A stroke or dementia can strip away the meaning of everyday words, objects, and symbols, leaving a person unable to follow a conversation or read a road sign. This research tackles a fundamental gap in understanding why semantic memory—the brain’s database of meaning—breaks down so differently across conditions like semantic dementia, Alzheimer’s disease, and brain infections. The team has already discovered that semantic memory relies on two distinct brain networks: one stores knowledge, the other flexibly manipulates it for the task at hand. They now aim to map how these networks interact under pressure and what compensatory processes kick in after brain damage. If successful, the work will produce a new mathematical model that mimics both healthy semantic processing and the specific impairment patterns of different patient groups. This model could sharpen differential diagnosis, guide speech therapy interventions, and help clinicians predict which strategies best support each patient’s remaining semantic abilities. The project is primarily fundamental science—building a complete picture of how the brain handles meaning—but its direct clinical payoff would be more precise, evidence-based rehabilitation for millions of people whose daily lives are quietly derailed by semantic loss.
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Semantic memory refers to the rich database of knowledge we have about the meanings of words, objects, people and all the stimuli present in our environment. We activate this information when we comprehend a word or recognise an object. We use the same knowledge for speech or non-verbal activities such as object use. The aim of communication, itself, is for meaning to be conveyed between people. It is evident, therefore, that semantic knowledge is crucial for many everyday activities both at work and at home. When this type of knowledge disintegrates or becomes inaccessible after brain damage, patients become significantly disabled in many aspects of their lives. Imagine, for example, being able to comprehend only a small proportion of the words in everyday conversation, a letter or newspaper; being stuck with significant word-finding problems; or being unable to understand everyday symbols or road signs. Sadly, these kinds of problems are a common feature of many types of brain disease. Semantic impairment is a characteristic of certain types of dementia, brain infections and after stroke or neurosurgery. In our last research programme, we developed the necessary methods and clinical links to undertake unique, detailed comparisons of different patient groups (semantic dementia, semantic aphasia, herpes simplex virus encephalitis, Alzheimer's disease, resection for temporal lobe epilepsy, and Wernicke's aphasia) and linked these patient studies directly with parallel explorations of the healthy semantic system. In particular, we discovered that there are two subsystems - one for coding the database of semantic information and a separate brain network for manipulating and shaping this information depending on the task requirements or context. The core aims of our continuing research programme, therefore, are (a) to investigate the nature and function of different key areas within each semantic brain network; (b) examine the flexible interaction between the networks when the system comes under pressure and the associated compensatory processes that are triggered by brain damage; and (c) we will begin to explore both the brain structures and brain chemicals that are involved in semantic function. These steps will be used to improve: detection of semantic deficits; differential diagnosis; clinical management; and evidence-based interventions. Our ultimate aim is to build up a complete picture and model of the network of brain regions that support semantic processing. We have pioneered a new type of mathematical model which mirrors brain regions and their connections, and after training, generates human semantic behaviours. When these models are damaged they can mimic the types of impairment found in different patient groups. We will use the new findings from the studies of patients and healthy participants to generate a model of semantic processing that includes the networks for both semantic knowledge and semantic manipulation. We will use this model to reproduce each patient group's pattern of performance. We will then be able to use this model not only to understand the nature of semantic problems across all these different patient groups but also to use the model to gain new insights about minimising these problems and for generating new interventions that could be used by speech therapists with these patient groups.
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