Esta pesquisa pretendia estabelecer um mapa espaço temporal das respostas de vernier no córtex visual humano. O uso do potencial visual provocado de varredura (PVPv) proporciona medidas eficientes e sensíveis dos limiares de vernier com os quais se pode começar a examinar as respostas corticais de vernier no âmbito dos parâmetros espaço temporais. As respostas de vernier foram avaliadas em relação à hipótese de que os sinais retinianos provenientes das células ganglionares da via magnocelular e não da via parvocelular compõem o input neural para córtex que é utilizado para gerar as respostas de vernier (tarefas de localização de alta precisão Lee et a., 1990; Lee et al., 1995). Métodos: As respostas de vernier no córtex humano foram medidas por meio do potencial visual provocado de varredura (PVPv). Quebras de vernier foram introduzidas em grades de ondas quadradas de produzindo colunas verticais intercaladas de barras estáticas e móveis. Medidas binoculares da acuidade vernier foram feitas em grades de alto contraste (64%) em função de 3 frequências temporais (3, 6 e 15 Hz) e 2 frequências espaciais (1 e 8 c/g). Medidas utilizando grades de baixo contraste foram feitas em função de 3 frequências temporais (3, 6 e 10Hz) e 3 frequências espaciais (1, 2 e 8c/g) em ambos os protocolos (alto e baixo contraste) as medidas foram feitas utilizando o PVPv. Foi utilizado o sistema POWER DIVA que utiliza a metodologia dos mínimos quadrados recursivos para extrair a amplitude e fase da resposta nos harmônicos selecionados da frequência do estímulo. Foram analisados o primeiro (1F1) e o segundo (2F1) harmônicos neste estudo. Com base em estudos anteriores, assume-se que o primeiro componente harmônico refere-se às respostas ao estímulo de vernier, e o segundo às respostas ao movimento relativo dos elementos do estímulo. Esta hipótese foi testada por meio da utilização de protocolos controle para ambos os arranjos de estímulos (alto e baixo contraste) em que foram utilizados os mesmos parâmetros, porém com deslocamentos entre as barras completamente simétricos (elementos da grade jamais se alinhavam). O sistema POWER DIVA calcula para cada segundo de janela de análise (bin) a amplitude local. A amplitude média do ruído nos 10 bins de análise é utilizada para calcular a razão sinal ruído para cada bin. Apenas sinais com razão sinal ruído maior que 3 foram considerados resposta. A média vetorial de 8 tentativas para cada condição de estímulo foi utilizada para determinar os limiares.Resultados: Os dados são consistentes com dados psicofísicos anteriores, especialmente os dados de Bradley & Skottun (1987) que demonstraram decréscimo significativo nos limiares de vernier com o aumento da frequência espacial. Os limiares eletrofisiológicos de vernier obtidos com o presente trabalho mostraram-se paralelos aos dados psicofísicos em função das frequências espaciais em ambos os protocolos. Os limiares no 1F1 também demonstraram redução significativa com o aumento da frequência temporal em altas frequências espaciais / The research was directed at establishing a spatiotemporal map of human cortical vernier responses. The use of swept-parameter, steady state visual evoked potential (sweep VEP, or sVEP) provides efficient and sensitive measurement of vernier thresholds with which to begin to examine cortical vernier responses over the spatio-temporal parameter space. The vernier responses were evaluated in relation to the hypothesis that the magnocellular (M) but not parvocellular (P) ganglion cell retinal output forms the neural input to cortex that is used to derive vernier (high precision localization task - Lee et al., 1990; Lee et al., 1995). Methods: Human cortical vernier responses were measured using the sweep visual evoked potential (sVEP). Vernier offsets are introduced into a square wave grating producing interleaved vertical columns of moving and static bars. Binocular measurements of the vernier acuity were made using high contrast (64%) gratings as a function of 3 temporal frequencies (TF = 3, 6 and 15 Hz) and 2 spatial frequencies (SF = 1 and 8 c/g). Measurements were also made at low contrast (8%) as a function of 3 temporal frequencies (3, 6 and 10Hz) and 3 spatial frequencies (1, 2 and 8c/g) using the sVEP. The POWER DIVA system uses the recursive least squares to extract the response amplitude and phase at selected harmonics of the stimulus frequency. We analyzed the evoked potentials at the first (1F1 fundamental) and second (2F1) harmonics. Based on prior research, we take the 1F1 component to be the specific response to the periodic vernier onset/offset, while the 2F1 component reflects local relative motion responses. We checked this assumption by also measuring sVEPs using a motion control protocol in which equivalent displacement amplitudes were presented in and identical stimulus array, but with the displacements being completely symmetrical alternations between two states of misalignment (grating elements were never aligned). To ensure that the amplitude data used for the regression and extrapolation to threshold is really a response to stimulus instead of noise, POWER DIVA calculates, for each 1-second analysis window (time bin), a local noise amplitude. The mean noise amplitude across 10 analysis bins is used to calculate the signal to noise ratio for each time bin. Only signals with a signal to noise ratio > 3 were considered as a response. The vector average of at least 8 trials was used to determine thresholds. Results: The data are consistent with some comparable prior psychophysical data, especially data from Bradley & Skottun (1987) who showed significant decrease in the vernier thresholds with the increase of spatial frequency. Our cortical (sVEP) vernier thresholds paralleled the psychophysical data as a function of SF in both protocols. The 1F1 (vernier) thresholds also exhibited a significant decrease with increase of temporal frequency at high SF

The perirhinal cortex (PRC) is a medial temporal lobe (MTL) structure known to be involved in assessing whether an object is familiar (i.e., meaningful) or novel. Recent evidence shows that the PRC is sensitive to the familiarity of both whole object configurations and their parts, and suggests the PRC may modulate part familiarity responses in V2. Here, using functional magnetic resonance imaging (fMRI), we investigated age-related decline in the PRC's sensitivity to part/configuration familiarity and assessed its functional connectivity to visual cortex in young and older adults. Participants categorized peripherally presented silhouettes as familiar ("real-world") or novel. Part/configuration familiarity was manipulated via three silhouette configurations: Familiar (parts/configurations familiar), Control Novel (parts/configurations novel), and Part-Rearranged Novel (parts familiar, configurations novel). "Real-world" judgments were less accurate than "novel" judgments, although accuracy did not differ between age groups. The fMRI data revealed differential neural activity, however: In young adults, a linear pattern of activation was observed in left hemisphere (LH) PRC, with Familiar > Control Novel > Part-Rearranged Novel. Older adults did not show this pattern, indicating age-related decline in the PRC's sensitivity to part/configuration familiarity. A functional connectivity analysis revealed a significant coupling between the PRC and V2 in the LH in young adults only. Older adults showed a linear pattern of activation in the temporopolar cortex (TPC), but no evidence of TPC-V2 connectivity. This is the first study to demonstrate age-related decline in the PRC's representations of part/configuration familiarity and its covariance with visual cortex.

Le cerveau montre d’étonnantes capacités d’adaptation aux modifications des entrées sensorielles, celles-ci pouvant avoir pour origine une modification de l’environnement ou être liées à une pathologie de l’organe récepteur lui-même. Les techniques d’imagerie fonctionnelle permettent d’étudier l’impact d’une atteinte du récepteur sensoriel du système visuel, la rétine, sur le fonctionnement et les capacités de réorganisation du cortex visuel primaire. Le but de ce travail était d’ouvrir des pistes de recherche sur les conséquences fonctionnelles centrales et périphériques de pathologies oculaires se manifestant toute par un scotome visuel important. Dans un premier temps, nous avons étudié l’organisation fonctionnelle du cortex visuel humain en Imagerie par Résonance Magnétique fonctionnelle (IRMf) à haut champ (3T). Le but de cette étude était de cartographier et de délimiter de manière reproductible les aires visuelles de bas niveau (V1, V2 et V3) par la réalisation de cartes corticales rétinotopiques. Nous avons développé un protocole expérimental spécifique afin d’étudier, chez le sujet sain, les modifications de l’organisation rétinotopique corticale en présence d’une interruption locale de stimulation rétinienne (scotome artificiel). Ce protocole a ensuite été appliqué chez un patient présentant une maculopathie en phase aiguë et après récupération fonctionnelle. Cette étude confirme la possibilité de mesurer sur la surface corticale des zones d’activités différentielles correspondant à une modification localisée de la sensibilité rétinienne et permettra, dans le cas d’atteintes rétiniennes évolutives, d’étudier les phénomènes de plasticité corticale au cours de l’évolution de ces pathologies. Dans un second temps, nous avons mis au point un dispositif d’imagerie optique afin de caractériser l’organisation rétinotopique de l’aire V1 chez le rat. Le développement de cette méthode va nous permettre de lancer deux études importantes. Premièrement, nous étudierons la cinétique des modifications de la carte rétinotopique et de l’activité neuronale afin d’évaluer le rôle respectif des phénomènes de plasticité corticale ou de modification du gain neuronal dans la réorganisation fonctionnelle du cortex visuel après lésion rétinienne. Ces résultats 3 seront à comparer aux données acquises en IRMf chez l’homme. Deuxièmement, cette méthode est le préalable à une étude complémentaire qui a pour but de tester l’impact fonctionnel d‘implants rétiniens chez le rat. Les lésions oculaires impliquent aussi des réorganisations locales, en particulier vasculaires dont les conséquences fonctionnelles sont mal connues. Nous avons donc développé en parallèle des modèles de lésions périphérique permettant l’étude des conséquences sur la rétinotopie d’un scotome induit à la suite d’une atteinte sensorielle périphérique. Ce travail ouvre plusieurs perspectives quant à l’exploration fonctionnelle dans des pathologies comme la DMLA. / The brain shows a high ability to reorganize following alteration of sensorial input that may result from modification of the environment or disease of sensorial organs. Modern functional imagery techniques allow to examine the impact on the visual system of such alterations. The aim of this thesis was to develop new approaches for studying at the cortical level, functional consequences of ocular disease associated with a significant visual scotoma. In the first section of this thesis, we used high-field (3T) functional magnetic resonance imaging (fMRI) to study the cortical functional architecture. Our goal was to map the retinotopic organization of human early visual cortical areas (V1, V2, V3). By this method, we identified modifications of retinotopic organization induced by a focal loss of retinal stimulation (artificial scotoma) and we observed the cortical projections of artificial scotoma on healthy subjects by the mean of a specific stimulus. In the following part of the experimentation, this protocol was used on a patient who showed a maculopathy at the acute stage and after recovery. This study confirms the ability to evaluate the cortical representation (size and location) of a focalized modification of the retinal sensibility threshold and could serve as a basis for the future investigation of cortical plasticity in the visual cortex following retinal diseases. The second section of this thesis was directed to the development of optical imaging intrinsic signals on small animals. Our goals were to characterize the retinotopic organization of rat’s visual cortex. With this method, we will investigate the kinetics of cortical remapping and modifications of the neuronal activity level following retinal lesion. These results will be compared to the data previously acquired by fMRI in humans. Another application of our method will be to study the functional impact of retinal prosthesis. Ocular lesions are associated with local modifications of retinal tissue, and especially with neovascular ingrowth, for which functional consequences have not been totally clarified. We therefore developed models of peripheral lesions, which allow to study the effect of scotoma on retinotopic organization of primary visual cortex after peripheral sensory lesion. This thesis gives some new directions in the functional exploration in retinal disease as Age Related Macular Degeneration (ARMD).

BACKGROUND: Idiopathic psychotic disorders, which include schizophrenia, schizoaffective and bipolar disorder with psychosis, are debilitating disorders affecting about 3% of the world’s population. Neurodevelopmental and neurodegenerative hypotheses have been proposed in psychosis, but the literature is mixed in regards to whether psychosis pathogenesis involves one or both of these processes. Since the visual system matures early in development, studying visual pathway abnormalities stratified by disease onset may further inform our understanding of psychosis pathogenesis. OBJECTIVE: The objective of this thesis is to determine whether disease onset, independent of illness duration, has a differential effect on visual cortical abnormalities in psychosis. We examined visual cortical measures for thickness, surface area, and volume using a pseudo-longitudinal study design of first episode psychosis-schizophrenia (FEP-SZ), FEP-non-schizophrenia (FEP-NSZ), early onset psychosis (EOP, <15 years of age), adult onset psychosis (OP, >15 and <30 years of age), and late onset psychosis (LOP, >30 years of age) groups. Relationships between visual cortical metrics and clinical or functional outcomes were performed. METHODS: The FEP sample (n= 102) included healthy controls (n= 44), FEP-SZ (n= 36), and FEP-NSZ (n= 22). The chronic psychosis data included healthy controls (n= 311) and psychosis probands (n=510). Psychosis probands was stratified by disease onset: EOP (n=213), OP (n=257), and LOP (n=40). Propensity matching was performed to match healthy controls (HC) according to age, sex and race. Linear regression models were performed comparing the means of visual cortical measures between groups. Partial Spearman correlations controlling for confounding factors were performed between visual cortical regions and clinical data. For FEP, clinical outcomes were assessed using Clinical Global Impression scale (CGI), Scale of Positive Symptoms (SAPS), and Scale of Negative Symptoms (SANS). For onset groups, clinical and functional outcomes were assessed using Positive and Negative Syndrome Scale (PANSS), Montgomery–Åsberg Depression Rating Scale (MADRS), Brief Assessment of Cognition (BACS), Wecshler Memory Scale (WMS) spatial span, anti-saccade error rates, dot expectancy pattern test, emotion recognition test, and Birchwood Social Functioning Scale (SFS). Multiple comparisons were performed using the Benjamini-Hochberg procedure. RESULTS: FEP-SZ was associated with smaller V1 and V2 areas, higher MT area and lower MT thickness compared to HCs. Lower MT thickness was associated with worse negative symptoms. Compared to HC, patients with chronic psychosis had lower V1, V2, and MT areas, as well as smaller MT thickness. V1 and V2 area and MT thickness were lower in the EOP group in comparison to matched HC. OP and LOP had a thinner MT region compared to matched HC. Of particular note, it was observed that EOP had greater area differences as compared to thickness reductions in the LOP group. Increased hallucinations and delusions were associated with a thinner MT region in the EOP group. CONCLUSION: When stratified by disease onset, FEP, EOP, OP, and LOP appear to have different pathogenic mechanisms and the severity of visual cortex neuroanatomical abnormalities are dependent on when the disease onset occurs. EOP occurs earlier in neurodevelopment resulting in greater severity in symptom and visual cortical measures as compared to OP. On the contrary, LOP appears to have a neurodegenerative mechanism which is evidenced by accelerated visual cortical thinning. / 2022-06-01T00:00:00Z

The human visual system is tasked with transforming variations in light within our environment into a coherent percept, typically described using properties such as luminance and contrast. The experiments described in this dissertation examine how the human visual cortex responds to each of these stimulus properties at the population-level, and explores the degree to which contrast adaptation can alter these response properties. The first set of experiments (Chapter 2) demonstrate how saturating sigmoidal contrast response functions can be captured using human fMRI by leveraging sustained contrast adaptation to reduce the heterogeneity of response profiles across neural populations. The results obtained using this methodology have the potential to rectify the qualitatively different findings reported across visual neuroscience, when comparing electrophysiological and population-based neuroimaging measures. The second set of experiments (Chapter 3) demonstrate how under certain conditions a well-established visuocortical response property, contrast response, can also reflect luminance encoding, challenging the idea that luminance information plays no significant role in supporting visual perception. Specifically, these results show that the mean luminance information of a visual signal persists within visuocortical representations, even after controlling for pupillary dynamics, and potentially reflects an inherent imbalance of excitatory and inhibitory components. The final set of experiments (Chapter 4) examine how the time course of population activity during initial periods of adaptation differs across seemingly slightly different adapter conditions. The degree to which stimulus adapter orientation bias (radial vs. concentric orientation) or stimulus adapter luminance (2409 cd/m2 vs. 757.3 cd/m2) can alter adaptation time course dynamics is examined in detail, as well as investigating the prevalence of any retinotopic bias. In an effort to coalesce the findings across all three chapters, the shape and efficacy of the initial adaptation time course is ultimately compared against the contrast and luminance response function parameters reported in previous chapters. As a whole, the findings reported in this dissertation challenge some common assumptions about how the early human visual cortex adjusts and responds to the environment, provide methodological tools and stimulus design caveats vision neuroscientists will need to consider, and play a significant role in cortical models of vision.

<p>The primary visual cortex (V1) is a center in the visual pathway that receives the converging information and sends diverging information to multiple visual areas. It is essential for the normal functioning of the visual system. While processing the input from the outside world, it is also continually modified by the sensory experience. This thesis is dedicated to studying the plasticity in the visual cortex that is associated with experience and brain damage recovery. In this thesis, we discovered that the visual experience induces 5 Hz oscillations that recruit inhibition in V1, sharpening the feature selectivity. We have also demonstrated that gene therapy to convert astrocytes into neurons induces neuronal circuit plasticity and functional recovery in mouse V1 following ischemia.</p>

No description available.

京都大学 / 0048 / 新制・課程博士 / 博士(情報学) / 甲第21909号 / 情博第692号 / 新制||情||119(附属図書館) / 京都大学大学院情報学研究科知能情報学専攻 / (主査)教授 神谷 之康, 教授 熊田 孝恒, 教授 西野 恒 / 学位規則第4条第1項該当 / Doctor of Informatics / Kyoto University / DGAM

As theoretical neuroscience has grown as a field, machine learning techniques have played an increasingly important role in the development and evaluation of theories of neural computation. Today, machine learning is used in a variety of neuroscientific contexts from statistical inference to neural network training to normative modeling. This dissertation introduces machine learning techniques for use across the various domains of theoretical neuroscience, and the application of these techniques to build theories of neural circuits. First, we introduce a variety of optimization techniques for normative modeling of neural activity, which were used to evaluate theories of primary motor cortex (M1) and supplementary motor area (SMA). Specifically, neural responses during a cycling task performed by monkeys displayed distinctive dynamical geometries, which motivated hypotheses of how these geometries conferred computational properties necessary for the robust production of cyclic movements. By using normative optimization techniques to predict neural responses encoding muscle activity while ascribing to an “untangled” geometry, we found that minimal tangling was an accurate model of M1. Analyses with trajectory constrained RNNs showed that such an organization of M1 neural activity confers noise robustness, and that minimally “divergent” trajectories in SMA enable the tracking of contextual factors. In the remainder of the dissertation, we focus on the introduction and application of deep generative modeling techniques for theoretical neuroscience. Specifically, both techniques employ recent advancements in approaches to deep generative modeling -- normalizing flows -- to capture complex parametric structure in neural models. The first technique, which is designed for statistical generative models, enables look-up inference in intractable exponential family models. The efficiency of this technique is demonstrated by inferring neural firing rates in a log-gaussian poisson model of spiking responses to drift gratings in primary visual cortex. The second technique is designed for statistical inference in mechanistic models, where the inferred parameter distribution is constrained to produce emergent properties of computation. Once fit, the deep generative model confers analytic tools for quantifying the parametric structure giving rise to emergent properties. This technique was used for novel scientific insight into the nature of neuron-type variability in primary visual cortex and of distinct connectivity regimes of rapid task switching in superior colliculus.

The mammalian visual system is an incredibly complex computation device, capable of performing the various tasks of seeing: navigation, pattern and object recognition, motor coordination, trajectory extrapolation, among others. Decades of research has shown that experience-dependent plasticity of cortical circuitry underlies the impressive ability to rapidly learn many of these tasks and to adjust as required. One particular thread of investigation has focused on unsupervised learning, wherein changes to the visual environment lead to corresponding changes in cortical circuits. The most prominent example of unsupervised learning is ocular dominance plasticity, caused by visual deprivation to one eye and leading to a dramatic re-wiring of cortex. Other examples tend to make more subtle changes to the visual environment through passive exposure to novel visual stimuli. Here, we use one such unsupervised paradigm, sequence learning, to study experience-dependent plasticity in the mouse visual system. Through a combination of theory and experiment, we argue that the mammalian visual system is an unsupervised learning device. Beginning with a mathematical exploration of unsupervised learning in biology, engineering, and machine learning, we seek a more precise expression of our fundamental hypothesis. We draw connections between information theory, efficient coding, and common unsupervised learning algorithms such as Hebbian plasticity and principal component analysis. Efficient coding suggests a simple rule for transmitting information in the nervous system: use more spikes to encode unexpected information, and fewer spikes to encode expected information. Therefore, expectation violations ought to produce prediction errors, or brief periods of heightened firing when an unexpected event occurs. Meanwhile, modern unsupervised learning algorithms show how such expectations can be learned. Next, we review data from decades of visual neuroscience research, highlighting the computational principles and synaptic plasticity processes that support biological learning and seeing. By tracking the flow of visual information from the retina to thalamus and primary visual cortex, we discuss how the principle of efficient coding is evident in neural activity. One common example is predictive coding in the retina, where ganglion cells with canonical center-surround receptive fields compute a prediction error, sending spikes to the central nervous system only in response to locally-unpredictable visual stimuli. This behavior can be learned through simple Hebbian plasticity mechanisms. Similar models explain much of the activity of neurons in primary visual cortex, but we also discuss ways in which the theory fails to capture the rich biological complexity. Finally, we present novel experimental results from physiological investigations of the mouse primary visual cortex. We trained mice by passively exposing them to complex spatiotemporal patterns of light: rapidly-flashed sequences of images. We find evidence that visual cortex learns these sequences in a manner consistent with efficient coding, such that unexpected stimuli tend to elicit more firing than expected ones. Overall, we observe dramatic changes in evoked neural activity across days of passive exposure. Neural responses to the first, unexpected sequence element increase with days of training while responses at other, expected time points either decrease or stay the same. Furthermore, substituting an unexpected element for an expected one or omitting an expected element both cause brief bursts of increased firing. Our results therefore provide evidence for unsupervised learning and efficient coding in the mouse visual system, especially because unexpected events drive prediction errors. Overall, our analysis suggests novel experiments, which could be performed in the near future, and provides a useful framework to understand visual perception and learning.