Question #9: Variation of neural processing in sensory systems

The fact that so many sensory systems eventually project to the cerebral cortex indicates that there are likely similarities in their processing. Evolutionarily, it’s plausible that most neural sensory systems diverged from one common system that involved early analogue of the cortex.

Within mammals, there is a large amount of variation in the number of cortical areas, with most of these subdivisions in all mammals involved in sensory-perceptual tasks. Additionally, some sensory regions of the neocortex have been well preserved throughout the mammalian lineage, including visual cortices V1 / V2, somatosensory cortices S1 / S2, and possibly the primary auditory cortex A1. In order to add additional regions from this baseline amount, evolution might have either selected for rapid duplication of one existing region, or the gradual differentiation of one region into two.

In the visual pathway, the different brain regions contain neurons with different cell morphologies that are arranged in hierarchical fashion. Elston et al gathered data from layer III pyramidal neurons of V1, V2, the medial temporal lobe, V4, the inferior temporal cortex, and finally the superior temporal polysensory of the macaque. When they arranged the data from the pyramidal cells in order they found a beautiful pattern in the basal dendritic field areas, spine densities, and somal areas. I’ve reproduced part a of their figure 2 below but check out the open-access pdf of their paper for all of the data:

This data shows that there is a hierarchical organization of pyramidal cell morphology in the visual system. If there is indeed a common form of neural processing between the various types of sensory systems, we should expect a similar hierarchical organization of cells in non-visual sensory systems as well.

Inspired by Inspired by CalTech’s Question #9 for cognitive scientists: “In mammals, somatosensory, visual, auditory, and olfactory sensory systems all project to the cerebral cortex. To what extent does this imply some common form of neural processing? Justify your answer by referring to and comparing specific details of cortical anatomy and physiology.”

Reference

Kaas JH. 1989 The evolution of complex sensory systems in mammals. Pdf.

Elston GN, Tweedale R, Rosa MG. 1999 Cortical integration in the visual system of the macaque monkey: large-scale morphological differences in the pyramidal neurons in the occipital, parietal and temporal lobes. Proc Biol Sci. 1999 July 7; 266(1426): 1367–1374. PubMed link here.

Question #8: Explaining the role of gamma oscillations

Lakatos et al have noted that “the role of neuronal oscillations in brain operations has been debated since the discovery of the electroencephalogram.” So this is no small cookie. But the current consensus seems to be that gamma waves with frequencies between 25 and 100 Hz are necessary for sensory processing.

Here’s the theory: Activated groups of neurons have the tendency to oscillate in coherent fashion, affecting the output of the given group and its sensitivity to input. Thus, two groups of neurons will be able to communicate much more effectively if their oscillations are phase-locked. Conversely, neural groups that don’t have this frequency oscillation synchrony will have a much reduced capability to communicate. So, incoming sensory info from the currently attended stimulus will have an advantage during recieving in upstream cortical regions. Also, a “broadcasting center” in the thalamus could distribute the selected rhythm to appropriate cortical regions and prime them to preferentially recieve certain frequencies of sensory input.

The theory implies that the spike-traveling time from sending to recieiving group must be timed correctly and have high fidelity. This is true of afferent thalamocortical axons. Spikes in thalamic neurons arrives in cortical cells in between 1-4 ms and peaks at 2 ms. Indeed, Salami et al (2003) found that the conduction velocity along axons on the thalamocortical tract is 10 times faster than other afferents in mice, due to its selective myelination. So this particular tract must be selected from development to be able to have a low latency interaction with the cortex.

The empirical work I’ve seen backs this theory up. For example, Dockstader et al (2010) used MRI and MEG on healthy participants while administering electrical current stimuli for 0.2 ms just above motor threshold. The participants attended either to the electrical stimuli or a distracting video. Selective attention to the electrical stimuli significantly increased activation in the early phase-locked contralateral primary somatosensory cortex gamma response, starting at 20 ms post-stimuli presentation. This shows that selective attention is likely mediated in neural circuits via gamma oscillations.

Note: Very high oscillations (100-500 Hz) are associated with epilepsy, and those between 250 and 500 Hz are often identified via EEG near the onset of focal seizures. The consensus on the role for lower Hz delta-range oscillations is much less distinct, but it may also be involved in early sensory selection. It is of course possible and likely that there are multiple roles for the gamma waves, and that sensory integration is only one of them.

Inspired by CalTech’s Question #8 for cognitive scientists: “What do you know about high-frequency oscillations (20-50 Hz) in invertebrates or vertebrates? What causes them?”

References

Salami M, et al. 2003 Change of conduction velocity by regional myelination yields constant latency irrespective of distance between thalamus and cortex. doi: 10.1073/pnas.0937380100 .

Fries P. 2005 A mechanism for cognitive dynamics: neuronal communication through neuronal coherence. doi:10.1016/j.tics.2005.08.011 .

Dockstader C, et al. 2010 Cortical dynamics of selective attention to somatosensory events. doi:10.1016/j.neuroimage.2009.09.035 .

Jirsch JD. 2006 High-frequency oscillations during human focal seizures. doi:10.1093/brain/awl085.

Question #7: Describing primary sensory pathways in humans

Visual: Path goes, photoreceptor cells in retina –> ganglion cells — (via optic nerve) –> optic chiasm (crossing of axons) –> lateral geniculate nucleus (mostly) + superior colliculi (can mediate saccades) + pretectal area (pupillary light reflex: if light shined in one eye, both pupils constrict). Then from lateral geniculate nucleus — (via optic radiations) –> V1 –> V2 –> parietal visual cortical areas (moving objects around in your head) + temporal visual areas (complex perception of patterns and forms). See here.

Auditory: Path starts in the hair cells of the cochlea, specifically the center axis called the spiral ganglion — (via auditory nerve) –> cochlear nucleus –> location of sound detection: (ventral cochlear nucleus –> superior olive of medulla) + quality of sound: (dorsal cochlear nucleus: frequency differences) — (via lateral lemniscus fiber tract) –> inferior colliculus –> auditory nucleus of the sensory thalamus (aka medial geniculate nucleus) –> primary auditory cortex of temporal lobes. See here.

Olfactory: Path is from olfactory receptors of roof of the nasal cavity — (via axons of receptors projecting as first cranial nerve) –> olfactory bulb — (via axons of mitral cells projecting as olfactory tract) –> olfactory cortex — (via mediodorsal nucleus of the thalamus) –> insular cortex (taste integrates with smell to produce flavor) + orbitofrontal cortex (odor-taste association learning at single neuron level). Notice that olfaction is the one sensation that gives info directly to the cortex from receptors without first passing through the thalamus. See here.

However, there are many multisensory connections in the cerebral cortex, superior colliculus, and thalamus, such that our sensations can feedback and “correct” one another well before conscious awareness. For example, the premotor cortex achieves multisensory integration by converging visual, auditory, and somatosensory inputs, and has large amounts of overlap with axons of various sensory systems sending projections to other cortical regions. These integration mechanisms vary by behavioral task as well type of sensory input and context must be taken into account.

Inspired by CalTech’s Question #7 for cognitive scientists: “Describe the main pathways between sensory receptors and cortex (including intra-cortical circuits) for mammalian vision, hearing and olfaction.”

References

Critchley HD, Rolls ET. 1996 Olfactory neuronal responses in the primate orbitofrontal cortex: analysis in an olfactory discrimination task. Abstract.

Cappe C, et al. 2009 Multisensory anatomical pathways. doi:10.1016/j.heares.2009.04.017.

The Washington University School of Medicine Neuroscience Tutorial, here.

Question #6: Amplification of auditory and olfactory sensation

Auditory: Mechanical basilar membrane displacement in the cochlea opens mechanoelectrical transduction channels in hair cells, allowing an influx of potassium (K+) mediated current. This leads to the downstream neural pathways for hearing. Amplification of this signal across the entire hearing range occurs as a result of one specific subset of these hair cells, the outer hair cells. In response to the transmembrane receptor potential, outer hair cells actively oscillate at the frequency of the incoming sound, in a process called electromotility. It is believed that these voltage-dependent cell vibrations are dependent upon a protein called prestin that is expressed highly in the lateral plasma membrane of the outer hair cells. This is supported based on Liberman et al’s homozygous gene disruption paradigm in mice that led to a greater than 100 fold loss of auditory sensitivity. Its mechanism seems to mediate the electroneutral exchange of two anions across the plasma membrane, chlorine (Cl -) and carbonate (CO2 -3), which causes a direct voltage to displacement conversion. The unique morphology of the outer hair cells allows them  to operate at frequencies higher than 50  kHz if properly stimulated. This amplification via outer hair cells only occurs in mammals and allows for improved frequency selectivity, which is necessary for the complexities of human speech!

Olfactory: The mucous epithelial layer of the nose contains olfactory receptor neurons, each of which has 8-20 whip-like cilia that are each 30-200 microns long, and are where molecular reception of the odor commences. The incoming odor stimulates the transmembrane protein andenylate cyclase which catalyzes the conversion of ATP to 3′,5′-cyclic AMP (cAMP). cAMP is directly connected to an ion channel, allowing an influx of cations (primarily calcium) that depolarize the cell. The influx of calcium leads to an opening of calcium-dependent chloride channels. The chloride conductance is the amplification step and accounts for 80-90% of the odorant-induced depolarizing current, in sigmoidal fashion. Lowe and Gold (1993) had a classic study showing the effects of this. Using a newt olfactory receptor cell, they used flash photolysis of caged cAMP to simulate an upstream odor reception and analyzed the chloride influx. In addition to varying the intensity of the light source to uncage varying amounts of cAMP, and measuring the chloride amplitude, the researchers also used a condition with 5 millimoles of a chloride channel blocker, SITS. Here’s their figure 3D. The normal condition shows a sigmoidal amplification curve (black circles), and the SITS condition of open circles has no such amplification:

Very cool!

Inspired by CalTech’s Question #6 for cognitive scientists: “Every sensory system relies on receptor cells that transduce a stimulus into an electrical signal. This clearly requires some significant amplification. Describe two different sensory receptor cells, with attention to the location(s) and the mechanism(s) of this amplification.”

References

Liberman MC, et al. 2002 Prestin is required for electromotility of the outer hair cell and for the cochlear amplifier. doi:10.1038/nature01059.

Mistrik P, et al. 2009 Three-dimensional current flow in a large-scale model of the cochlea and the mechanism of amplification of sound. doi: 10.1098/​rsif.2008.0201.

Stephan AB, et al. 2009 ANO2 is the cilial calcium-activated chloride channel that may mediate olfactory amplification. doi: 10.1073/pnas.0903304106.

Lowe G and Gold GH.  1993 Nonlinear amplification by calcium-dependent chloride channels in olfactory receptor cells. doi:10.1038/366283a0

Three problems with quantum dots for in vivo imaging

1) They’re usually too big (~30 nm) and thus may not be able to fit in very small morphological regions such as the synaptic cleft, which are usually about 20 nm wide. One possible way to deal with this is to make the QD smaller! This may be possible to do if researchers switch from CdSe to InP as the crystal core. It is a common mistake to assume that QD’s are smaller than conventional fluorescent dyes–they are in fact 10 to 20 times larger than fluorescein isothiocyanate fluorophores.

2) Since QD’s blink, it can be difficult to track multiple molecules bound to them in a given region as they might cross over undetected. Thus sophisticated algorithms must distinguish between various QD’s. However, it is possible for each QD to emit a different fluorescent wavelength if their sizes are varied slightly, due to variations in the effects of quantum confinement. Note also that the material of the outer surface plays a large role in determining the fluorescence emitted by the same crystal core, which could possibly also be exploited to yield more variation in QD emissions.

3) The QD’s often affect the ligand characteristics of the bound antibody. If one is hoping to detect the function of some protein in typical cellular processes it will be difficult to do so if the QD-bound molecule has different activity–for example, less preferential binding to another protein–than non-QD-bound endogenous molecules.  The possibility of this needs to be carefully quantified before an experimental design assumes that it is not the case.

Despite these problems, there are some ways that QD’s could be used in vivo to detect action potentials. If they were bound to synaptically-important proteins in multiple adjacent neurons, it might be possible to track the spike trains of each neuron and how they interact after exposure to various chemical manipulations. One of the most important benefits of QD’s to this type of design is their high photostability and long lifetime in the aqueous solution of cells.

References

Alcor D, et al. 2009 Single-particle tracking methods for the study of membrane receptors dynamics. doi: 10.1111/j.1460-9568.2009.06927.

Cao YW, et al. 1999 Synthesis and Characterization of InAs/InP and InAs/CdSe Core/Shell Nanocrystals. Abstract.

Pathak, et al. 2009 Quantum Dot Labeling and Imaging of Glial Fibrillary Acidic Protein Intermediate Filaments and Gliosis in the Rat Neural Retina and Dissociated Astrocytes. doi:10.1166/jnn.2009.GR08

Single neuron resolution following post-mortem dissection

The NYT on the project to dissect and analyze H.M.’s brain:

“We’re going to get the kind of resolution, all the way down to the level of single cells, that we have not had widely available before,” said Donna Simmons… The thin whole-brain slicing “will allow much better opportunities to study the connection between cells, the circuits themselves, which we have so much more to learn about.”… “Ideally, anyone with the technology could do the same with their own specimens.”

Ho hum. What happened to the apparent controversy over the feasibility of this a few months ago? It seems that we will indeed soon have neuron by neuron maps. The question is, at which level  do we achieve scale separation? Surely we will need to go lower than the level of the neuron to capture memories that are encoded via the strength of NMDA receptors. But how much further down?

Conjugating antibodies with quantum dots

Quantum (q) dots have a number of advantages over conventional organic fluorophores, and their application may prove fruitful to constructing input-output models for different neuron types. The dots can be as small as 5-8 nanometers, although their hydrophobic region has been reported to be at least 16 nm. Their small size allows researchers to combine them to individual protein molecules and thus visualize intracellular processes.

Pathak et al (2007) considered the actual binding potential of 605 nm q dots to the most common human antibody, immunoglobulin G, which has two light chains and two heavy chains linked by disulfide bonds–see a picture of the molecule here. It’s important to validate that the quantum dots not only bind to the antibody but that they bind in such a way that the antibody can still bind to its typical ligand and have normal biological function. Since the light chain is the part of the antibody that binds to other proteins, it needs to be oriented outward, and moreover the antibody molecule itself should not be cleaved by the q dot binding.

Of their two techniques, direct conjugation and biotin-streptavidin based conjugation, the latter yielded significantly more q dots bound correctly per antibody molecule. In this latter technique, the researchers coated their q dot with the protein streptavidin and added biotin groups to the immunoglobins, likely at some of the antibody’s primary amine groups (see biotinylation). The noncovalent interaction between streptavidin and biotin has one of the lowest known dissociation constants, ~ 10^-15 mol/L, and thus it leads to a strong interaction between the q dot and the antibody.

Ultimately, the highest ratio they were able to produce was 1.3 +/- 0.35 of antibodies bound per q dot with a 2:1 antibody to q dot molar ratio. Since not all of these bound antibodies will be functional, in part because some will have the light chain of the immoglobulin molecule blocked, that number represents an upper bound on functional antibodies. The researchers note that since there is currently no way to control the binding orientation of immoglobulin molecules, Brownian motion means there is no guaranteed way to ensure functionally bound antibodies. More on q dots and neuro to come–this will be an important tech in the years to come, no doubt.

Reference

Pathak S, et al. 2007 Characterization of the Functional Binding Properties of Antibody Conjugated Quantum Dots. doi:10.1021/nl062706i, pdf.

Three techniques to map neural circuitry

Wired has photos and brief explanations of them here. The labs they discuss are Lichtman’s Harvard lab, which uses its automatic tape-collecting lathe ultramicrotome (ATLUM), Winfried Denk’s Heidelberg lab, which first sliced the brain to 25 nm and uses electron microscopy on rabbit neurons, and Van Weeden’s Harvard lab that uses diffusion tensor imaging. Many of these researchers look to the semiconductor industry for motivation. The goal is to figure out a few of the best techniques and then automate them.

mRNA localization in neurons

Neuronal processes (axons, dendrites) are highly autonomous from the soma. This allows for synaptic plasticity (i.e., growth or shut down of receptors), alterations in spine morphology, and specific types of navigation towards extracellular guidance cues. Holt and Bullock implicate three major examples of this capability in neurons:

1) Synapse Plasticity. mRNA localization can affect the neuron’s ability to respond to activations with structural changes. For example, consider transcription of the activity-regulated cytoskeletal associated (Arc) gene. In activated hippocampal neurons, Arc mRNA is sent to dendrites that contain recently activated synapses with NMDA receptors and is locally translated into protein, where it probably modulates spine morphogenesis (i.e., causes shape changes in dendrites). It has a critical role in long term but not short term memory, as suggested by selective knock-out mice studies, where researchers replaced the  3′ untranslated region of the gene with a nonlocalizing transcript sequence. There are other examples in which mRNA localization can be necessary for synaptogenesis, the most important form of synapse plasticity. For example, localizing the neuropeptide-encoding sensorin mRNA into synapses is probably necessary for synapse formation in mechanosensory neurons in Aplysia and Helix pomatia.

2) Directionally Responsive Axon Protrusion. In neurodevelopment, changes in growth and directional steering of axons is dependent upon extracellular cues. For example, in growth cones beta-actin mRNA is concentrated near regions of attractive stimulus gradients, indicative of how the cell can transduce extracellular gradients into intracellular asymmetry. Inhibiting local beta-actin mRNA translation blocks attractive cues, but not repulsive ones, turning towards the favored extracellular stimuli. Presumably there are  similar mechanisms that target other aspects of axon guiding during neurodevelopment to weave the intricate neuronal networks that underly everything we think, do, and say.

3) Spatially Dependent Gene Expression. mRNA’s translated in particular regions of the neuron may be modified at some amino acid residues selectively depending upon which part of the cell they are in. When the protein travels back to the nucleus following translation, its pattern of phosphorylation can then signal which part of the cell the mRNA was translated in, which can change patterns of gene expression following the same transcription factor entering the nucleus. For example, mRNA encoding the transcription factor cAMP response element–binding protein (CREB), which promotes the survival of certain neurons, can be translated locally in axons in response to neurotrophic nerve growth factor. CREB is localized to the distal axons of neurons (as indicated by Boyden chamber axon isolation and fluorescent in situ hybridization), its mRNA is selectively translated in response to local innervations of nerve growth factor, and the phosphorylation patterns of CREB at sites other than serine-133 will affect its transcriptional effects. Thus the cell can tell whether the pCREB in the nucleus came from distal axons or from the soma, and alter gene expression accordingly.

References

Casadio A, et al. 2003 Distribution of sensorin immunoreactivity in the central nervous system of Helix pomatia: Functional aspects. 10.1002/jnr.1084.

Li L, et al. 2005 The neuroplasticity-associated arc gene is a direct transcriptional target of early growth response (egr) transcription factors. doi:10.1128/MCB.25.23.

Leung KL, et al. 2006 Asymmetrical bold beta-actin mRNA translation in growth cones mediates attractive turning to netrin-1. doi:10.1038/nn1775.

Cow LJ, et al. 2008 Intra-axonal translation and retrograde trafficking of CREB promotes neuronal survival. doi:10.1038/ncb1677.

Holt CE, Bullock SL. 2009 Subcellular mRNA localization in animal cells and why it matters. doi:10.1126/science.1176488

Irregular Blood Flow and Iron Deposition in multiple sclerosis

As individuals age, there is an increased amount of iron deposition in the brain, due in part to dysregulation of the proteins that regulate iron influx and sensing of intercellular iron stores. As a redox element, it can catalytically generate reactive oxygen species, leading to higher susceptibility to oxidative stress, and contributes to neurodegeneration.

Today an article by Loz Blain reports that iron may be implicated in possibel treatments for multiple sclerosis as well. In one study:

Dr. Paolo Zamboni took 65 patients with relapsing-remitting MS, performed a simple operation to unblock restricted bloodflow out of the brain – and two years after the surgery, 73% of the patients had no symptoms. Dr. Zamboni’s thinking could turn the current understanding of MS on its head, and offer many sufferers a complete cure.

Singh and Zamboni’s article (pdf) in the Journal of Cerebral Blood Flow and Metabolism indicates why this might be. Blood flow out of the brain often is blocked in MS patients, causing a high rate of cerebral venous reflux. In the main extracranial cervical vein the rate of venous reflux flow is 70% as compared to 0% in control populations. It is possible that this leads to extra iron deposition in the brain and is responsible for the autoimmune activation that leads to demyelination and scarring.

The academic article is much more nuanced in its claims that the popular article, as is to be expected.

Reference

Singh AV, Zamboni P. 2009 Anomalous venous blood flow and iron deposition in multiple sclerosis. Journal of Cerebral Blood Flow and Metabolism 00:1–12.