Editing Behavioral neuroscience (section)

== Research methods ==

The distinguishing characteristic of a behavioral neuroscience experiment is that either the [[independent variable]] of the experiment is biological, or some [[dependent variable]] is biological. In other words, the [[nervous system]] of the organism under study is permanently or temporarily altered, or some aspect of the nervous system is measured (usually to be related to a behavioral variable).

===Disabling or decreasing neural function===

* [[Lesions]] – A classic method in which a brain-region of interest is naturally or intentionally destroyed to observe any resulting changes such as degraded or enhanced performance on some behavioral measure. Lesions can be placed with relatively high accuracy "Thanks to a variety of brain 'atlases' which provide a map of brain regions in 3-dimensional" [[stereotactic surgery|stereotactic coordinates]].[[File:Journal.pone.0057573.g005 cropped.png|thumb|301x301px|The part of the picture emphasized shows the [[lesion]] in the brain. This type of lesion can be removed through surgery.]]
**'''Surgical''' lesions – Neural tissue is destroyed by removing it surgically.
** '''Electrolytic''' lesions – Neural tissue is destroyed through the application of electrical shock trauma.
** '''Chemical''' lesions – Neural tissue is destroyed by the infusion of a [[neurotoxin]].
** '''Temporary''' lesions – Neural tissue is temporarily disabled by cooling or by the use of [[anesthetics]] such as [[tetrodotoxin]].
* [[Transcranial magnetic stimulation]] – A new technique usually used with human subjects in which a magnetic coil applied to the scalp causes unsystematic electrical activity in nearby cortical neurons which can be experimentally analyzed as a functional lesion.
* [[Receptor activated solely by a synthetic ligand|Synthetic ligand injection]] – A receptor activated solely by a synthetic ligand (RASSL) or Designer Receptor Exclusively Activated by Designer Drugs (DREADD), permits spatial and temporal control of [[G protein]] signaling [[in vivo]]. These systems utilize G protein-coupled receptors ([[GPCR]]) engineered to respond exclusively to synthetic small molecules [[ligands]], like [[clozapine N-oxide]] (CNO), and not to their natural ligand(s). RASSL's represent a GPCR-based [[chemogenetic]] tool. These synthetic ligands upon activation can decrease neural function by G-protein activation. This can with Potassium attenuating neural activity.<ref>{{cite journal|last1=Zhu|first1=Hu|title=Silencing synapses with DREADDs|journal=Neuron|volume=82|issue=4|pages=723–725|pmc=4109642|year=2014|doi=10.1016/j.neuron.2014.05.002|pmid=24853931}}</ref>
* [[Optogenetic]] inhibition – A light activated inhibitory protein is expressed in cells of interest. Powerful millisecond timescale neuronal inhibition is instigated upon stimulation by the appropriate frequency of light delivered via fiber optics or implanted LEDs in the case of vertebrates,<ref>{{Cite journal |doi = 10.1176/appi.ajp.2008.08030444|title = Controlling Neuronal Activity|year = 2008|last1 = Schneider|first1 = M. Bret|last2 = Gradinaru|first2 = Viviana|last3 = Zhang|first3 = Feng|last4 = Deisseroth|first4 = Karl|journal = American Journal of Psychiatry|volume = 165|issue = 5|pages = 562|pmid = 18450936}}</ref> or via external illumination for small, sufficiently translucent invertebrates.<ref>{{Cite journal | doi=10.1038/nature05744| title=Multimodal fast optical interrogation of neural circuitry| year=2007| last1=Zhang| first1=Feng| last2=Wang| first2=Li-Ping| last3=Brauner| first3=Martin| last4=Liewald| first4=Jana F.| last5=Kay| first5=Kenneth| last6=Watzke| first6=Natalie| last7=Wood| first7=Phillip G.| last8=Bamberg| first8=Ernst| last9=Nagel| first9=Georg| last10=Gottschalk| first10=Alexander| last11=Deisseroth| first11=Karl| journal=Nature| volume=446| issue=7136| pages=633–639| pmid=17410168| bibcode=2007Natur.446..633Z| s2cid=4415339}}</ref> Bacterial [[Halorhodopsins]] or [[Proton pumps]] are the two classes of proteins used for inhibitory optogenetics, achieving inhibition by increasing cytoplasmic levels of halides ({{chem|Cl|-}}) or decreasing the cytoplasmic concentration of protons, respectively.<ref>Chow, B. Y. et al. "High-performance genetically targetable optical
neural silencing by light-driven proton pumps." Nature. Vol 463. 7 January 2010</ref><ref>{{Cite journal | doi=10.1007/s11068-008-9027-6| title=ENpHR: A Natronomonas halorhodopsin enhanced for optogenetic applications| year=2008| last1=Gradinaru| first1=Viviana| last2=Thompson| first2=Kimberly R.| last3=Deisseroth| first3=Karl| journal=Brain Cell Biology| volume=36| issue=1–4| pages=129–139| pmid=18677566| pmc=2588488}}</ref>

=== Enhancing neural function ===

* Electrical stimulation – A classic method in which neural activity is enhanced by application of a small electric current (too small to cause significant cell death).
* '''Psychopharmacological''' manipulations – A chemical [[receptor antagonist]] induces neural activity by interfering with [[neurotransmission]]. Antagonists can be delivered systemically (such as by intravenous injection) or locally (intracerebrally) during a surgical procedure into the ventricles or into specific brain structures. For example, [[NMDA]] [[antagonist]] [[AP5]] has been shown to inhibit the initiation of [[long term potentiation]] of excitatory synaptic transmission (in rodent fear conditioning) which is believed to be a vital mechanism in learning and memory.<ref>{{Cite journal |last1=Kim |first1=Jeansok J. |last2=Decola |first2=Joseph P. |last3=Landeira-Fernandez |first3=Jesus |last4=Fanselow |first4=Michael S. |year=1991 |title=N-methyl-D-aspartate receptor antagonist APV blocks acquisition but not expression of fear conditioning |journal=Behavioral Neuroscience |volume=105 |issue=1 |pages=126–133 |doi=10.1037/0735-7044.105.1.126 |pmid=1673846}}</ref>
* Synthetic Ligand Injection – Likewise, G<sub>q</sub>-DREADDs can be used to modulate cellular function by innervation of brain regions such as Hippocampus. This innervation results in the amplification of γ-rhythms, which increases motor activity.<ref>{{cite journal|last1=Ferguson|first1=Susan|title=Grateful DREADDs: Engineered Receptors Reveal How Neural Circuits Regulate Behavior|journal= Neuropsychopharmacology|date=2012|volume=37|issue=1|pages=296–297|doi=10.1038/npp.2011.179|pmid=22157861|pmc=3238068}}</ref>
* [[Transcranial magnetic stimulation]] – In some cases (for example, studies of [[motor cortex]]), this technique can be analyzed as having a stimulatory effect (rather than as a functional lesion).
* [[Optogenetic]] excitation – A light activated excitatory protein is expressed in select cells. [[Channelrhodopsin]]-2 (ChR2), a light activated cation channel, was the first bacterial opsin shown to excite neurons in response to light,<ref>{{Cite journal |doi = 10.1038/nmeth936|title = Channelrhodopsin-2 and optical control of excitable cells|year = 2006|last1 = Zhang|first1 = Feng|last2 = Wang|first2 = Li-Ping|last3 = Boyden|first3 = Edward S.|last4 = Deisseroth|first4 = Karl|journal = Nature Methods|volume = 3|issue = 10|pages = 785–792|pmid = 16990810|s2cid = 15096826}}</ref> though a number of new excitatory optogenetic tools have now been generated by improving and imparting novel properties to ChR2.<ref>{{Cite journal |doi = 10.1016/j.cell.2010.02.037|title = Molecular and Cellular Approaches for Diversifying and Extending Optogenetics|year = 2010|last1 = Gradinaru|first1 = Viviana|last2 = Zhang|first2 = Feng|last3 = Ramakrishnan|first3 = Charu|last4 = Mattis|first4 = Joanna|last5 = Prakash|first5 = Rohit|last6 = Diester|first6 = Ilka|last7 = Goshen|first7 = Inbal|last8 = Thompson|first8 = Kimberly R.|last9 = Deisseroth|first9 = Karl|journal = Cell|volume = 141|issue = 1|pages = 154–165|pmid = 20303157|pmc = 4160532}}</ref>

=== Measuring neural activity ===
* Optical techniques – Optical methods for recording neuronal activity rely on methods that modify the optical properties of neurons in response to the cellular events associated with action potentials or neurotransmitter release.
**[[Voltage sensitive dyes]] (VSDs) were among the earliest method for optically detecting neuronal activity. VSDs commonly changed their fluorescent properties in response to a voltage change across the neuron's membrane, rendering membrane sub-threshold and supra-threshold (action potentials) electrical activity detectable.<ref>{{Cite journal | doi=10.1016/0301-0082(95)00010-S| title=Use of voltage-sensitive dyes and optical recordings in the central nervous system| year=1995| last1=Ebner| first1=Timothy J.| last2=Chen| first2=Gang| journal=Progress in Neurobiology| volume=46| issue=5| pages=463–506| pmid=8532849| s2cid=17187595}}</ref> Genetically encoded voltage sensitive fluorescent proteins have also been developed.<ref>{{Cite journal | doi=10.1016/s0896-6273(00)80955-1| title=A Genetically Encoded Optical Probe of Membrane Voltage| year=1997| last1=Siegel| first1=Micah S.| last2=Isacoff| first2=Ehud Y.| journal=Neuron| volume=19| issue=4| pages=735–741| pmid=9354320| s2cid=11447982| doi-access=free}}</ref>
** [[Calcium imaging]] relies on dyes<ref>{{Cite journal | doi=10.1016/0165-0270(93)90145-H| title=Real-time imaging of neurons retrogradely and anterogradely labelled with calcium-sensitive dyes| year=1993| last1=O'Donovan| first1=Michael J.| last2=Ho| first2=Stephen| last3=Sholomenko| first3=Gerald| last4=Yee| first4=Wayne| journal=Journal of Neuroscience Methods| volume=46| issue=2| pages=91–106| pmid=8474261| s2cid=13373078}}</ref> or genetically encoded proteins<ref>{{Cite journal | doi=10.1074/jbc.M312751200| title=Genetically Encoded Indicators of Cellular Calcium Dynamics Based on Troponin C and Green Fluorescent Protein| year=2004| last1=Heim| first1=Nicola| last2=Griesbeck| first2=Oliver| journal=Journal of Biological Chemistry| volume=279| issue=14| pages=14280–14286| pmid=14742421| doi-access=free}}</ref> that fluoresce upon binding to the calcium that is transiently present during an action potential.
** [[Synapto-pHluorin]] is a technique that relies on a [[fusion protein]] that combines a synaptic vesicle membrane protein and a pH sensitive fluorescent protein. Upon synaptic vesicle release, the chimeric protein is exposed to the higher pH of the synaptic cleft, causing a measurable change in fluorescence.<ref>{{Cite journal | doi=10.1038/28190| title=Visualizing secretion and synaptic transmission with pH-sensitive green fluorescent proteins| year=1998| last1=Miesenböck| first1=Gero| last2=De Angelis| first2=Dino A.| last3=Rothman| first3=James E.| journal=Nature| volume=394| issue=6689| pages=192–195| pmid=9671304| bibcode=1998Natur.394..192M| s2cid=4320849}}</ref>
* [[Single-unit recording]] – A method whereby an electrode is introduced into the brain of a living animal to detect electrical activity that is generated by the neurons adjacent to the electrode tip. Normally this is performed with sedated animals but sometimes it is performed on awake animals engaged in a behavioral event, such as a thirsty rat whisking a particular sandpaper grade previously paired with water in order to measure the corresponding patterns of neuronal firing at the decision point.<ref>{{Cite journal |doi = 10.1371/journal.pbio.0050305|title = Neuronal Activity in Rat Barrel Cortex Underlying Texture Discrimination|year = 2007|last1 = von Heimendahl|first1 = Moritz|last2 = Itskov|first2 = Pavel M.|last3 = Arabzadeh|first3 = Ehsan|last4 = Diamond|first4 = Mathew E.|journal = PLOS Biology|volume = 5|issue = 11|pages = e305|pmid = 18001152|pmc = 2071938 | doi-access=free }}</ref>
* Multielectrode recording – The use of a bundle of fine electrodes to record the simultaneous activity of up to hundreds of neurons.
* [[Functional magnetic resonance imaging]] – fMRI, a technique most frequently applied on human subjects, in which changes in cerebral blood flow can be detected in an [[MRI]] apparatus and are taken to indicate relative activity of larger scale brain regions (i.e., on the order of hundreds of thousands of neurons).
*[[File:PET - Human Addiction.jpg|thumb|PET brain scans can show chemical differences in the brain between addicts and non-addicts. The normal images in the bottom row come from non-addicts while people with addictions have scans that look more abnormal.]][[Positron emission tomography]] - PET detects particles called photons using a 3-D nuclear medicine examination. These particles are emitted by injections of radioisotopes such as fluorine. PET imaging reveal the pathological processes which predict anatomic changes making it important for detecting, diagnosing and characterising many pathologies.<ref>{{Cite journal |pmid = 25835405|year = 2015|last1 = Ocampo|first1 = T.|last2 = Knight|first2 = K.|last3 = Dunleavy|first3 = R.|last4 = Shah|first4 = S. N.|title = Techniques, benefits, and challenges of PET-MR|journal = Radiologic Technology|volume = 86|issue = 4|pages = 393–412; quiz 413–6}}</ref>
* [[Electroencephalography]] – EEG, and the derivative technique of [[event-related potential]]s, in which scalp electrodes monitor the average activity of neurons in the cortex (again, used most frequently with human subjects). This technique uses different types of electrodes for recording systems such as needle electrodes and saline-based electrodes. EEG allows for the investigation of mental disorders, sleep disorders and physiology. It can monitor brain development and cognitive engagement.<ref>Sanei, S., & Chambers, J. A. (2013). EEG signal processing. John Wiley & Sons.</ref>
* Functional neuroanatomy – A more complex counterpart of [[phrenology]]. The expression of some anatomical marker is taken to reflect neural activity. For example, the expression of [[immediate early genes]] is thought to be caused by vigorous neural activity. Likewise, the injection of [[2-deoxyglucose]] prior to some behavioral task can be followed by anatomical localization of that chemical; it is taken up by neurons that are electrically active.
* [[Magnetoencephalography]] – MEG shows the functioning of the human brain through the measurement of electromagnetic activity. Measuring the magnetic fields created by the electric current flowing within the neurons identifies brain activity associated with various human functions in real time, with millimeter spatial accuracy. Clinicians can noninvasively obtain data to help them assess neurological disorders and plan surgical treatments.

=== Genetic techniques ===

* [[Quantitative trait loci|QTL mapping]] – The influence of a gene in some behavior can be statistically inferred by studying [[inbred strains]] of some species, most commonly mice. The recent sequencing of the [[genome]] of many species, most notably mice, has facilitated this technique.
* [[Selective breeding]] – Organisms, often mice, may be bred selectively among inbred strains to create a [[recombinant congenic strain]]. This might be done to isolate an experimentally interesting stretch of [[DNA]] derived from one strain on the background genome of another strain to allow stronger inferences about the role of that stretch of DNA.
* [[Genetic engineering]] – The genome may also be experimentally-manipulated; for example, [[knockout mice]] can be engineered to lack a particular gene, or a gene may be expressed in a strain which does not normally do so (the 'transgenic'). Advanced techniques may also permit the expression or suppression of a gene to occur by injection of some regulating chemical.

=== Quantifying behavior ===

* [[File:Drosophila anipose tracking.png|thumb|Fruit fly ([[Drosophila melanogaster]]) leg joints being tracked in 3D with Anipose.<ref>{{Cite journal |last1=Karashchuk |first1=Pierre |last2=Rupp |first2=Katie L. |last3=Dickinson |first3=Evyn S. |last4=Walling-Bell |first4=Sarah |last5=Sanders |first5=Elischa |last6=Azim |first6=Eiman |last7=Brunton |first7=Bingni W. |last8=Tuthill |first8=John C. |date=2021-09-28 |title=Anipose: A toolkit for robust markerless 3D pose estimation |journal=Cell Reports |language=en |volume=36 |issue=13 |page=109730 |doi=10.1016/j.celrep.2021.109730 |issn=2211-1247 |pmc=8498918 |pmid=34592148}}</ref>]][[Pose (computer vision)|Markerless pose estimation]] – The advancement of [[computer vision]] techniques in recent years have allowed for precise quantifications of animal movements without needing to fit physical markers onto the subject. On high-speed video captured in a behavioral assay, keypoints from the subject can be extracted frame-by-frame,<ref>{{Cite journal |last1=Mathis |first1=Alexander |last2=Mamidanna |first2=Pranav |last3=Cury |first3=Kevin M. |last4=Abe |first4=Taiga |last5=Murthy |first5=Venkatesh N. |last6=Mathis |first6=Mackenzie Weygandt |last7=Bethge |first7=Matthias |date=September 2018 |title=DeepLabCut: markerless pose estimation of user-defined body parts with deep learning |url=https://www.nature.com/articles/s41593-018-0209-y |journal=Nature Neuroscience |language=en |volume=21 |issue=9 |pages=1281–1289 |doi=10.1038/s41593-018-0209-y |pmid=30127430 |s2cid=52807326 |issn=1546-1726|url-access=subscription }}</ref> which is often useful to analyze in tandem with neural recordings/manipulations. Analyses can be conducted on how keypoints (i.e. parts of the animal) move within different phases of a particular behavior (on a short timescale),<ref>{{Cite web|last1=Syeda |first1=Atika |last2=Zhong |first2=Lin |last3=Tung |first3=Renee |last4=Long |first4=Will |last5=Pachitariu |first5=Marius |last6=Stringer |first6=Carsen |date=2022-11-04 |title=Facemap: a framework for modeling neural activity based on orofacial tracking |url=https://www.biorxiv.org/content/10.1101/2022.11.03.515121v1 |language=en |pages=2022.11.03.515121 |doi=10.1101/2022.11.03.515121|s2cid=253371320 }}</ref> or throughout an animal's behavioral repertoire (longer timescale).<ref>{{Cite journal |last1=Marshall |first1=Jesse D. |last2=Aldarondo |first2=Diego E. |last3=Dunn |first3=Timothy W. |last4=Wang |first4=William L. |last5=Berman |first5=Gordon J. |last6=Ölveczky |first6=Bence P. |date=2021-02-03 |title=Continuous Whole-Body 3D Kinematic Recordings across the Rodent Behavioral Repertoire |journal=Neuron |language=en |volume=109 |issue=3 |pages=420–437.e8 |doi=10.1016/j.neuron.2020.11.016 |issn=0896-6273 |pmc=7864892 |pmid=33340448}}</ref> These keypoint changes can be compared with corresponding changes in neural activity. A machine learning approach can also be used to identify specific behaviors (e.g. forward walking, turning, grooming, courtship, etc.), and quantify the dynamics of transitions between behaviors.<ref>{{Cite journal |last1=Berman |first1=Gordon J. |last2=Choi |first2=Daniel M. |last3=Bialek |first3=William |last4=Shaevitz |first4=Joshua W. |date=2014-10-06 |title=Mapping the stereotyped behaviour of freely moving fruit flies |journal=Journal of the Royal Society Interface |language=en |volume=11 |issue=99 |pages=20140672 |doi=10.1098/rsif.2014.0672 |issn=1742-5689 |pmc=4233753 |pmid=25142523}}</ref><ref>{{Cite journal |last1=Tillmann |first1=Jens F. |last2=Hsu |first2=Alexander I. |last3=Schwarz |first3=Martin K. |last4=Yttri |first4=Eric A. |date=April 2024 |title=A-SOiD, an active-learning platform for expert-guided, data-efficient discovery of behavior |url=https://www.nature.com/articles/s41592-024-02200-1 |journal=Nature Methods |language=en |volume=21 |issue=4 |pages=703–711 |doi=10.1038/s41592-024-02200-1 |pmid=38383746 |issn=1548-7105}}</ref><ref>{{Cite journal |last1=Goodwin |first1=Nastacia L. |last2=Choong |first2=Jia J. |last3=Hwang |first3=Sophia |last4=Pitts |first4=Kayla |last5=Bloom |first5=Liana |last6=Islam |first6=Aasiya |last7=Zhang |first7=Yizhe Y. |last8=Szelenyi |first8=Eric R. |last9=Tong |first9=Xiaoyu |last10=Newman |first10=Emily L. |last11=Miczek |first11=Klaus |last12=Wright |first12=Hayden R. |last13=McLaughlin |first13=Ryan J. |last14=Norville |first14=Zane C. |last15=Eshel |first15=Neir |date=2024-05-22 |title=Simple Behavioral Analysis (SimBA) as a platform for explainable machine learning in behavioral neuroscience |url=https://www.nature.com/articles/s41593-024-01649-9 |journal=Nature Neuroscience |volume=27 |issue=7 |language=en |pages=1411–1424 |doi=10.1038/s41593-024-01649-9 |pmid=38778146 |pmc=11268425 |pmc-embargo-date=July 1, 2025 |issn=1546-1726}}</ref><ref>{{Citation |last1=Weinreb |first1=Caleb |title=Keypoint-MoSeq: parsing behavior by linking point tracking to pose dynamics |date=2023-03-17 |language=en |doi=10.1101/2023.03.16.532307 |pmc=10055085 |pmid=36993589 |last2=Pearl |first2=Jonah |last3=Lin |first3=Sherry |last4=Osman |first4=Mohammed Abdal Monium |last5=Zhang |first5=Libby |last6=Annapragada |first6=Sidharth |last7=Conlin |first7=Eli |last8=Hoffman |first8=Red |last9=Makowska |first9=Sofia|journal=BioRxiv: The Preprint Server for Biology }}</ref>