Resting state fMRI


Resting state fMRI is a method of functional magnetic resonance imaging that is used in brain mapping to evaluate regional interactions that occur in a resting or task-negative state, when an explicit task is not being performed. A number of resting-state conditions are identified in the brain, one of which is the default mode network. These resting brain state conditions are observed through changes in blood flow in the brain which creates what is referred to as a blood-oxygen-level dependent signal that can be measured using fMRI.
Because brain activity is intrinsic, present even in the absence of an externally prompted task, any brain region will have spontaneous fluctuations in BOLD signal. The resting state approach is useful to explore the brain's functional organization and to examine if it is altered in neurological or mental disorders. Resting-state functional connectivity research has revealed a number of networks which are consistently found in healthy subjects, different stages of consciousness and across species, and represent specific patterns of synchronous activity.

Basics of fMRI

Functional magnetic resonance imaging is a specific magnetic resonance imaging procedure that measures brain activity by detecting associated changes in blood flow. More specifically, brain activity is measured through low frequency BOLD signal in the brain.
The procedure is similar to MRI but uses the change in magnetization between oxygen-rich and oxygen-poor blood as its basic measure. This measure is frequently corrupted by noise from various sources and hence statistical procedures are used to extract the underlying signal. The resulting brain activation can be presented graphically by color-coding the strength of activation across the brain or the specific region studied. The technique can localize activity to within millimeters but, using standard techniques, no better than within a window of a few seconds.
FMRI is used both in research, and to a lesser extent, in clinical settings. It can also be combined and complemented with other measures of brain physiology such as EEG and NIRS. Arterial spin labeling fMRI can be used as a complementary approach for assessing resting brain functions.

Physiological basis

The physiological blood-flow response largely decides the temporal sensitivity, how well neurons that are active can be measured in BOLD fMRI. The basic time resolution parameter is the sampling rate, or TR, which dictates how often a particular brain slice is excited and allowed to lose its magnetization. TRs could vary from the very short to the very long. For fMRI specifically, the haemodynamic response is assumed to last over 10 seconds, rising multiplicatively, peaking at 4 to 6 seconds, and then falling multiplicatively. Changes in the blood-flow system, the vascular system, integrate responses to neuronal activity over time. Because this response is a smooth continuous function, sampling with faster TRs helps only to map faster fluctuations like respiratory and heart rate signals.
While fMRI strives to measure the neuronal activity in the brain, the BOLD signal can be influenced by many other physiological factors other than neuronal activity. For example, respiratory fluctuations and cardiovascular cycles affect the BOLD signal being measured in the brain and therefore are usually tried to be removed during processing of the raw fMRI data. Due to these sources of noise, there have been many experts who have approached the idea of resting state fMRI very skeptically during the early uses of fMRI. It has only been very recently that researchers have become confident that the signal being measured is not an artifact caused by other physiological function.
Resting state functional connectivity between spatially distinct brain regions reflects the repeated history of co-activation patterns within these regions, thereby serving as a measure of plasticity.

History

Bharat Biswal
Marcus Raichle

Connectivity

Functional

Functional connectivity is the connectivity between brain regions that share functional properties. More specifically, it can be defined as the temporal correlation between spatially remote neurophysiological events, expressed as deviation from statistical independence across these events in distributed neuronal groups and areas. This applies to both resting state and task-state studies. While functional connectivity can refer to correlations across subjects, runs, blocks, trials, or individual time points, resting state functional connectivity focuses on connectivity assessed across individual BOLD time points during resting conditions. Functional connectivity has also been evaluated using the perfusion time series sampled with arterial spin labeled perfusion fMRI. Functional connectivity MRI, which can include resting state fMRI and task-based MRI, might someday help provide more definitive diagnoses for mental health disorders such as bipolar disorder and may also aid in understanding the development and progression of post-traumatic stress disorder as well as evaluate the effect of treatment. Functional connectivity has been suggested to be an expression of the network behavior underlying high level cognitive function partially because unlike structural connectivity, functional connectivity often changes on the order of seconds as in the case of dynamic functional connectivity.

Networks

Default mode network
Other resting state networks

Analyzing data

Processing data

Many programs exist for the processing and analyzing of resting state fMRI data. Some of the most commonly used programs include SPM, AFNI, FSL, CONN, , and Connectome Computation System.

Methods of analysis

There are many methods of both acquiring and processing rsfMRI data. The most popular methods of analysis focus either on independent components or on regions of correlation.
Independent component analysis
Regional analysis
Other methods for characterizing resting-state networks include partial correlation, coherence and partial coherence, phase relationships, dynamic time warping distance, clustering, and graph theory.

Reliability and reproducibility

Resting-state functional magnetic resonance imaging can image low-frequency fluctuations in the spontaneous brain activities, representing a popular tool for macro-scale functional connectomics to characterize inter-individual differences in normal brain function, mind-brain associations, and the various disorders. This suggests reliability and reproducibility for commonly used rfMRI-derived measures of the human brain functional connectomics. These metrics hold great potentials of accelerating biomarker identification for various brain diseases, which call the need of addressing reliability and reproducibility at first place.

Combining imaging techniques

fMRI with EEG
Many imaging experts feel that in order to obtain the best combination of spatial and temporal information from brain activity, both fMRI as well as electroencephalography should be used simultaneously. This dual technique combines the EEG's well documented ability to characterize certain brain states with high temporal resolution and to reveal pathological patterns, with fMRI's ability to image blood dynamics through the entire brain with high spatial resolution. Up to now, EEG-fMRI has been mainly seen as an fMRI technique in which the synchronously acquired EEG is used to characterize brain activity across time allowing to map the associated haemodynamic changes.
The clinical value of these findings is the subject of ongoing investigations, but recent researches suggest an acceptable reliability for EEG-fMRI studies and better sensitivity in higher field scanner. Outside the field of epilepsy, EEG-fMRI has been used to study event-related brain responses and provided important new insights into baseline brain activity during resting wakefulness and sleep.
fMRI with TMS
Transcranial magnetic stimulation uses small and relatively precise magnetic fields to stimulate regions of the cortex without dangerous invasive procedures. When these magnetic fields stimulate an area of the cortex, focal blood flow increases at the site of stimulation as well as at distant sites anatomically connected to the stimulated location. Positron emission tomography can then be used to image the brain and changes in blood flow and results show very similar regions of connectivity confirming networks found in fMRI studies and TMS can also be used to support and provide more detailed information on the connected regions.

Potential pitfalls

Potential pitfalls when using rsfMRI to determine functional network integrity are contamination of the BOLD signal by sources of physiological noise such as heart rate, respiration, and head motion. These confounding factors can often bias results in studies where patients are compared to healthy controls in the direction of hypothesized effects, for example a lower coherence might be found in the default network in the patient group, while the patient groups also moved more during the scan. Also, it has been shown that the use of global signal regression can produce artificial correlations between a small number of signals. Fortunately, the brain has many signals.

Current and future applications

Research using resting state fMRI has the potential to be applied in clinical context, including use in the assessment of many different diseases and mental disorders.
Disease Condition and Changes in Resting State Functional Connectivity
Other types of current and future clinical applications for resting state fMRI include identifying group differences in brain disease, obtaining diagnostic and prognostic information, longitudinal studies and treatment effects, clustering in heterogeneous disease states, and pre-operative mapping and targeting intervention. As resting state measurements have no cognitive demands, cognitively impaired persons can also be measured easily.