Complexity-modulated tasks elicit differential hemodynamic activations in the primary motor cortex for upper limb motor representations. However, much is yet to be learned regarding lower limb complexity modulation, as most fNIRS complexity modulation studies focus on the upper limb. It is currently unknown whether hemodynamic activations from single-joint lower limb motor tasks are detectable by fNIRS, and further, if fNIRS can detect differences between activations from simple and complex lower limb motor tasks. An fNIRS study was conducted to investigate the effects of an unpredictable, complex force-tracking task vs. a predictable, simple force-tracking task on hemodynamic activations in the TA motor representation. No significant TA motor cortex activations were found for 4/5 participants, with one participant showing a significant activation in one channel. Lack of activation in the TA motor representation was attributed to the depth of the area within the central sulcus. Significant hemodynamic activations were also found in areas assumed to overly STG/SII, and pre-SMA/SMA. These activations were attributed to sensory integration and motor learning, respectively. An fNIRS processing review was also conducted to inform processing decisions in the first experiment and to further fNIRS usage in our lab. Common techniques were identified as low-pass, band-pass, and high-pass filters, smoothing filters, wavelet filters, and the GLM. More appropriate alternative techniques were provided, including short-separation regression, pre-whitening, and spline interpolation with a Savitsky-Golay filter. Future studies may elucidate the lack of activity in the TA motor representation, and will further basic neuroscience regarding fNIRS. / Thesis / Master of Science in Kinesiology

This research explores the application of neuro-cognitive feedback in enhancing the ideation phase of engineering design. Brainstorming is identified as a dominant method for ideation, relying on cognitive processes linked to memory. Neuro-cognitive feedback is introduced as a technique to maintain high cognitive responses during ideation by providing information about brain states, aiding in semantic processing and attention. The study employs functional near-infrared spectroscopy (fNIRS) for neuro-cognitive feedback (NF), showing its advantages in spatial and temporal resolution, mobility, and cost over EEG and fMRI. This feedback method involves placing sensors in a headband on the forehead to measure cortical activity and provide real-time feedback to participants. The technique has been validated in various fields, including medicine, sports, and the arts, for enhancing cognitive and creative performance. A key focus of the research is on the effects of neuro-cognitive feedback on ideation and brain behavior. The research method involved recruiting engineering graduate students, employing various design tasks, and using fNIRS for data collection and analysis. It reveals differences in brain behavior between the baseline and neuro-cognitive feedback sessions, particularly in the right dorsolateral prefrontal cortex (DLPFC), which is associated with generating new ideas. Multiple neurofeedback sessions showed performance improvements in engineering design tasks, with changes in task-related oxygenation in the prefrontal cortex. The study concludes that neuro-cognitive feedback enhances ideation by providing a sustained high cognitive response, aiding in self-regulatory control of brain activity, and improving performance in various cognitive tasks. The results indicate significant improvements in ideation fluency and time spent on tasks with neurofeedback, suggesting its effectiveness in enhancing cognitive functions in engineering design. / Master of Science / This study investigates how neuro-cognitive feedback can improve the brainstorming phase of engineering design. Brainstorming, a method in design ideation, provides concrete quantitative results to compare idea production. The research evaluates neuro-cognitive feedback to boost cognitive activity during brainstorming by monitoring brain states to assist in understanding and attention. It utilizes a technology called functional near-infrared spectroscopy (fNIRS) for this purpose. This technique, which has proven benefits in fields such as athletics and the arts, involves a headband with sensors that measure brain activity and provide immediate feedback. The research focused on civil engineering graduate students, using various design tasks and fNIRS for data gathering and analysis. It found that neuro-cognitive feedback impacts a brain area that contributes to the creation of new ideas and the cohort saw improved performance in engineering tasks. The results highlight that the multiple interventions help manage brain activity and improve task performance. The findings suggest that this method significantly boosts the efficiency and duration of brainstorming sessions in engineering design, showing its potential to enhance cognitive skills.

This study assessed whether data collected while a participant was intentionally moving is of the same quality as data collected from a motionless participant via fNIRS (functional near-infrared spectroscopy). This study was a within-subjects design with 3 head-movement conditions (no head-movement, low head-movement, and high head-movement). Data was recorded via the fNIRS system as well as an app called VibSensor, which recorded head movement on the X, Y, and Z planes. Results for the behavioral data indicated significance only on the Y plane across the no and high movement conditions and one significant channel for the fNIRS data.

The present study is a novel investigation of neural mechanisms underlying reading development in bilingual children compared to monolinguals. We asked how do bilingual children learn to read when faced with phonological processing across two languages? Both behavioral measures and functional Near Infrared Spectroscopy (fNIRS) were used to observe any similarities or differences in brain activity between bilingual and monolingual readers. The behavioral findings corroborate a bilingual reading advantage; bilinguals were faster and more accurate than monolinguals when reading words. fNIRS data showed bilinguals demonstrated greater activation in classic language areas as compared to monolinguals. Taken together, this research advances contemporary scientific controversy concerning types of processing underlying reading and its maturational development over time. Ultimately, this research may have translational significance in education to situate normative developmental reading milestones in bilingual children, which is vitally important in developing effective therapies for bilingual children at risk for reading disorders.

The present study is a novel investigation of neural mechanisms underlying reading development in bilingual children compared to monolinguals. We asked how do bilingual children learn to read when faced with phonological processing across two languages? Both behavioral measures and functional Near Infrared Spectroscopy (fNIRS) were used to observe any similarities or differences in brain activity between bilingual and monolingual readers. The behavioral findings corroborate a bilingual reading advantage; bilinguals were faster and more accurate than monolinguals when reading words. fNIRS data showed bilinguals demonstrated greater activation in classic language areas as compared to monolinguals. Taken together, this research advances contemporary scientific controversy concerning types of processing underlying reading and its maturational development over time. Ultimately, this research may have translational significance in education to situate normative developmental reading milestones in bilingual children, which is vitally important in developing effective therapies for bilingual children at risk for reading disorders.

There has been extensive research investigating the differences between global and local feature discrimination. The role that global and local feature discrimination has in sustained attention tasks however has been relatively neglected. In the current research, participants were required to perform a sustained attention task requiring them to engage in either global or local shape stimuli discrimination. Reaction times to local feature discrimination revealed a quadratic trend with time-on-task, with performance levels showing a decline before returning to initial levels towards the end of the task. This trend was not found in the global shape discrimination condition. Functional near-infrared spectroscopy (fNIRS) was employed to assess hemispheric cerebral oxygenation during the tasks. It was found in both conditions that there was greater oxygenation in the right hemisphere compared to the left hemisphere. It was also found that right hemisphere oxygenation increased with time-on-task. Left hemisphere oxygenation decreased during the global task, while it increased during the local task with time on task. Total cerebral oxygenation, collapsed over both hemispheres, increased more over time in the local discrimination task than the global discrimination task. The performance data and the fNIRS results suggest an increased utilization of bilateral cognitive resources with time-on-task in the local discrimination condition, but not in the global discrimination condition. Results and implications are discussed.

Introduction: The prefrontal cortex (PFC) is highly susceptible to age-related deterioration. As such, executive function deficits are commonly observed when older adults process two attention-demanding tasks simultaneously. Everyday tasks such as walking and talking on the phone involve executive functions and the integration of cognitive-motor pathways. However, less is known about this relationship as cognitive demands increase. Methods: Twenty healthy older adults (M = 71.8 years, SD = 6.4) performed four auditory cognitive tasks of increasing demand, including a simple reaction time (SRT), go/no-go (GNG), n-back (NBK), and double number sequence (DNS) task with or without self-paced walking (i.e., single- versus dual-task). Using a blocked design, prefrontal hemodynamic changes (i.e., oxy- [∆HbO2] and deoxyhemoglobin [∆HbR]) were measured using functional near-infrared spectroscopy (fNIRS) and performance was assessed using measures of response time (s), accuracy (% correct) and gait speed (m/s). Results: Prefrontal activation decreased between the single- and dual-tasks across all task demands. Behaviourally, the SRT response times were significantly faster than GNG and NBK. Accuracy decreased between single- and dual-tasks and with increasing demand, but the NBK and DNS tasks were not significantly different. An interaction between task and demand was observed for gait speed such that the DNS dual-task was significantly slower than the single-task. Conclusion: Neural findings support an automatic locomotor control strategy in that cerebral oxygenation decreased between single- and dual-tasks and gait speed was maintained up until the most demanding cognitive task. However, decreased prefrontal activation was inefficient at supporting response time and accuracy performance which may indicate that cognitive performance is differentially affected by cognitive demand and deficits in executive functioning.

In the past decade, the COVIS model (Ashby, Alfonso-Reese, Turken, & Waldron, 1998) has emerged as the only neuropsychological theory for the existence of multiple brain systems for category learning. COVIS postulates that there are two systems, explicit and implicit, which compete against one another. These two systems reply on two discrete networks: explicit, or rule based categorization relies on executive function and working memory while implicit, or information integration categorization is mediated by dopaminergic pathways. The purpose of this pilot study was to further provide evidence for the existence of multiple systems of category learning. In all three experiments, we interrupted feedback processing using a modified Sternberg task. In Experiment 1 and 2, participants were separated into four conditions, rule based (RB) categorization with a short delay between feedback and the modified Sternberg task, RB categorization with a long delay, information integration (II) categorization with a short delay, and II categorization with a long delay. Participants in the RB conditions performed worse than those in the II conditions in Experiment 1 and 2. After determining there was no significant difference between the short and long delay manipulations, only the short delay was used for Experiment 3. Consistent with Experiment 1 and 2, participants in the RB condition performed worse than those in the II condition. Functional near-infrared spectroscopy (fNIRS) technology was also used in Experiment 3 to determine the difference in prefrontal activation between RB and II conditions. Although statistically not significant, across blocks, the difference in prefrontal activation increased.

The conscious or unconscious acquirement of knowledge in implicit category learning was examined in accordance with predictions made by the COVIS theory of categorization (Ashby & Maddox, 2011). COVIS assumes separate category learning systems. The explicit system relies on easily verbalized rules while the implicit system requires integration of more than one stimulus dimension. Participants in this experiment categorized lines varying in length and orientation as belonging to one of two categories; in the rule-based (RB) condition only length was relevant, while participants in the information integration (II) condition needed to integrate both dimensions. Corrective feedback was provided during training. In test phases, participants were asked to attribute their responses to one of four criteria (guess, intuition, memory, or rule), a measure adapted from Dienes and Scott (2005). Neural activity in dorsolateral prefrontal cortex (DLPFC) was recorded with a 20-optode fNIRS system. We found that in the implicit (II) learning condition, participants who reported guessing less than half the time were learning but were unconscious to the structures driving that learning, reflected by accuracy, attribution self-report and neural activation. Our results substantiate the claim that implicit category learning is mediated unconsciously and evidence the dual-system model of categorization postulated by COVIS, furthering our understanding of category learning and thus, the ways in which to improve it.

Sequential movements have become a common experimental paradigm for evaluating the neural correlates of motor learning. Currently, the understanding is that motor sequence learning engages the cortico-cerebellar and cortico-striatal networks and that their contributions differ depending on the stage of learning. The prefrontal cortex (PFC), in particular, has been observed at the early/fast phase and late/slow phase of motor sequence learning, suggesting involvement in processes such as movement automaticity, stimulus-response conflicts, explicit learning, and retrieval, to name a few. However, it is difficult for neuroimaging studies to evaluate the relative permanence of motor sequence learning due to the financial burden associated with functional magnetic resonance imaging (fMRI) and positron emission tomography (PET). In this dissertation, four experiments were performed to examine the functionality of functional near-infrared spectroscopy (fNIRS) in elucidating the role of the PFC in motor sequence learning and movement automaticity. The first experiment (Chapter 2) focused on validating fNIRS as a comparable technique to fMRI by replicating a previous motor sequence learning study (Wu et al., 2004) that reported decreased activity in the left dorsolateral prefrontal cortex (DLPFC) following achievement of movement automaticity. The fNIRS findings were unable to detect a similar decrease in the left DLPFC. The second experiment (Chapter 3) further investigated the cerebral oxygenation changes in the PFC following motor sequence learning. To enable better distinction between learning and performance, this experiment including multiple motor sequence tasks, a control group, four practice sessions and a retention phase. The findings revealed increased contributions from the right hemisphere (e.g., right ventrolateral PFC (VLPFC)) and the suggestion that the left DLPFC may not reflect movement automaticity but rather attentional investment in movement preparation. To address the signal processing concerns observed in experiment one and two, the third experiment (Chapter 4) investigated the effect of five motion correction techniques on the statistical outcomes of a motor sequence learning experiment. Additionally, the corrections were evaluated to determine which would yield the greatest improvement in hemodynamic response function (HRF) recovery and within-subject standard deviation. The findings revealed the location of significance to vary depending on the motion correction applied. Also, wavelet and spline + wavelet demonstrated limited improvement in reducing within-subject standard deviation. Lastly, the fourth experiment (Chapter 5) examined changes in the PFC associated with dual-task processing before and after motor sequence learning. Findings revealed decreased activity in the right DLPFC, medial PFC (mPFC), and orbitofrontal cortex following practice for dual-task sequence-4. A similar but marginal trend was observed in the right VLPFC. Minimal significance was observed during the dual-task sequence-12 task. Collectively, the findings of this dissertation suggest that 1) motor sequence learning when acquired with explicit knowledge requires contribution from predominately the right hemisphere, 2) the left DLPFC may represent attentional investment in movement preparation rather than movement automaticity, 3) the neural representations of dual-task processing are associated with the complexity of the motor sequence task, and 4) low-frequency motion artifacts may be difficult to remove using certain signal processing methods.