Research Group of Michael Brecht


Our research group is active in the field of cellular and systems neuroscience with the following major areas:

- Animal play

- Active touch and object recognition

- Social and sexual touch

- Cortical organization

- Cellular basis of sensations and movement generation

- Hippocampal and parahippocampal activity linked to spatial navigation

- Elephant behavior and neurobiology.

We work on the meaning of single neuron activity, cellular mechanisms of complex somatosensory-mediated behaviors, spatial representations and social representations in forebrain. Our contributions can be grouped in three areas of research:

Microcircuit analysis of the cortical column in barrel cortex

A series of in vivo whole-cell recording studies provided a high-resolution analysis of somatosensory circuits based on postsynaptic responses in identified cells (Brecht & Sakmann, 2002; Brecht et al., 2003). The richness and precision of this analysis has altered the field and suggested that neural representations in the whisker system are much sparser than previously thought. Together with Winfried Denk, Michael Brecht combined in vivo whole-cell recordings with two-photon microscopy and was thus able to target recordings in the intact brain to fluorescence labeled neurons (Margrie et al., 2003). This technology – which is now extremely widely used – allows to tailor recordings to genetically labelled/identified neurons, a major advance over previous in vivo recording techniques, which sampled neurons blindly in the mammalian brain.

Studies on single-cell stimulation

These studies in rodent sensorimotor cortices radically changed our perspective on the role single cortical neurons in sensation and movement. As a result of these studies we now know that single neuron activity can significantly impact on the animal’s behavior and can evoke complex sequences of whisker movements (Brecht et al., 2004). We demonstrated that the stimulation of single neurons in somatosensory cortex can be reported by animals (Houweling et al., 2008). The single cell stimulation effects were dependent on cell type and the experiments suggest that it may become possible to directly measure the perceptual relevance of different neurons and spike patterns. Indeed, the latest results from the Brecht lab indicated that the fine timing of single cell spikes – in particular the spike train irregularity – determine the detectability of single cell activity (Doron et al., 2014).


Development of novel methods for intracellular and juxtacellular recordings in behaving animals

Intracellular recordings are the key method for analyzing the cellular mechanisms underlying neural activity. So far intracellular recordings were restricted to brain slices, anesthetized animals or at least head-fixed animals, because mechanical disturbances disrupt these very sensitive measurements and the previously available recording instruments were too large for application in behaving animals. Our group succeeded in overcoming these technical difficulties by introducing novel miniaturization and stabilization techniques. As a result, it is now possible to obtain qualitatively excellent and highly stable recordings in behaving animals (Lee et al., 2006). The significance of such intracellular recordings from behaving animals for brain research can hardly be underestimated, as it has become clear that data from brain slice preparations cannot fully elucidate information processing in the awake brain. The application of this technique has led to a range of discoveries about the cellular mechanisms of spatial memory formation. Specifically, we showed that about a third of the spikes in the hippocampal CA1 region of awake behaving rats is generated by so-called spikelets (Epsztein et al., 2010). We further simplified and improved this recording technique and adapted it to juxtacellular recordings, which were shown very efficiently to identify neurons in behaving animals (Burgalossi et al., 2011, Tang et al., 2014). More than that this approach identified a candidate microcircuit for the grid-cell representation (Ray et al., 2014; Tang et al., 2014).

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