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fMRI of the Stop Signal Task: What computations support "stopping"?

Right inferior frontal cortex (rIFC) is thought by some to implement "inhibition" of motor responses when they must be abruptly stopped (as in the Stop Signal paradigm). It is still unclear how rIFC might actually accomplish this, and even if it does that in the first place. Nonetheless, this paper from the Journal of Neuroscience makes great strides in establishing the neural mechanisms of response inhibition.

Authors Aron & Poldrack argue that rIFC may target a region of the basal ganglia known as subthalamic nucleus (STN). The STN is a special region of basal ganglia in that it is thought to excite the internal/medial globus pallidus as well as the substantia nigra pars reticulata, both of which then inhibit the thalamus. Thus, the end result of rIFG activation may be a general "clamping down" of thalamic output, if the rIFG does indeed target the STN - this is known as the "hyperdirect pathway."

It is not controversial that STN accomplishes such inhibition both neurally and behaviorally. Aron & Poldrack review evidence showing that STN stimulation improves stop signal reaction time (thought to be a measure of how much time is required for subjects to "cancel" a motor action). Likewise, STN damage decreases stop signal reaction time.

What is controversial, however, is the existence of the "hyperdirect pathway" whereby rIFG directly activates STN and thus inhibits cortical activity. The more commonly accepted mechanism is known as the "indirect pathway," in which cortical areas activate striatal pathways, which themselves disinhibit STN, by inhibiting the external globus pallidus (you can probably see where it gets its name!).

To identify which of these two possible neural networks are active in motor inhibition, the authors put 18 healthy, right-handed adults into an fMRI scanner, where they were presented with a screen containing either a left- or right-pointing arrow. Each subject was told to press a corresponding left or right key, unless a sound was played after the presentation of the arrow, in which case subjects had to refrain from pressing the button (although this sound was only played on 25% of trials). The delay between the display of the arrow and the onset of the sound was dynamically calibrated to each subject while in the scanner, such that each subject was getting around 50% of the "stop trials" correct and 50% incorrect. The value of this delay is known as the stop signal delay, or SSD. This is then subtracted from the median reaction time on go trials to arrive at the stop signal reaction time, or SSRT.

The classic interpretation of SSRT is that it represents the rate of diffusion of a "stopping process," whereas the reaction time on normal go trials represents the rate of diffusion of a "go process." This is known as Logan's race model. The behavioral results were largely in line with this conceptual model, and showed that SSRT and RT on go trials were uncorrelated, supporting the "race model's" assumption that processes involved in "stop" and "go" trials are distinct. Secondly, the median reaction time for incorrect stop trials (i.e., where subjects incorrectly made a response) was faster than the median reaction time on correct go trials, which is again consistent with the race model. SSRTs were within the normal range of around 120 ms.

The fMRI results showed that all "stop" trials were associated with activity in right inferior frontal cortex and STN, consistent with the hyperdirect account. However, failed "stop" trials demonstrated strongly decreased motor cortex activity (M1) towards the end of each trial relative to both Go trials and correct "stop" trials. This was interpreted to indicate that inhibition was "triggered at the neural level, even if it was ineffective at the behavioral one." Conversely, correctly inhibited "stop" trials were associated with increased putamen activity relative to incorrect stop trials, which Aron & Poldrack persuasively argue to reflect higher conflict, resulting from a slower "go" process on those trials.

In support of the "hyperdirect" pathway, activity in rIFC was correlated with activity in STN , and activity in both regions was stronger for subjects with faster SSRTs. Other analyses suggest that while the degree to which rIFC is recruited does not depend on SSD, activity in STN, pSMA and globus pallidus does, such that those regions are more active the longer the SSD (and thus the closer to execution the response is).

There are several complications in interpreting these results. First, the decreased M1 activity on failed stop trials may have to do with the length of those trials as compared to the length of correct Go trials, which showed a very similar but protracted temporal profile. Furthermore, if signal strength reductions are to indicate inhibition, it is strange that "go" trials would show this pattern - because clearly inhibition is neither needed nor performed on correct "go" trials! This suggests that inhibition may not be an accurate term for what is observed in this case.

Secondly, there are at least three reasons that STN, pSMA and globus pallidus might be more active on trials in which the stop signal occurs later relative to trials where it occurs earlier. The possibility endorsed by Aron & Poldrack is that in late-signal trials motoric inhibition must be performed (since the movement may already be initiated), whereas in early-signal trials more "cognitive" inhibition must be performed (since only movement planning will have begun). However, it's also possible this is an an artifact of the longer "go" process which is necessarily present on these trials, as was argued to be the case for putamen activity. Or it could be that this activity is akin to the "lateralized readiness potential" detected by EEG studies of stop signal, in which there is increasingly negative frontal activity as a stop signal trial wears on. Either way, the conclusion that this reflects greater motoric inhibition is simply premature.

Third, if rIFC actually executes inhibition, it is strange that activity in that region is insensitive to the type of inhibition that would have to be performed. For example, one would expect different patterns of activity in rIFC for trials requiring motoric inhibition relative to those requiring "cognitive inhibition," and yet this was not observed. Instead, the activity in this region is more compatible with an account where rIFC is actively monitoring task cues/performance and orchestrating subsequent control or selection processes, rather than accomplishing inhibition per se.

This perspective is also compatible with a wide variety of findings on the functional role of rIFC. For example, right inferior frontal activity has been associated with both deviance and novelty detection in an oddball paradigm. Detection of unusual stimuli would be important for a region involved in "task monitoring." Likewise, rIFC is more activated by negative than positive feedback. Finally, rIFC is also most active during conditions of high WM load, also suggesting a role for that region in selection or monitoring processes, but not necessarily inhibition.

Related Posts:
Noninhibitory Accounts of Negative Priming
Inhibition and rTMS
Backward Inhibition: Evidence and Possible Mechanisms
Inhibition from Excitation: Reconciling Directed Inhibition with Cortical Structure
The Tyranny of Inhibition

Is "Executive Function" A Valid Construct?

The term "executive function" is frequently used but infrequently defined. In attempting to experimentally define executive functions in terms of their relationship to age, reasoning and perceptual speed, Timothy Salthouse reviewed the variety of verbal definitions given to construct of "executive function." Although these differ in terminology and emphasis, they are clearly addressing a similar concept:

“Executive functions cover a variety of skills that allow one to organize behavior in a purposeful, coordinated manner, and to reflect on or analyze the success of the strategies employed.” (from this book)

"Executive functions are those involved in complex cognitions, such as solving novel problems, modifying behavior in the light of new information, generating strategies or sequencing complex actions” (Elliott, 2003).

“Executive functions include processes such as goal selection, planning, monitoring, sequencing, and other supervisory processes which permit the individual to impose organization and structure upon his or her environment” (Foster, Black, Buck, & Bronskill, 1997, p. 117).

"The executive functions consist of those capacities that enable a person to engage successfully in independent, purposive, selfserving behavior” (Lezak, 1995)

Given such a wide variety of definitions, Salthouse notes that it is not surprising to see a correlation between executive function (EF) and intelligence (g). But as with any measure, its correlations depend on how it is measured - and executive function, due in part to its overly broad definitions - is measured in many different ways. In fact, a measure is often considered to index executive function simply if it has subjective "face validity."

Salthouse argues that psychometric techniques for establishing validity - i.e., a detailed investigation of EF's correlations with other measures - could help this sad state of affairs. If there are in fact distinct sources of variance underlying performance on complex tasks that are not accounted for by variation in age and "non-executive" processes (such as visual skill, speed of processing, etc), then executive function may be a valid construct.

Specifically, if the tasks thought to measure EF have unique predictive value of a participant's age, above and beyond the predictive value conveyed by other non-EF measures, then it appears to have good construct validity. Likewise, if the EF measures do not share variation with non-EF measures, then it also appears to have good construct validity. In Salthouse's own words:

"The rationale was that if the target variables represent something different from the cognitive abilities included in the model, then the variables not only should have relatively weak relations to those abilities but also should have significant unique (direct) relations with an individual-difference variable such as age if they are reliably influenced by another construct, such as executive functioning, that is related to age."

In pursuit of this goal, Salthouse analyzes data from over 7,000 adults on a variety of tasks. The most important findings from the study are reported next, with the methodological details of this study included at the end of the post in italicized text.

The results showed that many putative measures of "Executive Function" are strongly related to reasoning ability (as measured through Raven's Progressive Matrices) and processing speed (as measured through extremely simple tasks involving replacing number words with digits, etc). The vast majority of putative executive function measures did not share variance with age that was not also present in the simpler tasks. What does Salthouse conclude from these results?

Salthouse's First Conclusion: These findings are "inconsistent with the interpretation that [Executive Function] represents a distinct construct" from the other non-executive measures.

This conclusion is problematic for several reasons. First of all, it is arguable that every task involves some amount of executive function, whether it is coordination, planning, strategizing, inhibition, or any of the variety of processes mentioned in the definitions of executive function reviewed at the beginning of this post. Therefore, it is unreasonable to expect to find a task in which there is no relationship with executive function (except, perhaps, simple reaction time measures, which were not included here).

Second, performance on any given task includes variance that is incidental to the construct thought to be measured by that task. Salthouse clearly appreciates this fact in the case of the nonexecutive measures (reasoning, processing speed, etc) which is why latent variables are constructed from these measures. The same thing holds for measures of executive function, and yet no latent variables were constructed for these measures. This results in a decrement in statistical power to detect unique age-related variance in executive function measures.

Salthouse's Second Conclusion: EF measures may be of little use for the measurements of individual differences, since many nonexecutive tasks seem to measure the same things and have superior reliability/sensitivity.

In contrast to the conclusion above, this conclusion may indeed be accurate insofar as executive measures are often difficult to administer and have relatively low retest reliability. However, the issue of sensitivity - how well EF measures can detect things like brain damage, functional outcome, age, or other individual differences - is not clearly addressed by this paper (although this paper would suggest that EF measures may be more sensitive than many traditional psychometric tests). It is true that lower reliability may result in lower sensitivity, but this is not necessarily the case.

Tests of executive function may also have lower specificity than other tests - i.e., low performance on EF tests may reflect poor executive functioning or impairments in the processes on which executive function acts. Although this is generally a disadvantage, the fact that a single test might detect deficits in a variety of processes may be advantageous for situations in which cognitive function needs to be rapidly assessed (i.e., at the scene of an accident).

Salthouse's second conclusion is reminiscent of Arthur Jensen's claims in "Clocking the Mind" about the high correlations of simple and choice reaction time measures with IQ. Reaction time measures have several advantages compared to EF measures, in particular their relative simplicity and the fact that they do not rely on task novelty. However, it remains to be seen whether executive functions mediate the relationship of simple reaction time to IQ, or whether these represent distinct contributions to intelligence.

Related Posts:

Intelligence and Executive Function
Under The Rug: Executive Functioning
The Rules in the Brain
Localizing Executive Functions in Prefrontal Cortex
Clinical Neuropsychology and Executive Function
Factor Analyses of Executive Function Impairment Due to Brain Injury
Theory of Mind, Working Memory and Inhibition



Below are the construct variables used in Salthouse's structural equation modeling analysis on a group of 300 adults, along with the tasks used to measure them:

• Measures of Executive Functioning
  
• Wisconsin Card Sorting Test
• Letter, Category and Alternating Fluency Tasks
  
• Connections Test (a variant of Trail Making)
  
• Measures
• Synonym Vocab
• Antonym Vocab
• Wechsler Adult Intelligence Vocab Subscale
  
• Woodcock–Johnson Psycho-Educational Battery—Revised Picture Vocab
• Measures of Reasoning Ability
  
• Ravens Progressive Matrices Set II
  
• Shipley Institue of Living Scale - Abstraction Subscale
  
• Letter Sets
• Measures of Spatial Processing
  
• Spatial Relations
• Paper Folding
• Form Boards
• Measures of Memory Performance
  
• Free Recall
• Paired Associates
• Logical Memory
• Measures of Processing Speed
  
• Letter Comparison
• Pattern Comparison
• Digit Symbol

In the structural equation models, each of the non-executive construct variables was permitted to correlate with each other, as well as with age, while none of the underlying measures themselves was permitted to correlate with anything except for the construct it was purported to measure. Each of the executive construct variables was then examined to see whether a) it shared unique variance with age relative to the nonexecutive constructs, and b) whether it had significant loadings from non-executive measures. For each putative EF measure this was the case, with most loading on reasoning or perceptual speed ability.

This analysis was then repeated with a variety of different measures collected from over 7,000 adults. The factor loadings from thsi much larger sample were very similar to those in the smaller sample, reported above. Leaving aside for the moment the particular patterns of correlations discovered, the general finding was that no putative measure of executive functioning showed unique variation with age that could not be predicted by variation in "nonexecutive" tasks (with the sole exception of "Anti Cue," a type of anti-saccade task). The executive measures included in this larger analysis were Ruff Figural Frequency, Tower of Hanoi, Sort Recognition and Proverb Interpretation from the Delis-Kaplan Executive Function System, Trail Making, Stroop Color Word, switch costs from a task involving either "odd/even" and "greater/smaller than 5" judgments, RT and accuracy from the "Reading with Distraction" task, Anticue, computation span, listening span, N-back, Keeping Track task, Matric Monitoring, and the Running Memory task.

Review: Clocking the Mind

Arthur Jensen is a controversial figure in psychology, due in large part to his claims about racial differences in intelligence. In his newest book, "Clocking the Mind," Jensen turns his attention to a more focused topic: how is it that extraordinarily simple measures of reaction time can correlate so highly with intelligence?

To understand the importance of this question, consider the following. First, as Jensen notes, almost all reliable measures of cognitive performance are correlated. Across a large number of such tests, a single number - termed g, for "general intelligence" - can account for a large portion of individual differences on each task. Because no single test is "process pure," the correlations between g and scores on any given test are typically rather small; high correlations emerge from these measures only when they are considered in aggregate, with the following exception.

Despite the fact that g is commonly assessed with tests of vocabulary, memory for associations, reasoning ability on the Raven's Progressive Matrices (where subjects must discover a visual pattern within a matrix of stimuli, and select what the next pattern in the sequence would look like), and a wide variety of other very abstract and untimed tests, it appears that the variance they share can be reliably and accurately indexed by reaction time on a task where subjects must merely press a lighted button. The correlations between such simple tasks and g is around .62, which is higher than the correlation between many subscales of IQ tests and the g factor to which they contribute.

If you are skeptical of these results, you are not alone. Jensen notes a deep-seated bias against the idea that such simple measures could reveal important traits of the cognitive system, and reviews several historical reasons for this bias. However, in just over 200 pages, Jensen creates a persuasive argument for the RT-IQ correlation based on dozens of factor analyses, and both developmental and genetic work. In the process, he covers issues related to statistical methodology, procedural variations on simple RT tasks, and correlations between simple RT and Sternberg memory scanning, working memory, short-term memory, long term memory, and a variety of other cognitive constructs.

In the end, it appears that simple RT and g may be very closely related, if not indexing the same thing. Jensen advocates the "bottom-up" interpretation of the RT-IQ correlation, suggesting that individual differences in processing speed allow those individuals to think faster, accumulate more information per unit time, and provide other advantages that subsequently translate into g. Jensen notes that the "top-down" interpretation - for example, that increased IQ leads to better strategy-use, and for that reason result in lower RTs on simple tasks - is plausible but relatively uninteresting for those interested in mechanistic rather than merely descriptive accounts of intelligence. Whether or not you agree with Jensen's "neural oscillation" hypothesis of the RT-IQ correlation, these facts beg for a mechanistic explanation.

Jensen's writing is clear and concise, and every chapter is densely packed with information. The historical treatment of chronometry is perhaps most enjoyable, filled with personal anecdotes and unique insight into the politics of 20th century psychology and psychometrics. My only complaint is the index seems sparse for a book so rich in detail.

"Clocking the Mind" is not a popular science book; it is a scholarly work directed towards professionals and graduate students. Yet, anyone with a scientific interest in individual differences, intelligence, or executive functions will find much to consider here. After all, if Jensen is right, relatively simple and extremely reliable measures of reaction time might be a good replacement for the "fancy tasks" cognitive scientists have spent decades refining.

Blogging on the Brain: 12/15

Some highlights from recent brain blogging:

Psychological Operations: MindHacks discovers an archive of information warfare propaganda.

Hemisphericity: Handedness may not be the proper way to control for left or right-brain dominance, according to a recent article reviewed by BPS Research Digest.

The Neural Prediction Challenge: Can you predict a subject's responses to new stimuli given "recordings from visual and auditory neurons during naturalistic stimulation" ?

Psychedelic Treatments for OCD? It appears that psilocybin mushrooms may temporarily allieve obsessive-compulsive symptoms. [Though I have to ask, wouldn't large doses of any profoundly mind-altering drug be likely to change the profile of OCD behavior?]

IFG in mitigating interference: Aron points to the inferior frontal gyrus as the location of cognitive inhibition. This post at Cognitive Daily describes transcranial magnetic stimulation of IFG and its possible role in episodic interference.

Quantum Mechanics in the Brain? In contrast to theories of consciousness that invoke neural quantum mechanics, the Neurophilosopher reviews a viable theory of how quantum mechanics may be involved in the sense of smell.

Enhancing Memory During Sleep: SCLin's blog covers a fascinating recent study showing that minute electrical stimulation during sleep can enhance memory consolidation.

Localizing Intuition in the Brain: MindBlog reviews a recent fMRI study of intuitive judgments and their connection with orbito-frontal cortex.

Is the hand faster than the eye? Another BPS post reviews research suggesting that your eyes may not be fooled by magic tricks, even if "you" were! This is reviewed in the context of dissociable action/perception systems, but is also compatible with graded representation accounts of knowledge, where weaker representations suffice to guide eye movements but stronger representations are required for explicit knowledge (this has been demonstrated in A-Not-B tasks where infants fail to reach to the correct location of a hidden object, yet nonetheless gaze towards the correct location).

Two new blogs from Nature Publishing Group: Nautilus and Peer-to-Peer. And don't forget Action Potential!

Have a nice weekend!