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Archive for the ‘Neurotransmitters’ Category

Wyart et al expressed the light-gated ion channel LiGluR as well as the UAS promoter in some zebrafish and crossed these with zebrafish containing the GAL4 transcription factor in various classes of ventral spinal neurons. When the progeny was photo-stimulated in the caudal spinal cord, 94% displayed tail oscillations. The effects were localized down to Kolmer-Agduhr cells and since its action potentials were blocked by the GABA-A antagonist bicuculline, the researchers were able to identify the mechanism as GABAergic, of note because GABA is typically inhibitory. This is a good example of how a given behavior can be elicited in a non-intuitive way by a specific subset of neurons in a particular region of the nervous system.

Reference

Wyart C, et al. Optogenetic dissection of a behavioural module in the vertebrate spinal cord. Nature 461:407-410. doi:10.1038/nature08323.

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In 1999 Volkow et al injected carbon-11 radioisotoped raclopride into 23 males, an antagonist on dopamine family 2 (D2) receptors. After the radiotracer had seeped through the blood brain barrier, the researchers scanned them using PET to find time activity curves and thus quantify the amount of D2 receptors. On a later date they gave the same subjects a 0.5 mg/kg dose of methylphenidate (Ritalin), and quantified their responses to the drug. Subjects with lower levels of D2 receptors had significantly higher self-ratings of happiness, increases in mood, and lower self-ratings of annoyance and distrust.

Cocaine abusers have also found to have lower levels of D2 receptors than the rest of the population. It has been suggested that either users compensate for decreased activation of reward circuits with the drugs, or that low D2 users could on average enjoy the experience on the first time more, which is highly correlated with future use. Regardless of the specific mechanism, this is another data point suggesting that there is an optimal range of D2 receptor stimulation, where too little may be insufficient but too much may be aversive.

Reference

Volkow ND et al. 1999 Prediction of reinforcing responses to psychostimulants in humans by brain dopamine D2 receptor levels. Am J Psychiatry 156:1440-1443. Abstract.

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Maze learning in C. elegans

Qin and Wheeler (2006) show that C. elegans can learn to travel through a T maze, and that their latency to reach the bacterial reward diminishes as the trial number increases. These nematodes only have 302 neurons, so any example of them learning associatively always fascinates me. They also have data showing that cat-2 dopamine deficient mutants consistently display less exploratory behavior than wildtype worms, which makes sense because dopaminergic neurons are often linked to reward-seeking behavior. Here is their description, a short video (you get to see a worm in “traveling mode”) and a link to the actual paper.

Reference

Qin J, Wheeler AR. 2006 Maze exploration and learning in C. elegans. DOI: 10.1039/b613414a.

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In the mammalian hippocampus, parvalbulim (a calcium binding albumin protein) expressing interneurons can be classified into a number of groups. Basket, axo-axonic, and oriens–lacunosum-moleculare (O-LM) are the main three groups, and they each innervate different regions of pyramidal cells in CA1. These are also each GABA-releasing interneurons, which is the main inhibitory neurotransmitter in the brain.

Klausberger et al (2002) analyzed the firing patterns of each of these cells in rat brains in vivo with respect to network activity, such as theta oscillations (4–8 Hz) involved in REM sleep, and sharp-wave-associated ripples (120–200 Hz) in slow wave sleep. Although the researchers adminstered urethane–ketamine anaesthesia on the rats, theta and high-frequency ripple waves stil occured, at mean frequencies of 123 +/- 11 Hz and 4.2 +/- 0.3 Hz, respectively.

They found a significant difference in the discharge frequency of these interneurons during theta oscillations and non-oscillation periods. In sharp wave oscillations, both pyramidal cells and basket cells fire at the moment of maximum amplitude of the episode, which produces an awe-inspiring cross-correlogram. The data strongly suggests that the different types of GABA interneurons have evolved to regulate the polarization of pyramidal cells depending on the brain’s current condition.

Glickfield et al (2008) recently tested hippocampal slices of 4-6 week old rats with patch pipets filled with 3 M NaCl in order to determine the effect of individual interneurons on their postsynaptic targets. The action potential of a single basket cell produced a local unitary field potential (uField) in the stratum pyramidale. When the postsynaptic region was treated with the GABA antagonist gabazine the the uField was stopped, indicating that potential was due to action in the synapse.

The positive uField in the stratum pyramidale necessitates a locally generated outward synaptic current, which means that the pyramidal cells must have experienced a hyperpolarization of their cell bodies. They additionally found that the hyperpolarizing effect of the GABA interneurons is not dependent on its location along the hippocampal axis. The GABA microcurcuits effect on pyramidal cells is an integral part of general network activity in the hippocampus at large, and a bottom-up approach is a useful tool for analyzing it.

Reference

Klausberger T, Magill PJ, Marton LF, Roberts JDB, Cobden PM, Buzsaki G, Somoavi P. 2002 Brain-state- and cell-type-specific firing of hippocampal interneurons in vivo. Nature 421:844-848.

Glickfeld LL, Roberts JD, Somogyi P, Scanziani M. 2008 Interneurons hyperpolarize pyramidal cells along their entire somatodendritic axis. Nature Neuroscience 12:21-23.

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Most mammals do not form long-term pair bonding relationships, but two notable exceptions are prarie voles and humans. The explanation behind these relationships is that the animals have co-opted maternal love for the feelings they have towards their partner. This would explain the male fascination with breasts, which have been decoupled from sex but where stimulation still provides huge releases of the neurotransmitter oxytocin.

But perhaps more interesting is the possibility for genetic control of the varied behavior in pair bonding. Prarie voles show sexual and social fidelity while montane and meadow voles do not; prarie voles contain a 428-base pair sequence in the 5′ flanking region of the avpr1a gene while montane and meadow voles do not. When this gene (including the 428 bp sequence) is encoded transgenically in mice, which are not normally monogomous, they exhibit more social behavior similar to prarie voles. Finally, there is some intraspecific variation in the level of “monogaminity” in prarie voles depending upon polymorphisms in this 5′ flanking region of the avpr1a gene.

It is this last fact that probably tickled the fancy of Walum et al, because they tested to see whether variations in this gene affected pair bonding in humans as well. They designed their own measure behavior called the Pair Bonding Scale which depending on questions of time spent together (”How often are you and your partner involved in common interests outside the family?”), closeness (“I don’t like when other people come too close to me”), and the mushy stuff (“How often do you kiss your mate?”). They then analyzed twins and their offspring from Sweden to reduce variance in unexamined genes.

They tested for the effect of polymorphism in three different repetitive sequences in the human AVPR1A gene in both men and women: the (GT)25 dinucleotide repeat, a complex (CT)4-TT-(CT)8-(GT)24 repeat (RS3), and a (GATA)14 tetranucleotide repeat (RS1). The significant result that they found (it was P<.001 even after correcting for the other 11 hypotheses) was a correlation between having carrying the 334 RS3 allele and having a lower score on the Pair Bonding Scale. The effect sizes were d=0.27 between men who did not carry the 334 allele and 334 heterozygotes, and d=0.38 between men who did not carry it and those who carried 334 homozygotes, meaning that the effect was dose-dependent. The researchers confirmed the effect with further tests of marital instability. A few questions:

1) It is interesting that in this model it is the characteristics of the male that determine the quality of the relationship. Does this fit with our cultural expectations?

2) The 334 allele is associated with increased activity in the amygdala, which is involved in emotionally charged memories. Perhaps those expressing the allele are more likely to remember instances of fights? Or, perhaps they are more likely to remember past instances of infidelity, project them onto the future, and act overprotectively?

3) Should we conduct genetic tests of our partners to determine potential marital stability?

Reference

Young LF. 2009 Being human: Love: Neuroscience reveals all. Nature 457: 148. doi:10.1038/457148a.

Walum H, Westerg L, Henningsson S, Neiderhiser JM, Reiis D, Igl W, Ganiban JM, Spotts EL, Pedersen NL, Eriksson E, Lichtenstein P. 2008 Genetic variation in the vasopressin receptor 1a gene (AVPR1A) associates with pair-bonding behavior in humans. PNAS 37:14153-14156. doi:

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There is a wealth of literature describing how dopamine is used in reinforcement learning as a proxy of the value for a particular stimulus in conditioning tasks. These cues are context-dependent, and the plasticity is clearly adaptive. For example, attacking a lone animal may yield a food reward, but if that animal is in a pack of other animals who will protect each other, it may not be such a good idea. The lateral prefrontal cortex (LPFC) is believed to be involved with abstracting sensory information into behavioral cues, and involved especially in this context-dependent decision making.

One of the requirements for context-dependent decision making is that animals can make responses to stimuli that have not yet been rewarded directly, but have indirect associations to other stimuli which have been rewarded directly. Animals have shown to be able to exhibit transitive inference (if A->B and B->C, then A->C), causal reasoning, and categorical inference, and none of these necessitate conscious reasoning. But how do LPFC neurons accomplish these tasks? There are two suggestions: temporal-difference learning, where firing rates from upstream neurons would integrate depending on the context, and model-based learning, where a previously learned structure would be applied in a novel format.

In order to differentiate between the two hypotheses, Pan et al. designed a asymetric reward choice experiment for 3 monkeys, and recorded the action potentials for single neurons extracellularly after inserting electrodes into the cortex. The monkeys chose between the visual stimuli by merely gazing at the correct stimuli for a duration that varied between 800-1200 ms, and their eye movements were recorded using a machine with a 500 Hz sample rate. Here is their diagram of their choice experiment (figure 1C from Pan et al., 2008):

There were two blocks in this design: reward instruction trials (RITs), where the monkeys were trained to receive a higher reward for one response and a smaller reward for the other, and sequential paired-association trials (SPATs), where the monkeys were forced to make a series of responses before they recieved a reward. On the SPAT trials, the monkeys were forced to make inference about which choice would eventually lead to a higher reward (4 vs. 1). The monkeys learned both the RIT and the SPAT blocks well, and all 3 showed a higher rate of correct responses for the large reward sequence.

The researchers then analyzed the brain activation data they gathered, and grouped each neuron into either “reward”-type or “stimulus reward”-type depending on how each neurons responded in connection to its neighbors. For the “reward”-type cells, the response pattern was the same towards both types of stimuli (large and small). However, for the “stimulus reward”-type neurons, one subgroup was found to predict a large reward for one category of stimuli and another subgroup was found to predict a small reward for the other category of stimuli. The authors hypothesize that through these different neuron responsen patterns, the LPFC is able to represent category-based reward information, which could be used for category-based inference. The leap from this cellular category-based inference to context-dependent decision making is not too great, and therefore this work is quite fascinating.

Reference

Pan X, Sawa K, Tsuda I, Tsukada M, Sakagami M 2008 Reward prediction based on stimulus categorization in primate lateral prefrontal cortex. Nature Neuroscience 11(6): 703-712. doi:10.1038/nn.2128.

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