Document Actions

You are here: Home / Research / Meet the Scientist / Jan Benda

Jan Benda

Bernstein Award winner 2007,
Ludwig Maximilians University Munich

benda150

The role of background noise in sensory signal processing

Any information an animal receives about the outside world is transformed to neuronal signals by the sensory organs – neurons ‘fire’ short electrical impulses. How is this information coded and processed in the spatial and temporal pattern of neuronal activity? What influence does background noise have on this process – stochastic fluctuations of the electrical signals of the brain? These questions are addressed by Jan Benda using weakly-electric fish as a model. Jan Benda received the Bernstein Award 2007. The award is conferred annually by the Federal Ministry of Education and Research and enables excellent young scientists to establish their own research group. ‘The system is simply perfect for investigating the active role of noise,’ he says. Benda did his PhD in the group of Andreas Herz at the Humboldt University (Berlin). During his subsequent post-doctoral studies at the University of Ottawa (Canada) in the group of Leonard Maler and Andre Longtin, Benda came into contact with weakly-electric fish for the first time. Since 2004 he has been back in Berlin, where the ideas for the research project took form, which he can now realize with help of the Bernstein Award. Benda will move to the Ludwig-Maximilians-University in Munich to carry out the project.

Weakly-electric fish use specialized organs to emit sequences of fast electric discharge resulting in an electric field, and they have electroreceptors to sense their own field. In this way they can detect prey or the presence of other fish whose  lectric field interferes with their own. The frequency of the electric organ discharge varies between individual fish and is generally higher in females than in males. Just like the interference of two sound waves of a similar frequency, the interference of the electric fields of two fish also results in a so called ‘beat’: the amplitude of the interference wave varies periodically. When two fish of the same gender meet, the beat frequency is below 30 Hertz; for two fish of opposite sex it is above 100 Hertz. In this way, the fish distinguishes whether it encounters a female or male individual and sends the according communication signals.

How information is coded and processed in the nervous system has been a major topic in the field of neuroscience for decades. In some cases, only the firing rate of a neuron matters; in other cases the exact timing of neuronal impulses plays a role. Benda showed that the coding of communication signals in weakly-electric fish follows yet another principle. Here, the crucial factor is how synchronous the roughly 10,000 electroreceptors fire.

When a male fish encounters a male conspecific, it sends aggression signals: short accelerations of the electric organ discharge frequency by about 100 Hz, called ‘small chirps’. As a consequence, the amplitude of the beat rises abruptly. Receptor neurons fire in the rhythm of the electric organ discharge, though leaving out different cycles. Since different receptors skip different cycles, they fire asynchronously. However, receptor activity correlates with the amplitude of the beat signal – the greater the amplitude, the more impulses they send and the more synchronous their signal will thus become. Because of the sudden rise of the beat amplitude in a chirp, the activity of the receptors is exceptionally strong and thus they fire particularly synchronously.

When a male fish meets a female, the beat ampli-tude varies at a much higher frequency than when two males encounter. The receptor neurons correspondingly fire synchro-nously. The male fish sends courtship signals, accelerations of its electric organ discharge by about 600 Hz, termed ‘large chirps’. Large disrupt the fast beat considerably, and receptor neurons reacting to the amplitude of the beat are thrown out of their rhythm. Receptorneurons thus desynchronize in response to large chirps. ‘In both cases the level of synchronization carries the information – in one case neurons synchronize in response to a chirp, in the other case they desynchronize,’ says Benda.

Such a synchronization code sheds a completely different light on the role of background noise in the nervous system. The amount of noise strongly influences the synchrony of the neurons and thereby has a direct impact on the information they transmit. ‘So far, background noise has generally been regarded as an unavoidable disturbance inherent to the system. However, it is also possible that the processing characteristics of a neuronare tuned by adjusting the noise level,’ says Benda. According to this idea, neurons have adapted their noise level in the course of evolution so that the fish can preferentially react to signals that are relevant to it; irrelevant signals would perish due to noise.

Until now, there have been very few experimental studies investigating the role of noise in neurons – and for good reason. ‘It is impossible to experimentally manipulate the noise level in many neurons simultaneously,’ says Benda. Electrosensory systems of weakly electric fish, however, offer a unique possibility to circumvent this experimental problem. Weakly-electric fish have two kinds of electroreceptors: those reacting to distortions of their own electrical field as described above and those perceiving the electric field of a prey, which forms through the fish’s muscle contractions. ‘Interestingly, the two receptor types differ considerably in their level of noise. Nonetheless, the neuronal processing circuits arevery similar. Therefore, the two electrosensory systems are an ideal system for comparative experimental studies investigating the role of noise in sensory information processing,’ says Benda. His experimental work will be supported by theoretical studies, investigating how noise can shape neural population codes. Benda’s studies may contribute to a possible revision in our thinking about the function of neuronal background noise in sensory systems.