From the US News & World Report:

Cognitive science. This relatively new interdisciplinary field blends elements of psychology, computer science, philosophy, neuroscience and linguistics. In other words, it studies the mind, its processes and the nature of intelligence.

“It’s really about how people think in mental terms and neural terms,” says Michael McCloskey, professor of cognitive science at Johns Hopkins University in Baltimore, where the number of students choosing the major has doubled in the last five years.

There’s an emphasis on how to think critically and engage in constructive problem-solving. Cognitive science majors go on to work in health care settings, such as in hospital administration or as research coordinators in labs; neuropsychological testing centers; business-related careers such as marketing; and the technology sector, among others. The major can also be good training for medical school, law school and business school, McCloskey notes.

Schools with dedicated programs include Tufts University in Massachusetts, the University of California—Berkeley, the University of California—San Diego, Rice University in Houston and the University of Pennsylvania.

https://www.usnews.com/education/best-colleges/articles/2018-09-11/8-college-majors-with-great-job-prospects

Abstract:  Word embeddings are a widely-used tool to analyze language. Exponential family embeddings generalize the technique to other types of data by modeling the conditional probability of a target observation (a word or an item) conditioned on the elements in the context (other words or items).

One challenge to fitting embedding methods is sparse data, such as a document/term matrix that contains many zeros. We develop zero-inflated embeddings to address this issue. In a zero-inflated embedding (ZIE), a zero in the data can come from an interaction to other data (i.e., an embedding) or from a separate process by which many observations are equal to zero (i.e. a probability mass at zero). Fitting a ZIE naturally down-weights the zeros and dampens their influence on the model.

Another challenge is that the appear-to-be context often contains unrelated items. The embedding model considering all context elements will encode noisy co-occurrences as item relations in the embedding. We improve the quality of the embedding representations by choosing a subset of context elements for the embedding model. We develop a probabilistic attention model and use amortized variational inference to automatically choose this subset.

Bio:  Liping Liu holds the position of “The Schwartz Family Assistant Professor” at Tufts University. His research interests include variational inference, generative models, and embedding models. Prior to joining Tufts, Liu worked as a postdoctoral associate at Columbia University. Advised by Prof. David Blei, he worked on probabilistic embedding models. He earned his doctorate degree at Oregon State University, where he studied probabilistic models and applied these techniques to ecology studies. He also has industry experiences at IBM T.J. Watson Research and Alibaba. He is a reviewer for main machine learning conferences and journals, such as ICML, NIPS, ICLR, AISTATS, JMLR, and TPAMI.

From Paul Katz

Darcy Kelley is a Fellow of the American Academy of Arts and Sciences and an HHMI Professor.

She is the Harold Weintraub Professor of Biological Sciences in the Department of Biological Sciences at Columbia University.

Darcy studies the neural, hormonal, and genomic underpinnings of communication in different species of African Clawed Frogs. She is interested in understanding how species-typical calls are both produced and received. Furthermore she looks at how individuals affect the behavior of other individuals.

She gives a very exciting and energetic seminar. I highly recommend it.

Sinauer Associates / OUP Distinguished Scientist Lecture
Weds. Sept 12th, 4:00
Integrative Learning Center (ILC) Room N151
650 N Pleasant St, Amherst, 01003

Darcy Kelley

Harold Weintraub Professor
Columbia University

Mechanisms underlying the evolution and expression of vocal communication

Dr. Kelley will talk about the neural mechanisms underlying the production and evolution
of calling songs in various species of the African clawed frog.

This is the first of the fall Neuroscience and Behavior Seminars. For the full list visit: http://gpls.cns.umass.edu/nsb/colloquia.
Read more about the Initiative on Neurosciences.

The Initiative on Neurosciences (IONs) is an effort to bring together all of the different aspects related to brain research on the UMass Amherst campus. Paul Katz was hired by UMass a year ago to be the director of Neurosciences. In May, IONs organized a UMass Interdisciplinary Neurosciences conference that featured faculty from 4 colleges speaking about research in the Neurosciences and two outside speakers, Wolfram Schultz (Cambridge University), a leader in the field of neural mechanisms underlying reward and Graeme Davis (UCSF), a UMass alumnus who is well recognized for his work on synapses. This year, IONs is hosting a bi-weekly Neurosciences Faculty Forum an informal venue for faculty to share research ideas. Oct 29-Nov 2, IONs helping to host the UMass “Week of Memory and Forgetting: Science, Senescence, and Society”. In the spring semester, there will be a Distinguished Neurosciences Lecture Series. For more information see https://websites.umass.edu/ions/.

The launch of this initiative is an exciting development, and the CogSci initiative looks forward to partnering with IONs for future events in cognitive neuroscience.

Lisa Sanders will be presenting in the first first cognitive bag lunch Wednesday Sept. 12, 12:00-1:25 in Tobin 521B. The title of the talk is “A Potential Measure of Phonological Processing During Natural Speech Comprehension”. An abstract follows, and after that, the abstracts for several upcoming talks and the rest of the tentative schedule.

Abstract for Sanders’ talk. There is a long history of using ERPs to index semantic and syntactic processing of speech and text. However, we are lacking a measure of phonological processing that can be used with typical language stimuli. We have discovered a potential new ERP effect – a centrally distributed positivity around 100 ms after onset of the incorrect allomorphs on past tense verbs (e.g., walk/d/ and boo/t/) and plural nouns (e.g., back/z/ and shoe/s/). I’ll discuss our current data and plans for future experiments. We would appreciate your input on both!

9/19 Jennie Mack (UMass ComDis)

Title: The role of linguistic prediction in language impairments and recovery in aphasia

Many people with acquired impairments of language (aphasia) have difficulty using grammatical information to support auditory sentence comprehension. In this talk, I will provide evidence from visual-world eye-tracking that these difficulties stem, at least in part, from impaired linguistic prediction. In addition, I will present results from a language intervention study, which examined how the cognitive and neural bases of sentence comprehension change when language abilities recover in stroke-induced aphasia. Participants received 12 weeks of training aimed at improving their sentence production and comprehension abilities, without explicitly training prediction. Training-related improvements in sentence comprehension were associated with improved linguistic prediction (measured using eye-tracking) as well as increased activation in the right-hemisphere homologues of left-hemisphere language regions (measured using fMRI). These results suggest that linguistic prediction plays a key role in language impairments and recovery, and motivate future directions for basic and translational research.

9/26 Ethan Myers (Hampshire)

Title: Decoding the neural algorithms that underlie behavior

In order to understand how the brain enables complex behaviors, a step-by-step account of how information is transformed from sensory input to motor output is needed. To gain insight into such neural algorithms, I have developed ‘population decoding’ data analysis methods that can be used to accurately track what information is in a brain region and how information is coded in neural activity. In this talk I will describe how, in collaboration with experimental neuroscientists, I have applied this method to spiking activity in macaque monkeys to examine: 1) how information is transformed from sensory signals into more abstract representations that are useful for behavior 2) how such representations are modified by task demands (i.e., attention), 3) how high level brain regions that receive this input (i.e., the prefrontal cortex) only selectively represents task relevant information, and 4) how the flow of information flow can be precisely tracked in a simple pop-out attention task. I will also briefly describe a set of tools that can be used to analyze a range of neural signals in order to gain further insight into the algorithms that brain uses to solve tasks.

10/3 Barb Juhasz (Wesleyan)

Using eye movements to explore how experience with words in childhood impacts word recognition during college.

The age at which a word is first acquired has been found to affect word recognition in adulthood. Words that are rated as having an early age-of-acquisition (AoA) are processed faster than words rated as having a late AoA in many tasks. However, even words that are learned early in life may differ in how frequently they are encountered during childhood. Frequency trajectory refers to the pattern of frequency exposure across schooling and can be measured by comparing word frequency counts for texts that are relevant for early elementary students with frequency counts for college-level texts. Some words are more frequent in early grades compared to college (e.g. rabbit) while others become more frequent in college-level texts (e.g. brain). Other words maintain a consistently high or low word frequency across grades. In this talk, I will discuss current research projects that explore the time course of AoA and frequency trajectory effects on eye movements during reading in college students. These projects have demonstrated that both the age at which a word is initially acquired and its pattern of frequency exposure during schooling impact word recognition.

10/10 Cassandra Jacobs (Rochester)
10/17 Safa Zaki (Williams)
10/24 Sam Ling (BU)
10/31 Agnes Lacreuse (UMass PBS)
11/7 No talk on Wednesday; instead Brian Scholl (Yale) will be giving a joint Developmental/Cognitive Colloquium on Monday 11/5, 12:15-1:15
11/14 NO TALK: Monday Schedule
11/21 NO TALK: Thanksgiving
11/28 Jim Magnuson (UConn)
12/5 Philip Thomas (UMass CS)
12/12 Research Ethics (2nd year cognitive students)

From Joe Pater. Comments enabled

The Cambridge Analytica scandal has hit very close to home. Robert Mercer is a computational linguist, and Aleksandr Kogan is a cognitive psychologist. What should we academics be doing to respond and to prevent future violations of our ethical codes – and what exactly were the violations? I’ll share my current current thoughts in this post, and I would very much welcome others’ contributions on what I think is an important, and complicated, question.

The news yesterday (April 24, 2018) has shed a lot of light on Kogan’s work in collaboration with SCL, CA’s parent company, and how it likely violated the ethical standards of research in cognitive psychology. First, the Guardian released correspondence from the Cambridge University Ethics panel that it obtained with a FOI request. The letter rejects Kogan’s application to conduct research using the data he had acquired from Facebook because he had not obtained informed consent. The two pages of correspondence are well worth reading in whole.

Also yesterday in a news conference, CA’s spokesperson Clarence Mitchell admitted conducting research using those data (in explaining that the data were not useful for targeted advertising, and were therefore not used in the Trump campaign). This distinction between ethical standards for academic and industry research is troubling, though Kogan seems not to be troubled by it, as shown in this quote from his testimony yesterday to a British parliamentary hearing, published in another Guardian article.

Kogan also argued that his firm did not need ethics approval from Cambridge University, still his primary employer, since “there’s no real mechanism for a company to seek ethics approval for a commercial deal.

“I’ve never heard of anybody who runs a company trying to get ethics approval for a dataset whose primary function was really a commercial enterprise. Our primary deliverable here, first and foremost was the obligation in regards to SCL. Secondary purposes come later when you try and bring the work in for the university.”

Kogan admitted that, in transferring the data he had harvested from Facebook, he had acted against the specific words of its developer agreement. But, in a bizarre exchange with Labour’s Paul Farrelly, he argued that he had not broken the policy, because Facebook’s document did not amount to a policy.

“For you to break a policy it has to exist and really be their policy,” Kogan said. “But the reality is that Facebook’s policy is unlikely to be their policy.”

Part of the subtext here is a battle between Facebook and Kogan over who is to blame. My view is both have grievously violated generally held standards of ethical research.

The problematic distinction between academic and industry standards for non-medical human subjects research is also alluded to in the Cambridge University ethic board’s letter, in a discussion of  Kramer et al.’s 2014 PNAS article “Experimental evidence of massive-scale emotional contagion through social networks”. As the subsequent PNAS Editorial Expression of Concern explains, the study had not been reviewed by the authors’ Institutional Review Board at Cornell because it was done under the auspices of Facebook. The “expression of concern” is with the unacceptably weak definition of participant consent used by Facebook. PNAS does not seem to have stated, however, that the publication of the article was in violation of its policy. I have written to the current PNAS Editor-in-Chief for clarification of the policy, and will post any response I get in the comments. (Update April 26: see also the Fiske and Hauser editorial “Protecting human research participants in the age of big data”, which explicitly discusses differences between industry and academic research).

All of this points, I believe, to one thing that we academics can do to respond. We can demand that our journals apply a uniform standard of informed consent for academic and industry-based studies. In medical research, academic and industry standards seem to be basically identical (according to my father, who was the Director of the Clinical Trials Group of the Canadian National Cancer Institute; his e-mail to me on this is at the end of this post). It seems unlikely that we can achieve this standardization in non-medical research through the same mechanism – governmental regulation – but we certainly can at least press our professions’ journals and societies to maintain a uniform standard.

Robert Mercer’s role in Cambridge Analytica is comparatively old news – it came out in yet another Guardian piece, from February 2017. Mercer is the recipient of a lifetime achievement award from the Association for Computational Linguistics, and there have been some calls for this award to be revoked. Particularly relevant to the question I posed at the outset of this post is the way that Adam Goodkind, a Northwestern PhD student, frames his argument for this action in his change.org petition, in terms of violations of his discipline’s ethical codes:

• Robert Mercer’s firm illegally, or at least unethically, acquired personal information, and used this data expressly to influence a foreign election.
• Robert Mercer’s firm deliberately misled the population from which it collected data, exploiting their willingness to share personal information for purely financial and political gain.

https://www.change.org/p/marti-hearst-petition-to-revoke-robert-mercer-s-acl-lifetime-achievement-award

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E-mail of April 23, 2018, from Joseph L. Pater:

In the US, industry clinical trials (which is the main form of industry research on humans) are governed by an FDA regulation (CFR Title 21, Section 312). All clinical research funded by HHS, i.e., NIH, is governed by a federal regulation (45 CFR 46) that is enforced by an office within HHS called OHRP (the Office for Human Research Protections). For HHS funded clinical trials that require regulatory approval (i.e., involving investigational drugs) both regulations apply.

In Canada, there is a similar division. All research funded by the federal granting councils is governed by the Tri-Council Policy Statement (TCPS 2) whereas industry research is governed by something called ICH-GCP (International Council on Harmonization – Good Clinical Practice). Again, academic research that requires regulatory approval is subject to ICH-GCP as well as TCPS.

Most ethics committees that deal with clinical trials set themselves up to be compliant with everything at once.

I haven’t read the rules carefully in a long time, but it’s probably the case that you would be hard pressed to find anything substantially different, in principle at least, among these various requirements, so, in fact, industry and academia are supposed to follow more or less the same rules. My guess is that industry is better at following the letter of the law. For what it’s worth, historical examples of really egregious ethical violations like Tuskegee have come from academia.

Meghan Clayards of McGill University will present “Flexibility and individual differences in speech perception” Friday April 27th in ILC N400 at 3:30. An abstract is below. All are welcome!

Abstract. In order to understand spoken words, listeners integrate information across multiple acoustic dimensions such as spectral frequencies and durations. For each phonological contrast (e.g. bet vs. bat) we must learn which dimensions are relevant and how much to pay attention to each dimension (cue weights). This talk will focus on two aspects of this process. First, flexibility in what we pay attention to in perception and how this is tied to production patterns. Secondly, despite consistent overall patterns for particular contrasts/languages, there seem to be important individual differences in how people perform in speech perception tasks. I will present some data from my lab that is beginning to explore these differences.

Due to scheduling conflicts, the UMass CogSci workshop will be postponed until the fall. Save your conference posters for redisplay then!

Sue Carey, Department of Psychology, Harvard, will present “Do Non-Linguistic Creatures have a Fodorian (Logic-Like/Language-Like) Language of Thought?” Friday, April 20 at 3:30pm in ILC S131.  The talk is sponsored by the Five College Cognitive Science Speaker Series and the UMass Initiative in Cognitive Science. An abstract is below.

Abstract. The adult human conceptual repertoire is a unique phenomenon earth. Human adults build hierarchical representations on the fly, distinguishing “Molecules are made of tiny atoms” (True) from “Atoms are made of tiny molecules” (False). It is unknown whether non-linguistic creatures are capable of representing structured propositions in terms of hierarchical structures formulated over abstract variables, assigning truth values to those propositions, or are capable of abstract relational thought. How abstract knowledge and abstract combinatorial thought is acquired, over both evolutionary and ontogenetic time scales, is one of the outstanding scientific mysteries in the cognitive sciences, and has been debated in the philosophical literature at least since Descartes. Many philosophers, from Descartes through Davidson, have argued that abstract combinatorial thought is absent in creatures who lack natural language; others, such as Fodor, argue that such thought must be widely available to non-linguistic creatures, including human babies and animals at least throughout the vertebrates. A priori arguments will not get us far in settling this issue, which requires both theoretical analysis and empirical work. Theoretically, those who think there is a joint in nature between the kinds of representations that underlie perception and action, on the one hand, and abstract combinatorial thought, on the other, owe us an analysis of the essential differences between the representations and computations involved in each. Empirically, then, we must develop methods that could yield data that bear on the question of whether non-human animals or human infants have representations/computations on the abstract combinatorial thought side of the putative joint in nature. I will illustrate progress on both the theoretical and empirical fronts through two case studies: logical connectives and abstract relations.

A reminder that the fourth annual UMass CogSci Workshop will be held in conjunction with Sue Carey’s visit to the campus on April 20th (https://websites.umass.edu/cogsci/2018/01/30/sue-carey-friday-april-20th-at-330/). The workshop will consist of a poster session from 2:15-3:15; please submit your poster info here: https://goo.gl/forms/mt9v6NYU30zywGNe2. As always, previously presented work is allowed, even encouraged (don’t print a new poster if you can use one you already have!).