Brain network mechanisms in learning behavior

The study of learning has been a central focus of psychology and neuroscience since their inception. Cognitive neuroscience’s traditional approach to understanding learn-ing has been to decompose it into discrete cognitive processes with separable and localized underlying neural systems. While this focus on modular cognitive functions for individual brain areas has led to considerable progress, there is increasing evidence that much of learn-ing behavior relies on overlapping cognitive and neural systems, which may be harder to disentangle than previously envisioned. This is not surprising, as the processes underlying learning must involve widespread integration of information from sensory, affective, and motor sources. The standard tools of cognitive neuroscience limit our ability to describe processes that rely on widespread coordination of brain activity. To understand learning, it will be necessary to characterize dynamic co-activation at the circuit level. In this dissertation, I present three studies that seek to describe the roles of distrib-uted brain networks in learning. I begin by giving an overview of our current understand-ing of multiple forms of learning, describing the neural and computational mechanisms thought to underlie incremental feedback-based learning and flexible episodic memory. I will focus in particular on the difficulties in separating these processes at the cognitive level and in localizing them to individual regions at the neural level. I will then describe recent findings that have begun to characterize the brain’s large-scale network structure, emphasiz-ing the potential roles that distributed networks could play in understanding learning and cognition more generally. I will end the introduction by reviewing current attempts to char-acterize the dynamics of large-scale brain networks, which will be essential for providing a mechanistic link to learning behavior. Chapter 2 is a study demonstrating that intrinsic connectivity between the hippo-campus and the ventromedial prefrontal cortex, as well as between these regions and dis-tributed brain networks, is related to individual differences in the transfer of learning on a sensory preconditioning task. The hippocampus and ventromedial prefrontal cortex have both been shown to be involved in this type of learning, and this study represents an early attempt to link connectivity between individual regions and broader networks to learning processes. Chapter 3 is a study that takes advantage of recent developments in mathematical modeling of temporal networks to demonstrate a relationship between large-scale network dynamics and reinforcement learning within individuals. This study shows that the flexibil-ity of network connectivity in the striatum is related to learning performance over time, as well as to individual differences in parameters estimated from computational models of re-inforcement learning. Notably, connectivity between the striatum and visual as well as or-bitofrontal regions increased over the course of the task, which is consistent with an inte-grative role for the region in learning value-based associations. Network flexibility in a dis-tinct set of regions is associated with episodic memory for object images presented during the learning task. Chapter 4 examines the role of dopamine, a neurotransmitter strongly linked to val-ue updating in reinforcement learning, in the dynamic network changes occurring during learning. Patients with Parkinson’s disease, who experience a loss of dopaminergic neu-rons in the substantia nigra, performed a reversal-learning task while undergoing functional magnetic resonance imaging. Patients were scanned on and off of a dopamine precursor medication (levodopa) in a within-subject design in order to examine the impact of dopa-mine on brain network dynamics during learning. The reversal provided an experimental manipulation of dynamic connectivity, and patients on medication showed greater modula-tion of striatal-cortical connectivity. Similar results were found in a number of regions re-ceiving midbrain projections including the prefrontal cortex and medial temporal lobe. This study indicates that dopamine inputs from the midbrain modulate large-scale network dy-namics during learning, providing a direct link between reinforcement learning theories of value updating and network neuroscience accounts of dynamic connectivity. Together, these results indicate that large-scale networks play a critical role in multi-ple forms of learning behavior. Each highlights the potential importance of understanding dynamic routing and integration of information across large-scale circuits for our concep-tion of learning and other cognitive processes. Understanding the when, where, and how of this information flow in the brain may provide an alternative or compliment to traditional theories of distinct learning systems. These studies also illustrate challenges in integrating this perspective with established theories in cognitive neuroscience. Chapter 5 will situate the studies in a broader discussion of how brain activity relates to cognition in general, while pointing out current roadblocks and potential ways forward for a cognitive network neuroscience of learning

Social Media and Marketing as a Means of Planning and Promoting the 2022 Camp PolyHacks Hackathon

The recruitment of attendees and promotion of Camp PolyHacks, an annual Hackathon hosted by Cal Poly, required marketing strategies which were informed by relevant communication theories applied to event marketing campaign strategies. The theories utilized included Social Marketing Theory (SMT), Uncertainty Reduction Theory (URT), Consistency Theory (CT), and elements of persuasion and visual communication. The marketing strategies used by the Camp PolyHacks 2022 Marketing and Social Media team included social media marketing in the form of Instagram posts, stories, and direct messages, and external marketing in the form of presentations, emails, booths, and posters. This paper examines the utility of these marketing strategies, how they were informed by communication theories, and why they are valuable for future applications. The evaluation of the marketing tactics used during the Camp PolyHacks recruitment period offers insight into best practices for recruiting 100 student participants to attend a community and university based event in San Luis Obispo. An appendix at the end of the paper will provide a sample of the tools and content that were used throughout the marketing process through social media and external marketing

Cause of Death and Predictors of All-Cause Mortality in Anticoagulated Patients With Nonvalvular Atrial Fibrillation : Data From ROCKET AF

M. Kaste on työryhmän ROCKET AF Steering Comm jäsen.Background-Atrial fibrillation is associated with higher mortality. Identification of causes of death and contemporary risk factors for all-cause mortality may guide interventions. Methods and Results-In the Rivaroxaban Once Daily Oral Direct Factor Xa Inhibition Compared with Vitamin K Antagonism for Prevention of Stroke and Embolism Trial in Atrial Fibrillation (ROCKET AF) study, patients with nonvalvular atrial fibrillation were randomized to rivaroxaban or dose-adjusted warfarin. Cox proportional hazards regression with backward elimination identified factors at randomization that were independently associated with all-cause mortality in the 14 171 participants in the intention-to-treat population. The median age was 73 years, and the mean CHADS(2) score was 3.5. Over 1.9 years of median follow-up, 1214 (8.6%) patients died. Kaplan-Meier mortality rates were 4.2% at 1 year and 8.9% at 2 years. The majority of classified deaths (1081) were cardiovascular (72%), whereas only 6% were nonhemorrhagic stroke or systemic embolism. No significant difference in all-cause mortality was observed between the rivaroxaban and warfarin arms (P=0.15). Heart failure (hazard ratio 1.51, 95% CI 1.33-1.70, P= 75 years (hazard ratio 1.69, 95% CI 1.51-1.90, P Conclusions-In a large population of patients anticoagulated for nonvalvular atrial fibrillation, approximate to 7 in 10 deaths were cardiovascular, whereasPeer reviewe

Striatal intrinsic reinforcement signals during recognition memory: relationship to response bias and dysregulation in schizophrenia

Ventral striatum (VS) is a critical brain region for reinforcement learning and motivation, and VS hypofunction is implicated in psychiatric disorders including schizophrenia. Providing rewards or performance feedback has been shown to activate VS. Intrinsically motivated subjects performing challenging cognitive tasks are likely to engage reinforcement circuitry even in the absence of external feedback or incentives. However, such intrinsic reinforcement responses have received little attention, have not been examined in relation to behavioral performance, and have not been evaluated for impairment in neuropsychiatric disorders such as schizophrenia. Here we used fMRI to examine a challenging “old” vs. “new” visual recognition task in healthy subjects and patients with schizophrenia. Targets were unique fractal stimuli previously presented as salient distractors in a visual oddball task, producing incidental memory encoding. Based on the prediction error theory of reinforcement learning, we hypothesized that correct target recognition would activate VS in controls, and that this activation would be greater in subjects with lower expectation of responding correctly as indexed by a more conservative response bias. We also predicted these effects would be reduced in patients with schizophrenia. Consistent with these predictions, controls activated VS and other reinforcement processing regions during correct recognition, with greater VS activation in those with a more conservative response bias. Patients did not show either effect, with significant group differences suggesting hyporesponsivity in patients to internally generated feedback. These findings highlight the importance of accounting for intrinsic motivation and reward when studying cognitive tasks, and add to growing evidence of reward circuit dysfunction in schizophrenia that may impact cognition and function

Development of a theory-informed implementation intervention to improve the triage, treatment and transfer of stroke patients in emergency departments using the Theoretical Domains Framework (TDF): The T3 Trial

Background: Theoretical frameworks and models based on behaviour change theories are increasingly used in the development of implementation interventions. Development of an implementation intervention is often based on the available evidence base and practical issues, i.e. feasibility and acceptability. The aim of this study was to describe the development of an implementation intervention for the T3 Trial (Triage, Treatment and Transfer of patients with stroke in emergency departments (EDs)) using theory to recommend behaviour change techniques (BCTs) and drawing on the research evidence base and practical issues of feasibility and acceptability. Methods: A stepped method for developing complex interventions based on theory, evidence and practical issues was adapted using the following steps: (1) Who needs to do what, differently? (2) Using a theoretical framework, which barriers and enablers need to be addressed? (3) Which intervention components (behaviour change techniques and mode(s) of delivery) could overcome the modifiable barriers and enhance the enablers? A researcher panel was convened to review the list of BCTs recommended for use and to identify the most feasible and acceptable techniques to adopt. Results: Seventy-six barriers were reported by hospital staff who attended the workshops (step 1: thirteen TDF domains likely to influence the implementation of the T3 Trial clinical intervention were identified by the researchers; step 2: the researcher panellists then selected one third of the BCTs recommended for use as appropriate for the clinical context of the ED and, using the enabler workshop data, devised enabling strategies for each of the selected BCTs; and step 3: the final implementation intervention consisted of 27 BCTs). Conclusions: The TDF was successfully applied in all steps of developing an implementation intervention for the T3 Trial clinical intervention. The use of researcher panel opinion was an essential part of the BCT selection process to incorporate both research evidence and expert judgment. It is recommended that this stepped approach (theory, evidence and practical issues of feasibility and acceptability) is used to develop highly reportable implementation interventions. The classifying of BCTs using recognised implementation intervention components will facilitate generalisability and sharing across different conditions and clinical settings

Memory integration in humans with hippocampal lesions

Adaptive behavior frequently depends on inference from past experience. Recent studies suggest that the underlying process of integrating related memories may depend on interaction between hippocampus and prefrontal cortex. Here, we investigated how hippocampal damage affects memory integration. Subjects with mediotemporal lesions and healthy controls learned a set of overlapping AB- and BC-associations (object-face- and face-object pairs) and were then tested for memory of these associations (“direct” trials) and of inferential AC-associations (“indirect” trials). The experiment consisted of four encoding/retrieval cycles. In direct trials, performance of patients and controls was similar and stable across cycles. By contrast, in indirect trials, patients and controls showed distinct patterns of behavior. Whereas patients and controls initially showed only minor differences, controls increased performance across subsequent cycles, while patient performance decreased to chance level. Further analysis suggested that this deficit was not merely a consequence of impaired associative memory but rather resulted from an additional hippocampal contribution to memory integration. Our findings further suggest that contextual factors modulate this contribution. Patient deficits in more complex memory-guided behavior may depend on the flexible interaction of hippocampus-dependent and -independent mechanisms of memory integration

Coalition-building for labor actions in life sciences departments: lessons from the largest academic strike in history

Abstract: In life sciences graduate programs in the United States, efforts are underway to address barriers to academic success—namely, using interventions targeted at addressing inclusivity and diversity concerns. However, graduate students are typically simultaneously workers for their institutions, where they face workplace challenges such as low wages, inadequate benefits, and vulnerability to harassment and abuse. These challenges may disproportionately affect workers with excluded identities and are thereby barriers to diversity and equity. In recent years, graduate student unionization has expanded. The outcomes of these movements may improve pay, benefits, and working conditions for graduate workers; however, labor organizing presents numerous challenges in academic environments. We reflect on our experiences in a life sciences department at the University of California, Santa Cruz, in 2022 during the largest graduate labor strike to date. We summarize the challenges and discuss successful interventions, including communication strategies for cross-stage coalition building at the departmental level

Mechanisms of sporadic cerebral small vessel disease:insights from neuroimaging

The term “cerebral small vessel disease” (SVD) describes a range of neuroimaging, pathological and associated clinical features. The latter range from none, to discrete focal neurological symptoms (stroke), to insidious global neurological dysfunction and dementia. The public health burden is considerable. The pathogenesis is largely unknown. Although associated with vascular risk factors, and generally considered to result from an intrinsic cerebral arteriolar occlusive disease, the pathological processes leading to the arteriolar disease, how these result in brain disease, how SVD lesions contribute to neurological or cognitive symptoms and the relationship to risk factors, have been the subject of much speculation. Pathology often reflects end-stage disease making determination of the earliest stages difficult. Neuroimaging provides considerable insights: the small vessels are not easily seen themselves, but the effects of their malfunction on the brain can be tracked on detailed brain imaging. We review the growing evidence for the most likely mechanisms