Silvia Tommasin1,2, Daniele Mascali1,3, Tommaso Gili1,2, and Federico Giove1,2
1Enrico Fermi Centre, Rome, Italy, 2Fondazione Santa Lucia, Roma, Italy, 3Physics, Università La Sapienza, Roma, Italy
Synopsis
Task-related activity influences brain connectivity through a two-level pattern modulation both in attentive networks and in the default mode network. While strengthening the local homogeneity, task execution reduces regional synchronization. It produces correlation patterns with opposite large and small scale properties.
Task-related activity influences also the amplitude of the low frequency fluctuations in the same networks. The transition from resting state to steady state task execution, and the way back, causes a persisting slow drift in this quantity.Purpose
We investigated the pattern of modulation induced by working memory tasks on connectivity strength and spectral properties of resting state networks (RSN) to better understand how the reorganisation of intrinsic network activity does occur.
Introduction
Relationships among and within networks during resting state (RS) and task execution (TS) are still to be clarified. Ongoing spontaneous activity in the brain has been observed and has claimed to influence behaviour1 and task-evoked response in task-positive networks2. In response to attention-demanding tasks a reorganisation of intrinsic network activity occurs and reduced task-unrelated activity in the DMN keeps going3.
Full literature investigated the characterisation of steady state task-related changes of brain networks, what is still unclear is how connectivity is spatially and dynamically influenced by TS. We investigated how activation by TS influences 1. large and small scale connectivity and 2. the amplitude of low frequencies fluctuation.
Methods and Results
Ten healthy right handed subjects (age = 30 +/- 5), native italian, were scanned at 3T (Siemens Allegra system). Functional data were collected by using a 2D gradient echo planar sequence (TR/TE=2100/30ms, Flip Angle= 70deg, 3x3x2.5mm3 voxels), covering the whole brain with 33 slices, with 1.25mm skip, parallel to the anterior/posterior commisure plane. Sagittal, T1 weighted structural data were acquired at high resolution (TR/TE = 2000/4.38ms, Flip Angle= 8deg, 1.33x1.33x1mm3). During experiments, respiration and cardiac signals were recorded by using a photoplethysmograph and a pneumatic belt, respectively. Four subjects were excluded from the study because they accomplished only half of the experiment.
The experimental paradigm included a steady state recording of five alternated conditions of resting state (RS) and task (TS), lasting 5 minutes each. During rest participants laid in the scanner with open eyes, during task they were presented by a continuous n-back auditory working memory task (n=1,2). The experimental paradigm was repeated twice for each subject.
We used both seed to voxel correlation (StV4) and regional homogeneity (ReHo5) to detect networks reaction to RS and TS at large and small spatial scales. We also studied the fractional amplitude of slow frequency oscillations (fALFF6,7) to highlight networks slow dynamics. Among the resting state networks we considered those specifically related to the execution of working memory tasks: dorsal and ventral attention (DA, VA) and default mode network (DMN)
Fig. 1 shows the considered RSNs during the alternated experimental conditions. When involved in task execution networks’ within-connectivity significantly weakens on a large scale, as shown by StV, and increases on a small scale, as assessed by ReHo. All the changes found were statistically significant at p<0.05.
Fig. 2 reports the behaviour of fALFF within each experimental condition. Barplots show the slightly increasing drift during task conditions (intervals 6-10 and 16-20) and a decreasing drift during RS. It is better described in the nearby graphs, that show the distribution of fALFF-slopes across those voxels belonging to each of the ROIs. The curves have been tested for mean changes (p<0.001, bootstrap n = 1000). The calculated means and related standard deviations are reported in the figure. They confirm the positive/negative drift of TS/RS, whose estimate is 0.6% change per minute.
Discussion and Conclusions
We investigated the multi-scale modulation of functional connectivity induced by TS and how it influences the amplitude of low frequencies fluctuations of RS networks proved to be influenced by attention-demanding tasks3 .
Our findings show that the outcoming pattern of connectivity modulation is a characterized by the coexistence of two opposite trends: local weak connections tends to get stronger during TS, while regional correlations results to be stronger at rest. Furthermore we found a drift in the spectral amplitudes of fluctuations passing from the RS to the TS condition. Our findings can be considered as tools to probe the level of network corruption induced both by neurological8 and psychiatric diseases9.
Acknowledgements
No acknowledgement found.References
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