Basis for fMRI

fMRI is of course based on MRI, which in turn uses nuclear magnetic resonance coupled with gradients in magnetic field to create images that can incorporate many different types of contrast such as T1 weighting, T2 weighting, susceptibility, flow, and so forth. To understand the particular contrast mechanism predominantly used in fMRI it is necessary to first discuss brain metabolism.

All the processes of neural signaling in the brain, including formation and propagation of action potentials, binding of vesicles to the presynaptic junction, the release of neurotransmitters across the synaptic gap, their reception and regeneration of action potentials in the postsynaptic structures, scavenging of excess neurotransmitters, and so forth, require energy in the form of adenosine triphosphate (ATP). This nucleotide is produced principally by the mitochondria from glycolytic oxygenation of glucose, and its production results in carbon dioxide as a by-product. When a region of the brain is upregulated (ie, activated) by a cognitive task such as finger tapping, the additional neural firing and other increased signaling processes result in a locally increased energy requirement, in turn resulting in upregulated cerebral metabolic rate of oxygen (CMRO ₂ ) in the affected brain region. As the local stores of oxygen in tissues adjacent to capillaries are transiently consumed by glycolysis and waste products build up, various chemical signals (CO ₂ , NO, H ⁺ ) cause a vasomotor reaction in arterial sphincters upstream of the capillary bed, causing dilation of these vessels. The increased blood flow acts to restore the local [O ₂ ] level required to overcome the transient deficit; however, for reasons that are still not fully understood more oxygen is delivered than is needed to offset the increase in CMRO ₂ . As a result, neural upregulation results initially in a buildup of deoxygenated hemoglobin (Hb) and a decrease in oxygenated hemoglobin (HbO ₂ ) in the intra- and extravascular spaces, followed within a second or two by a vasodilatory response that reverses the situation to result in an increase in [HbO ₂ ] and decrease in [Hb] over that in the resting condition ( Fig. 1 ). This sequence of processes is described as the hemodynamic response to the neural event.

Sketch of brain tissue containing a capillary during rest ( top ) and activation ( bottom ). Red and blue circles represent red blood cells that are fully oxygenated (HbO ₂ ) and fully deoxygenated (Hb), respectively. The MRI signal is depressed in the venous side of the capillary due to the paramagnetic susceptibility of the Hb acting as an endogenous contrast agent (shown darker). In the stimulated condition, increased blood flow causes the Hb to be swept out and replaced by HbO ₂ , causing a BOLD signal increase.

Thus, there are 2 primary consequences of increased neural activity, and both can be detected by MRI: increased local cerebral blood flow (CBF) and changes in oxygenation concentration (Blood Oxygen Level Dependent, or BOLD, contrast). The change in CBF can be observed using an injected contrast agent and perfusion-weighted MRI, first demonstrated by Belliveau and colleagues, or noninvasively by arterial spin labeling (ASL). However, ASL suffers from reduced sensitivity, increased acquisition time, and increased sensitivity to motion compared with the BOLD contrast method, and its use has therefore centered on obtaining quantitative measurements of baseline CBF for studies modeling the neurobiological mechanisms of activation or calibration of vasoreactivity, rather than in routine mapping of brain function.

The second mechanism, termed BOLD contrast, was first demonstrated in rats and later in humans, and is the contrast that is used in virtually all conventional fMRI experiments. BOLD contrast results from the change in magnetic field surrounding the red blood cells depending on the oxygen state of the hemoglobin. When fully oxygenated, HbO ₂ is diamagnetic and is magnetically indistinguishable from brain tissue. However, fully deoxygenated Hb has 4 unpaired electrons and is highly paramagnetic. This paramagnetism results in local gradients in magnetic field whose strength depends on the [Hb] concentration. These endogenous gradients in turn modulate the intra- and extravascular blood’s T2 and T2* relaxation times through diffusion and intravoxel dephasing, respectively. Using a gradient refocused echo (GRE) MRI pulse sequence, the acquisition is made sensitive to T2* and T2. At 1.5 T and 3 T, the T2* contrast is predominant and is largest in venules, whereas at higher field strength the diffusion-weighted contrast of T2 relaxation becomes more important and, because signals are generated preferentially in capillaries and tissue with spin-echo acquisitions, provides greater spatial specificity. Because most fMRI is currently performed at 3 T or below, BOLD fMRI uses primarily GRE methods because of the increased T2* contrast.

Task activation fMRI studies seek to induce different neural states in the brain as the visual, auditory, or other stimulus is manipulated during the scan, and activation maps are obtained by comparing the signals recorded during the different states. Therefore, it is important to collect each image in a snapshot mode to avoid head motion, and prevent physiologic processes of respiration and cardiovascular functions from injecting noise signals unrelated to the neural processing being interrogated. In general, most fMRI is performed using an echo planar imaging (EPI) method, which can collect data for a 2-dimensional image in approximately 60 milliseconds at typical resolutions (3.4 × 3.4 × 4 mm ³ voxel size). Whole brain scans with approximately 32 2-dimensional slices typically are acquired with a repetition time (TR) of 2 seconds per volume. Each voxel in the resulting scan produces a time series that is subsequently analyzed in accordance with the task design.

The fMRI experiment

The typical fMRI task activation experiment uses visual, auditory, or other stimuli to alternately induce 2 or more different cognitive states in the subject, while collecting MRI volumes continuously as already described. With a 2-condition design, one state is called the experimental condition and the other is denoted the control condition; the goal is to test the hypothesis that the signals differ between the 2 states. Using a block design, the trials are arranged to alternate between the experimental and control conditions, as shown in Fig. 2 , with each block typically being a few tens of seconds long. The block design is optimum for detecting activation, but a jittered event-related (ER) design is superior when characterization of the amplitude or timing of the hemodynamic response is desired. In the ER design, task events are relatively brief and occur at nonconstant intertrial intervals with longer periods of control condition, which allows the hemodynamic response to return more fully to baseline. Jittering the timing serves to sample the hemodynamic response with higher temporal frequency in the overall time series, but may also be used to induce a desired cognitive strategy, for example, to avoid an anticipatory response or maintain attention.

Block-design fMRI experiment. A neural response to the state change from A to B in the stimulus is accompanied by a hemodynamic response (as shown in Fig. 1 ) that is detected by the rapid and continuous acquisition of MR images sensitized to BOLD signal changes. Using single or multivariate time series analysis methods, the average signal difference between the 2 states is computed for the scan and a contrast map generated. A statistical activation map is finally obtained using a suitable threshold for the difference; the map depicts the probability that a voxel is activated, given the uncertainty due to noise and the small BOLD signal differences.

The degree to which valid inferences can be drawn from the measured time series data depends in large part on careful design of the task. The investigator must take care that only the effect of interest changes between experimental and control conditions, while confounding effects such as attention and valence are maintained constant or irrelevant. In some studies this is straightforward, such as in the use of a sensory task for presurgical mapping, where the goal is only to localize activation so that important brain functions can be maintained after surgery. In this case the signal intensity is of minor interest as long as it is adequate to characterize the functional substrates to be preserved during surgical intervention. In many other cases, however, comparative inferences are desired, such as in parametric studies of the influence of task difficulty on a cognitive process, and thus control of such factors as learning, adaptation, and salience must be considered.

The fMRI experiment

The typical fMRI task activation experiment uses visual, auditory, or other stimuli to alternately induce 2 or more different cognitive states in the subject, while collecting MRI volumes continuously as already described. With a 2-condition design, one state is called the experimental condition and the other is denoted the control condition; the goal is to test the hypothesis that the signals differ between the 2 states. Using a block design, the trials are arranged to alternate between the experimental and control conditions, as shown in Fig. 2 , with each block typically being a few tens of seconds long. The block design is optimum for detecting activation, but a jittered event-related (ER) design is superior when characterization of the amplitude or timing of the hemodynamic response is desired. In the ER design, task events are relatively brief and occur at nonconstant intertrial intervals with longer periods of control condition, which allows the hemodynamic response to return more fully to baseline. Jittering the timing serves to sample the hemodynamic response with higher temporal frequency in the overall time series, but may also be used to induce a desired cognitive strategy, for example, to avoid an anticipatory response or maintain attention.

Block-design fMRI experiment. A neural response to the state change from A to B in the stimulus is accompanied by a hemodynamic response (as shown in Fig. 1 ) that is detected by the rapid and continuous acquisition of MR images sensitized to BOLD signal changes. Using single or multivariate time series analysis methods, the average signal difference between the 2 states is computed for the scan and a contrast map generated. A statistical activation map is finally obtained using a suitable threshold for the difference; the map depicts the probability that a voxel is activated, given the uncertainty due to noise and the small BOLD signal differences.

The degree to which valid inferences can be drawn from the measured time series data depends in large part on careful design of the task. The investigator must take care that only the effect of interest changes between experimental and control conditions, while confounding effects such as attention and valence are maintained constant or irrelevant. In some studies this is straightforward, such as in the use of a sensory task for presurgical mapping, where the goal is only to localize activation so that important brain functions can be maintained after surgery. In this case the signal intensity is of minor interest as long as it is adequate to characterize the functional substrates to be preserved during surgical intervention. In many other cases, however, comparative inferences are desired, such as in parametric studies of the influence of task difficulty on a cognitive process, and thus control of such factors as learning, adaptation, and salience must be considered.

Analysis methods

Once the images have been acquired, the time series data must be processed to obtain maps of brain activation. Because the BOLD contrast is small (<1% in many studies of higher cognitive processes), simply averaging images over the experimental and control conditions and then subtracting (as sketched in Fig. 2 ) is inadequate to reliably determine differences because noise will compete to render false positives and negatives. The noise results from thermal sources in the subject and electronics, bulk motion of the head, cardiac and respiratory-induced noise, and variations in baseline neural metabolism. Because the noise can sometimes be larger than the signal of interest, fMRI analyses compare the signal difference between the states using a statistical test. These tests result in an activation map that is a function of the probability that the brain states differ. The statistical test for activation can use a general linear model, cross-correlation with a modeled regressor, or one of several data-driven approaches such as independent components analysis. The models against which the acquired data are tested include the experimental design of interest as well as “nuisance regressors” of no interest such as signal drift, motion, and noise reflected in global or white-matter signals. In all cases, the activation testing is preceded by a series of preprocessing steps.

The steps in preprocessing can include all or some of the following: (1) time-slice correction, to eliminate differences between the time of acquisition of each slice in the volume; (2) motion coregistration, in which affine head motion is detected and the time series of volumes is resampled to register each time frame to a reference frame, such as the first or middle time series point; (3) correction for physiologic noise from breathing and cardiovascular function, low pass and/or high pass temporal filtering to improve the statistics while removing spectral components of no interest; (4) spatial smoothing to improve the signal to noise ratio (SNR) and improve the normality of the noise distribution; (5) prewhitening to correct for autocorrelation in the time series. The analysis of fMRI data continues to be a subject of intense research at this time, and is one about which numerous books have been written, to which the reader is referred for further information (eg, Sarty ).

Comparisons with other functional imaging modalities

fMRI can be compared with other imaging methods used to obtained functional assessment of brain metabolism in terms of spatial and temporal resolution and availability. The primary alternatives are positron emission tomography (PET), near-infrared spectroscopy (NIRS), electroencephalography (EEG), and magnetoencephalography (MEG).