Effect of Contrast on Visual Spatial Summation in Different Cell Categories in Cat Primary Visual Cortex

Characterization of extracellular spike waveforms recorded in wallaby primary visual cortex

Extracellular recordings were made from 642 units in the primary visual cortex (V1) of a highly visual marsupial, the Tammar wallaby. The receptive field (RF) characteristics of the cells were objectively estimated using the non-linear input model (NIM), and these were correlated with spike shapes. We found that wallaby cortical units had 68% regular spiking (RS), 12% fast spiking (FS), 4% triphasic spiking (TS), 5% compound spiking (CS) and 11% positive spiking (PS). RS waveforms are most often associated with recordings from pyramidal or spiny stellate cell bodies, suggesting that recordings from these cell types dominate in the wallaby cortex. In wallaby, 70-80% of FS and RS cells had orientation selective RFs and had evenly distributed linear and nonlinear RFs. We found that 47% of wallaby PS units were non-orientation selective and they were dominated by linear RFs. Previous studies suggest that the PS units represent recordings from the axon terminals of non-orientation selective cells originating in the lateral geniculate nucleus (LGN). If this is also true in wallaby, as strongly suggested by their low response latencies and bursty spiking properties, the results suggest that significantly more neurons in wallaby LGN are already orientation selective. In wallaby, less than 10% of recorded spikes had triphasic (TS) or sluggish compound spiking (CS) waveforms. These units had a mixture of orientation selective and non-oriented properties, and their cellular origins remain difficult to classify.

Analysis of extracellular spike waveforms and associated receptive fields of neurons in cat primary visual cortex

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.