Editing Brain (section)

== Research ==
{{Main|Neuroscience}}
{{Redirect|Brain research|the scientific journal|Brain Research}}
[[File:Henry Markram - Visualizing Synaptic Maps onto Neocrortical Neurons.jpg|thumb|The [[Human Brain Project]] is a large scientific research project, starting in 2013, which aims to simulate the complete human brain.]]

The field of neuroscience encompasses all approaches that seek to understand the brain and the rest of the nervous system.<ref name="Kandel 2000"/><!--Ch. 1--> [[Psychology]] seeks to understand mind and behavior, and [[neurology]] is the medical discipline that diagnoses and treats diseases of the nervous system. The brain is also the most important organ studied in [[psychiatry]], the branch of medicine that works to study, prevent, and treat [[mental disorder]]s.<ref name="Starrow 1969">{{Cite book |last1=Storrow |first1=Hugh A. |title=Outline of clinical psychiatry |date=1969 |publisher=Appleton-Century-Crofts, Educational Division |location=New York |isbn=978-0-390-85075-1 |oclc=47198}}</ref> [[Cognitive science]] seeks to unify neuroscience and psychology with other fields that concern themselves with the brain, such as [[computer science]] ([[artificial intelligence]] and similar fields) and [[philosophy]].<ref>{{Cite web|last=Thagard|first=Paul|year=2007|title=Cognitive Science|url=https://plato.stanford.edu/archives/fall2008/entries/cognitive-science/|access-date=2021-01-23|website=Stanford Encyclopedia of Philosophy|edition=Revised, 2nd}}</ref>

The oldest method of studying the brain is [[Neuroanatomy|anatomical]], and until the middle of the 20th century, much of the progress in neuroscience came from the development of better cell stains and better microscopes. Neuroanatomists study the large-scale structure of the brain as well as the microscopic structure of neurons and their components, especially synapses. Among other tools, they employ a plethora of stains that reveal neural structure, chemistry, and connectivity. In recent years, the development of [[immunostaining]] techniques has allowed investigation of neurons that express specific sets of genes. Also, ''functional neuroanatomy'' uses [[medical imaging]] techniques to correlate variations in human brain structure with differences in cognition or behavior.<ref>{{cite book|last1=Bear|first1=MF|url=https://archive.org/details/neuroscienceexpl00mark|title=Neuroscience: Exploring the Brain|last2=Connors|first2=BW|last3=Paradiso|first3=MA|publisher=Lippincott Williams & Wilkins|year=2007|isbn=978-0-7817-6003-4 |chapter=Ch. 2|url-access=registration}}</ref>

Neurophysiologists study the chemical, pharmacological, and electrical properties of the brain: their primary tools are drugs and recording devices. Thousands of experimentally developed drugs affect the nervous system, some in highly specific ways. Recordings of brain activity can be made using electrodes, either glued to the scalp as in [[electroencephalography|EEG]] studies, or implanted inside the brains of animals for [[extracellular]] recordings, which can detect action potentials generated by individual neurons.<ref>{{cite book |last=Dowling |first=JE |title=Neurons and Networks |publisher=Harvard University Press |year=2001 |isbn=978-0-674-00462-7 |pages=15–24}}</ref> Because the brain does not contain pain receptors, it is possible using these techniques to record brain activity from animals that are awake and behaving without causing distress. The same techniques have occasionally been used to study brain activity in human patients with intractable [[epilepsy]], in cases where there was a medical necessity to implant electrodes to localize the brain area responsible for [[epileptic seizure]]s.<ref>{{cite book |last1=Wyllie |first1=E |last2=Gupta |first2=A |last3=Lachhwani |first3=DK |title=The Treatment of Epilepsy: Principles and Practice |year=2005 |publisher=Lippincott Williams & Wilkins |isbn=978-0-7817-4995-4 |chapter=Ch. 77}}</ref> [[Functional imaging]] techniques such as [[Functional magnetic resonance imaging|fMRI]] are also used to study brain activity; these techniques have mainly been used with human subjects, because they require a conscious subject to remain motionless for long periods of time, but they have the great advantage of being noninvasive.<ref>{{cite book |last1=Laureys |first1=S |last2=Boly |first2=M |last3=Tononi |first3=G |chapter=Functional neuroimaging |title=The Neurology of Consciousness: Cognitive Neuroscience and Neuropathology |url=https://archive.org/details/neurologyconscio00laur_765 |url-access=limited |veditors=Laureys S, Tononi G |publisher=Academic Press |year=2009 |isbn=978-0-12-374168-4 |pages=[https://archive.org/details/neurologyconscio00laur_765/page/n45 31]–42}}</ref>

[[File:Brain-computer interface (schematic).jpg|thumb|left|300px|alt=Drawing showing a monkey in a restraint chair, a computer monitor, a rototic arm, and three pieces of computer equipment, with arrows between them to show the flow of information.|Design of an experiment in which brain activity from a monkey was used to control a robotic arm<ref>{{cite journal |title=Learning to Control a Brain–Machine Interface for Reaching and Grasping by Primates |journal=PLOS Biology |year=2003 |volume=1 |pages=193–208 |pmc=261882 |last1=Carmena |first1=JM |issue=2 |pmid=14624244 |doi=10.1371/journal.pbio.0000042 |last2=Lebedev |first2=Mikhail A. |last3=Crist |first3=Roy E. |last4=O'Doherty |first4=Joseph E. |last5=Santucci |first5=David M. |last6=Dimitrov |first6=Dragan F. |last7=Patil |first7=Parag G. |last8=Henriquez |first8=Craig S. |last9=Nicolelis |first9=Miguel A. L.|display-authors=1 |doi-access=free }}</ref>]]

Another approach to brain function is to examine the consequences of [[Brain damage|damage]] to specific brain areas. Even though it is protected by the skull and [[meninges]], surrounded by [[cerebrospinal fluid]], and isolated from the bloodstream by the blood–brain barrier, the delicate nature of the brain makes it vulnerable to numerous diseases and several types of damage. In humans, the effects of strokes and other types of brain damage have been a key source of information about brain function. Because there is no ability to experimentally control the nature of the damage, however, this information is often difficult to interpret. In animal studies, most commonly involving rats, it is possible to use electrodes or locally injected chemicals to produce precise patterns of damage and then examine the consequences for behavior.<ref>{{cite book |last1=Kolb |first1=B |last2=Whishaw |first2=I |title=Fundamentals of Human Neuropsychology |year=2008 |publisher=Macmillan |isbn=978-0-7167-9586-5 |chapter=Ch. 1}}</ref>

[[Computational neuroscience]] encompasses two approaches: first, the use of computers to study the brain; second, the study of how brains perform computation. On one hand, it is possible to write a computer program to simulate the operation of a group of neurons by making use of systems of equations that describe their electrochemical activity; such simulations are known as ''biologically realistic neural networks''. On the other hand, it is possible to study algorithms for neural computation by simulating, or mathematically analyzing, the operations of simplified "units" that have some of the properties of neurons but abstract out much of their biological complexity. The computational functions of the brain are studied both by computer scientists and neuroscientists.<ref name="Abbott">{{cite book |last1=Abbott |first1=LF |title=Theoretical Neuroscience: Computational and Mathematical Modeling of Neural Systems |publisher=MIT Press |year=2001 |isbn=978-0-262-54185-5 |last2=Dayan |first2=P |chapter=Preface}}</ref>

[[Computational neurogenetic modeling]] is concerned with the study and development of dynamic neuronal models for modeling brain functions with respect to genes and dynamic interactions between genes.

Recent years have seen increasing applications of genetic and genomic techniques to the study of the brain<ref name=Tonegawa/> and a focus on the roles of [[neurotrophic factors]] and physical activity in [[neuroplasticity]].<ref name="AirpollutionPhysicalactivity" /> The most common subjects are mice, because of the availability of technical tools. It is now possible with relative ease to "knock out" or mutate a wide variety of genes, and then examine the effects on brain function. More sophisticated approaches are also being used: for example, using [[Cre-Lox recombination]] it is possible to activate or deactivate genes in specific parts of the brain, at specific times.<ref name=Tonegawa/>

Recent years have also seen rapid advances in single-cell sequencing technologies, and these have been used to leverage the cellular heterogeneity of the brain as a means of better understanding the roles of distinct cell types in disease and biology (as well as how genomic variants influence individual cell types). In 2024, investigators studied a large integrated dataset of almost 3 million nuclei from the human prefrontal cortext from 388 individuals.<ref name="Emani">{{cite journal |title=Single-cell genomics and regulatory networks for 388 human brains |journal=[[Science (journal)|Science]] |year=2024 |volume=384 |pmid=38781369 |last1=Emani |first1=PS |last2=Liu |first2=J |issue=6698 |pages=eadi5199 |display-authors=1| doi=10.1126/science.adi5199|pmc=11365579 }}</ref> In doing so, they annotated 28 cell types to evaluate expression and chromatin variation across gene families and drug targets. They identified about half a million cell type–specific regulatory elements and about 1.5 million single-cell expression quantitative trait loci (i.e., genomic variants with strong statistical associations with changes in gene expression within specific cell types), which were then used to build cell-type regulatory networks (the study also describes cell-to-cell communication networks). These networks were found to manifest cellular changes in aging and neuropsychiatric disorders. As part of the same investigation, a machine learning model was designed to accurately impute single-cell expression (this model prioritized ~250 disease-risk genes and drug targets with associated cell types).

=== History ===
{{See also|History of neuroscience}}
[[File:Descartes-reflex.JPG|thumb|right|Illustration by [[René Descartes]] of how the brain implements a reflex response]]

The oldest brain to have been discovered was in [[Armenia]] in the [[Areni-1 cave complex]]. The brain, estimated to be over 5,000 years old, was found in the skull of a 12 to 14-year-old girl. Although the brains were shriveled, they were well preserved due to the climate found inside the cave.<ref>{{cite news|last1=Bower|first1=Bruce|date=2009-01-12|title=Armenian cave yields ancient human brain |agency=ScienceNews|url=https://www.sciencenews.org/article/armenian-cave-yields-ancient-human-brain|url-access=registration|access-date=2021-01-23}}</ref>

Early philosophers were divided as to whether the seat of the soul lies in the brain or heart. [[Aristotle]] favored the heart, and thought that the function of the brain was merely to cool the blood. [[Democritus]], the inventor of the atomic theory of matter, argued for a three-part soul, with intellect in the head, emotion in the heart, and lust near the liver.<ref name="Finger14">{{cite book|last=Finger|first=Stanley|title=Origins of Neuroscience|publisher=Oxford University Press|year=2001|isbn=978-0-19-514694-3|pages=14–15}}</ref> The unknown author of ''[[On the Sacred Disease]]'', a medical treatise in the [[Hippocratic Corpus]], came down unequivocally in favor of the brain, writing:

{{blockquote|Men ought to know that from nothing else but the brain come joys, delights, laughter and sports, and sorrows, griefs, despondency, and lamentations. ... And by the same organ we become mad and delirious, and fears and terrors assail us, some by night, and some by day, and dreams and untimely wanderings, and cares that are not suitable, and ignorance of present circumstances, desuetude, and unskillfulness. All these things we endure from the brain, when it is not healthy...|''On the Sacred Disease'', attributed to [[Hippocrates]]<ref name=Hippocrates>{{Citation |author=Hippocrates |title=On the Sacred Disease |year=2006 |orig-year=400 BCE |translator=Francis Adams |publisher=((Internet Classics Archive: The University of Adelaide Library)) |url=http://etext.library.adelaide.edu.au/mirror/classics.mit.edu/Hippocrates/sacred.html |archive-url=https://web.archive.org/web/20070926213032/http://etext.library.adelaide.edu.au/mirror/classics.mit.edu/Hippocrates/sacred.html |archive-date=September 26, 2007}}</ref>}}

[[File:1543, Andreas Vesalius' Fabrica, Base Of The Brain.jpg|thumb|left|upright|[[Andreas Vesalius]]' ''Fabrica'', published in 1543, showing the base of the human brain, including [[optic chiasm]]a, cerebellum, [[olfactory bulb]]s, etc.]]

The Roman physician [[Galen]] also argued for the importance of the brain, and theorized in some depth about how it might work. Galen traced out the anatomical relationships among brain, nerves, and muscles, demonstrating that all muscles in the body are connected to the brain through a branching network of nerves. He postulated that nerves activate muscles mechanically by carrying a mysterious substance he called ''pneumata psychikon'', usually translated as "animal spirits".<ref name=Finger14/> Galen's ideas were widely known during the Middle Ages, but not much further progress came until the Renaissance, when detailed anatomical study resumed, combined with the theoretical speculations of [[René Descartes]] and those who followed him. Descartes, like Galen, thought of the nervous system in hydraulic terms. He believed that the highest cognitive functions are carried out by a non-physical ''res cogitans'', but that the majority of behaviors of humans, and all behaviors of animals, could be explained mechanistically.<ref name="Finger14" />

The first real progress toward a modern understanding of nervous function, though, came from the investigations of [[Luigi Galvani]] (1737–1798), who discovered that a shock of static electricity applied to an exposed nerve of a dead frog could cause its leg to contract. Since that time, each major advance in understanding has followed more or less directly from the development of a new technique of investigation. Until the early years of the 20th century, the most important advances were derived from new methods for [[staining]] cells.<ref>{{cite book |last=Bloom |first=FE |veditors=Schmidt FO, Worden FG, Swazey JP, Adelman G |title=The Neurosciences, Paths of Discovery |publisher=MIT Press |year=1975 |isbn=978-0-262-23072-8 |page=[https://archive.org/details/TheNeurosc_00_Word/page/211 211] |url=https://archive.org/details/TheNeurosc_00_Word/page/211 }}</ref> Particularly critical was the invention of the [[Golgi's method|Golgi stain]], which (when correctly used) stains only a small fraction of neurons, but stains them in their entirety, including cell body, dendrites, and axon. Without such a stain, brain tissue under a microscope appears as an impenetrable tangle of protoplasmic fibers, in which it is impossible to determine any structure. In the hands of [[Camillo Golgi]], and especially of the Spanish neuroanatomist [[Santiago Ramón y Cajal]], the new stain revealed hundreds of distinct types of neurons, each with its own unique dendritic structure and pattern of connectivity.<ref>{{cite book |title=Foundations of the Neuron Doctrine |last=Shepherd |first=GM |year=1991 |publisher=Oxford University Press |isbn=978-0-19-506491-9 |chapter=Ch.1 : Introduction and Overview}}</ref>

[[File:PurkinjeCell.jpg|thumb|right|alt=A drawing on yellowing paper with an archiving stamp in the corner. A spidery tree branch structure connects to the top of a mass. A few narrow processes follow away from the bottom of the mass.|Drawing by [[Santiago Ramón y Cajal]] of two types of Golgi-stained neurons from the cerebellum of a pigeon]]

In the first half of the 20th century, advances in electronics enabled investigation of the electrical properties of nerve cells, culminating in work by [[Alan Lloyd Hodgkin|Alan Hodgkin]], [[Andrew Huxley]], and others on the biophysics of the action potential, and the work of [[Bernard Katz]] and others on the electrochemistry of the synapse.<ref>{{cite journal |last=Piccolino |first=M |year=2002 |title=Fifty years of the Hodgkin-Huxley era |journal=Trends in Neurosciences |volume=25 |pages=552–553 |pmid=12392928 |doi=10.1016/S0166-2236(02)02276-2 |issue=11|s2cid=35465936 }}</ref> These studies complemented the anatomical picture with a conception of the brain as a dynamic entity. Reflecting the new understanding, in 1942 [[Charles Scott Sherrington|Charles Sherrington]] visualized the workings of the brain waking from sleep:

{{blockquote|The great topmost sheet of the mass, that where hardly a light had twinkled or moved, becomes now a sparkling field of rhythmic flashing points with trains of traveling sparks hurrying hither and thither. The brain is waking and with it the mind is returning. It is as if the Milky Way entered upon some cosmic dance. Swiftly the head mass becomes an enchanted loom where millions of flashing shuttles weave a dissolving pattern, always a meaningful pattern though never an abiding one; a shifting harmony of subpatterns.|Sherrington, 1942, ''Man on his Nature''<ref>{{cite book |last=Sherrington |first=CS |title=Man on his nature |date=2000 |orig-date=1942 |publisher=Cambridge University Press |page=[https://archive.org/details/isbn_9780838577011/page/178 178] |isbn=978-0-8385-7701-1 |url=https://archive.org/details/isbn_9780838577011/page/178 }}</ref>}}

The invention of electronic computers in the 1940s, along with the development of mathematical [[information theory]], led to a realization that brains can potentially be understood as information processing systems. This concept formed the basis of the field of [[cybernetics]], and eventually gave rise to the field now known as [[computational neuroscience]].<ref name=CKS1993>{{cite book |chapter=What is computational neuroscience? |last1=Churchland |first1=PS |last2=Koch |first2=C |last3=Sejnowski |first3=TJ |title=Computational Neuroscience |pages=46–55 |editor=Schwartz EL |year=1993 |publisher=MIT Press |isbn=978-0-262-69164-2}}</ref> The earliest attempts at cybernetics were somewhat crude in that they treated the brain as essentially a digital computer in disguise, as for example in [[John von Neumann]]'s 1958 book, ''[[The Computer and the Brain]]''.<ref>{{cite book |title=The Computer and the Brain |year=2000 |publisher=Yale University Press |isbn=978-0-300-08473-3 |last1=von Neumann |first1=J |last2=Churchland |first2=PM |last3=Churchland |first3=PS |pages=xi–xxii |url=https://archive.org/details/computerbrain0000vonn }}</ref> Over the years, though, accumulating information about the electrical responses of brain cells recorded from behaving animals has steadily moved theoretical concepts in the direction of increasing realism.<ref name=CKS1993/>

One of the most influential early contributions was a 1959 paper titled ''What the frog's eye tells the frog's brain'': the paper examined the visual responses of neurons in the [[retina]] and [[superior colliculus|optic tectum]] of frogs, and came to the conclusion that some neurons in the tectum of the frog are wired to combine elementary responses in a way that makes them function as "bug perceivers".<ref>{{cite journal |title=What the frog's eye tells the frog's brain |journal=Proceedings of the Institute of Radio Engineers |volume=47 |issue=11 |pages=1940–1951 |year=1959 |url=http://jerome.lettvin.info/lettvin/Jerome/WhatTheFrogsEyeTellsTheFrogsBrain.pdf |last1=Lettvin |first1=JY |last2=Maturana |first2=HR |last3=McCulloch |first3=WS |last4=Pitts |first4=WH |doi=10.1109/jrproc.1959.287207 |s2cid=8739509 |url-status=dead |archive-url=https://web.archive.org/web/20110928024235/http://jerome.lettvin.info/lettvin/Jerome/WhatTheFrogsEyeTellsTheFrogsBrain.pdf |archive-date=2011-09-28 }}</ref> A few years later [[David H. Hubel|David Hubel]] and [[Torsten Wiesel]] discovered cells in the primary visual cortex of monkeys that become active when sharp edges move across specific points in the field of view—a discovery for which they won a Nobel Prize.<ref>{{cite book |title=Brain and visual perception: the story of a 25-year collaboration |url=https://archive.org/details/brainvisualperce00hube |url-access=limited |last1=Hubel |first1=DH |last2=Wiesel |first2=TN |publisher=Oxford University Press US |year=2005 |isbn=978-0-19-517618-6 |pages=[https://archive.org/details/brainvisualperce00hube/page/n665 657]–704}}</ref> Follow-up studies in higher-order visual areas found cells that detect [[binocular disparity]], color, movement, and aspects of shape, with areas located at increasing distances from the primary visual cortex showing increasingly complex responses.<ref>{{cite book |title=The Cognitive Neuroscience of Vision |last=Farah |first=MJ |year=2000 |publisher=Wiley-Blackwell |isbn=978-0-631-21403-8 |pages=1–29}}</ref> Other investigations of brain areas unrelated to vision have revealed cells with a wide variety of response correlates, some related to memory, some to abstract types of cognition such as space.<ref>{{cite journal |last1=Engel |first1=AK |last2=Singer |first2=W |title=Temporal binding and the neural correlates of sensory awareness |journal=Trends in Cognitive Sciences |year=2001 |volume=5 |pages=16–25 |pmid=11164732 |doi=10.1016/S1364-6613(00)01568-0 |issue=1|s2cid=11922975 }}</ref>

Theorists have worked to understand these response patterns by constructing mathematical [[Nervous system network models|models of neurons and neural networks]], which can be simulated using computers.<ref name=CKS1993/> Some useful models are abstract, focusing on the conceptual structure of neural algorithms rather than the details of how they are implemented in the brain; other models attempt to incorporate data about the biophysical properties of real neurons.<ref>{{cite book |last1=Dayan |first1=P |last2=Abbott |first2=LF |title=Theoretical Neuroscience |chapter=Ch.7: Network models |year=2005 |publisher=MIT Press |isbn=978-0-262-54185-5}}</ref> No model on any level is yet considered to be a fully valid description of brain function, though. The essential difficulty is that sophisticated computation by neural networks requires distributed processing in which hundreds or thousands of neurons work cooperatively—current methods of brain activity recording are only capable of isolating action potentials from a few dozen neurons at a time.<ref>{{cite journal |last1=Averbeck |first1=BB |last2=Lee |first2=D |title=Coding and transmission of information by neural ensembles |journal=Trends in Neurosciences |year=2004 |volume=27 |pages=225–230 |pmid=15046882 |doi=10.1016/j.tins.2004.02.006 |issue=4|s2cid=44512482 }}</ref>

Furthermore, even single neurons appear to be complex and capable of performing computations.<ref>{{cite journal |author=Forrest, MD |title=Intracellular Calcium Dynamics Permit a Purkinje Neuron Model to Perform Toggle and Gain Computations Upon its Inputs. |journal=Frontiers in Computational Neuroscience |volume=8 |pages=86 |year=2014 |doi=10.3389/fncom.2014.00086 |pmid=25191262 |pmc=4138505|doi-access=free }}</ref> So, brain models that do not reflect this are too abstract to be representative of brain operation; models that do try to capture this are very computationally expensive and arguably intractable with present computational resources. However, the [[Human Brain Project]] is trying to build a realistic, detailed computational model of the entire human brain. The wisdom of this approach has been publicly contested, with high-profile scientists on both sides of the argument.

In the second half of the 20th century, developments in chemistry, electron microscopy, genetics, computer science, functional brain imaging, and other fields progressively opened new windows into brain structure and function. In the United States, the 1990s were officially designated as the "[[Decade of the Brain]]" to commemorate advances made in brain research, and to promote funding for such research.<ref>{{Cite journal |last1=Jones |first1=EG |last2=Mendell |first2=LM |year=1999 |title=Assessing the Decade of the Brain |journal=Science |volume=284 |issue=5415 |page=739 |bibcode=1999Sci...284..739J |doi=10.1126/science.284.5415.739|pmid=10336393|s2cid=13261978}}</ref>

In the 21st century, these trends have continued, and several new approaches have come into prominence, including [[multielectrode array|multielectrode recording]], which allows the activity of many brain cells to be recorded all at the same time;<ref>{{cite journal |last=Buzsáki |first=G |title=Large-scale recording of neuronal ensembles |journal=Nature Neuroscience |volume=7 |year=2004 |pages=446–451 |pmid=15114356 |url=http://osiris.rutgers.edu/BuzsakiHP/Publications/PDFs/Buzsaki2004NatNeurosci.pdf |archive-url=https://web.archive.org/web/20060910225619/http://osiris.rutgers.edu/BuzsakiHP/Publications/PDFs/Buzsaki2004NatNeurosci.pdf |url-status=dead |archive-date=2006-09-10 |doi=10.1038/nn1233 |issue=5|s2cid=18538341 }}</ref> [[genetic engineering]], which allows molecular components of the brain to be altered experimentally;<ref name=Tonegawa>{{cite journal |title=Genetic neuroscience of mammalian learning and memory |journal=[[Philosophical Transactions of the Royal Society B]] |year=2003 |volume=358 |pages=787–795 |pmid=12740125 |pmc=1693163 |last1=Tonegawa |first1=S |last2=Nakazawa |first2=K |last3=Wilson |first3=MA |doi=10.1098/rstb.2002.1243 |issue=1432}}</ref> [[genomics]], which allows variations in brain structure to be correlated with variations in [[DNA]] properties and [[neuroimaging]].<ref>{{cite journal |last1=Geschwind |first1=DH |last2=Konopka |first2=G |title=Neuroscience in the era of functional genomics and systems biology |journal=Nature |year=2009 |volume=461 |pages=908–915 |pmid=19829370 |doi=10.1038/nature08537 |issue=7266 |pmc=3645852 |bibcode=2009Natur.461..908G}}</ref>