We request to extend the length and modify the contents of our previously approved experiment NP1306-LINAC07. Based on the new availability of ⁵⁰Ti and ⁵⁴Cr beams, and in light of the results of the commissioning portion of NP1306-LINAC07, we believe it is reasonable to extend the campaign to include isotopes of Rf, Db and Sg. We presently have 1.5 days of previously allocated machine time remaining, and wish to request an additional 20 days of machine time to complete the original proposed measurements of Fm, Md, No, and Lr isotopes and an additional 7 days to measure Rf and Db isotopes which can be produced using the new ⁵⁰Ti beam. We are further requesting 7 days of conditional machine time for measurements of Sg when a sufficiently intense ⁵⁴Cr beam becomes available.
In preliminary work towards No and Lr mass measurements (NP1306-LINAC07) we made precision mass measurements of 205, 206Fr and ²⁰¹At and rough mass measurements of ²⁰¹Bi, 201, 205Po, 205, 206At and 205, 206Rn . These measurements were achieved with only 6 hours of machine time, during which the system efficiency was ≈0.5% for ²⁰⁵Fr. As shown in Fig. [figIsobars], we have demonstrated an ability to measure multiple isobaric chains simultaneously. This will enable a very efficient survey of the general mass landscape in this region. Here we propose a separate and independent experiment to study this region in detail.
NEUROSCIENCE Variability of systems / balanced network 1. Softky, W. R., & Koch, C. (1993). The highly irregular firing of cortical cells is inconsistent with temporal integration of random EPSPs. The Journal of Neuroscience, 13(1), 334-350. - cortical pyramidal cells show irregular firing (Cv ≈ 1) - irregularity can be explained by strong EPSPs, or many synchronized weak EPSPs without non-sync. input - _integrator_ of many inputs yields regular firing (passive dendrites, AMPA) - _coincidence detector_ shows irregular firing rates (active dendrites, NMDA) - IRREGULAR FIRING SUGGESTS EXISTENCE OF SPIKE CODE OVER RATE CODE 2. Mainen, Z. F., & Sejnowski, T. J. (1995). Reliability of spike timing in neocortical neurons. Science, 268(5216), 1503-1506. - strong fluctuating input to cortical neurons lead to precise timing of spikes - slow inputs lead to regular spiking in neurons - unresolved: role of unreliable synapses - no proof for spike time carries information, but precise code would be possible 3. Shadlen, M. N., & Newsome, W. T. (1998). The variable discharge of cortical neurons: implications for connectivity, computation, and information coding. The Journal of neuroscience, 18(10), 3870-3896. - statistics of input and output should be the same - variability in activity consists of variability in mean firing rate and variance in ISIs - common input causes variability, but necessary for fast signal transmission - NICELY ELABORATED RELATIONSHIP BETWEEN Cv AND SPIKE COUNTS VARIANCE - suggests rate code over temporal code 4. van Vreeswijk, C., & Sompolinsky, H. (1996). Chaos in neuronal networks with balanced excitatory and inhibitory activity. Science, 274(5293), 1724-1726. - very simple model for balanced networks - network responds faster than membrane time constant 5. Brunel, N. (2000). Dynamics of sparsely connected networks of excitatory and inhibitory spiking neurons. Journal of computational neuroscience, 8(3), 183-208. 6. Okun, M., & Lampl, I. (2008). Instantaneous correlation of excitation and inhibition during ongoing and sensory-evoked activities. Nature neuroscience, 11(5), 535-537. - neuronal input is strongly synchronized - excitatory and inhibitory input is balanced and correlated in time and strength - excitatory input is followed by inhibitory input with time lag of few ms - found in anesthetized and awake behaving rat - INDICATION THAT TEMPORAL PRECISE COINCIDENCE DETECTION IN NEURONS IS POSSIBLE 7. Poulet, J. F., & Petersen, C. C. (2008). Internal brain state regulates membrane potential synchrony in barrel cortex of behaving mice. Nature, 454(7206), 881-885. - mice pyramidal cell barrel cortex layer 2/3 - membrane potential correlated during quiet wakefulness and decorrelated during whisking (internally modulated states) - APs are not synchronized, but SNR is higher during whisking (speaking for strong specific input to subpopulations) - In general: During whisking more decorrelated state of subthreshold potentials of populations, during behavior APs might be more reliable 8. Renart, A., de la Rocha, J., Bartho, P., Hollender, L., Parga, N., Reyes, A., & Harris, K. D. (2010). The asynchronous state in cortical circuits. science, 327(5965), 587-590. 9. Isaacson, J. S., & Scanziani, M. (2011). How inhibition shapes cortical activity. Neuron, 72(2), 231-243. 10. Tan, A. Y., Chen, Y., Scholl, B., Seidemann, E., & Priebe, N. J. (2014). Sensory stimulation shifts visual cortex from synchronous to asynchronous states. Nature. 11. Xue, Mingshan, Bassam V. Atallah, and Massimo Scanziani. “Equalizing excitation-inhibition ratios across visual cortical neurons.” Nature 511.7511 (2014): 596-600.