Inhibition has a powerful role shaping the network dynamics of the cortex, but most studies of inhibitory circuitry are done in brain slice or anesthetized animals. In Membrane potential dynamics of GABAergic neurons in barrel cortex of behaving mice, Gentet et al use two-photon imaging to guide dual, whole-cell patch clamp of inhibitory and excitatory neurons in the mouse barrel cortex. These mice are head fixed, but awake and naturally whisking. The authors can then see how the membrane dynamics of both subthreshold and suprathreshold voltages are correlated across pairs of cells. Differences between the correlations for excitatory and inhibitory neurons shed light on how cortical circuitry processes sensory information in natural brain states. For Journal Club #5, Mac Hooks, a post-doc here at Janelia working with Gordon Shepard and Karel Svoboda, walks us through these results.
Many organisms regulate gene transcription via sunlight. In plants, phototaxis, flowering and germination all are light dependent processes. Circadian rhythms in many species is entrained by light. Light-activated transcription is achieved through a variety of mechanisms. Some of these mechanisms may be usable as a powerful tool to control gene expression in selected cells with high spatial and temporal resolution. When paired with other optical tools, such as genetically-encoded calcium indicators or channelrhodopsins, this technique would give unprecedented specificity in recording and manipulating brain activity. In this journal club, I review two major systems for photoactivateable transcription and their prospects for application in mammalian systems.
SI is one of the best characterized regions of cortex. Far less understood is the structure and function of secondary somatosensory cortex (SII), but it likely plays an essential role in rodent sensory perception. For Journal Club #3, I review what is know of the location, structure, connectivity, physiology and function of SII.
A few months ago I threw together a short presentation on the history of calcium imaging for a journal club here at Janelia. It is incomplete. It lacks notes. It focuses much attention on early genetically-encoded indicators. However, calcium imaging is so intertwined with the work of Roger Tsien, my Ph.D. thesis advisor, and since he just won the Nobel Prize, I thought it might be of some interest to the audience of Brain Windows. It does provide a little bit of background for some of the more recent developments chronicled on this site.
How do neuronal populations in the auditory cortex represent acoustic stimuli? Although sound-evoked neural responses in the anesthetized auditory cortex are mainly transient, recent experiments in the unanesthetized preparation have emphasized subpopulations with other response properties. To quantify the relative contributions of these different subpopulations in the awake preparation, we have estimated the representation of sounds across the neuronal population using a representative ensemble of stimuli. We used cell-attached recording with a glass electrode, a method for which single-unit isolation does not depend on neuronal activity, to quantify the fraction of neurons engaged by acoustic stimuli (tones, frequency modulated sweeps, white-noise bursts, and natural stimuli) in the primary auditory cortex of awake head-fixed rats. We find that the population response is sparse, with stimuli typically eliciting high firing rates (>20 spikes/second) in less than 5% of neurons at any instant. Some neurons had very low spontaneous firing rates (<0.01 spikes/second). At the other extreme, some neurons had driven rates in excess of 50 spikes/second. Interestingly, the overall population response was well described by a lognormal distribution, rather than the exponential distribution that is often reported. Our results represent, to our knowledge, the first quantitative evidence for sparse representations of sounds in the unanesthetized auditory cortex. Our results are compatible with a model in which most neurons are silent much of the time, and in which representations are composed of small dynamic subsets of highly active neurons.