COGNITO (Computerized assessment of adult information processing): Normative scores for a rural Indian population from the SANSCOG study.

INTRODUCTION: Neuropsychological assessments are inexpensive and efficient methods to understand the cognitive abilities of individuals in research studies and clinical settings. Normative scores for such measures are crucial in serving as a reference standard for identifying cognitively healthy and impaired individuals belonging to similar sociodemographic characteristics. METHODS: Study subjects in rural India recruited into the Srinivaspura Aging, Neuro Senescence and Cognition (SANSCOG) study were administered the COGNITO battery of tests, which traverse cognitive domains of attention, memory, language, and visuospatial abilities. Percentile norms based on age and education stratification were derived for the above cohort. RESULTS: Percentile norms are commensurate with literacy levels in this population. The percentile scores for the cognitive tests show a decline for the individuals aged 75 years and above indicating lower cognitive functioning in this age group. DISCUSSION: This is the first-ever study reporting norms for diverse cognitive domains for illiterate, literate, low-literate individuals enrolled in a large-scale community-based cohort study in rural India.

Stimulus-induced gamma rhythms are weaker in human elderly with mild cognitive impairment and Alzheimer's disease.

Alzheimer's disease (AD) in elderly adds substantially to socioeconomic burden necessitating early diagnosis. While recent studies in rodent models of AD have suggested diagnostic and therapeutic value for gamma rhythms in brain, the same has not been rigorously tested in humans. In this case-control study, we recruited a large population (N = 244; 106 females) of elderly (>49 years) subjects from the community, who viewed large gratings that induced strong gamma oscillations in their electroencephalogram (EEG). These subjects were classified as healthy (N = 227), mild cognitively impaired (MCI; N = 12), or AD (N = 5) based on clinical history and Clinical Dementia Rating scores. Surprisingly, stimulus-induced gamma rhythms, but not alpha or steady-state visually evoked responses, were significantly lower in MCI/AD subjects compared to their age- and gender-matched controls. This reduction was not due to differences in eye movements or baseline power. Our results suggest that gamma could be used as a potential screening tool for MCI/AD in humans.

Alzheimer's disease is one of the most common forms of dementia, characterised by declining memory and thinking skills, and behavioural changes that worsen over time. It affects millions of people worldwide, mostly in older age, and yet early indicators of the disease are lacking. Most cases are only diagnosed once a person's brain function becomes noticeably impaired, even though known biological changes underpin the disease. Detecting Alzheimer's disease early could aid diagnosis and enable early intervention, while also improving the chances of finding treatments to halt or reverse the disease. Currently, brain function is measured by performing cognitive tests, such as remembering a set of words, imaging the brain with MRIs or CT scans, and blood or spinal fluid tests. Many of these tests can be invasive and expensive, so researchers are exploring whether measuring oscillations in the brain's electrical activity can be a non-invasive and chepaer way of testing brain function. Gamma oscillations are rhythmic signals, thought to be involved in attention and working memory. Animals used to study Alzheimer's disease have shown some abnormalities in gamma oscillations, and studies of healthy humans have also observed a decline in the strength and frequency of these oscillations with age. These findings have spurred an interest in understanding the link between gamma oscillations and AD in humans. To investigate this link, Murty et al. measured patterns of brain activity in elderly people chosen from the community using electrodes placed on their scalps (a technique called electroencephalography). These participants watched certain images previously shown to elicit gamma oscillations. Participants who were later diagnosed with early Alzheimer's disease had weaker gamma oscillations than their cognitively healthy peers in the part of the brain that processes visual images. These results build upon previous findings from animal research suggesting that gamma oscillations may be disrupted in early Alzheimer's disease. The work by Murty et al. could lead the way to new ways of diagnosing Alzheimer's disease, where early indicators are urgently needed.