Adam M Packer

University College London, London, ENG, United Kingdom

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Publications (13)131.54 Total impact

  • Adam M Packer, Botond Roska, Michael Häusser
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    ABSTRACT: Optogenetic approaches promise to revolutionize neuroscience by using light to manipulate neural activity in genetically or functionally defined neurons with millisecond precision. Harnessing the full potential of optogenetic tools, however, requires light to be targeted to the right neurons at the right time. Here we discuss some barriers and potential solutions to this problem. We review methods for targeting the expression of light-activatable molecules to specific cell types, under genetic, viral or activity-dependent control. Next we explore new ways to target light to individual neurons to allow their precise activation and inactivation. These techniques provide a precision in the temporal and spatial activation of neurons that was not achievable in previous experiments. In combination with simultaneous recording and imaging techniques, these strategies will allow us to mimic the natural activity patterns of neurons in vivo, enabling previously impossible 'dream experiments'.
    Nature Neuroscience 06/2013; 16(7):805-815. · 15.25 Impact Factor
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    ABSTRACT: We demonstrate a two-photon optogenetic method that generates action potentials in neurons with single-cell precision, using the red-shifted opsin C1V1(T). We applied the method to optically map synaptic circuits in mouse neocortical brain slices and to activate small dendritic regions and individual spines. Using a spatial light modulator, we split the laser beam onto several neurons and performed simultaneous optogenetic activation of selected neurons in three dimensions.
    Nature Methods 11/2012; · 23.57 Impact Factor
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    ABSTRACT: Optogenetics with microbial opsin genes has enabled high-speed control of genetically specified cell populations in intact tissue. However, it remains a challenge to independently control subsets of cells within the genetically targeted population. Although spatially precise excitation of target molecules can be achieved using two-photon laser-scanning microscopy (TPLSM) hardware, the integration of two-photon excitation with optogenetics has thus far required specialized equipment or scanning and has not yet been widely adopted. Here we take a complementary approach, developing opsins with custom kinetic, expression and spectral properties uniquely suited to scan times typical of the raster approach that is ubiquitous in TPLSM laboratories. We use a range of culture, slice and mammalian in vivo preparations to demonstrate the versatility of this toolbox, and we quantitatively map parameter space for fast excitation, inhibition and bistable control. Together these advances may help enable broad adoption of integrated optogenetic and TPLSM technologies across experimental fields and systems.
    Nature Methods 11/2012; · 23.57 Impact Factor
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    ABSTRACT: Neocortical GABAergic interneurons have important roles in the normal and pathological states of the circuit. Recent work has revealed that somatostatin-positive (SOM) and parvalbumin-positive (PV) interneurons connect promiscuously to pyramidal cells (PCs). We investigated whether Peters' rule, that is, the spatial overlap of axons and dendrites, could explain this unspecific connectivity. We reconstructed the morphologies of P11-17 mouse SOM and PV interneurons and their PC targets, and performed Monte Carlo simulations to build maps of predicted connectivity based on Peters' rule. We then compared the predicted with the real connectivity maps, measured with 2-photon uncaging experiments, and found no statistical differences between them in the probability of connection as a function of distance and in the spatial structure of the maps. Finally, using reconstructions of connected SOM-PCs and PV-PCs, we investigated the subcellular targeting specificity, by analyzing the postsynaptic position of the contacts, and found that their spatial distributions match the distribution of postsynaptic PC surface area, in agreement with Peters' rule. Thus, the spatial profile of the connectivity maps and even the postsynaptic position of interneuron contacts could result from the mere overlap of axonal and dendritic arborizations and their laminar projections patterns.
    Cerebral Cortex 08/2012; · 8.31 Impact Factor
  • Elodie Fino, Adam M Packer, Rafael Yuste
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    ABSTRACT: Although inhibition plays a major role in the function of the mammalian neocortex, the circuit connectivity of GABAergic interneurons has remained poorly understood. The authors review recent studies of the connections made to and from interneurons, highlighting the overarching principle of a high density of unspecific connections in inhibitory connectivity. Whereas specificity remains in the subcellular targeting of excitatory neurons by interneurons, the general strategy appears to be for interneurons to provide a global "blanket of inhibition" to nearby neurons. In the review, the authors highlight the fact that the function of interneurons, which remains elusive, will be informed by understanding the structure of their connectivity as well as the dynamics of inhibitory synaptic connections. In a last section, the authors describe briefly the link between dense inhibitory networks and different interneuron functions described in the neocortex.
    The Neuroscientist 08/2012; · 5.63 Impact Factor
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    Adam M Packer, Rafael Yuste
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    ABSTRACT: GABAergic interneurons play a major role in the function of the mammalian neocortex, but their circuit connectivity is still poorly understood. We used two-photon RuBi-Glutamate uncaging to optically map how the largest population of cortical interneurons, the parvalbumin-positive cells (PV+), are connected to pyramidal cells (PCs) in mouse neocortex. We found locally dense connectivity from PV+ interneurons onto PCs across cortical areas and layers. In many experiments, all nearby PV+ cells were connected to every local PC sampled. In agreement with this, we found no evidence for connection specificity, as PV+ interneurons contacted PC pairs similarly regardless of whether they were synaptically connected or not. We conclude that the microcircuit architecture for PV+ interneurons, and probably neocortical inhibition in general, is an unspecific, densely homogenous matrix covering all nearby pyramidal cells.
    Journal of Neuroscience 09/2011; 31(37):13260-71. · 6.91 Impact Factor
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    ABSTRACT: Recent advances in experimental stimulation methods have raised the following important computational question: how can we choose a stimulus that will drive a neuron to output a target spike train with optimal precision, given physiological constraints? Here we adopt an approach based on models that describe how a stimulating agent (such as an injected electrical current or a laser light interacting with caged neurotransmitters or photosensitive ion channels) affects the spiking activity of neurons. Based on these models, we solve the reverse problem of finding the best time-dependent modulation of the input, subject to hardware limitations as well as physiologically inspired safety measures, that causes the neuron to emit a spike train that with highest probability will be close to a target spike train. We adopt fast convex constrained optimization methods to solve this problem. Our methods can potentially be implemented in real time and may also be generalized to the case of many cells, suitable for neural prosthesis applications. With the use of biologically sensible parameters and constraints, our method finds stimulation patterns that generate very precise spike trains in simulated experiments. We also tested the intracellular current injection method on pyramidal cells in mouse cortical slices, quantifying the dependence of spiking reliability and timing precision on constraints imposed on the applied currents.
    Journal of Neurophysiology 04/2011; 106(2):1038-53. · 3.30 Impact Factor
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    ABSTRACT: Fluorescent calcium indicators are becoming increasingly popular as a means for observing the spiking activity of large neuronal populations. Unfortunately, extracting the spike train of each neuron from a raw fluorescence movie is a nontrivial problem. This work presents a fast nonnegative deconvolution filter to infer the approximately most likely spike train of each neuron, given the fluorescence observations. This algorithm outperforms optimal linear deconvolution (Wiener filtering) on both simulated and biological data. The performance gains come from restricting the inferred spike trains to be positive (using an interior-point method), unlike the Wiener filter. The algorithm runs in linear time, and is fast enough that even when simultaneously imaging >100 neurons, inference can be performed on the set of all observed traces faster than real time. Performing optimal spatial filtering on the images further refines the inferred spike train estimates. Importantly, all the parameters required to perform the inference can be estimated using only the fluorescence data, obviating the need to perform joint electrophysiological and imaging calibration experiments.
    Journal of Neurophysiology 12/2010; 104(6):3691-704. · 3.30 Impact Factor
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    ABSTRACT: Deciphering the circuitry of the neocortex requires knowledge of its components, making a systematic classification of neocortical neurons necessary. GABAergic interneurons contribute most of the morphological, electrophysiological and molecular diversity of the cortex, yet interneuron subtypes are still not well defined. To quantitatively identify classes of interneurons, 59 GFP-positive interneurons from a somatostatin-positive mouse line were characterized by whole-cell recordings and anatomical reconstructions. For each neuron, we measured a series of physiological and morphological variables and analyzed these data using unsupervised classification methods. PCA and cluster analysis of morphological variables revealed three groups of cells: one comprised of Martinotti cells, and two other groups of interneurons with short asymmetric axons targeting layers 2/3 and bending medially. PCA and cluster analysis of electrophysiological variables also revealed the existence of these three groups of neurons, particularly with respect to action potential time course. These different morphological and electrophysiological characteristics could make each of these three interneuron subtypes particularly suited for a different function within the cortical circuit.
    Frontiers in Neural Circuits 01/2010; 4:12. · 3.33 Impact Factor
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    Samuel B Snider, Rafael Yuste, Adam M Packer
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    ABSTRACT: In one of the most remarkable feats of motor control in the animal world, some Diptera, such as the housefly, can accurately execute corrective flight maneuvers in tens of milliseconds. These reflexive movements are achieved by the halteres, gyroscopic force sensors, in conjunction with rapidly tunable wing steering muscles. Specifically, the mechanosensory campaniform sensilla located at the base of the halteres transduce and transform rotation-induced gyroscopic forces into information about the angular velocity of the fly's body. But how exactly does the fly's neural architecture generate the angular velocity from the lateral strain forces on the left and right halteres? To explore potential algorithms, we built a neuromechanical model of the rotation detection circuit. We propose a neurobiologically plausible method by which the fly could accurately separate and measure the three-dimensional components of an imposed angular velocity. Our model assumes a single sign-inverting synapse and formally resembles some models of directional selectivity by the retina. Using multidimensional error analysis, we demonstrate the robustness of our model under a variety of input conditions. Our analysis reveals the maximum information available to the fly given its physical architecture and the mathematics governing the rotation-induced forces at the haltere's end knob.
    Frontiers in Neural Circuits 01/2010; 4:123. · 3.33 Impact Factor
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    ABSTRACT: As recent advances in calcium sensing technologies facilitate simultaneously imaging action potentials in neuronal populations, complementary analytical tools must also be developed to maximize the utility of this experimental paradigm. Although the observations here are fluorescence movies, the signals of interest--spike trains and/or time varying intracellular calcium concentrations--are hidden. Inferring these hidden signals is often problematic due to noise, nonlinearities, slow imaging rate, and unknown biophysical parameters. We overcome these difficulties by developing sequential Monte Carlo methods (particle filters) based on biophysical models of spiking, calcium dynamics, and fluorescence. We show that even in simple cases, the particle filters outperform the optimal linear (i.e., Wiener) filter, both by obtaining better estimates and by providing error bars. We then relax a number of our model assumptions to incorporate nonlinear saturation of the fluorescence signal, as well external stimulus and spike history dependence (e.g., refractoriness) of the spike trains. Using both simulations and in vitro fluorescence observations, we demonstrate temporal superresolution by inferring when within a frame each spike occurs. Furthermore, the model parameters may be estimated using expectation maximization with only a very limited amount of data (e.g., approximately 5-10 s or 5-40 spikes), without the requirement of any simultaneous electrophysiology or imaging experiments.
    Biophysical Journal 08/2009; 97(2):636-55. · 3.67 Impact Factor
  • Frontiers in Systems Neuroscience 01/2009;
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    ABSTRACT: Neuroscience produces a vast amount of data from an enormous diversity of neurons. A neuronal classification system is essential to organize such data and the knowledge that is derived from them. Classification depends on the unequivocal identification of the features that distinguish one type of neuron from another. The problems inherent in this are particularly acute when studying cortical interneurons. To tackle this, we convened a representative group of researchers to agree on a set of terms to describe the anatomical, physiological and molecular features of GABAergic interneurons of the cerebral cortex. The resulting terminology might provide a stepping stone towards a future classification of these complex and heterogeneous cells. Consistent adoption will be important for the success of such an initiative, and we also encourage the active involvement of the broader scientific community in the dynamic evolution of this project.
    Nature Reviews Neuroscience 08/2008; 9(7):557-68. · 31.38 Impact Factor

Publication Stats

651 Citations
131.54 Total Impact Points

Institutions

  • 2013
    • University College London
      • Department of Neuroscience, Physiology, and Pharmacology
      London, ENG, United Kingdom
  • 2011–2012
    • Columbia University
      • Department of Biological Sciences
      New York City, NY, United States
  • 2010–2012
    • Howard Hughes Medical Institute
      Ashburn, Virginia, United States
    • Johns Hopkins University
      • Department of Neuroscience
      Baltimore, MD, United States
  • 2009
    • Johns Hopkins Medicine
      • Department of Neuroscience
      Baltimore, MD, United States
  • 2008
    • George Mason University
      • Center for Neuroinformatics, Neural Structures, and Neuroplasticity
      Fairfax, VA, United States