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1.
bioRxiv ; 2024 Apr 27.
Artigo em Inglês | MEDLINE | ID: mdl-38712051

RESUMO

Measurements of neural responses to identically repeated experimental events often exhibit large amounts of variability. This noise is distinct from signal, operationally defined as the average expected response across repeated trials for each given event. Accurately distinguishing signal from noise is important, as each is a target that is worthy of study (many believe noise reflects important aspects of brain function) and it is important not to confuse one for the other. Here, we introduce a principled modeling approach in which response measurements are explicitly modeled as the sum of samples from multivariate signal and noise distributions. In our proposed method-termed Generative Modeling of Signal and Noise (GSN)-the signal distribution is estimated by subtracting the estimated noise distribution from the estimated data distribution. We validate GSN using ground-truth simulations and demonstrate the application of GSN to empirical fMRI data. In doing so, we illustrate a simple consequence of GSN: by disentangling signal and noise components in neural responses, GSN denoises principal components analysis and improves estimates of dimensionality. We end by discussing other situations that may benefit from GSN's characterization of signal and noise, such as estimation of noise ceilings for computational models of neural activity. A code toolbox for GSN is provided with both MATLAB and Python implementations.

2.
Sci Adv ; 9(35): eadg1736, 2023 09.
Artigo em Inglês | MEDLINE | ID: mdl-37647400

RESUMO

Face cells are neurons that respond more to faces than to non-face objects. They are found in clusters in the inferotemporal cortex, thought to process faces specifically, and, hence, studied using faces almost exclusively. Analyzing neural responses in and around macaque face patches to hundreds of objects, we found graded response profiles for non-face objects that predicted the degree of face selectivity and provided information on face-cell tuning beyond that from actual faces. This relationship between non-face and face responses was not predicted by color and simple shape properties but by information encoded in deep neural networks trained on general objects rather than face classification. These findings contradict the long-standing assumption that face versus non-face selectivity emerges from face-specific features and challenge the practice of focusing on only the most effective stimulus. They provide evidence instead that category-selective neurons are best understood by their tuning directions in a domain-general object space.


Assuntos
Córtex Cerebral , Neurônios , Animais , Macaca , Redes Neurais de Computação
3.
Commun Biol ; 6(1): 175, 2023 02 15.
Artigo em Inglês | MEDLINE | ID: mdl-36792693

RESUMO

Visual cortex contains regions of selectivity for domains of ecological importance. Food is an evolutionarily critical category whose visual heterogeneity may make the identification of selectivity more challenging. We investigate neural responsiveness to food using natural images combined with large-scale human fMRI. Leveraging the improved sensitivity of modern designs and statistical analyses, we identify two food-selective regions in the ventral visual cortex. Our results are robust across 8 subjects from the Natural Scenes Dataset (NSD), multiple independent image sets and multiple analysis methods. We then test our findings of food selectivity in an fMRI "localizer" using grayscale food images. These independent results confirm the existence of food selectivity in ventral visual cortex and help illuminate why earlier studies may have failed to do so. Our identification of food-selective regions stands alongside prior findings of functional selectivity and adds to our understanding of the organization of knowledge within the human visual system.


Assuntos
Reconhecimento Visual de Modelos , Córtex Visual , Humanos , Mapeamento Encefálico/métodos , Estimulação Luminosa/métodos , Córtex Visual/diagnóstico por imagem , Imageamento por Ressonância Magnética/métodos
4.
Sci Rep ; 12(1): 19467, 2022 11 14.
Artigo em Inglês | MEDLINE | ID: mdl-36376365

RESUMO

This study introduces a flexible, adhesive-integrated electrode array that was developed to enable non-invasive monitoring of cervical nerve activity. The device uses silver-silver chloride as the electrode material of choice and combines it with an electrode array consisting of a customized biopotential data acquisition unit and integrated graphical user interface (GUI) for visualization of real-time monitoring. Preliminary testing demonstrated this electrode design can achieve a high signal to noise ratio during cervical neural recordings. To demonstrate the capability of the surface electrodes to detect changes in cervical neuronal activity, the cold-pressor test (CPT) and a timed respiratory challenge were employed as stressors to the autonomic nervous system. This sensor system recording, a new technique, was termed Cervical Electroneurography (CEN). By applying a custom spike sorting algorithm to the electrode measurements, neural activity was classified in two ways: (1) pre-to-post CPT, and (2) during a timed respiratory challenge. Unique to this work: (1) rostral to caudal channel position-specific (cephalad to caudal) firing patterns and (2) cross challenge biotype-specific change in average CEN firing, were observed with both CPT and the timed respiratory challenge. Future work is planned to develop an ambulatory CEN recording device that could provide immediate notification of autonomic nervous system activity changes that might indicate autonomic dysregulation in healthy subjects and clinical disease states.


Assuntos
Adesivos , Neurônios , Humanos , Eletrodos , Neurônios/fisiologia , Razão Sinal-Ruído , Sistema Nervoso Autônomo
5.
Elife ; 112022 11 29.
Artigo em Inglês | MEDLINE | ID: mdl-36444984

RESUMO

Advances in artificial intelligence have inspired a paradigm shift in human neuroscience, yielding large-scale functional magnetic resonance imaging (fMRI) datasets that provide high-resolution brain responses to thousands of naturalistic visual stimuli. Because such experiments necessarily involve brief stimulus durations and few repetitions of each stimulus, achieving sufficient signal-to-noise ratio can be a major challenge. We address this challenge by introducing GLMsingle, a scalable, user-friendly toolbox available in MATLAB and Python that enables accurate estimation of single-trial fMRI responses (glmsingle.org). Requiring only fMRI time-series data and a design matrix as inputs, GLMsingle integrates three techniques for improving the accuracy of trial-wise general linear model (GLM) beta estimates. First, for each voxel, a custom hemodynamic response function (HRF) is identified from a library of candidate functions. Second, cross-validation is used to derive a set of noise regressors from voxels unrelated to the experiment. Third, to improve the stability of beta estimates for closely spaced trials, betas are regularized on a voxel-wise basis using ridge regression. Applying GLMsingle to the Natural Scenes Dataset and BOLD5000, we find that GLMsingle substantially improves the reliability of beta estimates across visually-responsive cortex in all subjects. Comparable improvements in reliability are also observed in a smaller-scale auditory dataset from the StudyForrest experiment. These improvements translate into tangible benefits for higher-level analyses relevant to systems and cognitive neuroscience. We demonstrate that GLMsingle: (i) helps decorrelate response estimates between trials nearby in time; (ii) enhances representational similarity between subjects within and across datasets; and (iii) boosts one-versus-many decoding of visual stimuli. GLMsingle is a publicly available tool that can significantly improve the quality of past, present, and future neuroimaging datasets sampling brain activity across many experimental conditions.


Assuntos
Inteligência Artificial , Imageamento por Ressonância Magnética , Humanos , Reprodutibilidade dos Testes , Neuroimagem , Razão Sinal-Ruído
6.
Nat Commun ; 13(1): 7342, 2022 11 29.
Artigo em Inglês | MEDLINE | ID: mdl-36446792

RESUMO

The full neural circuits of conscious perception remain unknown. Using a visual perception task, we directly recorded a subcortical thalamic awareness potential (TAP). We also developed a unique paradigm to classify perceived versus not perceived stimuli using eye measurements to remove confounding signals related to reporting on conscious experiences. Using fMRI, we discovered three major brain networks driving conscious visual perception independent of report: first, increases in signal detection regions in visual, fusiform cortex, and frontal eye fields; and in arousal/salience networks involving midbrain, thalamus, nucleus accumbens, anterior cingulate, and anterior insula; second, increases in frontoparietal attention and executive control networks and in the cerebellum; finally, decreases in the default mode network. These results were largely maintained after excluding eye movement-based fMRI changes. Our findings provide evidence that the neurophysiology of consciousness is complex even without overt report, involving multiple cortical and subcortical networks overlapping in space and time.


Assuntos
Estado de Consciência , Movimentos Oculares , Humanos , Percepção Visual , Encéfalo , Neurofisiologia
7.
Front Physiol ; 13: 798376, 2022.
Artigo em Inglês | MEDLINE | ID: mdl-35370794

RESUMO

Electrodiagnosis is routinely integrated into clinical neurophysiology practice for peripheral nerve disease diagnoses, such as neuropathy, demyelinating disorders, nerve entrapment/impingement, plexopathy, or radiculopathy. Measured with conventional surface electrodes, the propagation of peripheral nerve action potentials along a nerve is the result of ionic current flow which, according to Ampere's Law, generates a small magnetic field that is also detected as an "action current" by magnetometers, such as superconducting quantum interference device (SQUID) Magnetoencephalography (MEG) systems. Optically pumped magnetometers (OPMs) are an emerging class of quantum magnetic sensors with a demonstrated sensitivity at the 1 fT/√Hz level, capable of cortical action current detection. But OPMs were ostensibly constrained to low bandwidth therefore precluding their use in peripheral nerve electrodiagnosis. With careful OPM bandwidth characterization, we hypothesized OPMs may also detect compound action current signatures consistent with both Sensory Nerve Action Potential (SNAP) and the Hoffmann Reflex (H-Reflex). In as much, our work confirms OPMs enabled with expanded bandwidth can detect the magnetic signature of both the SNAP and H-Reflex. Taken together, OPMs now show potential as an emerging electrodiagnostic tool.

8.
Nat Neurosci ; 25(1): 116-126, 2022 01.
Artigo em Inglês | MEDLINE | ID: mdl-34916659

RESUMO

Extensive sampling of neural activity during rich cognitive phenomena is critical for robust understanding of brain function. Here we present the Natural Scenes Dataset (NSD), in which high-resolution functional magnetic resonance imaging responses to tens of thousands of richly annotated natural scenes were measured while participants performed a continuous recognition task. To optimize data quality, we developed and applied novel estimation and denoising techniques. Simple visual inspections of the NSD data reveal clear representational transformations along the ventral visual pathway. Further exemplifying the inferential power of the dataset, we used NSD to build and train deep neural network models that predict brain activity more accurately than state-of-the-art models from computer vision. NSD also includes substantial resting-state and diffusion data, enabling network neuroscience perspectives to constrain and enhance models of perception and memory. Given its unprecedented scale, quality and breadth, NSD opens new avenues of inquiry in cognitive neuroscience and artificial intelligence.


Assuntos
Neurociência Cognitiva , Imageamento por Ressonância Magnética , Inteligência Artificial , Encéfalo/diagnóstico por imagem , Encéfalo/fisiologia , Mapeamento Encefálico/métodos , Humanos , Imageamento por Ressonância Magnética/métodos , Redes Neurais de Computação , Reconhecimento Psicológico
9.
Nat Aging ; 1(6): 506-520, 2021 06.
Artigo em Inglês | MEDLINE | ID: mdl-35291561

RESUMO

Apolipoprotein E4 (APOE4), the main susceptibility gene for Alzheimer's disease (AD), leads to vascular dysfunction, amyloid-ß pathology, neurodegeneration and dementia. How these different pathologies contribute to advanced-stage AD remains unclear. Using aged APOE knock-in mice crossed with 5xFAD mice, we show that, compared to APOE3, APOE4 accelerates blood-brain barrier (BBB) breakdown, loss of cerebral blood flow, neuronal loss and behavioral deficits independently of amyloid-ß. BBB breakdown was associated with activation of the cyclophilin A-matrix metalloproteinase-9 BBB-degrading pathway in pericytes. Suppression of this pathway improved BBB integrity and prevented further neuronal loss and behavioral deficits in APOE4;5FAD mice while having no effect on amyloid-ß pathology. Thus, APOE4 accelerates advanced-stage BBB breakdown and neurodegeneration in Alzheimer's mice via the cyclophilin A pathway in pericytes independently of amyloid-ß, which has implication for the pathogenesis and treatment of vascular and neurodegenerative disorder in AD.


Assuntos
Doença de Alzheimer , Doenças Neurodegenerativas , Camundongos , Animais , Apolipoproteína E4/genética , Doença de Alzheimer/genética , Ciclofilina A/genética , Peptídeos beta-Amiloides/metabolismo
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