Faculty Bibliography

Emerging evidence suggests that olfactory function is closely linked to memory function. The aims of this study were to assess whether olfactory and episodic memory functions follow similar age-related decline trajectories, to identify different patterns of decline, as well as predictors of the patterns. 1023 participants from the Memory and Aging Project were followed for up to 8 years with annual episodic memory and odor identification assessments. Trajectories were modelled using growth mixture models. Multivariate logistic regression was used to identify pattern predictors. Three patterns of joint trajectories were identified; Class 1- stable average performance in both functions (n=690, 67.4%); Class 2- stable average episodic memory and declining odor identification (n=231, 22.6%); and Class 3- decline in both functions (n= 102, 10.0%). Class predictors included age, sex, APOE ε4 status, cognitive activity level and BMI. Participants in Class 3 were most likely to develop dementia. Episodic memory and olfactory function show similar trajectories in aging. Such classification can contribute to a better understanding of the factors related to cognitive decline and dementia.

Down syndrome (DS) is a genetic disorder caused by the triplication of human chromosome 21, which results in neurological and physiological pathologies. These deficits increase during aging and are exacerbated by cognitive decline and increase of Alzheimer's disease (AD) neuropathology. A nontoxic, noninvasive treatment, maternal choline supplementation (MCS) attenuates cognitive decline in mouse models of DS and AD. To evaluate potential underlying mechanisms, laser capture microdissection of individual neuronal populations of MCS offspring was performed, followed by RNA sequencing and bioinformatic inquiry. Results at ~6 months of age (MO) revealed DS mice (the well-established Ts65Dn model) have significant dysregulation of select genes within the Type 2 Diabetes Mellitus (T2DM) signaling pathway relative to normal disomic (2N) littermates. Accordingly, we interrogated key T2DM protein hormones by ELISA assay in addition to gene and encoded protein levels in the brain. We found dysregulation of adiponectin (APN) protein levels in the frontal cortex of ~6 MO trisomic mice, which was attenuated by MCS. APN receptors also displayed expression level changes in response to MCS. APN is a potential biomarker for AD pathology and may be relevant in DS. We posit that changes in APN signaling may be an early marker of cognitive decline and neurodegeneration.

LAY ABSTRACT/UNASSIGNED:. They also underscore the need to assess multiple sources of information for increased accuracy.

One pathway by which environments of socioeconomic risk are thought to affect cognitive development is through stress physiology. The biological systems underpinning stress and attention undergo a sensitive period of development during infancy. Psychobiological theory emphasizes a dynamic pattern of context-dependent development, however, research has yet to examine how basal cortisol and attention dynamically covary across infancy in ecologically valid contexts. Thus, to address these gaps, we leveraged longitudinal, multilevel analytic methods to disentangle between- from within-person associations of hypothalamic-pituitary-adrenal (HPA) axis activity and executive attention behaviors across infancy. We use data from a large longitudinal sample (N = 1,292) of infants in predominantly low-income, nonurban communities at 7-, 15-, and 24-months of age. Using multilevel models, we investigated longitudinal associations of infant attention and basal cortisol levels and examined caregiving behaviors as moderators of this relationship. Results indicated a negative between- and within-person association between attention and cortisol across infancy and a within-person moderation by caregiver responsiveness. In other words, on the within-person level, higher levels of cortisol were concomitantly associated with lower infant attention across the first 2 years of life. However, variation in the caregiver's level of responsiveness either buffered or sensitized the executive attention system to the negative effects of physiological stress.

Functional brain networks have been shown to undergo fundamental changes associated with aging or schizophrenia. However, the mechanism of how these factors exert influences jointly or interactively on brain networks remains elusive. A unified recognition of connectomic alteration patterns was also hampered by heterogeneities in network construction and thresholding methods. Recently, an unbiased network representation method regardless of network thresholding, so called minimal spanning tree algorithm, has been applied to study the critical skeleton of the brain network. In this study, we aimed to use minimum spanning tree (MST) as an unbiased network reconstruction and employed structural equation modeling (SEM) to unravel intertwined relationships among multiple phenotypic and connectomic variables in schizophrenia. First, we examined global and local brain network properties in 40 healthy subjects and 40 schizophrenic patients aged 21-55 using resting-state functional magnetic resonance imaging (rs-fMRI). Global network alterations are measured by graph theoretical metrics of MSTs and a connectivity-transitivity two-dimensional approach was proposed to characterize nodal roles. We found that networks of schizophrenic patients exhibited a more star-like global structure compared to controls, indicating excessive integration, and a loss of regional transitivity in the dorsal frontal cortex (corrected p <.05). Regional analysis of MST network topology revealed that schizophrenia patients had more network hubs in frontal regions, which may be linked to the "overloading" hypothesis. Furthermore, using SEM, we found that the level of MST integration mediated the influence of age on negative symptom severity (indirect effect 95% CI [0.026, 0.449]). These findings highlighted an altered network skeleton in schizophrenia and suggested that aging-related enhancement of network integration may undermine functional specialization of distinct neural systems and result in aggravated schizophrenic symptoms.

Since the beginning of the COVID-19 pandemic in early 2020, many governments have implemented national or regional lockdowns to slow the spread of infection. The widely anticipated negative impact these interventions would have on families, including on their mental health, were not included in decision models. The purpose of this editorial is, therefore, to stimulate debate by considering some of the barriers that have stopped governments setting the benefits of lockdown against, in particular, mental health costs during this process and so to make possible a more balanced approach going forward. First, evidence that lockdown causes mental health problems needs to be stronger. Natural experimental studies will play an essential role in providing such evidence. Second, innovative health economic approaches that allow the costs and benefits of lockdown to be compared directly are required. Third, we need to develop public health information strategies that allow more nuanced and complex messages that balance lockdown's costs and benefits to be communicated. These steps should be accompanied by a major public consultation/engagement campaign aimed at strengthening the publics' understanding of science and exploring beliefs about how to strike the appropriate balance between costs and benefits in public health intervention decisions.

Psychogenic Non-Epileptic Seizures (PNES) are a relatively common condition in children. While their clinical presentation resembles epileptic seizures, the underlying cause for PNES involves a multitude of bio-psychosocial factors. Patients may be misdiagnosed with epilepsy and subjected to unnecessary treatments, often delaying the diagnosis for years. A strong understanding of its symptomatology is essential for diagnosis of PNES. Successful management depends on effective teamwork that involves the neurologist as well as mental health professionals. This paper reviews the various aspects of PNES in children with emphasis on the clinical presentation, diagnosis as well as the underlying psychological basis and treatment.

Rhythms of the brain are generated by neural oscillations across multiple frequencies. These oscillations can be decomposed into distinct frequency intervals associated with specific physiological processes. In practice, the number and ranges of decodable frequency intervals are determined by sampling parameters, often ignored by researchers. To improve the situation, we report on an open toolbox with a graphical user interface for decoding rhythms of the brain system (DREAM). We provide worked examples of DREAM to investigate frequency-specific performance of both neural (spontaneous brain activity) and neurobehavioral (in-scanner head motion) oscillations. DREAM decoded the head motion oscillations and uncovered that younger children moved their heads more than older children across all five frequency intervals whereas boys moved more than girls in the age of 7 to 9 years. It is interesting that the higher frequency bands contain more head movements, and showed stronger age-motion associations but weaker sex-motion interactions. Using data from the Human Connectome Project, DREAM mapped the amplitude of these neural oscillations into multiple frequency bands and evaluated their test-retest reliability. The resting-state brain ranks its spontaneous oscillation's amplitudes spatially from high in ventral-temporal areas to low in ventral-occipital areas when the frequency band increased from low to high, while those in part of parietal and ventral frontal regions are reversed. The higher frequency bands exhibited more reliable amplitude measurements, implying more inter-individual variability of the amplitudes for the higher frequency bands. In summary, DREAM adds a reliable and valid tool to mapping human brain function from a multiple-frequency window into brain waves.