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Wiring the Brain 2009—Kids in a Candy Store: New Methods Dazzle Researchers

Over the next weeks, we will be bringing you several reports from the Wiring the Brain: From Genetic to Neuronal Networks, a conference held 21-24 April 2009, in Adare, County Limerick, Ireland. We are very grateful to Aiden Corvin from the organizing committee and to reporter Victoria Heimer-Torres, a graduate student in Paul Young's laboratory at University College Cork, Ireland.


27 July 2009. Wiring the Brain covered neuronal networks across a variety of disciplines, from genes to disease. Each session was concise, relevant, and built seamlessly on the previous. The April 24 session titled “Rewiring the Adult Nervous System” described new and powerful methods that study neural circuitry at different levels. In this summary, I have chosen to focus on two that may be especially useful for the Young laboratory’s study of synaptic connectivity and neuronal morphology.

In his lecture, "Optogenetics: Development and Application," Karl Deisseroth of Stanford University, Palo Alto, California, focused on recent developments in optogenetics, a method that allows optical control of defined cell types in freely behaving animals. [Editor's note: see also a commentary by G. Gonzalez-Burgos on the application of these methods to parvalbumin-positive neurons in cortex.] This is made possible by microbial opsins that can fire or inhibit action potentials with millisecond precision and without the addition of chemical cofactors. The first opsin applied to neurobiology was channelrhodopsin-2 (ChR2), which Deisseroth and colleagues showed becomes permeable to cations in response to blue light in living neurons and can be used to drive precisely timed action potentials (Boyden et al., 2005). Deisseroth and colleagues followed up their initial work by next showing that when delivered to the hippocampus in vivo using a lentivirus, the channel provides optical control of neuronal firing in intact tissue and behaving mammals. This system is tolerated well by neurons, requires no added chemical cofactors, and allows for rapid, temporally precise spiking. It has since proven useful in many experimental systems, including deep brain stimulation, Parkinson disease models, and depression models.

Deisseroth and colleagues next found that the light-activated chloride pump halorhodopsin can inhibit action potentials in response to yellow/green light. These results were reproduced in both intact tissue and in behaving animals. Refinements included introducing an endoplasmic reticulum export motif into the expression sequence to prevent protein aggregates due to elevated expression levels (Gradinaru et al., 2007). Since the ChR2 and halorhodopsin channels are excited at different wavelengths, they can be used simultaneously in the same cell. They also discovered and investigated the cation channel VchR1-VolvoxChR1, whose absorption spectrum is red-shifted relative to ChR2 sufficiently to allow combinatorial expression and modulation (Zhang et al., 2008).

Subsequently, Deisseroth's group has developed step function opsins (SFOs), which are engineered bi-stable optical switches that allow “light-off” to be uncoupled from “channel-off” (a modification at the C128 position of the channel extends the open state conformation). This effect is triggered with blue light pulses but can be terminated with green pulses. This system facilitates control through precisely synchronizing pulses, is complementary to ChR2, and provides a good technology for long time-scale studies (Berndt et al., 2009).

Finally, Deisseroth presented recent work on ”optoXRs,” a novel light-activated G protein-coupled receptor (GPCR) produced by fusing a rhodopsin channel (extracellular and transmembrane domains) and an adrenergic receptor (AR) (intracellular domain). Cell culture analysis confirmed that opto-α1AR chimeras recruited the inositol phosphate signaling pathway when stimulated, while opto-β2AR chimeras increased cAMP production. Functional studies of optoXR activation in mouse nucleus accumbens showed increased firing in opto-α1AR-expressing neurons upon optical stimulation, in contrast to slightly reduced firing in opto-β2AR-expressing accumbens neurons. Furthermore, behavioral studies showed that opto-α1AR stimulation of accumbens neurons robustly affects reward-related behavior, whereas opto-β2AR and ChR2 are less effective in driving preference (Airan et al., 2009).

In his talk, "Corticopoiesis in a Dish: Intrinsic Mechanism of Specification of Cortical Neurons from Pluripotent Stem Cells," Pierre Vanderhaeghen of the University of Brussels, Belgium, showed that mouse embryonic stem (ES) cells can be used to reproduce in vitro the major milestones of cortical development. Without the need for exogenous morphogens, ES cells in culture adopt a forebrain fate. These forebrain-like progenitors differentiate further into either cortical or ventral progenitors. In mice, these give rise to both the cortex and the basal ganglia.

In order to increase the population of presumptive cortical progenitors, Vanderhaeghen and colleagues used sonic hedgehog (Shh) to inhibit the development of ventral progenitors. Once efficient production of cortical progenitors was established, they went on to show that these cells generate a diversity of neuronal subtypes that resemble authentic cortical pyramidal neurons that are glutamatergic and synaptically active. Furthermore, when grafted into the cerebral cortex of neonatal mice, these neurons developed layer-specific axonal projections, as well as area-specific projections, corresponding mainly to the visual and limbic occipital cortex. The discovery of intrinsic corticogenesis demonstrates that a specific cortical area can differentiate without any influence from the brain (Gaspard et al., 2008).—Victoria Heimer-Torres.

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Related News: Commentary Brief: Optogenetics Links Interneurons and γ Oscillations

Comment by:  Guillermo Gonzalez-Burgos
Submitted 24 July 2009
Posted 24 July 2009

Blue light, yellow light, and the role of parvalbumin-positive neurons in the pathophysiology of schizophrenia
Parvalbumin (PV)-positive cells are a prominent subtype of GABA neuron that via perisomatic synapses may strongly inhibit pyramidal cell activity (however, see Szabadics et al., 2006). In schizophrenia, PV neurons have reduced levels of mRNA for PV and for GAD67, the 67 kilodalton form of the GABA-synthesizing enzyme glutamate decarboxylase. The functional consequences of the PV reduction in schizophrenia are poorly understood, but one possibility is that decreased PV partially compensates for a deficit in GABA release caused by the GAD67 reduction. PV is a slow Ca2+ buffer, and so decreasing PV in nerve terminals may facilitate GABA release during repetitive PV cell firing (for a review, see Gonzalez-Burgos and Lewis, 2008).

Why is PV cell-mediated inhibition significant to brain function? What deficits in cortical circuit function may be compensated for (at least partially) by a decrease of PV in schizophrenia? The answers to these questions depend on our knowledge of the functional role of PV neurons in cortical circuits. A leading hypothesis in this regard suggests that PV cells are essential for the production of synchronized oscillations in cortex, particularly in the γ frequency band (Bartos et al., 2007). γ oscillations are thought to be important for the transmission of information within and between neocortical areas (Salinas and Sejnowski, 2001). If so, then γ activity must be important for cognition, which is critically dependent on the flow of information across the neocortex (Singer, 1999; Fuster, 2004). Therefore, cognitive deficits (a key feature of schizophrenia) may result from the impairment of γ oscillations reported in the illness, which in turn could be a consequence of deficits in PV cell-mediated inhibition.

How is PV cell-mediated inhibition linked to the production of γ oscillations? PV neurons alone are not sufficient to produce network oscillations because, although PV cell membranes resonate at γ frequency (Pike et al., 2000), PV neurons actually lack intrinsic pacemaker activity. Therefore, whereas PV cells may be necessary to produce γ oscillations, synaptic interactions with other cell types in the cortical circuit must be necessary as well.

Studying the link between PV neuron activity and γ oscillations is complicated by the lack of tools available to selectively manipulate PV cell activity. Interestingly, two recent studies (Sohal et al., 2009; Cardin et al., 2009) employed novel “optogenetic” methods in mice, to further advance our understanding of how PV neurons are involved in γ oscillations.

Using viral vectors to drive cell type-specific expression of recombinant genes, Sohal and colleagues, as well as Cardin et al., produced expression of microbial opsins (which are light-sensitive ion channel proteins) selectively in specific populations of cortical neurons. Briefly described, modulation of neuronal activity using such optogenetic techniques works as follows: in cells expressing channelrhodopsin-2 (ChR2), illumination with blue light produces a depolarizing current that has excitatory effects (increases cell firing). On the other hand, cells expressing halorhodopsin (eNpHR) respond to yellow light with a hyperpolarizing current that has inhibitory effects (decreases cell firing). In this way, light of different wavelengths can be used to either inhibit or excite PV cells or pyramidal (PYR) neurons in the mouse cortex (in vivo or in vitro) in different experimental designs.

Sohal and colleagues first demonstrated that inhibiting the activity of eNpHR-expressing PV neurons with yellow light suppresses γ oscillations generated in vivo by rhythmic flashes of blue light applied to stimulate nearby ChR2-expressing PYR neurons. Furthermore, they show that non-rhythmic excitation of PYR cells produces non-rhythmic PYR cell firing. However, if the non-rhythmic PYR spikes are used to trigger feedback inhibition by PV neurons (driven by blue light flashes that stimulate ChR2-expressing PV cells), the addition of feedback inhibition induces a γ rhythm in PYR cell output. These results show that by means of recurrent interactions with pyramidal cells (consistent with the so-called PING models of γ rhythms; Whittington et al., 2000), PV cell activity is crucial for γ oscillations.

Finally, the experiments performed by Sohal et al. suggest that γ activity may selectively enhance the flow of information in cortical circuits. For example, their experiments demonstrate that the gain of the neuronal input-output relation (that is, the slope of the curve describing the transformation of inputs into outputs) is specifically enhanced when excitatory inputs onto a PYR cell are modulated rhythmically at γ frequency. Moreover, the amount of information flowing across synapses during interactions between PYR and PV neurons was estimated using concepts derived from information theory. The estimates from Sohal et al. showed that when network activity was driven by trains of blue flashes delivered at γ frequency, information transmission was markedly enhanced.

Using somewhat different genetic engineering approaches, Cardin and colleagues produced cell type-specific expression of ChR2 in PV cells or PYR neurons. Expression of ChR2 in PV cells of the mouse barrel (somatosensory) cortex allowed the activation of PV neurons with rhythmic flashes of light. Such manipulation produced rhythmic population activity (as detected recording local field potentials) more strongly when PV cells were driven at γ frequency compared with other frequencies. They report, in addition, some data showing that manipulation of PV cell activity has an impact on γ oscillations intrinsically generated by the cortical circuits, as opposed to γ rhythms induced by rhythmic stimuli applied by the investigators. For example, brief flashes of blue light applied to stimulate firing of ChR2-expressing PV neurons during spontaneous γ activity were able to reset the phase of the γ rhythm. Cardin et al. also demonstrate that activation of ChR2-expressing PV neurons can suppress the somatosensory response (to whisker stimulation) of nearby PYR cells. Then they go on to test an important functional role predicted for γ oscillations: that cells in a local network engaged in γ oscillations may respond differently to incoming inputs, depending on the timing of the incoming inputs relative to the phase of the γ cycle (Fries et al., 2007). In an elegant experiment, the investigators paired brief whisker stimulation with rhythmic flashes of blue light which, by stimulating ChR2-expressing PV cells, generate a γ rhythm locally. The crucial finding from this experiment is that the excitatory power of whisker stimulation was strongly dependent on the γ cycle phase at which whisker stimulation was delivered.

The data from these two recent studies briefly summarized above further consolidate the notion that PV-positive GABA neurons are key players in the mechanisms of γ synchrony in cortex. The data from these studies confirm that rhythmic PV neuron firing at γ frequency is sufficient to generate a γ rhythm in the population of postsynaptic neurons. This is not the same, however, as saying that PV neurons alone are sufficient to generate γ. Indeed, the data from these two studies point to the idea that PV neurons work in close interaction, via feedback loops, with nearby pyramidal cells. This makes sense, given that PV neurons are not intrinsic pacemakers. γ rhythms, therefore, seem to originate in complex network interactions that require the coordinated activity of pyramidal neurons, PV cells, and possibly other GABA neuron subtypes as well.

These two studies also highlight the similar importance of PV cell-dependent γ oscillations across different regions of cortex primarily involved in very different functions: Sohal and colleagues studied the role of PV neurons in frontal cortical areas, whereas Cardin et al. manipulated PV cell activity in the primary somatosensory cortex. The similarity of the findings regarding PV neuron function suggests that these neurons probably play a very similar role, at the microcircuit level, in these two very different cortical areas. Interestingly, deficits in GABA transmission, as assessed in postmortem brain studies, appear to be found in multiple areas of cortex simultaneously (Hashimoto et al., 2008). If this is indeed the case, then an impairment of γ oscillations may be present in most cortical areas. Thus, deficits in PV cell-dependent γ rhythms may explain the impairment of not only complex cognitive functions (for example, working memory), but also of more basic sensory processing which, as reviewed elsewhere (Javitt, 2009), is also impaired in schizophrenia. Finding a global deficit of GABA transmission and γ oscillations, as opposed to a deficit restricted to a single cortical area, increases the probability of success in developing pharmacological treatments.

A better understanding of the functional role of PV neurons in normal cortical circuits is crucial to developing better models that could explain how alterations of PV cells (and of other GABA neurons subtypes) originate in schizophrenia. As highlighted elsewhere (Lewis and Gonzalez-Burgos, 2008), any given alteration observed in schizophrenia may represent 1) cause, an upstream factor related to the disease pathogenesis; 2) consequence, a deleterious effect of a cause; 3) compensation, a response to either cause or consequence that helps restore homeostasis; or 4) confound, a product of factors frequently associated with, but not a part of, the disease process, or an artifact of the approach used to obtain the measure of interest. A major challenge for schizophrenia research is therefore determining to which of the four “C” categories each alteration belongs (Lewis and Gonzalez-Burgos, 2008). Certainly, information from basic neuroscience research studies such as those of Sohal et al. and Cardin et al. and many other past and future studies is extremely helpful in achieving this goal.

References:

Szabadics J, Varga C, Molnar G, Olah S, Barzo P, Tamas G: Excitatory effect of GABAergic axo-axonic cells in cortical microcircuits. Science 311:233-235, 2006. Abstract

Gonzalez-Burgos G, Lewis DA: GABA Neurons and the Mechanisms of Network Oscillations: Implications for Understanding Cortical Dysfunction in Schizophrenia. Schizophr Bull 34:944-961, 2008. Abstract

Bartos M, Vida I, Jonas P: Synaptic mechanisms of synchronized gamma oscillations in inhibitory interneuron networks. Nat Rev Neurosci 8:45-56, 2007.Abstract

Salinas E, Sejnowski TJ: Correlated neuronal activity and the flow of neural information. Nat Rev Neurosci 2:539-550, 2001. Abstract

Singer W: Neuronal synchrony: a versatile code for the definition of relations? Neuron 24:111-25, 1999. Abstract

Fuster JM: Upper processing stages of the perception-action cycle. Trends Cogn Sci 8:143-145, 2004. Abstract

Pike FG, Goddard RS, Suckling JM, Ganter P, Kasthuri N, Paulsen O: Distinct frequency preferences of different types of rat hippocampal neurones in response to oscillatory input currents. J Physiol 529 Pt 1:205-213, 2000. Abstract

Sohal VS, Zhang F, Yizhar O, Deisseroth K: Parvalbumin neurons and gamma rhythms enhance cortical circuit performance. Nature 2009 Jun 4;459(7247):698-702. Abstract

Cardin JA, Carlen M, Meletis K, Knoblich U, Zhang F, Deisseroth K, Tsai LH, Moore CI: Driving fast-spiking cells induces gamma rhythm and controls sensory responses. Nature 2009 Jun 4;459(7247):663-7. Abstract

Whittington MA, Traub RD, Kopell N, Ermentrout B, Buhl EH: Inhibition-based rhythms: experimental and mathematical observations on network dynamics. Int J Psychophysiol 38:315-336, 2000. Abstract

Fries P, Nikolic D, Singer W: The gamma cycle. Trends Neurosci 30:309-316, 2007. Abstract

Hashimoto T, Bazmi HH, Mirnics K, Wu Q, Sampson AR, Lewis DA: Conserved Regional Patterns of GABA-Related Transcript Expression in the Neocortex of Subjects With Schizophrenia. American Journal of Psychiatry 162:479-489, 2008. Abstract

Javitt DC: When doors of perception close: bottom-up models of disrupted cognition in schizophrenia. Annu Rev Clin Psychol 5:249-275, 2009. Abstract

Lewis DA, Gonzalez-Burgos G: Neuroplasticity of neocortical circuits in schizophrenia. Neuropsychopharmacology 33:141-165, 2008. Abstract

View all comments by Guillermo Gonzalez-Burgos

Related News: Studies Dissect Depression’s Circuitry

Comment by:  Anthony Grace, SRF Advisor (Disclosure)
Submitted 16 January 2013
Posted 17 January 2013
  I recommend the Primary Papers

The Nature articles on the role of dopamine and depression add greatly to our understanding of this transmitter system in affective disorders. While on the surface such studies may be viewed as being opposite in nature, both are highly consistent with results from our lab and others. We (Valenti et al., 2011) and others have shown that strong, acute stressors can activate dopamine neuron activity; however, when measured after long bouts of inescapable stress or following an incubation period, the activity of these neurons is markedly depressed (Moore et al., 2001; Valenti et al., 2012; Chang and Grace, 2013). These studies suggest that dopamine system activation during the stressor may be a precedent for dopamine system downregulation following termination of the stressor. Indeed, in the uncontrollable chronic stress model and in the learned helplessness model of depression (Chang and Grace, 2012; Belujon et al., 2012), we have found that dopamine neuron population activity depression correlates with behavioral indices of depressive-like behavior in rats.

The data from the Han and Deisseroth laboratories are actually highly consistent with these data. Thus, Han showed that phasic activation of dopamine neurons potentiates the effects of stress on subsequent depression (consistent with our studies showing dopamine activation during the initial stress events), whereas restoring dopamine activity during the depressed condition in Deisseroth's paper relieves the symptoms due to dopamine system downregulation.

Therefore, in our opinion, each phase of the depression process may have a dopamine component: an activation during the induction phase and an attenuation during symptom expression. Taken together, these findings provide unique insights into the process and expression of depression.

References:

Belujon, P., Dollish, H.D. and Grace, A.A. (2012) Ketamine restores activity of the dopamine system selectively in rats exhibiting learned helplessness in an animal model of depression. Program No. 774.02.2012. Neuroscience Meeting Planner, New Orleans, LA. Society for Neuroscience, 2012. Online.

Chang, C.H. and Grace, A.A. (2012) Chronic mild stress induces anxiety-like behavior and down-regulation of dopamine system activity in rats. Program No. 774.13.2012. Neuroscience Meeting Planner, New Orleans, LA. Society for Neuroscience, 2012. Online.

Chang, C.-H. and Grace, A.A. (2013) Amygdala beta noradrenergic receptors modulate delayed down-regulation of dopamine activity following restraint. Journal of Neuroscience (in press).

Moore, H., Rose, H.J.. and Grace, A.A. (2001) Chronic cold stress reduces the spontaneous activity of ventral tegmental dopamine neurons. Neuropsychopharmacology 24: 410-419. Abstract

Valenti, O., Lodge, D.J. and Grace, A.A. (2011) Aversive stimuli alter ventral tegmental area dopamine neuron activity via a common action in the ventral hippocampus. Journal of Neuroscience 31: 4280-4289. Abstract

Valenti, O., Gill, K.M. and Grace, A.A. (2012) Different stressors produce excitation or inhibition of mesolimbic dopamine neuron activity: Response alteration by stress pre-exposure. European Journal of Neuroscience 35: 1312-1321. Abstract

View all comments by Anthony Grace