Input matters! A novel explanation how sensory input contributes to shaping neuronal responses in the cortex

During the perception of sensory input signals, the activities of cortical neurons becomes less noisy and less correlated. These two activity features could be crucial to ensure an optimal representation of sensory information in the brain. The nature of the mechanisms that shape cortical responses to sensory inputs have puzzled scientist for decades.

As Alejandro F. Bujan, Ad Aertsen and Arvind Kumar from the Bernstein Center Freiburg explain in a new article published in the “Journal of Neuroscience”, the statistics of the input signal could play a key role in the generation of cortical responses that ensure an efficient representation of input signals in the brain's activity. To reach this result, they used computer simulations of the spiking activities of single neurons and networks of neurons, and studied the effects of different signal statistics on the responses of cortical neurons.

Previous proposals of how cortical neuronal responses are shaped during sensory perception suggested that the connectivities between neurons in the activated regions of cortex was the main factor determining the response features. Some of these models, however, had the flaw that they were unable to explain the decrease in the degree of functional coupling (or correlations) between neurons in response to sensory inputs. As Bujan and colleagues argue in their paper, these models had ignored the contribution of the factor that originated the responses in the first place: the sensory input signal!

The computational study by Bujan and colleagues introduces a novel way to classify the input activity features that help to understand the input's contribution to shaping the cortical response. As the authors point out, some input features have mainly an effect at the level of individual neurons, while others affect groups of neurons. Accordingly, input features affecting individual neuron responses determine the magnitude of the modulation induced by the input, whereas input features affecting populations of neurons define how the cortical activity is modified (see Figure). They further suggest that this classification of input features can be naturally linked to the way nerve cells send axonal projections into the cortex.

With their model, Bujan and colleagues propose a new view of cortical neuronal responses, in which stimulus-evoked activity features are shaped both by the connectivity within the cortex and by the connectivity of the input projections carrying the signal to the cortex, to ensure an optimal representation of the input signal in the cortical network activity.

Original publication:

Bujan AF, Aertsen A, Kumar A (2015)
Role of input correlations in shaping the variability and noise correlations of evoked activity in the neocortex.
J Neurosci. 35(22):8611-8625
doi:10.1523/jneurosci.4536-14.2015

Image Caption:

Representation of the cortical response caused by an input signal (“stimulus”). Axes in this scheme define three key features of the neuronal activity. The cortical activity is represented by filled circles. The black filled circle indicates the activity in the absence of a stimulus (also known as “ongoing” activity) and the green filled circle, the activity induced by the stimulus (“evoked”). The dashed red line indicates the “direction” of the modulation (green empty circle), representing the contribution of the input features to the activity of populations of neurons. The red arrows indicate the magnitude of the change determined by the input features (empty green circle) at the single cell level, given the level of ongoing activity (black filled circle).