Monday, June 19, 2017

The Big Bad Brain


I’m high, staring at the ceiling
Sending my love, what a wonderful feeling
What comes next, I see a light
I’m along for the ride as I’m taking flight




Plus a cool brain tattoo to boot. AND the song is an earworm (at least it is for me).


It feels good to be running from the devil
Another breath and I'm up another level
It feels good to be up above the clouds
It feels good for the first time in a long time now







A monument to love unspoken
Carved into stone “Unwilling to come undone”


Here's what singer Landon Jacobs had to say about those specific lyrics:
“in the face of what I incorrectly assumed was an impending brain aneurysm, I decided that the best way to spend my final moments was to push my love through the universe to the people I cared about. I was terrified of dying, but that’s not reason to squander a potential death bed situation.”

(he had gotten way too high on one occasion and had a panic attack... he thought he was dying)






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Thursday, June 08, 2017

Terrorism and the Implicit Association Test



Induced Stereotyping?

Imagine that you're riding on a very crowded bus in a busy urban area in the US. You get on during a shift change, when a new driver takes over for the old one. The new driver appears to be Middle Eastern, and for a second you have a fleeting reaction that the situation might become dangerous. This is embarrassing and ridiculous, you think. You hate that the thought even crossed your mind. There are 1.8 billion Muslims in the world. How many are radical Islamist extremists? For example, in the UK at present, the number comprises maybe 0.00000167% of all Muslims? 1


Language matters.

Theresa May:
“First, while the recent attacks are not connected by common networks, they are connected in one important sense. They are bound together by the single, evil ideology of Islamist extremism that preaches hatred, sows division, and promotes sectarianism. 

It is an ideology that claims our Western values of freedom, democracy and human rights are incompatible with the religion of Islam. It is an ideology that is a perversion of Islam and a perversion of the truth.”

Donald Trump:
“That means honestly confronting the crisis of Islamist extremism and the Islamist terror groups it inspires. And it means standing together against the murder of innocent Muslims, the oppression of women, the persecution of Jews, and the slaughter of Christians.
. . .

DRIVE THEM OUT OF THIS EARTH.”

In both of these cases, the world leaders did acknowledge that Islamist extremism is not the same as the religion of Islam. Nonetheless, in terms of statistical co-occurrence in the English language, the root word Islam- is now associated with all that is bad and evil in the world. Could the constant exposure to news about radical Islamist terrorism and Trump's proposed Muslim Ban result in an involuntary or “forced” stereotyping in the bus scenario above?

A recent study found that semantics derived automatically from language corpora contain human-like biases, which means that machines (which do not have cultural stereotypes) become “biased” when they learn word association patterns from large bodies of text, such as Google News. The authors used a word embedding algorithm called Global Vectors for Word Representation (GloVe) to improve the performance of the machine learning model. As a measure of human bias, they used the popular implicit association test (IAT), from which they developed the Word-Embedding Association Test (WEAT). Instead of response times (RTs) to a specific set of words, WEAT used the distance between a set of vectors in semantic space. The authors were able to replicate the associations seen in every IAT they tested (Caliskan et al., 2017), suggesting:
The number, variety, and substantive importance of our results raise the possibility that all implicit human biases are reflected in the statistical properties of language.

Arab-Muslim Implicit Association Test

Because of the relationship between word associations and implicit bias, I decided to take the Arab-Muslim IAT at Project Implicit, an organization interested in “implicit social cognition — thoughts and feelings outside of conscious awareness and control.” This definition seemed to fit with the bus scenario, which involved an impulse to profile the driver based on a rapid evaluation of perceived ethnicity.

In the Arab-Muslim IAT, the participant classifies words as good (e.g, Fantastic, Fabulous) or bad (e.g, Horrible, Hurtful), and proper names as Arab Muslim (e.g., Akbar, Hakim) or “Other People” (e.g, Ernesto, Philippe, Kazuki).2 The bias is revealed when you have to sort both of these categories at the same time. Are you slower when Good/Arab Muslim are mapped to the same key, compared to when Bad/Arab Muslim are mapped to the same key? (and vice versa).

My results are below.

- click on image for a larger view -


I showed a moderate automatic preference for Arab Muslims over Other People. But this wasn't completely unique compared to the population of 327,000 other participants who have taken this test:

The summary of other people's results shows that most people have little to no implicit preference for Arab Muslims compared to Other People - i.e., they are just as fast when sorting good words and Arab Muslims than sorting good words and Other People.”


The aggregate results above covered a period of 11.5 years ending in December 2015. The strength of semantic associations between words can vary over time and contexts, so we can wonder if this has shifted any in the last year. In addition, different results have been observed when faces were used instead of names, and when a better list of “Other People” names was used to specify ingroup vs. outgroup (see explanation in footnote #2).

A Muslim-Terrorism test has in fact been developed by Webb et al. (2011). They used a variant of the IAT (the GNAT) with Muslim names (e.g., Abdul, Ali, Farid, Khalid, Tariq), Scottish names (e.g., Alistair, Angus, Douglas, Gordon, Hamish), terrorism-related words (e.g., attack, bomb, blast, explosives, threat) and peace-related words (e.g., friendship, harmony, love, serenity, unity). In an interesting twist, the authors varied “implementation intentions” to flip the Muslim-Terrorism test to the Muslim-Peace test in half of the subjects:
Following the practice trials, one-half of the participants (implementation intention condition) were asked to form an implementation intention to help them to respond especially quickly to Muslim names and peace-related words. Participants were asked to tell themselves ‘If Muslim names and peace are at the top of the screen, then I respond especially fast to Muslim words and peace words!’. Participants were asked to repeat this statement several times before continuing with the experiment. The other half of the participants (standard instruction condition) were given no further instructions.

I actually discovered this strategy on my own in 2008, when my IAT results revealed I was Human AND Alien and NEITHER Dead NOR Alive.

And indeed, the Muslim-Peace instructions neutralized the strong Muslim-Terrorism association seen in the control participants Webb et al. (2011).



Calvin Lai and colleagues conducted a high-powered series of experiments showing that instructions such as implementation intentions and faking the IAT can shift implicit racial biases (Lai et al., 2014), but these interventions are short-lived (Lai et al., 2016).

I wrote about the former study in 2014: Contest to Reduce Implicit Racial Bias Shows Empathy and Perspective-Taking Don't Work. Failed interventions all tried to challenge the racially biased attitudes and prejudice presumably measured by the IAT. These interventions are below the red line in the figure below.

- click on image for a larger view -


Figure 1 (modified from Lai et al, 2014). Effectiveness of interventions on implicit racial preferences, organized from most effective to least effective. Cohen’s d = reduction in implicit preferences relative to control; White circles = the meta-analytic mean effect size; Black circles = individual study effect sizes; Lines = 95% confidence intervals around meta-analytic mean effect sizes. IAT = Implict Association Test; GNAT = go/no-go association task.


The major message here is that top-down cognitive control processes can affect thoughts and feelings that are purportedly outside of conscious awareness — and can apparently override semantic associations that are statistical properties of language obtained from a large-scale crawl of the Internet (containing 840 billion words)!

Now whether the IAT actually measures implicit bias is another story...


ADDENDUM (June 11 2017): Prof. Joanna J. Bryson, a co-author on the machine learning/semantic bias paper, wrote a very informative blog post about this work: We Didn't Prove Prejudice Is True (A Role for Consciousness).


Footnotes

1 I cannot imagine what it's like to be a survivor of the recent Manchester and London attacks, and my deepest condolences go out to the families who have lost loved ones

2 Notice I put “Other People” in quotes. That's because the names are not all from the same category (country/ethnicity)  Latino, French, and Japanese in the examples above. This lack of uniformity could slow down RTs for the “Other People” category. A better alternate category would have been all French names, for instance. Or use common European-American names to differentiate ingroup (Michael, Christopher, Tyler) vs. outgroup (Sharif, Yousef, Wahib)


References

Caliskan A, Bryson JJ, Narayanan A. (2017). Semantics derived automatically from language corpora contain human-like biases. Science 356(6334):183-186.

Lai CK, Marini M, Lehr SA, Cerruti C, Shin JE, Joy-Gaba JA, Ho AK, Teachman BA, Wojcik SP, Koleva SP, Frazier RS, Heiphetz L, Chen EE, Turner RN, Haidt J, Kesebir S, Hawkins CB, Schaefer HS, Rubichi S, Sartori G, Dial CM, Sriram N, Banaji MR, Nosek BA. (2014). Reducing implicit racial preferences: I. A comparative investigation of 17 interventions. J Exp Psychol Gen. 143(4):1765-85.

Lai CK, Skinner AL, Cooley E, Murrar S, Brauer M, Devos T, Calanchini J, Xiao YJ, Pedram C, Marshburn CK, Simon S, Blanchar JC, Joy-Gaba JA, Conway J, Redford L, Klein RA, Roussos G, Schellhaas FM, Burns M, Hu X, McLean MC, Axt JR, Asgari S, Schmidt K, Rubinstein R, Marini M, Rubichi S, Shin JE, Nosek BA. (2016). Reducing implicit racial preferences: II. Intervention effectiveness across time. J Exp Psychol Gen. 145(8):1001-16.

Webb TL, Sheeran P, Pepper J. (2012). Gaining control over responses to implicit attitude tests: Implementation intentions engender fast responses on attitude-incongruent trials. Br J Soc Psychol. 51(1):13-32.

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Thursday, May 25, 2017

Gaslighting in the Medical Literature



Have you felt that your sense of reality has been challenged lately? That the word “truth” has no meaning any more? Does the existence of alternative facts make you question your own sanity? In modern usage, the term gaslighting refers to “a form of psychological abuse in which false information is presented to the victim with the intent of making him/her doubt his/her own memory and perception”.
Gaslighting is a form of manipulation that seeks to sow seeds of doubt in a targeted individual or members of a group, hoping to make targets question their own memory, perception, and sanity. Using persistent denial, misdirection, contradiction, and lying, it attempts to destabilize the target and delegitimize the target's belief.

In December 2016, the amazing Lauren Duca1 wrote a widely shared piece for Teen Vogue, Donald Trump Is Gaslighting America. In it, she argued that Trump won the election by normalizing deception. Duca noted that the term gaslighting originated from the 1938 play Gas Light by Patrick Hamilton, and explained it in this way:
"Gas lighting" is a buzzy name for a terrifying strategy currently being used to weaken and blind the American electorate. We are collectively being treated like Bella Manningham in the 1938 Victorian thriller from which the term "gas light" takes its name. In the play, Jack terrorizes his wife Bella into questioning her reality by blaming her for mischievously misplacing household items which he systematically hides. Doubting whether her perspective can be trusted, Bella clings to a single shred of evidence: the dimming of the gas lights that accompanies the late night execution of Jack’s trickery. The wavering flame is the one thing that holds her conviction in place as she wriggles free of her captor’s control.

Gaslighting in the Medical Literature

Barton and Whitehead (1969) were the first to report cases where a patient's mental state was manipulated for material (or situational) gain, calling it the “Gas-Light Phenomenon”. If these incidents sound like something straight out of domestic noir or a TV crime drama, you'd be right.


Case 1 48 year old mechanic, married for 10 years, with three children
Mr. A. was admitted one evening to a psychiatric hospital as an emergency. His general practitioner, when asking for his admission, had said he was mentally ill and had attacked his wife. ...

On admission the patient said he had felt tense and depressed for about six months and related this to his wife’s changed attitude towards him. He said she had become "cold", and he thought she might have been seeing another man. He denied he had been violent and thought he had been sent into hospital because of his "nerves".
His wife had concocted an elaborate tale of abuse, saying he had become “irritable, bad-tempered, and liable to unprovoked violent outbursts in which he sometimes hit her and once struck her with a hatchet.” She also claimed his memory was deteriorating, and she categorically denied having an affair. Mr. A was hospitalized for 12 days with no obvious physical or psychiatric disorder and left feeling more relaxed.

However, he returned to hospital two weeks later: “He said his wife had started taunting him, saying he was mad and should be in a mental hospital. His wife said that his mental condition had considerably worsened and that he had attacked her twice.”

Fortunately for Mr. A, his boss overheard a conversation between two men in the local tavern. One of the men was Mrs. A's lover, discussing how the two of them had plotted to get rid of Mr. A using the false claims of mental illness and abuse. The hospital staff confronted Mrs. A with her lies:
She finally agreed that she had plotted with her boy-friend to get rid of her husband, but claimed she had been led on by him and now very much regretted her behaviour. Following some family counselling Mr. and Mrs. A. became reconciled and five years later were still living happily together.


Case 2 45 year old pub owner married for 14 years

Mr. B was admitted based on his wife's story about her husband’s “heavy drinking, erratic behaviour, and aggressive outbursts.”
On admission to the unit Mr. B. gave a history of domestic difficulties and described mild symptoms of anxiety and depression. ...  He agreed that he was irritable but said that he had never been aggressive and did not acknowledge any of the common symptoms of alcoholism. ... recently ... his wife had lost interest in him and had started associating with younger men. She often stayed out all night, and when he asked her about this behaviour she told him not to be silly and accused him of being a drunk who should be put away.
A member of the staff eventually found out about Mrs. B's fabrication and her intent to get rid of her husband, keep the pub, and “then really start living.” Unlike the outcome of Case 1, Mr. B left his wife and was quite happy without her five years later.


Case 3 72 year old widow

This case is unique, because it goes beyond mere mental manipulation. Mrs. C. was referred to a psychiatric hospital because of a "confusional state" and "fecal incontinence" that made her unfit for the old persons' home where she resided. She had moderate Parkinson's disease and slight dementia, but she was fairly well oriented and pleasant in demeanor. She stayed in the hospital for six weeks and showed no signs of fecal incontinence while there. And indeed it turned out that her incontinence had been cruelly induced by large doses of laxatives:
The lady running the home had been unable to develop a good relationship with Mrs. C. and considered "she was a naughty old thing making life difficult for me, my staff, and other folk on purpose".

For some weeks before admission to hospital Mrs. C. had been receiving ’Dulcolax’ tablets one three times a day. This had produced the expected effect with occasional "accidents" due to Mrs. C.’s mobility difficulties. The evidence suggested that Mrs. C. was not wanted in the home and induced incontinence was used as a method of getting her removed to hospital.


Case 4 Another example is an incident reported by Lund and Gardiner (1977), where the staff of the mental hospital conspired to keep a patient there so that one of them could live in her flat. The elderly woman had suffered from paranoid episodes in the past that were successfully treated with medication. But this time “they” were really out to get her:
Miss A., an 80-year-old retired professional lady, was first admitted to a mental hospital in connection with this incident under Section 31 of the Mental Health (Scotland) Act 1960, from her pleasant flat in a residential establishment. The admission notes stated that she had complained that there were people on the premises who had no business there, that they had spoken outside her door saying that they were going to throw her into the river and that she further believed that these people were 'after my flat'...
Miss A was shuttled in and out of hospital several times until the evil plot was finally foiled:
She was admitted for the third time some four months later with a depressingly similar story. Her general practitioner had been called to the home where the patient had allegedly ' barricaded her room'; she had simply put a chair against the door. She was again admitted under an Emergency Order and once more settled down very rapidly, showing no sign of disturbed behaviour. She was generally pleasant and witty, showing some evidence of valuing her independence and mildly resenting the help of the nursing staff, which she regarded as unnecessary interference.

At this point, suspicion about the motives of the staff at the institution were aroused. Discreet inquiries revealed that the rooms which Miss A occupied had been earmarked for a proposed additional member of staff...

[And the rental market has only gotten worse in the last 40 years!! So it's not surprising to see many stories emerging from trendy urban areas (and South Carolina). For starters, you can read these anecdotes of landlord gaslighting and harassment from tenants in New York, San Francisco, Santa Monica, and elsewhere.]


Case 5 Let's conclude with one final report from the Canadian Journal of Psychiatry. Kutcher (1982) described the sad case of Mrs. N, a 59 year old financially successful woman who was referred to a psychiatrist at her husband's insistence. Marital problems were clearly the source of her distress.
About two years into the marriage she established Mr. N in a business as he had entered the relationship without a secure financial basis. She then noted he would stay away from home, be unavailable when she tried to contact him, tell her he was visiting with friends even though they denied any visits, and so forth. When she confronted him with these issues he denied any extramarital activity.  ...
Mr. N. wasn't terribly creative; his ruse was ripped from the pages of Gaslight. An outside party described him as "a 60 year old Cassanova who thinks he's 25."
Numerous friends often intimated that he was involved with another woman and Mrs. N eventually saw this for herself. When confronted, he denied it, then said it was all over and refused to discuss the matter further. He then complained about her "saggy breasts" and when she had surgery for reduction he ridiculed her. He hid her jewelry and accused her of losing it, often changed times they were to meet without notifying her and berated her for being late; and told their acquaintances that she was "going a little strange."
Unfortunately, Mrs. N's case was not a success story: “Currently she is still in therapy and as yet is unable to resolve the issue.”


Let's hope the U.S. can collectively (and individually) regain its grip on the truth so it will not suffer a similar fate.


Footnote

1 I think she's amazing for her persistence as a guiding voice on social media despite the grotesque harassment she's received.


Further Reading

On the Origins of “Gaslighting” (by Rosemary Erickson Johnsen)

A Few Notes on Gaslighting (by Tressie McMillan Cottom)


References

Barton R, & Whitehead JA (1969). The gas-light phenomenon. Lancet (London, England), 1 (7608), 1258-60. PMID: 4182427

Kutcher SP (1982). The gaslight syndrome. Canadian journal of psychiatry. Revue canadienne de psychiatrie, 27 (3), 224-7 PMID: 7093877

Lund CA, & Gardiner AQ (1977). The gaslight phenomenon--an institutional variant. The British journal of psychiatry : the journal of mental science, 131, 533-4. PMID: 588872

Smith CG, & Sinanan K (1972). The "gaslight phenomenon" reappears. A modification of the Ganser syndrome. The British journal of psychiatry : the journal of mental science, 120 (559), 685-6 PMID: 5043219 [although Milo Tyndel (1973) pointed out those cases were nothing like Ganser syndrome].






You can watch the entire film for free at archive.org.

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Sunday, May 14, 2017

Looking for Empathy in All the Wrong Places: Bizarre Cases of Factitious Disorder




Factitious disorder is a rare psychiatric condition where an individual deliberately induces or fabricates an ailment because of a desire to fulfill the role of a sick person. This differs from garden variety malingering, where an individual feigns illness for secondary gain (drug seeking, financial gain, avoidance of work, etc.). The primary goal in factitious disorder is to garner attention and sympathy from caregivers and medical staff.

The psychiatric handbook DSM-5 identifies two types of factitious disorder:
  • Factitious Disorder Imposed on Self (formerly known as Munchausen syndrome when the feigned symptoms were physical, rather than psychological).
  •  
  • Factitious Disorder Imposed on Another: When an individual falsifies illness in another, whether that be a child, pet or older adult (formerly known as Munchausen syndrome by proxy).

Since the desire to elicit empathy is one of the main objectives in this disorder, it is odd indeed when the “patient” feigns a frightening or repellent condition. A recent report by Fischer et al. (2016) discussed a particularly flagrant example: the case of a middle-aged man who falsely claimed to be a sexually sadistic serial killer to impress his psychotherapist. Not surprisingly, his ruse was a complete failure.

The case report noted that Mr. S had been a loner his entire life:
 ... He described having anxiety growing up, mainly in social situations. ... Mr. S had a history of alcohol abuse starting in his mid-twenties and continuing into his early forties. He denied any significant medical history. He denied legal difficulties, psychiatric hospitalizations, and suicide attempts. He was single, had never been married, had no children, and reported having only one close friend for most of his life. He never had a close long-term romantic relationship and stated a clear preference for living a solitary life. 

Mr. S had served in the military but did not see combat, and afterwards worked the graveyard shift as a security guard (all the better to avoid people).
One year prior to his admission to the psychiatric hospital, Mr. S sought outpatient therapy for depression and engaged in weekly supportive psychotherapy with a young female psychology intern. His psychiatrist started an SSRI antidepressant and a low dose of antipsychotic medication for “depression with psychotic features.” Mr. S's alleged psychosis consisted of “voices” of crowds of people saying things that he could not make out, which he experienced while working the night shift. He consistently attended his therapy sessions and was noted to be making progress. However, several months into his therapy, Mr. S told his therapist that he had been involved in of military combat and described himself as a decorated war hero. After several therapy sessions in which he [falsely] recounted his combat experiences, Mr. S was queried as to whether he ever killed anyone, to which Mr. S replied, “During the military or after the military?” He then told his therapist that he had followed, raped, and killed numerous women during the 20 years since leaving the military.

He recounted his imaginary crimes to the young female intern:
Mr. S reported that he would follow a potential female victim for several months before raping and strangling her to death with a rope. Although he claimed to rape and kill the women, he did not describe any sexual arousal from the subjugation, torture, or killing of his alleged victims. He refused to disclose how many women he had killed, where he had killed them, or how he had disposed of their bodies. He described having purchased various supplies to aid in abduction, which he kept in the back of his van while cruising for victims. These supplies included rope and two identical sets of clothes and shoes to help evade detection by the police. He described using various techniques to track his victims, as well as evade surveillance of his activities. He informed his therapist that he was actively following a woman he had encountered in a local public library several days earlier. Mr. S acknowledged that he studied the modus operandi of famous sexually sadistic serial killers by reading books. The patient's therapist, feeling frightened and threatened by these disclosures, transferred his case to her supervisor, who then saw the patient for a few therapy sessions. Mr. S reported worsening depression, hearing more “voices,” and attempting to self-amputate his leg using a tourniquet. Consequently, Mr. S was involuntarily detained as a “danger to self” and “danger to others” for evaluation in the local psychiatric hospital.

He was diagnosed with major depressive disorder, single episode, unspecified severity, with psychotic features. His routine physical, neurological exam, and lab work all yielded normal results.
...The inpatient treatment team contacted the District Attorney's office in order to file for continued involuntary hospitalization due to the patient's homicidal ideation and history of violence. Subsequent police investigation and review of records could not substantiate any of the patient's claims of committing multiple homicides in the Pacific Northwest.
. . .

After the District Attorney accepted the application for the prolonged involuntary civil commitment (180-day hold), Mr. S was confronted with the inconsistencies between his self-reported symptoms and objective findings and the failure to corroborate his claims of prior homicides. In response, Mr. S then confessed that he “had made the whole thing up…about the killings…all of it” because he “wanted attention.” He said that he had never followed, raped, or killed anyone and never had an intention to do so. He said that he did not know why he claimed this, other than an “impulse came over me and I acted on it.”

His false identity as a serial killer backfired, and he couldn't understand why his therapist had discontinued their sessions:
He had believed that his feigned history and symptomatology would make him a “more interesting” patient to his therapist. He reported feeling rejected when his therapist transferred his care to her supervisor. He had little insight into why his therapist may have been frightened by his behavior. Mr. S revealed that following his initial fabrications, and despite his initial involuntary hospitalization, he had felt too embarrassed to admit the truth.

His original diagnosis was revised to “factitious disorder with psychological symptoms, and cluster A traits (particularly schizoid and schizotypal traits) without meeting criteria for any one specific personality disorder.” Because of these personality traits, he had no insight into why his therapist might feel threatened by his terrifying stories.

There are at least two other papers describing cases of factitious disorder with repugnant feigned symptoms: one reported a case of factitious pedophilia, and the other reported a case of factitious homicidal ideation.


Thanks to Dr. Tannahill Glen for the link.


References

Fischer, C., Beckson, M., & Dietz, P. (2017). Factitious Disorder in a Patient Claiming to be a Sexually Sadistic Serial Killer. Journal of Forensic Sciences, 62 (3), 822-826 DOI: 10.1111/1556-4029.13340

Porter, T., & Feldman, M. (2011). A Case of Factitious Pedophilia. Journal of Forensic Sciences, 56 (5), 1380-1382 DOI: 10.1111/j.1556-4029.2011.01804.x

Thompson CR, & Beckson M (2004). A case of factitious homicidal ideation. The journal of the American Academy of Psychiatry and the Law, 32 (3), 277-81. PMID: 15515916



Appendix

What are the symptoms of Factitious Disorder?

  • Dramatic but inconsistent medical history
  • Unclear symptoms that are not controllable, become more severe, or change once treatment has begun
  • Predictable relapses following improvement in the condition
  • Extensive knowledge of hospitals and/or medical terminology, as well as the textbook descriptions of illness
  • Presence of many surgical scars
  • Appearance of new or additional symptoms following negative test results
  • Presence of symptoms only when the patient is alone or not being observed
  • Willingness or eagerness to have medical tests, operations, or other procedures
  • History of seeking treatment at many hospitals, clinics, and doctors’ offices, possibly even in different cities
  • Reluctance by the patient to allow health care professionals to meet with or talk to family members, friends, and prior health care providers

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Tuesday, April 18, 2017

The Big Ideas in Cognitive Neuroscience, Explained



Are emergent properties really for losers? Why are architectures important? What are “mirror neuron ensembles” anyway? My last post presented an idiosyncratic distillation of the Big Ideas in Cognitive Neuroscience symposium, presented by six speakers at the 2017 CNS meeting. Here I’ll briefly explain what I meant in the bullet points. In some cases I didn't quite understand what the speaker meant so I used outside sources. At the end is a bonus reading list.

The first two speakers made an especially fun pair on the topic of memory: they held opposing views on the “engram”, the physical manifestation of a memory in the brain.1 They also disagreed on most everything else.


1. Charles Randy Gallistel (Rutgers University) What Memory Must Look Like

Gallistel is convinced that Most Neuroscientists Are Wrong About the Brain. This subtly bizarre essay in Nautilus (which was widely scorned on Twitter) succinctly summarized the major points of his talk. You and I may think the brain-as-computer metaphor has outlived its usefulness, but Gallistel says that “Computation in the brain must resemble computation in a computer.” 

Shannon information is a set of possible messages encoded as bit patterns and sent over a noisy channel to a recipient that will hopefully decode the message with minimal error. In this purely mathematical theory, the semantic content (meaning) of a message is irrelevant. The brain stores numbers and that's that.

  • Memories (“engrams”) are not stored at synapses.
Instead, engrams reside in molecules inside cells. The brain “encodes information into molecules inside neurons and reads out that information for use in computational operations.” A 2014 paper on conditioned responses in cerebellar Purkinje cells was instrumental in overturning synaptic plasticity (strengthening or weakening of synaptic connections) as the central mechanism for learning and memory, according to Gallistel.2 Most other scientists do not share this view.3

  • The engram is inter-spike interval.
Spike train solutions based on rate coding are wrong. Meaning, the code is not conveyed by the firing rate of neurons. Instead, numbers are conveyed to engrams via a combinatorial interspike interval code. Engrams then reside in cell-intrinsic molecular structures. In the end, memory must look like the DNA code.

  • Emergent properties are for losers.
“Emergent property” is a code word for “we don't know.”



2. Tomás Ryan (@TJRyan_77) Information Storage in Memory Engrams

Ryan began by acknowledging that he had tremendous respect for Gallistal's speech which was in turn powerful, illuminating, very categorical, polarizing, and rigid. But wrong. Oh so very wrong. Memory is not essentially molecular, we should not approach memory and the brain from a design perspective, and information storage need not mimic a computer.

  • The brain does not use Shannon information.
More precisely, “the kind of information the brain uses may be very different from Shannon information.” Why is that? Brains evolved, in kludgy ways that don't resemble a computer. The information used by the brain may be encoded without having to reduce it to Shannon form, and may not be quantifiable as units.

  • Memories (“engrams”) are not stored at synapses.
Memory is not stored by changes in synaptic weights, Ryan and Gallistel agree on this. The dominant view has been falsified by a number of studies including one by Ryan and colleagues that used engram labeling. Specific “engram cells” can be labeled during learning using optogenetic techniques, and later stimulated to induce the recall of specific memories. These memories can be reactivated even after protein synthesis inhibitors have (1) induced amnesia, and (2) prevented the usual memory consolidation-related changes in synaptic strength.

  • We learn entirely through spike trains.
Spike trains are necessary but not sufficient to explain how information is coded in the brain. On the other hand, instincts are transmitted genetically and are not learned via spike trains.

  • The engram is an emergent property.
And fitting with all of the above, “the engram is an emergent property mediated through synaptic connections” (not through synaptic weights). Stable connectivity is what stores information, not molecules.


Angela Friederici (Max Planck Institute for Human Cognitive and Brain Sciences) Structure and Dynamics of the Language Network

Following on the heels of the rodent engram crowd, Friederici pointed out the obvious limitations of studying language as a human trait.

  • Language is genetically predetermined.
The human ability to acquire language is based on a genetically predetermined structural neural network. Although the degree of innateness has been disputed, a bias or propensity of brain development towards particular modes of information processing is less controversial. According to Friederici, language capacity is rooted in “merge”, a specific computation that binds words together to form phrases and sentences.

  • The “merge” computation is localized in BA 44.
This wasn't one of my original bullet points, but I found this statement rather surprising and unbelievable. It implies that our capacity for language is located in the anterior ventral portion of Brodmann's area 44 in the left hemisphere (the tiny red area in the PHRASE > LIST panel below).



The problem is that acute stroke patients with dysfunctional tissue in left BA 44 do not have impaired syntax. Instead, they have difficulty with phonological short-term memory (keeping strings of digits in mind, like remembering a phone number).

  • There is something called mirror neural ensembles.
    I'll just have to leave this slide here, since I really didn't understand it, even on the second viewing.



    “This is a poor hypothesis,” she said.


    Jean-Rémi King (@jrking0) Parsing Human Minds

    King's expertise is in visual processing (not language), but his talk drew parallels between vision and speech comprehension. A key goal in both domains is to identify the algorithm (sequence of operations) that translates input into meaning.

    • Recursion is big. 
    Despite these commonalities, the structure of language presents the unique challenge of nesting (or recursion): each constituent in a sentence can be made of subconstituents of the same nature, which can result in ambiguity.


    • Architectures are important. 
    Decoding aspects of a sensory stimulus using MEG and machine learning is lovely, but it doesn't tell you the algorithm. What is the computational architecture? Is it sustained or feedforward or recurrent?

      Each architecture could be compatible with a pattern of brain activity at different time points. But do the classifiers at different time points generalize to other time points? This can be determined by a temporal generalization analysis, which “reveals a repertoire of canonical brain dynamics.”


      Danielle Bassett (@DaniSBassett A Network Neuroscience of Human Learning: Potential to Inform Quantitative Theories of Brain and Behavior

      Bassett previewed an arc of exciting ideas where we've shown progress, followed by frustrations and failures, which may ultimately provide an opening for the really Big Ideas. Her focus is on learning from a network perspective, which means patterns of connectivity in the whole brain. What is the underlying network architecture that facilitates the spatial distributed effects?



      What is the relationship between these two notions of modularity?
      [I ask this as an honest question.]

      Major challenges remain, of course.

      • Build a bridge from networks to models of behavior.
      Incorporate well-specified behavioral models such as reinforcement learning and the drift diffusion model of decision making. These models are fit to the data to derive parameters such as the alpha parameter from reinforcement learning rate. Models of behavior can help generate hypotheses about how the system actually works.

      • Use generative models to construct theories. 
      Network models are extremely useful, but they're not theories. They're descriptors. They don't generate new frameworks for understanding what the data should look like. Theory-building is obviously critical for moving forward.


      John Krakauer (@blamlab Big Ideas in Cognitive Neuroscience: Action

      Krakauer mentioned the Big Questions in Neuroscience symposium at the 2016 SFN meeting, which motivated the CNS symposium as well as a splashy critical paper in Neuron. He raised an interesting point about how the term “connectivity” has different meanings, i.e. the type of embedded connectivity that stores information (engrams) vs. the type of correlational connectivity when modules combine with each other to produce behavior. [BTW, is everyone here using “modules” in the same way?]

      • Machine learning will save us. 
      Krakauer discussed work on motor learning using adaptation paradigms and simple execution tasks. But there's a dirty secret: there is no computational model, no algorithmic theory of how practice makes you better on those tasks. Can the computational view get an upgrade from machine learning? Go out and read the manifesto by Marblestone, Wayne, and Kording: Toward an Integration of Deep Learning and Neuroscience. And you better learn about cost functions, because they're very important.4



      • Go back to behavioral neuroscience.
      This is the only way to work out the right cost functions. Bottom line: Networks represent weighting modules into the cost function.4 


      OVERALL, there was an emphasis on computational approaches with nods to the three levels of David Marr:

      computation – algorithm – implementation



      We know from from Krakauer et al. 2017 (and from CNS meetings past and present) that co-organizer David Poeppel is a big fan of Marr. The end goal of a Marr-ian research program is to find explanations, to reach an understanding of brain-behavior relations. This requires a detailed specification of the computational problem (i.e., behavior) to uncover the algorithms. The correlational approach of cognitive neuroscience and even the causal-mechanistic circuit manipulations of optogenetic neuroscience just don't cut it anymore.



      Footnotes

      1 Although neither speaker explicitly defined the term, it is most definitely not the engram as envisioned by Scientology: “a detailed mental image or memory of a traumatic event from the past that occurred when an individual was partially or fully unconscious.” The term was first coined by Richard Semon in 1904.

      2 This paper (by Johansson et al, 2014) appeared in PNAS, and Gallistel was the prearranged editor.

      3 For instance, here's Mu-ming Poo: “There is now general consensus that persistent modification of the synaptic strength via LTP and LTD of pre-existing connections represents a primary mechanism for the formation of memory engrams.”

      4 If you don't understand all this, you're not alone. From Machine Learning: the Basics.
      This idea of minimizing some function (in this case, the sum of squared residuals) is a building block of supervised learning algorithms, and in the field of machine learning this function - whatever it may be for the algorithm in question - is referred to as the cost function. 


      Reading List

      Everyone is Wrong

      Here's Why Most Neuroscientists Are Wrong About the Brain. Gallistel in Nautilus, Oct. 2015.

      Time to rethink the neural mechanisms of learning and memory. Gallistel CR, Balsam PD. Neurobiol Learn Mem. 2014 Feb;108:136-44.

      Engrams are Cool

      What is memory? The present state of the engram. Poo MM, Pignatelli M, Ryan TJ, Tonegawa S, Bonhoeffer T, Martin KC, Rudenko A, Tsai LH, Tsien RW, Fishell G, Mullins C, Gonçalves JT, Shtrahman M, Johnston ST,  Gage FH, Dan Y, Long J, Buzsáki G, Stevens C. BMC Biol. 2016 May 19;14:40.

      Engram cells retain memory under retrograde amnesia. Ryan TJ, Roy DS, Pignatelli M, Arons A, Tonegawa S. Science. 2015 May 29;348(6238):1007-13.

      Engrams are Overrated

      For good measure, some contrarian thoughts floating around Twitter...


      “Can We Localize Merge in the Brain? Yes We Can”

      Merge in the Human Brain: A Sub-Region Based Functional Investigation in the Left Pars Opercularis. Zaccarella E, Friederici AD. Front Psychol. 2015 Nov 27;6:1818.

      The neurobiological nature of syntactic hierarchies. Zaccarella E, Friederici AD. Neurosci Biobehav Rev. 2016 Jul 29. doi: 10.1016/j.neubiorev.2016.07.038.

      Really?

      Asyntactic comprehension, working memory, and acute ischemia in Broca's area versus angular gyrus. Newhart M, Trupe LA, Gomez Y, Cloutman L, Molitoris JJ, Davis C, Leigh R, Gottesman RF, Race D, Hillis AE.  Cortex. 2012 Nov-Dec;48(10):1288-97.

      Patients with acute strokes in left BA 44 (part of Broca's area) do not have impaired syntax.


      Dynamics of Mental Representations

      Characterizing the dynamics of mental representations: the temporal generalization method. King JR, Dehaene S. Trends Cogn Sci. 2014 Apr;18(4):203-10.

      King JR, Pescetelli N, Dehaene S. Brain Mechanisms Underlying the Brief Maintenance of Seen and Unseen Sensory InformationNeuron. 2016; 92(5):1122-1134.


      A Spate of New Network Articles by Bassett

      A Network Neuroscience of Human Learning: Potential to Inform Quantitative Theories of Brain and Behavior. Bassett DS, Mattar MG. Trends Cogn Sci. 2017 Apr;21(4):250-264.

      This one is most relevant to Dr. Bassett's talk, as it is the title of her talk.

      Network neuroscience. Bassett DS, Sporns O. Nat Neurosci. 2017 Feb 23;20(3):353-364.

      Emerging Frontiers of Neuroengineering: A Network Science of Brain Connectivity. Bassett DS, Khambhati AN, Grafton ST. Annu Rev Biomed Eng. 2017 Mar 27. doi: 10.1146/annurev-bioeng-071516-044511.

      Modelling And Interpreting Network Dynamics [bioRxiv preprint]. Ankit N Khambhati, Ann E Sizemore, Richard F Betzel, Danielle S Bassett. doi: https://doi.org/10.1101/124016


      Behavior is Underrated

      Neuroscience Needs Behavior: Correcting a Reductionist Bias. Krakauer JW, Ghazanfar AA, Gomez-Marin A, MacIver MA, Poeppel D. Neuron. 2017 Feb 8;93(3):480-490.

      The first author was a presenter and the last author an organizer of the symposium.



      Thanks to @jakublimanowski for the tip on Goldstein (1999).

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      Tuesday, April 04, 2017

      What are the Big Ideas in Cognitive Neuroscience?


      This year, the Cognitive Neuroscience Institute (CNI) and the Max-Planck-Society organized a symposium on Big Ideas in Cognitive Neuroscience. I enjoyed this fun forum organized by David Poeppel and Mike Gazzaniga. The format included three pairs of speakers on the topics of memory, language, and action/motor who “consider[ed] some major challenges and cutting-edge advances, from molecular mechanisms to decoding approaches to network computations.”

      Co-host Marcus Raichle recalled his inspiration for the symposium: a similar Big Ideas session at the Society for Neuroscience meeting. But human neuroscience was absent from all SFN Big Ideas, so Dr. Raichle contacted Dr. Gazzaniga, who “made it happen” (along with Dr. Poeppel). The popular event was standing room only, and many couldn't even get into the Bayview Room (which was too small a venue). More context:
      “Recent discussions in the neurosciences have been relentlessly reductionist. The guiding principle of this symposium is that there is no privileged level of analysis that can yield special explanatory insight into the mind/brain on its own, so ideas and techniques across levels will be necessary.”

      The two hour symposium was a welcome addition to hundreds of posters and talks on highly specific empirical findings. Sometimes we must take a step back and look at the big picture. But since I'm The Neurocritic, I'll start out with some modest suggestions for next time.

      • There was no time for questions or discussion.
      • There were too many talks.
      • It would be nice for all speakers to try to bridge different levels of analysis.
      • This is a small point, but ironically the first two speakers (Gallistel, Ryan) did not talk about human neuroscience.

      So my idea is to have four speakers on one topic (memory, let's say) with two at the level of Gallistel and Ryan1, and two who approach human neuroscience using different techniques. Talks are strictly limited to 20 minutes. Then there is a 20 minute panel discussion where everyone tries to consider the implications of the other levels for their own work. Then (ideally) there is time for 20 minutes of questions from the audience. However, since I'm not an expert in organizing such events, allotting 20 minutes for the audience could be excessive. So the timing could be restructured to 25 min for talks, 10-15 min panel, 5-10 min audience. Or combine the round table with audience participation.

      Last year, Symposium Session 7 on Human Intracranial Electrophysiology (which included the incendiary tDCS challenge by György Buzsáki) had a round table discussion as Talk 5, which I thought was very successful.

      Video of the Big Ideas symposium is now available on YouTube, but in case you don't want to watch the entire two hours, I'll present a brief summary below.


      Big Box Neuroscience

      Here's an idiosyncratic distillation of some major points from the symposium.

      • The brain is an information processing device in the sense of Shannon information theory.
      • The brain does not use Shannon information.
      • Memories (”engrams”) are not stored at synapses.
      • We learn entirely through spike trains.
      • The engram is inter-spike interval.
      • The engram is an emergent property.
      • Emergent properties are for losers.
      • Language is genetically predetermined.
      • There is something called mirror neural ensembles.
      • Recursion is big.
      • Architectures are important.
      • Build a bridge from networks to models of behavior.
      • Use generative models to construct theories.
      • Machine learning will save us.
      • Go back to behavioral neuroscience.

      Maybe I'll explain what this all means in the next post. You can also check out the official @CogNeuroNews coverage.


      ADDENDUM (April 18 2017): The sequel is finally up: The Big Ideas in Cognitive Neuroscience, Explained


      Footnote

      1 Controversy is always entertaining, and these two had diametrically opposed views.




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      Friday, March 24, 2017

      What's Popular at #CNS2017?

      Memory wins again!



      Word cloud for 835 poster titles at CNS 2017.


      The 2017 Cognitive Neuroscience Society annual meeting will start tomorrow, March 25. To no one's surprise, memory is the most popular topic in the bottom-up abstract submission sweepstakes.

      In contrast, the top-down selections of the Cognosenti are light on memory, with a greater emphasis on attention, speech, mind-wandering, and reward.



      Word cloud for 16 titles/abstracts in four Invited Symposia.


      The member-generated Symposium Sessions are once again memory-centric, but with the key additions of speech, learning, information, and oscillations.



      Word cloud for 43 titles/abstracts in nine Uninvited Symposia.


      The hot area of the brain this year is OFC, the orbitofrontal cortex.

      Kicking off the meeting is a new addition to the program, a symposium on Big Ideas in Cognitive Neuroscience, which will focus on language, motor control/action, and (you guessed it) memory:

      Six speakers, in three pairs, will consider some major challenges and cutting-edge advances, from molecular mechanisms to decoding approaches to network computations. The presentations and debate aim to provide a tentative outline of what might be a productive and ambitious agenda for our fields.

      Speakers:
      • Charles R. Gallistel (Rutgers University) and Tomás Ryan (Trinity College Dublin & MIT) on memory.
      • Angela Friederici (Max-Planck-Institute) and Jean-Rémi King (NYU) on language.
      • John Krakauer (Johns Hopkins University) and Danielle Bassett (University of Pennsylvania) on action/motor.

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