Behavioral evidence has shown that older adults are less able to overcome proactive interference in memory than young adults. However, it is unclear what underlies this deficit. Imaging studies in the young suggest overcoming interference may require post-retrieval selection, a process thought to be mediated by the left mid-ventrolateral prefrontal cortex (VLPFC). Further, selection may resolve interference by enhancing or suppressing perceptual processing. The present fMRI study investigated whether age-related changes in VLPFC-mediated post-retrieval selection underlie older adults' deficits in overcoming interference in associative memory. Participants were tasked with remembering which associate (face or scene) objects were paired with most recently during study, under conditions of high or low proactive interference. Behavioral results demonstrated that as interference increased, memory performance decreased similarly across groups. Across groups, activity in the left mid-VLPFC also increased with interference. However, right PFC post-retrieval monitoring effects, but not left mid-VLPFC, distinguished successful vs. unsuccessful resolution of interference for both young and older adults, suggesting selection alone may be insufficient for successful resolution of interference. Age-related memory deficits may be related to reduced recruitment of relational processing effects in the dorsolateral and anterior PFC, as well as reduced memory retrieval effects in the hippocampus. Lastly, results showed evidence that selection may modulate perceptual processing of retrieved memory representations. Namely, activity in the parahippocampal place area (PPA) was greater when participants selected scene, versus face, regardless of accuracy. Further, older adults showed reduced effects in the PPA, possibly reflecting reduced differentiation of perceptual processing. Taken together, these results suggest age-related deficits in overcoming proactive interference are not related to post-retrieval selection, but reduced recruitment of PFC-mediated relational processes, coupled with reduced associative memory retrieval.

The nature of visual properties used for object perception in mid- and high-level vision areas of the brain is poorly understood. Past studies have employed simplistic stimuli probing models limited in descriptive power and mathematical under-pinnings. Unfortunately, pursuit of more complex stimuli and properties requires searching through a wide, unknown space of models and of images. The difficulty of this pursuit is exacerbated in brain research by the limited number of stimulus responses that can be collected for a given human subject over the course of an experiment. To more quickly identify complex visual features underlying cortical object perception, I develop, test, and use a novel method in which stimuli for use in the ongoing study are selected in realtime based on fMRI-measured cortical responses to recently-selected and displayed stimuli. A variation of the simplex method controls this ongoing selection as part of a search in visual space for images producing maximal activity — measured in realtime — in a pre-determined 1 cm3 brain region. I probe cortical selectivities during this search using photographs of real-world objects and synthetic “Fribble” objects. Real-world objects are used to understand perception of naturally-occurring visual properties. These objects are characterized based on feature descriptors computed from the scale invariant feature transform (SIFT), a popular computer vision method that is well established in its utility for aiding in computer object recognition and that I recently found to account for intermediate-level representations in the visual object processing pathway in the brain. Fribble objects are used to study object perception in an arena in which visual properties are well defined a priori. They are constructed from multiple well-defined shapes, and variation of each of these component shapes produces a clear space of visual stimuli. I study the behavior of my novel realtime fMRI search method, to assess its value in the investigation of cortical visual perception, and I study the complex visual properties my method identifies as highly-activating selected brain regions in the visual object processing pathway. While there remain further technical and biological challenges to overcome, my method uncovers reliable and interesting cortical properties for most subjects — though only for selected searches performed for each subject. I identify brain regions selective for holistic and component object shapes and for varying surface properties, providing examples of more precise selectivities within classes of visual properties previously associated with cortical object representation. I also find examples of “surround suppression,” in which cortical activity is inhibited upon viewing stimuli slightly deviation from the visual properties preferred by a brain region, expanding on similar observations at lower levels of vision.

<p>Few aspects of human cognition are more personal than the choices we make. Our decisions &mdash; from the mundane to the impossibly complex &mdash; continually shape the courses of our lives. In recent years, researchers have applied the tools of neuroscience to understand the mechanisms that underlie decision making, as part of the new discipline of decision neuroscience. A primary goal of this emerging field has been to identify the processes that underlie specific decision variables, including the value of rewards, the uncertainty associated with particular outcomes, and the consequences of social interactions. Here, across three independent studies, I focus on the neural circuitry supporting social valuation &mdash; which shapes our social interactions and interpersonal choices. In the first study (Chapter 2), I demonstrate that social valuation relies on the posterior ventromedial prefrontal cortex (pVMPFC). Extending these findings, I next show that idiosyncratic responses within pVMPFC predict individual differences in complex social decision scenarios (Chapter 3). In addition, I also demonstrate that decisions involving other people (e.g., donations to a charitable organization) produce increased activation in brain regions associated with social cognition, particularly the temporal-parietal junction (TPJ). Finally, in my last study (Chapter 4), I employ functional connectivity analyses and show that social cognition regions &mdash; including the TPJ &mdash; exhibit increased connectivity with pVMPFC during social valuation, an effect that depends upon individual differences in preferences for social stimuli. Collectively, these results demonstrate that the computation of social value relies on distributed neural circuitry, including both value regions and social cognition regions. Future research on social valuation and interpersonal choice must build upon this emerging theme by linking neural circuits and behavior.</p> / Dissertation

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Neuroscientists have long known that brain function is inherently variable. Functional magnetic resonance imaging (fMRI) research often attributes blood oxygen level-dependent (BOLD) signal variance to measurement-related confounds. However, what is typically considered “noise” variance in data may be a vital feature of brain function that reflects development, cognitive adaptability, flexibility, and performance. In the present thesis, we examine how brain signal variability (measured with a modified BOLD time series standard deviation (SDBOLD)) relates to human aging and cognitive performance in a series of studies. In Study 1, we examined brain variability during fixation baseline periods. We found that not only was the SDBOLD pattern robust, its unique age-predictive power was more than five times that of meanBOLD (a common measure of BOLD activity), yet revealed a spatial pattern virtually orthogonal to meanBOLD. Contrary to typical conceptions of age-related neural noise, young adults exhibited greater brain variability overall. In Study 2, we found that younger, faster, and more consistent performers exhibited significantly higher brain variability across three cognitive tasks, and showed greater variability-based regional differentiation compared to older, poorer performing adults. SDBOLD and meanBOLD spatial patterns were again orthogonal across brain measures. Study 3 demonstrated experimental condition-based modulations in SDBOLD. SDBOLD was an effective discriminator between internal (lower variability) and external (higher variability) cognitive demands, particularly in younger, high performing adults. Finally, to gauge the extent that brain variability can be incrementally manipulated within a single cognitive domain, Study 4 examined parametric modulations in SDBOLD on a face processing task in a young-only sample. Results indicated that SDBOLD can be robustly manipulated through experimental control, and that this manipulation linearly follows performance trends across conditions. These studies help establish the age- and performance-relevance of BOLD variability. We thus argue that the precise nature of relations between aging, cognition, and brain function is incompletely characterized by using mean-based brain measures exclusively.

There is a paucity of research examining the neurobiological functioning of new mothers who have experienced parental loss during development. The current study investigated the relationship between inconsistent (IC) versus consistent (CC) care and brain activity in regions that comprise a putative neurobiological model of mothering. Mothers were shown positive and negative pictures of their own and an unfamiliar infant. Through repeated measures ANOVAs, it was found that BOLD activity was greater for own infant in the nucleus accumbens (NAC) and amygdala (AMY) and that positive pictures elicited greater BOLD response in the NAC, AMY and anterior cingulate cortex. Interestingly, IC mothers show an even greater response own infant in the NAC and left hypothalamus (HYPO). In the left dorsolateral prefrontal cortex, IC mothers showed greater BOLD response to other infant. Thus, functioning of the maternal circuit, which includes areas strongly implicated in reward, may be altered by early experiences.

Neuroscientists have long known that brain function is inherently variable. Functional magnetic resonance imaging (fMRI) research often attributes blood oxygen level-dependent (BOLD) signal variance to measurement-related confounds. However, what is typically considered “noise” variance in data may be a vital feature of brain function that reflects development, cognitive adaptability, flexibility, and performance. In the present thesis, we examine how brain signal variability (measured with a modified BOLD time series standard deviation (SDBOLD)) relates to human aging and cognitive performance in a series of studies. In Study 1, we examined brain variability during fixation baseline periods. We found that not only was the SDBOLD pattern robust, its unique age-predictive power was more than five times that of meanBOLD (a common measure of BOLD activity), yet revealed a spatial pattern virtually orthogonal to meanBOLD. Contrary to typical conceptions of age-related neural noise, young adults exhibited greater brain variability overall. In Study 2, we found that younger, faster, and more consistent performers exhibited significantly higher brain variability across three cognitive tasks, and showed greater variability-based regional differentiation compared to older, poorer performing adults. SDBOLD and meanBOLD spatial patterns were again orthogonal across brain measures. Study 3 demonstrated experimental condition-based modulations in SDBOLD. SDBOLD was an effective discriminator between internal (lower variability) and external (higher variability) cognitive demands, particularly in younger, high performing adults. Finally, to gauge the extent that brain variability can be incrementally manipulated within a single cognitive domain, Study 4 examined parametric modulations in SDBOLD on a face processing task in a young-only sample. Results indicated that SDBOLD can be robustly manipulated through experimental control, and that this manipulation linearly follows performance trends across conditions. These studies help establish the age- and performance-relevance of BOLD variability. We thus argue that the precise nature of relations between aging, cognition, and brain function is incompletely characterized by using mean-based brain measures exclusively.

There is a paucity of research examining the neurobiological functioning of new mothers who have experienced parental loss during development. The current study investigated the relationship between inconsistent (IC) versus consistent (CC) care and brain activity in regions that comprise a putative neurobiological model of mothering. Mothers were shown positive and negative pictures of their own and an unfamiliar infant. Through repeated measures ANOVAs, it was found that BOLD activity was greater for own infant in the nucleus accumbens (NAC) and amygdala (AMY) and that positive pictures elicited greater BOLD response in the NAC, AMY and anterior cingulate cortex. Interestingly, IC mothers show an even greater response own infant in the NAC and left hypothalamus (HYPO). In the left dorsolateral prefrontal cortex, IC mothers showed greater BOLD response to other infant. Thus, functioning of the maternal circuit, which includes areas strongly implicated in reward, may be altered by early experiences.

The feasibility of using real-time functional magnetic resonance imaging (fMRI) feedback regarding the level of activation in rostromedial prefrontal cortex (rMPFC) to learn improved regulation of this brain area was examined in a group of 5 young adults. Subjects received real-time feedback from the target brain region while engaging in a blocked-design task involving alternating blocks of attempted up-regulation and down-regulation of the target brain region. A transient negative emotional state was induced prior to each scanning session. Subjects completed 6 scanning sessions (a pre-training session, 4 feedback sessions and a post-training session - no feedback was provided for pre and post-training sessions). The guideline strategy provided to subjects of engaging in emotional awareness during up-regulation and bodily awareness during down-regulation was found to consistently regulate the region in the pre-training session prior to the fMRI feedback sessions. This finding is in line with the previously proposed role of the rMPFC in emotional awareness. In contrast to previous real-time fMRI findings, greater recruitment of the region was observed in the pre-training session compared to the post-training session, with a non-significant negative trend observed across feedback sessions. These results suggest that there may be limitations to which the feedback techniques successfully employed for other brain regions extend to yet unexplored brain regions.

Posttraumatic Stress Disorder (PTSD) is an anxiety disorder characterised by disturbed arousal, altered attention, and fear processing, and a reduction in the ability to perform cognitive tasks. Predominant neurophysiological models of PTSD have been focused on alterations in fear-related regulation, and few incorporate broader changes in generic executive control which may underlie many of the clinical symptoms and cognitive deficits in PTSD. This thesis aimed to investigate the neurophysiology of executive inhibitory control in PTSD using a Go/NoGo response inhibition task and converging functional imaging, structural imaging and electrophysiological measures. The first series of studies aimed to elucidate a normative neural network model of inhibitory control, and are consistent with normative control involving the activation of a mainly right-lateralised ventral lateral prefrontal cortex (VLPFC) network. Inhibitory control-related activation was found to be affected by levels of anxiety and changes in underlying neural structure; alterations in frontal cortical maturation and volume were related to additional activation of bilateral frontal cortical regions and the dorsal striatum, with anxiety increasing the demand on inhibitory control-related activation. In contrast to healthy participants, PTSD was associated with reduced inhibitory control as indexed by inhibitory behaviour, diminished activation of the right VLPFC, and slowed inhibition-related information processsing. PTSD participants relied on the greater activation of a left fronto-striatal inhibition network to support control, with the activation affected by levels of PTSD severity and comorbid anxiety. This left fronto-striatal activation in PTSD was related to underlying increases in fronto-striatal neural structure. Further, the ability to efficiently engage a left fronto-striatal network in PTSD during inhibitory control predicted better response to cognitive behavior for PTSD, consistent with the proposal that an improved ability to flexibly engage control systems may facilitate the resolution of PTSD symptoms. Taken together, this program of research extends current neurophysiological model of PTSD to show that PTSD involves a fundamental disturbance in the function and structure of key fronto-striatal response control networks associated with inhibitory control.