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Henson, R. N.

Publications and source records attributed to Henson, R. N..

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Multimodal integration and vividness in the angular gyrus during episodic encoding and retrieval

Much evidence suggests that the angular gyrus (AnG) is involved in episodic memory, but its precise role is yet to be determined. We examined two possible accounts, within the same experimental paradigm: the CoBRA account (Shimamura, 2011), which suggests that the AnG acts as a convergence zone that binds multimodal episodic features; and the Subjectivity account (Yazar et al., 2012), which implicates AnG involvement in subjective mnemonic experience (such as vividness or confidence). fMRI was employed during both encoding and retrieval of paired-associates. During study, female and male human participants memorised picture-pairs of common objects (in the unimodal task) or of an object-picture and an environmental sound (in the crossmodal task). At test, they performed a cued-recall task, and further indicated the vividness of their memory. During retrieval, BOLD activation in the AnG was greatest for vividly remembered associates, consistent with the Subjectivity account. During encoding, the same effect of vividness was found, but this was further modulated by task: Greater activations were associated with subsequent recall in the crossmodal than the unimodal task. Thus, encoding data suggests an additional role to the AnG in cross-modal integration, consistent with its role at retrieval proposed by CoBRA. These results resolve some of the puzzles in the literature and indicate that the AnG can play different roles during encoding and retrieval, determined by the cognitive demands posed by different mnemonic tasks.\n\nSignificance StatementWe offer new insights into the multiplicity of processes that are associated with angular gyrus (AnG) activation during encoding and retrieval of newly formed memories. We used fMRI while human participants learned and subsequently recalled pairs of objects presented to the same sensory modality or to different modalities. We were able to show that the AnG is involved when vivid memories are created and retrieved, as well as when encoded information is integrated across different sensory modalities. These findings provide novel evidence for the contribution of the AnG to our subjective experience of remembering, alongside its role in integrative processes that promote subsequent memory.

neuroscience

Motor learning decline with age is related to differences in the explicit memory system

The ability to adapt ones movements to changes in the environment is fundamental in everyday life, but this ability changes across the lifespan. Although often regarded as an implicit process, recent research has also linked motor adaptation with explicit learning processes. To understand how these processes contribute to differences in motor adaptation with age, we combined a visuomotor learning paradigm with cognitive tasks that measure implicit and explicit processes, and structural brain imaging. In a large population-based cohort from the Cambridge Centre for Ageing and Neuroscience (n=322, aged 18-89 years) we first confirmed that the degree of adaptation to an angular perturbation of visual feedback declined with age. There were no associations between adaptation and sensory attenuation, which has been previously hypothesised to contribute to implicit motor learning. However, interactions between age and scores on two independent memory tasks showed that explicit memory performance was a progressively stronger determinant of motor learning with age. Similarly, interactions between age and grey matter volume in the medial temporal lobe, amygdala and hippocampus showed that grey matter volume in these regions became a stronger determinant of adaptation in older adults. The convergent behavioural and structural imaging results suggest that age-related differences in the explicit memory system is a contributor to the decline in motor adaptation in older age. These results may reflect the more general compensatory reliance on cognitive strategies to maintain motor performance with age.\n\nSIGNIFICANCE STATEMENTThe central nervous system has a remarkable capacity to learn new motor skills and adapt to new environmental dynamics. This capacity is impaired with age, and in many brain disorders. We find that explicit memory performance and its associated medial temporal brain regions deteriorate with age, but the association between this brain system and individual differences in motor learning becomes stronger in older adults. We propose that these results reflect an increased reliance on cognition in order to maintain adaptive motor skill performance. This difference in learning strategy has implications for interventions to improve motor skills in older adults.

neuroscience

Neural evidence for age differences in representational quality and strategic retrieval processes

Mounting behavioral evidence suggests that declines in both representational quality and controlled retrieval processes contribute to episodic memory decline with age. The present study sought neural evidence for age-related change in these factors by measuring neural differentiation during encoding of paired associates, and changes in regional BOLD activity and functional connectivity during retrieval conditions that placed low (intact pairs) and high (recombined pairs) demands on controlled retrieval processes. Pattern similarity analysis revealed age-related declines in the differentiation of stimulus representations at encoding, manifesting as both reduced pattern similarity between closely related events, and increased pattern similarity between distinct events. During retrieval, both groups exhibited increased recruitment of areas within the core recollection network, including the hippocampus and angular gyrus, when endorsing studied pairs, whereas younger adults exhibited increased recruitment of, and hippocampal connectivity with, lateral prefrontal regions during correct rejections of recombined pairs. These results provide evidence for age-related changes in representational quality and in the neural mechanisms supporting memory retrieval under conditions of high, but not low, control demand.

neuroscience

Physical activity predicts population-level age-related differences in frontal white matter

Physical activity has positive effects on brain health and cognitive function throughout the lifespan. Thus far, few studies have examined the effects of physical activity on white matter (WM) microstructure and psychomotor speed within the same, population-based sample (critical if conclusions are to extend to the wider population). Here, using diffusion tensor imaging and a simple reaction time task within a relatively large population-derived sample (N = 399; 18-87 years) from the Cambridge Centre for Ageing and Neuroscience (Cam-CAN), we demonstrate that physical activity mediates the effect of age on white matter integrity, measured with fractional anisotropy. Higher self-reported daily physical activity was associated with greater preservation of WM in several frontal tracts, including the genu of corpus callosum, uncinate fasciculus, external capsule and anterior limb of the internal capsule. We also show that the age-related slowing is mediated by WM integrity in the genu. Our findings contribute to a growing body of work suggesting that a physically active lifestyle may protect against age-related structural disconnection and slowing.

neuroscience

Prospective Motion correction improves the sensitivity of fMRI pattern decoding

We evaluated the effectiveness of prospective motion correction (PMC) on a simple visual task when no deliberate subject motion was present. The PMC system utilizes an in-bore optical camera to track an external marker attached to the participant via a custom-moulded mouthpiece. The study was conducted at two resolutions (1.5mm vs 3mm) and under three conditions (PMC On and Mouthpiece On vs PMC Off and Mouthpiece On vs PMC Off and Mouthpiece Off). Multiple data analysis methods were conducted, including univariate and multivariate approaches, and we demonstrated that the benefit of PMC is most apparent for multi-voxel pattern decoding at higher resolutions. Additional testing on two participants showed that our inexpensive, commercially available mouthpiece solution produced comparable results to a dentist-moulded mouthpiece. Our results showed that PMC is increasingly important at higher resolutions for analyses that require accurate voxel registration across time.

neuroscience

The hippocampal film-editor: sensitivity and specificity to event boundaries in continuous experience

The function of the human hippocampus is normally investigated by experimental manipulation of discrete events. Less is unknown about what triggers hippocampal activity during more naturalistic, continuous experience. We hypothesized that the hippocampus would be sensitive to the occurrence of event boundaries, i.e. moments in time identified by observers as a transition between events. To address this, we analysed functional MRI data from two groups: one (N=253, 131 female) who viewed an 8.5min film and another (N=15, 6 female) who viewed a 120min film. We observed a strong hippocampal response at boundaries defined by independent observers, which was modulated by boundary strength (the number of observers that identified each boundary). In the longer film, there were sufficient boundaries to show that this modulation remained after covarying out a large number of perceptual factors. The hippocampus was the only brain region whose response showed a significant monotonic increase with boundary strength in both films, suggesting that modulation by boundary strength is selective to the hippocampus. This hypothesis-driven approach was complemented by a data-driven approach, in which we identified hippocampal-events as moments in time with the strongest hippocampal activity: The correspondence between these hippocampalevents and event boundaries was highly-significant, revealing that the hippocampal response is not only sensitive, but also specific to event boundaries. We conclude that the hippocampus plays an important role in segmenting the continuous experience that is typical of naturalistic settings.\n\nSignificance statementRecent years have seen the field of human neuroscience research transitioning from experiments with simple stimuli to the study of more complex and naturalistic experience. Nonetheless, our understanding of the function of many brain regions, such as the hippocampus, is based primarily on the study of brief, discrete events. As a result, we know little of what triggers hippocampal activity in real-life settings, when we are exposed to a continuous stream of information. When does the hippocampus \"decide\" to respond during the encoding of naturalistic experience? We reveal here that hippocampal activity measured by fMRI during film-watching is both sensitive and specific to event boundaries, identifying a potential mechanism whereby event boundaries shape experience by modulation of hippocampal activity.

neuroscience

MEG-BIDS: an extension to the Brain Imaging Data Structure for magnetoencephalography

We present a significant extension of the Brain Imaging Data Structure (BIDS) to support the specific aspects of magnetoencephalography (MEG) data. MEG provides direct measurement of brain activity with millisecond temporal resolution and unique source imaging capabilities. So far, BIDS has provided a solution to structure the organization of magnetic resonance imaging (MRI) data, which nature and acquisition parameters are different. Despite the lack of standard data format for MEG, MEG-BIDS is a principled solution to store, organize and share the typically-large data volumes produced. It builds on BIDS for MRI, and therefore readily yields a multimodal data organization by construction. This is particularly valuable for the anatomical and functional registration of MEG source imaging with MRI. With MEG-BIDS and a growing range of software adopting the standard, the MEG community has a solution to minimize curation overheads, reduce data handling errors and optimize usage of computational resources for analytics. The standard also includes well-defined metadata, to facilitate future data harmonization and sharing efforts.

neuroscience

From neurons to voxels - repetition suppression is best modelled by local neural scaling

Inferring neural mechanisms from functional magnetic resonance imaging (fMRI) is challenging because the fMRI signal integrates over millions of neurons. One approach is to compare computational models that map neural activity to fMRI responses, to see which best predicts fMRI data. We used this approach to compare four possible neural mechanisms of fMRI adaptation to repeated stimuli (scaling, sharpening, repulsive shifting and attractive shifting), acting across three domains (global, local and remote). Six features of fMRI repetition effects were identified, both univariate and multivariate, from two independent fMRI experiments. After searching over parameter values, only the local scaling model could simultaneously fit all data features from both experiments. Thus fMRI stimulus repetition effects are best captured by down-scaling neuronal tuning curves in proportion to the difference between the stimulus and neuronal preference. These results emphasize the importance of formal modelling for bridging neuronal and fMRI levels of investigation.

neuroscience

Increased prefrontal activity with aging reflects nonspecific neural responses rather than compensation

Elevated prefrontal cortex activity is often observed in healthy older adults despite declines in their memory and other cognitive functions. According to one view, this activity reflects a compensatory functional posterior-to-anterior shift, which contributes to maintenance of cognitive performance when posterior cortical function is impaired. Alternatively, the increased prefrontal activity may be less efficient or less specific, owing to structural and neurochemical changes accompanying aging. These accounts are difficult to distinguish on the basis of average activity levels within brain regions. Instead, we used a novel model-based multivariate analysis technique, applied to two independent functional magnetic resonance imaging datasets from an adult-lifespan human sample (N=123 and N=115; approximately half female). Standard analysis replicated the age-related increase in average prefrontal activation, but multivariate tests revealed that this activity did not carry additional information. The results contradict the hypothesis of a compensatory posterior-to-anterior shift. Instead, they suggest that the increased prefrontal activation reflects reduced efficiency or specificity, rather than compensation.\n\nSignificance statementFunctional brain imaging studies have often shown increased activity in prefrontal brain regions in older adults. This has been proposed to reflect a compensatory shift to greater reliance on prefrontal cortex, helping to maintain cognitive function. Alternatively, activity may become less specific as people age. This is a key question in the neuroscience of aging. In this study, we used novel tests of how different brain regions contribute to long- and short-term memory. We found increased activity in prefrontal cortex in older adults, but this activity carried less information about memory outcomes than activity in visual regions. These findings are relevant for understanding why cognitive abilities decline with age, suggesting that optimal function depends on successful brain maintenance rather than compensation.

neuroscience

Assessing dynamic functional connectivity in heterogeneous samples

Several methods have been developed to measure dynamic functional connectivity (dFC) in fMRI data. These methods are often based on a sliding-window analysis, which aims to capture how the brains functional organization varies over the course of a scan. The aim of many studies is to compare dFC across groups, such as younger versus older people. However, spurious group differences in measured dFC may be caused by other sources of heterogeneity between people. For example, the shape of the haemodynamic response function (HRF) and levels of measurement noise have been found to vary with age. We use a generic simulation framework for fMRI data to investigate the effect of such heterogeneity on estimates of dFC. Our findings show that, despite no differences in true dFC, individual differences in measured dFC can result from other (non-dynamic) features of the data, such as differences in neural autocorrelation, HRF shape, connectivity strength and measurement noise. We also find that common dFC methods such as k-means and multilayer modularity approaches can detect spurious group differences in dynamic connectivity due to inappropriate setting of their hyperparameters. fMRI studies therefore need to consider alternative sources of heterogeneity across individuals before concluding differences in dFC.

neuroscience

Symptoms of Depression in a Large Healthy Population Cohort are related to Subjective Memory Complaints and Memory Performance in Negative Contexts

Decades of research have investigated the impact of clinical depression on memory, which has revealed biases and in some cases impairments. However, little is understood about the effects of sub-clinical symptoms of depression on memory performance in the general population. Here we report the effects of symptoms of depression on memory problems in a large population-derived cohort (N = 2544), 87% of whom reported at least one symptom of depression. Specifically, we investigate the impact of depressive symptoms on subjective memory complaints, objective memory performance on a standard neuropsychological task and, in a subsample (n = 288), objective memory in affective contexts. There was a dissociation between subjective and objective memory performance, with depressive symptoms showing a robust relationship with self-reports of memory complaints, even after adjusting for age, gender, general cognitive ability and symptoms of anxiety, but not with performance on the standardised measure of verbal memory. Contrary to our expectations, hippocampal volume (assessed in a subsample, n = 592) did not account for significant variance in subjective memory, objective memory or depressive symptoms. Nonetheless, depressive symptoms were related to poorer memory for pictures presented in negative contexts, even after adjusting for memory for pictures in neutral contexts. Thus the symptoms of depression, associated with subjective memory complaints, appear better assessed by memory performance in affective contexts, rather than standardised memory measures. We discuss the implications of these findings for understanding the impact of depressive symptoms on memory functioning in the general population.

neuroscience

Adaptive Cortical Parcellations for Source Reconstructed EEG/MEG Connectomes

There is growing interest in the rich temporal and spectral properties of the brain's functional connectome that are provided by Electro- and Magnetoencephalography (EEG/MEG). However, the problem of leakage between brain sources that arises when reconstructing brain activity from EEG/MEG recordings outside the head makes it difficult to distinguish true connections from spurious connections, even when connections are based on measures that ignore zero-lag dependencies. In particular, standard anatomical parcellations for potential cortical sources tend to over- or under-sample the real spatial resolution of EEG/MEG. By using information from cross-talk functions (CTFs) that objectively describe leakage for a given sensor configuration and distributed source reconstruction method, we introduce methods for optimising the number of parcels while simultaneously minimising the leakage between them. More specifically, we compare two image segmentation algorithms: 1) a split-and-merge (SaM) algorithm based on standard anatomical parcellations and 2) a region growing (RG) algorithm based on all the brain vertices with no prior parcellation. Interestingly, when applied to minimum-norm reconstructions for EEG/MEG configurations from real data, both algorithms yielded approximately 70 parcels despite their different starting points, suggesting that this reflects the resolution limit of this particular sensor configuration and reconstruction method. Importantly, when compared against standard anatomical parcellations, resolution matrices of adaptive parcellations showed notably higher sensitivity and distinguishability of parcels. Furthermore, extensive simulations of realistic networks under various circumstances revealed significant improvements in network reconstruction accuracies, particularly in reducing false leakage-induced connections. Adaptive parcellations therefore allow a more accurate reconstruction of functional EEG/MEG connectomes.\n\nHighlightsO_LIWe introduce adaptive cortical parcellation algorithms for E/MEG source estimation.\nC_LIO_LIAlgorithms are based on cross-talk functions and image segmentation methods.\nC_LIO_LIThe resulting parcellations yielded ~70 parcels regardless of starting point.\nC_LIO_LISensitivity and distinguishability improved compared to anatomical parcellations.\nC_LIO_LIAccuracy of realistic whole-brain network reconstruction improved significantly.\nC_LI

neuroscience