Inferring neural circuit properties from optogenetic stimulation

Local stimulation of pyramidal neurons in deep cortical layers of anesthetized rats enhances cortical visual information processing

In the primary visual cortex area V1 activation of inhibitory interneurons, which provide negative feedback for excitatory pyramidal neurons, can improve visual response reliability and orientation selectivity. Moreover, optogenetic activation of one class of interneurons, parvalbumin (PV) positive cells, reduces the receptive field (RF) width. These data suggest that in V1 the negative feedback improves visual information processing. However, according to information theory, noise can limit information content in a signal, and to the best of our knowledge, in V1 signal-to-noise ratio (SNR) has never been estimated following either pyramidal or inhibitory neuron activation. Therefore, we optogenetically activated pyramidal or PV neurons in the deep layers of cortical area V1 and measured the SNR and RF area in nearby pyramidal neurons. Activation of pyramidal or PV neurons increased the SNR by 267% and 318%, respectively, and reduced the RF area to 60.1% and 77.5%, respectively, of that of the control. A simple integrate-and-fire neuron model demonstrated that an improved SNR and a reduced RF area can increase the amount of information encoded by neurons. We conclude that in V1 activation of pyramidal neurons improves visual information processing since the location of the visual stimulus can be pinpointed more accurately (via a reduced RF area), and more information is encoded by neurons (due to increased SNR).

Understanding the circuit basis of cognitive functions using mouse models

Understanding how cognitive functions arise from computations occurring in the brain requires the ability to measure and perturb neural activity while the relevant circuits are engaged for specific cognitive processes. Rapid technical advances have led to the development of new approaches to transiently activate and suppress neuronal activity as well as to record simultaneously from hundreds to thousands of neurons across multiple brain regions during behavior. To realize the full potential of these approaches for understanding cognition, however, it is critical that behavioral conditions and stimuli are effectively designed to engage the relevant brain networks. Here, we highlight recent innovations that enable this combined approach. In particular, we focus on how to design behavioral experiments that leverage the ever-growing arsenal of technologies for controlling and measuring neural activity in order to understand cognitive functions.

Probing the Mechanisms of Repetition Suppression in Inferior Temporal Cortex with Optogenetics

Neurons in macaque inferior temporal (IT) cortex show a decrease in the response with stimulus repetition, known as repetition suppression (RS). Several mechanisms may contribute to RS in IT, such as firing rate-dependent fatigue and transsynaptic mechanisms, like synaptic depression or reduced input from neurons within the same area or from up- or downstream areas. We examined the role of firing rate fatigue and transsynaptic mechanisms by stimulating directly IT neurons using optogenetics and measured the effect of photo-stimulation on their responses using timing parameters that resulted in RS for visual stimuli. Photo-stimulation of IT neurons resulted in a marginally decreased probability of spiking activity to a subsequent photo-stimulation or to a subsequent low-contrast visual stimulus. This response reduction was small relative to that for repeated visual stimuli and was related to post-stimulation inhibition of the activity during the interval between adapter and test stimuli. Presentation of a visual adapter did not change the response to subsequent photo-stimulation. In neurons whose response to the visual adapter was inhibited by simultaneous photo-stimulation, RS to visual stimuli was unaffected. Overall, these data imply that RS in IT has a transsynaptic origin, with little or no contribution of intrinsic firing rate fatigue. In addition, they suggest a limited contribution of both local synaptic depression and reduced input from nearby IT neurons, whose responses were postulated to be decreased by firing rate fatigue, to RS in IT.