Browsing by Author "English, Daniel Fine"

Now showing 1 - 6 of 6
  • Thumbnail Image
    Dual color optogenetic control of neural populations using low-noise, multishank optoelectrodes
    Kampasi, Komal; English, Daniel Fine; Seymour, John; Stark, Eran; McKenzie, Sam; Vöröslakos, Mihály; Buzsáki, György; Wise, Kensall D.; Yoon, Euisik (Nature, 2018)
    Optogenetics allows for optical manipulation of neuronal activity and has been increasingly combined with intracellular and extracellular electrophysiological recordings. Genetically-identified classes of neurons are optically manipulated, though the versatility of optogenetics would be increased if independent control of distinct neural populations could be achieved on a sufficient spatial and temporal resolution. We report a scalable multisite optoelectrode design that allows simultaneous optogenetic control of two spatially intermingled neuronal populations in vivo. We describe the design, fabrication, and assembly of low-noise, multisite/multicolor optoelectrodes. Each shank of the four-shank assembly is monolithically integrated with 8 recording sites and a dualcolor waveguide mixer with a 7 × 30 μm cross-section, coupled to 405 nm and 635 nm injection laser diodes (ILDs) via gradient-index (GRIN) lenses to meet optical and thermal design requirements. To better understand noise on the recording channels generated during diode-based activation, we developed a lumped-circuit modeling approach for EMI coupling mechanisms and used it to limit artifacts to amplitudes under 100 μV upto an optical output power of 450 μW. We implanted the packaged devices into the CA1 pyramidal layer of awake mice, expressing Channelrhodopsin-2 in pyramidal cells and ChrimsonR in paravalbumin-expressing interneurons, and achieved optical excitation of each cell type using sub-mW illumination. We highlight the potential use of this technology for functional dissection of neural circuits.
  • Thumbnail Image
    Granular retrosplenial cortex layer 2/3 generates high-frequency oscillations dynamically coupled with hippocampal rhythms across brain states
    Arndt, Kaiser C.; Gilbert, Earl T.; Klaver, Lianne M.F.; Kim, Jongwoon; Buhler, Chelsea M.; Basso, Julia C.; McKenzie, Sam; English, Daniel Fine (CellPress, 2024-03-26)
    The granular retrosplenial cortex (gRSC) exhibits high-frequency oscillations (HFOs; ~150 Hz), which can be driven by a hippocampus-subiculum pathway. How the cellular-synaptic and laminar organization of gRSC facilitates HFOs is unknown. Here, we probe gRSC HFO generation and coupling with hippocampal rhythms using focal optogenetics and silicon-probe recordings in behaving mice. ChR2-mediated excitation of CaMKII-expressing cells in L2/3 or L5 induces HFOs, but spontaneous HFOs are found only in L2/3, where HFO power is highest. HFOs couple to CA1 sharp wave-ripples (SPW-Rs) during rest and the descending phase of theta. gRSC HFO current sources and sinks are the same for events during both SPW-Rs and theta oscillations. Independent component analysis shows that high gamma (50–100 Hz) in CA1 stratum lacunosum moleculare is comodulated with HFO power. HFOs may thus facilitate interregional communication of a multisynaptic loop between the gRSC, hippocampus, and medial entorhinal cortex during distinct brain and behavioral states.
  • Thumbnail Image
    Inferring and validating mechanistic models of neural microcircuits based on spike-train data
    Ladenbauer, Josef; McKenzie, Sam; English, Daniel Fine; Hagens, Olivier; Ostojic, Srdjan (Springer Nature, 2019-10-30)
    The interpretation of neuronal spike train recordings often relies on abstract statistical models that allow for principled parameter estimation and model selection but provide only limited insights into underlying microcircuits. In contrast, mechanistic models are useful to interpret microcircuit dynamics, but are rarely quantitatively matched to experimental data due to methodological challenges. Here we present analytical methods to efficiently fit spiking circuit models to single-trial spike trains. Using derived likelihood functions, we statistically infer the mean and variance of hidden inputs, neuronal adaptation properties and connectivity for coupled integrate-and-fire neurons. Comprehensive evaluations on synthetic data, validations using ground truth in-vitro and in-vivo recordings, and comparisons with existing techniques demonstrate that parameter estimation is very accurate and efficient, even for highly subsampled networks. Our methods bridge statistical, data-driven and theoretical, model-based neurosciences at the level of spiking circuits, for the purpose of a quantitative, mechanistic interpretation of recorded neuronal population activity.
  • Thumbnail Image
    Inferring and validating mechanistic models of neural microcircuits based on spike-train data
    Ladenbauer, Josef; McKenzie, Sam; English, Daniel Fine; Hagens, Olivier; Ostojic, Srdjan (2018-02-07)
    The interpretation of neuronal spike train recordings often relies on abstract statistical models that allow for principled parameter estimation and model selection but provide only limited insights into underlying microcircuits. In contrast, mechanistic models are useful to interpret microcircuit dynamics, but are rarely quantitatively matched to experimental data due to methodological challenges. Here we present analytical methods to efficiently fit spiking circuit models to single-trial spike trains. Using the maximal-likelihood approach, we statistically infer the mean and variance of hidden inputs, neuronal adaptation properties and connectivity for coupled integrate-and-fire neurons. Evaluations based on simulated data, and validations using ground truth recordings in vitro and in vivo demonstrated that parameter estimation is very accurate, even for highly sub-sampled networks. We finally apply our methods to recordings from cortical neurons of awake ferrets and reveal population-level equalization between hidden excitatory and inhibitory inputs. The methods introduced here enable a quantitative, mechanistic interpretation of recorded neuronal population activity.
  • Thumbnail Image
    Propagation of hippocampal ripples to the neocortex by way of a subiculum-retrosplenial pathway
    Nitzan, Noam; McKenzie, Sam; Beed, Prateep; English, Daniel Fine; Oldani, Silvia; Tukker, John J.; Buzsáki, György; Schmitz, Dietmar (2020-04-23)
    Bouts of high frequency activity known as sharp wave ripples (SPW-Rs) facilitate communication between the hippocampus and neocortex. However, the paths and mechanisms by which SPW-Rs broadcast their content are not well understood. Due to its anatomical positioning, the granular retrosplenial cortex (gRSC) may be a bridge for this hippocampo-cortical dialogue. Using silicon probe recordings in awake, head-fixed mice, we show the existence of SPW-R analogues in gRSC and demonstrate their coupling to hippocampal SPW-Rs. gRSC neurons reliably distinguished different subclasses of hippocampal SPW-Rs according to ensemble activity patterns in CA1. We demonstrate that this coupling is brain state-dependent, and delineate a topographically-organized anatomical pathway via VGlut2-expressing, bursty neurons in the subiculum. Optogenetic stimulation or inhibition of bursty subicular cells induced or reduced responses in superficial gRSC, respectively. These results identify a specific path and underlying mechanisms by which the hippocampus can convey neuronal content to the neocortex during SPW-Rs. Communication between the hippocampus and neocortex is organized through high frequency sharp wave ripple activity. Here, the authors report ripple activity coupling between the hippocampus and granular retrosplenial cortex suggesting an involvement in communicating with the neocortex.
  • Thumbnail Image
    T-DOpE probes reveal sensitivity of hippocampal oscillations to cannabinoids in behaving mice
    Kim, Jongwoon; Huang, Hengji; Gilbert, Earl T.; Kaiser C., Arndt; English, Daniel Fine; Jia, Xiaoting (Nature Research, 2024-02-24)
    Understanding the neural basis of behavior requires monitoring and manipulating combinations of physiological elements and their interactions in behaving animals. We developed a thermal tapering process enabling fabrication of low-cost, flexible probes combining ultrafine features: dense electrodes, optical waveguides, and microfluidic channels. Furthermore, we developed a semi-automated backend connection allowing scalable assembly. We demonstrate T-DOpE (Tapered Drug delivery, Optical stimulation, and Electrophysiology) probes achieve in single neuron-scale devices (1) highfidelity electrophysiological recording (2) focal drug delivery and (3) optical stimulation. The device tip can beminiaturized (as small as 50 μm) tominimize tissue damage while the ~20 times larger backend allows for industrial-scale connectorization. T-DOpE probes implanted in mouse hippocampus revealed canonical neuronal activity at the level of local field potentials (LFP) and neural spiking. Taking advantage of the triple-functionality of these probes, we monitored LFP while manipulating cannabinoid receptors (CB1R; microfluidic agonist delivery) and CA1 neuronal activity (optogenetics). Focal infusion of CB1R agonist downregulated theta and sharp wave-ripple oscillations (SPWRs). Furthermore, we found that CB1R activation reduces sharp wave-ripples by impairing the innate SPW-R-generating ability of the CA1 circuit.