Showing papers by "Ann M. Graybiel published in 2011"

Cell type-specific channelrhodopsin-2 transgenic mice for optogenetic dissection of neural circuitry function

Abstract: Optogenetic methods have emerged as powerful tools for dissecting neural circuit connectivity, function and dysfunction. We used a bacterial artificial chromosome (BAC) transgenic strategy to express the H134R variant of channelrhodopsin-2, ChR2(H134R), under the control of cell type–specific promoter elements. We performed an extensive functional characterization of the newly established VGAT-ChR2(H134R)-EYFP, ChAT-ChR2(H134R)-EYFP, Tph2-ChR2(H134R)-EYFP and Pvalb(H134R)-ChR2-EYFP BAC transgenic mouse lines and demonstrate the utility of these lines for precisely controlling action-potential firing of GABAergic, cholinergic, serotonergic and parvalbumin-expressing neuron subsets using blue light. This resource of cell type–specific ChR2(H134R) mouse lines will facilitate the precise mapping of neuronal connectivity and the dissection of the neural basis of behavior.

Cell type–specific channelrhodopsin-2 transgenic mice for optogenetic dissection of neural circuitry function

Abstract: Optogenetic methods have emerged as powerful tools for dissecting neural circuit connectivity, function and dysfunction. We used a bacterial artificial chromosome (BAC) transgenic strategy to express the H134R variant of channelrhodopsin-2, ChR2(H134R), under the control of cell type–specific promoter elements. We performed an extensive functional characterization of the newly established VGAT-ChR2(H134R)-EYFP, ChAT-ChR2(H134R)-EYFP, Tph2-ChR2(H134R)-EYFP and Pvalb(H134R)-ChR2-EYFP BAC transgenic mouse lines and demonstrate the utility of these lines for precisely controlling action-potential firing of GABAergic, cholinergic, serotonergic and parvalbumin-expressing neuron subsets using blue light. This resource of cell type–specific ChR2(H134R) mouse lines will facilitate the precise mapping of neuronal connectivity and the dissection of the neural basis of behavior.

Basal Ganglia Disorders Associated with Imbalances in the Striatal Striosome and Matrix Compartments

Abstract: Eunice Kennedy Shriver National Institute of Child Health and Human Development (U.S.) (R01-HD028341)

Basal Ganglia Disorders Associated with Imbalances in the Striatal Striosome and Matrix Compartments

Abstract: The striatum is composed principally of GABAergic, medium spiny striatal projection neurons (MSNs) that can be categorized based on their gene expression, electrophysiological profiles, and input–output circuits. Major subdivisions of MSN populations include (1) those in ventromedial and dorsolateral striatal regions, (2) those giving rise to the direct and indirect pathways, and (3) those that lie in the striosome and matrix compartments. The first two classificatory schemes have enabled advances in understanding of how basal ganglia circuits contribute to disease. However, despite the large number of molecules that are differentially expressed in the striosomes or the extra-striosomal matrix, and the evidence that these compartments have different input–output connections, our understanding of how this compartmentalization contributes to striatal function is still not clear. A broad view is that the matrix contains the direct and indirect pathway MSNs that form parts of sensorimotor and associative circuits, whereas striosomes contain MSNs that receive input from parts of limbic cortex and project directly or indirectly to the dopamine-containing neurons of the substantia nigra, pars compacta. Striosomes are widely distributed within the striatum and are thought to exert global, as well as local, influences on striatal processing by exchanging information with the surrounding matrix, including through interneurons that send processes into both compartments. It has been suggested that striosomes exert and maintain limbic control over behaviors driven by surrounding sensorimotor and associative parts of the striatal matrix. Consistent with this possibility, imbalances between striosome and matrix functions have been reported in relation to neurological disorders, including Huntington’s disease, L-DOPA-induced dyskinesias, dystonia, and drug addiction. Here, we consider how signaling imbalances between the striosomes and matrix might relate to symptomatology in these disorders.

Mapping brain networks in awake mice using combined optical neural control and fMRI

Abstract: Behaviors and brain disorders involve neural circuits that are widely distributed in the brain. The ability to map the functional connectivity of distributed circuits, and to assess how this connectivity evolves over time, will be facilitated by methods for characterizing the network impact of activating a specific subcircuit, cell type, or projection pathway. We describe here an approach using high-resolution blood oxygenation level-dependent (BOLD) functional MRI (fMRI) of the awake mouse brain-to measure the distributed BOLD response evoked by optical activation of a local, defined cell class expressing the light-gated ion channel channelrhodopsin-2 (ChR2). The utility of this opto-fMRI approach was explored by identifying known cortical and subcortical targets of pyramidal cells of the primary somatosensory cortex (SI) and by analyzing how the set of regions recruited by optogenetically driven SI activity differs between the awake and anesthetized states. Results showed positive BOLD responses in a distributed network that included secondary somatosensory cortex (SII), primary motor cortex (MI), caudoputamen (CP), and contralateral SI (c-SI). Measures in awake compared with anesthetized mice (0.7% isoflurane) showed significantly increased BOLD response in the local region (SI) and indirectly stimulated regions (SII, MI, CP, and c-SI), as well as increased BOLD signal temporal correlations between pairs of regions. These collective results suggest opto-fMRI can provide a controlled means for characterizing the distributed network downstream of a defined cell class in the awake brain. Opto-fMRI may find use in examining causal links between defined circuit elements in diverse behaviors and pathologies.

Characterization of the functional MRI response temporal linearity via optical control of neocortical pyramidal neurons.

Abstract: The blood oxygenation level-dependent (BOLD) signal serves as the basis for human functional MRI (fMRI). Knowledge of the properties of the BOLD signal, such as how linear its response is to sensory stimuli, is essential for the design and interpretation of fMRI experiments. Here, we combined the cell-type and site-specific causal control provided by optogenetics and fMRI (opto-fMRI) in mice to test the linearity of BOLD signals driven by locally induced excitatory activity. We employed high-resolution mouse fMRI at 9.4 tesla to measure the BOLD response, and extracellular electrophysiological recordings to measure the effects of stimulation on single unit, multiunit, and local field potential activity. Optically driven stimulation of layer V neocortical pyramidal neurons resulted in a positive local BOLD response at the stimulated site. Consistent with a linear transform model, this locally driven BOLD response summated in response to closely spaced trains of stimulation. These properties were equivalent to responses generated through the multisynaptic method of driving neocortical activity by tactile sensory stimulation, and paralleled changes in electrophysiological measures. These results illustrate the potential of the opto-fMRI method and reinforce the critical assumption of human functional neuroimaging that—to first approximation—the BOLD response tracks local neural activity levels.

Habit learning is associated with major shifts in frequencies of oscillatory activity and synchronized spike firing in striatum.

Abstract: Rhythmic brain activity is thought to reflect, and to help organize, spike activity in populations of neurons during on-going behavior We report that during learning, a major transition occurs in task-related oscillatory activity in the ventromedial striatum, a striatal region related to motivation-dependent learning Early on as rats learned a T-maze task, bursts of 70- to 90-Hz high-γ activity were prominent during T-maze runs, but these gradually receded as bursts of 15- to 28-Hz β-band activity became pronounced Populations of simultaneously recorded neurons synchronized their spike firing similarly during both the high-γ–band and β-band bursts Thus, the structure of spike firing was reorganized during learning in relation to different rhythms Spiking was concentrated around the troughs of the β-oscillations for fast-spiking interneurons and around the peaks for projection neurons, indicating alternating periods of firing at different frequencies as learning progressed Spike-field synchrony was primarily local during high-γ–bursts but was widespread during β-bursts The learning-related shift in the probability of high-γ and β-bursting thus could reflect a transition from a mainly focal rhythmic inhibition during early phases of learning to a more distributed mode of rhythmic inhibition as learning continues and behavior becomes habitual These dynamics could underlie changing functions of the ventromedial striatum during habit formation More generally, our findings suggest that coordinated changes in the spatiotemporal relationships of local field potential oscillations and spike activity could be hallmarks of the learning process

Shifting responsibly: the importance of striatal modularity to reinforcement learning in uncertain environments

Abstract: We propose here that the modular organization of the striatum reflects a context-sensitive modular learning architecture in which clustered striosome-matrisome domains participate in modular reinforcement learning (RL). Based on anatomical and physiological evidence, it has been suggested that the modular organization of the striatum could represent a learning architecture. There is not, however, a coherent view of how such a learning architecture could relate to the organization of striatal outputs into the direct and indirect pathways of the basal ganglia, nor a clear formulation of how such a modular architecture relates to the RL functions attributed to the striatum. Here, we hypothesize that striosome-matrisome modules not only learn to bias behavior toward specific actions, as in standard RL, but also learn to assess their own relevance to the environmental context and modulate their own learning and activity on this basis. We further hypothesize that the contextual relevance or “responsibility” of modules is determined by errors in predictions of environmental features and that such responsibility is assigned by striosomes and conveyed to matrisomes via local circuit interneurons. To examine these hypotheses and to identify the general requirements for realizing this architecture in the nervous system, we developed a simple modular RL model. We then constructed a network model of basal ganglia circuitry that includes these modules and the direct and indirect pathways. Based on simple assumptions, this model suggests that while the direct pathway may promote actions based on striatal action values, the indirect pathway may act as a gating network that facilitates or suppresses behavioral modules on the basis of striatal responsibility signals. Our modeling functionally unites the modular compartmental organization of the striatum with the direct-indirect pathway divisions of the basal ganglia, a step that we suggest will have important clinical implications.

Shifting Responsibly: The Importance of Striatal Modularity to Reinforcement Learning in Uncertain Environments

Abstract: We propose here that the modular organization of the striatum reflects a context-sensitive modular learning architecture in which clustered striosome-matrisome domains participate in modular reinforcement learning (RL). Based on anatomical and physiological evidence, it has been suggested that the modular organization of the striatum could represent a learning architecture. There is not, however, a coherent view of how such a learning architecture could relate to the organization of striatal outputs into the direct and indirect pathways of the basal ganglia, nor a clear formulation of how such a modular architecture relates to the RL functions attributed to the striatum. Here, we hypothesize that striosome-matrisome modules not only learn to bias behavior toward specific actions, as in standard RL, but also learn to assess their own relevance to the environmental context and modulate their own learning and activity on this basis. We further hypothesize that the contextual relevance or “responsibility” of modules is determined by errors in predictions of environmental features and that such responsibility is assigned by striosomes and conveyed to matrisomes via local circuit interneurons. To examine these hypotheses and to identify the general requirements for realizing this architecture in the nervous system, we developed a simple modular RL model. We then constructed a network model of basal ganglia circuitry that includes these modules and the direct and indirect pathways. Based on simple assumptions, this model suggests that while the direct pathway may promote actions based on striatal action values, the indirect pathway may act as a gating network that facilitates or suppresses behavioral modules on the basis of striatal responsibility signals. Our modeling functionally unites the modular compartmental organization of the striatum with the direct-indirect pathway divisions of the basal ganglia, a step that we suggest will have important clinical implications.

Advance cueing produces enhanced action-boundary patterns of spike activity in the sensorimotor striatum.

Abstract: One of the most characteristic features of habitual behaviors is that they can be evoked by a single cue. In the experiments reported here, we tested for the effects of such advance cueing on the firing patterns of striatal neurons in the sensorimotor striatum. Rats ran in a T-maze with instruction cues about the location of reward given at the start of the runs. This advance cueing about reward produced a highly augmented task-bracketing pattern of activity at the beginning and end of procedural task performance relative to the patterns found previously with midtask cueing. Remarkably, the largest increase in activity early during the T-maze runs was not associated with the instruction cues themselves, the earliest predictors of reward; instead, the highest peak of early activity was associated with the beginning of the motor period of the task. We suggest that the advance cueing, reducing midrun demands for decision making but adding a working-memory load, facilitated chunking of the maze runs as executable scripts anchored to sensorimotor aspects of the task and unencumbered by midtask decision-making demands. Our findings suggest that the acquisition of stronger task-bracketing patterns of striatal activity in the sensorimotor striatum could reflect this enhancement of behavioral chunking. Deficits in such representations of learned sequential behaviors could contribute to motor and cognitive problems in a range of neurological disorders affecting the basal ganglia, including Parkinson's disease.

Identification and localization of a neuron-specific isoform of TAF1 in rat brain: implications for neuropathology of DYT3 dystonia

Abstract: Japan. Ministry of Education, Culture, Sports, Science and Technology (Grant-in-aid for Scientific Research 20591025)

Cell-type Specific Optogenetic Mice for Dissecting Neural Circuitry Function

Abstract: National Institutes of Health (U.S.) (Ruth L. Kirschstein National Research Service award (F32MH084460))

A novel instrumented multipeg running wheel system, Step-Wheel, for monitoring and controlling complex sequential stepping in mice

Abstract: Motor control is critical in daily life as well as in artistic and athletic performance and thus is the subject of intense interest in neuroscience. Mouse models of movement disorders have proven valuable for many aspects of investigation, but adequate methods for analyzing complex motor control in mouse models have not been fully established. Here, we report the development of a novel running-wheel system that can be used to evoke simple and complex stepping patterns in mice. The stepping patterns are controlled by spatially organized pegs, which serve as footholds that can be arranged in adjustable, ladder-like configurations. The mice run as they drink water from a spout, providing reward, while the wheel turns at a constant speed. The stepping patterns of the mice can thus be controlled not only spatially, but also temporally. A voltage sensor to detect paw touches is attached to each peg, allowing precise registration of footfalls. We show that this device can be used to analyze patterns of complex motor coordination in mice. We further demonstrate that it is possible to measure patterns of neural activity with chronically implanted tetrodes as the mice engage in vigorous running bouts. We suggest that this instrumented multipeg running wheel (which we name the Step-Wheel System) can serve as an important tool in analyzing motor control and motor learning in mice.