Population receptive field estimates in human visual cortex

Local field potentials (LFPs) provide a wealth of information about synaptic processing in cortical populations but are difficult to interpret. Einevoll and colleagues consider the neural origin of cortical LFPs and discuss LFP modelling and analysis methods that can improve the interpretation of LFP data.

Modelling and analysis of local field potentials for studying the function of cortical circuits

1. We recorded single-unit and multi-unit activity in response to transient presentation of texture and grating patterns at 25 sites within the parafoveal representation of V1, V2, and V3 of two awake monkeys trained to perform a fixation task. In grating experiments, stimuli varied in orientation, spatial frequency, or both. In texture experiments, stimuli varied in contrast, check size, texture type, or pairs of these attributes. 2. To examine the nature and precision of temporal coding, we compared individual responses elicited by each set of stimuli in terms of two families of metrics. One family of metrics, D(spike), was sensitive to the absolute spike time (following stimulus onset). The second family of metrics, D(interval), was sensitive to the pattern of interspike intervals. In each family, the metrics depend on a parameter q, which expresses the precision of temporal coding. For q = 0, both metrics collapse into the "spike count" metric D(Count), which is sensitive to the number of impulses but insensitive to their position in time. 3. Each of these metrics, with values of q ranging from 0 to 512/s, was used to calculate the distance between all pairs of spike trains within each dataset. The extent of stimulus-specific clustering manifest in these pairwise distances was quantified by an information measure. Chance clustering was estimated by applying the same procedure to synthetic data sets in which responses were assigned randomly to the input stimuli. 4. Of the 352 data sets, 170 showed evidence of tuning via the spike count (q = 0) metric, 294 showed evidence of tuning via the spike time metric, 272 showed evidence of tuning via the spike interval metric to the stimulus attribute (contrast, check size, orientation, spatial frequency, or texture type) under study. Across the entire dataset, the information not attributable to chance clustering averaged 0.042 bits for the spike count metric, 0.171 bits for the optimal spike time metric, and 0.107 bits for the optimal spike interval metric. 5. The reciprocal of the optimal cost q serves as a measure of the temporal precision of temporal coding. In V1 and V2, with both metrics, temporal precision was highest for contrast (ca. 10-30 ms) and lowest for texture type (ca. 100 ms). This systematic dependence of q on stimulus attribute provides a possible mechanism for the simultaneous representation of multiple stimulus attributes in one spike train. 6. Our findings are inconsistent with Poisson models of spike trains. Synthetic data sets in which firing rate was governed by a time-dependent Poisson process matched to the observed poststimulus time histogram (PSTH) overestimated clustering induced by D(count) and, for low values of q, D(spike)[q] and D(intervals)[q]. Synthetic data sets constructed from a modified Poisson process, which preserved not only the PSTH but also spike count statistics accounted for the clustering induced by D(count) but underestimated the clustering induced by D(spike)[q] and D(interval)[q].

Nature and precision of temporal coding in visual cortex: a metric-space analysis.

The Utah Intracortical Electrode Array: A recording structure for potential brain-computer interfaces

https://www.cell.com/neuron/pdf/S0896-6273(08)01006-4.pdf

Local Origin of Field Potentials in Visual Cortex

1. We recorded local field potentials in the parafoveal representation in the primary visual cortex of anesthetized and paralyzed macaque monkeys with a multicontact electrode that provided for sampling of neural activity at 16 sites along a vertical penetration. Differential recordings at adjacent contacts were transformed into an estimate of current source density (CSD), to provide a measure of local neural activity. 2. We used m-sequence stimuli to map the region of visual space that provided input to the recording site. The local field potential recorded in macaque V1 has a population receptive field (PRF) size of approximately 2 deg2. 3. We assessed spatial tuning by the responses to two-dimensional Gaussian noise, spatially filtered to retain power only within one octave. Responses to achromatic band-limited noise stimuli revealed a prominent band-pass spatial tuning in the upper layers, but a more low-pass spatial tuning in lower layers. 4. We assessed orientation tuning by the responses to band-limited noise whose spectrum was further restricted to lie within 45 degrees wedges. The local field potential showed evidence of orientation tuning at most sites. Orientation tuning in upper and lower layers was manifest by systematic variations not only in response size but also in response dynamics. 5. We assessed chromatic tuning by the responses to isotropic band-limited noise modulated in a variety of directions in tristimulus space. Some lower-layer locations showed a nulling of response under near-isoluminant conditions. However, response dynamics in upper and lower layers depended not only on luminance contrast, but also on chromatic inputs. 6. Responses to near-isoluminant stimuli and to low-contrast luminance modulation were shifted to lower spatial frequencies. 7. We determined the extent to which various temporal frequencies in the response conveyed information concerning spatial frequency, orientation, and color under the steady-state conditions used in these studies. In each case, information is distributed in the response dynamics across a broad temporal frequency range, beginning at 4 Hz (the lowest frequency used). For spatial frequency the information rate remains significant up to at least 25 Hz. For orientation tuning and chromatic tuning, the information rate is lower overall and remains significant up to 13 Hz. In contrast, for texture discrimination, information is shifted to lower temporal frequencies.

Population encoding of spatial frequency, orientation, and color in macaque V1

Spatial correlations define the statistical structure of any visual image. Two-point correlations inform the visual system about the spatial frequency content of an image. Higher-order correlations can capture salient features such as object contours. We studied "isodipole" texture discrimination in V1 to determine if higher-order spatial correlations can be extracted by early stages of cortical processing. We made epicortical, local field potential, and single-cell recordings of responses elicited by isodipole texture interchange in anesthetized monkeys. Our studies demonstrate that single neurons in V1 can signal the presence of higher-order spatial correlations in visual textures. This places a computational mechanism, which may be essential for form vision at the earliest stage of cortical processing.

https://www.pnas.org/content/pnas/91/18/8482.full.pdf

Ephraim Katz

Papers

Population encoding of spatial frequency, orientation, and color in macaque V1

Striate cortex extracts higher-order spatial correlations from visual textures

Isodipole textures: a window on cortical mechanisms of form processing