Key points Extracellular spikes recorded in the visual cortex (Area 17/18, V1) are commonly classified into either regular‐spiking (RS) or fast‐spiking (FS). Using multi‐electrode arrays positioned in cat V1 and a broadband stimulus, we show that there is also a distinct class with positive‐spiking (PS) waveforms. PS units were associated mainly with non‐oriented receptive fields while RS and FS units had orientation‐selective receptive fields. We suggest that PS units are recordings of axons originating from the thalamus. This conclusion was reinforced by our finding that we could record PS units after cortical silencing, but not record RS and FS units. The importance of our findings is that we were able to correlate spike shapes with receptive field characteristics with high precision using multi‐electrode extracellular recording techniques. This allows considerable increases in the amount of information that can be extracted from future cortical experiments. Abstract Extracellular spike waveforms from recordings in the visual cortex have been classified into either regular‐spiking (RS) or fast‐spiking (FS) units. While both these types of spike waveforms are negative‐dominant, we show that there are also distinct classes of spike waveforms in visual Area 17/18 (V1) of anaesthetised cats with positive‐dominant waveforms, which are not regularly reported. The spatial receptive fields (RFs) of these different spike waveform types were estimated, which objectively revealed the existence of oriented and non‐oriented RFs. We found that units with positive‐dominant spikes, which have been associated with recordings from axons in the literature, had mostly non‐oriented RFs (84%), which are similar to the centre‐surround RFs observed in the dorsal lateral geniculate nucleus (dLGN). Thus, we hypothesise that these positive‐dominant waveforms may be recordings from dLGN afferents. We recorded from V1 before and after the application of muscimol (a cortical silencer) and found that the positive‐dominant spikes (PS) remained while the RS and FS cells did not. We also noted that the PS units had spiking characteristics normally associated with dLGN units (i.e. higher response spike rates, lower response latencies and higher proportion of burst spikes). Our findings show quantitatively that it is possible to correlate the RF properties of cortical neurons with particular spike waveforms. This has implications for how extracellular recordings should be interpreted and complex experiments can now be contemplated that would have been very challenging previously, such as assessing the feedforward connectivity between brain areas in the same location of cortical tissue.

AbstractVisual object identification requires both selectivity for specific visual features that are important to the object’s identity and invariance to feature manipulations. For example, a hand can be shifted in position, rotated, or contracted but still be recognised as a hand. How are the competing requirements of selectivity and invariance built into the early stages of visual processing? Typically, cells in the primary visual cortex are classified as either simple or complex. They both show selectivity for edge-orientation but complex cells develop invariance to edge position within the receptive field (spatial phase). Using a data-driven model that extracts the spatial structures and nonlinearities associated with neuronal computation, we show that the balance between selectivity and invariance in complex cells is more diverse than thought. Phase invariance is frequently partial, thus retaining sensitivity to brightness polarity, while invariance to orientation and spatial frequency are more extensive than expected. The invariance arises due to two independent factors: (1) the structure and number of filters and (2) the form of nonlinearities that act upon the filter outputs. Both vary more than previously considered, so primary visual cortex forms an elaborate set of generic feature sensitivities, providing the foundation for more sophisticated object processing.

SUMMARYThe present study deals with a comprehensive thermodynamic modeling of a combined heat and power (CHP) system in a paper mill, which provides 50 MW of electric power and 100 ton h À1 saturated steam at 13 bars. This CHP plant is composed of air compressor, combustion chamber (CC), Air Preheater, Gas Turbine (GT) and a Heat Recovery Heat Exchanger. The design parameters of this cycle are compressor pressure ratio (r AC ), compressor isentropic efficiency (Z AC ), GT isentropic efficiency (Z GT ), CC inlet temperature (T 3 ), and turbine inlet temperature (T 4 ). In the multi-objective optimization three objective functions, including CHP exergy efficiency, total cost rate of the system products, and CO 2 emission of the whole plant, are considered. The exergoenvironmental objective function is minimized whereas power plant exergy efficiency is maximized using a Genetic algorithm. To have a good insight into this study, a sensitivity analysis of the results to the interest rate as well as fuel cost is performed. The results show that at the lower exergetic efficiency, in which the weight of exergoenvironmental objective is higher, the sensitivity of the optimal solutions to the fuel cost is much higher than the location of the Pareto Frontier with the lower weight of exergoenvironmental objective. In addition, with increasing exergy efficiency, the purchase cost of equipment in the plant is increased as the cost rate of the plant increases.

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