A comparison of imaging modalities and decoding methods for detecting semantic information in the brain

Representation of semantic information enables us to engage with the world in a meaningful way – to comprehend and produce language, identify and use objects, and understand and participate in events that involve us. Our understanding of where in the brain semantic information is represented has progressed much more rapidly than our understanding of how semantic information is represented – that is, how activity in the brain enables semantic knowledge to be stored, ready for later deployment. This thesis aimed (1) to develop a theoretical framework with which to describe the nature of neural representations, including semantic representations; (2) to assess and compare the capacities of electrocorticography (ECoG) and 7 tesla functional magnetic resonance imaging (7T-fMRI) to detect semantic representations; and (3) to evaluate the strengths and limitations of multivariate analysis methods, in particular methods based on regularised regression, for revealing properties of semantic representations. In Chapter 2 I propose a new theoretical framework for describing representations. By posing six questions about the computational and neural characteristics of the representations that different theorists posit, I situate each contemporary theory relative to the others and bring the inseparable relationship between theory and analysis into focus – different multivariate methods encapsulate different assumptions (not always made explicit) about how the brain represents information. In Chapter 3 I investigate the temporal dynamics of semantic representations, specifically time-frequency power and phase. By analysing ECoG data recorded from grid electrodes on the ventral temporal cortical surface, I established that semantic information could be decoded from multiple frequency bands. However, only when classifiers were trained on power from all frequencies between 4 and 200 Hz did the “distributed, dynamic" properties observed in voltage data and in a computational model of semantic cognition emerge, suggesting that semantic information is represented in the ventrolateral anterior temporal lobe (vATL) in a “transfrequency” fashion. In Chapter 4 I lay the foundations for studying semantic representations with 7T-fMRI– I optimised a 7T-fMRI acquisition sequence that improved sensitivity in the vATL while maintaining sensitivity across the rest of the brain. I demonstrated that a multi-echo, multiband sequence achieves these aims. In Chapter 5 I used the acquisition sequence optimised in Chapter 4, plus four different multivariate decoding methods, to ask why semantic information is so rarely detected in the vATL with fMRI despite the body of evidence for its presence and to ask whether and where semantic information is represented elsewhere in the brain. Having found evidence for dynamic, graded, multidimensional representations in the vATL, I concluded that my use of a distortion-corrected acquisition sequence and my choice of analysis methods are the most likely reasons for the difference between my findings and previous work. I also found evidence of graded, multidimensional semantic structure in posterior temporal cortex. To conclude, this thesis (1) developed a unifying theoretical framework in which to situate theories about, and methods for discovering, semantic representations in the brain; (2) established that both ECoG and fMRI can provide insight into the properties of semantic representations; and (3) demonstrated that decoding methods that incorporate neurally-inspired regularisation penalties can be beneficial for decoding, but argued that the best decoding methods for future studies are those that are carefully selected to complement the research question

Using fMRI and Behavioural Measures to Investigate Rehabilitation in Post-Stroke Aphasic Deficits

In this thesis I investigated whether an intensive computerised, home-based therapy programme could improve phonological discrimination ability in 19 patients with chronic post-stroke aphasia. One skill specifically targeted by the treatment demonstrated an improvement due to the therapy. However, this improvement did not generalise to untreated items, and was only effective for participants without a lesion involving the frontal lobe, indicating a potentially important role for this region in determining outcome of aphasia therapy. Complementary functional imaging studies investigated activity in domain-general and domain-specific networks in both patients and healthy volunteers during listening and repeating simple sentences. One important consideration when comparing a patient group with a healthy population is the difference in task difficulty encountered by the two groups. Increased cognitive effort can be expected to increase activity in domain-general networks. I minimised the effect of this confound by manipulating task difficulty for the healthy volunteers to reduce their behavioural performance so that it was comparable to that of the patients. By this means I demonstrated that the activation patterns in domain-general regions were very similar in the two groups. Region-of-interest analysis demonstrated that activity within a domain-general network, the salience network, predicted residual language function in the patients with aphasia, even after accounting for lesion volume and their chronological age. I drew two broad conclusions from these studies. First, that computer-based rehabilitation can improve disordered phonological discrimination in chronic aphasia, but that lesion distribution may influence the response to this training. Second, that the ability to activate domain-general cognitive control regions influences outcome in aphasia. This allows me to propose that in future work, therapeutic strategies, pharmacological or behavioural, targeting domain-general brain systems, may benefit aphasic stroke rehabilitation.Open Acces

Effects of Diversity and Neuropsychological Performance in an NFL Cohort

Objective: The aim of this study was to examine the effect of ethnicity on neuropsychological test performance by comparing scores of white and black former NFL athletes on each subtest of the WMS. Participants and Methods: Data was derived from a de-identified database in South Florida consisting of 63 former NFL white (n=28, 44.4%) and black (n=35, 55.6%) athletes (Mage= 50.38; SD= 11.57). Participants completed the following subtests of the WMS: Logical Memory I and II, Verbal Paired Associates I and II, and Visual Reproduction I and II. Results: A One-Way ANOVA yielded significant effect between ethnicity and performance on several subtests from the WMS-IV. Black athletes had significantly lower scores compared to white athletes on Logical Memory II: F(1,61) = 4.667, p= .035, Verbal Paired Associates I: F(1,61) = 4.536, p = .037, Verbal Paired Associates: II F(1,61) = 4.677, p = .034, and Visual Reproduction I: F(1,61) = 6.562, p = .013. Conclusions: Results suggest significant differences exist between white and black athletes on neuropsychological test performance, necessitating the need for proper normative samples for each ethnic group. It is possible the differences found can be explained by the psychometric properties of the assessment and possibility of a non-representative sample for minorities, or simply individual differences. Previous literature has found white individuals to outperform African-Americans on verbal and non-verbal cognitive tasks after controlling for socioeconomic and other demographic variables (Manly & Jacobs, 2002). This highlights the need for future investigators to identify cultural factors and evaluate how ethnicity specifically plays a role on neuropsychological test performance. Notably, differences between ethnic groups can have significant implications when evaluating a sample of former athletes for cognitive impairment, as these results suggest retired NFL minorities may be more impaired compared to retired NFL white athletes

The Effect of Ethnicity on Neuropsychological Test Performance of Former NFL Athletes

Objective: To investigate the effect of ethnicity on neuropsychological test performance by specifically exploring differences between white and black former NFL athletes on subtests of the WAIS-IV. Participants and Methods: Data was derived from a de-identified database in Florida consisting of 63 former NFL athletes (Mage=50.38; SD=11.57); 28 white and 35 black. Participants completed the following subtests of the WAIS-IV: Block Design, Similarities, Digit Span, Matrix Reasoning, Arithmetic, Symbol Search, Visual Puzzles, Coding, and Cancellation. Results: One-Way ANOVA yielded a significant effect between ethnicity and performance on several subtests. Black athletes had significantly lower scaled scores than white athletes on Block Design F(1,61)=14.266, p\u3c.001, Similarities F(1,61)=5.904, p=.018, Digit Span F(1,61)=8.985, p=.004, Arithmetic F(1,61)=16.07, p\u3c.001 and Visual Puzzles F(1,61)=16.682, p\u3c .001. No effect of ethnicity was seen on performance of Matrix Reasoning F(1,61)=2.937, p=.092, Symbol Search F(1,61)=3.619, p=.062, Coding F(1,61)=3.032, p=.087 or Cancellation F(1,61)=2.289, p=.136. Conclusions: Results reveal significant differences between white and black athletes on all subtests of the WAIS-IV but those from the Processing Speed Scale and Matrix Reasoning. These findings align with previous literature that found white individuals to outperform African-Americans on verbal and non-verbal tasks after controlling for socioeconomic and demographic variables (Manly & Jacobs, 2002). These differences may also be a reflection of the WAIS-IV’s psychometric properties and it is significant to consider the normative sample used may not be appropriate for African-Americans. This study highlights the need for future research to identify how ethnicity specifically influences performance, sheds light on the importance of considering cultural factors when interpreting test results, and serves as a call to action to further understand how and why minorities may not be accurately represented in neuropsychological testing

Regional Cerebral Blood Flow Patterns in Children vs. Adults with ADHD Combined and Inattentive Types: A SPECT Study

Objective: The current study sought to determine whether ADHD Combined Type (ADHD-C) and ADHD Primarily Inattentive Type (ADHD-PI) showed differential regional cerebral blood flow (rCBF) patterns in children vs. adults. Participants and Methods: The overall sample (N=1484) was effectively split into four groups: adults with ADHD-PI (n=519), adults with ADHD-C (n=405), children with ADHD-PI (n=192), children with ADHD-C (n=368). All participants were void of bipolar, schizophrenia, autism, neurocognitive disorders, and TBI. The data were collected from a de-identified archival database of individuals who underwent SPECT scans at rest. Results: Using αConclusions: Overall, the current study suggested that children may show rCBF differences between different ADHD subtypes, but adults may not. The current study did not find significance in any of the 17 brain regions examined when comparing adults with ADHD-C to adults with ADHD-PI. All significant findings were attributed to the children with ADHD-C group showing aberrant blood flow rate than at least one other group. Previous research has supported that the differentiation of these subtypes as distinctive disorders is difficult to make in adults (Sobanski et al., 2006). Other research has indicated the potential of imaging techniques to differentiate the two in children (Al-Amin, Zinchenko, & Geyer, 2018). The current findings support nuanced ways in which rCBF patterns of ADHD-C and ADHD-PI differ between children and adults

Towards Quantitative Assessment of Human Functional Brain Development in the First Years of Life

Characterizing the developmental process of human brain function is of critical importance not only in gaining insight into its maturing architecture but also in providing essential age-specific information for assessment and monitoring of both normal and abnormal neurodevelopment. The recent development of non-invasive neuroimaging techniques, particularly resting-state functional connectivity magnetic resonance imaging (rfcMRI) has opened a window into very early functional brain development. Together with diffusion tensor imaging (DTI), rfcMRI offers the unique opportunity to tackle a largely unknown area - early functional brain development as well as its structural underpinnings. In this dissertation, both rfcMRI and DTI were utilized to delineate early brain development. Structurally, we found that white matter fiber tracts experience most rapid axonal development as well as myelination in the first year, followed by a much slower but steady growth thereafter. Spatially, the central white matter tracts develop earlier than the peripheral ones. Functionally, by focusing on one of the most salient high-order cognitive networks during the resting condition (absence of any goal-directed tasks) - the default-mode network, our results showed early emergence of this network in neonates, followed by dramatic synchronization during the first year of life and an adult-like architecture in 2yr olds regarding the core regions. Moreover, we found the anti-correlation (competing functions) between the default network and the task positive network is largely mediated by the frontal-parietal control system using both regional and newly designed network-level approaches, shedding light on brain's functional interaction patterns at a network level. Finally, focusing on the whole brain architecture, our results showed interesting patterns of brain's functional organization development. Specifically, the brain's functional architecture develops from more anatomically sensible to more functionally sensible; for the functional hubs, they gradually shift from sensory-related cortices to higher-order cognitive function related cortices. In conclusion, by focusing on neural circuit development at regional, network as well as whole brain levels and coupling with structural elements, our results delineated interesting and important functional circuits growth patterns and may shed light on the potential principles guiding normal early brain functional development

Objective neurophysiologic markers to aid assessment of prolonged disorders of consciousness (PDoC)

Abstract: Clinical assessments of individuals with cognitive-motor dissociation (CMD) following brain injury are both challenging and error prone. Prior studies have shown that electroencephalographic or EEG-based brain-computer interface protocols for motor-command following (MCF) and differences in the N1 and P3 components of auditory evoked potentials (AEPs) in response to an auditory oddball paradigm, can provide a more accurate, quantitative assessment of children with CMD. This study investigates if these EEG measures would aid in the assessment of adults with prolonged disorders of consciousness (PDoC); and if brain-computer interface (BCI) protocols using motor-imagery decoding tasks or latencies of AEPs can improve cognitive assessments of individuals with PDoC. Methods: EEG data from nine individuals with PDoC, including cases of unresponsive wakefulness syndrome (UWS), minimally conscious state (MCS), and locked-in syndrome (LIS), were recorded using a 16-channel gNautilus system (g.tec). The MCF protocol included up to 12 sessions of 240 trials each. During the first six sessions, participants underwent training with and without feedback, to learn to consistently imagine moving one of two limbs, such as the left or right hand, in response to auditory cues. From the seventh session onward, this binary imagery task was associated with yes and no and applied in a closed question-and-answer task. Separately, the auditory oddball protocol included at least two sessions, approximately 10 days apart. Each session involved 2 five-minute sets of auditory stimuli: 340ms square-wave beeps at frequencies of 400 Hz (standard) or 575 Hz (deviant), along with various novel sounds, following a standard:deviant:novel ratio of 27:8:6 per set. Results: Mean N1 AEP latencies had significant group differences due to lower latencies for the LIS and MCS groups as compared to the UWS group (LIS v UWS - p < 0.001; MCS v UWS - p = 0.005). Furthermore, mean AEP latencies were found to be negatively correlated with the mean of the decoding accuracies (DA) obtained from significant runs for each participant during the corresponding motor-imagery sessions (i.e., latencies decreased as DA increased, p = 0.011, one-tailed). Conclusion: The latency of the N1 AEP may aid the assessment of awareness in PDoC. The finding that N1 latencies are correlated with motor imagery DA across groups suggest that both movement-independent measures could be used complementarily to improve accuracy in detecting consciousness in adults with PDoC

Objective neurophysiologic markers to aid assessment of prolonged disorders of consciousness (PDoC)

Clinical assessments of individuals with cognitive-motor dissociation (CMD) following brain injury are both challenging and error prone. Prior studies have shown that electroencephalographic or EEG-based brain computer interface protocols for motor-command following (MCF) and differences in the N1 and P3 components of auditory evoked potentials (AEPs) in response to an auditory oddball paradigm can provide a more accurate, quantitative assessment of children with CMD (Kim et al., 2022). This study investigates if these EEG measures would aid in the assessment of adults with prolonged disorders of consciousness (PDoC); and if brain-computer interface (BCI) protocols using motor-imagery decoding tasks or latencies of AEPs can improve cognitive assessments of individuals with PDoC.Methods: EEG data from nine individuals with PDoC, including cases of unresponsive wakefulness syndrome (UWS), minimally conscious state (MCS), and locked-in syndrome (LIS), were recorded using a 16-channel gNautilus system (g.tec). The MCF protocol included up to 12 sessions of 240 trials each. During the first six sessions, participants underwent training with and without feedback, to learn to consistently imagine moving one of two limbs, such as the left or right hand, in response to auditory cues. From the seventh session onward, this binary imagery task was associated with yes and no and applied in a closed question-and-answer task. Separately, the auditory oddball protocol included at least two sessions, approximately 10 days apart. Each session involved 2 five-minute sets of auditory stimuli: 340ms square-wave beeps at frequencies of 400 Hz (standard) or 575 Hz (deviant), along with various novel sounds, following a standard:deviant:novel ratio of 27:8:6 per set. Results: Mean N1 AEP latencies had significant group differences due to lower latencies for the LIS and MCS groups as compared to the UWS group (LIS v UWS – p &lt; 0.001; MCS v UWS – p = 0.005). Furthermore, mean AEP latencies were found to be negatively correlated with the mean of the decoding accuracies (DA) obtained from significant runs for each participant during the corresponding motor-imagery sessions (i.e., latencies decreased as DA increased, p = 0.011, one-tailed).Conclusion: The latency of the N1 AEP may aid the assessment of awareness in PDoC. The finding that N1 latencies are correlated with motor imagery DA across groups suggest that both movement-independent measures could be used complementarily to improve accuracy in detecting consciousness in adults with PDoC.<br/

A brief questionnaire to evaluate the semantic disorder in Alzheimer’s disease: the “Mini SKQ”

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