Motion artifacts are often a significant component of the measured signal in functional near-infrared spectroscopy (fNIRS) experiments. A variety of methods have been proposed to address this issue, including principal component analyses (PCA), Kalman filtering, correlation-based signal improvement (CBSI), wavelet filtering, spline interpolation, and autoregressive algorithms. The efficacy of these techniques has been compared using simulated data; however, our understanding of how these techniques fare when dealing with task-based cognitive data is limited. Recently, Brigadoi et al. (2014) quantitatively compared 6 motion correction techniques in a sample of adult data measured during a simple cognitive task. Wavelet filtering showed the most promise as an optimal technique for motion correction. Because fNIRS is often used with infants and young children, it is critical to evaluate the effectiveness of motion correction techniques directly with data from these age groups. Here we examined which techniques are most effective with data from young children. The efficacy of each technique was compared quantitatively using objective metrics related to the physiological properties of the hemodynamic response using two different sets of parameters to ensure maximum retention of included trials. Results showed that targeted PCA (tPCA) and CBSI retained a higher number of trials. These techniques also performed well in direct head-to-head comparisons with the other approaches using both quantitative metrics and a qualitative assessment. The CBSI technique corrected many of the artifacts present in our data; however, this technique was highly influenced by the parameters used to detect motion. The tPCA technique, by contrast, was robust across changes in parameters while also performing well across all comparison metrics. We conclude, therefore, that tPCA is an effective technique for the correction of motion artifacts in fNIRS data from young children.

The Intensive Cognitive and Communication Rehabilitation program (ICCR), developed to advance young adults with acquired brain injury (ABI) to college, targets a range of cognitive domains (e.g., memory, writing, verbal expression) via classroom-style lectures, individual therapy, and technology- and computer-based interventions on an intensive schedule (i.e., six hours/day, four days/week, 12-week iterations). One of the driving hypotheses of this dissertation work is that cognitive rehabilitation programs that are embedded with principles of experience-dependent neuroplasticity (i.e., repetition, intensity, specificity, salience), like ICCR, should lead to changes in behavior and the brain. The initial two studies of this dissertation focused on the first aspect of this hypothesis (i.e., assessing the impact of ICCR on overall cognitive-linguistic function and specific cognitive domains important for academic success in young adults with ABI), while the final two studies addressed the second aspect (i.e., using fNIRS to measure brain activation during language and domain-general cognitive tasks in neurotypicals and individuals with ABI at a single timepoint and over time). In Study 1, young adults with ABI who participated in ICCR demonstrated significant gains in at least one standardized assessment of global cognitive-linguistic function, while control participants did not. Yet, the study did not reveal what specific cognitive domains important for academic success improved after the ICCR program—an essential intermediate step in evaluating the utility of these programs in preparing young adults with ABI for academic reentry. Study 2 addressed this unanswered question with a novel approach that aggregated items from standardized neuropsychological assessments into specific cognitive domains (e.g., attention, verbal expression, memory) and then, applied growth curve modeling to assess whether those domains improved significantly over time in young adults with ABI participating in the ICCR program. This study also directly compared whether the treatment group improved at a significantly faster rate in overall item accuracy and subdomain item accuracy than a deferred treatment/control usual care group, extending the findings from Study 1 with a larger participant sample. Study 3 was a pilot study using fNIRS to capture brain activation in expected regions during language and domain-general cognitive processing in neurotypicals and individuals with stroke-induced aphasia. Findings from the young healthy control group in this study would serve as a reference for interpreting brain activation patterns in the damaged brain in future work. This study also provided opportunities to determine the acceptability of the fNIRS behavioral tasks and acquisition procedures for individuals with stroke-induced aphasia and to assess the utility of a novel method for managing areas of lesion. Based on the robust findings of Study 1 and 2 (i.e., ICCR promoted gains in overall cognitive domains and specific cognitive processes important for college success) and the promising results of Study 3 (i.e., activation patterns during language and domain-general cognitive processing could be captured in neurotypicals and individuals with brain damage at a single timepoint using fNIRS), Study 4 was undertaken to assess pre- to post-treatment activation changes following ICCR participation via fNIRS. Five young adults with ABI underwent fNIRS measurement while performing the same behavioral task battery used in Study 3 (i.e. semantic feature, picture naming, arithmetic) before and after a 12-week semester of ICCR. This preliminary work provided opportunities 1) to apply fNIRS to measure treatment-related neuroplasticity in the ABI population; 2) to examine the extent to which treatment participants demonstrated changes in the brain following ICCR in conjunction with a positive treatment response and improved behavioral task accuracy; and 3) to identify methodological considerations for future studies in this area. In closing, this dissertation reviews key findings from each of these studies and discusses their implications for studying rehabilitation-induced recovery in adults with ABI in future work. / 2023-08-06T00:00:00Z

Variability in neural activity has historically been treated as noise, in favour of deriving estimates based on central tendency (e.g., mean). Recently, researchers have shown that variability and mean confer different sources of information and that increased variability in neural activity is associated with superior behavioural performance and that it decreases during late-life. Although mounting evidence suggests that neural variability is beneficial, it is less clear whether these findings are driven by within- or between-person factors and whether they are apparent during higher-order cognitive tasks. Further, variability can be derived in several different ways, drawing into question its congruence across operationalizations. The present investigation sought to separate within- and between-person sources of variance in order to ascertain what was driving any observable effects in three operationalizations of cerebral oxygenation, computed based on central tendency (mean), variability (standard deviation) and signal complexity (multivariate multiscale entropy). 25 older adults (71-81 years of age) completed two tasks of executive functions while undergoing assessment using functional near infrared spectroscopy. Time-varying covariation models were employed to estimate the effects of cerebral oxygenation on behavioural performance, as well as the moderating effects of age and fall status. Findings suggest that mean and variability are differentially associated with behavioural performance and are increased in older adults at greater fall risk. Whereas mean based computations were positively associated with more accurate and faster responding, variability based computations were primarily associated with faster responding only and occurred in non-overlapping regions of prefrontal cortex. Future studies of neural variability may consider examining within- and between-person factors and operationalizing signal complexity in cerebral oxygenation over longer time periods to examine its effects over multiple time scales. / Graduate / drewh@uvic.ca

Regional tissue temperature dynamics in the brain are determined by the balance of the metabolic heat production rate and heat exchange with blood flowing through capillaries embedded in the brain tissue, the surrounding tissues and the environment. Local changes in blood flow and metabolism during functional activity can upset this balance and induce transient temperature changes. Invasive experimental studies in animal models have estab- lished that the brain temperature changes during functional activity are observable and a definitive relationship exists between temperature and brain activity. We present a theoreti- cal framework that links tissue temperature dynamics with hemodynamic activity allowing us to non-invasively estimate brain temperature changes from experimentally measured blood- oxygen level dependent (BOLD) signals. With this unified approach, we are able to pinpoint the mechanisms for hemodynamic activity-related temperature increases and decreases. In addition to these results, the potential uses and limitations of optical measurements are dis- cussed.

Orientador: Prof. Dr. João Ricardo Sato / Coorientador: Prof. Dr. André Mascioli Cravo / Tese (doutorado) - Universidade Federal do ABC, Programa de Pós-Graduação em Neurociência e Cognição, São Bernardo do Campo, 2018.

The postural control-cognition dual-task literature has demonstrated greater postural stability through the examination of multiple kinetic and kinematic measures. Recently, sample entropy (SampEn) and wavelet discrete transform have supported the claim of automaticity, as higher SampEn values and a shift toward higher contribution from automatic sensory systems have been demonstrated in dual-task settings. In order to understand the cortical component of postural control, functional near-infrared spectroscopy (fNIRS) has been used to identify cortical activation under postural control conditions. However, the neural correlates of automatic postural behaviour have yet to be fully investigated. Therefore, the purpose of this study is to confirm the presence of automatic postural control through static and dynamic measurements, and to investigate the prefrontal cortex activation (PFC) when concurrently performing quiet standing and auditory cognitive tasks. Eighteen healthy young adults (21,4 ± 3,96yo), 12 females and 6 males, with no balance deficits were recruited. Participants were instructed to either quietly stand on a force platform (SM), perform three cognitive tasks while seated (SC) and perform a combination of SM and SC concurrently (DT). Results revealed automatic postural control as evidenced by lower area and standard deviation of center-of-pressure in DT conditions. As for SampEn and the wavelet analysis, greater values and a shift from vision to the cerebellum contribution were demonstrated in DT conditions. For the DNS task, a trend toward significantly lower right hemisphere PFC activation compared to left hemisphere activation in DT was evidenced, which potentially reiterate the presence of automaticity. Therefore, as demonstrated by this experiment, the simultaneous performance of a difficult cognitive task and posture yields automatic postural behaviour, and provides insight into the neural correlates of automaticity.

Schizophrenia is a severe neuropsychiatric disorder characterized by delusions, hallucinations, behavioral symptoms, and cognitive deficits. Roughly, 70%-80% of schizophrenia patients experience auditory verbal hallucinations (AVHs), with 25%-30% demonstrating resistance to conventional antipsychotic medications. Studies suggest a promising role for add-on transcranial direct current stimulation (tDCS) in the treatment of medication-refractory AVHs. The mechanisms through which tDCS could be therapeutic in such cases are unclear, but possibly involve neuroplastic effects. In recent years, functional near-infrared spectroscopy (fNIRS) has been used successfully to study tDCS-induced neuroplastic changes. In a double-blind, sham-controlled design, we applied fNIRS to measure task-dependent cerebral blood flow (CBF) changes as a surrogate outcome of single session tDCS-induced effects on neuroplasticity in a schizophrenia patient with persistent auditory hallucinations. The observations are discussed in this case report.

The flow state is a subjective experience that most people can relate to. It represents an optimal balance between skills and difficulty and is the state that people often refer to when performing their best, with phrases like: “I was in the zone” or “I was in the bubble”. The flow state has mainly been studied through its psychological and behavioral components; it is not until lately the neuroscientific aspects have been investigated. This review attempts to go through the existing literature and find potential neural signatures of the flow state. The studies indicate that flow is related to activity in the dorsolateral prefrontal cortex and putamen, but the findings are too divided to reach a conclusion.

No description available.

The neurovisceral integration model (NVM) proposes that an organisms ability to flexibly adapt to their environment is related to biological flexibility within the central autonomic network. One important aspect of this flexibility is behavioral inhibition (Thayer and Friedman, 2002). During a behavioral inhibition task, the central autonomic network (CAN), which is comprised of a series of feedback loops, must be able to integrate information and react to these inputs flexibly to facilitate optimal performance. The functioning of the CAN is shown to be associated with respiratory sinus arrhythmia (RSA), as the vagus nerve is part of this feedback system. While the NVM has been examined through neural imaging and RSA, only a few studies have examined these measures simultaneously during the neuroimaging procedure. Furthermore, these studies were done at rest or used tasks that were not targeted at processes associated with the NVM, such as behavior inhibition and cognitive flexibility. For this reason, the present study assessed RSA and neural activation in the prefrontal cortex simultaneously while subjects completed a behavior inhibition task. Using a series of go/no-go tasks, RSA and functional near-infrared spectroscopy (fNIRS) were collected to investigate the relationship between prefrontal activation and vagal activity at rest and during behavioral inhibition. There are three primary aims of this study. First, examine prefrontal activation during various inhibition tasks through fNIRS. Second, evaluate the NVM during a cognitive task using simultaneous fNIRS and RSA analysis. Third, relate task performance, imaging, and RSA measures during behavioral inhibition to deficits in flexible everyday responding, as indicated by self-report measures of behavior. Doing so will elucidate the connection with prefrontal activation and RSA as proposed by the NVM model and determine whether neural and RSA metrics can be related to broader symptoms of inflexibility. / PHD / The neurovisceral integration model (NVM) proposes that the ability to adapt to the environment is related to biological flexibility within the brain. One important aspect of the ability to adapt to the environment is behavior inhibition (e.g., the ability to stop from engaging in a habitual response, Thayer & Friedman, 2002). During a behavior inhibition task, the brain must be able to integrate information and react to these inputs flexibly to facilitate optimal performance. The brain’s ability to do this is related to a measure of heart activity known as respiratory sinus arrhythmia (RSA). The present study assessed RSA and brain activity while subjects completed a behavior inhibition task. Neural activation was measured through functional near-infrared spectroscopy (fNIRS). fNIRS measures the amount of oxygenated blood in different areas of the brain. Greater concentrations of oxygenated blood indicated greater brain activity in an area. Through simultaneous fNIRS and RSA measurement the present study examined their relationship during various inhibition tasks. Doing so clarified the connection between brain activation and RSA as proposed by the NVM model.