Inter and intralaminar excitation of parvalbumin interneurons in mouse barrel cortex.

Parvalbumin (PV) interneurons are inhibitory fast-spiking cells with essential roles in directing the flow of information through cortical circuits. These neurons set the balance between excitation and inhibition and control rhythmic activity. PV interneurons differ between cortical layers in their morphology, circuitry, and function, but how their electrophysiological properties vary has received little attention. Here we investigate responses of PV interneurons in different layers of primary somatosensory barrel cortex (BC) to different excitatory inputs. With the genetically-encoded hybrid voltage sensor, hVOS, we recorded voltage changes in many L2/3 and L4 PV interneurons simultaneously, with stimulation applied to either L2/3 or L4. A semi-automated procedure was developed to identify small regions of interest corresponding to single responsive PV interneurons. Amplitude, half-width, and rise-time were greater for PV interneurons residing in L2/3 compared to L4. Stimulation in L2/3 elicited responses in both L2/3 and L4 with longer latency compared to stimulation in L4. These differences in latency between layers could influence their windows for temporal integration. Thus, PV interneurons in different cortical layers of BC respond in a layer specific and input specific manner, and these differences have potential roles in cortical computations.

Velocity of conduction between columns and layers in barrel cortex reported by parvalbumin interneurons.

Inhibitory interneurons expressing parvalbumin (PV) play critical roles throughout the brain. Their rapid spiking enables them to control circuit dynamics on a millisecond time scale, and the timing of their activation by different excitatory pathways is critical to these functions. We used a genetically encoded hybrid voltage sensor to image PV interneuron voltage changes with sub-millisecond precision in primary somatosensory barrel cortex (BC) of adult mice. Electrical stimulation evoked depolarizations with a latency that increased with distance from the stimulating electrode, allowing us to determine conduction velocity. Spread of responses between cortical layers yielded an interlaminar conduction velocity and spread within layers yielded intralaminar conduction velocities in different layers. Velocities ranged from 74 to 473 µm/ms depending on trajectory; interlaminar conduction was 71% faster than intralaminar conduction. Thus, computations within columns are more rapid than between columns. The BC integrates thalamic and intracortical input for functions such as texture discrimination and sensory tuning. Timing differences between intra- and interlaminar PV interneuron activation could impact these functions. Imaging of voltage in PV interneurons reveals differences in signaling dynamics within cortical circuitry. This approach offers a unique opportunity to investigate conduction in populations of axons based on their targeting specificity.

Unitary synaptic responses of parvalbumin interneurons evoked by excitatory neurons in the mouse barrel cortex.

The mammalian cortex integrates and processes information to transform sensory inputs into perceptions and motor outputs. These operations are performed by networks of excitatory and inhibitory neurons distributed through the cortical layers. Parvalbumin interneurons (PVIs) are the most abundant type of inhibitory cortical neuron. With axons projecting within and between layers, PVIs supply feedforward and feedback inhibition to control and modulate circuit function. Distinct populations of excitatory neurons recruit different PVI populations, but the specializations of these synapses are poorly understood. Here, we targeted a genetically encoded hybrid voltage sensor to PVIs and used fluorescence imaging in mouse somatosensory cortex slices to record their voltage changes. Stimulating a single visually identified excitatory neuron with small-tipped theta-glass electrodes depolarized multiple PVIs, and a common threshold suggested that stimulation elicited unitary synaptic potentials in response to a single excitatory neuron. Excitatory neurons depolarized PVIs in multiple layers, with the most residing in the layer of the stimulated neuron. Spiny stellate cells depolarized PVIs more strongly than pyramidal cells by up to 77%, suggesting a greater role for stellate cells in recruiting PVI inhibition and controlling cortical computations. Response half-width also varied between different excitatory inputs. These results demonstrate functional differences between excitatory synapses on PVIs.

Full-fusion and kiss-and-run in chromaffin cells controlled by irreversible vesicle size-dependent fusion pore transitions.

Exocytosis operates through two distinct modes. Full-fusion leads to rapid expulsion of the entire content of a vesicle; kiss-and-run leads to slow and partial expulsion. These two modes have important biological consequences for endocrine regulation and synaptic transmission. Amperometry recordings of catecholamine release from chromaffin cells reveal single-vesicle fusion events corresponding to both of these modes, but classification is often difficult. This study introduces a new method of analyzing amperometry data to improve this classification. The ratio of the average amplitude to the peak amplitude differs between full-fusion and kiss-and-run, and the probability distribution of this ratio is well fitted by a double-Gaussian. Kiss-and-run events identified by this method have fusion pores with kinetic properties different from pores associated with full-fusion. They have slower transition rates and lifetime distributions indicative of irreversible transitions. The total-charge of an amperometric spike is expected to scale with vesicle volume during a full-fusion event. The cube root of this quantity should therefore scale with diameter, but the distribution of this quantity differs from the distribution of vesicle diameter seen in the electron microscope. Fusion pore lifetimes associated with full-fusion depend on vesicle size, and this makes the choice of mode size dependent. The fusion pore thus bifurcates after opening, and vesicle size influences this choice. The secretory vesicle protein synaptophysin influences the size dependence of fusion pore lifetime and the choice of release mode. Incorporating vesicle size into an analysis of release mode reconciled the kinetics of fusion pores, as well as the distributions of vesicle diameter and catecholamine content. Thus, the initial fusion pore emerges as a critical focus in endocrine regulation. By modulating the size-dependence of the mode of exocytosis, changes in the molecular makeup of the exocytotic apparatus can impact the shape and size of an amperometric event, and the speed and composition of secretion.

Evolvix BEST Names for semantic reproducibility across code2brain interfaces.

Names in programming are vital for understanding the meaning of code and big data. We define code2brain (C2B) interfaces as maps in compilers and brains between meaning and naming syntax, which help to understand executable code. While working toward an Evolvix syntax for general-purpose programming that makes accurate modeling easy for biologists, we observed how names affect C2B quality. To protect learning and coding investments, C2B interfaces require long-term backward compatibility and semantic reproducibility (accurate reproduction of computational meaning from coder-brains to reader-brains by code alone). Semantic reproducibility is often assumed until confusing synonyms degrade modeling in biology to deciphering exercises. We highlight empirical naming priorities from diverse individuals and roles of names in different modes of computing to show how naming easily becomes impossibly difficult. We present the Evolvix BEST (Brief, Explicit, Summarizing, Technical) Names concept for reducing naming priority conflicts, test it on a real challenge by naming subfolders for the Project Organization Stabilizing Tool system, and provide naming questionnaires designed to facilitate C2B debugging by improving names used as keywords in a stabilizing programming language. Our experiences inspired us to develop Evolvix using a flipped programming language design approach with some unexpected features and BEST Names at its core.