Distinct roles for inhibitory neuron subtypes in cortical circuits : an examination of their structure, function, and connectivity

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Brain and Cognitive Sciences, 2012."June 2012." Cataloged from PDF version of thesis.Includes bibliographical references.Parvalbumin-containing (PV+) neurons and somatostatin-containing (SOM+) neurons are two key cortical inhibitory cell classes that are poised to play distinct computational roles in cortical circuits: PV+ neurons form synapses on the perisomatic region near the spike initiation zone of target cells, while SOM+ neurons form synapses on distal dendrites. The goals of this thesis are to better understand the functional roles of these two cell types with four major lines of questioning. 1) When and how do PV+ and SOM+ neurons respond to visual stimuli? 2) How do inhibitory neurons obtain their response selectivity? 3) How do PV+ and SOM+ neurons affect the responses of their targets? and 4) What are the targets of PV+ and SOM+ neurons? We used Cre-lox recombination to introduce either fluorescent protein or channelrhodopsin to PV+ or SOM+ neurons, targeting these cells for two-photon targeted physiological recording and morphological reconstruction, or selectively stimulating the population of PV+ or SOM+ neurons or stimulating single PV+ or SOM+ neurons. We find diverse response properties within both groups, suggesting that further functional subclasses of PV+ and SOM+ neurons may exist. Furthermore, orientation selectivity was strongly correlated to dendritic length in PV+ neurons, whose orientation preferences matched the preferences of neighboring cells, implying that inhibitory neurons may obtain selectivity by spatially limiting their sampling of the local network. When we stimulated PV+ and SOM+ neurons, we found that they perform distinct inhibitory operations on their targets: PV+ neurons divide responses while SOM+ neurons subtract. Even single PV+ and SOM+ neurons were capable of suppressing responses of other cells in the local network, but their functional targeting was sparse and followed different rules of wiring: PV+ neurons functionally suppressed a higher percentage of cells that shared their own tuning, while SOM+ neurons seemed to target other neurons independently of their preferred orientations. By studying the response properties and functional impacts of PV+ and SOM+ neurons in the intact primary visual cortex, we have gained insight into what information these cells are carrying and how they contribute to the response properties of other cells, which apply to cortical circuits in general.by Caroline A. Runyan.Ph.D

Division and subtraction by distinct cortical inhibitory networks in vivo

Brain circuits process information through specialized neuronal subclasses interacting within a network. Revealing their interplay requires activating specific cells while monitoring others in a functioning circuit. Here we use a new platform for two-way light-based circuit interrogation in visual cortex in vivo to show the computational implications of modulating different subclasses of inhibitory neurons during sensory processing. We find that soma-targeting, parvalbumin-expressing (PV) neurons principally divide responses but preserve stimulus selectivity, whereas dendrite-targeting, somatostatin-expressing (SOM) neurons principally subtract from excitatory responses and sharpen selectivity. Visualized in vivo cell-attached recordings show that division by PV neurons alters response gain, whereas subtraction by SOM neurons shifts response levels. Finally, stimulating identified neurons while scanning many target cells reveals that single PV and SOM neurons functionally impact only specific subsets of neurons in their projection fields. These findings provide direct evidence that inhibitory neuronal subclasses have distinct and complementary roles in cortical computations.National Institutes of Health (U.S.) (Postdoctoral Fellowship)Simons Foundation (Postdoctoral Fellowship)National Institutes of Health (U.S.) (Predoctoral Fellowship

Distinct timescales of population coding across cortex

The cortex represents information across widely varying timescales1–5. For instance, sensory cortex encodes stimuli that fluctuate over few tens of milliseconds6,7, whereas in association cortex behavioral choices can require the maintenance of information over seconds8,9. However, it remains poorly understood if diverse timescales result mostly from features intrinsic to individual neurons or from neuronal population activity. This question is unanswered because the timescales of coding in populations of neurons have not been studied extensively, and population codes have not been compared systematically across cortical regions. Here we discovered that population codes can be essential to achieve long coding timescales. Furthermore, we found that the properties of population codes differ between sensory and association cortices. We compared coding for sensory stimuli and behavioral choices in auditory cortex (AC) and posterior parietal cortex (PPC) as mice performed a sound localization task. Auditory stimulus information was stronger in AC than in PPC, and both regions contained choice information. Although AC and PPC coded information by tiling in time neurons that were transiently informative for ~200 milliseconds, the areas had major differences in functional coupling between neurons, measured as activity correlations that could not be explained by task events. Coupling among PPC neurons was strong and extended over long time lags, whereas coupling among AC neurons was weak and short-lived. Stronger coupling in PPC led to a population code with long timescales and a representation of choice that remained consistent for approximately one second. In contrast, AC had a code with rapid fluctuations in stimulus and choice information over hundreds of milliseconds. Our results reveal that population codes differ across cortex and that coupling is a variable property of cortical populations that affects the timescale of information coding and the accuracy of behavior

Two-way communication with neural networks in vivo using focused light

Neuronal networks process information in a distributed, spatially heterogeneous manner that transcends the layout of electrodes. In contrast, directed and steerable light offers the potential to engage specific cells on demand. We present a unified framework for adapting microscopes to use light for simultaneous in vivo stimulation and recording of cells at fine spatiotemporal resolutions. We use straightforward optics to lock onto networks in vivo, to steer light to activate circuit elements and to simultaneously record from other cells. We then actualize this 'free' augmentation on both an 'open' two-photon microscope and a leading commercial one. By following this protocol, setup of the system takes a few days, and the result is a noninvasive interface to brain dynamics based on directed light, at a network resolution that was not previously possible and which will further improve with the rapid advance in development of optical reporters and effectors. This protocol is for physiologists who are competent with computers and wish to extend hardware and software to interface more fluidly with neuronal networks.National Institutes of Health (U.S.) (Postdoctoral Fellowship)Simons Foundation (Postdoctoral Fellowship)National Institutes of Health (U.S.) (Predoctoral Fellowship)National Institutes of Health (U.S.)Simons Foundatio

Response Selectivity Is Correlated to Dendritic Structure in Parvalbumin-Expressing Inhibitory Neurons in Visual Cortex

Inhibitory neurons have been shown to perform a variety of functions within brain circuits, including shaping response functions in target cells. Still, how the properties of specific inhibitory neuron classes relate to their local circuits remains unclear. To better understand the distribution and origins of orientation selectivity in inhibitory neurons expressing the calcium binding protein parvalbumin (PV) in the mouse primary visual cortex, we labeled PV[superscript +] neurons with red fluorescent protein (RFP) and targeted them for cell-attached electrophysiological recordings. PV[superscript +] neurons could be broadly tuned or sharply tuned for orientation but tended to be more broadly tuned than unlabeled neurons on average. The dendritic morphology of PV[superscript +] cells, revealed by intracellular labeling, was strongly correlated with tuning: highly tuned PV[superscript +] neurons had shorter dendrites that branched nearer to the soma and had smaller dendritic fields overall, whereas broadly tuned PV[superscript +] neurons had longer dendrites that branched farther from the soma, producing larger dendritic fields. High-speed two-photon calcium imaging of visual responses showed that the orientation preferences of highly tuned PV[superscript +] neurons resembled the preferred orientations of neighboring cells. These results suggest that the diversity of the local neighborhood and the nature of dendritic sampling may both contribute to the response selectivity of PV[superscript +] neurons.Ruth L. Kirschstein National Research Service Award (NS679512)National Institutes of Health (U.S.) (Grant EY007023)National Institutes of Health (U.S.) (Grant EY018041)Simons Foundatio

Correlations enhance the behavioral readout of neural population activity in association cortex

Noise correlations (that is, trial-to-trial covariations in neural activity for a given stimulus) limit the stimulus information encoded by neural populations, leading to the widely held prediction that they impair perceptual discrimination behaviors. However, this prediction neglects the effects of correlations on information readout. We studied how correlations affect both encoding and readout of sensory information. We analyzed calcium imaging data from mouse posterior parietal cortex during two perceptual discrimination tasks. Correlations reduced the encoded stimulus information, but, seemingly paradoxically, were higher when mice made correct rather than incorrect choices. Single-trial behavioral choices depended not only on the stimulus information encoded by the whole population, but unexpectedly also on the consistency of information across neurons and time. Because correlations increased information consistency, they enhanced the conversion of sensory information into behavioral choices, overcoming their detrimental information-limiting effects. Thus, correlations in association cortex can benefit task performance even if they decrease sensory information