Summary

Autism is a highly heritable brain condition affecting 1-2% of people. Sensory processing symptoms are nearly universal in autism [1], despite the fact that the genetic predisposition and environmental contributors of austism are heterogeneous from individual to individual. Where does this convergence of sensory symptoms come from? Previous work by supervisor O’Donnell [2,3] suggests that it may be due to a ‘many-to-one’ mapping from cellular-level properties to the computational functions of sensory brain circuits. In this PhD project the student will address this interesting problem using a combination of statistical analysis of brain activity data recorded in vivo, and deep neural network models of brain circuits.

The project will have three phases:

1.Analyse previously recorded cortical activity data from mouse models of autism provided by collaborator Portera-Cailliau (UC Los Angeles) [4].

2.Design and train deep-learning networks constrained to model mouse cortex, matching the performance and neural activity of wild-type mice and established mouse models of autism on behavioural discrimination tasks (e.g. method from [5]).

3.Study parameter redundancies in the fitted deep neural networks, to propose a unified theory for sensory dysfunction across autism subtypes that can be used to guide treatment design.

The student will be a part of the computational neuroscience research group in Ulster University, joining in local meetings and activities. They will be supported and mentored by the local supervisors at Ulster, other PhD students, and a postdoctoral researcher currently working on related projects funded by the Medical Research Council and the Simons Foundation Autism Research Initiative. The project will involve collaboration with the experimental neuroscience research group of Prof. Carlos Portera-Cailliau at the University of California, Los Angeles.

The student should have an education in computer science, engineering, physics, applied mathematics, or a related field. Previous training in neurobiology is desirable but not required. During the PhD the student will learn skills in data science, deep neural networks, and neurobiology research. They will contribute to our understanding and development of treatments for autism.


Essential criteria

Applicants should hold, or expect to obtain, a First or Upper Second Class Honours Degree in a subject relevant to the proposed area of study.

We may also consider applications from those who hold equivalent qualifications, for example, a Lower Second Class Honours Degree plus a Master’s Degree with Distinction.

In exceptional circumstances, the University may consider a portfolio of evidence from applicants who have appropriate professional experience which is equivalent to the learning outcomes of an Honours degree in lieu of academic qualifications.

  • Experience using research methods or other approaches relevant to the subject domain
  • Research proposal of 1500 words detailing aims, objectives, milestones and methodology of the project
  • A demonstrable interest in the research area associated with the studentship

Desirable Criteria

If the University receives a large number of applicants for the project, the following desirable criteria may be applied to shortlist applicants for interview.

  • First Class Honours (1st) Degree
  • Masters at 70%
  • For VCRS Awards, Masters at 75%
  • Experience using research methods or other approaches relevant to the subject domain
  • Work experience relevant to the proposed project
  • Publications - peer-reviewed
  • Experience of presentation of research findings

Funding and eligibility

The University offers the following levels of support:

Vice Chancellors Research Studentship (VCRS)

Full award (full-time PhD fees + DfE level of maintenance grant + RTSG for 3 years).

This scholarship will cover full-time PhD tuition fees and provide the recipient with £15,840 (tbc) maintenance grant per annum for three years (subject to satisfactory academic performance). This scholarship also comes with £900 per annum for three years as a research training support grant (RTSG) allocation to help support the PhD researcher.

Applicants who already hold a doctoral degree or who have been registered on a programme of research leading to the award of a doctoral degree on a full-time basis for more than one year (or part-time equivalent) are NOT eligible to apply for an award.

Vice-Chancellor’s Research Bursary (VCRB)

Part award (full-time PhD fees + 50% DfE level of maintenance grant + RTSG for 3 years).

This scholarship will cover full-time PhD tuition fees and provide the recipient with £8,000 maintenance grant per annum for three years (subject to satisfactory academic performance). This scholarship also comes with £900 per annum for three years as a research training support grant (RTSG) allocation to help support the PhD researcher.

Applicants who already hold a doctoral degree or who have been registered on a programme of research leading to the award of a doctoral degree on a full-time basis for more than one year (or part-time equivalent) are NOT eligible to apply for an award.

Vice-Chancellor’s Research Fees Bursary (VCRFB)

Fees only award (PhD fees + RTSG for 3 years).

This scholarship will cover full-time PhD tuition fees for three years (subject to satisfactory academic performance). This scholarship also comes with £900 per annum for three years as a research training support grant (RTSG) allocation to help support the PhD researcher.

Applicants who already hold a doctoral degree or who have been registered on a programme of research leading to the award of a doctoral degree on a full-time basis for more than one year (or part-time equivalent) are NOT eligible to apply for an award.

Department for the Economy (DFE)

The scholarship will cover tuition fees at the Home rate and a maintenance allowance of £15,840 (tbc) per annum for three years (subject to satisfactory academic performance). This scholarship also comes with £900 per annum for three years as a research training support grant (RTSG) allocation to help support the PhD researcher.

  • Candidates with pre-settled or settled status under the EU Settlement Scheme, who also satisfy a three year residency requirement in the UK prior to the start of the course for which a Studentship is held MAY receive a Studentship covering fees and maintenance.
  • Republic of Ireland (ROI) nationals who satisfy three years’ residency in the UK prior to the start of the course MAY receive a Studentship covering fees and maintenance (ROI nationals don’t need to have pre-settled or settled status under the EU Settlement Scheme to qualify).
  • Other non-ROI EU applicants are ‘International’ are not eligible for this source of funding.
  • Applicants who already hold a doctoral degree or who have been registered on a programme of research leading to the award of a doctoral degree on a full-time basis for more than one year (or part-time equivalent) are NOT eligible to apply for an award.

Due consideration should be given to financing your studies. Further information on cost of living


Recommended reading

[1] Robertson CE, Baron-Cohen S.
Sensory perception in autism.
Nat Rev Neurosci. 2017 Nov;18(11):671-684. doi: 10.1038/nrn.2017.112

[2] Mizusaki BEP, O'Donnell C.
Neural circuit function redundancy in brain disorders.
Curr Opin Neurobiol. 2021 Aug 17;70:74-80. doi: 10.1016/j.conb.2021.07.008.

[3] O'Donnell C, Gonçalves JT, Portera-Cailliau C, Sejnowski TJ. Beyond excitation/inhibition imbalance in multidimensional models of neural circuit changes in brain disorders.

Elife. 2017 Oct 11;6:e26724. doi: 10.7554/eLife.26724.

[4] Goel A, Cantu DA, Guilfoyle J, Chaudhari GR, Newadkar A, Todisco B, de Alba D, Kourdougli N, Schmitt LM, Pedapati E, Erickson CA, Portera-Cailliau C.
Impaired perceptual learning in a mouse model of Fragile X syndrome is mediated by parvalbumin neuron dysfunction and is reversible.
Nat Neurosci. 2018 Oct;21(10):1404-1411. doi: 10.1038/s41593-018-0231-0.

[5] Perich MG, Arlt C, Soares S, Young ME, Mosher C, Minxha J, Carter E, Rutishauser U, Rudebeck PH, Harvey CD, Rajan K.
Inferring brain-wide interactions using data-constrained recurrent neural network models.

bioRxiv 2020.12.18.423348; doi: https://doi.org/10.1101/2020.12.18.423348


The Doctoral College at Ulster University