Archive for the ‘Neuroscience’ Category

What ‘Brain-Dead’ Means

Brain death is defined as complete and irreversible cessation of brain activity. Absence of apparent brain function is not enough. Evidence of irreversibility is also required. Brain death is often confused with the state of vegetation.

Traditionally, death is cessation of all body function, including respiration and heartbeat. Since it is possible to revive some people after a period without respiration, heartbeat, or other visible signs of life, as well as to maintain respiration and blood flow artificially using life support treatments, an alternative definition of death is needed.

In recent decades, the concept of brain death has emerged. By brain death criteria, a person can be pronounced legally dead even if the heart continues to beat due to the life support measures. The first nation in the world to adopt the brain death as a definition of legal death was Finland in 1971.

Brain-Dead individual has no brain electrical activity, no clinical evidence of brain function. On physical examination, there is no response to pain. Cranial nerve reflexes, for example, pupillary response, oculocephalic reflex, corneal reflex and spontaneous respiration are absent.

It is very important to distinguish between brain death and states that mimic brain death like the state of brain due to barbiturate intoxication, sedative overdose, hypothermia, hypoglycemia, coma or chronic vegetative states. The concept that death can be defined as the irreversible cessation of brain function is universally recognized through judicial decisions or regulations. A physician who makes a determination of death in accordance with these criteria and accepted medical standards is not liable for damages in any civil action or subject to prosecution in any criminal proceedings for his acts or the acts of others based on that determination.

Studies indicate that a patient will not survive with irreversible coma, apnea, absence of brain stem reflexes, and an isoelectric electroencephalogram that persists for more that 6 hours after the onset of coma and apnea. The patient in coma with some remaining brain-related bodily function is not dead. Presence of any behavioral responses or brainstem reflexes indicates that brain death has not occurred and therefore is not dead. A patient in chronic vegetative state may remain in a prolonged coma indefinitely, yet the patient will not meet criteria for brain death and therefore cannot be pronounced dead. Two physicians, namely, a neurologist or a neurosurgeon and an intensive care specialist should together pronounce the clinical assessment of brain death. The international clinical guidelines for this assessment are absence of cerebral functions and absence of brain stem functions.

Absence of cerebral functions for the purpose of diagnosis of brain death is the cause of coma is known. The patient must be in deep coma without any response to verbal or painful stimuli. All reversible causes of coma must be ruled out including hypothermia, that is, core body temperature less than 33 degree Centigrade, drug intoxication, hypotension, neuromuscular blockade, and sedating medicines. Confirmatory tests that have to be performed for concluding absence of cerebral functions are: Electroencephalogram, cerebral angiography, isotope angiography. Electroencephalogram alone could not be used because electroencephalogram is influenced by hypothermia and drugs, so an isoelectric electroencephalogram is very mandatory for diagnosis of brain death.

Clinical examination must confirm absence of brain stem reflexes including pupillary size and reactivity, corneal reflex, oculovestibular reflex, gag reflex, and cough reflex. Apnea test must demonstrate absence of all spontaneous respiratory drive. These examinations must preferably be conducted by physicians who are familiar with performance of these tests. The test of absent breathing should be performed following hyperoxygenation on 100% oxygen on mechanical ventilation and adequate circulation should be maintained during the entire apnea test.

The pupillary signs include round, oval, or irregularly shaped pupils are compatible with brain death, and most pupils are midsize about 4-6 mm. The pupillary light reflex must be absent to pronounce brain death. Although, many drugs influence pupillary size, pupillary light reflex remains intact only in the absence of brain death. Atropine administered intravenously does not markedly affect pupillary response; similarly, neuromuscular blocking agents do not markedly influence pupillary size; however, topical administration of drugs and ocular trauma influence pupillary size and reactivity. Any preexisting ocular anatomic abnormalities may also confound pupillary assessment in brain death.

Ocular movements tests include both oculocephalic “doll’s eye;” and vestibulo-ocular “caloric test” reflexes are absent in brain death. Contraindications to testing for oculocephalic reflexes include suspected fracture or instability of the cervical spine. Likewise, contraindications to testing of vestibulo-ocular reflexes include impaired integrity of tympanic membranes. Oculocephalic reflex is elicited by rapidly and vigorously turning the head to 90 degrees laterally on both sides. The normal response is deviation of the eye to the opposite side of the head turning. In brain death, oculocephalic reflexes are absent, and no eye movements occur in response to head movements. The vestibulo-ocular reflex is elicited by elevating the head 30 degrees and irrigating both tympanic membranes with 50 milliliters of iced saline or water. In brain death, vestibulo-ocular reflexes are absent, and no deviation of the eyes occurs in response to ear irrigations.

Can a person who has been declared brain-dead be revived? No. Brain death is death, plain and simple.

Posted January 22, 2017 by dranilj1 in Neuroscience

Seven Sins of Memory

Though often reliable, human memory is also fallible. How and why memory can get us into trouble? It is suggested that memory’s misdeeds can be classified into 7 basic sins, namely, transience, absentmindedness, blocking, misattribution, suggestibility, bias, and persistence. Evidences are available concerning each of the 7 sins from relevant sectors of psychology (cognitive, social, and clinical) and from cognitive neuroscience studies that include patients with focal brain damage or make use of recently developed neuroimaging techniques. Although the 7 sins may appear to reflect flaws in system design, it is argued instead that they are by-products of otherwise adaptive features of memory.

Despite memory’s obvious benefits, it can also let us down. Memory, for all that it does for us every day, for all the feats that can sometimes amaze us, can also be a troublemaker. However, the same brain mechanisms account for memory’s sins as well as its strengths, so investigating its negatives exposes its positives. We should not think of these fundamentally as flaws in the architecture of memory, but rather as costs we pay for benefits in memory that make it work as well as it does most of the time.

The first three are sins of omission that involve forgetting, and the second four are sins of commission that involve distorted or unwanted recollections.

Transience is the decreasing accessibility of memory over time. While a degree of this is normal with aging, decay of or damage to the hippocampus and temporal lobe can cause extreme forms of transience. To cite as a somewhat facetious example is former President Bill Clinton’s "convenient lapses of memory" during the Monica Lewinsky investigation. Clinton claimed in the hearings that he sometimes could not remember what had happened the previous week.

Absent-mindedness is lapse of attention and forgetting to do things. This sin operates when a memory is formed, that is to say, the encoding stage and when a memory is accessed, meaning, the retrieval stage. For examples, forgetting where you put your keys or glasses. Of note is particularly famous instance in which cellist Yo-Yo Ma forgot to retrieve his $2.5 million cello from the trunk of a New York City cab.

Blocking is temporary inaccessibility of stored information, such as tip-of-the-tongue syndrome. One can describe the embarrassment of John Prescott, British deputy prime minister, when a reporter asked him how the government was paying for the expensive Millennium Dome. Prescott struggled to find the word "lottery," trying "raffles" instead.

Suggestibility is incorporation of misinformation into memory due to leading questions, deception and other causes. Psychologists Elizabeth Loftus, PhD, and Stephen Ceci, PhD, are among those well-known in this research.

Biases are retrospective distortions produced by current knowledge and beliefs. Psychologist Michael Ross, PhD, and others have shown that present knowledge, beliefs and feelings skew our memory for past events. For example, research indicates that people currently displeased with a romantic relationship tend to have a disproportionately negative take on past states of the relationship.

Persistence is unwanted recollections that people cannot forget, such as the unrelenting, intrusive memories of post-traumatic stress disorder. For example, the case of Donnie Moore of the California Angels, who threw the pitch that, lost his team the 1986 American League Championship against the Boston Red Sox. Moore fixated on the bad play became a tragic prisoner of memory, and eventually committed suicide.

Misattribution is attribution of memories to incorrect sources or believing that one has seen or heard something one has not. Prominent researchers in this area include Henry L. Roediger III, PhD, and Kathleen McDermott, PhD. An illustration of it is the rental shop mechanic who thought that an accomplice, known as John Doe No. 2, had worked with Timothy McVeigh in the Oklahoma City bombing; he thought he had seen two of them together in his shop. In fact, the mechanic had encountered John Doe No. 2 alone on a different day.

Probing the neuropsychology of why people misremember having seen words with amnesiacs and normal participants, indicate that people’s normal tendency to remember the gist of a list of semantically similar words; a tendency missing in amnesiacs is also what causes them to misremember words not on the list. In the latest line of research, scientists are using imaging to detect the brain mechanisms at work in false and correct recognition of words and shapes, which highlights that by using cognitive neuroscience, we can start to home in on some of the brain mechanisms involved in each of the sins.


Brain, Not Eye Mechanisms Keep Color Vision Constant across Lifespan

Take pleasure in the moments! In the end, they are the only things we will have.

The color appearance mechanisms are to large extent unaffected by the known age-related changes in the optical media or yellowing of the lens whereas the ability to discriminate between small color differences is compromised with an increase in age. The approximate hue constancy across the life span could be explained by a concurrent parallel decline in cone signals. A mechanism that takes the difference between the L and M cone signals, for example, will not be greatly affected by a decline in both the L and M cone outputs. Hue constancy across the life span is not a simple consequence of the differential cone combinations of the higher-order chromatic mechanisms.

The human visual system can adjust the cone weightings of the chromatic mechanisms over the lifespan and thereby compensate for a decline in peripheral cone signals. This dissociation between discrimination and appearance mechanisms is supported by Neitz and colleagues who showed that shifts in unique yellow induced by long-term changes in the chromatic environment are not due to receptoral or sub-cortical changes, but must be of cortical origin, probably after chromatic information from both eyes has been integrated. The question remains how these higher order color mechanisms receive feedback on the strength of their cone inputs. The gains of the L and M cones are adjusted such that the red-green opponent mechanism is at equilibrium for the average daylight, but this recalibration is by no means complete. The brain uses information about the statistical properties of our chromatic environment to adjust the weighting of the receptor signals to achieve hue constancy across the life span.

The mean unique hue settings are not affected by the illumination conditions. There is a differential effect of adaptation on hue constancy only under daylight adaptation do the age-related changes in the green settings. What appears uniquely green for young observers appears more yellowish for older observers. Older observers require more S cone input to achieve unique green when the settings are obtained under simulated daylight, but still much less than predicted by the lens model. The yellow-blue mechanism; which is silenced by the unique green setting is most affected by the yellowing of the lens.

If the visual system were able to fully compensate for the changes in the optical media, the observed cone weightings should not vary with age. It is found that under most of the tested conditions, this is the case; only under adaptation to daylight, green hues changes slightly with age.

In summary, there are compensatory mechanisms operating on higher-order color functions and thereby ensuring that hue remains approximately constant despite the known age-related changes in the lens. The concurrent age-related decline in the chromatic discrimination sensitivity suggests that the neural site of these compensatory mechanisms is probably cortical; the underlying mechanism is still poorly understood, but is consistent with the idea that it is based on invariant sources in our visual environment.

How Biological Systems Stabilize Gait

Running cockroaches start to recover from being shoved sideways before their dawdling nervous system kicks in to tell their legs what to do, scientists have found. These new insights on how biological systems stabilize could one day help engineers design steadier robots and improve doctors’ understanding of human gait abnormalities. In experiments, the cockroaches were able to maintain their footing mechanically, using their momentum and the spring-like architecture of their legs, rather than neurologically, relying on impulses sent from their central nervous system to their muscles.

The response time observed is more than three times longer than you’d expect says Shai Revzen, an assistant professor of electrical engineering and computer science, as well as ecology and evolutionary biology, at the University of Michigan. What scientists see is that the animals’ nervous system is working at a substantial delay. It could potentially act a lot sooner, within about a thirtieth of a second, but instead, it kicks in after about a step and a half or two steps—about a tenth of a second. For some reason, the nervous system is waiting and seeing how it shapes out.

New findings imply that the biological brain, at least in cockroaches, adjusts the gait only at whole-step intervals rather than at any point in a step. To arrive at these findings, the scientists sent 15 cockroaches one-by-one, in 41 trials running across a small bridge onto a placemat-sized cart on wheels. The cart was attached to an elastic cord that was pulled tight like a loaded slingshot and held in place with a strong magnet on the other side. Once cockroach was about a body length onto the cart, the scientist released the magnet, sending the cart hurling sideways. The force was equivalent to a sumo wrestler hitting a jogger with a flying tackle.

To gather detailed information about the cockroaches’ gait, the scientists utilized a technique Revzen developed several years ago called kinematic phase analysis. It involves using a high-speed camera to constantly measure the position of each of the insects’ six feet as well as the ends of its body. A computer program then merges the continuous data from all these points into an accurate estimate of where the cockroach is in its gait cycle at all times. The technique gives scientists a more detailed picture than just measuring the timing of footfalls, a common metric used today to study gait.

In kinematic phase analysis, the signals are converted into a wave graph that illustrates the insect’s movement pattern. The pattern only changes when the nervous system kicks in. How do the scientists know this? In a separate but similar experiment, they implanted electrodes into the legs of seven cockroaches to measure nerve signals.

The nervous-system delay the scientists observed is substantially longer than scientists expected, and it runs contrary to assumptions in the robotics community, where computers stand in for brains and the machines’ movements are often guided by continuous feedback to that computer from sensors on the robots’ feet.

The new findings might imply that the biological brain, at least in cockroaches, adjusts the gait only at whole-step intervals rather than at any point in a step. Periodic, rather than continuous, feedback systems might lead to more stable, not to mention energy-efficient walking robots, whether they travel on two feet or six. Robot makers often look to nature for inspiration. As animals move through the world, they have to respond to unexpected disturbances like rocky, uneven ground or damaged limbs. Scientists believe that patterns in how they move as they adjust could give away how their machinery and neurology work together.

The fundamental question is, ‘What can you do with a mechanical suspension versus one that requires electronic feedback? The animals obviously have much better mechanical designs than anything we know how to build, but if scientists could learn how they do it, scientists might be able to reproduce it.

More than 70 percent of Earth’s land surface isn’t navigable by wheeled or tracked vehicles, so legged robots could potentially bridge the gap for ground-based operations like search and rescue and defense.

For human gait analysis, Revzen and colleagues’ noninvasive, high-resolution kinematic phase approach is valuable in the biomedical community. Falls are a primary cause for deterioration in the elderly. Anything scientists can do to understand gait pathology and stabilization of gait is very valuable. These experiments were conducted at the University of California, Berkeley, before Revzen came to University of Michigan


Now Scientists Can Make Old Brain Young

The flip of a single molecular switch helps create the mature neuronal connections that allow the brain to bridge the gap between adolescent impressionability and adult stability. Now, Yale School of Medicine researchers have reversed the process, recreating a youthful brain that facilitated both learning and healing in the adult mouse.

Scientists have long known that the young and old brains are very different. Adolescent brains are more malleable or plastic, which allows them to learn languages more quickly than adults and speeds recovery from brain injuries. The comparative rigidity of the adult brain results in part from the function of a single gene that slows the rapid change in synaptic connections between neurons.

By monitoring the synapses in living mice over weeks and months, Yale scientists have identified the key genetic switch for brain maturation a study released in the journal Neuron. The Nogo Receptor 1 gene is required to suppress high levels of plasticity in the adolescent brain and create the relatively quiescent levels of plasticity in adulthood. In mice without this gene, juvenile levels of brain plasticity persist throughout adulthood. When scientists blocked the function of this gene in old mice, they reset the old brain to adolescent levels of plasticity.

These are the molecules the brain needs for the transition from adolescence to adulthood says Dr. Stephen Strittmatter, Vincent Coates Professor of Neurology, Professor of Neurobiology. The findings suggest that we can turn back the clock in the adult brain and recover from trauma the way kids recover. Rehabilitation after brain injuries like strokes requires that patients re-learn tasks such as moving a hand. Scientists found that adult mice lacking Nogo Receptor recovered from injury as quickly as adolescent mice and mastered new, complex motor tasks more quickly than adults with the receptor.

This raises the potential that manipulating Nogo Receptor in humans might accelerate and magnify rehabilitation after brain injuries like strokes. Scientists also showed that Nogo Receptor slows loss of memories. Mice without Nogo receptor lost stressful memories more quickly; suggesting that manipulating the receptor could help treat post-traumatic stress disorder.

We know a lot about the early development of the brain, but we know amazingly little about what happens in the brain during late adolescence.

Managing Sleeplessness with Brief Behavioral Treatment for Insomnia

Although many patients find cognitive-behavioral therapy effective for management of their insomnia in both the short and long term, there aren’t enough clinical psychologists trained in the area. In addition, the initial treatment is lengthy, lasting 6 to 8 sessions. These are some of the barriers to such therapy. The clinical manual for the conduct of a shorter Brief Behavioral Treatment for Insomnia program has an explicit behavioral focus, is overtly linked to a physiological model of sleep regulation, and uses a hardcopy workbook that facilitates its concise delivery format and ease of training clinicians.

The rationale behind Brief Behavioral Treatment for Insomnia is that insomnia often is characterized by sleep-related behaviors that interfere with the underlying physiological mechanisms that regulate sleep homeostatic and circadian processes. Therefore, treatment involves modifying waking behaviors to increase and regulate the duration of wakefulness, thereby increasing the homeostatic sleep drive, sleep pressure and identifying an individualized prescription for sleep and wake time that optimizes and reinforces the circadian called internal biological clock drive for sleep. Optimizing these processes facilitates the ability to fall asleep and stay asleep and promotes improved sleep quality and daytime functioning and alertness.

Cognitive-behavioral therapy is used to manage a variety of behaviors and cognitive processes, including insomnia. Behavioral therapy for insomnia has several components, including sleep education, sleep restriction, stimulus control, and addressing anxiety-provoking beliefs about sleep. As the name suggests, Brief Behavioral Treatment for Insomnia is a 4-session intervention that focuses on modifying specific behaviors that may perpetuate insomnia.

Brief Behavioral Treatment for Insomnia is designed to be administered via 2 in-person sessions and 2 telephone sessions as part of a clinical research study published in Archives of Internal Medicine in 2011.2. In the original research study, Brief Behavioral Treatment for Insomnia was targeted toward older adults with comorbid conditions because the prevalence of insomnia is particularly high in this patient population, which often is under-represented in controlled research trials. However, beyond this clinical trial Brief Behavioral Treatment for Insomnia is used in the clinic setting for diverse populations, including older and younger adults with and without other co-occurring medical or psychiatric conditions.

Behavioral sleep interventions are as effective as sleep medications and typically have more lasting effects. Also, behavioral sleep interventions have fewer adverse effects than medications. Many patients prefer behavioral interventions over pharmacological ones because of concerns about becoming dependent on medications or potential consequences associated with long-term use. Use of sleep medications in older adults is a particular concern because of the increase risks of falls among those taking them.

Many patients continue to take sleep medications as adjunct therapy along with Brief Behavioral Treatment for Insomnia. For patients who choose to use medication as an adjunct therapy, recommendations are as follows:

Take your medication proactively at the beginning of the night, rather than reactively, after frustrated attempts to fall asleep without medication.

Take the medication at the right time, when you begin to feel naturally sleepy, rather than far too early in the night, hoping that it will “knock you out” before the natural drive for sleep is at its peak.

When ready to discontinue the medication, do so gradually, rather than abruptly, to minimize rebound insomnia and withdrawal effects.

Brief Behavioral Treatment for Insomnia is designed as an intervention that could be more widely disseminated, including to primary care practices. Brief Behavioral Treatment for Insomnia is administered by psychiatric nurse who did not have previous training in sleep medicine or behavioral interventions, suggesting that it could be a viable intervention with wider dissemination beyond specialty clinics. To date, however, there has not been a systematic effectiveness trial of Brief Behavioral Treatment for Insomnia in the primary care setting.

The clinical manual provides a detailed description of the program and is published in the journal article. Also, training sessions are offered through the University of Pittsburgh Sleep Medicine Institute as well as at national conferences and local meetings.

Neurobiology of Scale-Invariance

Image Credits: Paul Paradis

The scale-Invariance term indicates various properties like self-similarity or spatial scale-invariance, avalanche dynamics or temporal scale-invariance and complex networks or topological scale-invariance.  Generally speaking, scale-invariant systems have some properties that remain constant when looking at them either at different length or time scales. Constant quantities allow prediction of future behavior, no surprise that conserved quantities are fundamental in physics. This invariance is somewhat different though; still it can be used to extract useful information.

Visual perception is far more complex and powerful than our experience suggests.  Moreover, in attempting to understand vision and implement it in a computational device, the fact that a species’ senses developed in concert with the ecological niche in which that species evolved is a natural consideration; in this case, that means an evolutionary visual context consisting of natural objects, including mountains, rivers, trees, and other animals. Noting that neural representations of visual inputs are related to their statistical structure, natural structures display an inseparable size hierarchy indicative of scale invariance, and scale invariance also occurs near a critical point in wide range of physical systems including ferromagnetic; researchers at the Salk Institute for Biological Studies and the University of California-San Diego recently demonstrated what their paper describes as a unique approach to studying natural images by decomposing images into a hierarchy of layers at different logarithmic intensity scales and mapping them to a quasi-2D magnet.

The traditional way images are represented in vision is by an array of pixels with gray levels.  However, we know that visual perception is based on a log scale of luminance. The challenge was to find a new representation that would make the log levels explicit.  The idea was in using bit planes, later generalized to power in any integer base.  Scientists started looking at the bit planes of natural images.  It became apparent that each layer looked like a 2D Ising model at different temperatures; that is, the high-order bits were cold and the low order bits were hot.  An Ising model is a mathematical model of ferromagnetism in statistical mechanics, consisting of discrete variables that represent magnetic dipole moments of atomic spins that can be in one of two states (+1 or −1). Taken together, these bit planes represent a 3D quasimagnet with interesting properties. Understanding retinal encoding and possibly obtaining further insight into how the neocortex represents scale invariance requires, in turn, an understanding of the statistical structure in natural image hierarchies. Moreover, the brain is not a passive image receptor, but rather actively generates sensory models derived from sensory experience. The Bolzmann machine is a device that spin glasses with arbitrary connectivity running at a finite temperature, generalizing Hopfield nets, which run at zero temperature can represent image statistical structure.  Application of this idea is a unique approach, in which certain aspects of the Boltzmann machine’s input representations are learned from natural images.

There is remarkably simple learning algorithm that finds the connection weights for a network that could represent the probability distribution for an ensemble of inputs.  When scientists applied Boltzmann machine learning to natural images as inputs, they found positive pairwise connections that fell off with distance on each layer, much like the 2D Ising model for a ferromagnet, and negative pairwise weights between the layers, representing antiferromagnetic interactions. The theory of second-order phase transitions is vital to understanding the significance of what the scientists had found.  There are 15 bit planes corresponding to pixels with 15 bit integers, each corresponding to a different temperature.

Scale invariance had been observed in natural images for decades based on the power law drop-off in power as a function of spatial scale.  At a phase transition, the spatial correlation length becomes infinite and there is a critical slowing. This suggests that the reason there is structure at every spatial scale in the natural world is because nature is, in some sense, sitting at a phase transition between order and disorder. In terms of the evolution and neurobiology of perceptual invariants, the biological systems that have evolved to survive in this world may take advantage of this structure, and in particular the organization of the visual system may reflect those statistics and most of the information in natural images is captures in 3 bit planes, which may be why photoreceptors are linear over a single order of magnitude. Adaptation mechanisms in the retina shift the linear region over 10 orders of magnitude in luminance.  Scientists have trained the Boltzmann machine on only the connections between pixels in the "visible" input layer. The next step is to use this as the input layer in a hierarchy of hidden layers, such as that found in human visual systems, which are around 12 layers deep.  There are great advances in computer power and algorithms that now allow Boltzmann machines to be trained in deep networks. In the longer term, this new input representation may benefit computer vision.

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