Connectivity-based neurofeedback: Dynamic causal modeling for real-time fMRI

Neurofeedback based on real-time fMRI is an emerging technique that can be used to train voluntary control of brain activity. Such brain training has been shown to lead to behavioral effects that are specific to the functional role of the targeted brain area. However, real-time fMRI-based neurofeedback so far was limited to mainly training localized brain activity within a region of interest. Here, we overcome this limitation by presenting near real-time dynamic causal modeling in order to provide feedback information based on connectivity between brain areas rather than activity within a single brain area. Using a visual-spatial attention paradigm, we show that participants can voluntarily control a feedback signal that is based on the Bayesian model comparison between two predefined model alternatives, i.e. the connectivity between left visual cortex and left parietal cortex vs. the connectivity between right visual cortex and right parietal cortex. Our new approach thus allows for training voluntary control over specific functional brain networks. Because most mental functions and most neurological disorders are associated with network activity rather than with activity in a single brain region, this novel approach is an important methodological innovation in order to more directly target functionally relevant brain networks. (C) 2013 The Authors. Published by Elsevier Inc. All rights reserved.

Self-regulation of inter-hemispheric visual cortex balance through real-time fMRI neurofeedback training

Yury Koush, Frank Scharnowski, Dimitri Nestor Alice Van De Ville

Recent advances in neurofeedback based on real-time functional magnetic resonance imaging (fMRI) allow for learning to control spatially localized brain activity in the range of millimeters across the entire brain. Realtime fMRI neurofeedback studies have demonstrated the feasibility of self-regulating activation in specific areas that are involved in a variety of functions, such as perception, motor control, language, and emotional processing. In most of these previous studies, participants trained to control activity within one region of interest (ROI). In the present study, we extended the neurofeedback approach by now training healthy participants to control the interhemispheric balance between their left and right visual cortices. This was accomplished by providing feedback based on the difference in activity between a target visual ROI and the corresponding homologue region in the opposite hemisphere. Eight out of 14 participants learned to control the differential feedback signal over the course of 3 neurofeedback training sessions spread over 3 days, i.e., they produced consistent increases in the visual target ROI relative to the opposite visual cortex. Those who learned to control the differential feedback signal were subsequently also able to exert that control in the absence of neurofeedback. Such learning to voluntarily control the balance between cortical areas of the two hemispheres might offer promising rehabilitation approaches for neurological or psychiatric conditions associated with pathological asymmetries in brain activity patterns, such as hemispatial neglect, dyslexia, or mood disorders. (C) 2014 Elsevier Inc. All rights reserved.

Elsevier2014

Evolution amplified processing with temporally dispersed slow neuronal connectivity in primates

Hassan Ghaziri, Giorgio Innocenti

The corpus callosum (CC) provides the main route of communication between the 2 hemispheres of the brain. In monkeys, chimpanzees, and humans, callosal axons of distinct size interconnect functionally different cortical areas. Thinner axons in the genu and in the posterior body of the CC interconnect the prefrontal and parietal areas, respectively, and thicker axons in the midbody and in the splenium interconnect primary motor, somatosensory, and visual areas. At all locations, axon diameter, and hence its conduction velocity, increases slightly in the chimpanzee compared with the macaque because of an increased number of large axons but not between the chimpanzee and man. This, together with the longer connections in larger brains, doubles the expected conduction delays between the hemispheres, from macaque to man, and amplifies their range about 3-fold. These changes can have several consequences for cortical dynamics, particularly on the cycle of interhemispheric oscillators.

National Academy of Sciences2009

Real-time automated spectral assessment of the BOLD response for neurofeedback at 3 and 7 T

Yury Koush, Frank Scharnowski

Echo-planar imaging is the dominant functional MRI data acquisition scheme for evaluating the BOLD signal. To date, it remains the only approach providing neurofeedback from spatially localized brain activity. Real-time functional single-voxel proton spectroscopy (fSVPS) may be an alternative for spatially specific BOLD neurofeedback at 7T because it allows for a precise estimation of the local T2* signal, EPI-specific artifacts may be avoided, and the signal contrast may increase. In order to explore and optimize this alternative neurofeedback approach, we tested fully automated real-time fSVPS spectral estimation procedures to approximate T2* BOLD signal changes from the unsuppressed water peak, i.e. lorentzian non-linear complex spectral fit (LNLCSF) in frequency and frequency-time domain. The proposed approaches do not require additional spectroscopic localizers in contrast to conventional T2* approximation based on linear regression of the free induction decay (FID). For methods comparison, we evaluated quality measures for signals from the motor and the visual cortex as well as a real-time feedback condition at high (3 T) and at ultra-high (7T) magnetic field strengths. Using these methods, we achieved reliable and fast water peak spectral parameter estimations. At 7T, we observed an absolute increase of spectra line narrowing due to the-BOLD effect, but quality measures did not improve due to artifactual line broadening. Overall, the automated fSVPS approach can be used to assess dynamic spectral changes in real-time, and to provide localized T2* neurofeedback at 3 and 7T. (c) 2013 Elsevier B.V. All rights reserved.

Elsevier2013