Processing of sounds by population spikes in a model of primary auditory cortex

Abstract

We propose a model of the primary auditory cortex (A1), in which each iso-frequency column is represented by a recurrent neural network with short-term synaptic depression. Such networks can emit Population Spikes, in which most of the neurons fire synchronously for a short time period. Different columns are interconnected in a way that reflects the tonotopic map in A1, and population spikes can propagate along the map from one column to the next, in a temporally precise manner that depends on the specific input presented to the network. The network, therefore, processes incoming sounds by precise sequences of population spikes that are embedded in a continuous asynchronous activity, with both of these response components carrying information about the inputs and interacting with each other. With these basic characteristics, the model can account for a wide range of experimental findings. We reproduce neuronal frequency tuning curves, whose width depends on the strength of the intracortical inhibitory and excitatory connections. Non-simultaneous twotone stimuli show forward masking depending on their temporal separation, as well as on the duration of the first stimulus. The model also exhibits non-linear suppressive interactions between sub-threshold tones and broad-band noise inputs, similar to the hypersensitive locking suppression recently demonstrated in auditory cortex. We derive several predictions from the model. In particular, we predict that spontaneous activity in primary auditory cortex gates the temporally locked responses of A1 neurons to auditory stimuli. Spontaneous activity could, therefore, be a mechanism for rapid and reversible modulation of cortical processing.

Stimulus-specific adaptation in a recurrent network model of primary auditory cortex

“…The crucial property of our model is the use of synaptic depression in all of the excitatory connections, both intracortical and thalamocortical. A similar model has been used successfully to model many properties of auditory cortex [28]. Here we show that this model also exhibits stimulus-specific adaptation (SSA).…”

“…Our model network often responds to sensory stimulation by generating population spikes (PSs). PSs are events in which a large number of the neurons in a column fire a spike within a few milliseconds, and are characteristic of recurrent networks with synaptic depression [28,36,37]. A PS is generated when there are enough synaptic resources in the network to allow a spike in one neuron to evoke spikes in its post-synaptic targets.…”

“…Here we study an alternative mechanism: SSA may arise from the heavily recurrent cortical connectivity and the depression of the local, intracortical synapses in A1 [27]. We use a modified version of a recurrent neural network model with synaptic depression [28], which reproduced important properties of A1 responses, including frequency tuning, forward masking, and lateral inhibition. An important feature of this model is the generation of synchronized firing events called population spikes (PSs).…”

Inhibitory control of correlated intrinsic variability in cortical networks

“…The alternations between up states and down states have an intrinsic periodicity given by the timescale of the adaptation currents, but the chaotic nature of the network adds an apparent randomness to the timing of individual events, thus creating intrinsic temporal variability. Several previous studies (Tsodyks et al, 1998; Loebel et al, 2007) have modelled alternations between up states and down states using synaptic depression rather than spike-frequency adaptation. However, to our knowledge, there is no experimental evidence for the involvement of synaptic depression in the control of cortical state.…”

A physiologically based model for temporal envelope encoding in human primary auditory cortex

“…The PAC model recently proposed by Loebel et al (2007) also attempted to reproduce the functional properties of individual PAC cells. Pools of inhibitory and excitatory neurons forming cortical isofrequency columns that are interconnected to reflect the tonotopic map of the PAC and the intracortical connections are controlled by a model of short-term synaptic depression used in previous studies (Tsodyks et al, 2000;Loebel and Tsodyks, 2002).…”