Functional Organization of the Human Brain: How We See, Feel, and Decide.

The human brain is responsible for constructing how we perceive, think, and act in the world around us. The organization of these functions is intricately distributed throughout the brain. Here, I discuss how functional magnetic resonance imaging (fMRI) was employed to understand three broad questions: how do we see, feel, and decide? First, high-resolution fMRI was used to measure the polar angle representation of saccadic eye movements in the superior colliculus. We found that eye movements along the superior-inferior visual field are mapped across the medial-lateral anatomy of a subcortical midbrain structure, the superior colliculus (SC). This result is consistent with the topography in monkey SC. Second, we measured the empathic responses of the brain as people watched a hand get painfully stabbed with a needle. We found that if the hand was labeled as belonging to the same religion as the observer, the empathic neural response was heightened, creating a strong ingroup bias that could not be readily manipulated. Third, we measured brain activity in individuals as they made free decisions (i.e., choosing randomly which of two buttons to press) and found the activity within fronto-thalamic networks to be significantly decreased compared to being instructed (forced) to press a particular button. I also summarize findings from several other projects ranging from addiction therapies to decoding visual imagination to how corporations are represented as people. Together, these approaches illustrate how functional neuroimaging can be used to understand the organization of the human brain

Functional Organization of the Human Brain: How We See, Feel, and Decide.

The human brain is responsible for constructing how we perceive, think, and act in the world around us. The organization of these functions is intricately distributed throughout the brain. Here, I discuss how functional magnetic resonance imaging (fMRI) was employed to understand three broad questions: how do we see, feel, and decide? First, high-resolution fMRI was used to measure the polar angle representation of saccadic eye movements in the superior colliculus. We found that eye movements along the superior-inferior visual field are mapped across the medial-lateral anatomy of a subcortical midbrain structure, the superior colliculus (SC). This result is consistent with the topography in monkey SC. Second, we measured the empathic responses of the brain as people watched a hand get painfully stabbed with a needle. We found that if the hand was labeled as belonging to the same religion as the observer, the empathic neural response was heightened, creating a strong ingroup bias that could not be readily manipulated. Third, we measured brain activity in individuals as they made free decisions (i.e., choosing randomly which of two buttons to press) and found the activity within fronto-thalamic networks to be significantly decreased compared to being instructed (forced) to press a particular button. I also summarize findings from several other projects ranging from addiction therapies to decoding visual imagination to how corporations are represented as people. Together, these approaches illustrate how functional neuroimaging can be used to understand the organization of the human brain

Combination anti-Aβ treatment maximizes cognitive recovery and rebalances mTOR signaling in APP mice

Drug development for Alzheimer\u27s disease has endeavored to lower amyloid β (Aβ) by either blocking production or promoting clearance. The benefit of combining these approaches has been examined in mouse models and shown to improve pathological measures of disease over single treatment; however, the impact on cellular and cognitive functions affected by Aβ has not been tested. We used a controllable APP transgenic mouse model to test whether combining genetic suppression of Aβ production with passive anti-Aβ immunization improved functional outcomes over either treatment alone. Compared with behavior before treatment, arresting further Aβ production (but not passive immunization) was sufficient to stop further decline in spatial learning, working memory, and associative memory, whereas combination treatment reversed each of these impairments. Cognitive improvement coincided with resolution of neuritic dystrophy, restoration of synaptic density surrounding deposits, and reduction of hyperactive mammalian target of rapamycin signaling. Computational modeling corroborated by in vivo microdialysis pointed to the reduction of soluble/exchangeable Aβ as the primary driver of cognitive recovery

Genetic modulation of soluble Aβ rescues cognitive and synaptic impairment in a mouse model of Alzheimer\u27s disease

An unresolved debate in Alzheimer's disease (AD) is whether amyloid plaques are pathogenic, causing overt physical disruption of neural circuits, or protective, sequestering soluble forms of amyloid-β (Aβ) that initiate synaptic damage and cognitive decline. Few animal models of AD have been capable of isolating the relative contribution made by soluble and insoluble forms of Aβ to the behavioral symptoms and biochemical consequences of the disease. Here we use a controllable transgenic mouse model expressing a mutant form of amyloid precursor protein (APP) to distinguish the impact of soluble Aβ from that of deposited amyloid on cognitive function and synaptic structure. Rapid inhibition of transgenic APP modulated the production of Aβ without affecting pre-existing amyloid deposits and restored cognitive performance to the level of healthy controls in Morris water maze, radial arm water maze, and fear conditioning. Selective reduction of Aβ with a γ-secretase inhibitor provided similar improvement, suggesting that transgene suppression restored cognition, at least in part by lowering Aβ. Cognitive improvement coincided with reduced levels of synaptotoxic Aβ oligomers, greater synaptic density surrounding amyloid plaques, and increased expression of presynaptic and postsynaptic markers. Together these findings indicate that transient Aβ species underlie much of the cognitive and synaptic deficits observed in this model and demonstrate that significant functional and structural recovery can be attained without removing deposited amyloid

Genetic suppression of transgenic APP rescues hypersynchronous network activity in a mouse model of alzeimer\u27s disease

Alzheimer's disease (AD) is associated with an elevated risk for seizures that may be fundamentally connected to cognitive dysfunction. Supporting this link, many mouse models for AD exhibit abnormal electroencephalogram (EEG) activity in addition to the expected neuropathology and cognitive deficits. Here, we used a controllable transgenic system to investigate how network changes develop and are maintained in a model characterized by amyloid β (Aβ) overproduction and progressive amyloid pathology. EEG recordings in tet-off mice overexpressing amyloid precursor protein (APP) from birth display frequent sharp wave discharges (SWDs). Unexpectedly, we found that withholding APP overexpression until adulthood substantially delayed the appearance of epileptiform activity. Together, these findings suggest that juvenile APP overexpression altered cortical development to favor synchronized firing. Regardless of the age at which EEG abnormalities appeared, the phenotype was dependent on continued APP overexpression and abated over several weeks once transgene expression was suppressed. Abnormal EEG discharges were independent of plaque load and could be extinguished without altering deposited amyloid. Selective reduction of Aβ with a γ-secretase inhibitor has no effect on the frequency of SWDs, indicating that another APP fragment or the full-length protein was likely responsible for maintaining EEG abnormalities. Moreover, transgene suppression normalized the ratio of excitatory to inhibitory innervation in the cortex, whereas secretase inhibition did not. Our results suggest that APP overexpression, and not Aβ overproduction, is responsible for EEG abnormalities in our transgenic mice and can be rescued independently of pathology

Online Search Behavior for Cancer Immunotherapy Resources and Readability Analysis: An Opportunity to Aid in Medical Decision-making

Cancer patients are faced with increasing options for cancer care, especially with the introduction of cancer immunotherapy with immune checkpoint inhibitors (ICIs). Though many patients turn to online resources to supplement their decision-making, it is unknown whether online resources in cancer immunotherapy with ICIs are written at an appropriate level of readability according to national medical organizations. We performed a cross-sectional analysis of internet search behavior for cancer immunotherapy by ICIs and clinical trial availability per ClinicalTrials.gov in the United States (US) from 2004 - 2018 with subsequent quantitation of readability by four readability formulas of top 50 online resources. Internet search behavior for "cancer immunotherapy" has steadily increased since 2013 and coincides with the year of the US Food and Drug Administration (FDA) approval for individual ICIs. Furthermore, internet search behavior was significantly correlated with clinical trial availability in the US (R = 0.97, p < 0.0001). None of the top 50 resources available to patients were found to be within the recommended level of sixth-grade readability or less with only one (2%) written at the middle school level, 21 (42%) at the high school level, 23 (46%) at the university level, and five (8%) at a graduate level. Population-level internet search patterns may reflect patient behavior in seeking relevant online health information and may be influenced by new options for cancer therapy, including via clinical trials. However, low readability of available online resources may impede patient comprehension and negatively affect medical decision-making

Empathic Neural Responses Predict Group Allegiance.

Watching another person in pain activates brain areas involved in the sensation of our own pain. Importantly, this neural mirroring is not constant; rather, it is modulated by our beliefs about their intentions, circumstances, and group allegiances. We investigated if the neural empathic response is modulated by minimally-differentiating information (e.g., a simple text label indicating another's religious belief), and if neural activity changes predict ingroups and outgroups across independent paradigms. We found that the empathic response was larger when participants viewed a painful event occurring to a hand labeled with their own religion (ingroup) than to a hand labeled with a different religion (outgroup). Counterintuitively, the magnitude of this bias correlated positively with the magnitude of participants' self-reported empathy. A multivariate classifier, using mean activity in empathy-related brain regions as features, discriminated ingroup from outgroup with 72% accuracy; the classifier's confidence correlated with belief certainty. This classifier generalized successfully to validation experiments in which the ingroup condition was based on an arbitrary group assignment. Empathy networks thus allow for the classification of long-held, newly-modified and arbitrarily-formed ingroups and outgroups. This is the first report of a single machine learning model on neural activation that generalizes to multiple representations of ingroup and outgroup. The current findings may prove useful as an objective diagnostic tool to measure the magnitude of one's group affiliations, and the effectiveness of interventions to reduce ingroup biases

Data_Sheet_1_Empathic Neural Responses Predict Group Allegiance.pdf

<p>Watching another person in pain activates brain areas involved in the sensation of our own pain. Importantly, this neural mirroring is not constant; rather, it is modulated by our beliefs about their intentions, circumstances, and group allegiances. We investigated if the neural empathic response is modulated by minimally-differentiating information (e.g., a simple text label indicating another's religious belief), and if neural activity changes predict ingroups and outgroups across independent paradigms. We found that the empathic response was larger when participants viewed a painful event occurring to a hand labeled with their own religion (ingroup) than to a hand labeled with a different religion (outgroup). Counterintuitively, the magnitude of this bias correlated positively with the magnitude of participants' self-reported empathy. A multivariate classifier, using mean activity in empathy-related brain regions as features, discriminated ingroup from outgroup with 72% accuracy; the classifier's confidence correlated with belief certainty. This classifier generalized successfully to validation experiments in which the ingroup condition was based on an arbitrary group assignment. Empathy networks thus allow for the classification of long-held, newly-modified and arbitrarily-formed ingroups and outgroups. This is the first report of a single machine learning model on neural activation that generalizes to multiple representations of ingroup and outgroup. The current findings may prove useful as an objective diagnostic tool to measure the magnitude of one's group affiliations, and the effectiveness of interventions to reduce ingroup biases.</p