantitative MRI‐based morphometry further revealed experience‐dependent brain plasticity in clinical populations such as balance training for Parkinson's disease (Sehm et al., 2014) and physical activity for heart failure, Schizophrenia, and mild cognitive impairment (Alosco et al., 2015; McEwen et al., 2015; Reiter et al., 2015). Training‐induced changes in resting‐state networks in the healthy adult brain have also been reported following motor training (Lewis, Baldassarre, Committeri, Romani, & Corbetta, 2009; Taubert, Lohmann, Margulies, Villringer, & Ragert, 2011), cognitive training (Jolles, van Buchem, Crone, & Rombouts, 2013; Mackey, Miller Singley, & Bunge, 2013; Takeuchi et al., 2013), and physical activity in the elderly (Voss, 2010). In clinical populations, rsFC has also been used to identify changes in resting‐state networks induced by rehabilitation for multiple sclerosis (de Giglio et al., 2016) and stroke (Fan et al., 2015; Varkuti et al., 2013).…”

Brain activity and connectivity during poetry composition: Toward a multidimensional model of the creative process

“…Consistent with reports that these include internally generated thinking [Mason et al, 2007] it is possible that the MPFC and other components of this network facilitate the spontaneous, internal generation of novel ideas during the generation of new poems. Encoding these ideas in language must involve interactions with the perisylvian cortices, and enhanced neural synchronization between these two sets of regions may indicate a more efficient transfer of ideas into text which may itself result from years of training that improves processing efficiency [Lewis et al, 2009]. …”

Mouse optical imaging for understanding resting-state functional connectivity in human fMRI

“…The overall pattern of FC closely resembles anatomical connectivity [2] as well as effective connectivity assessed with electrical microstimulation [3,4]. Moreover, recent studies suggest that FC is sensitive enough to detect network-level functional changes due to behavioral training [5], wakefulness levels [6] and psychiatric diseases [7]. A key assumption underlying FC is that it reflects the large-scale spatiotemporal dynamics of spontaneous neuronal activity [8].…”