Wednesday, February 26, 2020

Job opportunities at the University of Bristol

The School of Psychological Science at the University of Bristol is seeking to appoint a Senior Lecturer with a track record of high-quality research in the areas of neuropsychology/neuroscience of human cognition, emotion and behaviour. The successful applicant will join a collegiate, supportive department with a vibrant research environment and a passion for excellence in research and teaching. 
Funding for this opportunity follows from the creation of a new MSci programme in Psychology and Neuroscience that will be jointly taught with the School of Physiology, Pharmacology, and Neuroscience.  It is available on a full-time basis with the new MSci starting in September 2020.  
The successful applicant will have a strong, well-developed research profile beyond doctoral level, with an established record of high-quality publishing commensurate with the applicant’s career stage.  You will be able to demonstrate your ability to contribute effectively to the management and delivery of the new MSci programme and existing teaching, including supervising student dissertations and running tutorials. 
The successful candidate will assume responsibility for an appropriate share of administration and will be expected to interact effectively with other academic colleagues within and across subject areas and with external partners. 
The School holds a departmental Bronze Athena SWAN Award. We are committed to the equality of opportunities and to selection on merit. The School and University have a wide range of policies aimed at ensuring fair and effective recruitment and supporting staff in work. 
For further information about the role please contact the Head of School, Professor Chris Jarrold  (, or the School Education Director, Dr Chris Kent ( 
Interviews will be held on Tuesday 31st March 2020. 
We welcome applications from all members of our community and are particularly encouraging those from diverse groups, such as members of the LGBT+ and BAME communities, to join us.
The University of Bristol is seeking to appoint an outstanding academic leader as the Head of the School of Psychological Science.
This is an exciting opportunity for someone with inspirational leadership skills to lead and manage the academic business of the School in relation to both strategy and operations, fostering its academic strengths, and promoting research and teaching at the forefront of Psychology.
Outstanding leadership and academic credentials, an open and inclusive approach, and a track record of excellent partnership working are key requirements of the role.
Applications should be made online at (job number ACAD104404).
For more information or an informal discussion please contact Professor Jeremy Tavaré, Dean of Life Sciences,
The closing date for applications is 11.59pm on 15 March 2020.  The interview process will take place over two days on 25/26 March 2020.
We welcome applications from all members of our community and are particularly encouraging those from diverse groups, such as members of the LGBT+ and BAME communities, to join us.

Friday, February 7, 2020

Word comprehension in people with left temporal lobe damage

[This is a snippet from a book I'm (slowly) working on for MIT Press. The comprehension task we used here was adapted from Baker et al. 1981 and looked like this, where the auditory presented word to be comprehended was "bear" or on other trials "pear":


With the help of my collaborator and former student Corianne Rogalsky, I probed our chronic stroke dataset, identifying 24 cases of left unilateral temporal lobe damage. The image below shows a lesion overlap map with warmer colors indicating more overlap across patients. 

The average score on the bear-pear-moose-grapes test was 97.9% correct; 16 people had a perfect score, 6 got 95%, and the 2 lowest scorers were at 90% accuracy. Not bad given the sustained damage to Wernicke’s area.

Wednesday, January 15, 2020

RESEARCH FELLOW POSITION at the BCBL- Basque Center on Cognition Brain and Language (San Sebastián, Basque Country, Spain)

RESEARCH FELLOW POSITION at the BCBL- Basque Center on Cognition Brain and Language (San Sebastián, Basque Country, Spain) (Center of excellence Severo Ochoa)

The Basque Center on Cognition Brain and Language (San Sebastián, Basque Country, Spain) offers research fellow positions in three main broad areas or research: 

(1)-Language, reading and developmental disorders: How language acquisition, comprehension, production, and reading take place in the human brain. Special attention will be paid to language disorders and the development of computerized tools for their early diagnosis and treatment.

(2)-Multilingualism and second language learning: The cognitive and brain mechanisms of language acquisition and processing in a second language, taking into consideration the age of acquisition, proficiency and usage. Special attention will be paid to multilingualism within the school system and to the development of new educational technologies for second language learning.

(3)- Neurodegeneration, brain damage and healthy aging: Language and Cognition: Early cognitive and brain markers related to language for neurodegenerative diseases (Alzheimer, Parkinson); neural plasticity and language functions through brain stimulation in the awake patient during surgical brain operations; developing of computerized diagnostic and training tools for aphasic patients and neurodegenerative diseases.

The Center promotes a rich research environment without substantial teaching obligations. It provides access to the most advanced behavioral and neuroimaging techniques, including 3 Tesla MRI, a whole-head MEG system, four ERP labs, a NIRS lab, a baby lab including an eyetracker, two eyetracking labs, and several well-equipped behavioral labs.  There are excellent technical support staff and research personnel (PhD and postdoctoral students). 

We are looking for cognitive neuroscientists or experimental psychologists with a background in psycholinguistics and/or neighboring cognitive neuroscience areas, computational modelers, and physicists and/or engineers with fMRI/MEG expertise. 

These five year Fellowships are directed to promising young researchers; they are intended to offer a track towards a PI role and independent research. The selected Fellows should be able to acquire the necessary skills for a research leader role. Ikerbasque is committed to offer a long-term career to the research community: Fellows in their 5th year can be assessed for a permanent position.

The applicants must have their PhD completed between 1/1/2009 and 31/12/2017.

Applications from women are especially welcomed. The eligibility period will be extended under special circumstances such as maternity.

Support letter from the host group is mandatory.

To submit your application please follow this link:

Deadline: 24th March 2020

For further information about the fellowships, please contact the Director of BCBL, Manuel Carreiras (

Monday, December 23, 2019

What is cognition? The view from the early cognitive psychologists

[The following is an excerpt from Chapter 6 (The Embodied Mind) of The Myth of Mirror Neurons, which describes how early cognitive psychologists viewed their break from behaviorism as resting on the idea of information processing. The term "cognition" was later applied to this movement and ended up leading to some confusion because of the colloquial definition of cognition as applying to higher-level mental abilities...]
Computation and the information processing approach
The question then became, how does the brain process information?  The digital computer was being developed around the same time and served as a convenient heuristic to think about how the brain might achieve such a feat.  The basic idea is that there is information on the one hand and a set of processing routines (mental apps or computational algorithms) on the other.  The information serves as input to the processing routines, which then transform it according to the set of computations defined in the program (e.g., if x, then y) and the processing routines output the results of the transformations.  The output can then be stored as new information, serve as input to other programs, and control devices like a display or printer.  Inputs to a computer -- key presses, mouse jiggles and pokes, image captures -- don’t directly control what’s displayed on the monitor or what the printer prints; rather, those inputs are processed by various apps to convert them into words and images, solve math problems, or play solitaire.  It is the output of the apps that directly control what is displayed or printed.  
The point of the computer analogy, or more accurately the computer program analogy, is that the mind/brain works the same way: the inputs to the brain – photons hitting the retina, air pressure fluctuations impinging on the ear drum, and so on – don’t control human behavior directly; rather, those inputs are processed by various neural apps to convert them to words and images, solve math problems, or play solitaire  
Some early cognitive models looked very much like computer programs.  In fact, some were computer programs.  One of the most famous programs, developed in the 1950s by Allen Newell, J.C. Shaw, and Herbert Simon, was called the Logic Theorist.  The Logic Theorist, or LT as it was nicknamed, was written to prove theorems using symbolic logic, similar in spirit to what a high schooler encounters in geometry class.  The program was given a database of axioms (e.g., symbolic logic statements like “p or q implies q or p”) and a set of processing rules for using the axioms to generate proofs, rules such as substitution or replacement.  LT was then presented with a series of new logic expressions and instructed to discover the proof for each using the “given” axioms and the rules.  If it proved a theorem, it could store that proof along with the given axioms for use in subsequent proofs.  
LT performed quite respectably, proving 73% of the theorems it was given. Writing a program that could pass a high school geometry class was an impressive accomplishment for the infant field of computer science, but it had far more significance for the information processing approach to understanding human behavior. LT showed that complex, human-like behavior could be approximated quite well with a purpose-built information processing system.  And this is how Newell et al. presented the LT program, as a straight-up theory of human problem solving. To bolster their argument, the team presented evidence that LT’s problem solving “behavior” exhibited features characteristic of humans solving similar problems, such as its ability to learn, its demonstration of a kind of “insight” (trying at first to solve a problem with trial and error and then, once hitting upon the solution, using the same approach to solve similar problems), and its ability to break a problem down into sub-problems.  
Now, Newell and company were careful to point out that their theory does not imply that humans are digital computers, only that humans appear to be running a program similar to LT.  
We wish to emphasize that we are not using the computer as a crude analogy to human behavior—we are not comparing computer structures with brains, nor electrical relays with synapses. Our position is that the appropriate way to describe a piece of problem-solving behavior is in terms of a program: a specification of what the organism will do under varying environmental circumstances in terms of certain elementary information processes it is capable of performing. This assertion has nothing to do—directly—with computers. Such programs could be written (now that we have discovered how to do it) if computers had never existed.  A program is no more, and no less, an analogy to the behavior of an organism than is a differential equation to the behavior of the electrical circuit it describes. Digital computers come into the picture only because they can, by appropriate programming, be induced to execute the same sequences of information processes that humans execute when they are solving problems. Hence, as we shall see, these programs describe both human and machine problem solving at the level of information processes.
It was a one-two punch for behaviorism.  Chomsky and others had pointed out the inadequacy of simple associationist explanations of human behavior and symbol-manipulating computer programs provided a viable and directly observable account of how the brain processes information.  Psychology whole-heartedly embraced the information processing approach.
The movement was later termed the cognitive revolution, an unfortunate term in my view because it implies that the revolution holds only for the everyday definition of “cognitive,”  higher-order functions like language, memory, problem solving, and the like. It is true that the majority of the earliest work in the field focused on these complex human behaviors, but the real point of the revolution was that everything about human behavior -- perception, motor control, all of psychology -- is a result of information processing.  Psychologist Ulric Neisser, who literally named the field and wrote the book on it with his 1967 text, Cognitive Psychology, defined the domain of cognition this way:
“Cognition” refers to all the processes by which the sensory input is transformed, reduced, elaborated, stored, recovered, and used.  … Such terms as sensation, perception, imagery, retention, recall, problem-solving, and thinking, among many others, refer to hypothetical stages or aspects of cognition.
Neisser’s table of contents underlined his view that cognition was not limited to higher-order functions.  His volume is organized into four parts.  Part I is simply the introductory chapter.  Part II is called “Visual Cognition” and contains five chapters.  Part III is “Auditory Cognition” with four chapters. Finally, Part IV deals with “The Higher Mental Processes” and contains a single chapter, which Neisser refers to as “essentially an epilogue” with a discussion that is “quite tentative”. He continues,
Nevertheless, the reader of a book called Cognitive Psychology has a right to expect some discussion of thinking, concept-formation, remembering, problem-solving, and the like…. If they take up only a tenth of these pages, it is because I believe there is still relatively little to say about them…. 
Most scientists today working on perception or motor control, even at fairly low levels, would count their work as squarely within the information processing model of the mind/brain and therefore within Neisser’s definition of cognition.  Consider this paper title, which appeared recently in a top-tier neuroscience journal: Eye Smarter than Scientists Believed: Neural Computations in Circuits of the Retina.  If anything in the brain is a passive recording device (like a camera) or a simple filter (like polarized sunglasses) it’s the retina, or so we thought. Here’s how the authors put it:
Whereas the conventional wisdom treats the eye as a simple prefilter for visual images, it now appears that the retina solves a diverse set of specific tasks and provides the results explicitly to downstream brain areas.
Solves a diverse set of specific tasks and provides the results… sounds like a purpose-built bit of programing—in the retina!  We observe similar complexity in the control of simple movements, such as tracking an object with the eyes, an ability that is thought to involve a cerebral cortex-cerebellar network including more than a half dozen computational nodes that generate predictions, detect errors, calculate correction signals, and learn. It is not much of an overstatement to say that there is universal agreement among perceptual and motor scientists in neuroscience and psychology that perception and action are complex systems that actively transform sensory information and dynamically control action. As Neisser wrote in 1967, “Information is what is transformed, and the structured pattern of its transformations is what we want to understand.” The information processing model of the mind -- cognitive psychology as defined eloquently by Ulric Neisser -- now dominates the study of the mind/brain from computation in the retina to motor control to complex problem solving.
[The rest of the chapter considers the contribution of embodied cognition in this context.]

Tuesday, October 22, 2019

PhD Opportunities in San Sebastian, Spain--BCBL

The Spanish Ministry of Science, Innovation and Universities has published the call for PhD Students 2019. The application period is from 17/10/19 to 07/11/19 at 14:00h.

The call offers:


Key words: Thalamus, Language Systems, Reading, Vision, Functional Connectivity, Structural Connectivity, Lateral Geniculate Nucleus, Medial Geniculate Nucleus, Pulvinar

Summary of the project:

Since the early 1960s, evidence from spontaneous and surgical lesions has pointed to the involvement of the human thalamic nuclei in language function. Several proposals have been put forward regarding a thalamic role in cognitive function in general and language function in particular. However, to date, our understanding of the role of the thalamus in language function remains limited. The thalamus is a diencephalic structure with massive white matter fiber projections to almost the entire cerebral cortex. It is involved in the flow of sensory signals to the cortex and continues to contribute to the processing of information within cortical hierarchies. Among other functions, the thalamus is involved in the regulation of consciousness, sleep and alert states, the motor system, language, memory and attention, as well as in clinical conditions such as schizophrenia, Alzheimers disease and dyslexia. Recently, we developed the first probabilistic atlas of the human thalamic nuclei combining high-resolution ex vivo magnetic reasonance imaging (MRI) and histology, and have implemented a companion segmentation toolbox in the neuroimaging package FreeSurfer to support in vivo study of the thalamus and its subnuclei in MRI research. The proposed research project will capitalize on this tool, the well-known neuroanatomy of thalamocortical connections and the use of multimodal MRI techniques to investigate: 1) the developmental trajectories of the thalamic nuclei gray-matter volume and white matter connections across the life span and their relation to individual differences in language-related variables; 2) the functional and structural involvement of specific thalamic nuclei and their thalamocortical interactions in language production, speech comprehension and reading in a large sample of young adults; 3) the functional and structural contributions of thalamocortical circuits to reading in typically and atypically-developing samples with reference to some of the most important theories of reading and dyslexia. Thus, this research project aims to conduct a comprehensive multimodal investigation of thalamic contributions and thalamocortical interactions in language function within a neurocognitive, neuroanatomical and psycholinguistic framework. A key focus will be a better understanding how reading disabilities may occur as a consequence of breakdowns in thalamocortical circuits. In this regard, this project stands at the cutting edge of national and international research precisely tracking the role of the thalamus in language function, and will further allow the development of a mechanistic model of the contribution of the thalamic subnuclei and their interactions with cortical regions to central language systems.
Individuals interested in the PhD position should have:
  • A strong theoretical and methodological background in cognitive neuroscience, biomedical engineering or experimental psychology.
  • A strong level of written and spoken English.
  • Strong computational skills (Matlab, Python,…)
Research experience with neuroimaging techniques (MRI, M/EEG) will be an asset. Possession of a Master degree in Cognitive Neuroscience, Biomedical Engineering, Experimental Psychology or any other related area is highly recommended and will be positively valued.
For more information:


Key words: Music training, Speech processing, Auditory cortical entrainment, Audiovisual synchronization, Predictive timing, Magnetoencephalography, Naturalistic stimulation

Summary of the project:
Recent studies have shown that musicians outperform nonmusicians on a variety of tasks related to speech processing, suggesting that musical training may boost our ability to process auditory language. Yet, we know very little about the neurocognitive mechanisms underlying such musician advantage. On one hand, a several studies suggest that musical training enhances the sensitivity of the auditory pathways to sound in general. This would improve human acoustic skills that may in turn transfer to language acquisition and processing.
On the other hand, it has been hypothesized that musical training might refine the interaction between motor and auditory regions. This in turn would boost the ability to develop regular and precise temporal predictions, utilizing more fine-tuned motor production plans of the spoken sounds. Understanding which is the driving force underlying the improved language performance in musicians is a topic of central interest in cognitive neuroscience, with inevitable implications for the development of intervention strategies for language acquisition and associated developmental disorders. This project aims at informing such applied research by uncovering the neural mechanisms underlying the musician advantage. To this purpose we will study auditory cortical entrainment in musicians and nonmusicians. Cortical entrainment refers to the ability of the brain to naturally synchronize its internal oscillatory activity with the rhythm of the external auditory signals. This phenomenon has been shown to play a pivotal role in the extrapolation of linguistic tokens from acoustic signals and in the construction of coherent auditory representations. Crucially, different components of this phenomenon have been linked to both passive auditory sensitivity (involving auditory regions) and active predictive timing (involving premotor regions). Comparing rhythmic auditory processing and cortical entrainment to speech and music in musician vs nonmusicians will provide us with a unique model to (1) evaluate the specific aspects of language processing that are enhanced by music training; (2) unveil the specific neurocognitive mechanisms underlying such improved performance; and (3) use the fundamental knowledge of (1) and (2) to define better treatment for intervention in language disorders.


Research experience with neuroimaging techniques (MRI, M/EEG) will be an asset. Possession of a Master degree in Cognitive Neuroscience, Biomedical Engineering Experimental Psychology or any other related area is highly recommended and will be positively valued.
For more information:

1 PhD Student position (4-year contract) to join RTI2018-093547-B-I00: Is the brain connectome a good predictor for the language network functional malleability? LangConn to be supervised by Prof. Carreiras and Dr. Quiñones.

Key words: Language network, connectome, individual variabilities, neuroplasticity, graph-theory, second language learners, pre-surgical patients, low-grade glioma

Summary of the project:
The current project introduces a novel multivariate network-based approach where the combination of functional and structural measures will allow us to characterize the language connectivity fingerprints (i.e., connectome) taking also into account its intrinsic individual variability. Using this pioneering approach, we will characterize the connectome underlying the decoding and integration of linguistic signals and determine whether this connectome could be used to predict individual differences in language performance. For the first time, structural and language-related functional measures will be collected on the same participants across different language-specific tasks (i.e., comprehension and production) in two different languages (i.e., Spanish-L1 and Basque-L2). After the definition and characterization of the language connectome, it will be possible to investigate the capacity of this system to react when a salient language-related event occurs. The location of Donostia-San Sebastian, where the BCBL is situated, and the work relationship established between our institution and the Hospital Universitario Cruces in Bilbao, offers a unique opportunity to address this question. The Basque Country holds a Spanish-Basque bilingual population where it is possible to test people with different linguistic profiles. Thus, here at the BCBL, we have access to two different populations where neural plasticity seems to be a remarkable feature in terms of neural adaptability: (1) adults second language learners and (2) pre-surgical patients with low-grade gliomas affecting perisylvian areas involved in the processing of linguistic signals. While the first group allows us to investigate neural plasticity associated with the acquisition of new language-specific knowledge in a healthy and functionally typical brain, the second group of participants enables us to study the neural capacity to negotiate L1 and L2 language information after the removal of a critical language-related area. In summary, our primary goal is to determine to what extent the language connectome could be used to predict plastic changes associated with language-related salient events. Thus, in order to test the predictability power of the language connectome, we propose a longitudinal approach where both adults L2 learners and pre-surgical patients will be recorded before and after the occurrence of the critical event. Specifically, L2 learners will be recorded before and after they learn to read/speak in a second language, and the pre-surgical patients will be tested before and six months after brain surgery. By longitudinally tracking individual profiles at both behavioral and neural levels, with a special focus on changes in the network topology and dynamics, it is possible to bridge the gap between language functions, bilingualism and brain plasticity.
Individuals interested in the PhD position should have:
  • MSc in Psychology (preferable biological or experimental psychology), Biomedical Engineering, or any other related area. Good experimental and statistical skills and excellent written and spoken English.
  • Previous experience with neuroimaging methods and programming are a plus.
For more information:

Friday, October 18, 2019


Three-year NIH-funded fellowships are available at the Moss Rehabilitation Research Institute (MRRI), in collaboration with the University of Pennsylvania (Penn), for research training in cognitive and motor neuroscience and neurorehabilitation. 
Available mentors conduct patient-oriented research using behavioral, computational, imaging, electrophysiologic, and electrical and pharmacologic neuromodulation methods. We welcome applications from individuals with a doctorate in psychology, cognitive science, communication science, kinesiology, movement science, or human neuroscience, who wish to learn to apply basic science principles to the study and treatment of behavioral and brain deficits in adult neurological patients. We also welcome applications from individuals with clinical rehabilitation backgrounds seeking to increase their depth in the basic science underpinnings of assessment and treatment. Applicants must have a track record in research and an interest in developing an independent research career.
We are an Equal Opportunity Employer; we are committed to ensuring a range of diversity among our training classes, and we strive to select candidates representing different kinds of programs and theoretical orientations, geographic areas, ages, racial and ethnic backgrounds, sexual orientations, disabilities, and life experiences. All things being equal, consideration is given to candidates who identify themselves as members of historically under-represented groups on the basis of racial or ethnic status, as representing diversity on the basis of sexual orientation, or as representing diversity on the basis of disability status. This may be indicated in the cover letter.
Mentors Include:
Laurel Buxbaum (MRRI)
Anjan Chatterjee (PENN)
Branch Coslett (PENN)
John Detre (PENN)
Dylan Edwards (MRRI)
Murray Grossman (PENN)
Roy Hamilton (PENN)
Shailesh Kantak (MRRI)
Erica Middleton (MRRI)
Amanda Rabinowitz (MRRI)
John Whyte (MRRI)

Applications should be submitted to Kevin Whelihan, Research Administrator,
( ) and must include:
- current CV
- letter describing research interests and career goals
-Given the translational focus of the training program, applicants should indicate a preferred primary mentor and, if possible, a secondary mentor.  The mentors should offer a good fit in balancing basic and applied aspects of the candidate’s interests.
- 2-3 letters of reference
Applications will be reviewed beginning November 1, 2019

Thursday, October 17, 2019

Postdoctoral Research Associate Computational neuroscience of human speech recognition - UCONN

Profs. James Magnuson and Jay Rueckl at the University of Connecticut, Department of Psychological Sciences, seek a postdoctoral research associate for a project focused on computational approaches to understanding the cognitive and neurobiological bases of human speech recognition. Our primary objective is bridging the gap between current cognitive models of human speech processing (such as TRACE) and cutting-edge deep learning models used for automatic speech recognition. The postdoctoral research associate will contribute to this project by playing a leading role in our computational work (devising, developing, and testing neural network models, and comparing them to human behavior and neurobiology), while having room to lead new projects related to this theme. 

The University of Connecticut (UConn) is home to a vibrant, interdisciplinary community of researchers in the brain and cognitive sciences, including more than a dozen labs with primary focus on language. UConn and the Magnuson and Rueckl labs are committed to increasing diversity in the STEM workforce. 

• PhD in psychology, neuroscience, linguistics, computer science, engineering, or a related field
• High level of expertise in Python and R
• Strong record of research (as demonstrated by presentations and publications)
• Evidence of ability to complete projects
• Evidence of strong writing skill

• Experience with TensorFlow
• Experience with another framework for neural network modeling
• Experience with Java or other programming languages
• Training and experience in empirical research with human subjects
• Hardware proficiency (e.g., ability to select components for and assemble a workstation for deep learning)

Start date for this position is anticipated for Fall, 2019, or early 2020. The position is for an initial one-year appointment and is potentially renewable until June, 2021. Continuation beyond June, 2021 is contingent upon future external funding applications. Salary for this position will be determined by NIH guidelines ($50,004 annually minimum).

Please apply online via UConn Jobs (, Staff positions, Search #2020123. For full consideration, candidates should submit a resume or CV, a personal statement describing their research interests and goals, and up to three supplemental PDF documents that reflect their academic writing (e.g., journal publications, Master's thesis, or dissertation). Three letters of recommendation should be emailed directly from letter writers to Dr. James Magnuson ( Screening of applicants will begin immediately. 

Employment of the successful candidate is contingent upon the successful completion of a pre-employment criminal background check. (Search #2020123)

This job posting is scheduled to be removed at 11:59 p.m. on November 15, 2019.

All employees are subject to adherence of the State Code of Ethics, which may be found at

The University of Connecticut is committed to building and supporting a multicultural and diverse community of students, faculty, and staff. The diversion of students, faculty, and staff continues to increase, as does the number of honors students, valedictorians and salutatorians who consistently make UConn their top choice. More than 100 research centers and institutes serve the University's teaching, research, diversity, and outreach missions, leading to UConn's ranking as one of the nation's top research universities. UConn's faculty and staff are the critical link to fostering and expanding our vibrant, multicultural and diverse University community. As an Affirmative Action/Equal Employment Opportunity employer, UConn encourages applications from women, veterans, people with disabilities, and members of traditionally underrepresented populations. 

James S. Magnuson -- website -- 860.486.3525 --