Hate On Halloween

It was only a matter of time...and it's just in time for Halloween!

The Neural Correlates of _____________¹ [insert complex emotion or behavior here] is still a news- and flashy-publication-worthy title for your next neuroimaging paper! Use your imagination. How about The Neural Correlates of Procrastination? The Neural Correlates of Blogging? [NOTE: compare and contrast these two for extra credit]. The Neural Correlates of Hematophagy? The Neural Correlates of Sanguivoriphobia? The Neural Correlates of Nasophilia? Add your favorite by commenting on this post.

OK, OK, enough with Sarcasm. On to Hate. Zeki and Romaya (2008) give the following rationale for their study:

...we were interested to explore the neural correlates of hate directed against an individual. ... The hatred may be directed against a public figure or a personally known individual, for a variety of reasons. We made no attempt to distinguish between different types of personal hatred. Instead, we recruited subjects through advertisements, asking them only to volunteer if they experienced an intense enough hate for an individual, without distinguishing further between different categories of individual hate. We conformed as much as possible to our previous studies on romantic and maternal love (Bartels & Zeki 2001, 2004), asking subjects to complete a questionnaire which allowed us to correlate the declared subjective experiences with changes in the BOLD signal.

And the groundbreaking hypothesis? Love and hate might be represented by different brain states! Who knew?

We hypothesized that the pattern of activity generated by viewing the face of a hated person would be quite distinct from that produced by viewing the face of a lover.

Then they really went out on a limb:

In particular, we did not anticipate activation of the brain's reward system but believed that it would result in a different pattern of activity within the emotional brain.

[Oops, more sarcasm there.] However, there might actually be an interesting question addressed by the paper, and it's this:

Given the common association between love and hate, and the relative frequency with which one of these sentiments can transform into the other, we also hypothesized that there would be some strong correlation in the brain sites activated during the experience of these two antipodean sentiments. The results surprised us.

The study participants were 17 people (10 male, 7 female) recruited specifically because they expressed intense hatred for a particular individual. Sixteen people hated an ex-lover or a competitor at work, and one person hated a famous political figure. Two weeks before the experiment, the participants brought in photographs of their hated person and of three other people of the same sex who elicited neutral feelings. Unfortunately, the fake exemplar figure chosen for the paper consisted of four photos that were not all matched for age and race! It makes you wonder whether the authors controlled for that in the actual stimulus materials.


Figure 1. An example set of four processed face images (faces not from this study).

During the experiment, the photographs were presented for 16 sec each, followed by an inter-trial interval of 2 sec. Sometimes a blank screen was presented for 16 sec instead of a face. Each face was presented a total of 8 times.² Subjects were instructed to press a button when the picture disappeared from the screen. After the scanning session (and also during the first visit), ratings of each photographed person were obtained on the Passionate Hate Scale (File S1), designed to be similar to the Passionate Love Scale.

The questionnaire revolved around three elements of hate: (A) negation of intimacy, when an individual seeks a distance from the hated person. This is usually because the hated person arouses feeling of revulsion and disgust, exactly the opposite of the desire for greater intimacy in the context of love; (B) passion, expressing itself in intense anger at, and fear of, the hated person; and (C) devaluation of the hated person through expressions of contempt.

Example questions included (with answers rated on a 7 point scale from "strongly agree" to "strongly disagree"):

A2/ The world would be a better place if X had never existed.
A4/ I would like to interact with X.

B1/ I cannot control my hatred for X.
B3/ I have violent thoughts about X.

C1/ X is scum.

One of the key fMRI results is illustrated below.


Figure 3. Activation for the contrast Hated faces>Neutral faces.

There were 7 regions significantly more active for the Hated Face condition than for the Neutral Face condition. Fig. 3 illustrates the medial frontal gyrus [including the anterior cingulate cortex and the pre-SMA]. Fig. 4 shows the right putamen, bilateral premotor cortex [were they restraining their murderous tendencies?], the frontal pole, and bilateral insula [activated in all sorts of conditions from speech to working memory to reasoning to pain to disgust to the allure of Chanel No. 5]. I won't report on the correlation analysis that related degree of hatred to level of activation across 5,225 voxels because it used an uncorrected statistical threshold of p≤0.01.

And as to The Neural Correlates of Hate, the authors say :

Our studies did indeed reveal a basic pattern. As far as we can determine, it is unique to the sentiment of hate even though individual sites within it have been shown to be active in other conditions that are related to hate. The network has components that have been considered to be important in (a) generating aggressive behavior and (b) translating this behavior into motor action through motor planning. Finally, and most intriguingly, the network involves regions of the putamen and the insula that are almost identical to the ones activated by passionate, romantic, love.

Popular media outlets, of course, really love this sort of thing, especially when your university issues this type of press release:

Brain’s ‘hate circuit’ identified

28 October 2008

People who view pictures of someone they hate display activity in distinct areas of the brain that, together, may be thought of as a ‘hate circuit’, according to new research by scientists at UCL.

See the newest neurocurmudgeon (The Neuroskeptic) for more skepticism. Zeki's flowery prose doesn't help matters:

“Hate is often considered to be an evil passion that should, in a better world, be tamed, controlled, and eradicated. Yet to the biologist, hate is a passion that is of equal interest to love. Like love, it is often seemingly irrational and can lead individuals to heroic and evil deeds. How can two opposite sentiments lead to the same behaviour?”

I must have missed the evil and heroic portion of the experiment...


Footnotes

¹ Top hits include The Neural Correlates of Consciousness, Desire (Kawabata & Zeki), Maternal and Romantic Love (Bartels & Zeki), Reward-Related Trial-and-Error Learning, Sensory Awareness, Subjective Value During Intertemporal Choice, Motor Skill Automaticity, and [my personal favorite] David Chalmers (NC/DC, the foremost Black Metal/Christian Rap band, is not to be confused with David Chalmers the philosopher).

² Not exactly an extraordinary S/N. And who knows what the subjects were actually thinking about for 16 sec?

References

Bartels A, Zeki S. (2000). The neural basis of romantic love. Neuroreport 11:3829-34.

Bartels A, Zeki S. (2004). The neural correlates of maternal and romantic love. Neuroimage 21:1155-66.

Semir Zeki, John Paul Romaya, Jan Lauwereyns (2008). Neural Correlates of Hate. PLoS ONE, 3 (10). DOI: 10.1371/journal.pone.0003556

In this work, we address an important but unexplored topic, namely the neural correlates of hate. In a block-design fMRI study, we scanned 17 normal human subjects while they viewed the face of a person they hated and also faces of acquaintances for whom they had neutral feelings. A hate score was obtained for the object of hate for each subject and this was used as a covariate in a between-subject random effects analysis. Viewing a hated face resulted in increased activity in the medial frontal gyrus, right putamen, bilaterally in premotor cortex, in the frontal pole and bilaterally in the medial insula. We also found three areas where activation correlated linearly with the declared level of hatred, the right insula, right premotor cortex and the right fronto-medial gyrus. One area of deactivation was found in the right superior frontal gyrus. The study thus shows that there is a unique pattern of activity in the brain in the context of hate. Though distinct from the pattern of activity that correlates with romantic love, this pattern nevertheless shares two areas with the latter, namely the putamen and the insula.

No-one loves you and you know it
Don't pretend that you enjoy
Or you don't care
'Cause now I wouldn't lie
Or tell you all the things you want to hear
'Cause I hate you
'Cause I hate you
'Cause I hate you
'Cause I hate you

-Green Day, Platypus (I Hate You)

Viva Hate!

Bidirectional Competition Between Striatum and Hippocampus During Learning

The "dry cleaning effect" paper was finally published online Monday Oct 27 at PNAS, a full week after the initial press release. To briefly review:

'Dry cleaning effect' explained by forgetful Yale researcher

Yale researchers have described how dueling brain systems may explain why you forget to drop off the dry cleaning and may point to ways that substance abusers and people with OCD can overcome bad habits.

In Proceedings of the National Academy of Sciences, Christopher J. Pittenger, M.D., and colleagues describe a sort of competition between areas of the brain involved in learning that results in what Pittenger calls the "dry cleaning effect."

At the time, The Neurocritic scoffed at the overreach of the authors in interpreting their data for the press, but at the same time acknowledged that the actual paper could be sound.

Call me humanocentric, but I think distractibility (and the frontal lobes) might have a role in this sort of absentmindedness. Nevertheless, the study itself could be perfectly reasonable, and the results sound interesting...

But what does the paper actually say? What were the experimental tasks and manipulations? To begin with, the authors (Lee et al., 2008) adopted the multiple memory systems perspective (e.g., Squire 2004) that views different types of learning and memory (e.g., spatial learning and stimulus-response learning) as subserved by dissociable brain circuits (which include the hippocampus and the dorsal striatum, respectively). That's nothing new. In rodents, these two types of learning and memory are differentially affected by damage to the hippocampus and striatum in the fashion of a "double dissociation"¹ -- lesions to the hippocampus impair spatial learning but not S-R learning, while lesions to the dorsal striatum impair S-R learning but not spatial learning. This is true in humans as well, where (more broadly speaking) hippocampal damage impairs declarative memory but not procedural memory, and striatal damage impairs procedural memory but not declarative memory.

So what is new here? The way these two systems interact with each other is not fully understood. However (as cited by the authors), neuroimaging studies in humans indicate that hippocampal and striatal activity during spatial navigation (for example) shows an inverse relationship (Hartley et al., 2003),² raising the possibility that the two systems compete with each other.³ And as far as competition goes, it's quite well-known that habit learning is suppressed by other learning mechanisms, even in flies (Brembs et al., submitted). Brembs goes on to state in his comment on the dry cleaning post:

What I thought was surprising was that apparently the habit learning striatum also inhibited spatial learning, which is something I have never heard about.

Or as Lee et al. put it in their Introduction:

In rodents, hippocampal lesions can enhance acquisition of a striatum-dependent win-stay behavioral strategy in a radial arm maze task, perhaps by removing competitive interference from spatial information.

To date, however, we are aware of no studies that have provided clear evidence for interference by striatum-dependent processes on hippocampus-dependent learning; as a result, it remains unclear whether there is true bi-directional competition between these learning systems.

Their methods? Cued and spatial learning were assessed in mice with a modified water-maze task described in great detail in Fig S1 (which has a 588 word legend, not reproduced below).


Fig S1 (Lee et al. 2008).

From the main Methods section:

Briefly, animals learned to escape a pool of opaque water (similar to that used in the Morris water maze) by swimming to one of two visually distinct cues. ... Three distinct visible cues were used [plastic cylinders painted either solid gray or with black-and-white stripes...]

The first 5 days consisted of shaping to the task. On day -5, animals were placed on the platform four times (20-min inter-trial interval). On days -4 through -1, the escape platform was marked with the uniform gray cue; animals were placed in the pool and allowed 120 seconds to swim to it.

Following shaping, animals were trained in the two-cue task for 5 or 7 days; each animal was trained in either the cued or spatial task, never in both. All experiments consisted of four trials per day with a 20-min inter-trial interval. In the cued task, the escape platform was moved on each trial but was reliably marked by one of the two cues... In the spatial task, the escape platform was always in the same location but was variably associated with the two striped cues. In both tasks, the second visible cue (i.e., the lure) was present in a quadrant adjacent to the escape platform and its associated cue (i.e., the goal) on a stand that held it at an identical height in the water but did not permit escape. [NOTE: mean!]...

Learning was assayed by using a probe trial, administered in place of the fourth training trial after 3, 5, and/or 7 days of training... In the probe trial, both goal and lure cues were placed on stands that did not allow escape; the animal’s search was monitored by an overhead camera over 60 seconds. Extra-maze cues were identical to those present in a training trial. In both the cued and the spatial task, a systematic bias toward the goal cue relative to the lure cue (i.e., toward the location where the platform would have been on a regular training trial) was interpreted as evidence of learning.

Hopefully, it was not as difficult for the mice to learn the task as it is for the reader to understand what was done. On that note, to minimize the reader's cognitive load, the major results of the study are conveyed via the authors' paragraph subheadings.

Dorsal Striatal Lesions Impair Cued Learning and Enhance Spatial Learning.

Disruption of Striatal Synaptic Plasticity in Transgenic Mice Also Impairs Cued Learning and Enhances Spatial Learning.

KCREB Transgenic Mice Continue to Show Accelerated Learning upon Spatial Reversal.

Lesions of Dorsal Hippocampus Impair Spatial Learning and Potentiate Cued Learning.

And the conclusion? It's in the title: A double dissociation revealing bidirectional competition between striatum and hippocampus during learning.


Footnotes

¹ It must be noted here that not all researchers agree on the significance of a double dissociation. Although many take it as strong evidence of independent brain (or cognitive) systems, others disagree. For instance, Berry et al. (2008) state:

Do dissociations imply independent systems? In the memory field, the view that there are independent implicit and explicit memory systems has been predominantly supported by dissociation evidence. Here, we argue that many of these dissociations do not necessarily imply distinct memory systems. We review recent work with a single-system computational model that extends signal-detection theory (SDT) to implicit memory. SDT has had a major influence on research in a variety of domains. The current work shows that it can be broadened even further in its range of application. Indeed, the single-system model that we present does surprisingly well in accounting for some key dissociations that have been taken as evidence for independent implicit and explicit memory systems.

² I have to point out here that even this spatial navigation study in humans is not analogous to the true "dry cleaning effect" where distractibility, absentmindedness, and lapses of attention are key culprits.

³ It seems to be a somewhat different story for reversal learning (Shohamy et al., 2008).

References

Berry CJ, Shanks DR, Henson RN. (2008). A unitary signal-detection model of implicit and explicit memory. Trends Cog Sci. 12:367-73.

Hartley T, Maguire EA, Spiers HJ, Burgess N. (2003). The well-worn route and the path less traveled: distinct neural bases of route following and wayfinding in humans. Neuron 37:877-88.

A. S. Lee, R. S. Duman, C. Pittenger (2008). A double dissociation revealing bidirectional competition between striatum and hippocampus during learning Proceedings of the National Academy of Sciences DOI: 10.1073/pnas.0807749105

The multiple memory systems framework proposes that distinct circuits process and store different sorts of information; for example, spatial information is processed by a circuit that includes the hippocampus, whereas certain forms of instrumental conditioning depend on the striatum. Disruption of hippocampal function can enhance striatum-dependent learning in some paradigms, which has been interpreted as evidence that these systems can compete with one another in an intact animal. However, it remains unclear whether such competition can occur in the opposite direction, as suggested by the multiple memory systems framework, or is unidirectional. We addressed this question using lesions and genetic manipulations in mice. Impairment of dorsal striatal function with either excitotoxic lesions or transgenic inhibition of the transcription factor cAMP response element-binding protein, which disrupts striatal synaptic plasticity, impaired striatum-dependent cued learning but enhanced hippocampus-dependent spatial learning. Conversely, excitotoxic lesions of the dorsal hippocampus disrupted spatial learning and enhanced cued learning. This double dissociation demonstrates bidirectional competition that constitutes strong evidence for the parallel operation of distinct memory systems.

Shohamy D, Myers CE, Hopkins RO, Sage J, Gluck MA. (2008). Distinct Hippocampal and Basal Ganglia Contributions to Probabilistic Learning and Reversal. J Cog Neurosci. Sep 29. [Epub ahead of print].

The hippocampus and the basal ganglia are thought to play fundamental and distinct roles in learning and memory, supporting two dissociable memory systems. Interestingly, however, the hippocampus and the basal ganglia have each, separately, been implicated as necessary for reversal learning-the ability to adaptively change a response when previously learned stimulus-outcome contingencies are reversed. Here, we compared the contribution of the hippocampus and the basal ganglia to distinct aspects of learning and reversal. Amnesic subjects with selective hippocampal damage, Parkinson's subjects with disrupted basal ganglia function, and healthy controls were tested on a novel probabilistic learning and reversal paradigm. In this task, reversal can be achieved in two ways: Subjects can reverse a previously learned response, or, they can select a new cue during the reversal phase, effectively "opting out" of the reversal. We found that both patient groups were intact at initial learning, but differed in their ability to reverse. Amnesic subjects failed to reverse, and continued to use the same cue and response learned before the reversal. Parkinson's subjects, by contrast, opted out of the reversal by learning a new cue-outcome association. These results suggest that both the hippocampus and the basal ganglia support reversal learning, but in different ways. The basal ganglia are necessary for learning a new response when a previously learned response is no longer rewarding. The failure of the amnesic subjects to reverse their response or to learn a new cue is consistent with a more general role for the hippocampus in configural learning, and suggests it may also support the ability to respond to changes in cue-outcome contingencies.

Squire LR. (2004). Memory systems of the brain: a brief history and current perspective. Neurobiol Learn Mem. 82:171-7.

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The Trouble With Tephritidae

A True Fruit Fly - Tephritidae (via Myrmecos Blog)

Bjoern Brembs has written extensively about the latest anti-science commentary by VP candidate Sarah Palin, who said...

Where does a lot of that earmark money end up anyway? […] You've heard about some of these pet projects they really don't make a whole lot of sense and sometimes these dollars go to projects that have little or nothing to do with the public good. Things like fruit fly research in Paris, France. I kid you not.

...in a series of blog posts, including this one:

Who needs to know about bears, planetariums or fruit flies anyway? To hell with science!

In the beginning, there was bear DNA. Then the projector for the quintessential planetarium experience. Last Friday it was research on fruit flies. Which research project a semi-educated Republican politician doesn't understand will be next?

Myrmecos Blog informs us that Drosophila is not a Fruit Fly:

Fruit flies are a family, Tephritidae, containing about 5,000 species of often strikingly colored insects. As the name implies, these flies are frugivores. Many, such as the mediterranean fruit fly, are agricultural pests.

Drosophila melanogaster, the insect that has been so important in genetic research, is not a true fruit fly. Drosophila is a member of the Drosophilidae, the vinegar or pomace flies. They are mostly fungivores, and their association with fruit is indirect: they eat the fungus that lives in rotting fruit...

I bring this up because the confusion between fruit flies and vinegar flies entered into U.S. presidential politics this week when Sarah Palin attacked Fruit Fly spending as wasteful...

. . .

Palin was referring to a project to fund studies of the olive fruit fly, a true tephritid and a major threat to California’s olive industry.

I guess California's olive industry has little or nothing to do with the public good...


via Bjoern Brembs

...because the public good is better served by astronomical deficits and defense spending.

The Trouble With Tina

Tiny Fey's trouble is with the ratings for her NBC comedy show, 30 Rock. But she hopes her recent appearances on SNL will provide a boost:

"I hope this ends up helping 30 Rock," allows Fey, referring to her Sarah Palin sideline the past few weeks on Saturday Night Live. But she's keeping her expectations modest. "I would like the audience to go up just enough so that people don't have to refer to it as 'the ratings-challenged 30 Rock' anymore."

Tina and her 30 Rock character (Liz Lemon) look a lot like Liz Spikol, who writes The Trouble With Spikol, a blog about mental health. TTWS was featured in Psych Central's Top Ten Bipolar Blogs 2008.

In January 2007, Tina Fey was asked, “Do you ever get confused with Philadelphia Weekly columnist Liz Spikol?” You can see her answer this question (and others) in Tina Fey Apologizes for Looking Like Me.

So will Liz Spikol go as Sarah Palin for Halloween?

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