Earlier detection of memory loss and dementia.
The worldís LARGEST standardized neuroscientific database.
NeuralScan System combine various electrophysiological biomarkers pertaining to numerous cognitive conditions. It details known clinical correlations based on over 600 scientific publications and defines electroencephalography-derived metrics, including qEEG, event-related potentials, eLoreta Source Analysis, and ECG. Recommended medical interventions are based on these clinical correlations.
The electroencephalogram (EEG) has been a medical standard for the evaluation of general brain health and overall function. This test detects abnormalities in the brain waves, or in the electrical activity. The brain is the most important organ in the body at the center of the nervous system and controls all parts of the body. An EEG can detect minuscule abnormalities the occur as a result of the normal ageing process, mental diseases or disorders, brain insults due to trauma, and abnormal changes due to exposure to toxins, substance abuse, and acute or chronic events.
Peak Alpha Frequency
The alpha frequency band (8 Ė 12 Hz) is the most dominant EEG frequency found in the brain. The Peak Alpha Frequency (PAF), or posterior dominant rhythm, is largely generated by the thalamus and reflects thalamo-cortical network activity; therefore, PAF can be conceptualized as the pacemaker of the brain and is known to be a good measure of information processing capacity.
EEG studies have found that PAF rises from childhood to adolescence, and then decreases slowly around 11 years old. Regardless of age, individuals with strong working memory abilities have faster PAF compared to inferior memory performers. Abnormally low PAF (< 8 Hz) can be found in patients with cognitive disturbances and dementia, while a slowed PAF is correlated with the loss of hippocampal volume in many posterior regions of the brain in individuals suffering from MCI. The PAF electrophysiology biomarker can, therefore, be used to help identify patients with preclinical dementia and monitor a patientís overall cognitive capacity over time.
Brain Mapping Source Analysis
Normal and productive brain function relies heavily on a complex array of interconnected networks that facilitate communication within and across brain structures.
With EEG source analysis we attempt to bridge the gap between surface EEG data and the respective neural source generators: EEG dynamics reflect the collective action (superposition) of many neuronal systems distributed across the brain. Source analysis disentangles the different neuronal sources and gives you a hint where and when it happened. Information pathways in the brain can be studied by using either the reconstructed activation waveforms or by time-frequency analysis. Source analysis can identify the brain regions involved in different tasks and depending on data quality and model quality, yield a precise localization of the generators in both space and time.
Quantitative EEG (qEEG) moves beyond the conventional visual inspection of an EEG to perform a strictly objective analysis of brain function. The patientís digital EEG data is statistically analyzed and compared to normative database reference values in order to provide insight to differential diagnoses and effects of treatment. Distinct differences in resting-state qEEG profiles exist between patients with dementia diagnoses and age-matched controls. Research has shown that some patients with dementia present with a slower alpha rhythm and a general decrease in beta power. This qEEG pattern may be especially useful in distinguishing dementia from pseudodementia. Moreover, qEEG brain maps can provide relevant information in order to differentiate between specific dementia diagnoses, such as AD and vascular dementia. Therefore, the sensitivity of the qEEG can be a useful assessment measure when considering memory impairment etiology.
Upwards of 20% of individuals age 65 and older already have detectable symptoms of mild cognitive impairment; however, diagnosing the cause of memory loss can prove challenging. Historically, many doctors have relied on self-report questionnaires and effort-based computerized testing for determining a diagnosis; however, even when used in optimal conditions, these assessments often fall short in the detection of early or less severe disease presentations. Additionally, current tools lack the sensitivity and objectivity needed to develop accurate diagnoses, resulting in misdiagnosis in a segment of the patient population. Therefore, when patients present with concerns of memory loss, the physician needs a quick, easy-to-use, low-cost, objective, and sensitive test.
Electroencephalography (EEG) has been employed extensively in clinical research and provides a non-invasive and office-based solution for objectively measuring brain function. Leading research agrees that clinical evaluation along with other supportive diagnostic techniques, such as functional neuroimaging, may be necessary to substantiate memory loss diagnoses; however, since the sensitive equipment needed is expensive and data interpretation can be difficult and time-consuming, the EEG has historically been out of reach for many practicing physicians.
A natural process of ageing includes the decline in neuro physical and cognitive abilities. Behavior performance can be measured as it relates to the daily stressors that everyone faces, including neuro-physical, emotional and mental challenges. The observable changes can include changes in reaction time, errors in commission (how often you make mistakes), and errors in omission (how often you miss information).
These performance measures can provide an accurate snapshot and an objective assessment of a patientís ability to effectively perform general or routine daily tasks and can indicate the level of decline.
Evoked Potentials (EPs)
Event-related potentials (ERP) are also referred to as evoked potentials (EP) and are a measurement of the brainís direct response to a specific sensory, cognitive, or motor event. EPRs have the ability to measure (to the millisecond) the speed in which the brain is able to process this information. This fast-paced processing is what allow us as humans to receive, filter, and process billions of pieces of information in order to make split-second decision every second of every day. Due to the sensitivity of ERP testing, we are able to detect changes in this processing speed that is related to cognitive decline. If this testing is performed early enough, these changes can be seen before they become physically noticeable. The ERP can detect slowing in physical reaction times and decision-making skills, as well as stress disorders, memory loss, and other neurological disorders.
Memory functions and cognitive processes within the brain can be measured using event-related potentials (ERPs). These waveforms represent time-locked neuronal responses generated in response to specific events or stimuli. The latency, or time delay, between the onset of the stimulus and a patientís physical response reflects brain processing speed, while waveform amplitude reflects neuronal recruitment and subsequent activation of the recruited neurons to process the information.
Fundamental elements of memory include the degree of attention to a stimulus and the subsequent encoding of information for storage and retrieval. P300a and P300b are two ERP components useful in measuring these aspects of memory. The P300b component has been exceptionally well-studied in regard to memory loss disorders, such as Mild Cognitive Impairment (MCI) and Alzheimer's disease (AD). When comparing individuals with AD to age-matched controls, individuals with AD had longer P300b latency measures and low amplitudes. P300b latency and amplitude have been shown to predict the progression of mild cognitive impairment. Additionally, P300b metrics demonstrate superior sensitivity over conventional assessments, such as the MMSE, in detecting early preclinical memory loss.
Neurofeedback is a self-regulated technique that involves direct training of brain function, by which the brain learns to function more efficiently. Neurofeedback is also called EEG Biofeedback because it is based on electrical brain activity. This is a gradual learning process and applies to any aspect of brain function that can be measured.
Neurofeedback addresses problems of brain dysregulation. These can include the anxiety-depression spectrum, attention deficits, behavior disorders, various sleep disorders, headaches and migraines, PMS and emotional disturbances. It is also useful for organic brain conditions such as seizures, the autism spectrum, and cerebral palsy.
Through computerized feedback, the patient is taught how to focus on making subtle changes in their body in order to achieve a healthier mental, emotional or physiological state. It is completely non-invasive and painless.