Developing and delivering neurocomputational models to bridge between brain and mind.

Project Information

BRAIN2MIND_NEUROCOMP

Grant agreement ID: 670428

DOI

10.3030/670428

Project closed

EC signature date 30 July 2015

Start date 1 January 2016

End date 31 December 2021

Funded under

• EXCELLENT SCIENCE - European Research Council (ERC)

Total cost

€ 2 294 781,00

EU contribution

€ 2 294 781,00

Coordinated by

THE CHANCELLOR MASTERS AND SCHOLARS OF THE UNIVERSITY OF CAMBRIDGE
United Kingdom

Periodic Reporting for period 4 - BRAIN2MIND_NEUROCOMP (Developing and delivering neurocomputational models to bridge between brain and mind.)

Reporting period: 2020-03-01 to 2021-12-31

Summary of the context and overall objectives of the project

What is the problem/issue being addressed?
The promise of cognitive neuroscience is truly exciting – to link mind and brain in order to reveal the neural basis of higher cognitive functions. This is crucial, scientifically, if we are to understand the nature of mental processes and how they arise from neural machinery but also, clinically, if we are to establish the basis of neurological patients’ impairments, their clinical management and treatment.

Why is it important for society?
The multi-disciplinary work focused on the neural basis of language and its disorders (aphasia and acquired dyslexia). The topic focus of language is socially and strategically important given that language impairments are a common, disabling feature in many types of dementia (including Alzheimer’s disease and the progressive aphasias) and following stroke (1/3 patients acutely and 1/5 in the chronic phase).

What are the overall objectives
This ERC Advanced grant contained three work packages:

Work Package 1 – Neurocomputational modelling: building computational models of language functions; linking these to cognitive neuroscience data; linking them to neuropsychological patient data.

Work Package 2 – Understanding how language functions arise from the underlying neural machinery.

Work Package 3 – how damage and recovery in neural systems give rise to acquired language impairments (aphasia) after brain damage.

Work performed from the beginning of the project to the end of the period covered by the report and main results achieved so far

Excellent progress and outcomes were made in all three workpackages.

Work Package 1– Neurocomputational modelling:
Our original neurocognitive models of semantics and language did not consider alternative computational architectures. We completed three sets of simulations to explore (i) the impact of the depth on a model of semantics (how many hidden layers); (ii) the interaction with different densities of representation; and (iii) comparison of models with different architectures but balanced computational resources. This major piece of computational research has now been published in a high profile journal (Jackson, Rogers & Lambon Ralph, Nature Human Behaviour, 2021: doi: 10.1038/s41562-020-01034-z).

Secondly, we have generated a bilateral model of language and recovery. Specifically, we have generated the first-ever computational model of a bilateral ‘dorsal’ language pathway model. The model generates behavioural responses and can also a proxy for fMRI BOLD imaging and analyses. Like real patients, the model shows chronic aphasia after left hemisphere but not right hemisphere damage. This substantial computational exploration is now published in a prominent international journal (Chang & Lambon Ralph, PNAS, 2020: https://doi.org/10.1073/pnas.2010193117)

1.2.2 Work package 2 – understanding how language functions arise from the underlying neural machinery:
Our initial study was a proof of concept study in which different parts of the anterior temporal lobe are removed from the brain images of healthy participants in order to check the resultant pattern of disconnections. This work was summarised in an international publication (Busby, ... & Lambon Ralph, 2019, Cortex: https://doi.org/10.1016/j.cortex.2018.11.003).

We have completed the work on exploring the relationship between structural (white matter) vs. functional connectivity and relating these to cognitive functions. This has turned to a major, in depth examination of the connectivity between the key regions that support spoken and written language. Utilising the HCP DWI open access database we have completed a key piece of technical work focused on to systematically threshold white-matter tractography results (this paper is under revision at Human Brain Mapping; Chang, Halai & Lambon Ralph (under revision); BioRxiv Reprint https://doi.org/10.1101/2022.07.27.501671). Superimposed on this methods work, we have completed a multimodal imaging exploration of the white matter, resting-state fMRI and task fMRI (reading) connectivity across this full language connectome.

We also had the objective to explore individual differences and the impact this has on the resultant effect of TMS. (Hoffman, Lambon Ralph, & Woollams, 2015, PNAS: doi: 10.1073/pnas.1502032112; Woollams, Madrid, & Lambon Ralph, 2017, PNAS: doi: 10.1073/pnas.1707162114).


1.2.3 Work package 3 – how damage and recovery in neural systems give rise to acquired language impairments (aphasia) after brain damage:
A major target was to build up the number of patients in our chronic post-stroke aphasia database and to increase the density of the behavioural data. The database was increased from 31 cases to 100, and we have added a whole new set of behavioural data This database has supported multiple PhD theses as well as a large number of published papers in international neurology, neuroscience and aphasiological journals. These include highly-cited papers on new insights about transdiagnostic graded variations across aphasia (Halai, Woollams, & Lambon Ralph, 2017, Cortex: doi: 10.1016/j.cortex.2016.04.016) lesion-to-aphasia prediction models (e.g. Halai, Woollams & Lambon Ralph, 2020, Nature Human Behaviour; DOI: 10.1038/s41562-020-0854-5) the status of verb and connected speech production in aphasia (e.g. Alyahya, Halai, Conroy, & Lambon Ralph, 2018, NeuroImage Clinical; https://doi.org/10.1016/j.nicl.2018.01.023 & Alyahya, Halai, Conroy, & Lambon Ralph, 2020, Brain; https://doi.org/10.1093/brain/awaa074) and an evolving appreciation of comorbid attention and executive deficits in post-stroke aphasia (e.g. Schumacher, Halai, & Lambon Ralph, 2019, Brain; https://doi.org/10.1093/brain/awz258).

Progress beyond the state of the art and expected potential impact (including the socio-economic impact and the wider societal implications of the project so far)

As well as tackling all stated targets in the ERC funded project, we have also taken the chance to go beyond these when exciting opportunities have arisen.

Further basic cognitive neuroscience:
(A) We explored the historical accounts of human white matter neuroanatomy. This includes the seminal work of the Dejerines. This work was published in French and we provided the first English translation. (Bajada, Banks, Lambon Ralph, & Cloutman, 2017, Brain; https://doi.org/10.1093/brain/awx225)
(B) We explored the ATL’s response to various social and non-social concepts (Binney, Hoffman, & Lambon Ralph, 2016, Cerebral Cortex; doi: 10.1093/cercor/bhw260).

Clinical translation:
The proposal did not list specific impact targets. However, we have three broad areas of impact activity. The first is through academic and clinical dissemination of results and materials. Our excellent publication output is listed above which provides the major, worldwide dissemination of results. We supplement this with presentation to national and international conferences and clinical workshops . We also make available all new materials, etc. such as the new verb semantic battery to clinicians and researchers.

Secondly, we have generated new clinical prediction models (see Section 1.2.3.a).

Thirdly, we have been able to utilise our large patient database ato explore novel speech therapy interventions (Conroy, Sotiropoulou Drosopoulou, Humphreys, Halai, Lambon Ralph, 2018, Brain; https://doi.org/10.1093/brain/awy087).

Summary of the ventral language related connections in the brain