AI-based differential diagnosis of dementia etiologies on multimodal data.

Differential diagnosis of dementia remains a challenge in neurology due to symptom overlap across etiologies, yet it is crucial for formulating early, personalized management strategies. Here, we present an artificial intelligence (AI) model that harnesses a broad array of data, including demographics, individual and family medical history, medication use, neuropsychological assessments, functional evaluations and multimodal neuroimaging, to identify the etiologies contributing to dementia in individuals. The study, drawing on 51,269 participants across 9 independent, geographically diverse datasets, facilitated the identification of 10 distinct dementia etiologies. It aligns diagnoses with similar management strategies, ensuring robust predictions even with incomplete data. Our model achieved a microaveraged area under the receiver operating characteristic curve (AUROC) of 0.94 in classifying individuals with normal cognition, mild cognitive impairment and dementia. Also, the microaveraged AUROC was 0.96 in differentiating the dementia etiologies. Our model demonstrated proficiency in addressing mixed dementia cases, with a mean AUROC of 0.78 for two co-occurring pathologies. In a randomly selected subset of 100 cases, the AUROC of neurologist assessments augmented by our AI model exceeded neurologist-only evaluations by 26.25%. Furthermore, our model predictions aligned with biomarker evidence and its associations with different proteinopathies were substantiated through postmortem findings. Our framework has the potential to be integrated as a screening tool for dementia in clinical settings and drug trials. Further prospective studies are needed to confirm its ability to improve patient care.

AI-based differential diagnosis of dementia etiologies on multimodal data.

Differential diagnosis of dementia remains a challenge in neurology due to symptom overlap across etiologies, yet it is crucial for formulating early, personalized management strategies. Here, we present an AI model that harnesses a broad array of data, including demographics, individual and family medical history, medication use, neuropsychological assessments, functional evaluations, and multimodal neuroimaging, to identify the etiologies contributing to dementia in individuals. The study, drawing on 51,269 participants across 9 independent, geographically diverse datasets, facilitated the identification of 10 distinct dementia etiologies. It aligns diagnoses with similar management strategies, ensuring robust predictions even with incomplete data. Our model achieved a micro-averaged area under the receiver operating characteristic curve (AUROC) of 0.94 in classifying individuals with normal cognition, mild cognitive impairment and dementia. Also, the micro-averaged AUROC was 0.96 in differentiating the dementia etiologies. Our model demonstrated proficiency in addressing mixed dementia cases, with a mean AUROC of 0.78 for two co-occurring pathologies. In a randomly selected subset of 100 cases, the AUROC of neurologist assessments augmented by our AI model exceeded neurologist-only evaluations by 26.25%. Furthermore, our model predictions aligned with biomarker evidence and its associations with different proteinopathies were substantiated through postmortem findings. Our framework has the potential to be integrated as a screening tool for dementia in various clinical settings and drug trials, with promising implications for person-level management.

Piecing it together: atrophy profiles of hippocampal subfields relate to cognitive impairment along the Alzheimer's disease spectrum.

Introduction: People with Alzheimer's disease (AD) experience more rapid declines in their ability to form hippocampal-dependent memories than cognitively normal healthy adults. Degeneration of the whole hippocampal formation has previously been found to covary with declines in learning and memory, but the associations between subfield-specific hippocampal neurodegeneration and cognitive impairments are not well characterized in AD. To improve prognostic procedures, it is critical to establish in which hippocampal subfields atrophy relates to domain-specific cognitive declines among people along the AD spectrum. In this study, we examine high-resolution structural magnetic resonance imaging (MRI) of the medial temporal lobe and extensive neuropsychological data from 29 amyloid-positive people on the AD spectrum and 17 demographically-matched amyloid-negative healthy controls. Methods: Participants completed a battery of neuropsychological exams including select tests of immediate recollection, delayed recollection, and general cognitive status (i.e., performance on the Mini-Mental State Examination [MMSE] and Montreal Cognitive Assessment [MoCA]). Hippocampal subfield volumes (CA1, CA2, CA3, dentate gyrus, and subiculum) were measured using a dedicated MRI slab sequence targeting the medial temporal lobe and used to compute distance metrics to quantify AD spectrum-specific atrophic patterns and their impact on cognitive outcomes. Results: Our results replicate prior studies showing that CA1, dentate gyrus, and subiculum hippocampal subfield volumes were significantly reduced in AD spectrum participants compared to amyloid-negative controls, whereas CA2 and CA3 did not exhibit such patterns of atrophy. Moreover, degeneration of the subiculum along the AD spectrum was linked to a significant decline in general cognitive status measured by the MMSE, while degeneration scores of the CA1 and dentate gyrus were more widely associated with declines on the MMSE and tests of learning and memory. Discussion: These findings provide evidence that subfield-specific patterns of hippocampal degeneration, in combination with cognitive assessments, may constitute a sensitive prognostic approach and could be used to better track disease trajectories among individuals on the AD spectrum.

Movement-related beta and gamma oscillations indicate parallels and disparities between Alzheimer's disease and HIV-associated neurocognitive disorder.

People with HIV (PWH) often develop HIV-related neurological impairments known as HIV-associated neurocognitive disorder (HAND), but cognitive dysfunction in older PWH may also be due to age-related disorders such as Alzheimer's disease (AD). Discerning these two conditions is challenging since the specific neural characteristics are not well understood and limited studies have probed HAND and AD spectrum (ADS) directly. We examined the neural dynamics underlying motor processing during cognitive interference using magnetoencephalography (MEG) in 22 biomarker-confirmed patients on the ADS, 22 older participants diagnosed with HAND, and 30 healthy aging controls. MEG data were transformed into the time-frequency domain to examine movement-related oscillatory activity and the impact of cognitive interference on distinct stages of motor programming. Both cognitively impaired groups (ADS/HAND) performed significantly worse on the task (e.g., less accurate and slower reaction time) and exhibited reductions in frontal and cerebellar beta and parietal gamma activity relative to controls. Disease-specific aberrations were also detected such that those with HAND exhibited weaker gamma interference effects than those on the ADS in frontoparietal and motor areas. Additionally, temporally distinct beta interference effects were identified, with ADS participants exhibiting stronger beta interference activity in the temporal cortex during motor planning, along with weaker beta interference oscillations dispersed across frontoparietal and cerebellar cortices during movement execution relative to those with HAND. These results indicate both overlapping and distinct neurophysiological aberrations in those with ADS disorders or HAND in key motor and top-down cognitive processing regions during cognitive interference and provide new evidence for distinct neuropathology.

Sleep quality differentially modulates neural oscillations and proteinopathy in Alzheimer's disease.

BACKGROUND: Alterations in resting-state neural activity have been reported in people with sleep disruptions and in patients with Alzheimer's disease, but the direct impact of sleep quality on Alzheimer's disease-related neurophysiological aberrations is unclear. METHODS: We collected cross-sectional resting-state magnetoencephalography and extensive neuropsychological and clinical data from 38 biomarker-confirmed patients on the Alzheimer's disease spectrum and 20 cognitively normal older control participants. Sleep efficiency was quantified using the Pittsburgh Sleep Quality Index. FINDINGS: Neural activity in the delta frequency range was differentially affected by poor sleep in patients on the Alzheimer's disease spectrum. Such neural changes were related to processing speed abilities and regional amyloid accumulation, and these associations were mediated and moderated, respectively, by sleep quality. INTERPRETATION: Together, our results point to a mechanistic role for sleep disturbances in the widely reported neurophysiological aberrations seen in patients on the Alzheimer's disease spectrum, with implications for basic research and clinical intervention. FUNDING: National Institutes of Health, USA.

Oscillatory markers of neuroHIV-related cognitive impairment and Alzheimer's disease during attentional interference processing.

People with HIV (PWH) frequently experience mild cognitive decline, which is typically attributed to HIV-associated neurocognitive disorder (HAND). However, such declines could also be a sign of early Alzheimer's disease (AD) in older PWH. Distinguishing these two pathologies in PWH is exceedingly difficult, as there is a major knowledge gap regarding their neural and neuropsychological bases. In the current study, we begin to address this knowledge gap by recording magnetoencephalography (MEG) during a flanker interference task in 31 biomarker-confirmed patients on the AD spectrum (ADS), 25 older participants with HAND, and 31 cognitively-normal controls. MEG data was examined in the time-frequency domain using a data-driven approach. Our results indicated that the clinical groups (ADS/HAND) performed significantly worse than controls on the task and exhibited aberrations in interference-related theta and alpha oscillations, some of which were disease-specific. Specifically, patients (ADS/HAND) exhibited weaker interference activity in frontoparietal and cingulate cortices compared to controls, while the ADS group exhibited stronger theta interference than those with HAND in frontoparietal, occipital, and temporal cortices. These results reveal overlapping and distinct patterns of neurophysiological alterations among those with ADS and HAND in attentional processing centers and suggest the existence of unique oscillatory markers of each condition.

Convergent and divergent oscillatory aberrations during visuospatial processing in HIV-related cognitive impairment and Alzheimer's disease.

Adults with HIV frequently develop a form of mild cognitive impairment known as HIV-associated neurocognitive disorder (HAND), but presumably cognitive decline in older persons with HIV could also be attributable to Alzheimer's disease (AD). However, distinguishing these two conditions in individual patients is exceedingly difficult, as the distinct neural and neuropsychological features are poorly understood and most studies to date have only investigated HAND or AD spectrum (ADS) disorders in isolation. The current study examined the neural dynamics underlying visuospatial processing using magnetoencephalography (MEG) in 31 biomarker-confirmed patients on the ADS, 26 older participants who met criteria for HAND, and 31 older cognitively normal controls. MEG data were examined in the time-frequency domain, and a data-driven approach was utilized to identify the neural dynamics underlying visuospatial processing. Both clinical groups (ADS/HAND) were significantly less accurate than controls on the task and exhibited stronger prefrontal theta oscillations compared to controls. Regarding disease-specific alterations, those with HAND exhibited stronger alpha oscillations than those on the ADS in frontoparietal and temporal cortices. These results indicate both common and unique neurophysiological alterations among those with ADS disorders and HAND in regions serving visuospatial processing and suggest the underlying neuropathological features are at least partially distinct.

Altered visual entrainment in patients with Alzheimer's disease: magnetoencephalography evidence.

Recent research has indicated that rhythmic visual entrainment may be useful in clearing pathological protein deposits in the central nervous system of mouse models of Alzheimer's disease. However, visual entrainment studies in human patients with Alzheimer's disease are rare, and as such the degree to which these patients exhibit aberrations in the neural tracking of rhythmic visual stimuli is unknown. To fill this gap, we recorded magnetoencephalography during a 15 Hz visual entrainment paradigm in amyloid-positive patients on the Alzheimer's disease spectrum and compared their neural responses to a demographically matched group of biomarker-negative healthy controls. Magnetoencephalography data were imaged using a beamformer and virtual sensor data were extracted from the peak visual entrainment responses. Our results indicated that, relative to healthy controls, participants on the Alzheimer's disease spectrum exhibited significantly stronger 15 Hz entrainment in primary visual cortices relative to a pre-stimulus baseline period. However, the two groups exhibited comparable absolute levels of neural entrainment, and higher absolute levels of entertainment predicted greater Mini-mental Status Examination scores, such that those patients whose absolute entrainment amplitude was closer to the level seen in controls had better cognitive function. In addition, 15 Hz periodic activity, but not aperiodic activity, during the pre-stimulus baseline period was significantly decreased in patients on the Alzheimer's disease spectrum. This pattern of results indicates that patients on the Alzheimer's disease spectrum exhibited increased visual entrainment to rhythmic stimuli and that this increase is likely compensatory in nature. More broadly, these results show that visual entrainment is altered in patients with Alzheimer's disease and should be further examined in future studies, as changes in the capacity to entrain visual stimuli may prove useful as a marker of Alzheimer's disease progression.

Signatures of somatosensory cortical dysfunction in Alzheimer's disease and HIV-associated neurocognitive disorder.

Alzheimer's disease is the most common type of dementia in the general population, while HIV-associated neurocognitive disorder is the most common neurological comorbidity in those infected with HIV and affects between 40 and 70% of this population. Both conditions are associated with cognitive impairment and have been associated with aberrant functioning in sensory cortices, but far less is known about their disparate effects on neural activity. Identifying such disparate effects is important because it may provide critical data on the similarities and differences in the neuropathology underlying cognitive decline in each condition. In the current study, we utilized magnetoencephalography, extensive neuropsychological testing and a paired-pulse somatosensory gating paradigm to probe differences in somatosensory processing in participants from two ongoing magnetoencephalography studies. The resulting participant groups included 27 cognitively normal controls, 26 participants with HIV-associated neurocognitive disorder and 21 amyloid biomarker-confirmed patients with Alzheimer's disease. The data were imaged using a beamformer and voxel time series were extracted to identify the oscillatory dynamics serving somatosensory processing, as well as the amplitude of spontaneous cortical activity preceding stimulation onset. Our findings indicated that people with Alzheimer's disease and HIV-associated neurocognitive disorder exhibit normal somatosensory gating but have distinct aberrations in other elements of somatosensory cortical function. Essentially, those with Alzheimer's disease exhibited accentuated neural responses to somatosensory stimulation, along with spontaneous gamma activity preceding stimulus onset. In contrast, those with HIV-associated neurocognitive disorder exhibited normal responses to somatosensory stimulation but had sharply elevated spontaneous gamma activity prior to stimulus onset. These distinct aberrations may reflect the impact of different neuropathological mechanisms underlying each condition. Further, given the differential pattern of deficits in somatosensory cortical function, these measures may function as unique biomarkers in each condition and be useful in identifying persons with HIV who may go on to develop Alzheimer's disease.

Multimodal deep learning for Alzheimer's disease dementia assessment.

Worldwide, there are nearly 10 million new cases of dementia annually, of which Alzheimer's disease (AD) is the most common. New measures are needed to improve the diagnosis of individuals with cognitive impairment due to various etiologies. Here, we report a deep learning framework that accomplishes multiple diagnostic steps in successive fashion to identify persons with normal cognition (NC), mild cognitive impairment (MCI), AD, and non-AD dementias (nADD). We demonstrate a range of models capable of accepting flexible combinations of routinely collected clinical information, including demographics, medical history, neuropsychological testing, neuroimaging, and functional assessments. We then show that these frameworks compare favorably with the diagnostic accuracy of practicing neurologists and neuroradiologists. Lastly, we apply interpretability methods in computer vision to show that disease-specific patterns detected by our models track distinct patterns of degenerative changes throughout the brain and correspond closely with the presence of neuropathological lesions on autopsy. Our work demonstrates methodologies for validating computational predictions with established standards of medical diagnosis.

Spatially resolved neural slowing predicts impairment and amyloid burden in Alzheimer's disease.

An extensive electrophysiological literature has proposed a pathological 'slowing' of neuronal activity in patients on the Alzheimer's disease spectrum. Supported by numerous studies reporting increases in low-frequency and decreases in high-frequency neural oscillations, this pattern has been suggested as a stable biomarker with potential clinical utility. However, no spatially resolved metric of such slowing exists, stymieing efforts to understand its relation to proteinopathy and clinical outcomes. Further, the assumption that this slowing is occurring in spatially overlapping populations of neurons has not been empirically validated. In the current study, we collected cross-sectional resting state measures of neuronal activity using magnetoencephalography from 38 biomarker-confirmed patients on the Alzheimer's disease spectrum and 20 cognitively normal biomarker-negative older adults. From these data, we compute and validate a new metric of spatially resolved oscillatory deviations from healthy ageing for each patient on the Alzheimer's disease spectrum. Using this Pathological Oscillatory Slowing Index, we show that patients on the Alzheimer's disease spectrum exhibit robust neuronal slowing across a network of temporal, parietal, cerebellar and prefrontal cortices. This slowing effect is shown to be directly relevant to clinical outcomes, as oscillatory slowing in temporal and parietal cortices significantly predicted both general (i.e. Montreal Cognitive Assessment scores) and domain-specific (i.e. attention, language and processing speed) cognitive function. Further, regional amyloid-ß accumulation, as measured by quantitative 18F florbetapir PET, robustly predicted the magnitude of this pathological neural slowing effect, and the strength of this relationship between amyloid-ß burden and neural slowing also predicted attentional impairments across patients. These findings provide empirical support for a spatially overlapping effect of oscillatory neural slowing in biomarker-confirmed patients on the Alzheimer's disease spectrum, and link this effect to both regional proteinopathy and cognitive outcomes in a spatially resolved manner. The Pathological Oscillatory Slowing Index also represents a novel metric that is of potentially high utility across a number of clinical neuroimaging applications, as oscillatory slowing has also been extensively documented in other patient populations, most notably Parkinson's disease, with divergent spectral and spatial features.

Stimulating Memory: Reviewing Interventions Using Repetitive Transcranial Magnetic Stimulation to Enhance or Restore Memory Abilities.

Human memory systems are imperfect recording devices that are affected by age and disease, but recent findings suggest that the functionality of these systems may be modifiable through interventions using non-invasive brain stimulation such as repetitive transcranial magnetic stimulation (rTMS). The translational potential of these rTMS interventions is clear: memory problems are the most common cognitive complaint associated with healthy aging, while pathological conditions such as Alzheimer's disease are often associated with severe deficits in memory. Therapies to improve memory or treat memory loss could enhance independence while reducing costs for public health systems. Despite this promise, several important factors limit the generalizability and translational potential of rTMS interventions for memory. Heterogeneity of protocol design, rTMS parameters, and outcome measures present significant challenges to interpretation and reproducibility. However, recent advances in cognitive neuroscience, including rTMS approaches and recent insights regarding functional brain networks, may offer methodological tools necessary to design new interventional studies with enhanced experimental rigor, improved reproducibility, and greater likelihood of successful translation to clinical settings. In this review, we first discuss the current state of the literature on memory modulation with rTMS, then offer a commentary on developments in cognitive neuroscience that are relevant to rTMS interventions, and finally close by offering several recommendations for the design of future investigations using rTMS to modulate human memory performance.

Somatosensory dysfunction is masked by variable cognitive deficits across patients on the Alzheimer's disease spectrum.

BACKGROUND: Alzheimer's disease (AD) is generally thought to spare primary sensory function; however, such interpretations have drawn from a literature that has rarely taken into account the variable cognitive declines seen in patients with AD. As these cognitive domains are now known to modulate cortical somatosensory processing, it remains possible that abnormalities in somatosensory function in patients with AD have been suppressed by neuropsychological variability in previous research. METHODS: In this study, we combine magnetoencephalographic (MEG) brain imaging during a paired-pulse somatosensory gating task with an extensive battery of neuropsychological tests to investigate the influence of cognitive variability on estimated differences in somatosensory function between biomarker-confirmed patients on the AD spectrum and cognitively-normal older adults. FINDINGS: We show that patients on the AD spectrum exhibit largely non-significant differences in somatosensory function when cognitive variability is not considered (p-value range: .020-.842). However, once attention and processing speed abilities are considered, robust differences in gamma-frequency somatosensory response amplitude (p < .001) and gating (p = .004) emerge, accompanied by significant statistical suppression effects. INTERPRETATION: These findings suggest that patients with AD exhibit insults to functional somatosensory processing in primary sensory cortices, but these effects are masked by variability in cognitive decline across individuals. FUNDING: National Institutes of Health, USA; Fremont Area Alzheimer's Fund, USA.

Visuospatial alpha and gamma oscillations scale with the severity of cognitive dysfunction in patients on the Alzheimer's disease spectrum.

BACKGROUND: Entrainment of neural oscillations in occipital cortices by external rhythmic visual stimuli has been proposed as a novel therapy for patients with Alzheimer's disease (AD). Despite this increased interest in visual neural oscillations in AD, little is known regarding their role in AD-related cognitive impairment and in particular during visuospatial processing. METHODS: We used source-imaged magnetoencephalography (MEG) and an established visuospatial processing task to elicit multi-spectral neuronal responses in 35 biomarker-confirmed patients on the AD spectrum and 20 biomarker-negative older adults. Neuronal oscillatory responses were imaged to the level of the cortex, and group classifications and neurocognitive relationships were modeled using logistic and linear regression, respectively. RESULTS: Visuospatial neuronal oscillations in the theta, alpha, and gamma ranges significantly predicted the classification of patients on the AD spectrum. Importantly, the direction of these effects differed by response frequency, such that patients on the AD spectrum exhibited weaker alpha-frequency responses in lateral occipital regions, and stronger gamma-frequency responses in the primary visual cortex, as compared to biomarker-negative older adults. In addition, alpha and gamma, but not theta, oscillations robustly predicted cognitive status (i.e., MoCA and MMSE scores), such that patients with neural responses that deviated more from those of healthy older adults exhibited poorer cognitive performance. CONCLUSIONS: We find that the multi-spectral neural dynamics supporting visuospatial processing differentiate patients on the AD spectrum from cognitively normal, biomarker-negative older adults. Oscillations in the alpha and gamma bands also relate to cognitive status in ways that are informative for emerging clinical interventions.

Spatio-spectral relationships between pathological neural dynamics and cognitive impairment along the Alzheimer's disease spectrum.

INTRODUCTION: Numerous studies have described aberrant patterns of rhythmic neural activity in patients along the Alzheimer's disease (AD) spectrum, yet the relationships between these pathological features and cognitive decline are uncertain. METHODS: We acquired magnetoencephalography (MEG) data from 38 amyloid-PET biomarker-confirmed patients on the AD spectrum and a comparison group of biomarker-negative cognitively normal (CN) healthy adults, alongside an extensive neuropsychological battery. RESULTS: By modeling whole-brain rhythmic neural activity with an extensive neuropsychological profile in patients on the AD spectrum, we show that the spectral and spatial features of deviations from healthy adults in neural population-level activity inform their relevance to domain-specific neurocognitive declines. DISCUSSION: Regional oscillatory activity represents a sensitive metric of neuronal pathology in patients on the AD spectrum. By considering not only the spatial, but also the spectral, definitions of cortical neuronal activity, we show that domain-specific cognitive declines can be better modeled in these individuals.

Screening for cognitive impairment in older adults with hematological malignancies using the Montreal Cognitive Assessment and neuropsychological testing.

OBJECTIVES: The primary objective of the current study is to describe the prevalence and profile of cognitive domains affected in older adults with hematological malignancies evaluated for hematopoietic cell transplantation (HCT) using the Montreal Cognitive Assessment (MoCA) and neuropsychological tests. The secondary objective is to determine if a specific MoCA cut-off score would correlate with the identification of cognitive impairment detected by neuropsychological tests. This would facilitate interpretation of cognitive screening and referral of patients who would likely need further neuropsychological testing. MATERIALS AND METHODS: Fifty-one patients 60 years and older who were evaluated for HCT were assessed using a battery of standardized neuropsychological tests and MoCA. We analyzed Receiver Operating Characteristics (ROC) comparing MoCA scores and four different neuropsychological test criteria for cognitive impairment. RESULTS: The prevalence of cognitive impairment detected by neuropsychological tests was 53 to 70.6% using the criteria for patients with cancer by the International Cancer Cognition Task Force (ICCTF). The following cognitive domains were most affected: language, learning and memory, visuospatial skills, and executive function. MoCA is an appropriate screening test for cognitive impairment. Using the ICCTF criteria, 86 to 100% of patients are correctly classified as having significant cognitive impairment on neuropsychological tests using a cut-off score of 20 or less. CONCLUSION: There is a high prevalence of cognitive impairment identified by neuropsychological tests in older patients with hematological malignancies evaluated for HCT. Identification of an appropriate MoCA cut-off score in this population is important to identify patients who would benefit from further assessment.

Cerebrovascular Reactivity Impairment in Preclinical Alzheimer's Disease.

BACKGROUND AND PURPOSE: A substantial overlap exists between declines in cerebral vasoreactivity (CVR) and symptomatic Alzheimer's disease (AD). CVR can be quantified using transcranial Doppler (TCD) measurement of cerebral blood flow velocities (CBFV) in the middle cerebral artery (MCA) with CO2 as a vasodilatory stimulus. The breath-hold acceleration index (BHAI) is a new, more reliable measure of CVR developed recently in our laboratory. Our primary goal is to explore the possibility of using TCD for asymptomatic AD screening. METHODS: A pilot study population was divided into three groups: 9 healthy control subjects, 8 subjects identified as preclinical AD, and 10 patients diagnosed with prodromal or mild AD. Control subjects had a Clinical Dementia Rating (CDR) score of 0 without elevated amyloid-ß (Aß) on amyloid positron emission tomography (PET) imaging, preclinical AD subjects had CDR = 0 with elevated Aß, and prodromal to mild AD subjects had CDR scores ≥.5 and elevated Aß. CVR was calculated using two indices: the conventional breath-holding index (BHI) and the new BHAI. TCD parameters between the three groups were compared. RESULTS: BHAI was able to distinguish between 9 normal control subjects and 8 preclinical-AD subjects with high statistical significance (P < .001). BHI and pulsatility index were able only to distinguish AD from healthy and preclinical subjects (P < .001). CONCLUSIONS: In this exploratory pilot study, CVR was significantly decreased in preclinical, prodromal, and mild AD subjects as compared to the healthy group. Lower CVR in the preclinical AD group was detected using the new BHAI index but not the conventional BHI index.

The Association Between Body Mass Index, and Cognitive, Functional, and Behavioral Declines for Incident Dementia.

BACKGROUND: Association between high adiposity and the clinical progression of dementia remains puzzling. OBJECTIVE: To separately examine the association between body mass index (BMI) and cognitive, functional, and behavioral declines before, at, and after diagnosis of dementia, and further stratified by age groups, and sex. METHODS: A total of 1,141 individuals with incident dementia were identified from the Uniform Data Set of the National Alzheimer's Coordinating Center. Cognitive function was evaluated by Mini-Mental State Exam, functional abilities were assessed using Functional Activities Questionnaire, and behavioral symptoms were captured by Neuropsychiatric Inventory Questionnaire at each follow-up visit. We used separate linear-mixed effects models to examine the association. RESULTS: Compared to moderate baseline BMI, high baseline BMI was associated with 0.30-point slower annual progression rates in functional decline. For individuals aged 76 and over, high baseline BMI was associated with 0.42-point faster progression rates in cognitive decline annually. A U-shaped association between baseline BMI and cognitive decline was observed among men. CONCLUSION: BMI levels before dementia diagnosis may facilitate the identification of different risk profiles for progression rates of cognitive and functional declines in individuals who developed dementia.

The Breath-Hold Acceleration Index: A New Method to Evaluate Cerebrovascular Reactivity using Transcranial Doppler.

BACKGROUND AND PURPOSE: Cerebrovascular reactivity (CR) is an ideal biomarker to detect cerebrovascular damage. CR can be quantified by measuring changes in cerebral blood flow velocity (CBFV) resulting from a CO2  vasodilatory stimulus, often using the breath-holding index (BHI). In this method, transcranial Doppler (TCD) ultrasound is used to measure CBFV changes in the middle cerebral artery (MCA) during a breath-hold maneuver. Despite its convenience, BHI has high variability. Changing body position may contribute to potential variability. It is important to determine if CR differs with body position. The aims of this study were, first, to propose an alternative, more robust index to evaluate CR using a breath-hold maneuver; second, investigate the effect of body position on CR measured with conventional (BHI) and a new proposed index. METHODS: Ten healthy young volunteers held their breath for 30 seconds on a tilt table. CR was calculated at five different angles using two indices: the conventional BHI, and the breath-hold acceleration index (BHAI), a new index obtained by linear regression of the most linear portion of the mean velocity change during the breath-hold maneuver. The regression represents acceleration (change in blood flow velocity per unit of time) sampled at each cardiac cycle. RESULTS: The mean coefficient of variation was 43.7% lower in BHAI in comparison with BHI. Neither index was statistically significant between body positions (P > .05). CONCLUSIONS: BHAI has less variability in comparison with the conventional standard BHI. Additionally, neither index showed statistical significance in CR based on change in body position.

Hyperbaric oxygen for late sequelae of carbon monoxide poisoning enhances neurological recovery: case report.

Neuropsychiatric sequelae have been reported in 15%-45% of survivors of carbon monoxide (CO) poisoning. Hyperbaric oxygen (HBO2) therapy reduces the incidence of cognitive and neurological a dysfunction. The efficacy of providing HBO2 beyond the first one to two days after initial insult is unknown. However, some evidence exists for the benefit of this treatment. We report on treating a patient 14 months after CO injury, who responded with markedly improved neurologic status. A 27-year-old scholar was found comatose due to CO poisoning (carboxyhemoglobin = 31.7%). He received five acute HBO2 treatments. After discharge, he developed chorea, Parkinsonism, dystonia, memory loss, slowed processing speed and verbal fluency, leaving him disabled. After the patient reached a clinical plateau, HBO2 was tried again at 90 minutes at 2.4 ATA plus air breaks. Neuropsychological testing was performed at baseline and after each 20 HBO2 cycles, five of which were performed during the period from 14-22 months after CO exposure. After the first 20 treatments, Parkinsonism and dystonia improved. After 40 sessions, further improvements were seen on mental speed, verbal fluency, and fine motor movements. The outcome following 100 treatments was that the patient regained independence, including the ability to drive and to become gainfully employed. Our case calls into question the concept that HBO2 therapy has no role during the chronic phase of CO brain injury. Randomized clinical trials should be considered to evaluate the therapeutic efficacy of HBO2 in patients with neurological sequelae following CO injury.