Periodic Reporting for period 4 - FLEXSEM (Graded constraints in semantic cognition: How do we retrieve knowledge in a flexible way?)
Reporting period: 2022-10-01 to 2024-03-31
For any concept (e.g. DOG), we have knowledge about diverse features – for example, a dog is furry, can chase rabbits, and is “man’s best friend”. This project examines the brain processes that allow us to flexibly retrieve relevant conceptual knowledge that suits our current goals and context. We can promote coherence between weakly-related aspects of knowledge as required (for example, to come up with creative solutions), and also achieve the timely release from patterns of retrieval when the situation changes. We can also tailor our ongoing retrieval to focus on specific features or associations that are relevant to our current goals - for example, if we are looking for an object we can use as a fan, we need to focus on items that are flat and stiff, even if these are not the most obvious features we know about the concepts. This ability to be flexible with our semantic knowledge is likely to play a central role in our mental lives – yet the underlying processes are poorly understood because past research has largely focused on how the conceptual store captures what is generally true across experiences (i.e. semantic representation). Consequently, the project should contribute to our basic scientific understanding of the mechanisms that shape and support our thoughts and behaviour. The project also has relevance for understanding the difficulties of patients with left hemisphere stroke, who often have semantic control impairments which mean they are relatively inflexible in the way they process conceptual knowledge.
The overall objective is to describe the brain processes underpinning flexible semantic retrieval. Control over semantic retrieval involves the recruitment of additional brain regions, organised within one or more networks, which place constraints on patterns of retrieval in the semantic store. In this way, semantic flexibility relates to the evolving interaction between distinct brain networks. The project draws on state-of-the-art accounts of brain organisation to consider the arrangement of different networks that contribute to semantic cognition in space, and through time. These accounts suggest that network transitions follow a systematic pattern as you move along the cortical surface, from the default mode network that supports coherent, heteromodal patterns of retrieval, through control regions to attentional networks that can focus processing on specific non-dominant but currently relevant features. This “graded constraints” hypothesis predicts that the location of networks is non-arbitrary, with brain regions further away from the heteromodal semantic store supporting retrieval when there is a greater mismatch between ongoing retrieval and the pattern required by the context. We test this idea with convergent neuroscientific methods that characterise functional recruitment in space (magnetic resonance imaging) and time (magnetoencephalography). We investigate causality (neuropsychology) and the broader implications of our account for cognition (using an individual differences approach).
The overall objective is to describe the brain processes underpinning flexible semantic retrieval. Control over semantic retrieval involves the recruitment of additional brain regions, organised within one or more networks, which place constraints on patterns of retrieval in the semantic store. In this way, semantic flexibility relates to the evolving interaction between distinct brain networks. The project draws on state-of-the-art accounts of brain organisation to consider the arrangement of different networks that contribute to semantic cognition in space, and through time. These accounts suggest that network transitions follow a systematic pattern as you move along the cortical surface, from the default mode network that supports coherent, heteromodal patterns of retrieval, through control regions to attentional networks that can focus processing on specific non-dominant but currently relevant features. This “graded constraints” hypothesis predicts that the location of networks is non-arbitrary, with brain regions further away from the heteromodal semantic store supporting retrieval when there is a greater mismatch between ongoing retrieval and the pattern required by the context. We test this idea with convergent neuroscientific methods that characterise functional recruitment in space (magnetic resonance imaging) and time (magnetoencephalography). We investigate causality (neuropsychology) and the broader implications of our account for cognition (using an individual differences approach).
The research is organised into 5 work packages.
1: Neuropsychology. We have recruited and tested participants with semantic aphasia, who have deficient semantic control following left hemisphere stroke. As part of this project, we have examined how these patients can understand coherent combinations of concepts relatively well but struggle whenever the task requires more control; for example, because the task involves sustaining a pattern of retrieval that is different from other recently-presented features.
2. Functional MRI. This is the method we have used most to date. Recent experiments show that the semantic control network is partially distinct from the multiple-demand network that underpins domain-general control, and located in between the default mode network and the multiple-demand network on the cortical surface in the left hemisphere. When we need to employ control in semantic cognition, either because we are trying to identify a creative link between two concepts that are only weakly related, or because we have a particular goal for retrieval in mind, we activate the same semantic control network. This suggests the application of goals to semantic retrieval in a top-down fashion draws on the same neural processes as bottom-up aspects of semantic control, when the concepts themselves specify the need for control processes. However, only top-down semntic control can be acheived by gating input processes, such that semantic activation from words and pictures is more efficently tailored to the task. When multiple pieces of information are provided and push us towards a consistent pattern of conceptual retrieval, the need for control is reduced and activation is focussed in the default mode network.
3. Time-sensitive neuroimaging using magnetoencephalography (MEG). MEG shows the oscillatory response to a pair of words differs across the semantic network, depending on the relationship between the items. When two words have highly coherent meanings, there is a stronger response in the anterior parts of the temporal lobes, close to default mode network areas, relatively late after the onset of the second word (suggesting coherence may build over time). When the words are only weakly-associated, there is a stronger response in posterior temporal areas associated with semantic control, at an earlier time point.
4. Later in the project, we plan to use transcranial magnetic stimulation to disrupt processes that lie at different points along the gradient of semantic networks, to investiagte their causal role. This part of the project has not yet started.
5. Individual differences in semantic cognition. We have found that individual differences within the semantic control network are associated with variability in the efficiency of controlled semantic retrieval. This part of the project is exploring the functional consequences of the neural architecture we have delineated.
1: Neuropsychology. We have recruited and tested participants with semantic aphasia, who have deficient semantic control following left hemisphere stroke. As part of this project, we have examined how these patients can understand coherent combinations of concepts relatively well but struggle whenever the task requires more control; for example, because the task involves sustaining a pattern of retrieval that is different from other recently-presented features.
2. Functional MRI. This is the method we have used most to date. Recent experiments show that the semantic control network is partially distinct from the multiple-demand network that underpins domain-general control, and located in between the default mode network and the multiple-demand network on the cortical surface in the left hemisphere. When we need to employ control in semantic cognition, either because we are trying to identify a creative link between two concepts that are only weakly related, or because we have a particular goal for retrieval in mind, we activate the same semantic control network. This suggests the application of goals to semantic retrieval in a top-down fashion draws on the same neural processes as bottom-up aspects of semantic control, when the concepts themselves specify the need for control processes. However, only top-down semntic control can be acheived by gating input processes, such that semantic activation from words and pictures is more efficently tailored to the task. When multiple pieces of information are provided and push us towards a consistent pattern of conceptual retrieval, the need for control is reduced and activation is focussed in the default mode network.
3. Time-sensitive neuroimaging using magnetoencephalography (MEG). MEG shows the oscillatory response to a pair of words differs across the semantic network, depending on the relationship between the items. When two words have highly coherent meanings, there is a stronger response in the anterior parts of the temporal lobes, close to default mode network areas, relatively late after the onset of the second word (suggesting coherence may build over time). When the words are only weakly-associated, there is a stronger response in posterior temporal areas associated with semantic control, at an earlier time point.
4. Later in the project, we plan to use transcranial magnetic stimulation to disrupt processes that lie at different points along the gradient of semantic networks, to investiagte their causal role. This part of the project has not yet started.
5. Individual differences in semantic cognition. We have found that individual differences within the semantic control network are associated with variability in the efficiency of controlled semantic retrieval. This part of the project is exploring the functional consequences of the neural architecture we have delineated.
Our use of cortical gradients to understand the functional organisation of cognition is novel. We are continuing to employ new methods to understand these functional transitions. We are also using multivariate imaging analysis methods to understand how the application of control proceses may change the representation of conceptual knowledge. This will advance our understanding of how flexible sematic retrieval emerges from interactions between control processes and long-term conceptual representations.
Over the next period until the end of the project, we expect these approaches to result in new knowledge. There are further fMRI studies in the pipeline, designed to replicate and extend our findings to date.
We will also do further MEG investigations, to understand how the context in which you encounter a concept changes the pattern of retrieval using time-resolved neuroimaging.
Finally, we will commence the TMS studies to demonstrate the causal necessity of semantic control processes for efficient semantic retrieval.
Over the next period until the end of the project, we expect these approaches to result in new knowledge. There are further fMRI studies in the pipeline, designed to replicate and extend our findings to date.
We will also do further MEG investigations, to understand how the context in which you encounter a concept changes the pattern of retrieval using time-resolved neuroimaging.
Finally, we will commence the TMS studies to demonstrate the causal necessity of semantic control processes for efficient semantic retrieval.