Inhibitory circuits of the cortex : control of rhythmic and stimulus evoked activity

We are surrounded by a world, which makes sense, only because we make sense of it. At every instant in our waking life we estimate the state of the world based on sensory data, then we reshape the world to meet our goals. How are these sensations encoded, goals represented and action computed? To answer these questions we dissect the biological circuitry in our brains that seamlessly performs these computations. To study the dynamics of neural circuits, we specifically focus on the role inhibition in shaping signal processing. This work examines how inhibitory circuits process increasingly complex forms of afferent input. First, we characterize and model local circuit responses to brief impulses of afferent activity. We find that local circuits generate feedforward inhibition in the first few milliseconds after an afferent impulse. This inhibition adjusts the excitability of the local population normalizing it to the afferent excitation level. Then, in the next few milliseconds, as individual local pyramidal cells spike they immediately recruit a distinct recurrent inhibitory circuit. This feedback circuit is extremely sensitive responding with negative feedback when even a single local pyramidal cell is active. By modeling the circuit dynamics during these stages in cortical processing we quantitatively demonstrate that the feedforward and feedback inhibitory circuits are tuned to be both sensitive to sparse activity and yet maintain fidelity with which a cortical circuit represents inputs at high activity levels. Next, the role inhibition during spontaneous rhythmic activity is dissected. Our results demonstrate that by rapidly balancing excitation with inhibition, cortical networks can swiftly modulate rhythms over a wide band of frequencies. Finally, we investigate the role of a distinct type of inhibitory interneuron during the first stage of cortical visual processing. Using optogenetics to either enhance or suppress parvalbumin positive interneurons spiking, we demonstrate that these neurons play a key role in modulating the selectivity of responses in primary visual cortex. Together, these results demonstrate the multifaceted role inhibitory circuits play in signal processing and shaping cortical computation; adding to our communal effort to develop a complete picture of how neural circuitry performs computations and encodes sensatio

Input normalization by global feedforward inhibition expands cortical dynamic range

The cortex is sensitive to weak stimuli, but responds to stronger inputs without saturating. The mechanisms that enable this wide range of operation are not fully understood. We found that the amplitude of excitatory synaptic currents necessary to fire rodent pyramidal cells, the threshold excitatory current, increased with stimulus strength. Consequently, the relative contribution of individual afferents in firing a neuron was inversely proportional to the total number of active afferents. Feedforward inhibition, acting homogeneously across pyramidal cells, ensured that threshold excitatory currents increased with stimulus strength. In contrast, heterogeneities in the distribution of excitatory currents in the neuronal population determined the specific set of pyramidal cells recruited. Together, these mechanisms expand the range of afferent input strengths that neuronal populations can represent.Fil: Pouille, Frédéric. University Of California. Department Of Neurobiology; Estados UnidosFil: Marin Burgin, Antonia. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Bioquímicas de Buenos Aires. Fundación Instituto Leloir. Instituto de Investigaciones Bioquímicas de Buenos Aires; Argentina. University Of California. Department Of Neurobiology; Estados UnidosFil: Adesnik, Hillel. University Of California. Department Of Neurobiology; Estados UnidosFil: Atallah, Bassam V.. University Of California. Department Of Neurobiology; Estados UnidosFil: Scanziani, Massimo. University Of California. Department Of Neurobiology; Estados Unido

Rapid target-specific remodeling of fast-spiking inhibitory circuits after loss of dopamine.

In Parkinson's disease (PD), dopamine depletion alters neuronal activity in the direct and indirect pathways and leads to increased synchrony in the basal ganglia network. However, the origins of these changes remain elusive. Because GABAergic interneurons regulate activity of projection neurons and promote neuronal synchrony, we recorded from pairs of striatal fast-spiking (FS) interneurons and direct- or indirect-pathway MSNs after dopamine depletion with 6-OHDA. Synaptic properties of FS-MSN connections remained similar, yet within 3 days of dopamine depletion, individual FS cells doubled their connectivity to indirect-pathway MSNs, whereas connections to direct-pathway MSNs remained unchanged. A model of the striatal microcircuit revealed that such increases in FS innervation were effective at enhancing synchrony within targeted cell populations. These data suggest that after dopamine depletion, rapid target-specific microcircuit organization in the striatum may lead to increased synchrony of indirect-pathway MSNs that contributes to pathological network oscillations and motor symptoms of PD.</p

Bonsai: An event-based framework for processing and controlling data streams

The design of modern scientific experiments requires the control and monitoring of many different data streams. However, the serial execution of programming instructions in a computer makes it a challenge to develop software that can deal with the asynchronous, parallel nature of scientific data. Here we present Bonsai, a modular, high-performance, open-source visual programming framework for the acquisition and online processing of data streams. We describe Bonsai's core principles and architecture and demonstrate how it allows for the rapid and flexible prototyping of integrated experimental designs in neuroscience. We specifically highlight some applications that require the combination of many different hardware and software components, including video tracking of behavior, electrophysiology and closed-loop control of stimulation