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Alexander Borst aims at understanding the foundations of information processing at the level of small neural circuits, focusing on the visual course control system in Drosophila. Borst’s lab uses a comprehensive approach , combining electron microscopy-aided anatomical reconstructions of the circuit, physiological characterization by both imaging and whole cell patch recordings, genetic circuit manipulation in behaving flies, computational modeling and last but not least, engineering of fly-inspired robots that implement the theoretical principles and test their functionality.
Borst’s outstanding research has yielded a very precise and detailed description of the circuit at the single cell resolution as well as a thorough understanding of the computations it performs.
Several of his major scientific contributions include the discovery that the direction of visually perceived motion is calculated following the Reichardt Model (Single & Borst, Science 1998), the separation of visual information in the fly brain into ON- and OFF-channels, similar to bipolar cells in the retina of vertebrate eyes (Jösch, Schnell, Raghu, Reiff & Borst, Nature 2010) and the existence of four types of neurons in each channel, tuned to one of the four cardinal directions (right, left, up, down) that project into four separate neuronal layers based on their preferred direction (Maisak et al, Nature 2013).

https://www.neuro.mpg.de/borst

An instance of the E2-Lin(2) problem is a system of equations of the form "x_i x_j = b (mod 2)". Given such a system in which it is possible to satisfy all but an epsilon fraction of the equations, we would like to find an assignment that violates as few equations as possible. In this paper, we show that it is NP-hard to satisfy all but a C*epsilon fraction of the equations, for any C < 11/8 and 0 < epsilon

Alexander Borst aims at understanding the foundations of information processing at the level of small neural circuits, focusing on the visual course control system in Drosophila. Borst&#8217;s lab uses a comprehensive approach , combining electron microscopy-aided anatomical reconstructions of the circuit, physiological characterization by both imaging and whole cell patch recordings, genetic circuit manipulation in behaving flies, computational modeling and last but not least, engineering of fly-inspired robots that implement the theoretical principles and test their functionality.
Borst&#8217;s outstanding research has yielded a very precise and detailed description of the circuit at the single cell resolution as well as a thorough understanding of the computations it performs.
Several of his major scientific contributions include the discovery that the direction of visually perceived motion is calculated following the Reichardt Model (Single & Borst, Science 1998), the separation of visual information in the fly brain into ON- and OFF-channels, similar to bipolar cells in the retina of vertebrate eyes (J&ouml;sch, Schnell, Raghu, Reiff & Borst, Nature 2010) and the existence of four types of neurons in each channel, tuned to one of the four cardinal directions (right, left, up, down) that project into four separate neuronal layers based on their preferred direction (Maisak et al, Nature 2013).

https://www.neuro.mpg.de/borst

The precision of measurements is ultimately limited by quantum mechanics. However, achieving the quantum limit in practical measurement application like sensing proves to be a significant challenge. Traditional sensing techniques often become subject to increasing levels of environmental noise especially in integrated designs or when the sensor size approaches small length scales. However, recently developed quantum control techniques originally targeting quantum information processing and communications show strategies to control quantum states even in noisy environment. Furthermore, specifically designed quantum states can enhance sensing precision when control is obtained. The talk shall describe na-noscale sensing of electric, magnetic fields, temperature etc. utilizing spin quantum sensors. Applications in such diverse areas like solid-state physics or cellular biology shall be discussed.