Literary Insights

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This is an incredibly moving story about the resilience of the human brain and spirit. While undergoing such a drastic surgery at a young age seems unfathomable, it’s remarkable that Matthew was able to thrive afterwards, showing the brain’s amazing ability to adapt and compensate. His story demonstrates the profound plasticity of the human mind.

Matthew, a young boy, was suffering from severe epilepsy and experiencing multiple seizures daily. His parents Valerie and Jim tried various treatments but nothing worked.
As a last resort, Matthew underwent a hemispherectomy surgery at Johns Hopkins hospital to remove half of his brain. This is an extremely rare and risky procedure.
The surgeon carefully removed half of Matthew’s brain over several hours. His parents waited anxiously to see if Matthew would survive and what condition he would be in after losing half of his brain.
The passage explains that the human brain is incredibly complex with over 80 billion neurons and hundreds of trillions of connections. It is a dynamic system that is constantly changing based on our experiences.
Even though Matthew had half his brain removed, the hope was that his remaining brain connections could rewire and adapt based on his experiences going forward. His parents waited to see if he could have any semblance of a normal life after such a drastic surgery.
The passage discusses how the brain is constantly reconfiguring and adapting through competition between neurons and neural connections. Territories are constantly being redrawn based on life experiences and goals.
If a person changes careers, the areas of the brain associated with the skills of the new career will expand, while others may shrink. This allows the brain’s resources to match what is important.
The brain operates through a principle of survival of the fittest competition among its parts. It sculpts and modifies its internal structure based on external challenges and goals. This allows it to operate rapidly and efficiently for important tasks.
Unlike technology which has fixed hardware and software, the brain is continually adapting and “livewiring” itself based on experiences. It is not static but always developing and changing in response to the world.
The concept of neuroplasticity captures how the brain can be molded by experience, but a better term is “livewired” to describe its ongoing adaptive nature throughout life rather than a single event of molding.
The story of Matthew illustrates how even after losing half his brain, he was able to dynamically rewire and take over missing functions, allowing him to live a normal life with little indication of his injury through the brain’s remarkable ability to reconfigure itself.

The passage encompasses the idea that our brains are dynamic, living systems that are shaped significantly by our experiences and environment, not just our genetics. It discusses how brain structure and function can change based on the richness of one’s experiences.

Early research on rats found that those raised in enriched environments with toys and stimuli had more elaborate dendrites (neural branches) and performed better on learning tasks than those in deprived cages. Similar effects have been found in other species including humans. Our brains require stimulation and interaction with the world to fully develop.

While genetics provide an initial blueprint, the human genome contains only around 20,000 genes, far fewer than expected given our brain’s complexity. The genome’s strategy is to build the brain in an incomplete state and let experiences refine and calibrate it. Things like our circadian rhythm and visual system require normal inputs to develop properly. The flexibility of the brain allows our life experiences to directly sculpt its structure and wiring over time. Experience is necessary to fully grow a good brain.

Put simply, the development of cortical connections in the brain is experience-dependent rather than genetically pre-specified. With so many neuronal connections and relatively few genes, the brain requires interaction with the world during development for its proper formation.
Early experiences like social interaction, sensory input, play, etc. shape the development of the brain as it forms the massive number of neuronal connections from a small set of genetic instructions. This makes the brain’s development dependent on environmental influences.
Without sufficient interaction and input during critical periods of development, the brain may not form typical connections and structures, as evidenced by cases of severe sensory deprivation or isolation in humans and animals. Proper development requires receiving the necessary inputs from one’s environment and experiences.

So in summary, the brain relies on experience with the world, rather than just genetic factors, to fully develop the elaborate networks of neuronal connections it requires - making its development experience-dependent rather than pre-determined. Depriving the brain of typical experiences can impair its formation and wiring.

Areas of the motor cortex that control finer, more detailed sensations and movements take up more space in the homunculus map of the body in the brain. This includes areas like the hands and face.
The homunculus maps were discovered to rearrange and adapt when Edward Taub severed nerves in monkeys’ arms and legs, causing them to lose sensation in those limbs. Years later, when one of the monkeys was put under anesthesia before euthanasia, researchers mapped its brain and found the areas that previously represented the nerve-severed limbs had been taken over by neighboring areas, adapting the homunculus to match the monkey’s new body plan.
This discovery showed that the homunculus maps are not genetically pre-programmed, but rather flexibly defined by active inputs from the body. When the body changes due to injury or other factors, the maps in the brain rearrange to match.

So in summary, the finer motor control areas take up more space in the homunculus maps, and the maps were found to rearrange and adapt when sensory inputs from the body change due to things like nerve severing injuries.

When parts of the body are damaged or deprived of sensory input, the brain dynamically reallocates the cortical territory formerly representing that part of the body. Nearby regions will colonize and take over the unused brain areas.
This applies to sensory loss from injuries like amputations or long-term sensory deprivation from things like limb immobilization. The brain’s map of the body changes as it loses input from parts of the body.
The same process occurs in cases of sensory loss like blindness. When visual input is lost, areas of the occipital cortex that normally process vision are taken over by other sensory systems like touch, sound, smell, etc. These areas can become active when processing non-visual sensory information.
This cortical reorganization and reallocation follows principles of neural plasticity - neurons that fire together wire together, so areas processing similar types of incoming information from different senses will converge in the brain.
Even after reorganization, some traces of the original architecture remain, like areas for visual language or motion processing being reused for tactile language and motion in the blind. This suggests the brain is organized more by computational tasks than specific senses.

Here are the key points about brain regions and reorganization:

Brain regions care about solving certain types of tasks, not the sensory channel that provides the information. So visual cortex can take over non-visual tasks if vision is lost.
The degree of cortical takeover/reorganization depends on age - it’s most extensive if a sense is lost early in life during development. The adult brain is less flexible.
When a sense is lost, the corresponding sensory cortex gets reallocated to other tasks. For example, visual cortex in blind people or auditory cortex in deaf people.
This leads to enhanced abilities in the remaining senses as more cortical territory is devoted to them. Examples given are enhanced musical ability in blind people and enhanced vision in deaf people.
More cortical territory devoted to a task allows for better performance, even if it’s a simpler task compared to normal abilities. For example color-blind people distinguish shades of gray better.
Neural redeployment shows brain areas are flexible and not predetermined. The organization changes based on the inputs received.
Some disorders like autistic savantism may arise from suboptimal cortical distributions that devote too much territory to one task at the expense of others.

So in summary, brain regions focus on task type over sensory modality, and loss of a sense leads to cortical reallocation that can enhance remaining abilities through devoted more cortical resources.

The visual cortex is disadvantaged every night as the planet rotates into darkness, depriving it of visual input for 12 hours. This puts it at risk of being taken over by other senses like touch, hearing, etc.
Neural plasticity causes territories to rapidly shift and change when deprived of activity. The visual cortex could lose territory to other senses overnight without a way to stay active.
Dreaming keeps the visual cortex active at night by stimulating it with bursts of activity originating in the brainstem. This activates the occipital cortex and prevents it from being taken over.
During REM sleep when dreaming occurs, the brainstem circuits stimulate only the visual cortex, not other areas. This precise targeting suggests dreaming has an important evolutionary role - to keep the visual cortex intact.
Dreaming evolved as a mechanism for the visual system to defend its territory against takeover each night, driven by the rotation of the planet that deprives it of visual input for half our lifetime. It helps the visual cortex survive the unfair disadvantage of nightly darkness.
Michael Chorost was born with hearing loss and used a hearing aid, but lost all remaining hearing when the battery died and he couldn’t replace it effectively.
He underwent cochlear implant surgery, which involves implanting a miniature computer into the inner ear to bypass the damaged parts and stimulate the auditory nerve directly with electrical signals.
At first, the signals sounded like nonsense but his brain gradually learned to interpret them. With practice over months, he regained the ability to use the phone, converse in noisy places, etc.
Cochlear implants have been available since 1982 and over 500,000 people have them. The implant’s software is upgradeable without further surgery, allowing improved hearing quality over time.
Terry Byland lives near LA and was diagnosed with retinitis pigmentosa, a degenerative retinal disorder that causes vision loss. He will likely require an implant to bypass his damaged retina in the future.
Terry underwent an experimental procedure in 2004 where he had a bionic retinal implant chip implanted in his eye. This was one of the first such procedures.
The chip has a grid of electrodes that plug into the retina. A camera beams signals to the chip which stimulates retinal cells with small electric zaps, allowing basic vision.
At first Terry could only see small specks of light, but over time his brain learned to make better sense of the signals. He started to be able to detect the presence of his son and navigate obstacles.
While the resolution is low, the implant has opened a “crack in the door of darkness” for Terry, allowing basic visual perception. His experience shows how the brain can learn to interpret artificial inputs from implants.
The brain figures out how to extract meaning and patterns from the signals it receives, regardless of where they come from. This allows for potential prosthetics and sensory implants, as the brain can adapt to new input sources.
Baby Eli was born without a nose, lacking a nasal cavity or sense of smell. Similarly, Baby Jordy was born without eyes beneath his eyelids.
Some conditions where sensory organs are missing include anotia (absent external ears), complete deafness from missing structures of the inner ear, and being born without a tongue like Brazilian baby Auristela.
Some children are also born without pain receptors in their skin and organs, leaving them unable to feel pain which can lead to injuries.
These sensory deficits occur due to minor mutations affecting specific genetic programs for developing peripheral sensory organs.
Paul Bach-y-Rita experimented with sensory substitution by transmitting video feed information to a blind person’s back via a grid of movable tips, allowing them to identify objects through touch alone. Later improvements let subjects control the camera themselves. This demonstrated the brain’s flexibility in adapting to alternative sensory inputs.
In the late 1960s and early 1970s, Dr. Paul Bach-y-Rita developed a device that used a grid of solenoids on the back of blind individuals to stimulate the skin and allow them to “see” images transmitted from a camera. This proved that the brain can learn to interpret visual information received through non-visual sensory channels.
Earlier attempts at sensory substitution included a device in the 1890s called the Elektroftalm that transmitted light intensities to the forehead as sounds, and another 1960s Polish device that used vibrations on a helmet to represent images. However, these were bulky and impractical.
The theory is that the brain is a general-purpose processing system that can learn to interpret any type of incoming sensory data, not just visual, auditory, etc. The cortex develops specialized functions based on the type of inputs it receives, not by innate specification.
Experiments showed transplanted or rerouted neural tissues and pathways can adapt to new input types, supporting the idea that cortical areas are shaped by experience, not predetermined functions.
Later versions like the BrainPort miniatured the technology, transmitting camera images to a small grid of electrodes on the tongue. Blind users could learn to perceive and interpret the stimulations as visual information like shapes and motion. This demonstrated vision can arise from non-visual brain processing of sensory input.
The passage discusses several technologies that allow blind people to regain a form of vision through non-visual senses like touch or hearing.
It describes BrainPort, which converts camera images to patterns of vibration on the tongue that the brain can interpret as vision. Tests found blind users could visually see objects.
Methods developed in Japan deliver video input as patterns of touch on the forehead or abdomen.
In the 1960s, Professor Kay created ultrasonic glasses that used sound to represent visual input from the environment. Tests found blind babies could learn to “see” with them.
In the 1980s, Peter Meijer developed the vOICe system, which converts video to sound patterns the brain can learn to interpret as sight over months of use. Tests found blind users regained a strange low-resolution form of vision through sound.
More recent apps have further developed these techniques, allowing blind people to access visual information through their phones and hearing. The brain can learn to “see” regardless of the sensory modality used.
Sensory substitution devices aim to help visually impaired or deaf individuals perceive the world through non-visual or non-auditory senses, like touch. Different technologies use things like vibrating pads on the tongue, vibrations through headphones or vests, to translate visual or sound inputs into tactile outputs.
At first these new senses require translation, but with practice the brain can learn to interpret the inputs directly, gaining a perception of the outside world similar to sight or hearing. Examples of devices discussed include a tongue display unit, vibratory vests and wristbands.
Studies with deaf individuals found they could learn to identify spoken words through vibration patterns after training. Deaf children using a vibratory chest strap started responding to sounds in their environment.
While complex, the skin can transmit sound information through vibration if the data is compressed. This transfers the function of the inner ear to the skin. Early experiments in 1923 found a deaf-blind girl could identify spoken words through vibrations on her fingertips.

So in summary, it discusses the potential for sensory substitution devices to help those with sensory impairments perceive the world through alternative senses like touch, by translating visual/auditory inputs into tactile outputs the brain can learn to interpret.

Researchers have found ways to communicate through touch by transmitting vibrations through glass tubes or having deaf-blind individuals place their hands on a speaker’s face to feel vocal vibrations and lip movements. This led to the development of vibrotactile devices that could translate sounds into vibrations felt on the body.
These early devices were large and had limited computational power, but newer technologies allow for more sophisticated and smaller devices that could make sensory substitution more practical. Using touch to substitute for lost senses has advantages over cochlear implants in being lower cost and non-invasive.
Translating inputs from prosthetic limbs or sensors on a sock into vibrations felt on the body through a wristband can restore lost sensation and feedback, helping with tasks like walking and balance. Training with these devices can strengthen residual signals in the brain over time.
Sensory substitution provides compensation, but enhancement aims to not just fix deficits but improve senses beyond normal levels. Examples given include a color-blind artist who perceives color as sound through a device, and genetically engineering animals for enhanced color vision capabilities. Accidental enhancements can also occur through medical procedures and technologies.
Traviolet light allows some people to see objects with a faint blue-violet glow that others cannot see. One man with a cornea replacement can now see this glow and discover objects have a hue he was unaware of before.
Biohackers have experimented with expanding human perception beyond normal senses. One implanted a magnet in his finger to sense magnetic fields, giving him a new form of touch perception.
Technology is allowing researchers to enhance, expand, or create novel senses in humans. Experiments have given vision in 360 degrees, allowed blind people to “see” with lidar, and allowed a rat to incorporate infrared detection into its sensory abilities with ease.
The brain is highly adaptable and new sensory inputs can be integrated smoothly. This points to possibilities for sensing magnetic fields, radio signals, smells beyond our range, and even creating entirely new synthetic senses. Expanding human perception moves beyond normal biological limitations.
Scientists developed a wearable belt called the feelSpace that uses vibratory motors to indicate magnetic north direction. Test subjects who wore the belt found their spatial orientation and navigation abilities improved over time as they intuitively integrated the magnetic directional cue.
Early pilots had to rely heavily on tactile feedback from their seats (“flying by the seat of their pants”) to sense aircraft pitch, roll, and other movements with limited instrumentation. Modern cockpits provide abundant instrument readings, but require visual scanning which is slow. Developing wearables to feed pilots high-dimensional flight data tactilely could improve situational awareness.
Beyond aviation, feeding back real-time data from factories, surgery patients, space stations, or partners could allow direct perceptual experiences of complex systems beyond normal human scale or provide new depths of mutual understanding in relationships. With training, vibratory patterns may convey weather patterns, stock markets, or other datasets in intuitions extractable by the brain. The goal is developing new forms of human experience and perception through sensory addition and expansion.
The passage discusses the possibility of a new type of human experience enabled by directly connecting data streams to the human body, specifically the skin, rather than traditional senses like vision or hearing.
One example given is connecting a stock trader’s skin to high-dimensional stock market data to allow intuitive perception of market trends.
Another example is creating a “Tweety sense” by connecting a person to sentiment analysis of millions of tweets in real-time, giving a sense of the global zeitgeist and issues capturing public attention worldwide.
This could allow sensing information and patterns beyond what an individual human could normally perceive. However, some questions are raised about directly connecting humans to vast data streams.
The passage also discusses the technological progress being made towards directly interfacing the brain with data, such as through brain implants, neural dust, or nanorobotics. This could eventually allow reading and writing signals at the level of individual neurons.

So in summary, the passage considers new augmented human experiences that may be possible by directly connecting the body and brain to various data sources, and the technological approaches being developed towards realizing this. Both opportunities and challenges are discussed.

The brain processes all sensory inputs (sight, sound, touch etc.) as electrical signals, but these feel qualitatively different to us. Why do vision and taste feel so distinct?
One hypothesis is that the structure of the data determines the subjective experience or “qualia”. Vision data comes from the retina in 2D, sound from the eardrum in 1D, touch is multidimensional. Our interactions with each sense also differ.
This suggests we could feed a new data stream directly to the brain, like from a robot or sensor, and it could develop into a novel qualia over time as patterns are learned.
However, a new qualia would be impossible to describe or imagine to others without experiencing it directly. Language only applies to shared experiences.
New senses might be learned through things like galvanic skin response devices, environmental sensors, or direct brain interfaces. The limits are unknown but the brain seems adept at sharing cortical territory among senses.
Developing extra senses could potentially come at the cost of reduced resolution for existing senses, due to finite cortical space. But experiments suggest senses don’t always engage in “winner-take-all” competition for territory.
The passage discusses the concept of adding new senses or enhancing existing ones through technology. It uses examples like cochlear implants, retinal implants, and sensory substitution devices.
The brain has flexibility to incorporate new sources of sensory data. It can “rewire” cortex regions to absorb new data streams, treating them as additional senses. This allows sensory enhancement or addition.
New senses may carry emotional meaning and associations, similar to how existing senses like smell, sound and vision are linked to emotions. Data streams can potentially elicit pleasure, pain and other feelings.
while adding senses may seem strange, the brain is accustomed to incorporating large amounts of sensory data. New senses are unlikely to be overwhelmingly stressful as the brain is good at merging information into our experience.
Future sensory technologies could allow perception in new parts of the electromagnetic spectrum, ultrasounds, or access to internal physiological states. This may lead to individuals customizing their own enhanced sensory abilities.
Overall the passage discusses the brain’s flexibility in incorporating new sources of sensory information through technology. This could allow enhanced or added senses in the future as interfaces become more advanced and wearable.
The idea of directly connecting a human brain to robotic limbs, allowing the brain to control the robotics, has shifted rapidly from science fiction to reality.
When a person loses a limb, their brain reorganizes itself over time. The motor cortex adjusts, with the areas that previously controlled the lost limb taking over control of remaining body parts. This shows how the brain optimizes itself to control the body it has.
This flexibility provides an opening for direct brain-machine interfaces. If the brain can naturally adjust to new body configurations, it may be able to control artificial limbs and tools attached externally through technology. Researchers are working to develop brain-computer interfaces that could allow paralyzed people to regain movement.
Examples from animals also demonstrate the brain’s ability to adapt. Dogs born without legs can learn to walk on two legs, and dogs have learned to surf, skateboard, demonstrating their ability to control new devices not part of natural dog evolution. This points to the brain’s fundamental adaptability to available “motor machinery.”

So in summary, the brain’s natural ability to reorganize motor control in response to body changes lays a foundation for directly connecting brains to robotic prosthetics through emergent brain-machine interface technologies.

Motor babbling is how humans and animals learn new motor skills like riding a bicycle. The brain tries out different movements and uses feedback from the environment to refine its actions.
Destin Sandlin had trouble learning to ride a bicycle where turning the handlebars left turned the wheel right, and vice versa. It required unlearning normal bicycle steering and retraining his motor cortex through practice and feedback.
Context is important - the brain runs different “programs” or schemas for different activities like bicycling, jogging, or driving. It subconsciously changes motor functions based on surroundings.
Babbling robots like Starfish use a similar process, making random movements and sensing feedback to build a model of their own body over time.
Skateboarding and surfing dogs master new skills through motor babbling - trying different techniques and positions, then adjusting based on whether they succeed or fail at tasks like balancing on a wave.
Social and problem-solving skills may also develop through a process of throwing out options, seeing what works, and refining based on feedback, similar to motor learning.
Motor babbling allows animals to adapt their brains to new body plans without complete redesign, supporting flexibility and biodiversity. The brain recalibrates to new contexts through feedback-driven learning.
The human brain has an amazing ability to learn to control new bodies and tools as natural extensions of itself, like Ripley controlling a mechanized suit in Aliens. This flexibility allows us to learn skills like skiing, surgery, and operating machines.
Disabled people like Jean-Dominique Bauby who suffered locked-in syndrome due to a stroke show the tragedy of losing control of one’s body. Advancing brain-machine interfaces try to restore movement by decoding motor cortex signals and using them to control prosthetics.
Early successes included people controlling computer cursors and artificial limbs through implants that monitor motor cortex activity. Continued research aims to develop thought-controlled robotic exoskeletons that can allow paralyzed people to walk again by bypassing spinal cord injuries. This shows the potential for neuroprosthetics to restore lost functions by treating the brain like a software system that can control different “hardware”.
Paralyzed participants are able to control robotic arms and hands through brain-machine interfaces, allowing them to grasp objects, manipulate them, and release them. They can even move individual fingers to do tasks like dial a phone or use a keyboard.
However, without sensory feedback from the robotic limbs, it is difficult to judge how much force to apply or whether something is grasped properly. Researchers are working on closing this feedback loop by sending patterns of neural activity to the somatosensory cortex, allowing participants to “feel” textures through the robotic limbs.
Monkeys have been able to control a third robotic arm implanted in the brain in addition to their two natural arms. With training, the monkeys’ brains separated the control of the real and robotic arms. This shows the brain’s ability to incorporate external limbs as new extensions of the body.
Brain-machine interfaces have also allowed a monkey to control a robot hundreds of miles away in real-time. With extensive training to decode neural signals, researchers were able to have the monkey and remote robot walk synchronously based only on the monkey’s brain activity. This demonstrates the future potential for controlling remote robots and prosthetics from a distance.
Avatar robotics allows people to control robots remotely and experience what the robot senses, through haptic feedback gloves. This gives a limited ability to experience different bodies.
Virtual reality offers a better way to explore unusual body plans by rendering virtual avatars. People can quickly adapt to controlling new virtual bodies with different numbers of limbs, sizes, etc. Studies have shown people can learn to accurately control a third virtual arm.
Changing one’s virtual body may change aspects of one’s thinking and behavior, as evidenced by studies where taking on avatars of other genders/ages influenced financial decisions and nurturing behavior.
In real life, a man with a bionic arm that has fewer limitations than a normal arm found he could think and do things not possible with a biological body, like continuously rotating his hand.
Exploring unusual virtual bodies through VR could enhance empathy and allow speeding up of human evolution by experiencing bodies evolution never produced, opening up new possibilities for thinking and abilities.

Here is a one paragraph summary:

The passage discusses how the brain physically changes and reorganizes based on what tasks a person engages in regularly through extensive practice. It provides examples of how the motor cortices of highly trained musicians like violinist Itzhak Perlman and pianist Vladimir Ashkenazy have distinct structures based on the specific movements and finger patterns required for their instruments. The passage emphasizes that repeated practice is necessary to reshape the brain’s circuitry and automate skills, highlighting the concept of the “10,000 hour rule” for achieving expertise in an area.

The brain changes and develops based on a person’s experiences, environment, and what they dedicate time and effort to learning. For example, medical students’ brains change when studying for exams, and London taxi drivers develop an enlarged hippocampus from navigating the city.
The Polgár sisters became champion chess players through dedicating countless hours to practicing and mastering the game. Their expertise developed from sculpting neural pathways through repeated exposure.
Brains form internal “landscapes” or representations based on what is important and relevant in a person’s world. For example, people now interpret minor leg twitches as a phone vibration due to phones’ importance. Infants also develop different internal representations of sounds depending on the language they are exposed to.
The brain is flexible and receptive to change, but goals and desires play a key role in shaping how and when it reorganizes. Faith the two-legged dog was able to learn to walk on two legs because it solved her goal of reaching food. Repetitive practice alone is not enough - the brain only changes when practice is aligned with internal goals and incentives.
The brain undergoes plastic changes based on what is rewarded or relevant, not just external inputs. Fred Williams gets no better at tennis because he derives no reward or motivation from it.
Constraint therapy for stroke patients works by forcing the use of the impaired arm through strapping down the good arm. This engages the brain’s natural motivations and rewards improvement, leading to neural changes that recover function.
Neuromodulators like acetylcholine trigger plasticity by increasing when events are salient or rewarding. They mark what is important for the brain to encode better. Acetylcholine release during a task improves learning and performance through expanded cortical maps, while blocking it prevents improvement.
Without engagement of these neuromodulatory systems, just repeating a task provides no reward signal and leads to no neural or behavioral changes, even with extensive practice like Fred Williams putting in hours of unrewarding tennis work. Reward and motivation are needed to trigger the brain changes underlying skill learning.
Neuromodulators like acetylcholine are involved in modulating neural plasticity and learning in the brain. Acetylcholine turns on plasticity, but other neurotransmitters like dopamine encode whether something was rewarding or punishing to direct the type of neural changes.
London taxi drivers who memorize the city’s map show physical changes in brain structure due to learning a relevant task. However, with GPS and maps now easily accessible, the need for such rigorous memorization has diminished.
In contrast, AI can accomplish vast feats of memorization but lacks relevance - it does not care which problems are more interesting or important to humans. This limits AI’s ability to be truly human-like.
Effective learning requires engagement and curiosity to trigger the right neuromodulators for plasticity. Traditional classrooms often fail to do this. Alternative approaches like questioning styles, adaptive learning programs, and gamification can better individualize learning and maintain engagement.
While the future of education with technology looks promising, it is difficult to study exactly how growing up immersed in screens may affect brain development, due to a lack of control groups without similar digital exposure for comparison. Nonetheless, constant online access to information represents a profound change from the past.

The article discusses how our visual perception can be actively recalibrated by prolonged exposure to certain stimuli. It gives several examples of visual illusions and aftereffects that demonstrate this.

One example is the motion aftereffect, seen when staring at something moving in one direction (like a waterfall) and then looking elsewhere - the other objects appear to move in the opposite direction briefly. This is because the brain adjusts its baseline expectation of motion after prolonged exposure.

Other examples given include the illusions experienced after getting off a boat or treadmill, where the stationary land/walls appear to move due to the brain’s recalibrated expectations.

The article also describes an experiment where subjects stared at alternating red and green lines for minutes. After, when looking at plain black and white lines, the spaces took on the complementary colors - again showing how the brain actively recalibrates its assumptions.

Finally, it explains how in the 1980s, some people who used early green-screen computer monitors extensively saw printed text as appearing reddish afterwards. This was because their visual systems had recalibrated to expect horizontal lines to be green.

So in summary, the article uses several visual illusions and aftereffects to demonstrate how prolonged stimulus exposure can actively recalibrate the brain’s perceptual baseline or expectations.

The passage discusses how the visual system works to make expected or unchanging stimuli invisible over time through a process of adaptation. This is because the brain’s goal is to only represent unexpected information that could provide useful information about changes in the environment. Anything that remains constant and predictable is “predicted away” and ceases to be consciously perceived. Several optical illusions are presented that demonstrate this principle, such as the Troxler effect where fixed blobs in peripheral vision fade over time, or how blood vessels on the retina are invisible due to their unchanging position. This process of adapting to and predicting away constant inputs helps the brain conserve energy and neurological resources to focus on detecting genuine changes in the environment.

When people start wearing a device that picks up sounds from their wrist, they are surprised by how loud certain predictable sounds are, like their own voice, flushing toilets, closing doors, footsteps. This is because the brain normally predicts and filters out these expected sounds.
The brain builds an internal model of the world to make predictions. It pays more attention to things that don’t match expectations to update its model. This allows it to focus on new or unexpected stimuli while ignoring predictable ones.
Neural predictions and attention are the key to learning - the brain only needs to change when predictions are incorrect. Blocking occurs when new stimuli are predicted by old cues and so are not independently learned.
Drug addiction occurs because consumption changes the brain’s receptors to expect the drug, requiring more to have an effect. Withdrawal occurs when the expected substance is absent.
The brain forms expectations of close people, so their loss results in withdrawal-like effects as predictions are unmet. Over time the brain must readjust its internal model.
The brain works to maximize the information it receives through a process of “infotropism,” constantly shifting circuits like plants growing toward light or bacteria moving toward food sources. It optimizes its interaction with the world through reward-based learning.
When certain areas of the brain are damaged or missing due to injury, disease, or abnormalities, the brain can radically rewire itself to maintain functionality.
In one case described, a girl named Alice was born with only the left half of her brain. Despite this, she developed normally and had normal vision. Her visual system rewired such that both visual fields were represented in the single remaining hemisphere.
Another case involved a man named Matthew who had one hemisphere surgically removed. He was still able to live independently with some minor impairments. His remaining hemisphere rewired to take over necessary functions.
Studies in frogs showed that if half the optic tectum (part of the visual system) is removed early in development, the visual map compresses to fit onto the smaller remaining territory, with a full map still present.
This indicates the brain has an impressive ability to radically rewire its maps and functions to maintain normal operation even when large areas are damaged or missing. The cerebral maps can squish onto half the previous territory while retaining relationships and tasks.
Experiments were done transplanting extra eyes onto tadpoles. The optic tectum (where retinal fibers project in the brain) accommodated the additional input by dividing its territory into alternating stripes, with each stripe containing a full map from one eye.
When half the retina was removed in another experiment, the map stretched out to utilize the entire, normal-sized tectum territory instead of just half.
This shows that neural maps are flexible and can compress, stretch, or share territory as needed based on the available input and space.
After brain damage or stroke, major cortical reorganization can occur over months/years as functions shift to different areas, showing the brain’s ability to dynamically rewire.
At the neuronal level, there is constant competition as each neuron fights for resources and tries to maintain its territory through ongoing activity and input. Loss of input causes neurons to change connections and seek new areas of activity.
Experiments in visual cortex showed maps are experience-dependent and can be altered by early deprivation of one eye. The competition framework explains these and other findings about how brain maps form and change.
Neurons compete for neurotrophins, which are proteins secreted by their target neurons that act as life-preserving chemicals. Getting enough neurotrophins allows neurons to thrive, while neurons that don’t receive enough eventually die.
In addition to seeking neurotrophins as a reward, neurons also avoid toxic factors that can eliminate existing synaptic connections or cause axons to be eliminated if they become inactive.
This system of attractive and repulsive molecular signals provides feedback to neurons on whether they should stay connected, grow more, shrink, seek out new connections, or die off to help optimize the system.
A balanced level of excitatory vs inhibitory neurotransmission is important for maintaining flexibility in the neural networks. Too much inhibition locks everything down, while too little leads to excessive, uncontrolled competition.
Rapid changes in the brain can occur through the unmasking of existing silent synaptic connections that were previously inhibited. Disinhibition allows these weaker connections to become functionally activated.
Over longer timescales, new axon growth and blossoming of new synaptic connections can establish entirely new pathways between brain regions that were previously disconnected.
Programmed cell death, where neurons that cannot find their proper role die off in an orderly way, also helps shape and optimize the neural circuits.

Here are the key points about why it is harder to teach old dogs new tricks:

Young brains have more plasticity and are able to rewire more easily than adult brains due to experience-dependent plasticity over time. As we learn and master certain skills, our brains become optimized for those tasks.
Neural connections and maps in the brain become more solidified and established with age through constant “border disputes” and competition between neurons for limited resources. Older brains have less capacity to reassign settled territories for new tasks.
Studies showed that younger soldiers who incurred brain injuries in WWII had better recovery outcomes than older soldiers, indicating young brains can still reimagine their maps more easily.
As we age, we specialize in certain skills, abilities, habits and patterns of behavior at the expense of flexibility to learn new things. There is a trade-off between adaptability and efficiency that comes with experience and mastery.
To become proficient at something requires focused practice that closes doors to other potential skills and pathways. Our brains descend into familiar patterns over time, making it more difficult but not impossible to acquire new tricks later in life.

So in summary, experience-dependent plasticity reduces the malleability of neural connections with age, making relearning and rewiring for new skills more challenging for older brains.

The brain develops hardened pathways over time through repeated use, much like local governments lay down roadways that eventually become highways. Unused neural pathways are pruned away.
The brain is highly flexible and malleable early in life, allowing widespread changes across neural connections. As the brain matures into adulthood, it changes in only localized areas and holds on tightly to established pathways.
There is a “sensitive period” early in development when the brain is most receptive to input and changes. Without proper sensory input during this time, skills like language, vision, and motor abilities will not develop normally.
The sensitive period closes earlier for some skills like sound acquisition and accents, around age 7-10. Recovery from injuries or deprivation is best if they occur during the sensitive period rather than later in life. Surgical or rehabilitative outcomes depend greatly on a person’s age.
Early experiences thus have a lasting influence as the brain becomes hardened in its connectivity patterns. It is difficult to attain high-level skills if learning begins past the sensitive period of plasticity in childhood. Timing is critical for normal neurodevelopment.
Taller men earn more on average than shorter men. The best predictor is height at age 16 - growing taller after that doesn’t change earnings. This suggests social status development in teenage years impacts adult success.
Careers like sales and management that rely more on social skills show stronger effects of teenage height, while blue-collar/artistic jobs are less influenced.
Early childhood experiences deeply shape personality traits like self-esteem and confidence through adulthood. Oprah Winfrey’s early poverty shaped her fears despite later success.
Brain areas have different sensitive periods of plasticity depending on their function. Visual cortex locks in patterns early while motor/somatosensory cortices remain flexible.
The degree of plasticity reflects how much the underlying data/variables change in the real world. Basic visual/auditory properties are static, so those areas solidify, while bodies change so motor skills remain learnable.
Within a sense like vision, lower areas encoding basic properties solidify first to provide stable foundations for higher-order learning on top of them.
Adults cannot regain all forms of childhood plasticity but maintain flexibility in some brain networks depending on their function and experience-dependent variability over the lifespan. Early experiences influence us profoundly.
The passage discusses the pattern of memory loss in aging and dementia, where more recent memories are lost first while childhood memories remain intact. This was first noted by French psychologist Théodule Ribot in 1882 and is known as Ribot’s law.
It provides the example from Tillie Olsen’s short story where a dying grandmother reverts to memories of her childhood, able to recall events from when she was young but not more recent memories.
When Albert Einstein died, his final words were spoken in German, his native tongue, as his English had receded even though he lived in America for many years.
This pattern of retaining old memories while losing new ones is strange as most storage systems focus on more recent information, not older. But the human brain follows this backward pattern of memory loss.
The passage wonders why the brain does it backward by preserving childhood memories over more recent ones as aging and dementia progress. It is an unusual characteristic of human memory organization.
Older memories tend to become more securely stored over time as the connections between neurons are strengthened. This process was first described by Aristotle but is now being understood through neuroscience research.
Experiments with animals like sea slug: s have uncovered molecular changes involved in simple forms of memory formation and storage. However, human memory is more complex, allowing autobiographical memories and skills to be remembered.
Early experiments in the 1920s by Lashley revealed that memory is not localized to one brain area but rather distributed broadly across many areas.
Discoveries in the late 19th/early 20th century established that the brain is made up of discrete neurons that communicate at synaptic connections.
Hebb proposed in 1949 that connections between neurons are strengthened (“potentiated”) when they fire at the same time, providing a mechanism for associative learning and memory formation.
In the 1970s, long-term potentiation and depression were discovered, providing evidence that synaptic strengths can be persistently modified, supporting Hebbian learning.
Artificial neural network models in the 1980s demonstrated that simple networks could store and recall distributed “memories” through Hebbian synaptic plasticity principles.

So in summary, neuroscience research has revealed that memories are physically embodied as strengthened synaptic connections between widely distributed neural networks in the brain.

Artificial neural networks are inspired by the brain but have limited capabilities compared to real brains. They fail when switching tasks and memories get easily overwritten.
The brain faces the challenge of lifelong learning while retaining old memories. Simply strengthening and weakening synapses over time leads to “memory mud” where new memories overwrite old ones.
The brain has developed two solutions to this problem. First, it tightly controls plasticity so changes only occur when new learning is relevant. Second, memories are moved from temporary storage areas like the hippocampus to more permanent storage in the cortex.
The hippocampus is needed to initially form memories but not to recall older ones, suggesting its role is temporary consolidation before storage shifts to cortical regions. Reactivating memories helps lock them into the cortex.
Synaptic plasticity is necessary for learning and memory but may not be the only or primary mechanism. Other adjustable parameters in neurons like growth and shapes of dendrites also change with experience and could support memory storage.

So in summary, the brain has evolved sophisticated mechanisms to balance plasticity and stability through localized control of synaptic changes and redistribution of memories to different storage areas over time. Memory is not just encoded at synapses.

The brain has plasticity at many levels, from synapses to gene expression, but neuroscientists focus mostly on synapses that can be easily measured.
Large structural changes in the brain seen during learning suggest memories are not just retained in synaptic weights. Neurogenesis and changes to epigenetics and gene expression also play a role.
Different levels of the brain operate on different timescales - from fast biochemical cascades to slow changes in gene expression.
If these timescales are linked up correctly, fast changes can kick off slower changes that make memories more durable. This distributed plasticity across timescales allows the brain to modify without disrupting function.
Examples like relearning sign language show memories are retained even when faster layers forget, due to savings in deeper, slower layers. This illustrates how multiple timescales interact in the brain.
Schemas emerge from programs being burned into long-term circuitry across different timescales, allowing flexible switching between related skills and contexts.
Instincts and traits that aid survival and reproduction tend to multiply over generations through natural selection. Traits that improve an organism’s chance of surviving to reproduce and having offspring that also reproduce will become more common in populations over time.
Memory is shaped by a person’s prior experiences and knowledge. New information is understood and encoded in the context of what someone already knows. Early experiences provide a framework that later memories are built upon.
The interaction between different layers or regions of the brain is important for understanding various memory-related phenomena. Conditions like phantom limb sensations, hyperthymesia (highly superior autobiographical memory), and synesthesia may result from unusual interactions between brain areas involved in perception, memory storage and retrieval.
Memory is not a single thing but has multiple aspects. Various types of amnesia demonstrate that different kinds of memory can be impaired independently, such as episodic/autobiographical memory versus skills and procedural memory. The case description shows how someone can lose their identity and personal past while retaining other abilities.
Jody was in a car accident and suffered brain damage that erased her memory of her entire life up until that point. She had no memory of her family or past.
However, she retained memories for things like language, skills like driving, how to interact socially, care for children, etc. She just couldn’t remember autobiographical details.
This shows that memory is not a single entity but comprised of different types. She lost declarative/explicit memory but retained non-declarative/procedural memory. Different brain areas support different types of memory.
Twelve years later she was reunited with her distraught family but was polite but distant since she had no memory of them. Her basic personality was the same according to her father.

So in summary, Jody lost her autobiographical memory due to brain damage but retained everyday skills and knowledge, demonstrating the complexity of human memory systems.

The wolf and rover differ in that the wolf operates with purposes (escaping danger, reaching safety) driven by its reward systems (food, shelter, pack support). Its brain figures out solutions based on this.
Unlike the rover, the wolf has internal goals and adapts its actions/intentions accordingly based on environmental threats and bodily needs. Its brain processes information in the service of reaching its goals.
The wolf keeps going after damage because animals don’t shut down from moderate injuries, as Mother Nature designed them for adaptability, not predefined wiring.
For robots to keep going after damage, they would need goals like survival/socialization/nutrition, and the ability to adapt their body plans and circuitry to finish tasks with remaining parts, like reconfiguring after losing a wheel.
Mother Nature builds infotropic systems that can optimize on the fly based on inputs, capabilities and goals, rather than predefined circuits, to handle the complexity and flux of the real world. This is a better model for building adaptive machines.

So in summary, it argues for building robots with internal purposes/goals and adaptive, goal-driven processing like animals, rather than fixed circuits, to allow them to keep functioning autonomously after damage through self-reconfiguration and goal-directed problem-solving based on their sensorimotor interactions.

The passage discusses Ötzi, a 5,000 year old man found frozen in ice in the Alps in 1991. Scientists were able to learn a lot about Ötzi’s life from examining his remains, like his last meals, where he grew up, potential illnesses, and activities.
The author suggests that in the future, as we learn more about how the brain works, we may be able to glean even more specific details about a person’s life directly from their brain structure. Things like which hand they used predominantly, their language structure, important people in their life, daily activities, etc. could potentially be readable from how their neural network was shaped by their experiences.
This would allow us to understand Ötzi and others not just as representatives of their era, but to truly see their individual narratives and perspective by reading about their lives etched in their brain cells and structure on a microscopic level. The passage frames this as advancing our ability to reconstruct individuals’ lives beyond what can currently be determined from external remains.
The passage describes the brain of Matthew, a young boy who survived a rare brain tumor removal surgery. Despite the surgery affecting half his brain, he was able to develop normally.
It notes that the human brain contains around 80-100 billion neurons, with an equal number of glial cells providing support. Previous estimates thought there were 10 times as many glia, but newer research methods show a roughly 1:1 ratio.
The brain’s remarkable plasticity allows it to rewire itself and compensate even after substantial damage or injury. In Matthew’s case, the remaining half of his brain assumed functions previously handled by the resected areas.
Every experience a child has, no matter how minor, helps shape their brain and future development in complex and unknowable ways. The passage lists some typical everyday experiences a two-year-old might have that all contribute to this shaping process.
Live experiences and interactions with people, animals, objects, stories and more all leave imprints on the developing brain through plasticity and neural wiring/rewiring. This allows the brain to adapt remarkably even after significant trauma or changes.
Early experiences and environment shape brain development and function in significant ways through a process known as plasticity. The brain remains plastic throughout life, allowing continual adaptation.
Studies on individuals deprived of social and cognitive stimulation early in life, like Kaspar Hauser and Danielle DeGregory, demonstrate the profound impacts of neglect and isolation on cognitive and social development. Severe deprivation can lead to permanent impairments.
While genes lay the groundwork, experience interacts with genetic factors to influence neural circuits and brain organization. In early development, spontaneous neural activity helps establish basic patterns before visual input refines connections.
Both experience-dependent and experience-independent mechanisms contribute to brain development in an intertwined way. The brain uses its own activity to simulate experience when external stimuli are absent.
Enriching experiences through education, new skills, social interaction etc. can promote positive brain changes and cognitive reserve even late in life. Conversely, a impoverished environment may limit brain plasticity and potential. Early experiences are particularly influential.
The implications are that nurturing environments and stimulation are important for optimal development, and deprivation can seriously hinder cognitive abilities unless addressed through later intervention. Both genetics and experience shape who we become.

Here is a summary of the key points in the excerpt on how the brain remaps and rewires itself after sensory loss or changes:

Pioneering work by neurosurgeon Penfield in the 1950s found that the brain’s maps of the body can change after injury or amputation. Areas previously representing a lost limb would start responding to other body parts like the face.
Later studies in monkeys found massive cortical reorganization after sensory deprivation like digit amputation. Nearby areas would take over the deafferented regions.
Brain imaging studies in humans also observed plastic reorganization, such as crossover of visual and auditory areas in the blind. Losing one sense enhances processing in other modalities.
Critical periods of development aside, the adult brain remains highly plastic. It continuously rewires connectivity through mechanisms like Hebbian learning. Experience and use strengthen connections, while disuse allows pruning.
Changing maps can occur rapidly, within days/weeks of injury or sensory changes. This challenges the view that brain organization is fixed after development. The brain continuously reshapes representations to adapt to environment.

So in summary, the brain possesses a remarkable ability to remap and reroute connections even in adulthood in response to sensory loss or changes, allowing it to regain or enhance function through crossmodal plasticity. This demonstrates the brain’s lifelong capacity for structural and functional remodeling.

Here is a summary of the key points from the papers and reviews cited:

Auditory cortex in deaf individuals can take on visual processing functions. Studies have found that visual stimuli activate auditory cortex in deaf individuals. (Finney et al. 2001)
Brain areas devoted to processing one sense can take over functions of other senses when one sense is impaired. For example, occipital cortex involved in vision has been found to process touch in blind individuals. (Amedi et al. 2003; Merabet et al. 2008)
Complete blindness early in life leads to more profound reorganization of visual cortex functions compared to later onset blindness. (Bola et al. 2017)
Some blind individuals can use echolocation to detect objects in their environment with high spatial acuity, activating occipital cortex. (Teng et al. 2012; Arnott et al. 2013)
Blind individuals can have visual content in their dreams, and the amount of visual detail decreases with earlier age of blindness. Sighted individuals who become blind later in life report more visual dreams. (Hurovitz et al. 1999; Kirtley 1975)
REM sleep may play a role in visual system development and maintenance even in the absence of vision, through random visual cortex activation. (Eagleman and Vaughn 2020)

So in summary, sensory deprivation leads to cross-modal changes and reorganization of brain areas across senses, supported by evidence from studies of blindness, deafness and sensory substitution in blind individuals.

The occipital lobe in late blind individuals is less dominated by other senses compared to early blind individuals. Studies by Voss et al. found that the occipital lobe is less fully reorganized by other senses like touch in late blind people.
Several examples are provided of devices that can provide sensory substitution to blind individuals, allowing them to perceive aspects of vision through other senses. This includes the Tongue Display Unit, which converts images into vibrotactile patterns on the tongue. Studies found individuals were able to improve performance on spatial tasks using the Argus II retinal prosthesis.
Research suggests the brain has considerable plasticity and can learn to extract useful information from new sensory inputs to build novel perceptual abilities. Areas beyond the primary sensory cortices can become involved in processing substituted senses. However, the cortical reorganization may be less precise than with early sensory loss.
Sensory substitution relies on the brain’s ability to learn new input-output rules and rearrange functionally based on experiences. This allows novel sensory pathways to develop and new patterns of brain activity to support new perceptual abilities enabled by these technologies.

Here is a summary of the key points from the paper:

The paper studied sensory substitution in congenitally blind children using the Tongue Display Unit (TDU), which converts images seen by a video camera into electrotactile stimulation of the tongue.
10 blind children between the ages of 7-15 years old participated in the study. They underwent training to learn the image-to-tactile code over multiple sessions.
Results showed that the children were able to learn the code and use it to identify simple objects and shapes. Their ability to do this improved with more training.
The study provided early evidence that blind individuals can learn to use sensory substitution devices to obtain visual information through their other senses like touch. It helped demonstrate the brain’s ability to adapt and process information from different senses.
However, the effectiveness of the substitution decreased with more complex images. Also, performance varied between individuals. Overall it supported the idea that sensory substitution is possible but has limitations and requires extensive training.

So in summary, this early study helped provide proof-of-concept that sensory substitution can work for the blind, by showing blind children could learn to identify objects through a device transmitting images to the tongue. But it also highlighted the challenges and limitations of the approach.

Here is a summary of the key points about getting a better body from the passage:

The human brain is highly plastic and can remap areas related to limbs even after amputation. Remapping has been shown in amputees’ brains.
Reattached body parts like hands can also lead to remapping of hand representations in the motor cortex.
Homeobox genes control body development and mutations can lead to abnormal extra body parts like tails in rare cases.
Brain-computer interfaces allow direct connection from the brain to machines like prosthetic limbs, enabling control without muscle signals.
Techniques are being developed to implant electrodes in the brain during neurosurgery to restore functional movement in paralyzed patients.
Non-invasive techniques are also being developed using external electrodes on the head.
The ability to control external tools is shown by the integration of tools into the body schema in the brain. This provides a route to integrating prosthetics controlled by thought.

So in summary, the key ideas are about brain plasticity and remapping, direct brain interfaces to prosthetics, and integrating external tools into the body schema to control advanced prosthetics with thought. This outlines different avenues being explored to enhance and restore bodily functions.

Current research uses stretchable rubbers and flexible plastics to build artificial limbs and body parts that mimic biological structures. These materials allow for the creation of adaptive shapes that change based on air pressure, electrical signals, or chemical signals.
Example applications include artificial fingers, tentacles, worms, etc. The shape and movement can be controlled to approximations of biological counterparts through adjustment of the embedded materials.
This represents ongoing work to create prosthetics and artificial structures that have flexible, adaptive capabilities similar to natural body parts and organisms. The goal is to build devices that can change shape dynamically based on internal or external inputs.
A neuromodulator is a chemical messenger that broadly affects populations of neurons and has wider-ranging effects, as opposed to a neurotransmitter which acts more specifically on an individual neuron. Acetylcholine can act as either depending on context - as a neurotransmitter in the periphery but as a neuromodulator in the central nervous system.
Acetylcholine, released by cholinergic neurons in the basal forebrain, modulates neuron excitability, neurotransmitter release, and small neuron population coordination in the brain. It plays a role in visual cortex plasticity.
Stimulation of the cholinergic basal forebrain during exposure to tones expands the auditory cortex representation of those tones, demonstrating acetylcholine’s role in enabling learning-induced cortical map plasticity. Lesions of the basal forebrain impair this type of cortical plasticity.
Acetylcholine and norepinephrine modulate visual cortical plasticity. The broad effects of neuromodulators can transiently change neuronal excitation and inhibition balances, proposed as one mechanism by which neuromodulation enables long-term synaptic changes underlying learning and memory.

Here is a summary of the key points about which arm is put in a sling:

Putting one arm in a sling immobilizes it and prevents its normal use and movement. This can lead to changes in the brain’s map of the body.
The brain represents the body somatotopically, with adjoining areas representing adjoining body parts. When an arm is immobilized in a sling, its representation in the brain may shrink or become less defined.
Nearby representations, such as of the shoulder or elbow, may expand into the territory previously representing the immobilized arm. This helps explain why it is difficult to rehabilitate motor skills after immobilization - the brain map has been remapped.
Plastic changes like this occur more readily in the developing brain. Immobilizing an arm during sensitive periods of development could have long-lasting effects on the brain and motor skills. In adults, rehabilitation is needed to reshape the brain map after an immobilized arm is freed from the sling.

So in summary, putting an arm in a sling leads to changes in the brain’s body map as other areas encroach on the shrinking representation of the immobilized arm, making rehabilitation more difficult. This effect is especially strong if immobilization occurs during development.

Memory formation is thought to involve long-term potentiation (LTP) and long-term depression (LTD) of synapses. LTP strengthens synapses while LTD weakens them.
LTP was first demonstrated experimently by Bliss and Lomo in 1973. It involves the opening of NMDA receptors on the postsynaptic membrane during coincident pre- and postsynaptic firing.
Hebb’s rule proposes that neurons wire together if they fire together, capturing the idea that associations are formed through correlated activity. However, it does not account for the temporal order of firing, which experiments show is important.
Spike-timing dependent plasticity (STDP) proposes that synapses are strengthened when the presynaptic neuron fires briefly before the postsynaptic neuron, and weakened in the reverse order. This accounts for temporal order effects.
While LTP/LTD underlie learning, memory formation also requires structural changes and gene expression in neurons over time. Protein synthesis is required to consolidate short-term memories into long-lasting ones.
The hippocampus plays a critical role in declarative memory formation, as shown by patient HM’s selective amnesia after bilateral medial temporal lobe removal. But remote memories eventually transition to neocortical regions like the anterior cingulate cortex.
Neuroplasticity underlies memory formation, as demonstrated by studies finding cortical map reorganization and grey matter changes with learning. However, many open questions remain about how cellular contexts determine synaptic modification.

Here is a summary of the key points from the papers:

Oldrini et al. (2018) found that human hippocampal neurogenesis, the growth of new neurons in the hippocampus, persists throughout aging. This challenges the previous dogma that mammals are born with a fixed number of neurons.
Gould et al. (1999) and Eriksson et al. (1998) provided evidence that neurogenesis also occurs in the adult primate and human hippocampus/cortex. This challenges the view that neurogenesis only occurs during development.
Neurogenesis was suspected for a long time but ignored. It has now been found in mammals from mice to humans, similar to how bird brains generate new neurons when learning songs.
Stimulating environments and exercise promote neurogenesis. Early primate studies may have missed it due to unstimulating captive conditions.
New neurons could serve as repositories for long-term memories by irreversibly changing neuronal connectivity through cell division and differentiation. However, more research is needed to understand the role and integration of new neurons.
Epigenetic tagging and histone modifications during memory formation allow for changes in gene expression that could underlie long-term potentiation and memory consolidation. Maternal care also induces epigenetic changes influencing lifelong gene expression patterns.

Here is a summary of the key points from the provided text about complementary learning systems in the brain:

The original idea proposed that the hippocampus and cortex have complementary learning systems, with the hippocampus supporting rapid one-shot learning of episodes/events and the cortex supporting slower, statistical learning over many experiences.
More recent models have suggested the different learning rates could occur entirely within the hippocampus. Specifically:
The trisynaptic pathway in the CA3 region of the hippocampus supports fast learning of clearly demarcated episodes due to its connectivity.
Meanwhile, the monosynaptic pathway in the CA1 region supports slower, statistical learning due to its connectivity. This helps reconcile the hippocampus’ role in episodic memory with its involvement in statistical learning.
In summary, the core idea is that different regions and pathways within the brain, particularly the hippocampus and cortex, have evolved complementary learning systems - some optimized for rapid one-shot learning, others for slower incremental statistical learning over multiple experiences. More recent work has focused on mapping these complementary systems specifically within the hippocampus.

Here is a summary of the key points from the references provided:

Several studies show plasticity and neurogenesis in the adult brain following learning, sensory deprivation, injury, or skill acquisition. Areas like the visual cortex can reorganize following blindness.
Training can lead to cortical thickening and changes in gray matter. Musicians have enhanced representations of fingers in motor/somatosensory cortex.
Following amputation, sensory cortex can reorganize with axonal sprouting and referred sensations develop in phantom limbs. Cortex also reorganizes after peripheral injuries.
Cross-modal plasticity allows sensory areas to take on new functions, like visual cortex processing sound in the blind. Congenitally blind have enhanced tactile abilities.
Synesthesia involves cross-wiring between sensory areas leading to unusual perceptions like letter-color associations.
Skill learning is accompanied by enhanced long-term potentiation and reactivation of distributed memory traces.
Optogenetic approaches and brain-machine interfaces have allowed communication with and control of prosthetics by paralyzed individuals.
Cholinergic systems modulate plasticity in visual and other cortices. Neuromodulation plays a role in cortical Map remodeling.
Adult neurogenesis occurs in hippocampus and is enhanced by learning. Memory consolidation involves reorganization over time.

So in summary, the references provide evidence that the adult brain remains highly plastic and can reorganize and modify connections in response to sensory, motor and cognitive challenges through mechanisms like axonal sprouting, synaptogenesis and neurogenesis.

Here is a summary of the key papers:

Dsen EI (2002) studied instructed learning in the auditory localization pathway of the barn owl.
Kubanek M, Bobulski J (2018) developed a device for acoustic support of orientation for blind people using sensors.
Kuhl PK (2004) examined early language acquisition and how infants crack the speech code.
Kupers R, Ptito M (2014) reviewed compensatory plasticity and cross-modal reorganization following early visual deprivation.
Law MI, Constantine-Paton M (1981) studied the anatomy and physiology of experimentally produced striped tecta in frogs.
Lenay et al (2003) discussed the limits and perspectives of sensory substitution.
Levy (2008) described the case of a blind climber who uses tongue sensing to “see”.
Lisman et al (2018) proposed that memory formation depends on synaptic modifications and neuronal excitability changes.
Lobo et al (2018) had subjects use a vibrotactile device to orient and walk to targets.
Macpherson (2018) edited a book on sensory substitution and augmentation.
Mancuso et al (2009) performed gene therapy for color blindness in primates.
Merabet et al (2005, 2007, 2008, 2010) studied neural plasticity and reorganization following sensory loss.
Merzenich (1998) discussed long-term neural changes underlying learning and memory.
Nagel et al (2005) aimed to go beyond sensory substitution to learn a “sixth sense”.
Nau et al (2015) studied how blind adults acquired visual perception using a vision device.
Noë (2009) discussed arguments against the sense-organ view of perception.
Norimoto and Ikegaya (2015) restored spatial navigation in blind rats using a geomagnetic compass.
Pascual-Leone et al (2005) reviewed plasticity in the human brain cortex.

This paper discusses brain plasticity and the ability of the brain to reorganize itself and adapt in response to changes or injuries. It reviews research on cross-modal plasticity where one sensory modality takes over functions of another that is lost. Examples discussed include blind individuals who can perceive visual inputs through touch on the tongue, and blind individuals showing tactile discrimination abilities in visual cortex. The paper also discusses brain plasticity induced by transplantation of inhibitory neurons, and long-term potentiation allowing learning and memory formation. While some studies found limited cortical reorganization after retinal lesions in monkeys, others reported extensive rewiring in primary visual cortex after focal injuries. Overall, the review demonstrates the brain’s remarkable ability to rewire and adapt even in adulthood through mechanisms of plasticity.

#book-summary

Livewired The Inside Story of the Ever-Changing Brain - David Eagleman