Wednesday, November 25, 2015

Call for Papers: Translating Research to Practice in the Language Sciences

Special Issue of Translational Issues in Psychological Science (TPS)

Submissions accepted from January 15 - March 1, 2016

We are encouraging submissions for consideration in a special issue titled “Translating
Research to Practice in the Language Sciences” in the innovative journal titled Translational
Issues in Psychological Science, co-sponsored by the American Psychological Association
(APA) and the American Psychological Association of Graduate Students (APAGS).

“Translating Research to Practice in the Language Sciences” is due out in in March of 2017.
For this issue, the Editors will consider manuscripts across a broad area of language science
research concerning such topics as:

• Cognitive and neural consequences of bilingualism
• Enhancing second language learning
• Raising bilingual children
• Global perspectives on language science
• Language and aging
• Advances in the neuroscience of language
• Language development and atypical trajectories
• Translating language science to the classroom
• Literacy across the lifespan and language context
• Other important and timely topics in language science research

Manuscripts submitted to TPS should be co-authored by at least one psychologist in training
(graduate student, postdoctoral fellow), should be written concisely for a broad audience, and
focus on the practical implications of the research presented in the manuscript. For more
information about the journal, including detailed instructions to authors, visit the TPS website

The deadline for submissions is March 1, 2016. Please feel free to forward this correspondence

to interested colleagues and the psychologists in training with whom you work.

Mary Beth Kenkel, PhD, Editor-in-Chief 
Daniel J. Weiss, PhD, Special Issue Editor

American Psychological Association
750 First Street NE, Washington, DC 20002
Phone: (202) 336-5667 Fax: (202) 336-5549

Monday, November 23, 2015

Multiple Positions in Human Neuroimaging -- UC Riverside

The University of California, Riverside, invites applications for five positions in human neuroimaging at the Assistant & Associate level. Successful candidates will become core faculty in the newly established Human Neuroimaging Center that includes a new Prisma 3T Siemens scanner. We seek applicants with a strong track record of research publications and funding (or funding potential) in basic science and methods of human neuroimaging with one position in each of the following areas: Human Cognitive Neuroscience (speech/language, learning/memory, attention, perceptual systems),  Human Developmental Neuroscience (cognitive development, emotion regulation, lifespan, psychopathology),  Human Social Neuroscience (social cognition, affect, relationships, personality),  MR Physics/Engineering (MRI sequences and reconstruction, DTI, SWI, hardware, MR spectroscopy), and Neuroimaging Data Processing/Analysis (fMRI data processing and analysis, neuroimaging data mining and imaging genetics, MRI computational neuroscience),
Applicants should be committed to excellence in undergraduate and graduate education. UCR is a world-class research university with an exceptionally diverse undergraduate student body. Its mission is explicitly linked to providing routes to educational success for underrepresented and first-generation college students. A commitment to this mission is a preferred qualification. Salary will be commensurate with education and experience. Review of completed applications begins January 4, 2016 and continues until a position is filled, with appointments beginning June 30, 2016.

Interested candidates should send a cover letter describing research and teaching interest, their curriculum vitae, reprints and preprints, and should arrange to have three letters of recommendation provided. Application to senior rank positions must have a Ph.D in a related field, and apply at this link: Applicants for junior ranked positions must have a Ph.D. by time of appointment and should apply at this link: Advancement through the faculty ranks at the University of California is through a series of structured, merit-based evaluations, occurring every 2-3 years, each of which includes substantial peer input. Questions about the position should be directed to Professor John Andersen, Chair, Human Neuroimaging Search Committee, at

The University of California at Riverside (UCR) is embarking on a major new hiring initiative that will add 300 tenured and tenure-track positions in 33 cross-disciplinary areas selected through a peer-reviewed competition. Over the next three years, we will hire multiple faculty members in each area and invest in research infrastructure to support their work. This initiative will build critical mass in vital and emerging fields of scholarship, foster truly cross-disciplinary work and further diversify the faculty at one of America’s most diverse research universities. We encourage applications from scholars committed to excellence and seeking to help redefine the research university for the next generation. For information regarding UCR’s hiring initiative go to

The University of California is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, protected veteran status, or any other characteristic protected by law.

Friday, October 30, 2015

Mirror neurons do not have the right response properties to support action understanding

Ten years ago the action understanding interpretation of monkey mirror neurons was the only game in town.  There really was no other viable account so even if there were problems with the theory (e.g., 8 in particular), it was the best we had.  Now there are alternative explanations.  Cecelia Heyes has argued that they reflect learned sensorimotor associations (that don't support understanding), recent writings of Michael Arbib and separately James Kilner have argued that they fundamentally serve a motor control function but which are used fruitfully to augment perceptual function via predictive coding, and I have argued for something of a hybrid between Heyes and Arbib/Kilner: MNs reflect learned sensorimotor associations that are critical for motor control (action selection specifically) and may modulate perception a tiny bit under rather rare circumstances.

This is great progress because it means we are now in position to evaluate the various theories against existing data and just see which one does a better job of explaining the facts.

I have argued extensively that the action understanding theory does not hold up well to lesion data. Disruption of the mirror system by stroke, sodium amytal, degenerative disease, or developmental disease does not impair action understanding in the way that the Parma story should predict.  Add to this an impressive, new, large N study on gesture comprehension, and the evidence against the action understanding theory in humans is overwhelming.

But what about monkey mirror neurons? They still look like they are coding some sort of action understanding, right?  Not if you actually look at the data rather than reading the headlines.

I discussed this issue in my debate with Gallese.  You can watch the whole thing here, but to put the argument into a condensed form, I reiterate it below.

First, what got everyone so excited about mirror neurons in the first place is that some of them showed a fairly strict congruence in their response preference for executed and observed actions: cells that responded to, say, whole hand grasping in execution and observation.  There are other, more broadly congruent mirror neurons too, but these took a theoretical back seat in the 1990s.  But there was a problem: strictly congruent mirror neurons aren't that useful for understanding because they can't recognize that grasping with a whole hand grip and grasping with a pincher grip are both instances of grasping.  They are simply too specific.  So the bulk of the theoretical work with monkey mirror neurons has shifted to broadly congruent mirror neurons, which in fact, are more common anyway (see below).  Here's some quotes from this paper by the Parma group to prove that I'm not making this stuff up:

How is understanding achieved?
“The similarity between the motor representation generated in observation and that generated during motor behavior allows the observer to understand others’ actions, without the necessity for inferential processing.”
What counts as similar?
“neurons in F5 code the goal of the motor act [grasping, holding, tearing], regardless of how it is achieved.”  
“The defining characteristic of F5 mirror neurons is that they fire in response to the presentation of a motor act, which is congruent with the one coded motorically by the same neuron.”
Which types of mirror neurons are critical? 
“the vast majority of F5 mirror neurons, termed broadly congruent respond to different motor acts, provided that they serve the same goal (Gallese et al. 1996).
“Thus, like the visual system, where, as postulated by Shepard (1984), resonating elements (neurons or neuronal assemblies) respond maximally to a set of stimuli, but are also able to respond to similar stimuli when they are incomplete or corrupt, a set of mirror neurons (broadly congruent) appears to resonate to all visual stimuli that have sufficient critical features to describe the goal of a given motor act.”

So what do the data show?  Most of the relevant data come from the first major mirror neuron study in which a range of actions was examined.  After that initial study research on monkey mirror neurons has focused almost exclusively on one type of action: grasping.  (We should probably worry about that.)  So let's look at that first and more thorough study.  

Here is the distribution of cell types:

1. Strictly congruent: 31.5%

Same goal (e.g., grasping), same motor act (e.g., precision grip)
Can’t capture the similarity in goal between grasping with precision grip vs. whole hand grip as pointed out above.

2. Broadly congruent: 60.9%
  • Type 1 (12.5%): execution response=“highly specific” (e.g., grasping w/precision grip); observation response more general (precision or whole hand)

Captures the similarity between precision and whole hand grasping, but “interprets” them as one or the other specific type of grasping and doesn’t capture the similarity between grasping with hand & mouth, for example.  Therefore these have a similar problem to the strictly congruent MNs.
  • Type 2 (82%): execution response=one goal (e.g., grasping); observation response > 1 goal (e.g., grasping or manipulating)

Falsely collapses different goals onto a single goal, i.e., confuses manipulating and grasping.
  • Type 3 (5%): execution response=grasping; observation response=grasping with hand, grasping with mouth

Responds to goals! This is a useful subtype for action understanding. But only 3 cells out of 92 mirror neurons & only one goal represented (grasping). If you want to maintain an action understanding theory, this is what you have to hang your hat on. 

 3. Non-congruent (7.6%)
No obvious relation between execution and observation preferences. Not useful for understanding.

There are more problems, which may apply to the 3/92 cells that have the right response properties for understanding, making their suitability for understanding questionable.  Mirror neurons are sensitive to all sorts of features that have nothing to do with action understanding.  Here's a list:

And indeed the Parma group has acknowledged this and claimed that mirror neuron system "contributes to choosing appropriate behavioral responses to those actions" (Caggiano et al. 2009)

Notice that all of these response properties make sense if this system is simply coding relations between a range of actions and a range of possible action responses.  For example Type 2 congruent mirror neurons (by far the most common) take multiple possible observed actions and map them onto a single executed response.  This is useful for motor selection if a single motor response is appropriate to multiple cue types but not useful for understanding.  For another example, the value of the grasped object should modulate response selection (do I want to grasp that object?) but should not play a role in action understanding. 

The evidence is overwhelming:

1. Monkey mirror neurons have response properties that do not fit the action understanding theory and instead fit an action selection account.

2. Human data from stroke and other neurological conditions clearly demonstrate a dissociation between action execution and action understanding ability in a range of domains (speech, praxis, sign language, emotional face recognition).  

If this isn't convincing, what evidence do we need to reject the action understanding account?  Or is it an unfalsifiable theory?   

Thursday, October 29, 2015

What does embodied simulation add to understanding?

Observing someone else being touched seems to activate one's own somatosensory cortex (e.g., this report).  It is has been claimed that this effect contributes to action understanding via embodied simulation. Some view this as an example of the "mirror mechanism" by which we understand others by mirroring their experience in our own bodies (or something like that).

First note that this touch-based "mirror mechanism" is quite different from so-called motor mirroring. The motor claim is non-trivial: perceptual understanding is not achieved by perceptual systems alone, but must (or can benefit from) involvement of the motor system.

What about perceptual mirroring?  At the most abstract level, the claim is this: perceptual understanding is based on perceptual processes.  Not so insightful is it?  Perhaps it's even vacuous. But maybe this is too harsh an analysis.  One could presumably understand the concept of someone being touched on the arm without involving an actual somatosensory representation.  So maybe it is non-trivial, insightful even, that we do activate our touch cortex when observing touch.  In fact, for the sake of argument, let's grant that the empirical observation is true and that it does contribute to our understanding.

What might it add to understanding?  Or put differently, how much does that somatosensory "simulation" add to our understanding of an observed touch?  Consider the following narrative scenarios.

Scenario #1: After he expressed his affection during the romantic dinner, the man reached out and touched the girl gently on the arm.

Scenario #2: After subduing his victim during the home invasion, the man reached out and touched the girl gently on the arm.

How much our understanding of the meaning of that touch action is encoded in the somatosensory experience?  Almost none of it.  The "meaning" of the action is determined for the most part by the context as it interacts with the observed action. The touch wouldn't even have to actually happen, or it could occur on a different body part (all very different experiences from a somato standpoint!), and it wouldn't alter our understanding of the event.  Yes, it's true that simulating the actual touch might add something, i.e., having a sense of what the actual gentle touch felt like on the arm, but what drives real understanding is the interpretation of that touch in its context, not the somatopically specific touch sensation itself.

Conceptualized in these terms, to say that somatosensory simulation contributes to understanding of others' touch experiences is like saying that "acoustic simulation" of the voiceless labiodental fricative in the experience of hearing "fuck you" contributes to the understanding of that phrase.  Yes, I suppose the /f/ plays a role, but how it combines with "uck you" and more importantly who said it to whom and under what circumstances is where the meat of the understanding will be found.

It's interesting and worthwhile to understand all the cognitive and neural bits and pieces that contribute to understanding.  Lowish-level embodied "simulation," whether motor or sensory, may have a role to play.  But it is important to understand these effects in the broader context.  Don't for a second think that we've cracked the cognitive code for understanding just because M1 or S1 activates when we see someone do something.

Tuesday, October 13, 2015

The Embodied Cognition Challenge

Typical embodied cognition experiments ask whether low-level sensory or motor information affects performance on this task or that.  The journals are filled with these kinds of experiments.  Some of these effects might even be real.  Assuming some of these effects are indeed real, let's now move on to the next questions: How much of the variance in performance does embodied cognition explain? And can embodied models improve on standard models?

I've pointed out previously that embodied effects are small at best. Here's an example--a statistically significant crossover interaction--from a rather high-profile TMS study that investigated the role of motor cortex in the recognition of lip- versus hand-related movements during stimulation of lip versus hand motor areas:

Effect size = ~1-2%  This is typical of these sorts of studies and beg for a theory of the remaining 98-99% of the variance.

A Challenge

So, let me throw out a challenge to the embodied cognition crowd in the context of well worked out non-embodied models of speech production.  Let's take a common set of data, build our embodied and non-embodied computational models and see how much of the data is accounted for by the standard versus the embodied model (or more likely, the embodied component of a more standard model).

Here is a database that contains naming data from a large sample of aphasic individuals.  The aim is to build a model that accounts for the distribution of naming errors.

Here is a standard, non-embodied model that we have called SLAM for Semantic-Lexical-Auditory-Motor.  (No, the "auditory-motor" part isn't embodied in the sense implied by embodied theorists, i.e., the level of representation in this part of the network is phonological and abstract.)  Here's a picture of the structure of the model:

This model accounts for about 98% of the variance in patient naming error-type distributions.  Here is an example fit for a single patient (figure from Walker & Hickok, in press, PB&R), which shows the percent response for various categories of response types (correct, semantic error, formal error etc) for the patient (dotted line) and the model (solid line):

Incidentally, Matt Goldrick argued in a forthcoming reply to the SLAM model paper that this fit represents a complete model failure due to the fact that the patient had zero semantic errors whereas the model predicted some. This is an interesting claim that we had to take seriously and evaluate quantitatively, which we did.  But I digress.

The point is that if you believe that embodied cognition is the new paradigm, you need to start comparing embodied models to non-embodied models to test your claim.  Here we have an ideal testing ground: established models that use abstract linguistic representations to account for a large dataset.

My challenge: build an embodied model that beats SLAM.  You've got about 2% room for improvement.

Thursday, October 8, 2015

Postdoctoral Research Fellow – Neurobiology of Language and Memory, Queensland University of Technology (QUT)

The Language, Cognition and Brain Sciences (LCBS) laboratory at Queensland University of Technology (QUT) is seeking a motivated and enthusiastic Postdoctoral Research Fellow to contribute to a range of research projects investigating the neurobiology of language in both healthy and language-impaired individuals. Applicants should have completed a PhD or have submitted a PhD for qualification in psychology, linguistics, cognitive neuroscience, speech pathology or an equivalent field, and have proven technical ability with a demonstrated publication track record in diffusion tensor imaging (DTI) and functional magnetic resonance imaging (fMRI). Appointment may be made at Level A or B, depending on the qualifications and experience of the successful applicant. 

Work conducted within the lab focuses on investigating the neural and cognitive mechanisms responsible for language processing in healthy individuals, how these mechanisms are affected by brain tumours and stroke, and how language recovery can be facilitated by various treatments. It is anticipated that the appointee will work across a range of projects involving neuroimaging, brain stimulation, genetic and psycholinguistic methods. There will also be opportunity for the appointee to develop new projects and obtain competitive funding based on their own research interests, in alignment with the goals and interests of the lab.

The position will entail conducting research at the Herston Imaging Research Facility (HIRF), a purpose built state-of-the-art imaging centre. The HIRF is a joint initiative between the Queensland University of Technology, Metro North Hospital and Health Service, the QIMR Berghofer Medical Research Institute, the University of Queensland, and industry partner Siemens. The primary focus of HIRF is on research, with a 3 Tesla Siemens Prisma MRI equipped for cognitive neuroscience research (including a 64-channel BrainProducts MR-compatible EEG system), in addition to Siemens PET-MR and PET-CT systems.

Interested candidates should apply online via the  QUT website or Seek addressing the selection criteria.

The deadline for application is November 15, 2015. Questions regarding this position may be addressed to the lab director, Prof Greig de Zubicaray:

Monday, October 5, 2015

University of California, Irvine Junior Faculty Position in Language Science

The Program in Language Science ( at the University of California, Irvine (UCI) is seeking applicants for a tenure-track assistant professor faculty position. We seek candidates who combine a strong background in theoretical linguistics and a research focus in one of its sub-areas with computational, psycholinguistic, neurolinguistic, or logical approaches.
The successful candidate will interact with a dynamic and growing community in language, speech, and hearing sciences within the Program, the Center for Language Science, the Department of Cognitive Sciences, the Department of Logic and the Philosophy of Science, the Center for the Advancement of Logic, its Philosophy, History, and Applications, the Center for Cognitive Neuroscience & Engineering, and the Center for Hearing Research. Individuals whose interests mesh with those of the current faculty and who will contribute to the university's active role in interdisciplinary research and teaching initiatives will be given preference.
Interested candidates should apply online at with a cover letter indicating primary research and teaching interests, CV, three recent publications, three letters of recommendation, and a statement on previous and/or past contributions to diversity, equity and inclusion.
Application review will commence on November 20, 2015, and continue until the position is filled.
The University of California, Irvine is an Equal Opportunity/Affirmative Action Employer advancing inclusive excellence. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age, protected veteran status, or other protected categories covered by the UC nondiscrimination policy.