Running Current Through Your Brain Improves Performance, Not As Likely To Kill You As You Think

For many people placing a nine-volt battery on their tongue, like sex, can be a fun, exciting activity, sometimes resulting in death. Based on this observation, Reinhart and Woodman (2014) decided to turn the brain into an improvised battery by placing electrodes on different areas of the skull and zapping it with enough current to toast a frozen hotpocket. If this sounds insane to you, then you are obviously not a cognitive neuroscientist - as I have said before, we live for these kinds of experiments.

However, the researchers had good reasons for doing this. First of all, they are scientists, and they did not spend nine years on their doctorate only to justify themselves to the likes of you. Second, directly messing with brain activity can lead to valuable scientific insights, such as how much you have to pay an undergraduate to have them consent to turn their brain into a microwave oven. But third, and most important, delivering direct current through a pair of electrodes can increase or decrease certain patterns of neural activity - specifically, the error-related negativity (ERN) following an error trial.

The ERN is a negative deflection in voltage over the medial frontal lobes that correlates with behavior adjustment and error correction in the future. For example, if I commit what some narrow-minded, parochial individuals consider an error, such as asking out my girlfriend's sister, the larger my ERN is, the less likely I am to make that same mistake in the future. Similarly, with experiments such as the Stroop task, or any performance task, the larger the ERN after committing an error, the greater the probability of making a correct response on the next trial. Furthermore, whereas the ERN usually occurs immediately after the response is made, another related signal, the feedback related negativity (FRN) occurs once feedback is received. In sum, larger ERNs and FRNs generally lead to better future performance.

This is exactly what the experimenters manipulated when they sent current through the medial frontal area of the brain, corresponding to the dorsal anterior cingulate cortex (dACC) and supplementary motor area (SMA) cortical regions. The electrode over this area was changed to either a cathode (i.e., positively charged, or where the electrons flowed toward) or an anode (i.e., negatively charged, or where the electrons flowed away from). If the electrode was a cathode, the ERN decreased significantly, whereas if the electrode was an anode, the ERN significantly increased.

Figure 1 from Reinhart & Woodman (2014). Panels A and D represent the current distribution throughout the medial prefrontal cortex. B: Stop-signal task used in the experiment. A stop signal leads to a greater chance of screwing up, and the longer the delay between the cue and the stop signal, the more difficult it is to stop a response. This is what physicists and individuals with severe incontinence refer to as an "event horizon." C: Placement of Cathode or Anode on the medial frontal surface, along with a sham condition. Lower panel: Difference in ERN and FRN dependent on whether the fronto-medial electrode is an Anode or Cathode.

As interesting as these neural differences are, however, the real punch of the paper lies in the behavioral changes. Participants who had an anode placed over their cingulate and SMA areas not only showed greater ERN and FRN profiles, but also steep gains in their accuracy and improvements in reaction time. For regular trials which did not include a distracting stop signal, anode subjects were markedly faster than in the cathode and sham conditions, and in both regular and stop-signal trials, accuracy nearly reached a hundred percent.


Nor were these gains limited to the duration of the experiment; in fact, behavioral improvements could last as long as five hours after switching on the current. These results make for wild and reckless speculations about what could be done with this kind of setup; one could imagine creating caps for students which get them "juiced up" for exams, hats for the elderly to help them find their Mysteriously Disappearing Reading Glasses, or modified helmets for soldiers which allow them get even better at BSU (blowing stuff up). Because, after all, what's the use of a scientific result if you can't weaponize it?

More figures and results from experiments further extending and confirming their results can be seen in the paper, found here.

When Stuff Goes Wrong

One complaint I have with FMRI tutorials and manuals is this: The user is provided a downloadable dataset and given a tutorial to generate a specific result. There is some commentary about different aspects of the analysis pipeline, and there might be a nod to artifacts that show up in the data. But for the most part things are expected to be more or less uneventful, and if anything goes wrong during the tutorial, it is likely because your fat fingers made a typo somewhere. God, you are fat.

Another thing: When you first read theory textbooks about fMRI data analysis, a few boogie men are mentioned, such as head motion or experimental design confounds. However, nothing is mentioned about technicians or RAs screwing stuff up, or (more likely) you yourself screwing stuff up. Not because you are fat, necessarily, but it doesn't help.

Bottom line: Nobody tells you how to respond when stuff goes wrong - really wrong - which it inevitably will.

No, I'm not talking about waking up feeling violated next to your frat brother; I'm talking about the millions of tiny things that can derail data acquisition or data analysis or both. This can end up costing your lab and the American taxpayer literally thousands - that's thousands, with a "T" - of dollars. No wonder the Tea Party is pissed off. And while you were hoping to get that result showing that conservatives/liberals exhibit abnormal neural patterns when shown pictures of African-Americans, and are therefore bigoted/condescending scum that deserve mandatory neural resocialization, instead you end up with a statistical map of blobs that looks like the frenetic finger-painting of a toddler tripping balls from Nutella overdose. How could this happen? Might as well go ahead and dump all seventy activation clusters in a table somewhere in the supplementary material where it will never see the light of day, and argue that the neural mechanisms of prejudice arise from the unfortunate fact that the entire brain is, indeed, active. (If this happens, just use the anodyne phrase "frontal-parietal-temporal-occipital network" to describe results like these. It works - no lie.)

How to deal with this? The best approach, as you learned in your middle school health class, is prevention. (Or abstinence. But let's get real, kids these days are going to analyze FMRI data whether we like it or not, the little minks.) Here are some prophylactic measures you can take to ensure that you do not get scalded by unprotected data analysis:

1) Plan your experiment. This seems intuitive, but you would be surprised how many imaging experiments get rushed out the door without a healthy dose of deliberative planning. This is because of the following reasons:
  1. You will probably get something no matter what you do.
  2. See reason #1
2) Run a behavioral pilot. Unless the neural mechanism or process is entirely cognitive and therefore has no behavioral correlate (e.g., instructing the subject to fantasize about Nutella), try to obtain a performance measure of your conditions, such as reaction time. Doing this will also reinforce the previous point, which is to plan out your experiment. For example, the difference in reaction time between conditions can provide an estimate of how many trials you may need during your scanning session, and also lead to stronger hypotheses about what regions might be driving this effect.

3) Have a processing stream already in place before the data starts rolling in. After running your first pilot subject, have a script that extracts the data and puts everything in a neat, orderly file hierarchy. For example, create separate directories for your timing data and for your raw imaging data.

4) As part of your processing stream, use clear, understandable labels for each new analysis that you do. Suffixes such as "Last", "Final", "Really_The_Last_One", and "Goodbye_Cruel_World", although optimistic, can obscure what analysis was done when, and for what reason. This will protect you from disorganization, the bane of any scanning experiment.

5) Analyze the hell out of your pilot scan. Be like psychopath federal agent Jack Bauer and relentlessly interrogate your subject. Was anything unclear? What did they think about the study, besides the fact that it was so boring and uncomfortable that instead of doing it again they would rather have a vasectomy with a weed-whipper? You may believe your study is the bomb, but unless the subject can actually do it, your study is about as useful as a grocery bag full of armpit hair.

6) Buy a new printer. Chicks dig guys with printers, especially printers that print photos.

Your ticket to paradise

7) Check the results of each step of your processing stream. After you've had some experience looking at brain images, you should have an intuition about what looks reasonable and what looks suspect. Knowing which step failed is critical for troubleshooting.

8) Know how to ask questions on the message boards. AFNI, SPM, and FSL all have excellent message boards and listservs that will quickly answer your questions. However, you should make your question clear, concise, and provide enough detail about everything you did until your analysis went catastrophically wrong. Moderators get pissed when questions are vague, whiny, or unclear.

9) When all else fails, blame the technicians. FMRI has been around for a while now, but the magnets are still extremely large and unwieldy, cost millions to build and maintain, and we still can't get around the temporal resolution-spatial resolution tradeoff. Clearly, the physicists have failed us.


These are just a few pointers to help you address some of the difficulties and problems that waylay you at every turn. Obviously there are other dragons to slay once you have collected a good sample size and need to plan your interpretation and possible follow-up analysis. However, devoting time to planning your experiment and running appropriate behavioral studies can go a long way toward mitigating the suffering and darkness that follows upon our unhappy trade.

Lesion Studies: Thoughts

(Note: I recently completed my candidacy exam, which involved writing a trio of papers focusing on different aspects of my research. Most of this post is cannibalized from a section I wrote on lesion studies of the anterior cingulate cortex, which produce counterintuitive results when contrasted to lesions of other areas, such as the DLPFC and OFC, which do indeed seem to disrupt the processes that those regions are implicated in from the neuroimaging literature.

My work primarily involves healthy people with intact brains, and observing indirect measures of neural firing through tracking slow blood flow changes in the brain. However, "activation" as defined by fMRI is not the same as the underlying neural dynamics, and, barring invasive single-cell recordings, we have few options for directly measuring neural firing in response to different tasks and psychological contexts. This caveat inherent in fMRI research becomes particularly important when interpreting the results of lesion studies.) 

Although the majority of the neuroimaging literature has implicated the dACC as playing a critical role in the signaling for cognitive control when necessary, the most direct test of a brain structure’s necessity in a cognitive process is through examining subjects presenting with lesions in that part of the brain. For example, if it can be demonstrated that a subject without an ACC still performs equivalent to controls on tasks involving cognitive control, then that would argue against the necessity of that area’s involvement in the hypothesized cognitive process. Studies involving human subjects with lesions are relatively rare and suffer from low power, but can still reveal important aspects of neural functioning.


The ACC, in particular, has been the subject of several lesion studies that have shown conflicting and counterintuitive results. For example, a single-subject lesion study of a patient with left ACC damage exhibited both smaller ERNs and increased RT in response to incongruent stimuli in a spatial Stroop paradigm. This study showed that conflict monitoring and error detection, at least in this patient, do not both come from the same area of ACC, suggesting that these processes occur in different areas. However, while the ERN was shown to be attenuated in the patient, the conflict response (a waveform called the N450) was actually enhanced (Swick & Turken, 2002). This suggests that conflict monitoring occurs in a nearby prefrontal area, such as the DLPFC, before information about the conflict is sent to the ACC.


Figure of the lesion for the single subject analyzed by Turken & Swick (2002). Overlaid are coordinates of peak activation for conflict-related tasks from other studies.


On the other hand, a lesion study conducted by Fellows & Farah (2005) compared the performance of individuals with dACC lesions to that of controls across a battery of tasks hypothesized to involve cognitive control. These tasks included a Stroop task and a go-nogo task which are known to elicit significantly greater increases in RT after errors, and to induce significantly greater amounts of errors during incongruent trials. The results showed no significant interactions between group and task, suggesting that the dACC is not necessary for the implementation of cognitive control. Furthermore, the authors pointed out that tasks involving cognitive control may be confounded with emotional responding, which in turn could simply be associated with the ACC's involvement in regulating muscle tone. In any case, it is apparent that although this structure is somehow associated with cognitive control, it is not strictly necessary for it. 


Figure showing group overlap of lesions in the Fellows & Farah (2005) study.  Circles and squares represent an overlay of a meta-analysis by Bush et al (2000), with circles representing peak activations for cognitive tasks, and squares representing peak activations for emotional tasks.

Comparison of Stroop effect (measured in percent signal change from mean congruent trial RT) and error rate between lesion patients and controls. No significant difference was found on either measure between the two groups.

In sum, these lesion studies suggest that the dACC may not be indispensable for signaling the DLPFC to implement cognitive control. However an alternative explanation is that patients with ACC lesions are usually ipsilateral, and that furthermore they may be compensating for required cognitive control by recruiting nearby cortical areas. However, two lines of evidence argue against this interpretation. First, one of the lesion patients examined in the Fellows & Farah (2005) had extensive medial ACC damage encompassing dACC bilaterally, but showed a similar pattern of error rates and RT difference between congruent and incongruent conditions as did the other lesion patients and the control group. Secondly, lesion studies of other areas of the brain – such as the orbitofrontal cortex – have shown that those regions appear to be specific to the cognitive processes they are hypothesized to be involved in. For example, patients with OFC lesions exhibit significantly impaired performance in decision-making tasks such as the Iowa Gambling Task and Wisconsin Card Sorting Task, as well as decreased autonomic activity in response to highly risky gambles (Bechara et al, 1994). Even though the patients in this study had suffered from their lesions for a comparable amount of time as the lesion subjects in the Fellows & Farah (2005) study, there was no evidence of recruitment of other cortical areas in order to support their deficits in decision-making.

However, although these lesion studies have shown no significant differences in error rates between the lesion patients and controls, other experiments have revealed that patients with ACC damage are less likely to correct for their mistakes on trials immediately following an error. In addition, patients with ACC lesions are less likely to be aware that an error has occurred (Swick & Turken, 2002). These results suggest that there may be a necessary role for of the ACC for the actual detection of errors, which would be consistent with the hypothesis that this area is involved in the comparison of actions against their predicted outcomes. How lesions affect the transfer of information from the ACC to the DLPFC and other cortical regions supposedly involved in the implementation of cognitive control, however, is less well understood.

Bottom line: If the inferences from neuroimaging studies are to believed, then the ACC is necessary somehow for cognitive control or executive function; however, lesion studies belie this claim, suggesting perhaps that the necessary processes for these cognitive functions take place elsewhere and merely light up the ACC as some sort of epiphenomenon. Admittedly, I am unsure of what to make of all this. The most useful experiments to carry out, in my opinion, would be to apply transcranial magnetic stimulation (TMS) to temporarily knock out this area in healthy controls, and then observe what happens; however, as TMS is only able to disrupt neural firing on surface areas of the cortex, stimulation of deeper areas remains impractical. With continuing advances in the ability of TMS to stimulate deeper cortical (and, possibly, subcortical?) structures, we may get a better grasp of what is going on.