Comparison of spatial integration and surround suppression characteristics in spiking activity and the local field potential in macaque V1

Abstract

Neurons in primary visual cortex exhibit well documented centre-surround receptive field organization, whereby the centre is dominated by excitatory influences and the surround is generally dominated by inhibitory influences. These effects have largely been established by measuring the output of neurons, i.e. their spiking activity. How excitation and inhibition are reflected in the local field potential (LFP) is little understood. As this can bear on the interpretation of human fMRI BOLD data and on our understanding of the mechanisms of local field potential oscillations, we measured spatial integration and centre-surround properties in single- and multiunit recordings of V1 in the awake fixating macaque monkey, and compared these to spectral power in different frequency bands of simultaneously recorded LFPs. We quantified centre-surround organization by determining the size of the summation and suppression area in spiking activity as well as in different frequency bands of the LFP, with the main focus on the gamma band. Gratings extending beyond the summation area usually inhibited spiking activity while the LFP gamma-band activity increased monotonically for all grating sizes. This increase was maximal for stimuli infringing upon the near classical receptive field surround, where suppression started to dominate spiking activity. Thus, suppressive influences in primary cortex can be inferred from spiking activity, but they also seem to affect specific features of gamma-band LFP activity.

Significant reductions in human visual gamma frequency by the gaba reuptake inhibitor tiagabine revealed by robust peak frequency estimation

“…Increased peak gamma frequency has been reported also for stimuli of smaller size, in both LFP [Gieselmann and Thiele, 2008; Ray and Maunsell, 2011] and MEG recordings [van Pelt and Fries, 2013; although, see Perry et al, 2013 for inconsistent results]. This could be explained with smaller stimuli being represented by smaller neuronal ensembles, which in turn could be synchronized at a higher frequency over a shorter cortical distance [Gieselmann and Thiele, 2008]. Interestingly, gamma responses in monkey visual areas are induced at higher frequencies in response to repeated stimulus presentations compared with novel stimuli [Brunet et al, 2014a], and functionally synchronous networks appear to be tuned to higher frequencies when representing stimuli that are under the focus of attention [Bosman et al, 2012; see also Fries et al, 2001; Fries, 2015].…”

“…Gamma frequency in visual cortex is modulated by sensory input strength, increasing monotonically with respect to stimulus contrast [Perry, 2015; Perry et al, 2015; Ray and Maunsell, 2010]. Increased peak gamma frequency has been reported also for stimuli of smaller size, in both LFP [Gieselmann and Thiele, 2008; Ray and Maunsell, 2011] and MEG recordings [van Pelt and Fries, 2013; although, see Perry et al, 2013 for inconsistent results]. This could be explained with smaller stimuli being represented by smaller neuronal ensembles, which in turn could be synchronized at a higher frequency over a shorter cortical distance [Gieselmann and Thiele, 2008].…”

“…The peak frequency of visual gamma responses is modulated by properties of the visual stimulus such as size [Gieselmann and Thiele, 2008; Jia et al, 2013; Ray and Maunsell, 2011; van Pelt and Fries, 2013], contrast [Hadjipapas et al, 2015; Jia et al, 2013; Lowet et al, 2015; Perry et al, 2015; Ray and Maunsell, 2010; Roberts et al, 2013], motion [Friedman‐Hill, 2000; Muthukumaraswamy and Singh, 2013; Swettenham et al, 2009], motion velocity [Gray et al, 1990; Gray and Viana Di Prisco, 1997; Orekhova et al, 2015], eccentricity [van Pelt and Fries, 2013], noise masking [Jia et al, 2013], and cross‐orientation masking [Lima et al, 2010; Perry, 2015]. Across individuals, peak gamma frequency correlates with psychophysical performance in visual discrimination tasks [Dickinson et al, 2015; Edden et al, 2009].…”

Intersubject variability and induced gamma in the visual cortex: DCM with empirical Bayes and neural fields

“…The neurobiological mechanisms considered above highlight the central role of inhibitory connectivity in generating gamma response variability [Cardin et al, 2009] and regulating PING activity [Brunel and Wang, 2003; Gieselmann and Thiele, 2008; Ray and Maunsell, 2010]. It should be noted that these mechanisms are not mutually exclusive and might coexist or contribute to a different extent depending on individual differences and experimental conditions [Webb et al, 2005; Liu et al, 2011].…”

“…In particular, the spatial structure of the visual stimulus has been shown to affect gamma band activity [Bauer et al, 1995; Gieselmann and Thiele, 2008; Lima et al, 2010]. In our earlier work [Perry et al, 2013], we tested the relationship between the gamma‐band response and the size of visual grating stimuli in humans using MEG.…”