Investigating White Matter Lesion Load, Intrinsic Functional Connectivity, and Cognitive Abilities in Older Adults

Changes to the while matter of the brain disrupt neural communication between spatially distributed brain regions and are associated with cognitive changes in later life. While approximately 95% of older adults experience these brain changes, not everyone who has significant white matter damage displays cognitive impairment. Few studies have investigated the association between white matter changes and cognition in the context of functional brain network integrity. This study used a data-driven, multivariate analytical model to investigate intrinsic functional connectivity patterns associated with individual variability in white matter lesion load as related to fluid and crystallized intelligence in a sample of healthy older adults (n = 84). Several primary findings were noted. First, a reliable pattern emerged associating whole-brain resting-state functional connectivity with individual variability in measures of white matter lesion load, as indexed by total white matter lesion volume and number of lesions. Secondly, white matter lesion load was associated with increased network disintegration and dedifferentiation. Specifically, lower white matter lesion load was associated with greater within- versus between-network connectivity. Higher white matter lesion load was associated with greater between-network connectivity compared to within. These associations between intrinsic functional connectivity and white matter lesion load were not reliably associated with crystallized and fluid intelligence performance. These results suggest that changes to the white matter of the brain in typically aging older adults are characterized by increased functional brain network dedifferentiation. The findings highlight the role of white matter lesion load in altering the functional network architecture of the brain

Predictive coding in auditory perception: challenges and unresolved questions.

Predictive coding is arguably the currently dominant theoretical framework for the study of perception. It has been employed to explain important auditory perceptual phenomena, and it has inspired theoretical, experimental and computational modelling efforts aimed at describing how the auditory system parses the complex sound input into meaningful units (auditory scene analysis). These efforts have uncovered some vital questions, addressing which could help to further specify predictive coding and clarify some of its basic assumptions. The goal of the current review is to motivate these questions and show how unresolved issues in explaining some auditory phenomena lead to general questions of the theoretical framework. We focus on experimental and computational modelling issues related to sequential grouping in auditory scene analysis (auditory pattern detection and bistable perception), as we believe that this is the research topic where predictive coding has the highest potential for advancing our understanding. In addition to specific questions, our analysis led us to identify three more general questions that require further clarification: (1) What exactly is meant by prediction in predictive coding? (2) What governs which generative models make the predictions? and (3) What (if it exists) is the correlate of perceptual experience within the predictive coding framework

An integrated neurovascular investigation of cognitive aging

Age-related declines in cognition are associated with widespread structural and functional brain changes, including changes in resting state functional connectivity (rsFC) and gray and white matter status. In addition, research has demonstrated that individual variance in cognitive aging is associated with cardiovascular health. In this dissertation, I integrate these factors into a cascade model and show how they might jointly and hierarchically account for individual differences in cognitive aging. The aim here is to have a framework that provides a starting point from which mechanistic pathways can be revealed and tested, ultimately advancing our knowledge for preventing or reducing age- related cognitive decline. In Chapter 1, I first review the factors that promote healthy cognitive aging and discuss the motivation for the focus on rsFC in later chapters. In Chapter 2, I introduce a cascade framework for cognitive aging that integrates the factors important for healthy brain health in aging. The results demonstrate for the first time that optically-measured cerebral arterial elasticity is strongly associated with segregation measures, and replicate previous findings of strong relationships between brain structure, brain function and cognition. In addition, the pattern of associations between these different factors is consistent with a hierarchical cascade framework linking them, suggesting that preventing or slowing age-related changes in one or more of these factors may induce a neurophysiological cascade beneficial for preserving cognition in aging. Extending these findings, Chapter 3 demonstrates that the results in Chapter 2 are not limited to parcellations derived from young-adult populations and can be extended to age-cohort- based parcellations. In Chapter 4, the main rsFC measure used in this dissertation– segregation – is investigated. Specifically, while network segregation is without doubt important as an index of brain health and cognitive function, the age-related changes in its topography has not been fully explored in previous studies due to various methodological constraints. In this chapter, I employ a distribution-based analysis to examine how decreased segregation is topographically changed with aging, manifesting in age-related cognitive declines. The results show that connectivity between networks is in fact systematically increased during aging, and that age-related decreases in segregation as a result of age-related adjustments in connectivity between networks are not simply the result of increased neural noise. Finally, Chapter 5 summarizes the results of previous chapters and discusses implications and future directions for the work in this dissertation. Overall, the research here demonstrates that individual variations in cognitive aging are connected to neurovascular factors in a cascade fashion, and implicates how we might optimize future interventions aimed at mitigating cognitive aging. Further, it extends our current understanding of how age changes the modular organization of functional networks, allowing us greater insight into how cognitive aging might be affected. Taken together with research showing the intervention effects of exercise, the current research supports the importance and potential of a healthy and active lifestyle for promoting healthy cognitive aging

Macro-scale patterns in functional connectivity associated with ongoing thought patterns and dispositional traits

Complex macro-scale patterns of brain activity that emerge during periods of wakeful rest provide insight into the organisation of neural function, how these differentiate individuals based on their traits, and the neural basis of different types of self-generated thoughts. Although brain activity during wakeful rest is valuable for understanding important features of human cognition, its unconstrained nature makes it difficult to disentangle neural features related to personality traits from those related to the thoughts occurring at rest. Our study builds on recent perspectives from work on ongoing conscious thought that highlight the interactions between three brain networks - ventral and dorsal attention networks, as well as the default mode network. We combined measures of personality with state-of-the-art indices of ongoing thoughts at rest and brain imaging analysis, and explored whether this ‘tri-partite’ view can provide a framework within which to understand the contribution of states and traits to observed patterns of neural activity at rest. To capture macro-scale relationships between different brain systems, we calculated cortical gradients to describe brain organisation in a low dimensional space. Our analysis established that for more introverted individuals, regions of the ventral attention network were functionally more aligned to regions of the somatomotor system and the default mode network. At the same time, a pattern of detailed self-generated thought was associated with a decoupling of regions of dorsal attention from regions in the default mode network. Our study, therefore, establishes interactions between attention systems and the default mode network are important influences on ongoing thought at rest and highlights the value of integrating contemporary perspectives on conscious experience when understanding patterns of brain activity at rest

Causes and Consequences of Dedifferentiation in the Aging Brain.

Cognitive performance declines across the adult lifespan. According to the dedifferentiation hypothesis of cognitive aging, age-related cognitive impairments reflect reductions in the fidelity of neural representations. However, behavioral tests of this hypothesis have yielded mixed results. Thus, the present research sought to explore age-related dedifferentiation using pattern classification of neural activity, which may yield a more direct measure of representational fidelity. Three studies examined age differences in the fidelity of the neural representations of visual stimuli, motor actions, and cognitive task sets, respectively. Study 1 showed that multi-voxel activation patterns evoked by presentation of face and house stimuli were less distinctive in older adults than in young adults. No regions showed greater distinctiveness in older adults than in young adults, and the spatial pattern of category information was similar across age groups, suggesting that older adults do not compensate for low- fidelity representations in visual cortex by forming higher-fidelity representations elsewhere in the brain. Study 2 extended these results to the domain of motor control, using multi-voxel pattern analysis to distinguish between left- and right-hand finger movements. Older adults showed reduced distinctiveness throughout a network of regions related to motor representation and control; again, no regions showed greater distinctiveness in older adults. Study 3 further investigated age differences in neural representations in the context of verbal and spatial working memory tasks. Results from memory encoding and retrieval were consistent with Studies 1 and 2, with reduced discrimination of verbal versus spatial information in older adults. In contrast, results from working memory maintenance showed that representational fidelity was decreased in older adults at high levels of task demand but increased in older adults at low levels of demand. Overall, results from perceptual and motor tasks were consistent with the dedifferentiation hypothesis, while results from memory maintenance were more consistent with compensation-related accounts of cognitive aging. These results suggest that both dedifferentiation- and compensation-based accounts can explain some phenomena, but that neither theory can offer a comprehensive account of age differences in neural representation. Future research should investigate the generalizability of the present results across analysis methods, cognitive tasks, and participant populations.PhDPsychologyUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/107180/1/jmcarp_1.pd

Predictive coding in auditory perception: challenges and unresolved questions

Predictive coding is arguably the currently dominant theoretical framework for the study of perception. It has been employed to explain important auditory perceptual phenomena, and it has inspired theoretical, experimental, and computational modelling efforts aimed at describing how the auditory system parses the complex sound input into meaningful units (auditory scene analysis). These efforts have uncovered some vital questions, addressing which could help to further specify predictive coding and clarify some of its basic assumptions. The goal of the current review is to motivate these questions, and show how unresolved issues in explaining some auditory phenomena lead to general questions of the theoretical framework. We focus on experimental and computational modelling issues related to sequential grouping in auditory scene analysis (auditory pattern detection and bistable perception), as we believe that this is the research topic where predictive coding has the highest potential for advancing our understanding. In addition to specific questions, our analysis led us to identify three more general questions that require further clarification: 1) What exactly is meant by prediction in predictive coding? 2)What governs which generative models make the predictions? and, 3) What (if it exists) is the correlate of perceptual experience within the predictive coding framework

Functional brain networks: intra and inter-subject variability in healthy individuals and patients with neurological or neuropsychiatric diseases.

The projects of this thesis sits at the intersection between classical neuroscience and aspects related to engineering, signals’ and neuroimaging processing. Each of the three years has been dedicated to specific projects carried out on distinct datasets, groups of individuals/patients and methods, putting great emphasis on multidisciplinarity and international mobility. The studies carried out in Cagliari were based on EEG (electroencephalography), and the one conducted abroad was developed on functional magnetic resonance imaging (fMRI) data. The common thread of the project concerns variability and stability of individuals' features related primarily to functional connectivity and network, as well as to the periodic and aperiodic components of EEG power spectra, and their possible use for clinical purposes. In the first study (Fraschini et al., 2019) we aimed to investigate the impact of some of the most commonly used metrics to estimate functional connectivity on the ability to unveil personal distinctive patterns of inter-channel interaction. In the second study (Demuru et al., 2020) we performed a comparison between power spectral density and some widely used nodal network metrics, both at scalp and source level, with the aim of evaluating their possible association. The first first-authored study (Pani et al., 2020)was dedicated to investigate how the variability due to subject, session and task affects electroencephalogram(EEG) power, connectivity and network features estimated using source-reconstructed EEG time-series of healthy subjects. In the study carried out with the supervision of Prof. Fornito (https://doi.org/10.1016/j.pscychresns.2020.111202) during the experience at the Brain, Mind and Society Research Hub of Monash University, partial least square analysis has been applied on fMRI data of an healthy cohort to evaluate how different specific aspects of psychosis-like experiences related to functional connectivity. Due to the pandemic of Sars-Cov-2 it was impossible to continue recording the patients affected by neurological diseases (Parkinson’s, Diskynesia) involved in the study we planned for the third year, that should have replicated the design of the first first-authored one, with the aim of investigate how individual variability/stability of functional brain networks is affected by diseases. For the aforementioned reason, we carried out the last study on a dataset we finished to record in February 2020. The analysis has the aim of investigate whether it is possible by using 19 channels sleep scalp EEG to highlight differences in the brain of patients affected by non-rem parasomnias and sleep-related hypermotor epilepsy, when considering the periodic and aperiodic component of EEG power spectra

The Sync-Fire/deSync Model: modelling the reactivation of dynamic memories from cortical alpha oscillations

We propose a neural network model to explore how humans can learn and accurately retrieve temporal sequences, such as melodies, movies, or other dynamic content. We identify target memories by their neural oscillatory signatures, as shown in recent human episodic memory paradigms. Our model comprises three plausible components for the binding of temporal content, where each component imposes unique limitations on the encoding and representation of that content. A cortical component actively represents sequences through the disruption of an intrinsically generated alpha rhythm, where a desynchronisation marks information-rich operations as the literature predicts. A binding component converts each event into a discrete index, enabling repetitions through a sparse encoding of events. A timing component – consisting of an oscillatory “ticking clock” made up of hierarchical synfire chains – discretely indexes a moment in time. By encoding the absolute timing between discretised events, we show how one can use cortical desynchronisations to dynamically detect unique temporal signatures as they are reactivated in the brain. We validate this model by simulating a series of events where sequences are uniquely identifiable by analysing phasic information, as several recent EEG/MEG studies have shown. As such, we show how one can encode and retrieve complete episodic memories where the quality of such memories is modulated by the following: alpha gate keepers to content representation; binding limitations that induce a blink in temporal perception; and nested oscillations that provide preferential learning phases in order to temporally sequence events

Change blindness: eradication of gestalt strategies

Arrays of eight, texture-defined rectangles were used as stimuli in a one-shot change blindness (CB) task where there was a 50% chance that one rectangle would change orientation between two successive presentations separated by an interval. CB was eliminated by cueing the target rectangle in the first stimulus, reduced by cueing in the interval and unaffected by cueing in the second presentation. This supports the idea that a representation was formed that persisted through the interval before being 'overwritten' by the second presentation (Landman et al, 2003 Vision Research 43149–164]. Another possibility is that participants used some kind of grouping or Gestalt strategy. To test this we changed the spatial position of the rectangles in the second presentation by shifting them along imaginary spokes (by ±1 degree) emanating from the central fixation point. There was no significant difference seen in performance between this and the standard task [F(1,4)=2.565, p=0.185]. This may suggest two things: (i) Gestalt grouping is not used as a strategy in these tasks, and (ii) it gives further weight to the argument that objects may be stored and retrieved from a pre-attentional store during this task