Filip Piekniewski

Emergence of bottom-up saliency in a spiking model of V1

We present anatomically detailed spiking model of the parvo and magno pathways of the retina, primary visual cortex (V1), and superior colliculus (SC) to enable active saccades. Due to STDP and visual experience, the model shows the emergence of a saliency map, resulting in the perceptual behavior of bottom-up (pop-out) attention. In contrast to previous models proposed to explain pop-out based attention for simple features (e.g., saliency map hypothesis of [1]), where feature selectivity and inhibitory mechanisms between similar features are pre-wired, connectivity in our spiking model is neither pre-wired nor are neurons pre-labeled, but feature selectivity and pop-out behavior still emerges. Projections between cell types in the V1 model (L4 and L2/3) are in agreement with anatomical data. Both excitatory and inhibitory synapses are subject to different forms of STDP. These plasticity mechanisms and exposure to rich natural visual stimuli lead to (i) neuronal responses similar to those recorded in vivo, (ii - parvo) formation in color selective cells, and (iii - magno) formation of simple and complex cells covering a broad range of orientations and spatial frequencies. Pop-out mechanism is mediated by modifying the activity in layer 2/3 with long-range effective inhibition using a narrow form of STDP, which selectively picks up short temporal correlations between neurons responding to similar features but depresses ignores neurons responding to different features. Stronger within-feature long-range inhibition dampens the population response to features that are abundant in the input, but allows strong response to salient input features. The activity of V1 drives the SC, resulting in pop-out saccades. (The SC model is presented in a separate submission.) The model connects electrophysiology (spiking activity) and perception, and it explains animal behavior in a variety of standard pop-out tasks. Neurons responding to vertical features will receive strong inhibition from other vertical neurons, therefore weakening their response, while response triggered by the single horizontal bar remains strong. Figure 1 A. Input image; B. V1 layer 2/3 activity without long-range inhibition; C. V1 layer 2/3 activity with long-range inhibition; D. Superior colliculus activity that directly drives the saccadic mechanism. Activity is averaged over two seconds.

Balanced excitation and inhibition in a spiking model of V1

Experimental studies have shown that neuronal excitation is balanced with inhibition and spikes are triggered only when that fine balance is perturbed. It is also known that inhibition is critical for receptive field tuning, yet it is not clear what role is played by different types of inhibitory interneurons and how the corresponding balanced circuitry could emerge via spike timing dependent plasticity (STDP). To study these questions we have constructed a large-scale detailed spiking model of V1 involving a variety of simulated neurons: fast-spiking (FS) interneurons, low threshold spiking (LTS) interneurons and regular spiking (RS) neurons. We modeled layer 4 and layer 2/3 of the primary visual cortex and a number of projections between cell types in agreement with anatomical data. Synaptic dynamics is governed by a set of STDP and activity dependent plasticity mechanisms for both inhibitory and excitatory synapses. The plasticity rules have been chosen to be in quantitative agreement with experiment where the data is available. For many of connections however, the data is either unavailable or noisy. In these cases plasticity rules were chosen based on a guided guess constrained by the requirement of structural stability of the system and expected response properties of cells to probing stimuli. Together, the plasticity rules lead to stable neuronal response and formation of orientation-selective receptive fields. The network learns simple and complex cells of a broad range of orientations and spatial frequencies. The model converges to a balanced neurodynamics and biologically reasonable firing rates. Our study shows that in the presence of strong thalamic drive, plastic inhibition is necessary for feature selectivity. The FS cells remove DC component of the input while firing of the LTS cells imposes sparse response and balances out feedback excitation.