Spatial frequency and orientation tuning dynamics in area V1

Mazer, James A.; Vinje, William E.; McDermott, Josh H.; Schiller, Peter H.; Gallant, Jack L.

doi:10.1073/pnas.022638499

Cited by 263 publications

(279 citation statements)

References 28 publications

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“…This separability has been a disputed issue (30-32) with evidence on both sides (24,33,34). Recordings in a recent study by Mazer et al (35) from awake behaving monkeys point toward separability, but Ringach et al (36) arrive at a different conclusion.…”

Section: Resultsmentioning

confidence: 79%

The organization of orientation and spatial frequency in primary visual cortex

Sirovich

Uglesich²

2004

Proc. Natl. Acad. Sci. U.S.A.

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Many studies have demonstrated that the primary visual cortex contains multiple functional maps of visual properties (e.g., ocular dominance, orientation preference, and spatial-frequency preference), but as yet no consistent picture has emerged as to how these maps are related to one another. Three divergent, prior opticalimaging studies of spatial frequency are reanalyzed and critiqued in this article. Evidence is presented that a nonstimulus-specific response biased the interpretation of results in previous studies. In addition to reexamining four prior cat experiments, we carried out one new experiment. Through the use of different methods and a careful removal of the nonspecific response, we are led in all instances to a unique view of cortical organization for spatialfrequency preference. In particular, we find little apparent evidence for a columnar organization for spatial frequency. The response recorded by each image pixel may be viewed as arising from an admixture of low-and high-spatial-frequency populations. For most pixels, the ratio of these populations is 1:1.optical imaging ͉ nonspecific response ͉ generalized indicator ͉ function analysis T he retinotopic map relates an element of visual space to an element of cortical tissue. Neurons in the primary visual cortex are known to be differentially sensitive to orientation, , and spatial frequency (SF), k, of corresponding image elements that appear in visual space. ‡ Thus, it may be said that the primary visual cortex maps visual space through a local Fourier analysis (1, 2). The process by which this mapping takes place, although not fully understood, is known to involve information processing by the retina, lateral geniculate nucleus (LGN), and primary visual cortex area V1 (V1) and feedback from higher areas.Casting aside the nature of neuronal circuitry, the functional layout of the primary visual cortex is well established for orientation preference and ocular dominance. Anatomical (3-5) and optical-imaging (6-9) studies have elaborated and extended the columnar view of V1 that emerged from electrophysiology (10, 11). Less can be said of the representation of SF. Extensive electrophysiological recordings (12-17) and optical-imaging experiments have not provided a consistent picture of SF layout. The situation can be further complicated if variations in the temporal properties of the stimuli are included (18).One series of optical-imaging studies (7,(19)(20)(21)(22) advanced the viewpoint that the orientation layout of V1 is organized into high-and low-SF preference columns. From this view, it follows that only a single map is needed to characterize SF. This map contains regions corresponding to high and low SF with opposite signs. Thus high-and low-SF stimuli result in responses of opposite signatures. An obvious shortcoming is that intermediate SF would lead to null or near-null results. On the other hand, Everson et al. (23) reported that SF preference is continuously distributed and that at least two maps are required to depict SF represen...

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Section: Resultsmentioning

confidence: 79%

The organization of orientation and spatial frequency in primary visual cortex

Sirovich

Uglesich²

2004

Proc. Natl. Acad. Sci. U.S.A.

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“…A few studies have estimated complex cell STRFs by removing all spatial phase information from the stimulus, thereby linearizing the stimulus-response relationship (Ringach et al, 1997;Mazer et al, 2002). A similar approach has been used in the temporal dimension for data in the auditory system (Aertsen and Johannesma, 1981;Theunissen et al, 2000;Machens et al, 2004).…”

Section: Linearized Spatiotemporal Receptive Field Modelmentioning

confidence: 99%

“…There is evidence that some V1 neurons possess a significant spacetime inseparable component (Mazer et al, 2002;Shapley et al, 2003). Because the space-time separable model may fail to capture some response properties of such neurons, we compared STRFs estimated using the inseparable model (Eq.…”

Section: E)mentioning

confidence: 99%

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Natural Stimulus Statistics Alter the Receptive Field Structure of V1 Neurons

David¹,

Vinje²,

Gallant³

2004

J. Neurosci.

316

304

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Studies of the primary visual cortex (V1) have produced models that account for neuronal responses to synthetic stimuli such as sinusoidal gratings. Little is known about how these models generalize to activity during natural vision. We recorded neural responses in area V1 of awake macaques to a stimulus with natural spatiotemporal statistics and to a dynamic grating sequence stimulus. We fit nonlinear receptive field models using each of these data sets and compared how well they predicted time-varying responses to a novel natural visual stimulus. On average, the model fit using the natural stimulus predicted natural visual responses more than twice as accurately as the model fit to the synthetic stimulus. The natural vision model produced better predictions in Ͼ75% of the neurons studied. This large difference in predictive power suggests that natural spatiotemporal stimulus statistics activate nonlinear response properties in a different manner than the grating stimulus. To characterize this modulation, we compared the temporal and spatial response properties of the model fits. During natural stimulation, temporal responses often showed a stronger late inhibitory component, indicating an effect of nonlinear temporal summation during natural vision. In addition, spatial tuning underwent complex shifts, primarily in the inhibitory, rather than excitatory, elements of the response profile. These differences in late and spatially tuned inhibition accounted fully for the difference in predictive power between the two models. Both the spatial and temporal statistics of the natural stimulus contributed to the modulatory effects.

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“…1 C and D). Response latency was determined from the temporal profile of RF (SI Materials and Methods) (18,19). As shown in Fig.…”

Section: V1 Neurons Respond Faster In Desynchronized Brainmentioning

confidence: 99%

Cumulative latency advance underlies fast visual processing in desynchronized brain state

Wang

Chen

Zhang

et al. 2013

Proc. Natl. Acad. Sci. U.S.A.

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Fast sensory processing is vital for the animal to efficiently respond to the changing environment. This is usually achieved when the animal is vigilant, as reflected by cortical desynchronization. However, the neural substrate for such fast processing remains unclear. Here, we report that neurons in rat primary visual cortex (V1) exhibited shorter response latency in the desynchronized state than in the synchronized state. In vivo whole-cell recording from the same V1 neurons undergoing the two states showed that both the resting and visually evoked conductances were higher in the desynchronized state. Such conductance increases of single V1 neurons shorten the response latency by elevating the membrane potential closer to the firing threshold and reducing the membrane time constant, but the effects only account for a small fraction of the observed latency advance. Simultaneous recordings in lateral geniculate nucleus (LGN) and V1 revealed that LGN neurons also exhibited latency advance, with a degree smaller than that of V1 neurons. Furthermore, latency advance in V1 increased across successive cortical layers. Thus, latency advance accumulates along various stages of the visual pathway, likely due to a global increase of membrane conductance in the desynchronized state. This cumulative effect may lead to a dramatic shortening of response latency for neurons in higher visual cortex and play a critical role in fast processing for vigilant animals.state-dependent temporal processing | synaptic inputs | hierarchical accumulation F ast reaction is essential for the survival of animals, such as when detecting and fleeing a predator. Humans or animals react rapidly in a vigilant state (1-3). The vigilance level of animals (also humans) varies with brain state, which can be characterized by the patterns of population activities measured by electroencephalogram (EEG) and local field potential (LFP) (4, 5). Although brain state exhibits diverse activity patterns, it can be broadly classified into a desynchronized state dominated by small-amplitude, high-frequency activities, and a synchronized state dominated by large-amplitude, low-frequency fluctuations (4, 5). The brain operates in the desynchronized state when the animal is alert or vigilant, whereas it operates in the synchronized state when the animal is quiescent or drowsy (4, 5). To understand the neural substrate for fast processing in the vigilant state, it is important to compare response latencies in the two brain states for sensory cortical neurons, which are at the initial stage along the sensorimotor pathway.Brain state has a dominant impact on both resting properties (6, 7) and sensory evoked responses (4, 8, 9) of cortical neurons. For the visual system, although brain state or behavioral state can modulate response amplitude, spatial receptive field, and temporal frequency tuning of the neurons in the early visual pathway (10-13), it is not clear whether brain state can modulate response latency of primary visual cortex (V1) neurons. Furthermore, the ...

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Spatial frequency and orientation tuning dynamics in area V1

Cited by 263 publications

References 28 publications

The organization of orientation and spatial frequency in primary visual cortex

The organization of orientation and spatial frequency in primary visual cortex

Natural Stimulus Statistics Alter the Receptive Field Structure of V1 Neurons

Cumulative latency advance underlies fast visual processing in desynchronized brain state

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