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Статті в журналах з теми "Visual cortical areas"

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Pollen, Daniel A. "Cortical areas in visual awareness." Nature 377, no. 6547 (September 1995): 293–94. http://dx.doi.org/10.1038/377293b0.

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Crick, Francis, and Christof Koch. "Cortical areas in visual awareness." Nature 377, no. 6547 (September 1995): 294–95. http://dx.doi.org/10.1038/377294a0.

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Kallenberger, S., C. Schmidt, T. Wustenberg, and H. Strasburger. "Visual Fusion and Binocular Rivalry in Cortical Visual Areas." Journal of Vision 10, no. 7 (August 3, 2010): 360. http://dx.doi.org/10.1167/10.7.360.

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Vanni, S., L. Henriksson, and A. C. James. "Multifocal fMRI mapping of visual cortical areas." NeuroImage 27, no. 1 (August 2005): 95–105. http://dx.doi.org/10.1016/j.neuroimage.2005.01.046.

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5

Yue, Xiaomin, Sophia Robert, and Leslie G. Ungerleider. "Curvature processing in human visual cortical areas." NeuroImage 222 (November 2020): 117295. http://dx.doi.org/10.1016/j.neuroimage.2020.117295.

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6

Cortes, Nelson, Bruno O. F. de Souza, and Christian Casanova. "Pulvinar Modulates Synchrony across Visual Cortical Areas." Vision 4, no. 2 (April 10, 2020): 22. http://dx.doi.org/10.3390/vision4020022.

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The cortical visual hierarchy communicates in different oscillatory ranges. While gamma waves influence the feedforward processing, alpha oscillations travel in the feedback direction. Little is known how this oscillatory cortical communication depends on an alternative route that involves the pulvinar nucleus of the thalamus. We investigated whether the oscillatory coupling between the primary visual cortex (area 17) and area 21a depends on the transthalamic pathway involving the pulvinar in cats. To that end, visual evoked responses were recorded in areas 17 and 21a before, during and after inactivation of the pulvinar. Local field potentials were analyzed with Wavelet and Granger causality tools to determine the oscillatory coupling between layers. The results indicate that cortical oscillatory activity was enhanced during pulvinar inactivation, in particular for area 21a. In area 17, alpha band responses were represented in layers II/III. In area 21a, gamma oscillations, except for layer I, were significantly increased, especially in layer IV. Granger causality showed that the pulvinar modulated the oscillatory information between areas 17 and 21a in gamma and alpha bands for the feedforward and feedback processing, respectively. Together, these findings indicate that the pulvinar is involved in the mechanisms underlying oscillatory communication along the visual cortex.
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7

Benoliel, Tal, Noa Raz, Tamir Ben-Hur, and Netta Levin. "Cortical functional modifications following optic neuritis." Multiple Sclerosis Journal 23, no. 2 (July 11, 2016): 220–27. http://dx.doi.org/10.1177/1352458516649677.

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Background: We have recently suggested that delayed visual evoked potential (VEP) latencies in the fellow eye (FE) of optic neuritis patients reflect a cortical adaptive process, to compensate for the delayed arrival of visual information via the affected eye (AE). Objective: To define the cortical mechanism that underlies this adaptive process. Methods: Cortical activations to moving stimuli and connectivity patterns within the visual network were tested using functional magnetic resonance imaging (MRI) in 11 recovered optic neuritis patients and in 11 matched controls. Results: Reduced cortical activation in early but not in higher visual areas was seen in both eyes, compared to controls. VEP latencies in the AEs inversely correlated with activation in motion-related visual cortices. Inter-eye differences in VEP latencies inversely correlated with cortical activation following FE stimulation, throughout the visual hierarchy. Functional correlation between visual regions was more pronounced in the FE compared with the AE. Conclusion: The different correlation patterns between VEP latencies and cortical activation in the AE and FE support different pathophysiology of VEP prolongation in each eye. Similar cortical activation patterns in both eyes and the fact that stronger links between early and higher visual areas were found following FE stimulation suggest a cortical modulatory process in the FE.
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8

Smith, Ikuko T., Leah B. Townsend, Ruth Huh, Hongtu Zhu, and Spencer L. Smith. "Stream-dependent development of higher visual cortical areas." Nature Neuroscience 20, no. 2 (January 9, 2017): 200–208. http://dx.doi.org/10.1038/nn.4469.

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Yue, Xiaomin, Amisha Gandhi, and Leslie Ungerleider. "Curvature-biased cortical areas in human visual cortex." Journal of Vision 15, no. 12 (September 1, 2015): 625. http://dx.doi.org/10.1167/15.12.625.

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Andermann, Mark L., Aaron M. Kerlin, Demetris K. Roumis, Lindsey L. Glickfeld, and R. Clay Reid. "Functional Specialization of Mouse Higher Visual Cortical Areas." Neuron 72, no. 6 (December 2011): 1025–39. http://dx.doi.org/10.1016/j.neuron.2011.11.013.

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Дисертації з теми "Visual cortical areas"

1

Ferro, Demetrio. "Effects of attention on visual processing between cortical layers and cortical areas V1 and V4." Doctoral thesis, Università degli studi di Trento, 2019. http://hdl.handle.net/11572/246290.

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Visual attention improves sensory processing, as well as perceptual readout and behavior. Over the last decades, many proposals have been put forth to explain how attention affects visual neural processing. These include the modulation of neural firing rates and synchrony, neural tuning properties, and rhythmic, subthreshold activity. Despite the wealth of knowledge provided by previous studies, the way attention shapes interactions between cortical layers within and between visual sensory areas is only just emerging. To investigate this, we studied neural signals from macaque V1 and V4 visual areas, while monkeys performed a covert, feature-based spatial attention task. The data were simultaneously recorded from laminar electrodes disposed normal to cortical surface in both areas (16 contacts, 150 μm inter-contact spacing). Stimuli presentation was based on the overlap of the receptive fields (RFs) of V1 and V4. Channel depths alignment was referenced to laminar layer IV, based on spatial current source density and temporal latency analyses. Our analyses mainly focused on the study of Local Field Potential (LFP) signals, for which we applied local (bipolar) re-referencing offline. We investigated the effects of attention on LFP spectral power and laminar interactions between LFP signals at different depths, both at the local level within V1 and V4, and at the inter-areal level across V1 and V4. Inspired by current progress from literature, we were interested in the characterization of frequency-specific laminar interactions, which we investigated both in terms of rhythmic synchronization by computing spectral coherence, and in terms of directed causal influence, by computing Granger causalities (GCs). The spectral power of LFPs in different frequency bands showed relatively small differences along cortical depths both in V1 and in V4. However, we found attentional effects on LFP spectral power consistent with previous literature. For V1 LFPs, attention to stimuli in RF location mainly resulted in a shift of the low-gamma (∼30-50 Hz) spectral power peak towards (∼3-4 Hz) higher frequencies and increases in power for frequency bands above low-gamma peak frequencies, as well as decreases in power below these frequencies. For V4 LFPs, attention towards stimuli in RF locations caused a decrease in power for frequencies < 20 Hz and a broad band increase for frequencies > 20 Hz. Attention affected spectral coherence within V1 and within V4 layers in similar way as the spectral power modulation described above. Spectral coherence between V1 and V4 channel pairs was increased by attention mainly in the beta band (∼ 15-30 Hz) and the low-gamma range (∼ 30-50 Hz). Attention affected GC interactions in a layer and frequency dependent manner in complex ways, not always compliant with predictions made by the canonical models of laminar feed-forward and feed-back interactions. Within V1, attention increased feed-forward efficacy across almost all low-frequency bands (∼ 2-50 Hz). Within V4, attention mostly increased GCs in the low and high gamma frequency in a 'downwards' direction within the column, i.e. from supragranular to granular and to infragranular layers. Increases were also evident in an ‘upwards’ direction from granular to supragranular layers. For inter-areal GCs, the dominant changes were an increase in the gamma frequency range from V1 granular and infragranular layers to V4 supragranular and granular layers, as well as an increase from V4 supragranular layers to all V1 layers.
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2

Heuer, Hilary Whetu. "Visual motion analysis in extrastriate cortical areas MT and MST /." For electronic version search Digital dissertations database. Restricted to UC campuses. Access is free to UC campus dissertations, 2003. http://uclibs.org/PID/11984.

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3

Ferro, Demetrio. "Effects of attention on visual processing between cortical layers and cortical areas V1 and V4." Doctoral thesis, Università degli studi di Trento, 2019. http://hdl.handle.net/11572/246290.

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Анотація:
Visual attention improves sensory processing, as well as perceptual readout and behavior. Over the last decades, many proposals have been put forth to explain how attention affects visual neural processing. These include the modulation of neural firing rates and synchrony, neural tuning properties, and rhythmic, subthreshold activity. Despite the wealth of knowledge provided by previous studies, the way attention shapes interactions between cortical layers within and between visual sensory areas is only just emerging. To investigate this, we studied neural signals from macaque V1 and V4 visual areas, while monkeys performed a covert, feature-based spatial attention task. The data were simultaneously recorded from laminar electrodes disposed normal to cortical surface in both areas (16 contacts, 150 μm inter-contact spacing). Stimuli presentation was based on the overlap of the receptive fields (RFs) of V1 and V4. Channel depths alignment was referenced to laminar layer IV, based on spatial current source density and temporal latency analyses. Our analyses mainly focused on the study of Local Field Potential (LFP) signals, for which we applied local (bipolar) re-referencing offline. We investigated the effects of attention on LFP spectral power and laminar interactions between LFP signals at different depths, both at the local level within V1 and V4, and at the inter-areal level across V1 and V4. Inspired by current progress from literature, we were interested in the characterization of frequency-specific laminar interactions, which we investigated both in terms of rhythmic synchronization by computing spectral coherence, and in terms of directed causal influence, by computing Granger causalities (GCs). The spectral power of LFPs in different frequency bands showed relatively small differences along cortical depths both in V1 and in V4. However, we found attentional effects on LFP spectral power consistent with previous literature. For V1 LFPs, attention to stimuli in RF location mainly resulted in a shift of the low-gamma (∼30-50 Hz) spectral power peak towards (∼3-4 Hz) higher frequencies and increases in power for frequency bands above low-gamma peak frequencies, as well as decreases in power below these frequencies. For V4 LFPs, attention towards stimuli in RF locations caused a decrease in power for frequencies < 20 Hz and a broad band increase for frequencies > 20 Hz. Attention affected spectral coherence within V1 and within V4 layers in similar way as the spectral power modulation described above. Spectral coherence between V1 and V4 channel pairs was increased by attention mainly in the beta band (∼ 15-30 Hz) and the low-gamma range (∼ 30-50 Hz). Attention affected GC interactions in a layer and frequency dependent manner in complex ways, not always compliant with predictions made by the canonical models of laminar feed-forward and feed-back interactions. Within V1, attention increased feed-forward efficacy across almost all low-frequency bands (∼ 2-50 Hz). Within V4, attention mostly increased GCs in the low and high gamma frequency in a 'downwards' direction within the column, i.e. from supragranular to granular and to infragranular layers. Increases were also evident in an ‘upwards’ direction from granular to supragranular layers. For inter-areal GCs, the dominant changes were an increase in the gamma frequency range from V1 granular and infragranular layers to V4 supragranular and granular layers, as well as an increase from V4 supragranular layers to all V1 layers.
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4

Knoblauch, Andreas [Verfasser]. "Synchronization and pattern separation in spiking associative memories and visual cortical areas / Andreas Knoblauch." Ulm : Universität Ulm. Fakultät für Informatik, 2004. http://d-nb.info/1015438466/34.

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5

Gieselmann, Marc Alwin. "The role of the primate cortical middle temporal area in visually guided hand movements." [S.l.] : [s.n.], 2004. http://deposit.ddb.de/cgi-bin/dokserv?idn=97349655X.

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Tard, Céline. "Modulation corticale de la locomotion." Thesis, Lille 2, 2015. http://www.theses.fr/2015LIL2S067/document.

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Les patients atteints de maladie de Parkinson présentent des troubles de la marche, parfois paroxystiques, pouvant être aggravés ou améliorés par les stimuli environnementaux. L'attention portée, soit aux stimuli extérieurs, soit à la marche, pourrait ainsi moduler la locomotion.L’objectif principal était donc de mieux caractériser la manière dont les stimuli environnementaux modulent par le biais de réseaux attentionnels la locomotion. Ceci a été étudié chez les sujets sains puis chez les patients parkinsoniens, avec ou sans enrayage cinétique.Nous avons d'abord défini précisément les déficits attentionnels des patients, avec ou sans troubles de la marche. Ils présentaient respectivement des difficultés en flexibilité mentale et plus particulièrement en attention divisée.Nous avons ensuite exploré l'interaction attention-locomotion grâce à l'étude de la préparation motrice. Ainsi, nous avons pu démontrer que les ajustements posturaux anticipés étaient un marqueur sensible de l’attention. Chez les patients, ils pouvaient témoigner d’une altération de l'interaction attention-programmation motrice.L'étude des régions cérébrales activées lors de la locomotion visuo-guidée chez ces patients a permis de confirmer l'implication de structures corticales attentionnelles. Un déséquilibre d’activation au sein du réseau pariéto-prémoteur (nécessaire à la modulation de l'action motrice en fonction des stimuli externes) était présent.Enfin, nous avons essayé de modifier l'excitabilité du cortex prémoteur via des techniques de stimulation magnétique transcrânienne répétitive afin de moduler la locomotion visuo-guidée
Patients with Parkinson 's disease present gait impairments, sometimes sudden and unexpected, either improved or deteriorated with environmental stimuli. Attention focalization, either on external stimuli or on gait, could then modulate locomotion.The main objective was to better characterize how environmental stimuli would modulate locomotion, via attentional networks, in healthy subjects and in parkinsonian patients, with or without freezing of gait.At first, we precisely defined the attentional deficits in patients, with or without gait impairment. They showed altered performance respectively in mental flexibility and in divided attention.Then, we explored the attention-locomotion interaction by studying motor preparation. So, we highlighted that anticipatory postural adjustments were a sensitive marker of attention. In patients, they evidenced an alteration of the attention-motor program interaction.Studying the brain activation during the visuo-driven locomotion in these patients confirmed the involvement of cortical attentional regions. We observed an imbalance inside the parieto-premotor network (useful to modulate motor action according external stimuli)Finally, we tried to change the excitability of the premotor cortex with transcranial magnetic stimulation to modulate visuo-driven locomotion
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7

McKeefry, D. J., M. P. Burton, C. Vakrou, B. T. Barrett, and A. B. Morland. "Induced deficits in speed perception by transcranial magnetic stimulation of human cortical areas V5/MT+ and V3A." 2008. http://hdl.handle.net/10454/6093.

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In this report, we evaluate the role of visual areas responsive to motion in the human brain in the perception of stimulus speed. We first identified and localized V1, V3A, and V5/MT+ in individual participants on the basis of blood oxygenation level-dependent responses obtained in retinotopic mapping experiments and responses to moving gratings. Repetitive transcranial magnetic stimulation (rTMS) was then used to disrupt the normal functioning of the previously localized visual areas in each participant. During the rTMS application, participants were required to perform delayed discrimination of the speed of drifting or spatial frequency of static gratings. The application of rTMS to areas V5/MT and V3A induced a subjective slowing of visual stimuli and (often) caused increases in speed discrimination thresholds. Deficits in spatial frequency discrimination were not observed for applications of rTMS to V3A or V5/MT+. The induced deficits in speed perception were also specific to the cortical site of TMS delivery. The application of TMS to regions of the cortex adjacent to V5/MT and V3A, as well as to area V1, produced no deficits in speed perception. These results suggest that, in addition to area V5/MT+, V3A plays an important role in a cortical network that underpins the perception of stimulus speed in the human brain.
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8

D'Souza, Dany V. [Verfasser]. "An fMRI study of chromatic processing in humans : spatial and temporal characteristics of the cortical visual areas / submitted by Dany V. D'Souza." 2009. http://d-nb.info/1000161021/34.

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Pedersini, Caterina Annalaura. "The neural basis of residual vision and attention in the blind field of hemianopic patients: behavioural, electrophysiological and neuroimaging evidence." Doctoral thesis, 2016. http://hdl.handle.net/11562/939354.

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L’emianopsia è un disturbo visivo caratterizzato da cecità in una porzione del campo, controlaterale alla sede di lesione che coinvolge il circuito visivo. Nonostante tale difficoltà, alcune abilità visive residue (“blindsight”) possono essere mantenute nel campo cieco; la probabilità di riscontrare tale fenomeno risulta incrementata dalla presentazione di stimoli in movimento che possono attivare l’area visiva motoria (hMT) senza passare dall’area visiva primaria (V1). Di conseguenza, un comportamento guidato dalla visione risulta possibile nel campo cieco, in assenza di consapevolezza percettiva. Questo progetto di ricerca è costituito da tre sessioni sperimentali svolte con sei pazienti emianoptici e partecipanti sani, allo scopo di esplorare le basi neurali del “blindsight” o della visione residua, valutare la risposta neurale determinata da stimoli presentati nel campo cieco e valutare se lo spostamento dell’attenzione spaziale verso il campo cieco incrementi la risposta sia neurale che comportamentale. Durante la prima sessione è stata valutata la presenza di “blindsight” o di visione residua esaminando la presenza di un punteggio superiore al caso durante lo svolgimento di compiti di discriminazione di movimento e orientamento di stimoli presentati nel campo cieco. In un paziente su quattro (L.F.) si è ottenuto un punteggio superiore al caso in assenza di consapevolezza percettiva nel compito di discriminazione del movimento. In questo caso il punteggio era associato alla sensazione di presentazione dello stimolo riportata dal paziente, che può rimandare al Blindsight di secondo tipo. Nella seconda parte è stata svolta una sessione di neuroimaging (fMRI) utilizzando uno scanner a 3Tesla, allo scopo di i) valutare la presenza di anormalità nella rappresentazione corticale del campo cieco, all’interno della corteccia visiva (Retinotopic Mapping), ii) valutare la posizione e l’attivazione dell’area hMT (hMT Localizer) e iii) valutare la connettività strutturale e l’integrità delle fibre di sostanza bianca nello stesso paziente (Imaging con Tensore di Diffusione, DTI). Nel paziente A.G. abbiamo riscontrato un’ organizzazione retinotopica delle aree visive di basso livello in entrambi gli emisferi, nonostante la lesione interessasse prevalentemente la porzione dorsale della corteccia visiva primaria di sinistra (Retinotopic Mapping); abbiamo osservato l’attivazione dell’area hMT nell’emisfero leso (hMT Localizer) e l’integrità delle vie visive ad eccezione delle radiazioni ottiche nell’ area lesa (DTI). Durante la terza sessione è stato utilizzato un approccio elettrofisiologico. Per ottenere una risposta affidabile presentando stimoli nel campo cieco, è stata utilizzata la tecnica dei potenziali evocati Steady-state (SSVEP) che ha dimostrato essere più informativa rispetto ai potenziali evocati transienti in questo tipo di pazienti. La sessione includeva una stimolazione passiva e un compito di attenzione. L’obiettivo della prima era di valutare la risposta a stimoli che “sfarfallavano” (flickering) ad una frequenza specifica all’interno dei quattro quadranti; è stato osservato che in tutti i pazienti la presentazione dello stimolo nel quadrante cieco produceva una modulazione della risposta neurale che coinvolgeva entrambi gli emisferi. Nel compito di attenzione l’orientamento di quest’ultima verso il campo cieco determinava un incremento della risposta evocata rispetto alla condizione di non attenzione, anche quando quest’ultima veniva rivolta verso il campo cieco, seppur in assenza di consapevolezza percettiva. E’ stata confermata quindi l’utilità degli SSVEP nella valutazione della risposta neurale in seguito alla presentazione di stimoli nel campo cieco. Questi risultati rappresentano un punto chiave interessante per lo studio delle basi neurali della visione inconsapevole in quanto dimostrano come stimoli presentati nel campo cieco possano determinare un’ attività neurale attendibile in varie aree corticali.
Hemianopia is a visual field defect characterized by blindness in the hemifield contralateral to the side of a lesion of the central visual pathway. Despite this loss of vision, it has been shown that some unconscious visual abilities (“blindsight”) might be present in the blind field; the probability of finding this phenomenon can be increased by presenting moving stimuli in the blind field which activate the motion visual area (hMT), bypassing the damaged primary visual area (V1). As a consequence, visually guided behaviour is made possible but perceptual awareness is lacking. The present research project consists of three experimental sessions carried out with six hemianopic patients and healthy participants, in order to explore the neural basis of blindsight or residual vision, to assess whether unseen visual stimuli presented to the blind field can evoke neural responses in the lesioned or intact hemisphere and to evaluate whether shifts of spatial attention to the blind field can enhance these responses as well as the behavioral performance. In the first session we assessed the presence of blindsight or conscious residual vision by testing for the presence of unconscious above chance performance in motion and orientation discrimination tasks with stimuli presented to the blind area. We found evidence of unconscious above chance performance in one patient (L.F.) in the Motion Discrimination Task. In this case the above chance performance was associated with a feeling of something occurring on the screen, reported by the patient that resembles the so-called Blindsight Type II. In the second session we used a neuroimaging technique with the purpose of: i) assess the presence of abnormalities in the cortical representation of the blind visual field in the visual cortex, ii) evaluate position and activation of area hMT and iii) assess the structural connectivity and the integrity of white matter fibers in the same patient. To do that, by using a 3 Tesla Scanner, we carried out a fMRI session with Retinotopic Mapping, hMT Localizer and Diffusion Tensor Imaging procedures (DTI). In patient A.G. we found a retinotopic organization of low-level visual areas in the blind as well as in the intact hemisphere, despite the lesion involving mainly the dorsal portion of the left primary visual cortex. Importantly, we documented an activation of area hMT in the damaged hemisphere and the integrity of the entire visual pathways except for the optic radiations in the area of the lesion. In the third session we used an electrophysiological approach to study the neural basis of attention in the blind field of hemianopics. In order to obtain a reliable response with stimuli presented to the blind field, we used the Steady-State Evoked-Potentials (SSVEP) technique that is likely to be more informative than transient Visual Evoked Potentials in these kind of patients. This session included a passive stimulation and an attentional task. The former was performed to assess the response to stimuli flickering at a specific frequency in four visual field quadrants, two in the left and two in the right hemifield. In this session, we found in all hemianopic patients that visual stimuli presented to the blind hemifield produced a modulation of the neural response involving the damaged as well as the intact hemisphere. In the attentional task we found that orienting attention toward the blind field yielded an enhanced evoked response with respect to the non-orienting condition, even toward the blind field despite lack of perceptual awareness. Thus, SSVEP confirmed to be a useful means to assess a neural response following stimulus presentation in a blind field. In a broader perspective these results represent novel interesting evidence on the neural bases of unconscious vision in that they show that despite being unseen visual stimuli presented to the blind field elicit reliable neural activity in various cortical areas.
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Bair, Wyeth. "Analysis of temporal structure in spike trains of visual cortical area MT." Thesis, 1996. https://thesis.library.caltech.edu/7600/2/Bair%201996.pdf.

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The temporal structure of neuronal spike trains in the visual cortex can provide detailed information about the stimulus and about the neuronal implementation of visual processing. Spike trains recorded from the macaque motion area MT in previous studies (Newsome et al., 1989a; Britten et al., 1992; Zohary et al., 1994) are analyzed here in the context of the dynamic random dot stimulus which was used to evoke them. If the stimulus is incoherent, the spike trains can be highly modulated and precisely locked in time to the stimulus. In contrast, the coherent motion stimulus creates little or no temporal modulation and allows us to study patterns in the spike train that may be intrinsic to the cortical circuitry in area MT. Long gaps in the spike train evoked by the preferred direction motion stimulus are found, and they appear to be symmetrical to bursts in the response to the anti-preferred direction of motion. A novel cross-correlation technique is used to establish that the gaps are correlated between pairs of neurons. Temporal modulation is also found in psychophysical experiments using a modified stimulus. A model is made that can account for the temporal modulation in terms of the computational theory of biological image motion processing. A frequency domain analysis of the stimulus reveals that it contains a repeated power spectrum that may account for psychophysical and electrophysiological observations.

Some neurons tend to fire bursts of action potentials while others avoid burst firing. Using numerical and analytical models of spike trains as Poisson processes with the addition of refractory periods and bursting, we are able to account for peaks in the power spectrum near 40 Hz without assuming the existence of an underlying oscillatory signal. A preliminary examination of the local field potential reveals that stimulus-locked oscillation appears briefly at the beginning of the trial.

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Книги з теми "Visual cortical areas"

1

Saalmann, Yuri B., and Sabine Kastner. Neural Mechanisms of Spatial Attention in the Visual Thalamus. Edited by Anna C. (Kia) Nobre and Sabine Kastner. Oxford University Press, 2014. http://dx.doi.org/10.1093/oxfordhb/9780199675111.013.013.

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Neural mechanisms of selective attention route behaviourally relevant information through brain networks for detailed processing. These attention mechanisms are classically viewed as being solely implemented in the cortex, relegating the thalamus to a passive relay of sensory information. However, this passive view of the thalamus is being revised in light of recent studies supporting an important role for the thalamus in selective attention. Evidence suggests that the first-order thalamic nucleus, the lateral geniculate nucleus, regulates the visual information transmitted from the retina to visual cortex, while the higher-order thalamic nucleus, the pulvinar, regulates information transmission between visual cortical areas, according to attentional demands. This chapter discusses how modulation of thalamic responses, switching the response mode of thalamic neurons, and changes in neural synchrony across thalamo-cortical networks contribute to selective attention.
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Cohen, Marlene R., and John H. R. Maunsell. Neuronal Mechanisms of Spatial Attention in Visual Cerebral Cortex. Edited by Anna C. (Kia) Nobre and Sabine Kastner. Oxford University Press, 2014. http://dx.doi.org/10.1093/oxfordhb/9780199675111.013.007.

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Attention is associated with improved performance on perceptual tasks and changes in the way that neurons in the visual system respond to sensory stimuli. While we now have a greater understanding of the way different behavioural and stimulus conditions modulate the responses of neurons in different cortical areas, it has proven difficult to identify the neuronal mechanisms responsible for these changes and establish a strong link between attention-related modulation of sensory responses and changes in perception. Recent conceptual and technological advances have enabled progress and hold promise for the future. This chapter focuses on newly established links between attention-related modulation of visual responses and bottom-up sensory processing, how attention relates to interactions between neurons, insights from simultaneous recordings from groups of cells, and how this knowledge might lead to greater understanding of the link between the effects of attention on sensory neurons and perception.
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Clark, Kelsey L., Behrad Noudoost, Robert J. Schafer, and Tirin Moore. Neuronal Mechanisms of Attentional Control. Edited by Anna C. (Kia) Nobre and Sabine Kastner. Oxford University Press, 2014. http://dx.doi.org/10.1093/oxfordhb/9780199675111.013.010.

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Covert spatial attention prioritizes the processing of stimuli at a given peripheral location, away from the direction of gaze, and selectively enhances visual discrimination, speed of processing, contrast sensitivity, and spatial resolution at the attended location. While correlates of this type of attention, which are believed to underlie perceptual benefits, have been found in a variety of visual cortical areas, more recent observations suggest that these effects may originate from frontal and parietal areas. Evidence for a causal role in attention is especially robust for the Frontal Eye Field, an oculomotor area within the prefrontal cortex. FEF firing rates have been shown to reflect the location of voluntarily deployed covert attention in a variety of tasks, and these changes in firing rate precede those observed in extrastriate cortex. In addition, manipulation of FEF activity—whether via electrical microstimulation, pharmacologically, or operant conditioning—can produce attention-like effects on behaviour and can modulate neural signals within posterior visual areas. We review this evidence and discuss the role of the FEF in visual spatial attention.
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Schoenen, Jean, Valentin Bohotin, and Alain Maertens De Noordhout. Tms in Migraine. Edited by Charles M. Epstein, Eric M. Wassermann, and Ulf Ziemann. Oxford University Press, 2012. http://dx.doi.org/10.1093/oxfordhb/9780198568926.013.0024.

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Transcranial magnetic stimulation (TMS) has been used to search for cortical dysfunction in migraine. Both, the motor and the visual cortices have been explored in this area. This article reviews and discusses the results of the various studies performed in migraine patients with TMS of motor or visual cortices. The majority of evoked and event-related potential studies in migraine have shown two abnormalities: increased amplitude of grand averaged responses and lack of habituation in successive blocks of averaged responses with decreased amplitude in the first block. These abnormalities suggest that the excitability state of the cerebral cortex, particularly of the visual cortex, is abnormal in migraineurs between attacks. The use of TMS to assess motor and visual cortex excitability has yielded conflicting results, which could be due to methodological differences. Taken together, all studies indicate that the changes in cortical reactivity are more complex in migraineurs than initially thought and suggest that both larger multidisciplinary studies and focused analyses of subgroups of patients with more refined clinical phenotypes are necessary to disentangle the role of the cerebral cortex in migraine pathophysiology.
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Rajan, Shobana, and Vibha Mahendra. Awake Craniotomy. Edited by David E. Traul and Irene P. Osborn. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780190850036.003.0003.

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Awake craniotomies are performed when the site of surgical instrumentation or resection directly involves or abuts eloquent areas of the brain and require a cooperative patient, a tailored neuroanesthetic technique, and good teamwork. Eloquent cortex refers to any cortical region in which injury produces a symptomatic cognitive or motor deficit and includes the primary sensorimotor cortex, essential speech areas, occipital visual areas, and mesial temporal regions crucial for episodic memory. An awake patient allows for intraoperative testing of motor, speech, or sensation function while removing or manipulating brain tissue. The two principal aims of resection of a brain tumor or an epileptic focus are to maximize excision of the offending lesion for better prognosis while minimizing or avoiding damage to surrounding brain tissue. Damage to adjacent brain tissue can be catastrophic, especially if the tumor or epileptogenic areas are located close to the eloquent regions of the brain.
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Anderson, James A. The Brain Doesn’t Work by Logic. Oxford University Press, 2018. http://dx.doi.org/10.1093/acprof:oso/9780199357789.003.0008.

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This chapter gives three examples of real neural computation. The conclusion is that the “brain doesn’t work by logic.” First, is the Limulus (horseshoe crab) lateral eye. The neural process of “lateral inhibition” tunes the neural response of the compound eye to allow crabs to better see other crabs for mating. Second, the retina of the frog contains cells that are selective to specific properties of the visual image. The frog responds strongly to the moving image of a bug with one class of selective retinal receptors. Third, experiments on patients undergoing neurosurgery for epilepsy found single neurons in several cortical areas that were highly selective to differing images, text strings, and spoken names of well-known people. In addition, new selective responses could be formed quickly. The connection to concepts in cognitive science seems inevitable. One possible mechanism is through associatively linked “cell assemblies.”
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Prasad, Girijesh. Brain–machine interfaces. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780199674923.003.0049.

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A brain–machine interface (BMI) is a biohybrid system intended as an alternative communication channel for people suffering from severe motor impairments. A BMI can involve either invasively implanted electrodes or non-invasive imaging systems. The focus in this chapter is on non-invasive approaches; EEG-based BMI is the most widely investigated. Event-related de-synchronization/ synchronization (ERD/ERS) of sensorimotor rhythms (SMRs), P300, and steady-state visual evoked potential (SSVEP) are the three main cortical activation patterns used for designing an EEG-based BMI. A BMI involves multiple stages: brain data acquisition, pre-processing, feature extraction, and feature classification, along with a device to communicate or control with or without neurofeedback. Despite extensive research worldwide, there are still several challenges to be overcome in making BMI practical for daily use. One such is to account for non-stationary brainwaves dynamics. Also, some people may initially find it difficult to establish a reliable BMI with sufficient accuracy. BMI research, however, is progressing in two broad areas: replacing neuromuscular pathways and neurorehabilitation.
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Butz, Martin V., and Esther F. Kutter. Primary Visual Perception from the Bottom Up. Oxford University Press, 2017. http://dx.doi.org/10.1093/acprof:oso/9780198739692.003.0008.

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This chapter addresses primary visual perception, detailing how visual information comes about and, as a consequence, which visual properties provide particularly useful information about the environment. The brain extracts this information systematically, and also separates redundant and complementary visual information aspects to improve the effectiveness of visual processing. Computationally, image smoothing, edge detectors, and motion detectors must be at work. These need to be applied in a convolutional manner over the fixated area, which are computations that are predestined to be solved by means of cortical columnar structures in the brain. On the next level, the extracted information needs to be integrated to be able to segment and detect object structures. The brain solves this highly challenging problem by incorporating top-down expectations and by integrating complementary visual information aspects, such as light reflections, texture information, line convergence information, shadows, and depth information. In conclusion, the need for integrating top-down visual expectations to form complete and stable perceptions is made explicit.
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Pinna, Baingio. On the Pinna Illusion. Oxford University Press, 2017. http://dx.doi.org/10.1093/acprof:oso/9780199794607.003.0074.

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The Pinna illusion is the first case of visual illusion showing a rotating motion phenomenon. Squares, arranged in two concentric rings, show a strong counter-rotation effect. The inner ring of the squares appears to rotate counterclockwise and the outer ring clockwise when the observer’s head is slowly moved toward the figure while the gaze is kept fixed in the center of the stimulus pattern. The direction of rotation is reversed when the observer’s head moves away from the stimulus. The speed of the illusory rotation is proportional to the one of the motion imparted by the observer. While the way each individual check receives a local illusory motion signal can be explained by the response of direction-selective neurons at the earliest cortical stage of visual processing, the whole illusory rotational motion can be thought to be sensed by the higher cortical area, which collates all the signals provided by the local motion checks.
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Schlaug, Gottfried. Music, musicians, and brain plasticity. Edited by Susan Hallam, Ian Cross, and Michael Thaut. Oxford University Press, 2012. http://dx.doi.org/10.1093/oxfordhb/9780199298457.013.0018.

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This article reviews studies on the brains of musicians. Making music not only engages primary auditory and motor regions and the connections between them, but also regions that integrate and connect areas involved in both auditory and motor operations, as well as in the integration of other multisensory information. Professional instrumentalists learn and repeatedly practice associating hand/finger movements with meaningful patterns in sound, and sounds and movements with specific visual patterns (notation) while receiving continuous multisensory feedback. Learning to associate actions with particular sounds leads to functional but also structural changes in frontal cortices.
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Частини книг з теми "Visual cortical areas"

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Gulyás, Balázs. "Functional Organization of Human Visual Cortical Areas." In Extrastriate Cortex in Primates, 743–75. Boston, MA: Springer US, 1997. http://dx.doi.org/10.1007/978-1-4757-9625-4_16.

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Taylor, N. R., M. Hartley, and J. G. Taylor. "Coding of Objects in Low-Level Visual Cortical Areas." In Artificial Neural Networks: Biological Inspirations – ICANN 2005, 57–63. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11550822_10.

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Ahlfors, S. P., H. J. Aronen, J. W. Belliveau, A. M. Dale, M. Huotilainen, R. J. Ilmoniemi, A. Korvenoja, et al. "Spatiotemporal Imaging of Human Cortical Areas Sensitive to Visual Motion." In Biomag 96, 701–4. New York, NY: Springer New York, 2000. http://dx.doi.org/10.1007/978-1-4612-1260-7_171.

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Troncoso, Xoana G., Stephen L. Macknik, and Susana Martinez-Conde. "Vision’s First Steps: Anatomy, Physiology, and Perception in the Retina, Lateral Geniculate Nucleus, and Early Visual Cortical Areas." In Visual Prosthetics, 23–57. Boston, MA: Springer US, 2011. http://dx.doi.org/10.1007/978-1-4419-0754-7_2.

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Rolls, Edmund T. "Information Processing in the Temporal Lobe Visual Cortical Areas of Macaques." In Research Notes in Neural Computing, 339–52. Berlin, Heidelberg: Springer Berlin Heidelberg, 1991. http://dx.doi.org/10.1007/978-3-642-84545-1_22.

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Hogan, Dale, and Nancy E. J. Berman. "Emergence of Visual Cortical Areas: Patterns of Development of Neuropeptide-Y Immunoreactivity and Somatostatin-Immunoreactivity in the Cat." In The Changing Visual System, 385–89. Boston, MA: Springer US, 1991. http://dx.doi.org/10.1007/978-1-4615-3390-0_33.

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Gattass, R., A. P. B. Sousa, and E. Covey. "Cortical Visual Areas of the Macaque: Possible Substrates for Pattern Recognition Mechanisms." In Experimental Brain Research Supplementum, 1–20. Berlin, Heidelberg: Springer Berlin Heidelberg, 1985. http://dx.doi.org/10.1007/978-3-662-09224-8_1.

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Brodal, Per, and Jan G. Bjaalie. "Quantitative Studies of Pontine Projections from Visual Cortical Areas in the Cat." In Cerebellum and Neuronal Plasticity, 41–62. Boston, MA: Springer US, 1987. http://dx.doi.org/10.1007/978-1-4613-0965-9_3.

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Eckhorn, Reinhard, Thomas Schanze, Michael Brosch, Wageda Salem, and Roman Bauer. "Stimulus-Specific Synchronizations in Cat Visual Cortex: Multiple Microelectrode and Correlation Studies from Several Cortical Areas." In Induced Rhythms in the Brain, 47–80. Boston, MA: Birkhäuser Boston, 1992. http://dx.doi.org/10.1007/978-1-4757-1281-0_3.

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Vaina, Lucia Maria, Finnegan Calabro, Fa-Hsuan Lin, and Matti S. Hämäläinen. "Long-Range Coupling of Prefrontal Cortex and Visual (MT) or Polysensory (STP) Cortical Areas in Motion Perception." In IFMBE Proceedings, 298–301. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-12197-5_69.

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Тези доповідей конференцій з теми "Visual cortical areas"

1

Baseler, H. A., B. A. Wandell, A. B. Morland, S. R. Jones, and K. H. Ruddock. "Activity in the visual cortex of a hemianope measured using fMRI." In Vision Science and its Applications. Washington, D.C.: Optica Publishing Group, 1997. http://dx.doi.org/10.1364/vsia.1997.suc.3.

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Functional magnetic resonance imaging (fMRI) can be used to identify and map visual areas in the cerebral cortex of visually normal humans (Engel et al., in press). Here, we use the methods that have been developed on normal observers to assess the neural responses in subject, G.Y., who has cortical damage that includes left area V1. This subject has reported limited sensation of select stimuli beyond 2.5 deg in his right peripheral visual field (Barbur et al. 1980). Here we report preliminary analyses of the organization of this subject’s visual areas, and we describe some of the cortical signals that occur when stimuli are presented to the subject’s “blind” visual field.
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Movshon, J. Anthony. "Organization of primate visual cortex." In OSA Annual Meeting. Washington, D.C.: Optica Publishing Group, 1989. http://dx.doi.org/10.1364/oam.1989.tuj1.

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The monkey's visual cortex contains more than two dozen separate areas, comprising in all about half the cerebral cortex. Each area provides a representation of the visual scene, and the existence of these multiple representations suggests that different areas may be specialized for the analysis of different aspects of the visual world. This tutorial reviews experimental evidence on functional specialization in the cortex and considers the validity and utility of this mosiac conception of cortical function.
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ROLLS, EDMUND T. "FUNCTIONS OF THE PRIMATE TEMPORAL LOBE CORTICAL VISUAL AREAS IN INVARIANT VISUAL OBJECT AND FACE RECOGNITION." In Proceedings of the International School of Biophysics. WORLD SCIENTIFIC, 2001. http://dx.doi.org/10.1142/9789812799975_0035.

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Gilbert, Charles. "Color processing in visual cortex." In Advances in Color Vision. Washington, D.C.: Optica Publishing Group, 1992. http://dx.doi.org/10.1364/acv.1992.fc1.

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Wavelength specific cells in visual cortex are grouped together into compartments that are interdigitated between other compartments specializing in form, movement and depth. The first evidence for a functional organization of color based on cortical area came from the work of Semir Zeki, who described an area prestriate cortex, known as area V4, that was enriched for color specific cells. Other cortical areas also contained wavelength selective cells, but the precise distribution of these cells eluded investigators for a number of years until the discovery by Margaret Wong- Riley that in area VI the enzyme cytochrome oxidase (CO) was distributed in a regular series of patches, as seen in tangential sections through the superficial cortical layers. Using CO histochemistry, David Hubei and Margaret Livingstone found that wavelength selective cells were located within these patches or "blobs", with broadband, orientation selective cells being found predominantly outside them. This lent support to the idea that color, as represented by wavelength selective cells, and form, as represented by orientation selective cells, were analyzed by separate, parallel pathways in the visual system. This left open, however, the question of how information about form and color might be attributed to a particular object, the so called "binding" problem, and also about how boundaries made by different colors could provide information about form. In fact, the existence of cells selective both for wavelength and for orientation had been known from a number of studies, and Ts'o and Gilbert found that such cells tended to lie at the boundaries of the CO blobs. With regard to the color selectivity found within the blobs, they found that cells sharing similar color opponency were grouped into columns, and that individual blobs specialized in either red-green or blue-yellow opponency.
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Carney, Thom, Justin Ales, and Stanley A. Klein. "Combining MRI and VEP imaging to isolate the temporal response of visual cortical areas." In Electronic Imaging 2008, edited by Bernice E. Rogowitz and Thrasyvoulos N. Pappas. SPIE, 2008. http://dx.doi.org/10.1117/12.773383.

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ROLLS, EDMUND T. "FUNCTIONS OF THE PRIMATE TEMPORAL LOBE CORTICAL VISUAL AREAS IN INVARIANT VISUAL OBJECT AND FACE RECOGNITION: COMPUTATIONAL MECHANISMS." In Proceedings of the International School of Biophysics. WORLD SCIENTIFIC, 2001. http://dx.doi.org/10.1142/9789812799975_0036.

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Cronin-Golomb, Alice, S. Corkin, and J. H. Growdon. "Alzheimer’s disease: a disorder of the precortical visual system?" In OSA Annual Meeting. Washington, D.C.: Optica Publishing Group, 1986. http://dx.doi.org/10.1364/oam.1986.tut1.

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Alzheimer’s disease (AD) is characterized by maximal degeneration of the parietal and temporal lobes with relative sparing of primary visual areas. As may be expected from this pattern of degeneration, AD patients as a group are widely impaired on tests of higher-order visuospatial function, whereas only a minority show deficiencies in color vision, Vernier acuity, and stereoacuity. This pattern of functional sparing of basic visual processes does not hold, however, for contrast sensitivity function, which is commonly impaired at all spatial frequencies in patients with AD, relative to age-matched controls.1 In cats, ablation of the striate cortex results in only modest changes in contrast sensitivity function; furthermore, blocking the ON channel in the monkey retina affects contrast sensitivity but not color discrimination, acuity, motion detection or stereopsis. Thus contrast sensitivity, unlike the other basic visual functions we have measured in AD, may involve precortical brain areas. In light of a recent report of optic nerve degeneration and retinal changes in AD,2 these observations raise the intriguing possibility that, as far as basic visual processes are concerned, AD is a precortical, not a cortical disease.
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Carman, George J. "The function of topography in the visual pathway." In OSA Annual Meeting. Washington, D.C.: Optica Publishing Group, 1992. http://dx.doi.org/10.1364/oam.1992.fo6.

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Such basic functions of vision as stereopsis and kineopsis can be accomplished through the use of topographic mappings of the visual field, such as those seen in the primate visual pathway. In binocular or motion parallax viewing, parallax cues to depth are contained in pairs of images that differ locally by a combination of translations, rotations, and dilations. These generalized disparities can be represented by a pair of scaler harmonic potentials defined on the visual field. These potentials are used to determine a flow of visual information that nulls these disparities so as to fuse the pair of images. The values of these potentials at each point of the visual field are computed through use of a Green’s function, which contains an explicit specification of a composition of conformal mappings of the visual field. These mappings may be interpreted as a sequence of topographic transformations of the visual field and are qualitatively similar to those seen in the lateral geniculate nucleus (LGN) and the primary and secondary cortical areas (V1 and V2) of the primate visual pathway.
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Shipley, Thorne. "Visual contours in homogeneous space: revisited." In OSA Annual Meeting. Washington, D.C.: Optica Publishing Group, 1989. http://dx.doi.org/10.1364/oam.1989.wcc8.

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In 1965 (Science 150, 348-350) I first showed that stereoscopic depth contours could be generated across large homogeneous central regions of visual space and that these contours were real in that they reversed directly when the sign of the disparity in the frame also reversed, provided that the inducing frame(s) was of sufficient strength. I left the issue unsettled as to what that strength must consist of. Much work has been done by others since, but no one seems to have advanced significantly on this key issue. It thus seemed worthwhile to devise some new targets and to repeat and extend the early measurements. These contours seem limited to a range of ~5° of visual angle, and they are most robust, paradoxically perhaps, when they pass directly across the foveal region, hence, between the two interhemispherical cortical projection areas. Consequently, neural processes must extend over these ranges, and any adequate model of stereopsis must take account of this impressive low frequency global event. The contrast to high spatial frequency stereoacuity processes seems worthy, also, of reemphasis.
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Sereno, Margaret E. "Neural network model for the measurement of visual motion." In OSA Annual Meeting. Washington, D.C.: Optica Publishing Group, 1986. http://dx.doi.org/10.1364/oam.1986.wi4.

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A neurallike model (a Boltzmann machine) was built to extract the true 2-D motion of an entire pattern from ambiguous local motion information available at the pattern’s component contours (i.e., it solves the aperture problem). The model has an input and output layer representing visual cortical areas V1 and MT, respectively. Area MT, an area involved in motion analysis, receives a direct topographic projection from V1. V1 neurons act as local motion detectors in that they can only measure the component of motion perpendicular to the orientation of a moving contour. In contrast, ~20% of MT neurons possess pattern direction selectivity—selectivity for the motion of a pattern as a whole. In the model, each unit is selective for a specific speed and direction of motion. Connectivity is restricted so that each V1 unit projects only to the MT units with which it is consistent (i.e., that could describe its true motion). The input to the system is the set of velocity vectors perpendicular to the contours of a moving pattern. Input units are clamped to represent the input, and the system is allowed to relax to find the state which represents the minimum energy configuration given the input. The network relaxes quickly and the MT units describing the motion of the entire pattern are maximally activated.
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