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Volitional eyes opening perturbs brain dynamics and functional connectivity regardless of light input.

ABSTRACT: The act of opening (or closing) one's eyes has long been demonstrated to impact on brain function. However, the eyes open condition is usually accompanied by visual input, and this effect may have been a significant confounding factor in previous studies. To clarify this situation, we extended the traditional eyes open/closed study to a two-factor balanced, repeated measures resting state fMRI (rs-fMRI) experiment, in which light on/off was also included as a factor. In 16 healthy participants, we estimated the univariate properties of the BOLD signal, as well as a bivariate measure of functional connectivity and multivariate network topology measures. Across all these measures, we demonstrate that human brain adopts a distinctive configuration when eyes are open (compared to when eyes are closed) independently of exogenous light input: (i) the eyes open states were associated with decreased BOLD signal variance (P-value=0.0004), decreased fractional amplitude of low frequency fluctuation (fALFF. P-value=0.0061), and decreased Hurst exponent (H. P-value=0.0321) mainly in the primary and secondary sensory cortical areas, the insula, and the thalamus. (ii) The strength of functional connectivity (FC) between the posterior cingulate cortex (PCC), a major component of the default mode network (DMN), and the bilateral perisylvian and perirolandic regions was also significantly decreased during eyes open states. (iii) On the other hand, the average network connection distance increased during eyes open states (P-value=0.0139). Additionally, the metrics of univariate, bivariate, and multivariate analyses in this study are significantly correlated. In short, we have shown that the marked effects on the dynamics and connectivity of fMRI time series brought by volitional eyes open or closed are simply endogenous and irrespective of exogenous visual stimulus. The state of eyes open (or closed) may thus be an important factor to control in design of rs-fMRI and even other cognitive block or event-related experiments.

SUBMITTER: Jao T

PROVIDER: S-EPMC9317210 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Introduction: Previous studies have shown significant conditional differences between eyes open, fixated at an image (EO) and eyes closed (EC) in the acquired resting-state functional magnetic resonance imaging (rs-fMRI) data. Aim: We recently showed significant functional network connectivity (FNC) differences between EO and EC across a variety of networks. In this study, we aim at further evaluating differences in dynamic FNC (dFNC) between EO and EC. Materials and Methods: Rs-fMRI were collected from adolescents aged 9-15 years old during both EO and EC conditions, and dFNC was calculated by using the independent component analysis framework. Results: We found that out of five states (clusters), state 1 was observed to be more dominant in the EO condition, whereas state 2 was observed to be more dominant in the EC condition. States 1 and 2 showed significant differences in the mean dwell time based on false discovery rate, and states 1, 2, 3, and 4 differed in the frequency of occurrences. These results are consistent with our previous study of static connectivity in suggesting that EO and EC differences not only are relatively strong but also importantly reveal that these differences vary over time, especially in one particularly transient connectivity pattern. Conclusion: Our results manifest as changes in the proportion of time spent in unique functional connectivity patterns, and they show unique transient functional connectivity patterns in a subset of identified states. Overall, our findings indicate that both static and dynamic rs-fMRI connectivity patterns are strongly impacted by basic conditional differences such as EO and EC. Impact statement Our findings not only suggest that eyes open, fixated at an image (EO) and eyes closed (EC) condition-related resting state functional magnetic resonance imaging differences are relatively strong, but they also reveal an important attribute of these conditions that these differences vary over time, especially in one particularly transient connectivity pattern. Our results manifest as changes in the proportion of time spent in unique functional connectivity patterns, and they show unique transient functional connectivity patterns in a subset of identified states. We believe there is benefit in having the EO/EC as a contrast of interest in future studies, if time allows.

Project description:Brain-machine interfaces allow neuroscientists to causally link specific neural activity patterns to a particular behaviour. Thus, in addition to their current clinical applications, brain-machine interfaces can also be used as a tool to investigate neural mechanisms of learning and plasticity in the brain. Decades of research using such brain-machine interfaces have shown that animals (non-human primates and rodents) can be operantly conditioned to self-regulate neural activity in various motor-related structures of the brain. Here, we ask whether the human brain, a complex interconnected structure of over 80 billion neurons, can learn to control itself at the most elemental scale-a single neuron. We used the unique opportunity to record single units in 11 individuals with epilepsy to explore whether the firing rate of a single (direct) neuron in limbic and other memory-related brain structures can be brought under volitional control. To do this, we developed a visual neurofeedback task in which participants were trained to move a block on a screen by modulating the activity of an arbitrarily selected neuron from their brain. Remarkably, participants were able to volitionally modulate the firing rate of the direct neuron in these previously uninvestigated structures. We found that a subset of participants (learners), were able to improve their performance within a single training session. Successful learning was characterized by (i) highly specific modulation of the direct neuron (demonstrated by significantly increased firing rates and burst frequency); (ii) a simultaneous decorrelation of the activity of the direct neuron from the neighbouring neurons; and (iii) robust phase-locking of the direct neuron to local alpha/beta-frequency oscillations, which may provide some insights in to the potential neural mechanisms that facilitate this type of learning. Volitional control of neuronal activity in mnemonic structures may provide new ways of probing the function and plasticity of human memory without exogenous stimulation. Furthermore, self-regulation of neural activity in these brain regions may provide an avenue for the development of novel neuroprosthetics for the treatment of neurological conditions that are commonly associated with pathological activity in these brain structures, such as medically refractory epilepsy.

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Volitional eyes opening perturbs brain dynamics and functional connectivity regardless of light input.

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