Jie Mei

Jie Mei
The University of Western Ontario | UWO · The Brain and Mind Institute

Doctor of Philosophy

About

27
Publications
7,211
Reads
How we measure 'reads'
A 'read' is counted each time someone views a publication summary (such as the title, abstract, and list of authors), clicks on a figure, or views or downloads the full-text. Learn more
127
Citations
Additional affiliations
September 2021 - September 2021
The University of Western Ontario
Position
  • PostDoc Position
Description
  • Neuromodulation-aware models for artificial intelligence and learning
September 2019 - September 2021
Université du Québec à Trois-Rivières
Position
  • PostDoc Position
April 2016 - April 2019
Charité Universitätsmedizin Berlin
Position
  • PhD Student
Education
April 2016 - April 2019
Charité Universitätsmedizin Berlin
Field of study
  • Medical Neuroscience
September 2013 - June 2015
Ecole Normale Supérieure de Paris - CogMaster
Field of study
  • Cognitive Neuroscience

Publications

Publications (27)
Article
Our brains have evolved the ability to configure and adapt their processing states to match the unique challenges of acting and learning in diverse environments and behavioral contexts. In biological nervous systems, such state specification and adaptation arise in part from neuromodulators, including acetylcholine, noradrenaline, serotonin, and do...
Article
Olfactory and gustatory dysfunctions (OD, GD) are prevalent symptoms following COVID-19 and persist in 6%–44% of individuals post-infection. As only few reports have described their prognosis after 6 months, our main objective was to assess the prevalence of OD and GD 11-month post-COVID-19. We also aimed to determine intraclass correlation coeffic...
Preprint
Full-text available
Background and Objectives: Olfactory and gustatory dysfunctions (OD, GD) are prevalent symptoms following COVID-19 and persist in 6%-44% of individuals in the first months after the infection. As only few reports have described their prognosis more than 6 months later, the main objective of this study was to assess the prevalence of OD and GD 11 mo...
Preprint
Full-text available
Background Idiopathic rapid eye movement sleep behavior disorder (iRBD) is a major risk factor for synucleinopathies, and patients often present with clinical signs and morphological brain changes. However, there is an important heterogeneity in the presentation and progression of these alterations, and the brain regions that are more vulnerable to...
Article
Full-text available
Several studies have revealed either self-reported chemosensory alterations in large groups or objective quantified chemosensory impairments in smaller populations of patients diagnosed with COVID-19. However, due to the great variability in published results regarding COVID-19-induced chemosensory impairments and their follow-up, prognosis for che...
Preprint
Full-text available
Several studies have revealed either self-reported chemosensory alterations in large groups or objective quantified chemosensory impairments in smaller populations of patients diagnosed with COVID-19. However, due to the great variability in published results regarding COVID-19-induced chemosensory impairments and their follow-up, prognosis for che...
Article
Full-text available
Diagnosis of Parkinson's disease (PD) is commonly based on medical observations and assessment of clinical signs, including the characterization of a variety of motor symptoms. However, traditional diagnostic approaches may suffer from subjectivity as they rely on the evaluation of movements that are sometimes subtle to human eyes and therefore dif...
Article
Full-text available
Humans and some animal species are able to learn stimulus-response (S-R) associations by observing others' behavior. It saves energy and time and avoids the danger of trying the wrong actions. Observational learning (OL) depends on the capability of mapping the actions of others into our own behaviors, processing outcomes, and combining this knowle...
Preprint
Full-text available
Deep neural networks (DNNs) can learn accurately from large quantities of labeled input data, but DNNs sometimes fail to generalize to test data sampled from different input distributions. Unsupervised Deep Domain Adaptation (DDA) proves useful when no input labels are available, and distribution shifts are observed in the target domain (TD). Exper...
Preprint
Despite a long history of research favors left lateralization of language, increasingevidence provides support to the claim that the right hemisphere also plays a role inlanguage. Although studies have indicated that the right hemisphere contributes tolanguage representation, the underlying neural mechanisms are partly investigated andremain elusiv...
Preprint
Full-text available
Diagnosis of Parkinson's disease (PD) is commonly based on medical observations and assessment of clinical signs, including the characterization of a variety of motor symptoms. However, traditional diagnostic approaches may suffer from subjectivity as they rely on the evaluation of movements that are sometimes subtle to human eyes and therefore dif...
Article
Full-text available
Background The olfactory bulb is one of the first regions of insult in Parkinson’s disease (PD), consistent with the early onset of olfactory dysfunction. Investigations of the olfactory bulb may, therefore, help early pre-motor diagnosis. We aimed to investigate olfactory bulb and its surrounding regions in PD-related olfactory dysfunction when sp...
Preprint
Full-text available
FreeSurfer is among the most widely used suites of software for the study of cortical and subcortical brain anatomy. However, analysis using FreeSurfer can be time-consuming and it lacks support for the graphics processing units (GPUs) after the core development team stopped maintaining GPU-accelerated versions due to significant programming cost....
Article
Full-text available
This paper presents the design of an ultra-low energy neural network that uses time-mode signal processing). Handwritten digit classification using a single-layer artificial neural network (ANN) with a Softmin-based activation function is described as an implementation example. To realize time-mode operation, the presented design makes use of monos...
Article
The radial arm maze (RAM) is a common behavioral test to assess spatial working and reference memory in mice. However, conventional RAM experiments require a substantial degree of manual handling and animals are usually subjected to prolonged periods of food or water deprivation to achieve sufficient learning motivation resulting in stress-induced...
Article
Full-text available
Ideally, humane endpoints allow for early termination of experiments by minimizing an animal's discomfort, distress and pain, while ensuring that scientific objectives are reached. Yet, lack of commonly agreed methodology and heterogeneity of cut-off values published in the literature remain a challenge to the accurate determination and application...
Conference Paper
Contrary to the traditional view that the thalamus acts as a passive relay station of sensory information to the cortex, a number of experimental studies have demonstrated the effects of peri-geniculate and cortico-thalamic projections on the transmission of visual input. In the present study, we implemented a mechanistic model to facilitate the un...
Article
Full-text available
Body temperature is a valuable parameter in determining the wellbeing of laboratory animals. However, using body temperature to refine humane endpoints during acute illness generally lacks comprehensiveness and exposes to inter-observer bias. Here we compared two methods to assess body temperature in mice, namely implanted radio frequency identific...
Preprint
Full-text available
Technology is increasingly shaping our social structures and is becoming a driving force in altering human biology. Besides, human activities already proved to have a significant impact on the Earth system which in turn generates complex feedback loops between social and ecological systems. Furthermore, since our species evolved relatively fast fro...
Article
Full-text available
Technology is increasingly shaping our social structures and is becoming a driving force in altering human biology. Besides, human activities already proved to have a significant impact on the Earth system which in turn generates complex feedback loops between social and ecological systems. Furthermore, since our species evolved relatively fast fro...
Poster
With machine learning methods, we found that both core and surface temperature measurements were adequately suited for the prediction of death. An automatized parameter search method with finer increments in the predictor allowed us to achieve high prediction accuracy for a body-temperature-based humane endpoint, thus reducing unnecessary suffering...
Article
Full-text available
The present study investigates a Brain-Computer Interface (BCI) spelling procedure based on the P300 evoked potential. It uses a small matrix of words arranged in a tree-shaped organization ("multimenu"), and allows the user to build phrases one word at a time, instead of letter by letter. Experiments were performed in two sessions on a group of se...

Questions

Question (1)
Question
Hello everyone,
I'm new to FreeSurfer and this question might sound a bit stupid: I'm trying to get the volumetric measures, surface area and cortical thickness of brain regions of three groups of subjects (patient group 1, group 2 and healthy controls), and I was wondering whether the morphometric variance across subjects (gender, shape of brain, etc) unrelated to the neurological condition has been corrected automatically within the recon-all pipeline using the default options.
That is, given that the groups are age-, gender- and otherwise matched, after segmentation and calculation of these values with FreeSurfer, the morphometric differences we are looking at could be attributed to the neurological condition itself, instead of other factors.
From what I read, the step Talaraich which computes the affine transform from the orig volume to the MNI305 atlas (https://surfer.nmr.mgh.harvard.edu/fswiki/recon-all#Talairach.28-.3Cno.3Etalairach.29) seems to be one of the steps that does what I need, and we are therefore safe using the default recon-all for pre-processing and extraction of morphometric data. Otherwise, please let me know what I could do.
Thanks very much for your information and help in advance!

Network

Cited By