San Andreas Fault

From Wikipedia, the free encyclopedia

https://en.wikipedia.org/wiki/San_Andreas_Fault

 

San Andreas Fault
Arrows show relative motion of the North American plate (southeastward) and the Pacific plate (northwestward)

Plaque showing location of San Andreas Fault in San Mateo County

The San Andreas Fault is a continental right-lateral strike-slip transform fault that extends roughly 1,200 kilometers (750 mi) through the U.S. state of California. It forms part of the tectonic boundary between the Pacific plate and the North American plate. Traditionally, for scientific purposes, the fault has been classified into three main segments (northern, central, and southern), each with different characteristics and a different degree of earthquake risk. The average slip rate along the entire fault ranges from 20 to 35 mm (0.79 to 1.38 in) per year.

In the north, the fault terminates offshore near Eureka, California, at the Mendocino triple junction, where three tectonic plates meet. The Cascadia subduction zone intersects the San Andreas fault at the Mendocino triple junction. It has been hypothesized that a major earthquake along the Cascadia subduction zone could trigger a rupture along the San Andreas Fault.

In the south, the fault terminates near Bombay Beach, California, in the Salton Sea. Here, the plate motion is being reorganized from right-lateral to divergent. In this region (known as the Salton Trough), the plate boundary has been rifting and pulling apart, creating a new mid-ocean ridge that is an extension of the Gulf of California. Sediment deposited by the Colorado River is preventing the trough from being filled in with sea water from the gulf.

The fault was first identified in 1895 by Professor Andrew Lawson of UC Berkeley. In the wake of the 1906 San Francisco earthquake, Lawson was tasked with deciphering the origin of the earthquake. He began by surveying and mapping offsets (such as fences or roads that had been sliced in half) along surface ruptures. When the location of these offsets were plotted on a map, he noted that they made a near perfect line on top of the fault he previously discovered. He concluded that the fault must have been the origin of the earthquake.

This line ran through San Andreas Lake, a sag pond. The lake was created from an extensional step over in the fault, which created a natural depression where water could settle. A common misconception is that Lawson named the fault after this lake. However, according to some of his reports from 1895 and 1908, he actually named it after the surrounding San Andreas Valley. Following the 1906 San Francisco earthquake, Lawson also concluded that the fault extended all the way into Southern California. In 1953, geologist Thomas Dibblee concluded that hundreds of miles of lateral movement could occur along the fault.

A National Science Foundation funded project called the San Andreas Fault Observatory at Depth (SAFOD) near Parkfield, California, involved drilling through the fault from 2004 to 2007. The aim was to collect core samples and make direct geophysical and geochemical observations to better understand fault behavior at depth.

Fault zones

Northern

See also: Calaveras Fault and Hayward Fault Zone

A map displaying each of the seven major faults in the San Francisco Bay Area, and the probability of an M6.7 earthquake or higher occurring on each fault between 2003 and 2032

The slip on the San Andreas Fault which caused the 1906 San Francisco earthquake was visible in Wrights Tunnel along the South Pacific Coast Railroad after the earthquake

The northern segment of the fault runs from Hollister, through the Santa Cruz Mountains, epicenter of the 1989 Loma Prieta earthquake, then up the San Francisco Peninsula, where it was first identified by Professor Lawson in 1895, then offshore at Daly City near Mussel Rock. This is the approximate location of the epicenter of the 1906 San Francisco earthquake. The fault returns onshore at Bolinas Lagoon just north of Stinson Beach in Marin County. It returns underwater through the linear trough of Tomales Bay which separates the Point Reyes Peninsula from the mainland, runs just east of Bodega Head through Bodega Bay and back underwater, returning onshore at Fort Ross. (In this region around the San Francisco Bay Area several significant "sister faults" run more-or-less parallel, and each of these can create significantly destructive earthquakes.) From Fort Ross, the northern segment continues overland, forming in part a linear valley through which the Gualala River flows. It goes back offshore at Point Arena. After that, it runs underwater along the coast until it nears Cape Mendocino, where it begins to bend to the west, terminating at the Mendocino triple junction.

Central

The central segment of the San Andreas Fault runs in a northwestern direction from Parkfield to Hollister. While the southern section of the fault and the parts through Parkfield experience earthquakes, the rest of the central section of the fault exhibits a phenomenon called aseismic creep, where the fault slips continuously without causing earthquakes. It was formed by a transform boundary.

Southern

See also: Elsinore Fault Zone, Imperial Fault, Laguna Salada Fault, and San Jacinto Fault Zone

Aerial photo of the San Andreas Fault in the Carrizo Plain

The Vasquez Rocks in Agua Dulce, California are evidence of the San Andreas Fault and part of the 2,650-mile Pacific Crest Trail.

The southern segment (also known as the Mojave segment) begins near Bombay Beach, California. Box Canyon, near the Salton Sea, contains upturned strata associated with that section of the fault. The fault then runs along the southern base of the San Bernardino Mountains, crosses through Cajon Pass and continues northwest along the northern base of the San Gabriel Mountains. These mountains are a result of movement along the San Andreas Fault and are commonly called the Transverse Range. In Palmdale, a portion of the fault is easily examined at a roadcut for the Antelope Valley Freeway. The fault continues northwest alongside the Elizabeth Lake Road to the town of Elizabeth Lake. As it passes the towns of Gorman, Tejon Pass and Frazier Park, the fault begins to bend northward, forming the "Big Bend". This restraining bend is thought to be where the fault locks up in Southern California, with an earthquake-recurrence interval of roughly 140–160 years. Northwest of Frazier Park, the fault runs through the Carrizo Plain, a long, treeless plain where much of the fault is plainly visible. The Elkhorn Scarp defines the fault trace along much of its length within the plain.

The southern segment, which stretches from Parkfield in Monterey County all the way to the Salton Sea, is capable of an 8.1-magnitude earthquake. At its closest, this fault passes about 35 miles (56 km) to the northeast of Los Angeles. Such a large earthquake on this southern segment would kill thousands of people in Los Angeles, San Bernardino, Riverside, and surrounding areas, and cause hundreds of billions of dollars in damage.

Plate boundaries

The Pacific plate, to the west of the fault, is moving in a northwest direction while the North American plate to the east is moving toward the southwest, but relatively southeast under the influence of plate tectonics. The rate of slippage averages about 33 to 37 millimeters (1.3 to 1.5 in) a year across California.

The southwestward motion of the North American plate towards the Pacific is creating compressional forces along the eastern side of the fault. The effect is expressed as the Coast Ranges. The northwest movement of the Pacific plate is also creating significant compressional forces which are especially pronounced where the North American plate has forced the San Andreas to jog westward. This has led to the formation of the Transverse Ranges in Southern California, and to a lesser but still significant extent, the Santa Cruz Mountains (the location of the Loma Prieta earthquake in 1989).

Studies of the relative motions of the Pacific and North American plates have shown that only about 75 percent of the motion can be accounted for in the movements of the San Andreas and its various branch faults. The rest of the motion has been found in an area east of the Sierra Nevada mountains called the Walker Lane or Eastern California Shear Zone. The reason for this is not clear. Several hypotheses have been offered and research is ongoing. One hypothesis – which gained interest following the Landers earthquake in 1992 – suggests the plate boundary may be shifting eastward away from the San Andreas towards Walker Lane.

Assuming the plate boundary does not change as hypothesized, projected motion indicates that the landmass west of the San Andreas Fault, including Los Angeles, will eventually slide past San Francisco, then continue northwestward toward the Aleutian Trench, over a period of perhaps twenty million years.

Formation

Tectonic evolution of the San Andreas Fault

The San Andreas began to form in the mid-Cenozoic about 30 Mya (million years ago). At this time, a spreading center between the Pacific plate and the Farallon plate (which is now mostly subducted, with remnants including the Juan de Fuca plate, Rivera plate, Cocos plate, and the Nazca plate) was beginning to reach the subduction zone off the western coast of North America. As the relative motion between the Pacific and North American plates was different from the relative motion between the Farallon and North American plates, the spreading ridge began to be "subducted", creating a new relative motion and a new style of deformation along the plate boundaries. These geological features are what are chiefly seen along San Andreas Fault. It also includes a possible driver for the deformation of the Basin and Range, separation of the Baja California peninsula, and rotation of the Transverse Range.

The main southern section of the San Andreas Fault proper has only existed for about 5 million years. The first known incarnation of the southern part of the fault was Clemens Well-Fenner-San Francisquito fault zone around 22–13 Ma. This system added the San Gabriel Fault as a primary focus of movement between 10–5 Ma. Currently, it is believed that the modern San Andreas will eventually transfer its motion toward a fault within the eastern California shear zone. This complicated evolution, especially along the southern segment, is mostly caused by either the "Big Bend" and/or a difference in the motion vector between the plates and the trend of the fault and its surrounding branches.

Study

Early years

The fault was first identified in Northern California by UC Berkeley geology professor Andrew Lawson in 1895 and named by him after the surrounding San Andreas valley. Eleven years later, Lawson discovered that the San Andreas Fault stretched southward into southern California after reviewing the effects of the 1906 San Francisco earthquake. Large-scale (hundreds of miles) lateral movement along the fault was first proposed in a 1953 paper by geologists Mason Hill and Thomas Dibblee. This idea, which was considered radical at the time, has since been vindicated by modern plate tectonics.

Current research

Seismologists discovered that the San Andreas Fault near Parkfield in central California consistently produces a magnitude 6.0 earthquake approximately once every 22 years. Following recorded seismic events in 1857, 1881, 1901, 1922, 1934, and 1966, scientists predicted that another earthquake should occur in Parkfield in 1993. It eventually occurred in 2004. Due to the frequency of predictable activity, Parkfield has become one of the most important areas in the world for large earthquake research.

In 2004, work began just north of Parkfield on the San Andreas Fault Observatory at Depth (SAFOD). The goal of SAFOD is to drill a hole nearly 3 kilometres (1.9 mi) into the Earth's crust and into the San Andreas Fault. An array of sensors will be installed to record earthquakes that happen near this area.

A 2023 study found a link between the water level in Lake Cahuilla (now the Salton Sea) and seismic activity along the southern San Andreas Fault. The study suggests that major earthquakes along this section of the fault coincided with high water levels in the lake. The hydrological load caused by high water levels can more than double the stress on the southern San Andreas Fault, which is likely sufficient for triggering earthquakes. This may explain the abnormally long period of time since the last major earthquake in the region since the lake has dried up.

The San Andreas Fault System has been the subject of a flood of studies. In particular, scientific research performed during the last 23 years has given rise to about 3,400 publications.

The next "Big One"

"The Big One (earthquake)" redirects here. For another hypothetical earthquake known in the Philippines as "The Big One", see Marikina Valley Fault System § Threat.

Radar generated 3-D view of the San Andreas Fault, at Crystal Springs Reservoir near San Mateo, California

A study published in 2006 in the journal Nature by Yuri Fialko, an associate professor at the Cecil H. and Ida M. Green Institute of Geophysics and Planetary Physics at Scripps Institution of Oceanography, found that the San Andreas fault has reached a sufficient stress level for an earthquake of magnitude greater than 7.0 on the moment magnitude scale to occur. This study also found that the risk of a large earthquake may be increasing more rapidly than scientists had previously believed. Moreover, the risk is currently concentrated on the southern section of the fault, i.e. the region around Los Angeles, because strong earthquakes have occurred relatively recently on the central (1857) and northern (1906) segments of the fault, while the southern section has not seen any similar rupture for at least 300 years. According to this study, a major earthquake on that southern section of the San Andreas fault would result in major damage to the Palm Springs–Indio metropolitan area and other cities in San Bernardino, Riverside and Imperial counties in California, and Mexicali Municipality in Baja California. It would be strongly felt (and potentially cause significant damage) throughout much of Southern California, including densely populated areas of Los Angeles County, Ventura County, Orange County, San Diego County, Ensenada Municipality and Tijuana Municipality, Baja California, San Luis Rio Colorado in Sonora and Yuma, Arizona. Older buildings would be especially prone to damage or collapse, as would buildings built on unconsolidated gravel or in coastal areas where water tables are high (and thus subject to soil liquefaction). Of the study, Fialko stated:

All these data suggest that the fault is ready for the next big earthquake but exactly when the triggering will happen and when the earthquake will occur we cannot tell. It could be tomorrow or it could be 10 years or more from now.

Nevertheless, in the 18 years since that publication there has not been a substantial quake in the Los Angeles area, and two major reports issued by the United States Geological Survey (USGS) have made variable predictions as to the risk of future seismic events. The ability to predict major earthquakes with sufficient precision to warrant increased precautions has remained elusive.

The U.S. Geological Survey's most recent forecast, known as UCERF3 (Uniform California Earthquake Rupture Forecast 3), released in November 2013, estimated that an earthquake of magnitude 6.7 M or greater (i.e. equal to or greater than the 1994 Northridge earthquake) occurs about once every 6.7 years statewide. The same report also estimated there is a 7% probability that an earthquake of magnitude 8.0 or greater will occur in the next 30 years somewhere along the San Andreas Fault. A different USGS study in 2008 tried to assess the physical, social and economic consequences of a major earthquake in southern California. That study predicted that a magnitude 7.8 earthquake along the southern San Andreas Fault could cause about 1,800 deaths and $213 billion in damage.

The HayWired Scenario

This scenario hypothesizes the potential effects of a 7.0 magnitude earthquake on the San Andreas Fault in the San Francisco Bay Area. It aims to estimate the impacts on urban infrastructures along with the rebuilding efforts to both the landscape and economy. This study combines not only the geological impacts/effects of the event, but also the societal impacts such as property damage, economic rebuilding, and aims at estimating damages if cities increased risk-reduction. It was developed for preparedness geared towards Bay Area residents and as a warning with an attempt to encourage local policy makers to create infrastructure and protections that would further risk reduction and resilience-building. This study is a combined effort from experts in the physical sciences, social sciences, and engineering both in the public and private sectors- ranging from urban planners to economists/business professionals. Not only does this study aim to estimate the impacts of the event, but aims to estimate the years of rebuilding and funding needed to recover communities from a potential disaster such as the HayWired Scenario.

The first volume of the HayWired Scenario study was released in 2017, with consistent continuations and contributions by engineers. This continuation was published in the second volume, Engineering Implications, in 2018.

Estimating damages

As of the 2021 Fact sheet update, there are several estimates on damages ranging from the approximate people affected at home, work, effects of lifeline infrastructures such as telecommunications, and more. This group of scientists have worked together to create estimates of how hazards such as liquefaction, landslides, and fire ignition will impact access to utilities, transportation, and general emergency services.

This study goes into detail about the specific populations to be hardest impacted by a potential earthquake of a 7.0 magnitude, specifically in the San Francisco Bay Area. This includes intensified hardships for those with low-income, racially and culturally-diverse populations, and people with literacy hardships that would significantly "increase their risk of displacement and add to recovery challenges" (Wein et al.).

Scientific and economic involvement

In addition to societal and landscape impacts, this study looks at potential business interruptions. This portion estimates impacts to the California economy within the first 6 months post-recovery from the event through estimates of "utility outages, property damages, and supply chain disruptions resulting in an estimated $44 billion of gross state product (GSP) losses, or translated at 4% of the California economy"(Wein et al.). This study also projects the recovery of jobs lost in highly impacted areas, such as Alameda County, could take up to 10 years to fully recover job losses and possible economic recession. Trajectories for economic recovery are improved by reconstruction but also delayed with impacts to the construction industry.

Cascadia connection

A 2008 paper, studying past earthquakes along the Pacific coastal zone, found a correlation in time between seismic events on the northern San Andreas Fault and the southern part of the Cascadia subduction zone (which stretches from Vancouver Island to Northern California). Scientists believe quakes on the Cascadia subduction zone may have triggered most of the major quakes on the northern San Andreas within the past 3,000 years. The evidence also shows the rupture direction going from north to south in each of these time-correlated events. Howver the 1906 San Francisco earthquake seems to have been the exception to this correlation because the plate movement was mostly from south to north and it was not preceded by a major quake in the Cascadia zone.

Earthquakes

See also: List of earthquakes in California

The San Andreas Fault has had some notable earthquakes in historic times:

• 1812 San Juan Capistrano earthquake: At least 25 kilometers(16 mi) were ruptured in Southern California. Several of the Roman Catholic missions in the area experienced heavy damage. Early studies indicated the earthquake was on the Newport-Inglewood fault, but a later study in 2002 indicated the San Andreas fault was the cause. Other faults have been suggested, but the San Andreas fault is considered the most likely fault. Around 40 people died, and the magnitude ranged from 6.9-7.5.
• 1857 Fort Tejon earthquake: About 350 kilometers (220 mi) were ruptured in central and southern California. Though it is known as the Fort Tejon earthquake, the epicenter is thought to have been located far to the north, just south of Parkfield. Two deaths were reported. Its moment magnitude was 7.9.
• 1906 San Francisco earthquake: About 430 kilometers (270 mi) were ruptured in Northern California. The epicenter was near San Francisco. At least 3,000 people died in the earthquake and subsequent fires. The magnitude was estimated to be 7.8.
• 1957 San Francisco earthquake: A magnitude 5.7 quake with an epicenter on the San Andreas fault in the ocean west of San Francisco and Daly City.
• 1989 Loma Prieta earthquake: About 40 kilometers (25 mi) were ruptured (although the rupture did not reach the surface) near Santa Cruz, California, causing 63 deaths and moderate damage in certain vulnerable locations in the San Francisco Bay Area. Moment magnitude was about 6.9. This quake occurred on October 17, 1989, at approximately 5:04 pm PDT.
• 2004 Parkfield earthquake: On September 28, 2004, at 10:15 a.m. PDT, a magnitude 6.0 earthquake struck the Parkfield area. It was felt across the state, including the San Francisco Bay Area.

ARkStorm

From Wikipedia, the free encyclopedia
https://en.wikipedia.org/wiki/ARkStorm

A USGS model image shows the enormous atmospheric river that may have been present during the 1861–1862 flood event.

The ARkStorm (for Atmospheric River 1,000) is a hypothetical megastorm, whose proposal is based on repeated historical occurrences of atmospheric rivers and other major rain events first developed and published by the Multi-Hazards Demonstration Project (MHDP) of the United States Geological Survey (USGS) in 2010. An updated model was published as ARkStorm 2.0 in 2022.

ARkStorm 1.0 (2010 Study)

The ARkStorm 1.0 scenario describes an extreme storm that devastates much of California, causing up to $725 billion in losses (mostly due to flooding and erosion), and affecting a quarter of California's homes. The scenario projects impacts of a storm that would be significantly less intense (25 days of rain) than the California storms that occurred between December 1861 and January 1862 (43 days). That event dumped nearly 10 feet (3.0 m) of rain in parts of California.

USGS sediment research in the San Francisco Bay Area, Santa Barbara Basin, Sacramento Valley, and the Klamath Mountain region found that "megastorms" have occurred in the years: 212, 440, 603, 1029, c. 1300, 1418, 1605, 1750, 1810, and, most recently, 1861–1862. Based on the intervals of these known occurrences, ranging from 51 to 426 years, for a historic recurrence of, on average, every 100–200 years.

Geologic evidence indicates that several of the previous events were more intense than the one in 1861–1862, particularly those in 440, 1418, 1605, and 1750, each of which deposited a layer of silt in the Santa Barbara Basin more than one inch (2.5 cm) thick. The largest event was the one in 1605, which left a layer of silt two inches (5 cm) thick, indicating that this flood was at least 50% more powerful than any of the others recorded.

Description

A USGS map shows flooded areas during the 1861–1862 event.

The conditions built into the scenario are "two super-strong atmospheric rivers, just four days apart, one in Northern California and one in Southern California, and one of them stalled for an extra day".

The ARkStorm 1.0 scenario would have the following effects:

• The Central Valley would experience flooding 300 miles (480 km) long and at least 20 miles (30 km) wide.
• Serious flooding also would occur in Orange County, Los Angeles County, San Diego, the San Francisco Bay area, and other coastal communities.
• Wind speeds in some places would reach 125 miles per hour (200 km/h).
• Hundreds of landslides would damage roads, highways, and homes.
• Property damage would exceed $300 billion, most from flooding.
• Demand surge (an increase in labor rates and other repair costs after major natural disasters) could increase property losses by 20 percent.
• Agricultural losses and other costs to repair lifelines, drain flooded islands, and repair damage from landslides, could bring the total direct property loss to nearly $400 billion.
• Power, water, sewer, and other lifelines would experience damage that could take weeks or months to restore.
• Up to 1.5 million residents in the inland region and delta counties would need to evacuate due to flooding.
• Business interruption costs could reach $325 billion, in addition to the $400 billion required for property repair costs, meaning that an ARkStorm scenario is projected to cost $750 billion (~$1 trillion in 2022 dollars), nearly three times the amount of damage predicted by the next "Big One", a hypothetical Southern California earthquake with roughly the same annual occurrence probability.

ARkStorm 2.0 (2022 update)

This update, with parts of the research on impacts still ongoing, has examined how climate change is expected to increase the risk of severe flooding from a hypothetical ARkStorm, with runoff 200% to 400% above historical values for the Sierra Nevada in part due to a decrease in the portion of precipitation that falls as snow, as well as an increase in the amount of water that storms can carry. The likelihood of the event outlined in the ARkStorm scenario is now once every 25–50 years, with projected economic losses of over $1 trillion (or more than five times that of Hurricane Katrina).

Large Atmospheric River Scenarios (2022 data)

	Odds of Occurring
Scenario	Annual Risk	1920 Risk	2071–2080 Risk (worst case with RCP 8.5)	Days	Precipitation	Damage (if it happened today)
Great Flood of 1862	1.2–1.6%	0.5–0.7%	3.4%–4.8%	43+	10 feet (3.0 metres)
ARkStorm	2–4%			25+		US$1 trillion+ (2010 estimate in 2022 dollars)

Implications

Current flood maps in the U.S. rarely take recent projections from projects like ARkStorm into account, especially FEMA's maps, which many decision-makers have relied on. Land owners, flood insurers, governments and media outlets often use maps like FEMA's that still fail to represent many significant risks due to: 1) using only historical data (instead of incorporating climate change models), 2) the omission of heavy rainfall events, and 3) lack of modeling of flooding in urban areas. More robust and up-to-date models, like the First Street Foundation's riskfactor.com, should better represent true flood risk though it is unclear if that model, for example, incorporates any ARkStorm science.

Government agencies may decide how much risk to accept, and how much risk to mitigate. The Netherlands' approach to flood control, for example, plans for 1 in 10,000 year events in heavily-populated areas and 1 in 4,000 year events in less well-populated areas.

Social construction of technology

From Wikipedia, the free encyclopedia

https://en.wikipedia.org/wiki/Social_constructionism

Social construction of technology (SCOT) is a theory within the field of science and technology studies. Advocates of SCOT—that is, social constructivists—argue that technology does not determine human action, but that rather, human action shapes technology. They also argue that the ways a technology is used cannot be understood without understanding how that technology is embedded in its social context. SCOT is a response to technological determinism and is sometimes known as technological constructivism.

SCOT draws on work done in the constructivist school of the sociology of scientific knowledge, and its subtopics include actor-network theory (a branch of the sociology of science and technology) and historical analysis of sociotechnical systems, such as the work of historian Thomas P. Hughes. Its empirical methods are an adaptation of the Empirical Programme of Relativism (EPOR), which outlines a method of analysis to demonstrate the ways in which scientific findings are socially constructed (see strong program). Leading adherents of SCOT include Wiebe Bijker and Trevor Pinch.

SCOT holds that those who seek to understand the reasons for acceptance or rejection of a technology should look to the social world. It is not enough, according to SCOT, to explain a technology's success by saying that it is "the best"—researchers must look at how the criteria of being "the best" is defined and what groups and stakeholders participate in defining it. In particular, they must ask who defines the technical criteria success is measured by, why technical criteria are defined this way, and who is included or excluded. Pinch and Bijker argue that technological determinism is a myth that results when one looks backwards and believes that the path taken to the present was the only possible path.

SCOT is not only a theory, but also a methodology: it formalizes the steps and principles to follow when one wants to analyze the causes of technological failures or successes.

Legacy of the Strong Programme in the sociology of science

At the point of its conception, the SCOT approach was partly motivated by the ideas of the strong programme in the sociology of science (Bloor 1973). In their seminal article, Pinch and Bijker refer to the Principle of Symmetry as the most influential tenet of the Sociology of Science, which should be applied in historical and sociological investigations of technology as well. It is strongly connected to Bloor's theory of social causation.

Symmetry

The Principle of Symmetry holds that in explaining the origins of scientific beliefs, that is, assessing the success and failure of models, theories, or experiments, the historian/sociologist should deploy the same kind of explanation in the cases of success as in cases of failure. When investigating beliefs, researchers should be impartial to the (a posteriori attributed) truth or falsehood of those beliefs, and the explanations should be unbiased. The strong programme adopts a position of relativism or neutralism regarding the arguments that social actors put forward for the acceptance/rejection of any technology. All arguments (social, cultural, political, economic, as well as technical) are to be treated equally.

The symmetry principle addresses the problem that the historian is tempted to explain the success of successful theories by referring to their "objective truth", or inherent "technical superiority", whereas s/he is more likely to put forward sociological explanations (citing political influence or economic reasons) only in the case of failures. For example, having experienced the obvious success of the chain-driven bicycle for decades, it is tempting to attribute its success to its "advanced technology" compared to the "primitiveness" of the Penny Farthing, but if we look closely and symmetrically at their history (as Pinch and Bijker do), we can see that at the beginning bicycles were valued according to quite different standards than nowadays. The early adopters (predominantly young, well-to-do gentlemen) valued the speed, the thrill, and the spectacularity of the Penny Farthing – in contrast to the security and stability of the chain-driven Safety Bicycle. Many other social factors (e.g., the contemporary state of urbanism and transport, women's clothing habits and feminism) have influenced and changed the relative valuations of bicycle models.

A weak reading of the Principle of Symmetry points out that there often are many competing theories or technologies, which all have the potential to provide slightly different solutions to similar problems. In these cases, sociological factors tip the balance between them: that's why we should pay equal attention to them.

A strong, social constructivist reading would add that even the emergence of the questions or problems to be solved are governed by social determinations, so the Principle of Symmetry is applicable even to the apparently purely technical issues.

Original Core concepts

The Empirical Programme of Relativism (EPOR) introduced the SCOT theory in two stage.

First Stage: Interpretative flexibility

The first stage of the SCOT research methodology is to reconstruct the alternative interpretations of the technology, analyze the problems and conflicts these interpretations give rise to, and connect them to the design features of the technological artifacts. The relations between groups, problems, and designs can be visualized in diagrams.

Interpretative flexibility means that each technological artifact has different meanings and interpretations for various groups. Bijker and Pinch show that the air tire of the bicycle meant a more convenient mode of transportation for some people, whereas it meant technical nuisances, traction problems and ugly aesthetics to others. In racing air tires lent to greater speed.

These alternative interpretations generate different problems to be solved. For the bicycle, it means how features such as aesthetics, convenience, and speed should be prioritized. It also considers tradeoffs, such as between traction and speed.

Relevant social groups

The most basic relevant groups are the users and the producers of the technological artifact, but most often many subgroups can be delineated – users with different socioeconomic status, competing producers, etc. Sometimes there are relevant groups who are neither users, nor producers of the technology, for example, journalists, politicians, and civil organizations. Trevor Pinch has argued that the salespeople of technology should also be included in the study of technology. The groups can be distinguished based on their shared or diverging interpretations of the technology in question.

Design flexibility

Just as technologies have different meanings in different social groups, there are always multiple ways of constructing technologies. A particular design is only a single point in the large field of technical possibilities, reflecting the interpretations of certain relevant groups.

Problems and conflicts

The different interpretations often give rise to conflicts between criteria that are hard to resolve technologically (e.g., in the case of the bicycle, one such problem was how a woman could ride the bicycle in a skirt while still adhering to standards of decency), or conflicts between the relevant groups (the "Anti-cyclists" lobbied for the banning of the bicycles). Different groups in different societies construct different problems, leading to different designs.

Second Stage: Closure

The second stage of the SCOT methodology is to show how closure is achieved.

Over time, as technologies are developed, the interpretative and design flexibility collapse through closure mechanisms. Two examples of closure mechanisms:

1. Rhetorical closure: When social groups see the problem as being solved, the need for alternative designs diminishes. This is often the result of advertising.
2. Redefinition of the problem: A design standing in the focus of conflicts can be stabilized by using it to solve a different, new problem, which ends up being solved by this very design. As an example, the aesthetic and technical problems of the air tire diminished, as the technology advanced to the stage where air tire bikes started to win the bike races. Tires were still considered cumbersome and ugly, but they provided a solution to the "speed problem", and this overrode previous concerns.

Closure is not permanent. New social groups may form and reintroduce interpretative flexibility, causing a new round of debate or conflict about a technology. (For instance, in the 1890s automobiles were seen as the "green" alternative, a cleaner environmentally-friendly technology, to horse-powered vehicles; by the 1960s, new social groups had introduced new interpretations about the environmental effects of the automobile, eliciting the opposite conclusion.)

Subsequent extension of the SCOT theory

Many other historians and sociologists of technology extended the original SCOT theory.

Technological Frame

Relating the content of the technological artifact to the wider sociopolitical milieu

This is often considered the third stage of the original theory.

For example, Paul N. Edwards shows in his book "The Closed World: Computers and the Politics of Discourse in Cold War America" the strong relations between the political discourse of the Cold War and the computer designs of this era.

Criticism

In 1993, Langdon Winner published a critique of SCOT entitled "Upon Opening the Black Box and Finding it Empty: Social Constructivism and the Philosophy of Technology." In it, he argues that social constructivism is an overly narrow research program. He identifies the following specific limitations in social constructivism:

1. It explains how technologies arise, but ignores the consequences of the technologies after the fact. This results in a sociology that says nothing about how such technologies matter in the broader context.
2. It examines social groups and interests that contribute to the construction of technology, but ignores those who have no voice in the process, yet are affected by it. Likewise, when documenting technological contingencies and choices, it fails to account for those options that never made it to the table. According to Winner, this results in conservative and elitist sociology.
3. It is superficial in that it focuses on how the immediate needs, interests, problems and solutions of chosen social groups influence technological choice, but disregards any possible deeper cultural, intellectual or economic origins of social choices concerning technology.
4. It actively avoids taking any kind of moral stance or passing judgment on the relative merits of the alternative interpretations of a technology. This indifference makes it unhelpful in addressing important debates about the place of technology in human affairs.

Other critics include Stewart Russell with his letter in the journal Social Studies of Science titled "The Social Construction of Artifacts: A Response to Pinch and Bijker".

Deborah Deliyannis, Hendrik Dey, and Paolo Squatriti criticize the concept of social construction of technology for being a false dichotomy with a technologically determinist straw man that ignores third, fourth and more alternatives, as well as for overlooking the process of how the technology is developed as something that can work. For example, accounting for which groups would have interests in a windmill cannot explain how a windmill is practically constructed, nor does it account for the difference between having the knowledge but for some reason not using it and lacking the knowledge altogether. This distinction between knowledge that have not yet been invented and knowledge that is merely prevented from being used by commercial, bureaucratic or other socially constructed factors, which it is argued that SCOT overlooks, is argued to explain the archaeological evidence of rich technological cultures in the aftermath of the collapse of civilizations (such as early medieval technology in the aftermath of the collapse of the Roman Empire, which was much richer than it is depicted as by the "Dark Medieval" stereotype) as a result of technology being remembered even when prevented from being used with the potential to being put into use when the artificial repression is no longer in place due to societal collapse.

Brain abscess

From Wikipedia, the free encyclopedia

(Redirected from Cerebral abscess)

 

Brain abscess
Brain abscess in a person with a CSF shunt. The abscess is the darker gray region in the lower left of the image (corresponding to the right parietal lobe). The lateral ventricles are visible in black in the center of the brain, adjacent to the abscess.
Specialty	Neurology, infectious diseases

Brain abscess (or cerebral abscess) is an abscess within the brain tissue caused by inflammation and collection of infected material coming from local (ear infection, dental abscess, infection of paranasal sinuses, infection of the mastoid air cells of the temporal bone, epidural abscess) or remote (lung, heart, kidney etc.) infectious sources. The infection may also be introduced through a skull fracture following a head trauma or surgical procedures. Brain abscess is usually associated with congenital heart disease in young children. It may occur at any age but is most frequent in the third decade of life.

Signs and symptoms

Fever, headache, and neurological problems, while classic, only occur in 20% of people with brain abscess.

The famous triad of fever, headache and focal neurologic findings are highly suggestive of brain abscess. These symptoms are caused by a combination of increased intracranial pressure due to a space-occupying lesion (headache, vomiting, confusion, coma), infection (fever, fatigue etc.) and focal neurologic brain tissue damage (hemiparesis, aphasia etc.).

The most frequent presenting symptoms are headache, drowsiness, confusion, seizures, hemiparesis or speech difficulties together with fever with a rapidly progressive course. Headache is characteristically worse at night and in the morning, as the intracranial pressure naturally increases when in the supine position. This elevation similarly stimulates the medullary vomiting center and area postrema, leading to morning vomiting.

Other symptoms and findings depend largely on the specific location of the abscess in the brain. An abscess in the cerebellum, for instance, may cause additional complaints as a result of brain stem compression and hydrocephalus. Neurological examination may reveal a stiff neck in occasional cases (erroneously suggesting meningitis).

Pathophysiology

Bacterial

Brain abscess after metastasis treatment.

Anaerobic and microaerophilic cocci and gram-negative and gram-positive anaerobic bacilli are the predominant bacterial isolates. Many brain abscesses are polymicrobial. The predominant organisms include: Staphylococcus aureus, aerobic and anaerobic streptococci (especially Streptococcus intermedius), Bacteroides, Prevotella, and Fusobacterium species, Enterobacteriaceae, Pseudomonas species, and other anaerobes. Less common organisms include: Haemophillus influenzae, Streptococcus pneumoniae and Neisseria meningitidis.

Bacterial abscesses rarely (if ever) arise de novo within the brain although establishing a cause can be difficult in many cases. There is almost always a primary lesion elsewhere in the body that must be sought assiduously because failure to treat the primary lesion will result in relapse. In cases of trauma, for example in compound skull fractures where fragments of bone are pushed into the substance of the brain, the cause of the abscess is obvious. Similarly, bullets and other foreign bodies may become sources of infection if left in place. The location of the primary lesion may be suggested by the location of the abscess: infections of the middle ear result in lesions in the middle and posterior cranial fossae; congenital heart disease with right-to-left shunts often result in abscesses in the distribution of the middle cerebral artery; and infection of the frontal and ethmoid sinuses usually results in collection in the subdural sinuses.

Other organisms

Fungi and parasites may also cause the disease. Fungi and parasites are especially associated with immunocompromised patients. Other causes include: Nocardia asteroides, Mycobacterium, Fungi (e.g. Aspergillus, Candida, Cryptococcus, Mucorales, Coccidioides, Histoplasma capsulatum, Blastomyces dermatitidis, Bipolaris, Exophiala dermatitidis, Curvularia pallescens, Ochroconis gallopava, Ramichloridium mackenziei, Pseudallescheria boydii), Protozoa (e.g. Toxoplasma gondii, Entamoeba histolytica, Trypanosoma cruzi, Schistosoma, Paragonimus), and Helminths (e.g. Taenia solium). Organisms that are most frequently associated with brain abscess in patients with AIDS are poliovirus, Toxoplasma gondii, and Cryptococcus neoformans, though in infection with the latter organism, symptoms of meningitis generally predominate.

These organisms are associated with certain predisposing conditions:

• Sinus and dental infections—Aerobic and anaerobic streptococci, anaerobic gram-negative bacilli (e.g. Prevotella, Porphyromonas, Bacteroides), Fusobacterium, S. aureus, and Enterobacteriaceae
• Penetrating trauma—S. aureus, aerobic streptococci, Enterobacteriaceae, and Clostridium spp.
• Pulmonary infections—Aerobic and anaerobic streptococci, anaerobic gram-negative bacilli (e.g. Prevotella, Porphyromonas, Bacteroides), Fusobacterium, Actinomyces, and Nocardia
• Congenital heart disease—Aerobic and microaerophilic streptococci, and S. aureus
• HIV infection—T. gondii, Mycobacterium, Nocardia, Cryptococcus, and Listeria monocytogenes
• Transplantation—Aspergillus, Candida, Cryptococcus, Mucorales, Nocardia, and T. gondii
• Neutropenia—Aerobic gram-negative bacilli, Aspergillus, Candida, and Mucorales

Diagnosis

MRI (T1 with contrast) showing the ring-enhancing lesion. From a rare case report of an abscess formed as a complication of the CSF shunt. Jamjoom et al., 2009.

The diagnosis is established by a computed tomography (CT) (with contrast) examination. At the initial phase of the inflammation (which is referred to as cerebritis), the immature lesion does not have a capsule and it may be difficult to distinguish it from other space-occupying lesions or infarcts of the brain. Within 4–5 days the inflammation and the concomitant dead brain tissue are surrounded with a capsule, which gives the lesion the famous ring-enhancing lesion appearance on CT examination with contrast (since intravenously applied contrast material can not pass through the capsule, it is collected around the lesion and looks as a ring surrounding the relatively dark lesion). Lumbar puncture procedure, which is performed in many infectious disorders of the central nervous system is contraindicated in this condition (as it is in all space-occupying lesions of the brain) because removing a certain portion of the cerebrospinal fluid may alter the concrete intracranial pressure balances and causes the brain tissue to move across structures within the skull (brain herniation).

Ring enhancement may also be observed in cerebral hemorrhages (bleeding) and some brain tumors. However, in the presence of the rapidly progressive course with fever, focal neurologic findings (hemiparesis, aphasia etc.) and signs of increased intracranial pressure, the most likely diagnosis should be the brain abscess.

Treatment

The treatment includes lowering the increased intracranial pressure and starting intravenous antibiotics (and meanwhile identifying the causative organism mainly by blood culture studies).^{[citation needed]}

Hyperbaric oxygen therapy (HBO2 or HBOT) is indicated as a primary and adjunct treatment which provides four primary functions. Firstly, HBOT reduces intracranial pressure. Secondly, high partial pressures of oxygen act as a bactericide and thus inhibits the anaerobic and functionally anaerobic flora common in brain abscess. Third, HBOT optimizes the immune function thus enhancing the host defense mechanisms and fourth, HBOT has been found to be of benefit when brain abscess is concomitant with cranial osteomyelitis.

Secondary functions of HBOT include increased stem cell production and up-regulation of VEGF which aid in the healing and recovery process.

Surgical drainage of the abscess remains part of the standard management of bacterial brain abscesses. The location and treatment of the primary lesion is also crucial, as is the removal of any foreign material (bone, dirt, bullets, and so forth).

There are few exceptions to this rule: Haemophilus influenzae meningitis is often associated with subdural effusions that are mistaken for subdural empyemas. These effusions resolve with antibiotics and require no surgical treatment. Tuberculosis can produce brain abscesses that look identical to conventional bacterial abscesses on CT imaging. Surgical drainage or aspiration is often necessary to identify Mycobacterium tuberculosis, but once the diagnosis is made no further surgical intervention is necessary.

CT guided stereotactic aspiration is also indicated in the treatment of brain abscess. The use of pre-operative imaging, intervention with post-operative clinical and biochemical monitoring used to manage brain abscesses today dates back to the Pennybacker system pioneered by Somerset, Kentucky-born neurosurgeon Joseph Buford Pennybacker, director of the neurosurgery department of the Radcliffe Infirmary, Oxford from 1952 to 1971. 

Prognosis

While death occurs in about 10% of cases, people do well about 70% of the time. This is a large improvement from the 1960s due to improved ability to image the head, more effective neurosurgery and more effective antibiotics.

Evolution of the brain

From Wikipedia, the free encyclopedia

https://en.wikipedia.org/wiki/Evolution_of_the_brain 

Evolution of the brain from ape to man

The evolution of the brain refers to the progressive development and complexity of neural structures over millions of years, resulting in the diverse range of brain sizes and functions observed across different species today, particularly in vertebrates.

The evolution of the brain has exhibited diverging adaptations within taxonomic classes, such as Mammalia, and even more diverse adaptations across other taxonomic classes. Brain-to-body size scales allometrically. This means that as body size changes, so do other physiological, anatomical, and biochemical connections between the brain and body. Small-bodied mammals tend to have relatively large brains compared to their bodies, while larger mammals (such as whales) have smaller brain-to-body ratios. When brain weight is plotted against body weight for primates, the regression line of the sample points can indicate the brain power of a species. For example, lemurs fall below this line, suggesting that for a primate of their size, a larger brain would be expected. In contrast, humans lie well above this line, indicating they are more encephalized than lemurs and, in fact, more encephalized than any other primate. This suggests that human brains have undergone a larger evolutionary increase in complexity relative to size. Some of these changes have been linked to multiple genetic factors, including proteins and other organelles.

Early history

Main article: Evolution of nervous systems

One approach to understanding overall brain evolution is to use a paleoarchaeological timeline to trace the necessity for ever increasing complexity in structures that allow for chemical and electrical signaling. Because brains and other soft tissues do not fossilize as readily as mineralized tissues, scientists often look to other structures as evidence in the fossil record to get an understanding of brain evolution. This, however, leads to a dilemma as the emergence of organisms with more complex nervous systems with protective bone or other protective tissues that can then readily fossilize occur in the fossil record before evidence for chemical and electrical signaling. Evidence from 2008 showed that the ability to transmit electrical and chemical signals existed even before more complex multicellular lifeforms.

Fossilization of brain tissue, as well as other soft tissue, is nonetheless possible, and scientists can infer that the first brain structure appeared at least 521 million years ago, with fossil brain tissue present in sites of exceptional preservation.

Another approach to understanding brain evolution is to look at extant organisms that do not possess complex nervous systems, comparing anatomical features that allow for chemical or electrical messaging. For example, choanoflagellates are organisms that possess various membrane channels that are crucial to electrical signaling. The membrane channels of choanoflagellates' are homologous to the ones found in animal cells, and this is supported by the evolutionary connection between early choanoflagellates and the ancestors of animals. Another example of extant organisms with the capacity to transmit electrical signals would be the glass sponge, a multicellular organism, which is capable of propagating electrical impulses without the presence of a nervous system.

Before the evolutionary development of the brain, nerve nets, the simplest form of a nervous system developed. These nerve nets were a sort of precursor for the more evolutionarily advanced brains. They were first observed in Cnidaria and consist of a number of neurons spread apart that allow the organism to respond to physical contact. They are able to rudimentarily detect food and other chemicals, but these nerve nets do not allow them to detect the source of the stimulus.

Ctenophores also demonstrate this crude precursor to a brain or centralized nervous system, however they phylogenetically diverged before the phylum Porifera (the Sponges) and Cnidaria. There are two current theories on the emergence of nerve nets. One theory is that nerve nets may have developed independently in Ctenophores and Cnidarians. The other theory states that a common ancestor may have developed nerve nets, but they were lost in Porifera. While comparing the average neuron size and the packing density the difference between primate and mammal brains is shown.

A trend in brain evolution according to a study done with mice, chickens, monkeys and apes concluded that more evolved species tend to preserve the structures responsible for basic behaviors. A long term human study comparing the human brain to the primitive brain found that the modern human brain contains the primitive hindbrain region – what most neuroscientists call the protoreptilian brain. The purpose of this part of the brain is to sustain fundamental homeostatic functions, which are self regulating processes organisms use to help their bodies adapt. The pons and medulla are major structures found there. A new region of the brain developed in mammals about 250 million years after the appearance of the hindbrain. This region is known as the paleomammalian brain, the major parts of which are the hippocampi and amygdalas, often referred to as the limbic system. The limbic system deals with more complex functions including emotional, sexual and fighting behaviors. Of course, animals that are not vertebrates also have brains, and their brains have undergone separate evolutionary histories.

The brainstem and limbic system are largely based on nuclei, which are essentially balled-up clusters of tightly packed neurons and the axon fibers that connect them to each other, as well as to neurons in other locations. The other two major brain areas (the cerebrum and cerebellum) are based on a cortical architecture. At the outer periphery of the cortex, the neurons are arranged into layers (the number of which vary according to species and function) a few millimeters thick. There are axons that travel between the layers, but the majority of axon mass is below the neurons themselves. Since cortical neurons and most of their axon fiber tracts do not have to compete for space, cortical structures can scale more easily than nuclear ones. A key feature of cortex is that because it scales with surface area, more of it can be fit inside a skull by introducing convolutions, in much the same way that a dinner napkin can be stuffed into a glass by wadding it up. The degree of convolution is generally greater in species with more complex behavior, which benefits from the increased surface area.

The cerebellum, or "little brain," is behind the brainstem and below the occipital lobe of the cerebrum in humans. Its purposes include the coordination of fine sensorimotor tasks, and it may be involved in some cognitive functions, such as language and different motor skills that may involve hands and feet. The cerebellum helps keep equilibrium. Damage to the cerebellum would result in all physical roles in life to be affected. Human cerebellar cortex is finely convoluted, much more so than cerebral cortex. Its interior axon fiber tracts are called the arbor vitae, or Tree of Life.

The area of the brain with the greatest amount of recent evolutionary change is called the neocortex. In reptiles and fish, this area is called the pallium and is smaller and simpler relative to body mass than what is found in mammals. According to research, the cerebrum first developed about 200 million years ago. It is responsible for higher cognitive functions—for example, language, thinking, and related forms of information processing. It is also responsible for processing sensory input (together with the thalamus, a part of the limbic system that acts as an information router). The thalamus receives the different sensations before the information is then passed onto the cerebral cortex. Most of its function is subconscious, that is, not available for inspection or intervention by the conscious mind. The neocortex is an elaboration, or outgrowth, of structures in the limbic system, with which it is tightly integrated. The neocortex is the main part controlling many brain functions as it covers half of the whole brain in volume. The development of these recent evolutionary changes in the neocortex likely occurred as a result of new neural network formations and positive selections of certain genetic components.

Role of embryology

Further information: Embryology and Brain development timelines

In addition to studying the fossil record, evolutionary history can be investigated via embryology. An embryo is an unborn/unhatched animal and evolutionary history can be studied by observing how processes in embryonic development are conserved (or not conserved) across species. Similarities between different species may indicate evolutionary connection. One way anthropologists study evolutionary connection between species is by observing orthologs. An ortholog is defined as two or more homologous genes between species that are evolutionarily related by linear descent. By using embryology the evolution of the brain can be tracked between various species.

Bone morphogenetic protein (BMP), a growth factor that plays a significant role in embryonic neural development, is highly conserved amongst vertebrates, as is sonic hedgehog (SHH), a morphogen that inhibits BMP to allow neural crest development. Tracking these growth factors with the use of embryology provides a deeper understanding of what areas of the brain diverged in their evolution. Varying levels of these growth factors lead to differing embryonic neural development which then in turn affects the complexity of future neural systems. Studying the brain's development at various embryonic stages across differing species provides additional insight into what evolutionary changes may have historically occurred. This then allows scientists to look into what factors may have caused such changes, such as links to neural network diversity, growth factor production, protein- coding selections, and other genetic factors.

Randomizing access and increasing size

Some animal phyla have gone through major brain enlargement through evolution (e.g. vertebrates and cephalopods both contain many lineages in which brains have grown through evolution) but most animal groups are composed only of species with extremely small brains. Some scientists argue that this difference is due to vertebrate and cephalopod neurons having evolved ways of communicating that overcome the scalability problem of neural networks while most animal groups have not. They argue that the reason why traditional neural networks fail to improve their function when they scale up is because filtering based on previously known probabilities cause self-fulfilling prophecy-like biases that create false statistical evidence giving a completely false worldview and that randomized access can overcome this problem and allow brains to be scaled up to more discriminating conditioned reflexes at larger brains that lead to new worldview forming abilities at certain thresholds. This means when neurons scale in a non randomized fashion that their functionality becomes more limited due to their neural networks being unable to process more complex systems without the exposure to new formations. This is explained by randomization allowing the entire brain to eventually get access to all information over the course of many shifts even though instant privileged access is physically impossible. They cite that vertebrate neurons transmit virus-like capsules containing RNA that are sometimes read in the neuron to which it is transmitted and sometimes passed further on unread which creates randomized access, and that cephalopod neurons make different proteins from the same gene which suggests another mechanism for randomization of concentrated information in neurons, both making it evolutionarily worth scaling up brains.

Brain re-organization

With the use of in vivo Magnetic resonance imaging (MRI) and tissue sampling, different cortical samples from members of each hominoid species were analyzed. In each species, specific areas were either relatively enlarged or shrunken, which can detail neural organizations. Different sizes in the cortical areas can show specific adaptations, functional specializations and evolutionary events that were changes in how the hominoid brain is organized. In early prediction it was thought that the frontal lobe, a large part of the brain that is generally devoted to behavior and social interaction, predicted the differences in behavior between hominoid and humans. Discrediting this theory was evidence supporting that damage to the frontal lobe in both humans and hominoids show atypical social and emotional behavior; thus, this similarity means that the frontal lobe was not very likely to be selected for reorganization. Instead, it is now believed that evolution occurred in other parts of the brain that are strictly associated with certain behaviors. The reorganization that took place is thought to have been more organizational than volumetric; whereas the brain volumes were relatively the same but specific landmark position of surface anatomical features, for example, the lunate sulcus suggest that the brains had been through a neurological reorganization. There is also evidence that the early hominin lineage also underwent a quiescent period, or a period of dormancy, which supports the idea of neural reorganization.

Dental fossil records for early humans and hominins show that immature hominins, including australopithecines and members of Homo, have a quiescent period (Bown et al. 1987). A quiescent period is a period in which there are no dental eruptions of adult teeth; at this time the child becomes more accustomed to social structure, and development of culture. During this time the child is given an extra advantage over other hominoids, devoting several years into developing speech and learning to cooperate within a community. This period is also discussed in relation to encephalization. It was discovered that chimpanzees do not have this neutral dental period, which suggests that a quiescent period occurred in very early hominin evolution. Using the models for neurological reorganization it can be suggested the cause for this period, dubbed middle childhood, is most likely for enhanced foraging abilities in varying seasonal environments.

Genetic factors in recent evolution

Genes involved in the neuro-development and in neuron physiology are extremely conserved between mammalian species (94% of genes expressed in common between humans and chimpanzees, 75% between humans and mice), compared to other organs. Therefore, few genes account for species differences in the human brain development and function.

Development of the human cerebral cortex

Main differences rely on the evolution of non-coding genomic regions, involved in the regulation of gene expression. This leads to differential expression of genes during the development of the human brain compared to other species, including chimpanzees. Some of these regions evolved fast in the human genome (human accelerated regions). The new genes expressed during human neurogenesis are notably associated with the NOTCH, WNT and mTOR pathways, but are also involved ZEB2, PDGFD and its receptor PDGFRβ. The human cerebral cortex is also characterized by a higher gradient of retinoic acid in the prefrontal cortex, leading to higher prefrontal cortex volume. All these differential gene expression lead to higher proliferation of the neural progenitors leading to more neurons in the human cerebral cortex. Some genes are lost in their expression during the development of the human cerebral cortex like GADD45G and FLRT2/FLRT3.

Another source of molecular novelty rely on new genes in the human or hominid genomes through segmental duplication. Around 30 new genes in the hominid genomes are dynamically expressed during human corticogenesis. Some were linked to higher proliferation of neural progenitors: NOTCH2NLA/B/C, ARHGAP11B, CROCCP2, TBC1D3, TMEM14B. Patients with deletions with NOTCH2NL genes display microcephaly, showing the necessity of such duplicated genes, acquired in the human genomes, in the proper corticogenesis.

MCPH1 and ASPM

Bruce Lahn, the senior author at the Howard Hughes Medical Center at the University of Chicago and colleagues have suggested that there are specific genes that control the size of the human brain. These genes continue to play a role in brain evolution, implying that the brain is continuing to evolve. The study began with the researchers assessing 214 genes that are involved in brain development. These genes were obtained from humans, macaques, rats and mice. Lahn and the other researchers noted points in the DNA sequences that caused protein alterations. These DNA changes were then scaled to the evolutionary time that it took for those changes to occur. The data showed the genes in the human brain evolved much faster than those of the other species. Once this genomic evidence was acquired, Lahn and his team decided to find the specific gene or genes that allowed for or even controlled this rapid evolution. Two genes were found to control the size of the human brain as it develops. These genes are Microcephalin (MCPH1) and Abnormal Spindle-like Microcephaly (ASPM). The researchers at the University of Chicago were able to determine that under the pressures of selection, both of these genes showed significant DNA sequence changes. Lahn's earlier studies displayed that Microcephalin experienced rapid evolution along the primate lineage which eventually led to the emergence of Homo sapiens. After the emergence of humans, Microcephalin seems to have shown a slower evolution rate. On the contrary, ASPM showed its most rapid evolution in the later years of human evolution once the divergence between chimpanzees and humans had already occurred.

Each of the gene sequences went through specific changes that led to the evolution of humans from ancestral relatives. In order to determine these alterations, Lahn and his colleagues used DNA sequences from multiple primates then compared and contrasted the sequences with those of humans. Following this step, the researchers statistically analyzed the key differences between the primate and human DNA to come to the conclusion, that the differences were due to natural selection. The changes in DNA sequences of these genes accumulated to bring about a competitive advantage and higher fitness that humans possess in relation to other primates. This comparative advantage is coupled with a larger brain size which ultimately allows the human mind to have a higher cognitive awareness.

ZEB2 protein

ZEB2

ZEB2 is a protein- coding gene in the Homo sapien species. A 2021 study found that a delayed change in the shape of early brain cells causes the distinctly large human forebrain compared to other apes and identify ZEB2 as a genetic regulator of it, whose manipulation lead to acquisition of nonhuman ape cortical architecture in brain organoids.

NOVA1

In 2021, researchers reported that brain organoids created with stem cells into which they reintroduced the archaic gene variant NOVA1 present in Neanderthals and Denisovans via CRISPR-Cas9 shows that it has a major impact on neurodevelopment and that such genetic mutations during the evolution of the human brain underlie traits that separate modern humans from extinct Homo species. They found that expression of the archaic NOVA1 in cortical organoids leads to "modified synaptic protein interactions, affects glutamatergic signaling, underlies differences in neuronal connectivity, and promotes higher heterogeneity of neurons regarding their electrophysiological profiles". This research suggests positive selection of the modern NOVA1 gene, which may have promoted the randomization of neural scaling. A subsequent study failed to replicate the differences in organoid morphology between the modern human and the archaic NOVA1 variant, consistent with suspected unwanted side effects of CRISPR editing in the original study.

SRGAP2C and neuronal maturation

Less is known about neuronal maturation. Synaptic gene and protein expression are protracted, in line with the protracted synaptic maturation of human cortical neurons so called neoteny. This probably relies on the evolution of non-coding genomic regions. The consequence of the neoteny could be an extension of the period of synaptic plasticity and therefore of learning. A human-specific duplicated gene, SRGAP2C accounts for this synaptic neoteny and acts by regulating molecular pathways linked to neurodevelopmental disorders. Other genes are deferentially expressed in human neurons during their development such as osteocrin or cerebelin-2.

LRRC37B and neuronal electrical properties

Even less is known about molecular specificities linked to the physiology of the human neurons. Human neurons are more divergent in the genes they express compared to chimpanzees than chimpanzees to gorilla, which suggests an acceleration of non-coding genomic regions associated with genes involved in neuronal physiology, in particular linked to the synapses. A hominid-specific duplicated gene, LRRC37B, codes for a transmembrane receptor that is selectively localized at the axon initial segment of human cortical pyramidal neurons. It inhibits their voltage-gated sodium channels that generate the action potentials leading to a lower neuronal excitability. Human cortical pyramidal neurons display a lower excitability compared to other mammalian species (including macaques and marmosets) which could lead to different circuit functions in the human species. Therefore, LRRC37B whose expression has been acquired in the human lineage after the separation from the chimpanzees could be a key gene in the function of the human cerebral cortex. LRRC37B binds to secreted FGF13A and SCN1B and modulate indirectly the activity of SCN8A, all involved in neural disorders such as epilepsy and autism. Therefore, LRRC37B may contribute to human-specific sensitivities to such disorders, both involved defects in neuronal excitability.

Genome repair

The genomic DNA of postmitotic neurons ordinarily does not replicate. Protection strategies have evolved to ensure the distinctive longevity of the neuronal genome. Human neurons are reliant on DNA repair processes to maintain function during an individual's life-time. DNA repair tends to occur preferentially at evolutionarily conserved sites that are specifically involved with the regulation of expression of genes essential for neuronal identity and function.

Other factors

Many other genetics may also be involved in recent evolution of the brain.

• For instance, scientists showed experimentally, with brain organoids grown from stem cells, how differences between humans and chimpanzees are also substantially caused by non-coding DNA (often discarded as relatively meaningless "junk DNA") – in particular via CRE-regulated expression of the ZNF558 gene for a transcription factor that regulates the SPATA18 gene. SPATA18 gene encodes a protein and is able to influence lysosome-like organelles that are found within mitochondria that eradicate oxidized mitochondrial proteins. This helps monitor the quality of the mitochondria as the disregulation of its quality control has been linked to cancer and degenerative diseases. This example may contribute to illustrations of the complexity and scope of relatively recent evolution to Homo sapiens.
• A change in gene TKTL1 could be a key factor of recent brain evolution and difference of modern humans to (other) apes and Neanderthals, related to neocortex-neurogenesis. However, the "archaic" allele attributed to Neanderthals is present in 0.03% of Homo sapiens, but no resultant phenotypic differences have been reported in these people. Additionally, as Herai et al. contend, more is not always better. In fact, enhanced neuron production "can lead to an abnormally enlarged cortex and layer-specific imbalances in glia/neuron ratios and neuronal subpopulations during neurodevelopment." Even the original study's authors agree that “any attempt to discuss prefrontal cortex and cognitive advantage of modern humans over Neandertals based on TKTL1 alone is problematic”.
• Some of the prior study's authors reported a similar ARHGAP11B mutation in 2016.
• Epigenetics also play a major role in the brain evolution in and to humans.

Recently evolved traits

Language

A genome-wide association study meta-analysis reported genetic factors of, the so far uniquely human, language-related capacities, in particular factors of differences in skill-levels of five tested traits. It e.g. identified association with neuroanatomy of a language-related brain area via neuroimaging correlation. The data contributes to identifying or understanding the biological basis of this recently evolved characteristic capability.

Human brain evolution

Further information: Cranial capacity and Brain-to-body mass ratio

One of the prominent ways of tracking the evolution of the human brain is through direct evidence in the form of fossils. The evolutionary history of the human brain shows primarily a gradually bigger brain relative to body size during the evolutionary path from early primates to hominids and finally to Homo sapiens. Because fossilized brain tissue is rare, a more reliable approach is to observe anatomical characteristics of the skull that offer insight into brain characteristics. One such method is to observe the endocranial cast (also referred to as endocasts). Endocasts occur when, during the fossilization process, the brain deteriorates away, leaving a space that is filled by surrounding sedimentary material over time. These casts, give an imprint of the lining of the brain cavity, which allows a visualization of what was there. This approach, however, is limited in regard to what information can be gathered. Information gleaned from endocasts is primarily limited to the size of the brain (cranial capacity or endocranial volume), prominent sulci and gyri, and size of dominant lobes or regions of the brain. While endocasts are extremely helpful in revealing superficial brain anatomy, they cannot reveal brain structure, particularly of deeper brain areas. By determining scaling metrics of cranial capacity as it relates to total number of neurons present in primates, it is also possible to estimate the number of neurons through fossil evidence.

Facial reconstruction of a Homo georgicus from over 1.5 Mya

Despite the limitations to endocasts, they can and do provide a basis for understanding human brain evolution, which shows primarily a gradually bigger brain. The evolutionary history of the human brain shows primarily a gradually bigger brain relative to body size during the evolutionary path from early primates to hominins and finally to Homo sapiens. This trend that has led to the present day human brain size indicates that there has been a 2-3 factor increase in size over the past 3 million years. This can be visualized with current data on hominin evolution, starting with Australopithecus—a group of hominins from which humans are likely descended. After all of the data, all observations concluded that the main development that occurred during evolution was the increase of brain size.

However, recent research has called into question the hypothesis of a threefold increase in brain size when comparing Homo sapiens with Australopithecus and chimpanzees. For example, in an article published in 2022 compiled a large data set of contemporary humans and found that the smallest human brains are less than twice that of large brained chimpanzees. As the authors write '...the upper limit of chimpanzee brain size is 500g/ml yet numerous modern humans have brain size below 900 g/ml.' (Note that in this quote, the unit g/ml is to be understood not in the usual way as gram per millilitre but rather as gram or millilitre. This is consistent because brain density is close to 1 g/ml.) Consequently, the authors argue that the notion of an increase in brain size being related to advances in cognition needs to be re-thought in light of global variation in brain size, as the brains of many modern humans with normal cognitive capacities are only 400g/ml larger than chimpanzees. Additionally, much of the increase in brain size - which occurs to a much greater degree in specific modern populations - can be explained by increases in correlated body size related to diet and climatic factors.

Australopiths lived from 3.85 to 2.95 million years ago with the general cranial capacity somewhere near that of the extant chimpanzee—around 300–500 cm³. Considering that the volume of the modern human brain is around 1,352 cm³ on average this represents a substantial amount of brain mass evolved. Australopiths are estimated to have a total neuron count of ~30-35 billion.

Progressing along the human ancestral timeline, brain size continues to steadily increase (see Homininae) when moving into the era of Homo. For example, Homo habilis, living 2.4 million to 1.4 million years ago and argued to be the first Homo species based on a host of characteristics, had a cranial capacity of around 600 cm³. Homo habilis is estimated to have had ~40 billion neurons.

A little closer to present day, Homo heidelbergensis lived from around 700,000 to 200,000 years ago and had a cranial capacity of around 1290 cm³ and having around 76 billion neurons.

Homo neaderthalensis, living 400,000 to 40,000 years ago, had a cranial capacity comparable to that of modern humans at around 1500–1600 cm³on average, with some specimens of Neanderthal having even greater cranial capacity. Neanderthals are estimated to have had around 85 billion neurons. The increase in brain size topped with Neanderthals, possibly due to their larger visual systems.

It is also important to note that the measure of brain mass or volume, seen as cranial capacity, or even relative brain size, which is brain mass that is expressed as a percentage of body mass, are not a measure of intelligence, use, or function of regions of the brain. Total neurons, however, also do not indicate a higher ranking in cognitive abilities. Elephants have a higher number of total neurons (257 billion) compared to humans (100 billion). Relative brain size, overall mass, and total number of neurons are only a few metrics that help scientists follow the evolutionary trend of increased brain to body ratio through the hominin phylogeny.

In 2021, scientists suggested that the brains of early Homo from Africa and Dmanisi, Georgia, Western Asia "retained a great ape-like structure of the frontal lobe" for far longer than previously thought – until about 1.5 million years ago. Their findings imply that Homo first dispersed out of Africa before human brains evolved to roughly their modern anatomical structure in terms of the location and organization of individual brain regions. It also suggests that this evolution occurred – not during – but only long after the Homo lineage evolved ~2.5 million years ago and after they – Homo erectus in particular – evolved to walk upright. What is the least controversial is that the brain expansion started about 2.6 Ma (about the same as the start of the Pleistocene), and ended around 0.2 Ma.

Evolution of the neocortex

Further information: Neocortex

In addition to just the size of the brain, scientists have observed changes in the folding of the brain, as well as in the thickness of the cortex. The more convoluted the surface of the brain is, the greater the surface area of the cortex which allows for an expansion of cortex. It is the most evolutionarily advanced part of the brain. Greater surface area of the brain is linked to higher intelligence as is the thicker cortex but there is an inverse relationship—the thicker the cortex, the more difficult it is for it to fold. In adult humans, thicker cerebral cortex has been linked to higher intelligence.

The neocortex is the most advanced and most evolutionarily young part of the human brain. It is six layers thick and is only present in mammals. It is especially prominent in humans and is the location of most higher level functioning and cognitive ability. The six-layered neocortex found in mammals is evolutionarily derived from a three-layer cortex present in all modern reptiles. This three-layer cortex is still conserved in some parts of the human brain such as the hippocampus and is believed to have evolved in mammals to the neocortex during the transition between the Triassic and Jurassic periods. After looking at history, the mammals had little neocortex compared to the primates as they had more cortex. The three layers of this reptilian cortex correlate strongly to the first, fifth and sixth layers of the mammalian neocortex. Across species of mammals, primates have greater neuronal density compared to rodents of similar brain mass and this may account for increased intelligence.

Theories of human brain evolution

Explanations of the rapid evolution and exceptional size of the human brain can be classified into five groups: instrumental, social, environmental, dietary, and anatomo-physiological. The instrumental hypotheses are based on the logic that evolutionary selection for larger brains is beneficial for species survival, dominance, and spread, because larger brains facilitate food-finding and mating success. The social hypotheses suggest that social behavior stimulates evolutionary expansion of brain size. Similarly, the environmental hypotheses suppose that encephalization is promoted by environmental factors such as stress, variability, and consistency. The dietary theories maintain that food quality and certain nutritional components directly contributed to the brain growth in the Homo genus. The anatomo-physiologic concepts, such as cranio-cerebral vascular hypertension due to head-down posture of the anthropoid fetus during pregnancy, are primarily focused on anatomic-functional changes that predispose to brain enlargement.

No single theory can completely account for human brain evolution. Multiple selective pressures in combination seems to have been involved. Synthetic theories have been proposed, but have not clearly explained reasons for the uniqueness of the human brain. Puzzlingly, brain enlargement has been found to have occurred independently in different primate lineages, but only human lineage ended up with an exceptional brain capacity. Fetal head-down posture may be an explanation of this conundrum because Homo sapiens is the only primate obligatory biped with upright posture.