The Virus Zoo: A Quick Primer on Molecular Virology


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Genome and Structure:

The SARS-CoV-2 genome consists of about 30 kb of linear positive-sense ssRNA. There is a m7G-cap (specifically m7GpppA1) at the 5’ end of the genome and a 30-60 nucleotide poly-A tail at the 3’ end of the genome. These protective structures minimize exonuclease degradation.1 The genome also has a 5’ UTR and a 3’ UTR which contain sequences that aid in transcriptional regulation and in packaging. The SARS-CoV-2 genome directly translates two partially overlapping polyproteins, ORF1a and ORF1b. There is a –1 ribosomal frameshift in ORF1b relative to ORF1a. Within the polyproteins, two self-activating proteases (Papain-like protease PLpro and 3-chymotrypsin-like protease 3CLpro) perform cleavage events that lead to the generation of the virus’s 16 non-structural proteins (nsps). It should be noted that the 3CLpro is also known as the main protease or Mpro. The coronavirus also produces 4 structural proteins, but these are not translated until after the synthesis of corresponding subgenomic RNAs via the viral replication complex. To create these subgenomic RNAs, negative-sense RNA must first be made and then undergo conversion back to positive-sense RNA for translation. Genes encoding the structural proteins are located downstream of the ORF1b section.

SARS-CoV-2’s four structural proteins include the N, E, M, and S proteins. Many copies of the N (nucleocapsid) protein bind the RNA genome and organize it into a helical ribonucelocapsid complex. The complex undergoes packaging into the viral envelope during coronavirus budding. Interactions between the N protein and the other structural proteins may facilitate this packaging process. The N protein also inhibits host immune responses by antagonizing viral suppressor RNAi and by blocking the signaling of interferon production pathways.2

The transmembrane E (envelope) protein forms pentamers and plays a key but poorly understood role in the budding of viral envelopes into the endoplasmic reticulum Golgi intermediate compartment (ERGIC).3–5 Despite its importance in budding, mature viral particles do not incorporate very many E proteins into their envelopes. One of the posttranslational modifications of the E protein is palmitoylation. This aids subcellular trafficking and interactions with membranes. E protein pentamers also act as ion channels that alter membrane potential.6,7 This may lead to inflammasome activation, a contributing factor to cytokine storm induction.

The M (membrane) protein is the most abundant protein in the virion and drives global curvature in the ERGIC membrane to facilitate budding.5,8 It forms transmembrane dimers that likely oligomerize to induce this curvature.9 The M protein also has a cytosolic (and later intravirion) globular domain that likely interacts with the other structural proteins. M protein dimers also induce local curvature through preferential interactions with phosphatidylserine and phosphatidylinositol lipids.4,5 M proteins help sequester S proteins into the envelopes of budding viruses.10

The S (spike) protein of SARS-CoV-2 has been heavily studied due to its central roles in the infectivity and immunogenicity of the coronavirus. It forms a homotrimer that protrudes from the viral envelope and is heavily glycosylated. It binds the host’s ACE2 receptor (angiotensin-converting enzyme 2 receptor) and undergoes conformational changes to promote viral fusion.11 The S protein undergoes cleavage into S1 and S2 subunits by the host’s furin protease during viral maturation.12,13 This enhances SARS-CoV-2 entry into lung cells and may partially explain the virus’s high degree of transmissibility. The S1 fragment contains the receptor binding domain (RBD) and associated machinery while the S2 fragment facilitates fusion. Prior to cellular infection, most S proteins exist in a closed prefusion conformation where the RBDs of each monomer are hidden most of the time.14 After the S protein binds ACE2 during transient exposure of one of its RBDs, the other two RBDs quickly bind as well. This binding triggers a conformational change in the S protein that loosens the structure, unleashing the S2 fusion component and exposing another proteolytic cleavage site called S2’. Host transmembrane proteases such as TMPRSS2 cut at S2’, causing the full activation of the S2 fusion subunit and the dramatic elongation of the S protein into the postfusion conformation. This results in the viral envelope fusing with the host membrane and uptake of the coronavirus’s RNA into the cell.

The 16 nsps of SARS-CoV-2 play a variety of roles. For instance, nsp1 shuts down host cell translation by plugging the mRNA entry channel of the ribosome, inhibiting the host cell’s immune responses and maximizing viral production.15,16 Viral proteins still undergo translation because a conserved sequence in the coronavirus RNA helps circumvent the blockage through a poorly understood mechanism. The nsp5 protein is the protease 3CLpro.17 The nsp3 protein contains several subcomponents, including the protease PLpro. The nsp12, nsp7, and nsp8 proteins come together to form the RNA-dependent RNA polymerase (RdRp) that replicates the viral genome.17,18 The nsp2 protein is likely a topoisomerase which functions in RNA replication. The nsp4 and nsp6 proteins as well as certain subcomponents of nsp3 restructure intracellular host membranes into double-membrane vesicles (DMVs) which compartmentalize viral replication.19

Beyond the 4 structural proteins and 16 nsps of SARS-CoV-2, the coronaviral genome also encodes some poorly understood accessory proteins including ORF3a, ORF3b, ORF6, ORF7a, ORF7b, ORF8 and ORF9b.20 These accessory proteins are non-essential for replication in vitro, but they are thought to be required for the virus’s full degree of virulence in vivo.

Life cycle:

As mentioned, SARS-CoV-2 infects cells by first binding a S protein RBD to the ACE2 receptor. This triggers a conformational change that elongates the S protein’s structure and reveals the S2 fusion fragment, facilitating fusion of the virion envelope with the host cell membrane.14 Cleavage of the S’ site by proteases like TMPRSS2 aid this change from the prefusion to postfusion configurations. Alternatively, SARS-CoV-2 can enter the cell by binding to ACE2, undergoing endocytosis, and fusing with the endosome to release its genome (as induced by endosomal cathepsin proteases).20 After release of the SARS-CoV-2 genome into the cytosol, the N protein disassociates and allows translation of ORF1a and ORF1b, producing polyproteins which are cleaved into mature proteins by the PLpro and 3CLpro proteases as discussed earlier. 

The RdRp complex synthesizes negative-sense full genomic RNAs as well as negative-sense subgenomic RNAs. In the latter case, discontinuous transcription is employed, a process by which the RdRp jumps over certain sections of the RNA and initiates transcription separately from the rest of the genome.21 The negative-sense RNAs are subsequently converted back into positive-sense full genomic RNAs and positive-sense subgenomic RNAs. The subgenomic RNAs are translated to make structural proteins and some accessory proteins.20

As described earlier, the nsp4, nsp6, and parts of nsp3 proteins remodel host endoplasmic reticulum (ER) to create DMVs.20 These DMVs are the site of the coronaviral genomic replication and serve to shield the viral RNA and RdRp complex from cellular innate immune factors. DMVs cluster together and are continuous with the ER mostly through small tubular connections. After replication, the newly synthesized coronavirus RNAs undergo export into the cytosol through molecular pore complexes that span both membranes of the DMVs.22 These molecular pore complexes are composed of nsp3 domains and possibly other viral and/or host proteins.

Newly replicated SARS-CoV-2 genomic RNAs complex with N proteins to form helical nucleocapsids. To enable packaging, the nucleocapsids interact with M protein cytosolic domains which protrude at the ERGIC.23 M proteins, E proteins, and S proteins are all localized to the ERGIC membrane. The highly abundant M proteins induce curvature of the membrane to facilitate budding. As mentioned, E proteins also play essential roles in budding, but the mechanisms are poorly understood. Once the virions have budded into the ERGIC, they are shuttled through the Golgi via a series of vesicles and eventually secreted out of the cell.

Adeno-associated virus (AAV)

Genome and Structure:

AAV genomes are about 4.7 kb in length and are composed of ssDNA. Inverted terminal repeats (ITRs) form hairpin structures at ends of the genome. These ITR structures are important for AAV genomic packaging and replication. Rep genes (encoded via overlapping reading frames) include Rep78, Rep68, Rep52, Rep40.24 These proteins facilitate replication of the viral genome. As a Dependoparvovirus, additional helper functions from adenovirus (or certain other viruses) are needed for AAVs to replicate.

AAV capsids are about 25 nm in diameter. Cap genes include VP1, VP2, VP3 and are transcribed from overlapping reading frames.25 The VP3 protein is the smallest capsid protein. The VP2 protein is the same as VP3 except that it includes an N-terminal extension with a nuclear localization sequence. The VP1 protein is the same as VP2 except that it includes a further N-terminal extension encoding a phospholipase A2 (PLA2) that facilitates endosomal escape during infection. In the AAV capsid, VP1, VP2, and VP3 are present at a ratio of roughly 1:1:10. It should be noted that this ratio is actually the average of a distribution, not a fixed number.

Frame-shifted start codons in the Cap gene region transcribe AAP (assembly activating protein) and MAAP (membrane associated accessory protein). These proteins help facilitate packaging and other aspects of the AAV life cycle.

Life cycle:

There are a variety of different AAV serotypes (AAV2, AAV6, AAV9, etc.) that selectively infect certain tissue types. AAVs bind to host cell receptors and are internalized by endocytosis. The particular receptors involved can vary depending on the AAV serotype, though some receptors are consistent across many serotypes. Internalization occurs most often via clathrin-coated pits, but some AAVs are internalized by other routes such as macropinocytosis or the CLIC/GEEC tubulovesicular pathway.26

After endocytosis, conformational changes in the AAV capsid lead to exposure of the PLA2 VP1 domain, which facilitates endosomal escape. The AAV is then transported to the nucleus mainly by motor proteins on cytoskeletal highways. It enters via nuclear pores and finishes uncoating its genome.

AAV genomes initiate replication using the ends of their ITR hairpins as primers. This leads to a series of complex steps involving strand displacement and nicking.24 In the end, new copies of the AAV genome are synthesized. The Rep proteins are key players in this process. It is important to realize that AAVs can only replicate in cells which have also been infected by adenovirus or similar helper viruses (this is why they are called “adeno-associated viruses”). Adenoviruses provide helper genes encoding proteins (e.g. E4, E2a, VA) that are vital for the successful completion of the AAV life cycle. After new AAV capsids have assembled from VP1, VP2, and VP3 and once AAV genomes have been replicated, the ssDNA genomes are threaded into the capsids via pores at their five-fold vertices.

AAVs are nonpathogenic, though a large fraction of people possess antibodies against at least some serotypes, so exposure to them is fairly common.


Genome and Structure:

Adenovirus genomes are about 36 kb in size and are composed of linear dsDNA. They possess inverted terminal repeats (ITRs) which help facilitate replication and other functions. These genomes contain a variety of transcriptional units which are expressed at different times during the virus’s life cycle.27 E1A, E1B, E2A, E2B, E3, and E4 transcriptional units are expressed early during cellular infection. Their proteins are involved in DNA replication, transcriptional regulation, and suppression of host immune responses. The L1, L2, L3, L4, and L5 transcriptional units are expressed later in the life cycle. Their products include most of the capsid proteins as well as other proteins involved in packaging and assembly. Each transcriptional unit can produce multiple mRNAs through the host’s alternative splicing machinery.

The capsid of the adenovirus is about 90 nm in diameter and consists of three major proteins (hexon, penton, and fiber proteins) as well as a variety of minor proteins and core proteins. Hexon trimer is the most abundant protein in the capsid, the pentameric pentons occur at the vertices, and trimeric fibers are positioned on top of the pentons.28 The fibers point outwards from the capsid and end in knob domains which bind to cellular receptors. In Ad5, a commonly studied type of adenovirus, the fiber knob primarily binds to the coxsackievirus and adenovirus receptor (CAR). That said, it should be noted that Ad5’s fiber knob can also bind to alternative receptors such as vascular cell adhesion molecule 1 and heparan sulfate proteoglycans.

Minor capsid proteins include pIX, pIIIa, pVI, and pVIII. The pIX protein interlaces between hexons and helps stabilize the capsid. Though pIX is positioned in the crevices between the hexons, it is still exposed to the outside environment. By contrast, the pIIIa, pVI, and pVIII proteins bind to the inside of the capsid and contribute further structural stabilization. When the adenovirus is inside of the acidic endosome during infection, conformational changes in the capsid release the pVI protein, which facilitates endosomal escape through membrane lytic activity.

Adenovirus core proteins include pV, pVII, protein μ (also known as pX), adenovirus proteinase (AVP), pIVa2, and terminal protein (TP).29 The pVII protein has many positively-charged arginine residues and so functions to condense the viral DNA. The pV protein bridges the core with the capsid through interactions with pVII and with pVI. AVP cleaves various adenoviral proteins (pIIIa, TP, pVI, pVII, pVIII, pX) to convert them to their mature forms.30 The pIVa2 and pX proteins interact with the viral DNA and may play roles in packaging or replication. TP binds to the ends of the genome and is essential for localizing the viral DNA in the nucleus and for viral replication.

Life Cycle:

Adenovirus infects cells by binding its fiber knob to cellular receptors such as CAR (in the case of Ad5). The penton then binds certain αv integrins, positioning the viral capsid for endocytosis.31 When the endosome acidifies, the adenovirus capsid partially disassembles, fibers and pentons fall away, and pVI is released.32 The pVI protein’s membrane lytic activity facilitates endosomal escape. Partially disassembled capsids then undergo dynein-mediated transport along microtubules and dock at the entrance to nuclear pores. The capsids further disassemble and releases DNA through the nuclear pore. This DNA remains complexed with pVII after it enters the nucleus.

Adenoviral transcription is initiated by the E1A protein, inducing expression of early genes.33 This subsequently leads to expression of the E2, E3, and E4 transcriptional units, which help the virus escape immune responses. This cascade leads to expression of the L1, L2, L3, L4, and L5 transcriptional units, which mainly synthesize viral structural proteins and facilitate capsid assembly.

In the nucleus, adenovirus genomes replicate within dense complexes of protein that can be seen as spots via fluorescence microscopy. Replication begins at the ITRs and is primed by TP.34 Several more viral proteins and host proteins also aid the initiation of replication. Nontemplate strands are displaced during replication but may reanneal and act as template strands later. Adenovirus DNA binding protein and adenovirus DNA polymerase play important roles in replication. Once the genome has been replicated, TP undergoes cleavage into its mature form, signaling for packaging of new genomes.

The adenoviral capsid assembly and maturation process occurs in the nucleus.33 Once enough assembled adenoviruses have accumulated, they rupture the nuclear membrane using adenoviral death protein and subsequently lyse the cell, releasing adenoviral particles.

Herpes Simplex Virus 1 (HSV-1)

Genome and Structure:

HSV-1 genomes are about 150 kb in size and are composed of linear dsDNA. These genomes include a unique long (UL) region and a unique short (US) region.35 The UL and US regions are both flanked by their own inverted repeats. The terminal inverted repeats are called TRL and TRS while the internal inverted repeats are called IRL and IRS. HSV-1 contains approximately 80 genes, though the complexity of its genomic organization makes an exact number of genes difficult to obtain. As with many other viruses, HSV-1 genomes encode early, middle, and late genes. The early genes activate and regulate transcription of the middle and late genes. Middle genes facilitate genome replication and late genes mostly encode structural proteins.

The diameter of HSV-1 ranges around 155 nm to 240 nm.36 Its virions include an inner icosahedral capsid (with a 125 nm diameter) surrounded by tegument proteins which are in turn enveloped by a lipid membrane containing glycoproteins.

HSV-1’s icosahedral capsid consists of a variety of proteins. Some of the most important capsid proteins are encoded by the UL19, UL18, UL38, UL6, UL17, and UL25 genes.37 The UL19 gene encodes the major capsid protein VP5, which forms pentamers and hexamers for the capsid. These VP5 pentamers and hexamers are glued together by triplexes consisting of two copies of VP23 (encoded by UL18) and one copy of VP19C (encoded by UL38).38 The UL6 gene encodes the protein that makes up the portal complex, a structure used by HSV-1 to release its DNA during infection. Each HSV-1 capsid has a single portal (composed of 12 copies of the portal protein) located at one of the vertices. UL17 and UL25 encode additional structural proteins that stabilize the capsid by binding on top of the other vertices. These two proteins also serve as a bridge between the capsid core and the tegument proteins.

The tegument of HSV-1 contains dozens of distinct proteins. Some examples include pUL36, pUL37, pUL7, and pUL51 proteins. The major tegument proteins are pUL36 and pUL37. The pUL36 protein binds on top of the UL17-UL25 complexes at the capsid’s vertices.39 The pUL37 protein subsequently associates with pUL36. The pUL51 protein associates with cytoplasmic membranes in infected cells and recruits the pUL7 protein.40 This pUL51-pUL7 interaction is important for HSV-1 assembly. HSV-1 has many more tegument proteins which play various functional roles.

HSV-1’s envelope contains up to 16 unique glycoproteins. Four of these glycoproteins (gB, gD, gH, and gL) are essential for viral entry into cells.41 The gD glycoprotein first binds to one of its cellular receptors (nectin-1, herpesvirus entry mediator or HVEM, or 3-O-sulfated heparan sulfate). This binding event triggers a conformational change in gD that allows it to activate the gH/gL heterodimer. Next, gH/gL activate gB which induces fusion of HSV-1’s envelope with the cell membrane. Though the remaining 12 envelope glycoproteins are poorly understood, it is thought that they also play roles that influence cellular tropism and entry.

Life cycle:

After binding to cellular receptors via its glycoproteins, HSV-1 induces fusion of its envelope with the host cell membrane.42 The capsid is trafficked to nuclear pores via microtubules. Since the capsid is too large to pass through a nuclear pore directly, the virus instead ejects its DNA through the pore via the portal complex.43

HSV-1 replicates its genome and assembles its capsids in the nucleus. But the assembled capsids are again too large to exit the nucleus through nuclear pores. To overcome this issue, HSV-1 first buds via the inner nuclear membrane into the perinuclear cleft (the space between nuclear membranes), acquiring a primary envelope.42 This process is driven by a pair of proteins (pUL34 and pUL31) which together form the nuclear egress complex. Next, the primary envelope fuses with the outer nuclear membrane, releasing the assembled capsids into the cytosol.

To acquire its final envelope, the HSV-1 capsid likely buds into the trans-Golgi network or into certain tubular vesicular organelles.44 These membrane sources contain the envelope proteins of the virus as produced by transcription and various secretory pathways. One player is the pUL51 tegument protein that starts associated with the membrane into which the virus buds. The interaction between pUL51 and pUL7 helps facilitate recruitment of the capsid to the membrane. (Capsid envelopment is also coupled in many other ways to formation of the outer tegument). The enveloped virion eventually undergoes trafficking through the secretory system and eventually is packaged into exosomes that fuse with the cell membrane and release completed virions into the extracellular environment.

In humans, HSV-1 infects the epithelial cells first and produces viral particles.45 It subsequently enters the termini of sensory neurons, undergoes retrograde transport into the brain, and remains in the central nervous system in a dormant state. During periods of stress in the host, the virus is reactivated and undergoes anterograde transport to infect epithelial cells once again.


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Notes on x-ray physics

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PDF version: Notes on x-ray physics – Logan Thrasher Collins

Thomson scattering and Compton scattering

  • Electrons are the main type of particle that can scatter x-rays. Elastic or Thomson scattering occurs when a non-relativistic electron is accelerated by the electrical component of an incoming electromagnetic field from an x-ray. The accelerated electron then reradiates light at the same frequency. Since the frequency of the input light and output light are the same, this is an elastic process.
  • The intensity of the re-emitted radiation at an observer’s location depends on the angle Χ between the incident light and the observer. Because of the sinusoidal wave character of light, the scattered intensity at the observer’s location is given by the proportionality equation below.


  • Light that encounters the electron is scattered if it is incident on the region defined by the electron’s classical radius. This region is called the Thomson scattering length r0. For a free electron, r0 = 2.82×10-5 Å.


  • Compton scattering occurs when an electron scatters a photon and the scattered photon has a lower energy than the incident photon (an inelastic process). For Compton scattering, a fraction of the incident photon’s energy is transferred to the electron.


  • The amount of energy lost via Compton scattering where the incident photon has energy E0 = hc/λ0 and the scattered photon has energy E1 = hc/λ1 is described by the following equation. Here, ψ represents the angle between the paths of the incident photon and the scattered photon.


Scattering from atoms

  • X-rays are scattered throughout the volumes of atomic electron clouds. For x-rays that scattered in the same direction as the incident x-rays, the strength of scattering is proportional to the atom’s Z-number. In the case of an ionic atom, this value is adjusted to equal the atom’s number of electrons. Note that this assumes free electron movement within the cloud.
  • By contrast, x-rays that are scattered at some angle 2θ relative to the incident x-rays exhibit lower scattering magnitudes. Each of the x-rays scattered at angle 2θ will possess different magnitudes and phases depending on where they were scattered from within the atomic cloud. As a result, the scattering amplitude for the x-rays at angle 2θ will be a vector sum of these waves with distinct magnitudes and phases.


  • A wavevector k is a vector with magnitude 2π/λ that points in the direction of a wave’s propagation. The difference between the wavevector of the incident wave k0 and the wavevector of the scattered wave k1 is equal to a scattering vector Q (that is, Q = k0k1). The magnitude of Q is given by the following equation.


  • The atomic scattering factor f describes the total scattering amplitude for an atom as a function of sin(θ)/λ. By assuming that the atom is spherically symmetric, f will depend only on the magnitude of Q and not on its orientation relative to the atom. Values for f can be found in the International Tables for Crystallography or computed using nine known coefficients a1,2,3,4, b1,2,3,4, and c (which can also be looked up) and the following expression. The coefficients vary depending on the atom and ionic state. The units of f are the scattering amplitude that would be produced by a single electron.


  • If the incident x-ray has an energy that is much less than that of an atom’s bound electrons, the response of the electrons will be damped due to their association with the atom. (This no longer assumes free electron movement within the cloud). As a result, f will be decreased by some value fa. The value fa increases when the incoming x-ray’s energy is close to the energy level of the electron and decreases when the incoming x-ray’s energy is far above the energy levels of the electrons.
  • When the incident x-ray’s energy is close to an electron’s energy level (called an absorption edge), the x-ray is partially absorbed. With this process of partial absorption, some of the radiation is still directly scattered and another part of the radiation is re-emitted after a delay. This re-emitted radiation interferes with the directly scattered radiation. To mathematically describe the effect of the re-emitted radiation’s phase shift and interference, f is adjusted by a second term fb (which is an imaginary value). Far from absorption edges, fb has a much weaker effect (it decays by E-2). The total atomic scattering factor is then given by the following complex-valued equation.


Refraction, reflection, and absorption

  • A material’s index of refraction can be expressed as a complex quantity nc = nRe + inIm. The real part represents the rate at which the wave propagates through the material and the imaginary part describes the degree of attenuation that the wave experiences as it passes through the material.
  • The reason that a material can possess a complex refractive index involves the complex plane wave equation. The wavenumber k = 2π/λ0 is the spatial frequency in wavelengths per unit distance and it is a constant within the complex plane wave equation (λ0 is the wave’s vacuum wavelength). The complex wavenumber kc = knc is the wavenumber multiplied by the complex refractive index. As such, the complex refractive index can be related to the complex wavenumber via kc = 2πnc0 where λ0 is the vacuum wavelength of the wave. After inserting 2π(nRe + inIm)/λ0 into the complex plane wave equation, a decaying exponential can be simplified out as a coefficient for the rest of the equation. The decaying exponential represents the attenuation of the wave in the material. Once this simplification is performed, the equation’s complex wavenumber is converted to a real-valued wavenumber.


  • For x-rays, a material’s complex refractive index for wavelength λ is related to the atomic scattering factors of atoms in the material using the following equation. Ni represents the number of atoms of type j per unit volume and fj(0) is the atomic scattering factor in the forward direction (angle of zero) for atoms of type j. Recall that r0 is the Thomson scattering length.


  • The refractive index is a function of the wavelength. For most optical situations, as the absorption maximum of a material is approached from lower frequencies, the refractive index increases. But when the radiation’s frequency is high enough that it passes the absorption maximum, the refractive index decreases to a value of less than one.
  • The refractive index is defined by n = c/v, where v is the wave’s phase velocity. Phase velocity is the rate at which a wave’s phase propagates (i.e. how rapidly one of the wave’s peaks moves through space). Rearranging the equation, v = c/n is obtained. When the refractive index is less than one, the phase velocity is greater than the speed of light. However, this does not violate relativity because the group velocity (not the phase velocity) carries the wave’s energy and information. For comparison, group velocity is the rate at which a change in amplitude of an oscillation propagates.
  • Anomalous dispersion occurs when the radiation’s frequency is high enough that the refractive index of a material is less than one. As a result, x-rays entering a material from vacuum are refracted away from the normal of the refracting surface. This is in contrast to the typical case where the radiation would be refracted toward the normal of the refracting surface. In addition, the refracted wave is phase shifted by π radians.
  • The complex refractive index is often expressed using the equation below. Here, δ is called the refractive index decrement and β is called the absorption index. Note that nRe = 1 – δ and nIm = β (as a comparison to the previously used notation). Recall that nIm = β describes the degree of a wave’s attenuation as it moves through a material.


  • The refractive index decrement can be approximately computed using the average density of electrons ρ, the Thomson scattering length r0, and the wavenumber k = 2π/λ0. Note that this approximation is better for x-rays that are far from an absorption edge.


  • With most materials, the resulting real part of the index of refraction is only slightly less than one when dealing with x-rays. For example, a typical electron density of one electron per cubic Angstrom yields a δ value of about 5×10-6.
  • Snell’s law applies to the index of refraction for x-rays and is given as follows.


  • Because the index of refraction for x-rays is slightly less than one, total external reflection can occur when x-rays are incident on a surface at angles less than the critical angle θcritical. This stands in contrast with the total internal reflection that commonly occurs with visible light.


  • The critical angle can be approximated with a high level of accuracy using the following equation (derived from the Taylor expansion of the cosine function). With typical values of δ on the order of 10-5, θcritical is often equal to just a few milliradians (or a few tenths of a degree). These small angles relative to the surface are called grazing angles.


  • Because grazing incident angles facilitate x-ray reflection, special curved mirrors can be used to focus x-rays. The curvature of these mirrors must be small enough that the steepest incident angle is less than θcritical. It should be noted that, even when undergoing total external reflection, x-rays do penetrate the reflecting material to a depth of a few nanometers via an evanescent wave.


  • The absorption index β is related to the value fb using the following equation where r0 is the Thomson scattering length. Recall that fb represents the effects of scattering from absorption and remission of x-rays with energies that are close to the absorption edges of a material.


  • Using the process explained earlier for computing the decaying exponential exp(-2πnImx/λ0) that represents the attenuation of a wave’s amplitude as it travels through a material, the decay of a wave’s intensity as it travels through a material can also be found. Recall that λ0 is the wavelength in a vacuum. Because intensity is proportional to the square of the amplitude, the equation below describes the exponential decay of a wave’s intensity in a material. (This decaying exponential function is multiplied by the equation of the wave). Here, μ is called the absorption coefficient and is defined as the reciprocal of the thickness of a material required to decrease a wave’s intensity by a factor of 1/e. The absorption coefficient is a rough indication of a material’s electron density and electron binding energy.


  • The correspondences between the atomic configurations associated with an x-ray absorption edge and the commonly used name for said absorption edge are given in the following table. The subscripts used with the configurations represent the total angular momenta.


X-ray fluorescence and Auger emission

  • Materials fluoresce after bombardment with x-rays or high-energy electrons. If electrons are used, the emitted light consists of Bremsstrahlung radiation (which comes from the deacceleration of the electrons) and fluorescence lines. The Bremsstrahlung radiation includes a broad spectrum of wavelengths and has low intensity while the fluorescence lines are sharp peaks and exhibit high intensity. If x-rays are used to bombard a material, there is no Bremsstrahlung radiation, but fluorescence lines occur.
  • Different materials exhibit different characteristic fluorescence lines. These x-ray fluorescence lines are caused by outer-shell electrons relaxing to fill the holes left after the ejection of photoelectrons. However, not all electronic transitions are allowed, only those which follow the selection rules for electric dipoles. These selection rules are given below. J is the total angular momentum and can be computed from the sum of the Azimuthal quantum number L (which determines the type of atomic orbital) and the spin quantum number S (which determines the direction of an electron’s spin).


  • The nomenclature for x-ray fluorescence lines is based on the shell to which an electron relaxes. If an excited electron relaxes to the 1s shell state, then the fluorescence line is part of the K series. For an excited electron that relaxes to the 2s or 2p state, the fluorescence line is part of the L series. The M series includes relaxations to 3s, 3p, and 3d. The N series includes relaxations to 5s, 5p, 5d, and 5f. As such, the Azimuthal quantum number determines if the fluorescence line falls into the K, L, M, or N series (there are some series beyond these as well which follow the same pattern). The transition within each series that exhibits the smallest energy difference is labeled with α (i.e. Kα), the transition with the next smallest energy difference is labeled with β, and so on. It should be noted that the fluorescence lines are further split by the effects of electron spin and angular momentum and so are labeled with suffixes of 1, 2, etc.
  • Auger emission is the process where a photoelectron is ejected, an outer shell electron relaxes to fill the hole, and the released energy causes ejection another electron instead of emitting a photon. The energies of emitted Auger electrons are independent of the energies of the incident photons.
  • The excess energy released by the relaxation of the outer shell electron is equal to |Ecore – Eouter|. In order for the last electron ejection to occur, the electron must have a binding energy that is less than the excess released energy from the relaxation. The kinetic energy of the ejected Auger electron is |Ecore – Eouter – Ebinding|. Note that Ebinding is the binding energy of the Auger electron in the ionized atom (which is different from the binding energy in the neutral form of the atom).
  • Auger emission and x-ray fluorescence are competitive with each other. Fluorescence is stronger for heavier atoms (higher Z-number) since they exhibit larger energy differences between adjacent shells as well as binding electrons more tightly. For the same reasons, Auger emission is stronger from atoms with lower Z-numbers.



Reference: Willmott, P. (2011). An Introduction to Synchrotron Radiation: Techniques and Applications. Wiley.

Cover image courtesy of: Asia Times






Global Highlights in Neuroengineering 2005-2018

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PDF version: global highlights in neuroengineering 2005-2018 – logan thrasher collins

Optogenetic stimulation using ChR2

(Boyden, Zhang, Bamberg, Nagel, & Deisseroth, 2005)

  • Ed Boyden, Karl Deisseroth, and colleagues developed optogenetics, a revolutionary technique for stimulating neural activity.
  • Optogenetics involves engineering neurons to express light-gated ion channels. The first channel used for this purpose was ChR2 (a protein originally found in bacteria which responds to blue light). In this way, a neuron exposed to an appropriate wavelength of light will be stimulated.
  • Over time, optogenetics has gained a place as an essential experimental tool for neuroscientists across the world. It has been expanded upon and improved in numerous ways and has even allowed control of animal behavior via implanted fiber optics and other light sources. Optogenetics may eventually be used in the development of improved brain-computer interfaces.


Blue Brain Project cortical column simulation

(Markram, 2006)

  • In the early stages of the Blue Brain Project, neuronal cell types from the layers of the rat neocortex were reconstructed. Furthermore, their electrophysiology was experimentally characterized.
  • Next, a virtual neocortical column with about 10,000 multicompartmental Hodgkin-Huxley-type neurons and over ten million synapses was built. Its connectivity was defined according the patterns of connectivity found in biological rats, (though this involved the numbers of inputs and outputs quantified for given cell types rather than explicit wiring). In addition, the spatial distributions of boutons forming synaptic terminals upon target cells reflected biological data.
  • The cortical column was emulated using the Blue Gene/L supercomputer and the dynamics of the emulation reflected its biological counterpart.

cortical column

Optogenetic silencing using halorhodopsin

(Han & Boyden, 2007)

  • Ed Boyden continued developing optogenetic tools to manipulate neural activity. Along with Xue Han, he expressed a codon-optimized version of a bacterial halorhodopsin (along with the ChR2 protein) in neurons.
  • Upon exposure to yellow light, halorhodopsin pumps chloride ions into the cell, hyperpolarizing the membrane and inhibiting neural activity.
  • Using halorhodopsin and ChR2, neurons could be easily activated and inhibited using yellow and blue light respectively.

halorhodopsin and chr2 wavelengths


(Livet et al., 2007)

  • Lichtman and colleagues used Cre/Lox recombination tools to create genes which express a randomized set of three or more differently-colored fluorescent proteins (XFPs) in a given neuron, labeling the neuron with a unique combination of colors. About ninety distinct colors were emitted across a population of genetically modified neurons.
  • The detailed structures within neural tissue equipped with the Brainbow system can be imaged much more easily since neurons can be distinguished via color contrast.
  • As a proof-of-concept, hundreds of synaptic contacts and axonal processes were reconstructed in a selected volume of the cerebellum. Several other neural structures were also imaged using Brainbow.
  • The fluorescent proteins expressed by the Brainbow system are usable in vivo.


High temporal precision optogenetics

(Gunaydin et al., 2010)

  • Karl Deisseroth, Peter Hegemann, and colleagues used protein engineering to improve the temporal resolution of optogenetic stimulation.
  • Glutamic acid at position 123 in ChR2 was mutated to threonine, producing a new ion channel protein (dubbed ChETA).
  • The ChETA protein allows for induction of spike trains with frequencies up to 200 Hz and greatly decreases the incidence of unintended spikes. Furthermore, ChETA eliminates plateau potentials (a phenomenon which interferes with precise control of neural activity).

ultrafast optogenetics

Hippocampal prosthesis in rats

(Berger et al., 2012)

  • Theodore Berger and his team developed an artificial replacement for neurons which transmit information from the CA3 region to the CA1 region of the hippocampus.
  • This cognitive prosthesis employs recording and stimulation electrodes along with a multi-input multi-output (MIMO) model to encode the information in CA3 and transfer it to CA1.
  • The hippocampal prosthesis was shown to restore and enhance memory in rats as evaluated by behavioral testing and brain imaging.

In vivo superresolution microscopy for neuroimaging

(Berning, Willig, Steffens, Dibaj, & Hell, 2012)

  • Stefan Hell (2014 Nobel laureate in chemistry) developed stimulated emission depletion microscopy (STED), a type of superresolution fluorescence microscopy which allows imaging of synapses and dendritic spines.
  • STED microscopy uses a torus-shaped de-excitation laser that interferes with the excitation laser to deplete fluorescence except in a very small spot. In this way, the diffraction limit is surpassed since the resulting light illuminates extremely small regions of the sample.
  • Neurons in transgenic mice (equipped with glass-sealed holes in their skulls) were imaged using STED. Synapses and dendritic spines were observed up to fifteen nanometers below the surface of the brain tissue.

superresolution microscopy in vivo

In vivo three-photon microscopy

(Horton et al., 2013)

  • Multi-photon excitation uses pulsed lasers to excite fluorophores with two or more photons of light with long wavelengths. During the excitation, the photons undergo a nonlinear recombination process, yielding a single emitted photon with a much shorter wavelength. Because the excitation photons possess long wavelengths, they can penetrate tissue much more deeply than traditional microscopy allows.
  • Horton and colleagues developed a three-photon excitation method to facilitate even deeper tissue penetration than the commonly used two-photon microscopic techniques.
  • Since three photons were involved per excitation event, even longer excitation wavelengths (about 1,700 nm) were usable, allowing the construction of a 3-dimensional image stack that reached a depth of up to 1.4 mm within the living mouse brain.
  • Blood vessels and RFP-labeled neurons were imaged using this approach. Furthermore, the depth was sufficient to enable imaging of neurons within the mouse hippocampus.

3-photon microscopy

Whole-brain functional recording from larval zebrafish

(Ahrens, Orger, Robson, Li, & Keller, 2013)

  • Laser-scanning light-sheet microscopy was used to volumetrically image the entire brains of larval zebrafish (an optically transparent organism).
  • The genetically encoded calcium sensor GCaMP5G facilitated functional recording at single-cell resolution from about 80% of the total neurons in the larval zebrafish brains. Computational methods were used to distinguish between individual neurons.
  • Populations of neurons that underwent correlated activity patterns were identifiedto show the technique’s utility for uncovering the dynamics of neural circuits. These populations included hindbrain neurons that were functionally linked to neural activity in the spinal cord and a population of neurons which showed coupled oscillations on the left and right halves.

whole-brain recording from larval zebrafish

Eyewire: crowdsourcing method for retina mapping

(Marx, 2013)

  • The Eyewire project was created by Sebastian Seung’s research group. It is a crowdsourcing initiative for connectomic mapping within the retina towards uncovering neural circuits involved in visual processing.
  • Laboratories first collect data via serial electron microscopy as well as functional data from two-photon microscopy.
  • In the Eyewire game, images of tissue slices are provided to players who then help reconstruct neural morphologies and circuits by “coloring in” the parts of the images which correspond to cells and stacking many images on top of each other to generate 3D maps. Artificial intelligence tools help provide initial “best guesses” and guide the players, but the people ultimately perform the task of reconstruction.
  • By November 2013, around 82,000 participants had played the game. Its popularity continues to grow.


The BRAIN Initiative

(“Fact Sheet: BRAIN Initiative,” 2013)

  • The BRAIN Initiative (Brain Research through Advancing Innovative Technologies) provided neuroscientists with $110 million in governmental funding and $122 million in funding from private sources such as the Howard Hughes Medical Institute and the Allen Institute for Brain Science.
  • The BRAIN Initiative focused on funding research which develops and utilizes new technologies for functional connectomics. It helped to accelerate research on tools for decoding the mechanisms of neural circuits in order to understand and treat mental illness, neurodegenerative diseases, and traumatic brain injury.
  • The BRAIN Initiative emphasized collaboration between neuroscientists and physicists. It also pushed forward nanotechnology-based methods to image neural tissue, record from neurons, and otherwise collect neurobiological data.

The CLARITY method for making brains translucent

(Chung & Deisseroth, 2013)

  • Karl Deisseroth and colleagues developed a method called CLARITY to make samples of neural tissue optically translucent without damaging the fine cellular structures in the tissue. Using CLARITY, entire mouse brains have been turned transparent.
  • Mouse brains were infused with hydrogel monomers (acrylamide and bisacrylamide) as well as formaldehyde and some other compounds for facilitating crosslinking. Next, the hydrogel monomers were crosslinked by incubating the brains at 37°C. Lipids in the hydrogel-stabilized mouse brains were extracted using hydrophobic organic solvents and electrophoresis.
  • CLARITY allows antibody labeling, fluorescence microscopy, and other optically-dependent techniques to be used for imaging entire brains. In addition, it renders the tissue permeable to macromolecules, which broadens the types of experimental techniques that these samples can undergo (i.e. macromolecule-based stains, etc.)

clarity imaging technique

X-ray microtomography used to reconstruct Drosophila brain hemisphere

(Mizutani, Saiga, Takeuchi, Uesugi, & Suzuki, 2013)

  • Mizutani and colleagues stained Drosophila brains with silver nitrate and tetrachloroaurate (a gold-containing compound), facilitating 3-dimensional imaging using X-ray microtomography at a voxel size of 220 × 328 × 314 nm.
  • To generate the X-rays, a synchrotron source was used. It should be noted that synchrotron sources require large facilities to operate.
  • Neuronal tracing was performed manually on the 3-dimensional X-ray images of the fly brain, a process which took about 1,700 person-hours. Some neuronal processes were too dense to be resolved, so they were “fused” into unified structures. Furthermore, some neuronal traces were fragmented and most of the cell bodies were not considered. This decreased the number of traces to one third of the estimated number of actual processes in the hemisphere.
  • Mizutani’s investigation represents an early effort at large-scale connectomics that sets the stage for further initiatives as neuronal tracing, sample preparation, and X-ray microtomography technologies continue to improve.

traced drosophila brain hemisphere

Telepathic rats engineered using hippocampal prosthesis

(S. Deadwyler et al., 2013)

  • Berger’s hippocampal prosthesis was implanted in pairs of rats. When “donor” rats were trained to perform a task, they developed neural representations (memories) which were recorded by their hippocampal prostheses.
  • The donor rat memories were run through the MIMO model and transmitted to the stimulation electrodes of the hippocampal prostheses implanted in untrained “recipient” rats. After receiving the memories, the recipient rats showed significant improvements on the task that they had not been trained to perform.

rat telepathy

Integrated Information Theory 3.0

(Oizumi, Albantakis, & Tononi, 2014)

  • Integrated information theory (IIT) was originally proposed by Giulio Tononi in 2004. IIT is a quantitative theory of consciousness which may help explain the hard problem of consciousness.
  • IIT begins by assuming the following phenomenological axioms; each experience is characterized by how it differs from other experiences, an experience cannot be reduced to interdependent parts, and the boundaries which distinguish individual experiences are describable as having defined “spatiotemporal grains.”
  • From these phenomenological axioms and the assumption of causality, IIT identifies maximally irreducible conceptual structures (MICS) associated with individual experiences. MICS represent particular patterns of qualia that form unified percepts.
  • IIT also outlines a mathematical measure of an experience’s quantity. This measure is called integrated information or ϕ.


(Szigeti et al., 2014)

  • The anatomical elegans connectome was originally mapped in 1976 by Albertson and Thomson. More data has since been collected on neurotransmitters, electrophysiology, cell morphology, and other characteristics.
  • Szigeti, Larson, and their colleagues made an online platform for crowdsourcing research on elegans computational neuroscience, with the goal of completing an entire “simulated worm.”
  • The group also released software called Geppetto, a program that allows users to manipulate both multicompartmental Hodgkin-Huxley models and highly efficient soft-body physics simulations (for modeling the worm’s electrophysiology and anatomy).

c. elegans connectome

Expansion microscopy

(F. Chen, Tillberg, & Boyden, 2015)

  • The Boyden group developed expansion microscopy, a method which enlarges neural tissue samples (including entire brains) with minimal structural distortions and so facilitates superior optical visualization of the scaled-up neural microanatomy. Furthermore, expansion microscopy greatly increases the optical translucency of treated samples.
  • Expansion microscopy operates by infusing a swellable polymer network into brain tissue samples along with several chemical treatments to facilitate polymerization and crosslinking and then triggering expansion via dialysis in water. With 4.5-fold enlargement, expansion microscopy only distorts the tissue by about 1% (computed using a comparison between control superresolution microscopy of easily-resolvable cellular features and the expanded version).
  • Before expansion, samples can express various fluorescent proteins to facilitate superresolution microscopy of the enlarged tissue once the process is complete. Furthermore, expanded tissue is highly amenable to fluorescent stains and antibody-based labels.

expansion microscopy

Japan’s Brain/MINDS project

(Okano, Miyawaki, & Kasai, 2015)

  • In 2014, the Brain/MINDS (Brain Mapping by Integrated Neurotechnologies for Disease Studies) project was initiated to further neuroscientific understanding of the brain. This project received nearly $30 million in funding for its first year alone.
  • Brain/MINDS focuses on studying the brain of the common marmoset (a non-human primate abundant in Japan), developing new technologies for brain mapping, and understanding the human brain with the goal of finding new treatments for brain diseases.

The TrueNorth chip from DARPA and IBM

(Akopyan et al., 2015)

  • The TrueNorth neuromorphic computing chip was constructed and validated by DARPA and IBM. TrueNorth uses circuit modules which mimic neurons. Inputs to these fundamental circuit modules must overcome a threshold in order to trigger “firing.”
  • The chip can emulate up to a million neurons with over 250 million synapses while requiring far less power than traditional computing devices.

Human Brain Project cortical mesocircuit reconstruction and simulation

(Markram et al., 2015)

  • The Human Brain Project reconstructed a 0.29 mm3 region of rat cortical tissue including about 31,000 neurons and 37 million synapses based on morphological data, statistical connectivity rules (rather than exact connectivity), and other datasets. The cortical mesocircuit was emulated using the Blue Gene/Q supercomputer.
  • This emulation was sufficiently accurate to reproduce emergent neurological processes and yield insights on the mechanisms of their computations.

cortical mesocircuit

Recording from C. elegans neurons reveals motor operations

(Kato et al., 2015)

  • Live elegans worms were immobilized in microfluidic devices and the neurons in their head ganglia as well as some of their motor systems were imaged and recorded from using the calcium indicator GCaMP. As the C. elegans connectome is well-characterized, Kato and colleagues were able to determine the identities of most of the cells that underwent imaging (with the help of computational segmentation techniques).
  • Principal component analysis was used to reduce the dimensionality of the neural activity datasets since over 100 neurons per worm were recorded from simultaneously.
  • Next, phase space analysis was utilized to visualize the patterns formed by the recording data. Motor behaviors including dorsal turns, ventral turns, forward movements, and backward movements were found to correspond to specific sequences of neural events as uncovered by examining the patterns found in the phase plots. Further analyses revealed various insights about these brain dynamics and their relationship to motor actions.

c. elegans brain dynamics

Neural lace

(Liu et al., 2015)

  • Charles Lieber’s group developed a syringe-injectable electronic mesh made of submicrometer-thick wiring for neural interfacing.
  • The meshes were constructed using novel soft electronics for biocompatibility. Upon injection, the neural lace expands to cover and record from centimeter-scale regions of tissue.
  • Neural lace may allow for “invasive” brain-computer interfaces to circumvent the need for surgical implantation. Lieber has continued to develop this technology towards clinical application.

neural lace

BigNeuron initiative towards standardized neuronal morphology acquisition

(Peng et al., 2015)

  • Because of the inconsistencies between neuronal reconstruction methods and lack of standardization found in neuronal morphology databases, BigNeuron was established as a community effort to improve the situation.
  • BigNeuron tests as many automated neuronal reconstruction algorithms as possible using large-scale microscopy datasets (from several types of light microscopy). It uses the Vaa3D neuronal reconstruction software as a central platform. Reconstruction algorithms are added to Vaa3D as plugins. These computational tests are performed on supercomputers.
  • BigNeuron aims to create a superior community-oriented neuronal morphology database, a set of greatly improved tools for neuronal reconstruction, a standardized protocol for future neuronal reconstructions, and a library of morphological feature definitions to facilitate classification.

Human telepathy during a 20 questions game

(Stocco et al., 2015)

  • Using an interactive question-and-answer setup, Stocco and colleagues demonstrated real-time telepathic communication between pairs of individuals via EEG and transcranial magnetic stimulation. Five pairs of participants played games of 20 questions and attempted to identify unknown objects.
  • EEG data were recorded from the respondent, computationally processed, and transmitted as transcranial magnetic stimulation signals into the mind (occipital lobe stimulation) of a respondent. The respondent’s answers were translated into higher-intensity transcranial magnetic stimulation pulses corresponding to “yes” answers or lower-intensity transcranial magnetic stimulation pulses corresponding to “no” answers.
  • When compared to control trials in which sham interfaces were used, the people using the brain-brain interfaces were significantly more successful at playing 20 questions games.

Expansion FISH

(F. Chen et al., 2016)

  • Boyden, Chen, Marblestone, Church, and colleagues combined fluorescent in situ hybridization (FISH) with expansion microscopy to image the spatial localization of RNA in neural tissue.
  • The group developed a chemical linker to covalently attach intracellular RNA to the infused polymer network used in expansion microscopy. This allowed for RNAs to maintain their relative spatial locations within each cell post-expansion.
  • After the tissue was enlarged, FISH was used to fluorescently label targeted RNA molecules. In this way, RNA localization was more effectively resolved.
  • As a proof-of-concept, expansion FISH was used to reveal the nanoscale distribution of long noncoding RNAs in nuclei as well as the locations of RNAs within dendritic spines.

expansion fish

Neural dust

(Seo et al., 2016)

  • Michel Maharbiz’s group invented implantable, ~ 1 mm biosensors for wireless neural recording and tested them in rats.
  • This neural dust could be miniaturized to less than 0.5 mm or even to microscale dimensions using customized electronic components.
  • Neural dust motes consist of two recording electrodes, a transistor, and a piezoelectric crystal.
  • The neural dust received external power from ultrasound. Neural signals were recorded by measuring disruptions to the piezoelectric crystal’s reflection of the ultrasound waves. Signal processing mathematics allowed precise detection of activity.

neural dust

The China Brain Project

(Poo et al., 2016)

  • The China Brain Project was launched to help understand the neural mechanisms of cognition, develop brain research technology platforms, develop preventative and diagnostic interventions for brain disorders, and to improve brain-inspired artificial intelligence technologies.
  • This project will be take place from 2016 until 2030 with the goal of completing mesoscopic brain circuit maps.
  • China’s population of non-human primates and preexisting non-human primate research facilities give the China Brain Project an advantage. The project will focus on studying rhesus macaques.

Somatosensory cortex stimulation for spinal cord injuries

(Flesher et al., 2016)

  • Gaunt, Flesher, and colleagues found that microstimulation of the primary somatosensory cortex (S1) partially restored tactile sensations to a patient with a spinal cord injury.
  • Electrode arrays were implanted into the S1 regions of a patient with a spinal cord injury. The array performed intracortical microstimulation over a period of six months.
  • The patient reported locations and perceptual qualities of the sensations elicited by microstimulation. The patient did not experience pain or “pins and needles” from any of the stimulus trains. Overall, 93% of the stimulus trains were reported as “possibly natural.”
  • Results from this study might be used to engineer upper-limb neuroprostheses which provide somatosensory feedback.

somatosensory stimulation

Simulation of rat CA1 region

(Bezaire, Raikov, Burk, Vyas, & Soltesz, 2016)

  • Detailed computational models of 338,740 neurons (including pyramidal cells and various types of interneurons) were equipped with connectivity patterns based on data from the biological CA1 region. External inputs were also estimated using biological data and incorporated into the simulation. It is important to note that these connectivity patterns described the typical convergence and divergence of neurites to and from particular cell types rather than explicitly representing the exact connections found in the biological rat.
  • Each neuron was simulated using a multicompartmental Hodgkin-Huxley-type model with its morphological structure based on biological data from the given cell type. Furthermore, different cell types received different numbers of presynaptic terminals at specified distances from the soma. In total, over five billion synapses were present within the CA1 model.
  • The simulation was implemented on several different supercomputers. Due to the model’s complexity, a four second simulation took about four hours to complete.
  • As with the biological CA1 region, the simulation gave rise to gamma oscillations and theta oscillations as well as other biologically consistent phenomena. In addition, parvalbumin-expressing interneurons and neurogliaform cells were identified as drivers of the theta oscillations, demonstrating the utility of detailed neuronal simulations for uncovering biological insights.

ca1 simulation

UltraTracer enhances existing neuronal tracing software

(Peng et al., 2017)

  • UltraTracer is an algorithm that can improve the efficiency of existing neuronal tracing software for handling large datasets while maintaining accuracy.
  • Datasets with hundreds of billions of voxels were utilized to test UltraTracer. Ten existing tracing algorithms were augmented.
  • For most of the existing algorithms, the performance improvements were around 3-6 times, though a few showed improvements of 10-30 times. Even when using computers with smaller memory, UltraTracer was consistently able to enhance conventional software.
  • UltraTracer was made opensource and is available as a plugin for the Vaa3D tracing software suite.

Whole-brain electron microscopy in larval zebrafish

(Hildebrand et al., 2017)

  • Serial electron microscopy facilitated imaging of the entire brain of a larval zebrafish at 5.5 days post-fertilization.
  • Neuronal tracing software (a modified version of the CATMAID software) was used to reconstruct all the myelinated axons found in the larval zebrafish brain.
  • The reconstructed dataset included 2,589 myelinated axon segments along with some of the associated soma and dendrites. It should be noted that only 834 of the myelinated axons were successfully traced back to their cell bodies.

ssem of larval zebrafish brain

Hippocampal prosthesis in monkeys

(S. A. Deadwyler et al., 2017)

  • Theodore Berger continued developing his cognitive prosthesis and tested it in Rhesus Macaques.
  • As with the rats, monkeys with the implant showed substantially improved performance on memory tasks.

The $100 billion Softbank Vision Fund

(Lomas, 2017)

  • Masayoshi Son, the CEO of Softbank (a Japanese telecommunications corporation), announced a plan to raise $100 billion in venture capital to invest in artificial intelligence. This plan involved partnering with multiple large companies in order to raise this enormous amount of capital.
  • By the end of 2017, the Vision Fund successfully reached its $100 billion goal. Masayoshi Son has since announced further plans to continue raising money with a new goal of over $800 billion.
  • Masayoshi Son’s reason for these massive investments is the Technological Singularity. He agrees with Kurzweil that the Singularity will likely occur at around 2045 and he hopes to help bring the Singularity to fruition. Though Son is aware of the risks posed by artificial superintelligence, he feels that superintelligent AI’s potential to tackle some of humanity’s greatest challenges (such as climate change and the threat of nuclear war) outweighs those risks.

Bryan Johnson launches Kernel

(Regalado, 2017)

  • Entrepreneur Bryan Johnson invested $100 million to start Kernel, a neurotechnology company.
  • Kernel plans to develop implants that allow for recording and stimulation of large numbers of neurons at once. The company’s initial goal is to develop treatments for mental illnesses and neurodegenerative diseases. Its long-term goal is to enhance human intelligence.
  • Kernel originally partnered with Theodore Berger and intended to utilize his hippocampal prosthesis. Unfortunately, Berger and Kernel parted ways after about six months because Berger’s vision was reportedly too long-range to support a financially viable company (at least for now).
  • Kernel was originally a company called Kendall Research Systems. This company was started by a former member of the Boyden lab. In total, four members of Kernel’s team are former Boyden lab members.

Elon Musk launches NeuraLink

(Etherington, 2017)

  • Elon Musk (CEO of Tesla, SpaceX, and a number of other successful companies) initiated a neuroengineering venture called NeuraLink.
  • NeuraLink will begin by developing brain-computer interfaces (BCIs) for clinical applications, but the ultimate goal of the company is to enhance human cognitive abilities in order to keep up with artificial intelligence.
  • Though many of the details around NeuraLink’s research are not yet open to the public, it has been rumored that injectable electronics similar to Lieber’s neural lace might be involved.

Facebook announces effort to build brain-computer interfaces

(Constine, 2017)

  • Facebook revealed research on constructing non-invasive brain-computer interfaces (BCIs) at a company-run conference in 2017. The initiative is run by Regina Dugan, Facebook’s head of R&D at division building 8.
  • Facebook’s researchers are working on a non-invasive BCI which may eventually enable users to type one hundred words per minute with their thoughts alone. This effort builds on past investigations which have been used to help paralyzed patients.
  • The building 8 group is also developing a wearable device for “skin hearing.” Using just a series of vibrating actuators which mimic the cochlea, test subjects have so far been able to recognize up to nine words. Facebook intends to vastly expand this device’s capabilities.

DARPA funds research to develop improved brain-computer interfaces

(Hatmaker, 2017)

  • The U.S. government agency DARPA awarded $65 million in total funding to six research groups.
  • The recipients of this grant included five academic laboratories (headed by Arto Nurmikko, Ken Shepard, Jose-Alain Sahel and Serge Picaud, Vicent Pieribone, and Ehud Isacoff) and one small company called Paradromics Inc.
  • DARPA’s goal for this initiative is to develop a nickel-sized bidirectional brain-computer interface (BCI) which can record from and stimulate up to one million individual neurons at once.

Human Brain Project analyzes brain computations using algebraic topology

(Reimann et al., 2017)

  • Investigators at the Human Brain Project utilized algebraic topology to analyze the reconstructed ~ 31,000 neuron cortical microcircuit from their earlier work.
  • The analysis involved representing the cortical network as a digraph, finding directed cliques (complete directed subgraphs belonging to a digraph), and determining the net directionality of information flow (by computing the sum of the squares of the differences between in-degree and out-degree for all the neurons in a clique). In algebraic topology, directed cliques of n neurons are called directed simplices of dimension n-1.
  • Vast numbers of high-dimensional directed cliques were found in the cortical microcircuit (as compared to null models and other controls). Spike correlations between pairs of neurons within a clique were found to increase with the clique’s dimension and with the proximity of the neurons to the clique’s sink. Furthermore, topological metrics allowed insights into the flow of neural information among multiple cliques.
  • Experimental patch-clamp data supported the significance of the findings. In addition, similar patterns were found within the elegans connectome, suggesting that the results may generalize to nervous systems across species.

hbp algebraic topology

Early testing of hippocampal prosthesis algorithm in humans

(Song, She, Hampson, Deadwyler, & Berger, 2017)

  • Dong Song (who was working alongside Berger) tested the MIMO algorithm on human epilepsy patients using implanted recording and stimulation electrodes. The full hippocampal prosthesis was not implanted, but the electrodes acted similarly, though in a temporary capacity. Although only two patients were tested in this study, many trials were performed to compensate for the small sample size.
  • Hippocampal spike trains from individual cells in CA1 and CA3 were recorded from the patients during a delayed match-to-sample task. The patients were shown various images while neural activity data were recorded by the electrodes and processed by the MIMO model. The patients were then asked to recall which image they had been shown previously by picking it from a group of “distractor” images. Memories encoded by the MIMO model were used to stimulate hippocampal cells during the recall phase.
  • In comparison to controls in which the same two epilepsy patients were not assisted by the algorithm and stimulation, the experimental trials demonstrated a significant increase in successful pattern matching.

Brain imaging factory in China

(Cyranoski, 2017)

  • Qingming Luo started the HUST-Suzhou Institute for Brainsmatics, a brain imaging “factory.” Each of the numerous machines in Luo’s facility performs automated processing and imaging of tissue samples. The devices make ultrathin slices of brain tissue using diamond blades, treat the samples with fluorescent stains or other contrast-enhancing chemicals, and image then using fluorescence microscopy.
  • The institute has already demonstrated its potential by mapping the morphology of a previously unknown neuron which “wraps around” the entire mouse brain.

china brain mapping image

Automated patch-clamp robot for in vivo neural recording

(Suk et al., 2017)

  • Ed Boyden and colleagues developed a robotic system to automate patch-clamp recordings from individual neurons. The robot was tested in vivo using mice and achieved a data collection yield similar to that of skilled human experimenters.
  • By continuously imaging neural tissue using two-photon microscopy, the robot can adapt to a target cell’s movement and shift the pipette to compensate. This adaptation is facilitated by a novel algorithm called an imagepatching algorithm. As the pipette approaches its target, the algorithm adjusts the pipette’s trajectory based on the real-time two-photon microscopy.
  • The robot can be used in vivo so long as the target cells express a fluorescent marker or otherwise fluoresce corresponding to their size and position.

automated patch clamp system

Genome editing in the mammalian brain

(Nishiyama, Mikuni, & Yasuda, 2017)

  • Precise genome editing in the brain has historically been challenging because most neurons are postmitotic (non-dividing) and the postmitotic state prevents homology-directed repair (HDR) from occurring. HDR is a mechanism of DNA repair which allows for targeted insertions of DNA fragments with overhangs homologous to the region of interest (by contrast, non-homologous end-joining is highly unpredictable).
  • Nishiyama, Mikuni, and Yasuda developed a technique which allows genome editing in postmitotic mammalian neurons using adeno-associated viruses (AAVs) and CRISPR-Cas9.
  • The AAVs delivered ssDNA sequences encoding a single guide RNA (sgRNA) and an insert. Inserts encoding a hemagglutinin tag (HA) and inserts encoding EGFP were both tested. Cas9 was encoded endogenously by transgenic host cells and in transgenic host animals.
  • The technique achieved precise genome editing in vitro and in vivo with a low rate of off-target effects. Inserts did not cause deletion of nearby endogenous sequences for 98.1% of infected neurons.

genome editing neuronsNeuropixels probe

(Jun et al., 2017)

  • Jun and colleagues created the Neuropixels probe to facilitate simultaneous recording from hundreds of individual neurons with high spatiotemporal resolution. Previous extracellular probes were only able to record from a few dozen individual neurons.
  • The Neuropixels recording shank is one centimeter long and includes 384 recording channels. Due to the small size of the accompanying apparatus (a 6×9 mm base and a data transmission cable), it enables high-throughput recording in freely moving animals. Because the shank is quite long, Neuropixels can record from multiple brain regions at once.
  • Voltage signals are processed directly on the base of the Neuropixels apparatus, allowing for noise-free data transmission along the cable for further analysis.


EEG-based facial image reconstruction

(Nemrodov, Niemeier, Patel, & Nestor, 2018)

  • EEG data associated with viewing images of faces was collected and used to determine the neural correlates of facial processing. In this way, the images were computationally reconstructed in a fashion resembling “mind reading.”
  • It should be noted that the images reconstructed using data taken from multiple people were more accurate than the images reconstructed using single individuals. Nonetheless, the single individual data still yielded statistically significant accuracy.
  • In addition to reconstructing the images themselves, the process gave insights on the cognitive steps involved in perceiving faces.

eeg reconstructions of faces

Near-infrared light and upconversion nanoparticles for optogenetic stimulation

(S. Chen et al., 2018)

  • Upconversion nanoparticles absorb two or more low-energy photons and emit a higher energy photon. For instance, multiple near-infrared photons can be converted into a single visible spectrum photon.
  • Shuo Chen and colleagues injected upconversion nanoparticles into the brains of mice and used them to convert externally applied near-infrared (NIR) light into visible light within the brain tissue. In this way, optogenetic stimulation was performed without the need for surgical implantation of fiber optics or similarly invasive procedures.
  • The authors demonstrated stimulation via upconversion of NIR to blue light (to activate ChR2) and inhibition via upconversion of NIR to green light (to activate a rhodopsin called Arch).
  • As a proof-of-concept, this technology was used to alter the behavior of the mice by activating hippocampally-encoded fear memories.

upconversion nanoparticles and nir

Map of all neuronal cell bodies within mouse brain

(Murakami et al., 2018)

  • Ueda, Murakami, and colleagues combined methods from expansion microscopy and CLARITY to develop a protocol called CUBIC-X which both expands and clears entire brains. Light-sheet fluorescence microscopy was used to image the treated brains and a novel algorithm was developed to detect individual nuclei.
  • Although expansion microscopy causes some increased tissue transparency on its own, CUBIC-X greatly improved this property in the enlarged tissues, facilitating more detailed whole-brain imaging.
  • Using CUBIC-X, the spatial locations of all the cell bodies (but not dendrites, axons, or synapses) within the mouse brain were mapped. This process was performed upon several adult mouse brains as well as several developing mouse brains to allow for comparative analysis.
  • The authors made the spatial atlas publicly available in order to facilitate global cooperation towards annotating connectivity among the neural cell bodies within the atlas.


Clinical testing of hippocampal prosthesis algorithm in humans

(Hampson et al., 2018)

  • Further clinical tests of Berger’s hippocampal prosthesis were performed. Twenty-one patients took part in the experiments. Seventeen patients underwent CA3 recording so as to facilitate training and optimization of the MIMO model. Eight patients received CA1 stimulation so as to improve their memories.
  • Electrodes with the ability to record from single neurons (10-24 single-neuron recording sites) and via EEG (4-6 EEG recording sites) were implanted such that recording and stimulation could occur at CA3 and CA1 respectively.
  • Patients performed behavioral memory tasks. Both short-term and long-term memory showed an average improvement of 35% across the patients who underwent stimulation.

Precise optogenetic manipulation of fifty neurons

(Mardinly et al., 2018)

  • Mardinly and colleagues engineered a novel excitatory optogenetic ion channel called ST-ChroME and a novel inhibitory optogenetic ion channel called IRES-ST-eGtACR1. The channels were localized to the somas of host neurons and generated stronger photocurrents over shorter timescales than previously existing opsins, allowing for powerful and precise optogenetic stimulation and inhibition.
  • 3D-SHOT is an optical technique in which light is tuned by a device called a spatial light modulator along with several other optical components. Using 3D-SHOT, light was precisely projected upon targeted neurons within a volume of 550×550×100 μm3.
  • By combining novel optogenetic ion channels and the 3D-SHOT technique, complex patterns of neural activity were created in vivo with high spatial and temporal precision.
  • Simultaneously, calcium imaging allowed measurement of the induced neural activity. More custom optoelectronic components helped avoid optical crosstalk of the fluorescent calcium markers with the photostimulating laser.

optogenetic control of fifty neurons

Whole-brain Drosophila connectome data acquired via serial electron microscopy

(Zheng et al., 2018)

  • Zheng, Bock, and colleagues collected serial electron microscopy data on the entire adult Drosophila connectome, providing the data necessary to reconstruct a complete structural map of the fly’s brain at the resolution of individual synapses, dendritic spines, and axonal processes.
  • The data are in the form of 7050 transmission electron microscopy images (187500 x 87500 pixels and 16 GB per image), each representing a 40nm-thin slice of the fly’s brain. In total the dataset requires 106 TB of storage.
  • Although much of the the data still must be processed to reconstruct a 3-dimensional map of the Drosophila brain, the authors did create 3-dimensional reconstructions of selected areas in the olfactory pathway of the fly. In doing so, they discovered a new cell type as well as several other previously unrealized insights about the organization of Drosophila’s olfactory biology.

drosophila connectome with sem

Human telepathy using BrainNet

(Jiang et al., 2018)

  • EEG recordings were taken from two individuals (termed senders) while they played a Tetris-like game. Next, the recordings were converted into transcranial magnetic stimulation signals that acted to provide a third individual (called a receiver) with the necessary information to make decisions in the game without seeing the screen. The occipital cortex was stimulated. Fifteen people (five groups of three) took part in the study.
  • To convey their information, the senders were told to focus upon either a higher or a lower intensity light corresponding to commands within the game (the two lights were placed on different sides of the computer screen). In the receiver’s mind, this translated to perceiving a flash of light. The receiver was able to distinguish the intensities and implement the correct command within the game.
  • Using only the telepathically provided stimulation, the receiver made the correct game-playing decisions 81% of the time.


Transcriptomic cell type classification across mouse neocortex

(Tasic et al., 2018)

  • Single-cell RNA sequencing was used to characterize gene expression across 23,822 cells from the primary visual cortex and the anterior lateral motor cortex of mice.
  • Using dimensionality reduction and clustering methods, the resulting data were used to classify the neurons into 133 transcriptomic cell types.
  • Injections of adeno associated viruses (engineered to express fluorescent markers) facilitated retrograde tracing of neuronal projections within a subset of the sequenced cells. In this way, correspondences between projection patterns and transcriptomic identities were established.



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