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Sunday, July 19 • 8:00pm - 9:00pm
P53: A simple, non-stationary normalization model to explain and successfully predict change detection in monkey area MT

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Detlef Wegener, Xiao Chen, Lisa Bohnenkamp, Fingal Orlando Galashan, Udo Ernst

Successful visually-guided behavior in natural environments critically depends on rapid detection of changes in visual input. A wildcat chasing a gazelle needs to quickly adapt its motions to sudden direction changes of the prey, and a human driving a fast car on a highway must instantaneously react to the onset of the red brake light of the car in front. Visually responsive neurons represent such rapid feature changes in comparably rapid, transient changes of their firing rate. In the motion domain, for example, neurons in monkey area MT were shown to represent the sign and magnitude of a rapid speed change in the sign and amplitude of the evoked firing rate modulation following that change [1]. For positive speed changes, it was also shown that the transient’s latency closely correlates with reaction time, and is modulated by both spatial and non-spatial visual attention [2,3].

We here introduce a computational model based on a simple, canonical circuit in a cortical hypercolumn. We use the model to investigate the computational mechanisms underlying transient neuronal firing rate changes and their modulation by attention under a wide range of stimulus conditions. It is built of an excitatory and an inhibitory unit, both of which are in response to an external input _I_ (t). The excitatory unit receives additional divisive input from the inhibitory unit. The model’s dynamics is described by two differential equations quantifying how mean activity _A_ e of the excitatory unit and divisive input current change with time _t_. By fitting the model parameters to experimental data, we show that it is capable to reproduce the time courses of transient responses under passive viewing conditions. Mathematical analysis of the circuit explains hallmark effects of transient activations and identifies the relevant parameters determining response latency, peak response, and sustained activation. Visual attention is implemented by a simple multiplicative gain to the input of both units.

A key result of the analysis of the model’s dynamics is that steeper rise or decay times of the transient provide a consistent mechanisms of attentional modulation, independent of both the overall activation of the neuron prior to the speed change, and the sign of the change. This prediction is tested by new experiments requiring attention to both positive and negative speed changes. The results of the experiment are in full accordance with the prediction of the model, providing evidence that even decreases in firing rate in response to the reduction of the speed of an attended stimulus occur with shorter latency. Thus, the model provides a unique framework for a mechanistic understanding of MT response dynamics under very different sensory and behavioral conditions.


1\. Traschütz A, Kreiter AK, Wegener D. Transient activity in monkey area MT represents speed changes and is correlated with human behavioral performance. J Neurophysiol 2015, 113, 890-903.

2\. Galashan FO, Saßen HC, Kreiter AK, Wegener D. Monkey area MT latencies to speed changes depend on attention and correlate with behavioral reaction times. Neuron 2013, 78, 740-750.

3\. Schledde B, Galashan FO, Przybyla M, Kreiter AK, Wegener D. Task-specific, dimension-based attentional shaping of motion processing in monkey area MT. _ _ J Neurophysiol 2017, 118, 1542-1555.


Supported by BMBF grant 01GQ1106 and DFG grant WE 5469/3-1.


Detlef Wegener

Brain Research Institute, University of Bremen

Sunday July 19, 2020 8:00pm - 9:00pm CEST
Slot 16