Talk: Neuroimaging Markers of Cognitive Reserve and Brain Aging

Lihong Wang PhD
UCONN Health, Dept of Psychiatry
Wednesday September 5, 2018 1:30-2:30pm in Arjona 307

Abstract

Our brain can reorganize its function and neural resources to counteract neural damages. The ability of reorganization of brain function depends on cognitive reserve capacity. To examine dynamic changes of cognitive reserve over time, we developed a new measure for evaluating neural compensatory capacity, a core factor of cognitive reserve, using independent component analysis and a cognitively very challenging task in older adults. Interestingly, we find higher neural compensatory capacity to be related to working memory function. In another study, we show a one-month physical exercise training to improve working memory as well as neural compensatory capacity through activating addition neural networks, i.e., the cerebellar and motor cortex. We believe the new measure on neural compensatory capacity can be applied to broad lines of research on neuroplasticity. Other imaging markers related to brain aging and cognitive decline will also be discussed.

Speaker

Dr. Wang obtained her Ph.D. degree in neurology from Japan and has six years of experience as a neurologist in China. She has performed neuroimaging-related research in depression at Duke University for over 12 years, primarily focused on geriatric depression and cognitive neuroscience. Her recent research centers on neural signatures of depression vulnerability and neural plasticity in patients with late-life depression and mild cognitive decline.

Vistors from UCHC are encourage to use the UCHC-Storrs shuttle service. Talks can also be joined remotely. Please contact us if you are interested in meeting with the speaker.

Download and post a flyer in your area.

Introducing the new Scientific Director (August 2018)

The BIRC is delighted to welcome our new Scientific Director: Dr. Fumiko Hoeft, M.D./ Ph.D. She is a cognitive neuroscientist, with theoretical interests in the neurobiological mechanisms underlying individual differences in brain maturational processes and the acquisition of skills such as reading (and dyslexia). She will be leading the BIRC, and joining the Department of Psychological Sciences. She brings an impressive track record of externally-funded research and development, and a dynamic vision for the future of BIRC.  Welcome, Dr. Hoeft!

Talk: Stephen Wilson 4/4 3:30

Stephen Wilson, PhD
Vanderbilt

Wednesday, April 4, 2018
3:30-5:00pm
BOUS A106

Imaging the language network: functional neuroanatomy, acquired aphasia, and recovery

What is the functional architecture of the language network? How is it impacted by damage to its various nodes and connections? And when it is damaged, how can it reorganize to support recovery of language function? To address these questions, we have carried out a series of multimodal neuroimaging studies in individuals with acquired language deficits of diverse etiologies–stroke, neurodegenerative disease, and resective surgery–as well as neurologically normal volunteers. Our findings, along with those of others, reveal a complex, variegated language network in which numerous distinct regions and tracts in the temporal, frontal and parietal lobes play distinct functional roles. Yet the network is strikingly resilient to most patterns of damage, indicating that in many cases, functional specialization is graded rather than absolute. Our findings suggest that recovery from aphasia depends primarily on reconfiguration of spared language regions, rather than macroscopic reorganization of the whole system.

Talk: Evelina Fedorenko 3/28 3:30pm

Evelina Fedorenko, PhD
Assistant Professor
Harvard Medical School and Massachusetts General Hospital

Wednesday March 28, 2018
3:30-5:00pm, BOUS A106

The cognitive and neural architecture of the human language system

Brain regions that support high-level language processing are strikingly selective. This selectivity rules out a few prominent hypotheses — e.g., that left frontal lobe structures support language via domain-general executive processes, or that language relies on an abstract syntactic processing mechanism shared by other domains — but leaves open the nature of the exact computations that the language system supports. I will discuss three lines of work that, in tandem, suggest that the language network is fundamentally concerned with meaning, including both the processing of individual word meanings and semantic composition.
First, both lexical and combinatorial processing elicit robust responses throughout the fronto-temporal language network (e.g., Fedorenko et al., 2010; Blank et al., 2016). Further, some language regions show stronger responses to lexico-semantic processing and represent lexico-semantic information more robustly than structural information (Fedorenko et al., 2012), but no regions show the opposite pattern. In recent work (Mollica et al., in prep.), we further found that stimuli that are not well-formed but interpretable elicit as strong a response as intact sentences, in line with current sentence comprehension models whereby our interpretation mechanisms are robust to signal corruption (e.g., Levy et al., 2009; Gibson et al., 2013).
Second, intracranial recordings from the surface of the human brain show that neural activity, indexed by gamma power, increases monotonically over the course of a sentence across the language system (Fedorenko et al., 2016). Having ruled out a number of alternative explanations of this effect in terms of generic attention, working memory, and cognitive load, we argue that the most likely explanation is that this response increase reflects the increasing complexity of the evolving representation of the sentence meaning and is thus a candidate neural marker of complex meaning construction.
And third, we have recently developed a new approach for decoding linguistic meanings from the brain (Pereira et al., in press), based on a procedure for broadly sampling a semantic space constructed from massive text corpora. After the system was trained on imaging data of individual concepts, it could decode sentences from a wide variety of topics. These decoded representations were sufficiently detailed to distinguish even semantically similar sentences. Thus, we established the viability of using distributed semantic representations to probe meaning representations in the brain, laying a foundation for future development and evaluation of precise hypotheses about how concepts are represented and combined.
We encourage members of our MRI community, including students, to schedule a meeting; please email Inge-marie.eigsti@uconn.edu with your availability.

Seed Grant Applications and Reports Due March 1

The next deadline for Seed Grant proposals is March 1, 2018.

The Seed Grant Program is intended for both experienced MRI users seeking pilot data and researchers with little or no MRI experience seeking to establish a track record of MRI research.

See the Seed Grants page for more information about the Seed Grant Program or to submit an application.

Current recipients of a seed grant should also submit a progress report by March 1.

 

Neuroimaging software containers

The initial release of the BIRC User Container for Research (BURC) is now available, providing a pre-configured, reproducible environment for a variety of neuroimaging analyses. Containers have several use cases:

  • Preserving the software environment used for an analysis, so that the analysis can be reproduced later
  • Running software on a high performance computing (HPC) or other system where you may not have the privileges necessary to configure software
  • Rapidly setting up a software environment on a new computer

The BURC provides a large (40GB+) smorgasbord of useful packages in an Ubuntu Linux environment that can be run on your own computer using Docker or on a HPC system with Singularity. More information and documentation is available on GitHub. Additional support is available via the BIRC_HELP-L listserv. To subscribe, send an email to listserv@listserv.uconn.edu with the body:

SUB BIRC_HELP-L Firstname Lastname

The BURC is available as:

  • A prebuilt Singularity container at /scratch/birc_ro/containers/burc.img on the Storrs HPC system
  • A prebuilt Singularity container for download (internal link)
  • An exported Docker image for download (internal link)
  • A Docker build file on GitHub.
  • As a Docker image on the iMacs in the data processing room at BIRC

Installed software includes:

DICOM converters

  • dcm2niix
  • dicm2nii (requires Matlab)
  • pydicom, nibabel, dcmstack, bidskit, heudiconv

Neuroimaging Analysis

  • AFNI
  • FSL with patched eddy_cuda
  • Freesurfer 6.0
  • ANTs
  • DTIPrep

Spectroscopy

  • Tarquin
  • Gannet 3.0 master (requires Matlab)
  • VESPA (in the vespa conda-2.7 environment)

M/EEG

  • Fieldtrip (requires Matlab)

Neuroimaging Pipelines

  • fmriprep
  • mriqc
  • C-PAC
  • nipype

Statistics

  • R
  • pystan and Rstan
  • MCMCglmm

Python

There are several versions of python installed:

  • A system python 2.7 at /usr/bin/python
  • Anaconda python 2.7 (/usr/bin/env python)
  • A python 3.6 Anaconda environment (python3)

Python environments

There are several Anaconda-based environments. Switch between them using source activate name

  • python3 Python 3.6 with nibabel, nipype and pystan
  • cpac (Python 2.7)
  • poldrack (Python 3.6) with fmriprep and mriqc
  • vespa (Python 2.7) with vespa

 

NEW POSITION ADVERTISED: Scientific Director, BIRC

The University of Connecticut invites applications for a full-time, tenure track/tenured faculty position and Scientific Director of the Brain Imaging Research Center (BIRC). The salary and academic rank will be commensurate with qualifications and experience. Responsibilities will include intellectual leadership and financial management of the Brain Imaging Research Center and active participation in cognitive neuroscience research. The candidate’s academic appointment will be in Psychological Sciences, Speech, Hearing, and Language Sciences, or Education, and will include teaching at the undergraduate and graduate levels. The Scientific Director should be able to demonstrate leadership and collaboration across disciplines, and have a track record of grant-funded research. The Director should be able to articulate a vision statement and a strategic plan for the BIRC to be an intellectual hub, and will be instrumental in building an interdisciplinary MRI research program. Specifically, the Director will be responsible for the continued development of a nationally prominent collaborative research effort by: 1) promoting funded research in human neuroscience and related fields; 2) the administration of imaging services to the UConn cognitive neuroscience community; 3) broadening the base of BIRC users by mentoring new users, organizing classes, workshops, and symposia on imaging methodology and advanced techniques, establishing partnerships with local and regional organizations, and ensuring that scientists have access to the technical and scientific expertise needed to advance their research; 4); recruiting outstanding investigators and 5) working with the UConn Foundation.

 

University of Connecticut has dynamic, highly-regarded research programs in cognition and cognitive neuroscience, language, speech, and reading, developmental psychopathology, health psychology, kinesiology, genetics/genome sciences, and others, including the Institutes for the Brain and Cognitive Sciences (IBaCS) and for Collaboration on Health, Intervention, and Policy (InCHIP). UConn’s ambitious program of growth in cognitive neuroscience is housed at a 3,200 square foot, research-dedicated neuroimaging center with a Siemens Prisma 3-Tesla scanner, with facilities for simultaneous and standalone EEG, TMS and tDCS.

 

Minimum Qualifications: A Ph.D., M.D., or both, with specialization in cognitive science, neuroscience, psychology, psychiatry, biomedical engineering, or related fields. Significant fMRI experience, with a strong track record of funded research and impactful publications, and expertise in techniques relevant to human neuroimaging. Possesses flexibility and expertise to (1) support research across a variety of content areas and (2) coordinate staff to keep BIRC at the cutting edge of neuroimaging. Previous laboratory management experience. Evidence of effective graduate and undergraduate teaching. Excellent communication skills.

 

Preferred Qualifications: Evidence of effective graduate or undergraduate teaching of MRI methods. Published research using diffusion imaging, volumetry, susceptibility-weighted imaging, MR spectroscopy, MR relaxometry, cardiovascular and musculoskeletal imaging, EEG, TMS, tDCS, or multi-modal imaging techniques.

 

To Apply: Interested applicants must apply electronically (hr.uconn.edu/jobs/) by submitting the following documents as a single PDF file: cover lettercurriculum vitaeteaching statement (teaching philosophy, teaching experience, commitment to effective learning, concepts for new course development, etc.); research and scholarship statement (innovative concepts that will form the basis of academic career, experience in proposal development, mentorship of graduate students, etc.); commitment to diversity statement (broadening participation, integrating multicultural experiences in instruction and research, etc.); and names of three references. For additional information, contact: Inge-Marie Eigsti, Chair of Search # 2018194; Psychological Sciences, U-1020, University of Connecticut; 406 Babbidge Road; Storrs, CT 06269-1020; inge-marie.eigsti@uconn.edu. Evaluation of applicants will begin November 15. For more information regarding the BIRC, please visit our website at www.birc.uconn.edu.

 

At the University of Connecticut, our commitment to excellence is complemented by our commitment to building a culturally diverse community. As an Affirmative Action/Equal Employment Opportunity employer, UConn encourages applications from women, veterans, people with disabilities and members of traditionally underrepresented populations.

New England Research on Dyslexia Society Meeting October 21

The 3rd meeting of the New England Research on Dyslexia Society will be held in Storrs, CT on October 21, 2017. The meeting will take place on the University of Connecticut campus in Oak Hall.

KEYNOTE SPEAKER: John Gabrieli, Ph.D, Professor of Brain and Cognitive Sciences, MIT

“Dyslexia: From Neurophysiology to Intervention”

The New England Research Group on Dyslexia is an interdisciplinary community of researchers, educators, clinicians, and policy experts, whose work aims at elucidating the biological, including psychological, and social underpinnings of Developmental Dyslexia and related disorders with the objective of improving prevention, early detection, diagnosis, treatment/intervention and social support (including legal, political, and public health) associated with this learning disability.

For more information and to register, visit: http://ibacs.uconn.edu/nerdy/

 

BOLD Brownbag Series

BIRC is pleased to present a series of informal BOLD Brownbag talks, held on Wednesdays from 9-10 AM in Bous 162. If you are not currently on the MRI distribution list, but would like to hear updates about these talks, please join the list serve. This venue is an informal one, geared toward discussion of work in progress (especially methodological/analytical) rather than formal polished presentations of finished products (though we’ll have some of those as well!).

You can find the current schedule here.