HOW-TO #3 BACKGROUND: GENERAL INFORMATION FMRI Experimental Design Studies of functional magnetic resonance imaging (FMRI) employ various types of experiment designs, most of which fall into one of two categories: 1) block design, or 2) event-related design. In this 'How-To', block design and various forms of event-related design will be presented, along with the advantages and disadvantages of using each paradigm. Below is an outline of the experiment designs that will be discussed, along with information regarding randomization of stimulus trials and fixed versus stochastic or "jittered" inter-stimulus intervals (ISI) in rapid event-related design: 1) Block Design 2) Event-Related Design (ER-FMRI) A. "Slow" Event-Related Design B. "Rapid" Event-Related Design 1. Fixed ISI and NON-RANDOMIZED stimulus presentation 2. Fixed ISI and RANDOMIZED stimulus presentation 3. "Jittered" ISI and RANDOMIZED stimulus presentation --------------------------------------------------------------------------- --------------------------------------------------------------------------- 1) BLOCK DESIGN Block design was the first type of experimental paradigm to be used in FMRI research, as well as the first to involve more complex statistical analysis. It is still the most commonly used experimental paradigm in FMRI studies. The block design consists of several discrete epochs of on-off periods, with the "on" representing a period of stimulus presentations, and the "off" referring to a state of rest or baseline. Although blocks may range in duration from 16 seconds to a minute or more (average is about 20-30 seconds), they all share the same basic on-off pattern. These on-off states are alternated throughout the experiment to ensure that signal variation from small changes in scanner sensitivity, subject movement, or attention shifts have a similar effect on the signal responses associated with each of the different states. Below is an example of a block design with two experimental conditions: pictures (red blocks) and words (green blocks), along with their resulting hemodynamic response functions. Once an experiment has been run and the data have been collected, the appropriate statistical analysis must be implemented. With block design, individual trials are not compared. Rather, the underlying hemodynamic responses acquired during one blocked condition are compared to the signals acquired from baseline, or from other blocks involving different task conditions (e.g., "picture" blocks versus "word" blocks). As such, regions of signal activity that change between one condition and another can be identified with considerable statistical power. Advantages of Block Design: * A simple block design is adequate for many types of experiments, especially in early, exploratory stages of research projects. * Block designs allow for considerable experimental flexibility, allowing parametric designs and multi-factorial designs to be employed. * Block design can be especially advantageous and a good starting point for newcomers to the field of FMRI research. * Block design is statistically powerful and straightforward to analyze, as the shape of the response function can be assumed to be simple. Disadvantages of Block Design: * Block design can be predictable and boring, making it prone to potential confounds such as rapid habituation, anticipation, set, or other strategy effects. * It may be difficult to control a specific cognitive state for the relatively long periods of each block. A 'rest' state is rarely true rest, as the mind may wander in a subject who is not engaged in a specific task. * Information regarding activation response time courses cannot be obtained with block design because individual responses are lost within the block. * The high predictability of block design makes it inappropriate for certain cognitive tasks, such as an 'oddball' paradigm where a reaction to an unexpected stimulus is probed. * The BOLD signal may not remain constant across the epoch of interest. Within a block, the underlying hemodynamic response can change from the first trial in the block to the last trial within the block. This result may be a consequence of anticipatory effects. * Block design is not feasible for certain patient populations. For instance, hallucinatory schizophrenics who often display irregular or uncontrollable behaviors cannot be forced into a block design. --------------------------------------------------------------------------- 2) EVENT-RELATED DESIGN (ER-FMRI) Event-related designs associate brain processes with discrete (rather than blocked) events, which may occur at any point in the scanning session. That is, different trials or stimuli are presented in arbitrary sequences. This type of design mimics the format of a behavioral study more closely than block design. With behavioral studies, stimulus events such as pictures or words are presented one at a time, usually in a randomized fashion, and separated by an inter-stimulus interval of a specified length. Advantages of ER-FMRI: * This type of design allows for stimulus events from various experiment conditions (e.g., conditions A, B, and C) to be presented randomly in one run. This type of scenario is not possible with block design. * By detecting signals to individual trial events, ER-FMRI can parallel behavioral studies by examining responses to individual trials rather than blocks of trials. * Event-related paradigms allow for greater flexibility and randomization than block design, leading to more clever and less predictable experiments. * Unlike block design, ER-FMRI allows the experimenter to estimate the hemodynamic response function from a single event type. The hemodynamic response can be identified by averaging data acquired after many discrete events. This approach is more powerful than block design because it allows considerable flexibility for determining, for example, responses to novel or aperiodically presented stimuli, or exploring changes over time. * Post-hoc sorting of stimulus trials can be done with ER-FMRI (e.g., correct vs. incorrect responses, aware vs. unaware, remembered vs. forgotten items, quick vs. slow response times, etc.). Disadvantages of ER-FMRI: * The event-related design requires a greater understanding and grasp of functional MRI because the design and statistical measures that follow are more complex than those of block design. As a result, a newcomer to the world of FMRI may initially encounter some difficulty when attempting to design an event-related study. * One major disadvantage of event-related design involves the signal-to- noise (SNR) ratio. The timing of single events results in a lower SNR for event-related FMRI. Specifically, for block design, the percent signal change may be in the range of 3% to 5% while for event-related design, it may be less than 1%. To compensate for this loss in statistical power, the number of trials should be increased by approximately 50 to 100 trials per condition. The result, however, is longer scanning runs (more on this issue in the sections that follow). The inter-stimulus interval between stimulus trials can vary, and this time interval determines whether the event-related design is identified as 'SLOW' or 'RAPID.' An explanation of slow and rapid event-related design is provided in the sections below. A. SLOW EVENT-RELATED DESIGN Within the scanner, a patient's exposure to a stimulus event may result in a significant increase in brain activation, which is correlated with localized changes in blood flow, oxygenation, and volume. These local increases in blood flow and microvascular oxygenation take some time to occur. The result is a delay in onset of the BOLD signal, which evolves over an extended period of time, even for brief neuronal events. In fact, the "plateau" of the hemodynamic response may not occur until 6-9 seconds after the stimulus onset. The result will be a hemodynamic response function that is spread out, usually far beyond the stimulus duration. This phenomenon is known as "dispersion." On average, one should expect the BOLD signal to rise and fall within 12-20 seconds. When implementing an event-related design, one must consider this post-stimulus delay of the BOLD signal. Stimulus trials spaced too close together will result in an overlapping of their respective hemodynamic response functions, causing them to become "tangled" or convolved. When this happens, more sophisticated statistical measures are required to deconvolve the data. With SLOW event-related design (a.k.a. 'widely spaced' or 'simple' event- related design), the individual stimulus trials are spaced far apart in time to prevent overlap of their hemodynamic functions. In other words, the hemodynamic response that results from a single trial is allowed to rise and fall completely before the next trial begins. Below is an illustration of a slow event-related design, along with the resulting hemodynamic response functions. Advantages of slow event-related design: * Since there is no overlap of the hemodynamic responses, slow event- related paradigms do not require deconvolution analysis and are therefore fairly easy to analyze statistically. Disadvantages of slow event-related design: * The long rest periods between stimulus presentations mitigate habituation, expectation, and boredom, which can taint the experiment with anticipatory effects. * This type of design tends to be extremely time inefficient. Since scanner time is limited, it is wasteful to spend so much time waiting for the hemodynamic response to return to baseline. * In addition to being wasteful, a disproportionate amount of time at baseline results in the collection of less non-baseline data. Since FMRI is a measurement of differences in response signal, it is perhaps more efficient to get half of one's data at or near the baseline state, and half at the non-baseline state. If too much time is spent at baseline, the result is a good estimate of baseline ('small sigma' in statistical terms), but a bad estimate of the activation ('large Sigma'). If too much time is spent in activation, then the reverse is true. However, an equal number of baseline and active trials will increase the likelihood of sucessfully detecting a statistically significant difference in response signal between baseline and non-baseline states. * Compared to block design, the signal-to-noise ratio (SNR) is lost by approximately 33% in slow ER-FMRI. As mentioned before, one way to compensate for this loss in statistical power is to increase the number of trials per condition for event-related averaging. Unfortunately, the additional trials will increase the experiment duration, thus taking up more scanner time. Logistically, this option may not be feasible when employing a slow ER design. B. RAPID EVENT-RELATED DESIGN Rapid event-related design is similar to slow event-related design with the exception that it takes individual stimulus events and spaces them at close intervals. For instance, the ISI may be set to as little as two seconds. The result is a significant overlap of hemodynamic response functions that must later be disentangled to determine the effect of each stimulus condition on brain activation. Advantages of rapid event-related design: * The shorter resting gaps between events leads (hopefully) to a decrease in subject boredom. Thus, rapid ER design is much more resistant to habituation, set, and expectation than slow ER paradigms. * Rapid stimulus presentation makes is possible to adequately squeeze in more stimulus trials per run, thus improving statistical power by increasing the number of responses to be averaged per unit of time. Disadvantages of rapid event-related design: * The signal-to-noise ratio loss is even greater for rapid event-related design than it is for slow ER-FMRI. Specifically, SNR loss is approximately 17% more for rapid ER than for slow ER, and 50% more for rapid ER compared to block design. * The decreased inter-stimulus interval results in hemodynamic responses that overlap substantially. Assuming linearity, the overlapping hemodynamic responses often found in rapid designs must be separated by a statistical process known as deconvolution. In simpler terms, each individual hemodynamic response function must be disentangled so that the effect of each stimulus condition (say, conditions A, B, and C) can be differentiated and measured. This requires greater statistical savvy and know-how on the part of the experimenter. In addition, this overlap problem can only be resolved if the experimental design is properly randomized. (It should become quite clear in the next section why randomization of stimuli is so essential in rapid event-related FMRI). Now that the basics of rapid event-related design have been covered, the issues of proper randomization of stimuli and fixed versus "jittered" inter-stimulus intervals will be discussed. 1. Rapid ER-FMRI: Fixed ISI + NON-randomized stimulus presentation = BAD DESIGN When using an event-related design, it is important to remember that the stimuli must be properly counterbalanced to ensure that each trial type is preceded and followed by each trial type equally often. If this does not happen, the result can be detrimental when it comes time to run the statistics on the data. Primarily, a short, fixed ISI paired with a sequential ordering of the stimulus events can lead to a problem known as "multicollinearity" or "identification problem". The problem of multicollinearity is illustrated below in Figure 3: As Figure 3 demonstrates, it is problematic to combine a short, fixed ISI with a stimulus presentation that always orders the trials in the same exact manner (e.g., A, rest, B, rest, C, rest, A, rest, B, rest, C, rest...). In this example, the responses always overlap in the same way (A followed by B followed by C). As a result, there is much ambiguity as to the source of the observed response. Is the observed sum of the hemodynamic response functions due to stimulus A alone? Is it due to the combined contributions of stimuli A and B? A and C? A, B, and C? It is impossible to answer this question. It is also important to note that multicollinearity is not a problem due to the limitations of statistical programs that calculate the deconvolution of time-series datasets (e.g., AFNI 3dDeconvolve). Rather, the limitation is mathematical in nature. In such a case, it is mathematically impossible to determine the contribution of each individual stimulus trial to the sum of the hemodynamic responses. Fortunately, the resolution to this dilemma can be simple. When implementing a rapid ER design, it is important to randomize the stimulus presentations so that every trial is preceded and followed by every other trial type an equal number of times. The 'AFNI_howto' section of this HowTo provides a script that does this very thing using the AFNI program 'RSFgen' (i.e., Random Stimulus Functions generator). 2. Rapid ER-FMRI: Fixed ISI + RANDOMIZED stimulus presentation = BETTER DESIGN Figure 3 illustrates the detrimental effects of ignoring randomization in rapid event-related design. To successfully deconvolve the overlapping HRF's, a rapid ER design should include every possible combination of trial sequences. Since responses sum in an approximately linear fashion, the responses to rapidly presented stimuli can be extracted from the data if the stimulus presentations are randomly varied. Figure 4 provides an example of such a design and the resulting HRF's: In the above figure, the effort was made to randomize the stimulus trials in a way that ensured successful deconvolution of the overlapping HRF's. By properly counterbalancing the trials, one can now mathematically determine the contribution of each stimulus condition on the observed sum of the hemodynamic responses. Hopefully, these examples demonstrate how taking the time to carefully design and execute an experiment is well worth the effort. The end result will be the collection of 'deconvolvable' data, which can be properly analyzed and understood. 3. Rapid ER-FMRI with "jittered" ISI Up to this point, this HowTo has illustrated examples of FMRI designs involving inter-stimulus intervals that are "fixed." In other words, the ISI remains constant throughout the experiment. However, just as stimulus presentations can be randomized, so can the ISI. With a "jittered" or stochastic stimulus timing, the inter-stimulus interval is randomized throughout the experiment. The result is a varied onset of successive stimulus events, with randomly intervening rest intervals. Below is an example of a rapid event-related design with a jittered inter-stimulus interval: A differential ISI results in an even more differential HRF overlap, further reducing the probability that an experiment design will confront multicollinearity problems. However, these types of designs will be more challenging to analyze. In some cases, differential ISI's are necessary because the timing of the stimulus presentations is determined by the subject. Many behavioral studies implement this type of "self-paced" timing. In other cases, jittered stimulus timing is incorporated into the experiment design because it introduces more overall randomness to the study. This can be a good thing considering subjects are inquisitive creatures who are constantly attempting to "figure out" the experiment. More randomness and unpredictability significantly decreases anticipatory effects. --------------------------------------------------------------------------- --------------------------------------------------------------------------- SUMMARY While block design provides a fairly simple and straightforward approach to creating an experimental paradigm, the habituation and possible hemodynamic lag that afflict a design of this sort is problematic. Furthermore, block design may not be feasible for certain types of cognitive tasks or patient populations. On the other hand, event-related design is more flexible and can introduce randomization of stimulus trials into the experiment, thus mimicking behavioral studies more closely. The downside is that analysis of the data may be more complicated, particularly if the hemodynamic response functions overlap significantly as in the case of rapid event- related design. In addition, the signal-to-noise ratio decreases dramatically with event-related design. When implementing an event-related design, one must decide between a fixed or "jittered" inter-stimulus interval, and appreciate the benefits of proper counterbalancing of stimulus events. One must also choose between a "slow" or "rapid" ISI, and consider the pros and cons of each. While slow ER design avoids the overlap of hemodynamic response functions, the longer ISI mitigates habituation and results in the collection of less non-baseline data. Conversely, rapid ER design is less boring and more non-baseline data can be obtained, but the substantial overlap of hemodynamic response functions reduces the SNR ratio and requires more complex deconvolution measures. Given the advantages and disadvantages of each research paradigm, many researchers are opting for the best of both worlds by creating experiments that incorporate both block and event-related design. Ultimately, it is up to the user to decide which particular design (or combination) is most suitable for their experimental needs. Whichever paradigm one decides to implement, it is important that the experiment design be thought out and planned well in advance. One should consider which experimental paradigm will be best for the cognitive phenomenon being examined and the patient population being tested. Likewise, one should consider which statistical measures are appropriate for the data being gathered. By doing so, the scanning process, data collection, and statistical analysis will go much smoother.