forwebsite

Upcoming:

Annual Meeting Canadian Pain Society, Montreal, 2018 

Symposium talk: Using Neuroimaging to Predict Pain and Its Relief: Clinical Utility and Neurothics

Organization of the Human Brain Mapping, Singapore, 2018

Symposium talk: Prediction bias in perceptual experience and decision making

Trainee abstract First author: Marzie Saghayi. Brain connectivity states predict participant engagement in web-based behavioral training

The 8th International Workshop on Pattern Recognition in Neuroimaging, Singapore, 2018

Keynote talk: Predicting treatment outcomes from prior brain connectivity states.

 


March, 2018

fMRI paper comparing different types of meditation accepted. Congrats to our collaborators Gunes Sevinc and Sara Lazar et al

February, 2018

MEG paper on brain development published online in Neuroimage. Congrats to our collaborators Sheraz Khan and Tal Kenet et al

August, 2016

Christos Papadelis from Boston Children’s and Harvard Medical School to speak at BIOTIC on August 3rd, at 11:00 am. Title: Advanced Multimodal Neuroimaging for Studying Prevalent Neurological Pediatric Disorders.

August 2016- December 2017

We secured some money to do research and much more.

Hashmi traversed Tour du Mont Blanc on foot in 15 days.  It was not easy to say the least.

montblanc

Above: Google tracker image. Learn how to track you travels here.

July, 2016

Congratulations Tareq Yousef on receiving the Graduate Student Stipend Award from the Department of Anesthesia, Pain Management and Perioperative Medicine!

Three spectacular candidates have been shortlisted for the Postdoc position and will be giving talks to our group for the final selection.

NetPhysJC resumed last week. We discussed a paper from Tim Behren’s group (Boorman et al., 2016, Neuron). Great discussion on information theory and Bayesian frameworks ensued. Mathematical modelling was discussed. Follow us on twitter @netphys1 #netphysJC

June, 2016

Poster presented at GENEVA OHBM 2016!

Dexmedetomidine disrupts local and global communication in large-scale brain networks
Javeria A Hashmi, Marco Loggia, Sheraz Khan, Rafael Vazquez, Jim Rhee, Emery N Brown, Oluwaseun Akeju

Introduction:
Large-scale networks formed by synchronized fluctuations in functional MRI (fMRI) signals show a distinct architecture when observed from the vantage point of complex network analysis and graph theory [1]. Spatial correlations in fMRI signal can be represented by several clusters of connected brain regions representing ‘local networks’. These clusters are in turn connected to each other to form a ‘global network’ primarily though connections between hubs that have both inter and intra-cluster connections. The configuration of these networks is a putative mechanism to explain information dissemination in the brain.

A more precise understanding of the functional roles of these large-scale brain networks may be obtained by studying how network topology changes during altered states of arousal. General anesthetic and sedative drugs are routinely used in the clinical settings to manipulate arousal states, and provide a scientifically valid and clinically relevant approach to study the functional role of topology in large scale brain networks [2]. In a previous study, we have demonstrated how dexmedetomidine, an alpha-2 adrenergic agonist, alters functional connectivity between the thalamus and the default mode network [3]. However, the effects of dexmedetomidine on global brain networks have not been investigated. Here we tested how dexmedetomidine effects brain network capacity for efficient information transfer within local and global networks. We hypothesized that anesthesia-induced sedation reduces the local and global efficiency of large-scale brain networks.

Methods:
Using resting state functional MRI, we imaged the brain of 14 healthy subjects during baseline (awake), dexmedetomidine-induced sedation, and recovery from the dexmedetomidine-induced states [4]. Using a whole-brain network approach, networks were constructed at 6 different network density thresholds from a 131-ROI parcellation [5]. We used the Brain Connectivity Toolbox and custom codes written in MATLAB [6]. Graph metrics were compared with paired t-tests and results were corrected for multiple comparison using FDR (p<0.05).

Results:
Our investigations showed that neural communication mediated by synchronizations in slow rsfMRI signals were disrupted during dexmedetomidine-induced sedation. In particular, we found significantly reduced capacity for efficient information transfer within the brain at both a local and a global level in weighted networks during the sedated state. The topological changes were associated with reduced strength of connections (nodal strength) at a global mean level during the sedated state (p<0.05 for all network density thresholds). Importantly, we did not find significant changes in number of connections at a nodal level (degree distribution). As previously reported with sedatives and anesthetics, we also observed reduced connectivity in thalamic [3], attention networks [7] and default-mode networks, however, our global network approach also showed reduced functional connectivity within and between all resting state networks. The most robust change was observed for subcortical connections with multimodal networks, and for sensory connections with language/memory processing networks.

Conclusions:
Our findings are the first to demonstrate that sedation induced with dexmedetomidine significantly disrupts the capacity for efficient information transfer at a local and a global scale. By using a global network approach, we have found that the effects of dexmedetomidine are not specific to a particular network; instead, connectivity was reduced both within and between several resting state networks.

March, 2016

DAL PAIN NETWORK MEETING 2016

As part of Dal Pain Day, the NetPhys Lab presented a poster and attended talks by Dr. Irene Tracey from Oxford University. We had a lovely and informative day from 7am Grand Rounds to an informal dinner at the end of the night. 

#dalpain16

                               Taking a look at some research at the poster presentation session during Dal Pain Day.

Image 2016-05-24 at 9.26 AM

 

brainApplications are invited for two PhD students to join the Brain Networks and Neurophysiology (NetPhys) Lab in Dalhousie University. The degree is multidisciplinary with options of admission through different graduate departments (Physics, Computer Science, Medical Neuroscience, Psychology and Neuroscience).

The NetPhys Lab is dedicated to understanding the behavioral relevance of neural communication in large-scale brain networks. We use pain as our modality for understanding how the brain processes internal and external information to generate perception. We also observe how ongoing mental processes alter pain perception. Our overall goal is to establish the scope and limits as to which we will be able to use brain imaging for predicting complex behavior such as pain. Our core focus is on predictive analytics geared at using multimodal brain imaging data to develop tools that can predict treatment outcomes, especially in chronic pain patients in all ages and across the lifespan. Other projects will study brain networks in altered states of consciousness—such as general anesthesia or mindful-awareness meditation—in multimodal data.

The planned studies will use leading-edge-imaging methods to analyze multimodal data (MEG, EEG, fMRI, DTI and EEG) combined with quantitative data analysis with a special focus on intrinsic and dynamic brain networks. We will use opensource resting and task related data to build new knowledge on brain function. This is thus a unique opportunity to contribute to the scientific models of the brain and to build transferable skills such as use of multimodal brain imaging, machine learning, dynamic connectivity and graph theory based network analysis in predictive analytics.

The student will learn how to use high dimensional data and cognitive neuroscience to develop neuropsychiatric biomarkers.

Applicants should submit a cover letter stating their research interests and current CV (including a list of scholarly publications), along with the names and contact information for three referees to Javeria.Hashmi@dal.ca asap.

The NetPhys lab is based in the Department of Anesthesia, Pain Management and Perioperative Medicine at Dalhousie University. Brain imaging projects will be conducted in collaboration with the leading neuroimaging facility in the Canadian Atlantic region (http://www.bioticimaging.com/) and The Big Data Institute https://bigdata.cs.dal.ca/ and with several other departments. You will work in collaboration with neuroscientists, computer scientists and clinical research experts.

Halifax is a port city, rich with culture and history, and is encircled in extraordinary coastal line and landscapes. The city has a bustling academic environment with six major universities located in the city municipality. It offers opportunities to think creatively, learn in a nurturing environment and to explore pristine nature.

We encourage students from all backgrounds including international students, women and minorities to apply.

Follow us @netphys1 and see #NetPhysJC on twitter

brain3We would like to invite applications for a research assistant position in brain imaging and cognition at the Brain Networks and Neurophysiology lab in Dalhousie University, Department of Anesthesia, Pain Management and Perioperative Medicine. The primary goal of the project is to develop predictors of treatment outcomes in chronic pain patients with brain imaging.

This position is ideal for students aiming at a career in biomedical research. Candidates who are planning to apply to graduate or medical school will have the opportunity to spend 1-2 years performing full-time research and working side-by-side with leading scientists in the fields of neuroimaging, clinical, and preclinical research.

EDUCATION/WORK EXPERIENCE: A undergraduate degree in Statistics, Biostatistics, Neuroscience, psychology, Mathematics, Physics, Computer Science, Engineering, or related field is preferred. Excellent writing skills for grant proposals and scientific papers is a necessary requirements. Familiarity with neuroimaging acquisition methods and systems such as MRI, MEG and EEG. A back ground in neuroscience and brain imaging is an asset. Also desired is experience in human research studies involving clinical screening, patient recruitment, REB, data base and research documentation. Also required is interest in neuroscience and neuroimaging and translational biomedical research.

The successful candidate will be well organized, will demonstrate a thorough and conscientious approach to performing her/his duties, and will be able to handle multiple tasks simultaneously.

Interested applicants should send a cover letter, a CV, and the names and contact information of three professional references, including at least one supervisor, to:

Javeria.hashmi@dal.ca

brain_em

Applications are invited for a fully funded position at the rank of postdoctoral student to join the Brain Networks and Neurophysiology (NetPhys) Lab. Salary will be commensurate with experience.  This is a full-time position with salary and benefits available for a period of three years. Starting date is September 2016 (negotiable).

In addition to a doctoral degree, the student needs to have demonstrated proficiency in writing code and should have strong analytical skills in processing brain imaging data (in fMRI or in MEG/EEG). The student will be trained in 1. How to use and combine information from different brain imaging modalities (fMRI, MEG/EEG) with the most current methods, 2. Gain expertise in cognitive neuroscience and clinical pain research. Through this training the student will learn how to use brain data and cognitive neuroscience to develop neuropsychiatric biomarkers.

The NetPhys Lab is dedicated to understanding the behavioral relevance of neural communication in large-scale brain networks. We use pain as our modality for understanding how the brain processes internal and external information to generate perception. We also observe how ongoing mental processes alter pain perception. Our overall goal is to establish the scope and limits as to which we will be able to use brain imaging for predicting complex behavior such as pain. Our core focus is on predictive analytics geared at using multimodal brain imaging data to develop tools that can predict treatment outcomes, especially in chronic pain patients in all ages and across the lifespan. Other projects will study brain networks in altered states of consciousness—such as general anesthesia or mindful-awareness meditation—in multimodal data.

The planned studies will use leading-edge-imaging methods to analyze multimodal data (MEG, EEG, fMRI, DTI and EEG) combined with quantitative data analysis with a special focus on intrinsic and dynamic brain networks. This is thus a unique opportunity to contribute towards new models of brain function and to build transferable skills such as use of multimodal brain imaging, machine learning, dynamic connectivity and graph theory based network analysis in predictive analytics.

Statistical, computational and signal processing skills are required for this research. We are especially interested in devotion to advanced quantitative data analysis including the ability to write code and/or to modify existing analysis code. The ideal applicant will have direct experience using MATLAB/Bash for analyzing brain data. Expertise in analyzing HCP or other open source data is a plus. Experience with source based MEG/EEG or the ability and motivation to combine M/EEG sources with fMRI will be an advantage. Expertise in computational modelling is a big plus.

The NetPhys lab is based in the Department of Anesthesia, Pain Management and Perioperative Medicine at Dalhousie University. Brain imaging projects will be conducted in collaboration with the vibrant brain imaging research environment, in a leading neuroimaging facility (http://www.bioticimaging.com/). You will work in a supportive environment consisting of neuroscientists, computer scientists and clinical research experts.

Halifax is a port city, rich with culture and history, and is encircled in extraordinary coastal line and landscapes. The city has a bustling academic environment with six major universities located in the city municipality. It offers opportunities to think creatively, learn in a nurturing environment, explore nature, and focus on self-growth.

Applicants should submit a cover letter and current CV (including a list of scholarly publications), along with the names and contact information for three referees to Javeria.Hashmi@dal.ca by August 1st, 2016.