Neuronal oscillations and the rate-to-phase transform: mechanism, model and mutual information

Theoretical and experimental studies suggest that oscillatory modes of processing play an important role in neuronal computations. One well supported idea is that the net excitatory input during oscillations will be reported in the phase of firing, a ‘rate-to-phase transform’, and that this transform might enable a temporal code. Here, we investigate the efficiency of this code at the level of fundamental single cell computations. We first develop a general framework for the understanding of the rate-to-phase transform as implemented by single neurons. Using whole cell patch-clamp recordings of rat hippocampal pyramidal neurons in vitro, we investigated the relationship between tonic excitation and phase of firing during simulated theta frequency (5 Hz) and gamma frequency (40 Hz) oscillations, over a range of physiological firing rates. During theta frequency oscillations, the phase of the first spike per cycle was a near-linear function of tonic excitation, advancing through a full 180 deg, from the peak to the trough of the oscillation cycle as excitation increased. In contrast, this relationship was not apparent for gamma oscillations, during which the phase of firing was virtually independent of the level of tonic excitatory input within the range of physiological firing rates. We show that a simple analytical model can substantially capture this behaviour, enabling generalization to other oscillatory states and cell types. The capacity of such a transform to encode information is limited by the temporal precision of neuronal activity. Using the data from our whole cell recordings, we calculated the information about the input available in the rate or phase of firing, and found the phase code to be significantly more efficient. Thus, temporal modes of processing can enable neuronal coding to be inherently more efficient, thereby allowing a reduction in processing time or in the number of neurons required

Geology of the basement complex Thorvald Nilsen Mountains, Antarctica

Online access for this thesis was created in part with support from the Institute of Museum and Library Services (IMLS) administered by the Nevada State Library, Archives and Public Records through the Library Services and Technology Act (LSTA). To obtain a high quality image or document please contact the DeLaMare Library at https://unr.libanswers.com/ or call: 775-784-6945.The basement complex was investigated along the western escarpment of the Thorvald Nilsen Mountains in the central part of the Transantarctic Mountains. The complex is composed of a composite batholith formed by plutons of pretectonic granodiorite and syntectonic quartz monzonite

Theta-Gamma Coding Meets Communication-through-Coherence: Neuronal Oscillatory Multiplexing Theories Reconciled.

Several theories have been advanced to explain how cross-frequency coupling, the interaction of neuronal oscillations at different frequencies, could enable item multiplexing in neural systems. The communication-through-coherence theory proposes that phase-matching of gamma oscillations between areas enables selective processing of a single item at a time, and a later refinement of the theory includes a theta-frequency oscillation that provides a periodic reset of the system. Alternatively, the theta-gamma neural code theory proposes that a sequence of items is processed, one per gamma cycle, and that this sequence is repeated or updated across theta cycles. In short, both theories serve to segregate representations via the temporal domain, but differ on the number of objects concurrently represented. In this study, we set out to test whether each of these theories is actually physiologically plausible, by implementing them within a single model inspired by physiological data. Using a spiking network model of visual processing, we show that each of these theories is physiologically plausible and computationally useful. Both theories were implemented within a single network architecture, with two areas connected in a feedforward manner, and gamma oscillations generated by feedback inhibition within areas. Simply increasing the amplitude of global inhibition in the lower area, equivalent to an increase in the spatial scope of the gamma oscillation, yielded a switch from one mode to the other. Thus, these different processing modes may co-exist in the brain, enabling dynamic switching between exploratory and selective modes of attention

Evaluating the Effectiveness of British Columbia's Environmental Assessment for First Nations' Participation in Mining Development

This paper applies effectiveness as a criterion to measure the participation of First Nations' participation in British Columbia's environmental assessment process. Effectiveness is reviewed as a means to measure policy implementation and an expanded framework is proposed to measure effectiveness. The framework is applied to three case studies in north-central British Columbia to measure the effectiveness of First Nations' participation in the EA process for mining development. All three cases failed to achieve procedural, substantive, and transactive efficacy and thereby failed to meet overall policy effectiveness. The policies used by the British Columbia government, including the relatively recent Environmental Assessment Act (1995), reflect a poor integration of First Nations people in the EA decision-making process with respect to mine development

Advanced III-V HEMT MMIC Technologies for Millimetre-Wave Applications

In this paper,we review advanced III-V HEMT device technologies for millimetre-wave applications,particularly targeted above 100 GHz.We demonstrate performance advantages in moving to self- aligned T-gate strategies in lattice matched InP HEMTs. For 120 nm gate lengths,we have obtained self-aligned, non-annealed Ohmic contact devices with gm of 1450 mS/mm,fT of 220 GHz and fmax of 435 GHz.We will also present data on a high yield 50 nm T-gate process in the metamorphic GaAs material system utilizing non-selective digital wet etching with performance metrics including gm of 1500 mS/mm and fT of 350 GHz,to our knowledge,the fastest GaAs-based transistors reported to date

LJ-multiplexing–representation of multiple items.

<p><b>A.</b> The system is capable of representing more objects (more closely matching the proposals of the LJ-multiplexing theory), provided that ensembles auto-inhibit for a longer period, and therefore fire only once per slow cycle. Results from a series of simulations (100 repeats), summarizing activity in the higher area (red for high contrast object, blue for mid, green for low). Parameters as for <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1005162#pcbi.1005162.g003" target="_blank">Fig 3D</a> (i.e. strong global inhibition in the lower area), except that the synaptic decay time constant for local inhibition in the lower area was increased to 20 ms. Following 200 ±50 ms of blank screen, the stimulus (3 objects, see text) was turned on. i) shows a PSTH (spike probability across simulation repeats), ii) is a cross-correlogram (calculated for spikes from all 3 cells), iii) shows a polar phase plot of firing probability relative to the slow oscillation. <b>B</b>. As for A, except that the amplitude of the slow oscillation was halved, such that some lower area cells were never fully suppressed. Again (c.f. F-multiplexing, <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1005162#pcbi.1005162.g005" target="_blank">Fig 5D</a>), lower area synchrony was disrupted and object representation was impaired.</p

The feature-pair conjunction model.

<p><b>A.</b> The lower area of the model is similar to the first model (<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1005162#pcbi.1005162.g002" target="_blank">Fig 2</a>), with retinotopically arranged layers of excitatory and inhibitory cells, but with the addition of layers of excitatory cells selective for stimulus colour (red, green and blue), again duplicated across spatial scales, but without orientation selectivity. The higher area is more significantly modified: in this case, there is no spatial selectivity, with all cells receiving inputs from the full spatial extent of the lower area. Instead, due to restricted connectivity, these cells are selective for particular colour-orientation conjunctions, as indicated diagrammatically. <b>B.</b> Summary of network activity in response to a red-vertical stimulus patch, and a slightly lower contrast blue-horizontal patch, across the same three network states as described earlier (default, F- and LJ-multiplexing), showing the activity across one slow oscillatory cycle for each state (average of 1 s simulated activity, 100 simulation repeats). Plots of mean firing rate vs phase of slow oscillation are shown for activity in the lower area. For the higher area, the probability of firing at a given time point is shown, for each of the correctly activated conjunction cells (red-vertical and blue-horizontal) as well as for either of the false conjunctions (red-horizontal or blue-vertical).</p

Comparative illustration of multiplexing theories.

<p><b>A.</b> Consider a simple scene comprising 3 discrete objects of different saliency. <b>B.</b> LJ-multiplexing. Multiple Items are processed across consecutive fast cycles in decreasing order of saliency, and this sequence is repeated over slow oscillatory cycles. Note that items of low saliency may not be processed at all. <b>C.</b> F-multiplexing. Within any given slow cycle, only a single item is represented, repeated across multiple fast cycles. Across slow cycles, the represented item may switch, due to changes in the stimulus or top-down attentional mechanisms altering relative stimulus saliency.</p

The network model.

<p><b>A.</b> The model comprises two areas: a lower area approximating primary visual cortex, composed of multiple retinotopically arranged ‘simple cell’ layers duplicated across orientation, spatial phase and spatial frequency tuning. For input, these cells received a visual stimulus (excitatory conductance driven via an appropriate Gabor filter), noise (independent across cells) and a common slow rhythmic inhibitory conductance to mimic an alpha/theta oscillation (9 Hz in all of our simulations). In turn, the lower area sent convergent connections to a simplistic higher area, comprised in this case of just 4 cells, each receiving input from one retinotopic quadrant of the lower area (i.e. pure spatial selectivity). <b>B.</b> Within each area, a number of local circuit mechanisms could be implemented: lateral excitation (see Methods for details); local inhibition with a 2-D Gaussian distribution of synaptic strength both to and from a layer of inhibitory interneurons; and global inhibition implemented via a single interneuron receiving input from and sending output to all the excitatory cells in the lower area. In the simulations reported, local excitation and inhibition were always included, whereas global inhibition was varied as an important parameter determining network behaviour. <b>C</b>. The power spectrum of activity generated in the lower area in response to a single stimulus object (light rectangle, 9 x 39 pixels, with a single-pixel dark outline) as a function of its contrast, calculated for the PSTH of all activated cells (10 repeats of 1 second of activity for each contrast level tested; note that no global inhibition was included in these simulations). The network readily generates gamma frequency activity, via a PING mechanism as illustrated diagrammatically below the plot (pyramidal cells and their times of firing shown in gray; inhibitory interneurons in orange; the orange rectangles in the background represent the time course of inhibitory feedback). The frequency of gamma activity is contrast dependent, matching experimental results.</p