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Article: Fiber photometry. Fiber photometry is a calcium imaging technique that captures 'bulk' or population-level calcium (Ca2+) activity from specific cell-types within a brain region or functional network in order to study neural circuits Population-level calcium activity can be correlated with behavioral tasks, su... | Wikipedia - Fiber photometry - Summary | 192 | 1,048 | null |
Section: Technical description. Fiber photometry relies on the expression of genetically encoded calcium indicators (GECIs), like GCaMP or RCaMP, which can be targeted to specific cells using cell-specific promoters like Ca2+/calmodulin-dependent protein kinase II (CaMKII) and human synapsin (hSyn) that confer excitato... | Wikipedia - Fiber photometry - Technical description | 314 | 1,423 | null |
These indicators can be expressed in the brain in two main ways: viral expression and transgenic mouse lines. Recently, there has been a growing list of indicators that have become available to measure different chemical signals, like dLight to record dopamine signaling, or OxLight to record orexin, for example. GCaMP,... | Wikipedia - Fiber photometry - Technical description | 342 | 1,536 | null |
Section: Genetically-encoded calcium indicators (GECIs) > Expression. Optimal expression of genetically encoded calcium indicators (GECIs) can be accomplished in two ways: adeno-associated viral vectors and transgenic rodent lines. Viral injection requires GECI infusion into the brain region of interest. This virus can... | Wikipedia - Fiber photometry - Genetically-encoded calcium indicators (GECIs) > Expression | 210 | 1,094 | null |
Section: Genetically-encoded calcium indicators (GECIs) > GCaMP. GCaMP is a genetically encoded calcium indicator (GECI) that is commonly used in multiple imaging methods. GCaMP emits fluorescence when the indicator is bound to a calcium ion (Ca2+). This calcium signal is directly tied to neural response patterns, neur... | Wikipedia - Fiber photometry - Genetically-encoded calcium indicators (GECIs) > GCaMP | 282 | 1,349 | null |
Section: Genetically-encoded calcium indicators (GECIs) > Multiple-color fiber photometry. To observe simultaneous calcium dynamics in multiple cell types, researchers have combined two or more GECIs in a single brain region. For example, a research group recorded fluorescence from the green and red GECIs, GCaMP6f and ... | Wikipedia - Fiber photometry - Genetically-encoded calcium indicators (GECIs) > Multiple-color fiber photometry | 212 | 1,022 | null |
Section: Equipment. The goal of fiber photometry is to precisely deliver, extract and record bulk calcium signal from specific populations of cells within a brain region of interest. To access the signal, an optical cannula/fiber must be surgically implanted at the site of GECI expression. This optical fiber can only c... | Wikipedia - Fiber photometry - Equipment | 325 | 1,608 | null |
Section: Benefits and limitations > Benefits. For individuals in labs that want to integrate calcium imaging into their experiments but may not have the financial or technical circumstances to do so yet, fiber photometry is a low barrier of entry. Optical fibers are simpler to implant, less invasive and are more inexpe... | Wikipedia - Fiber photometry - Benefits and limitations > Benefits | 184 | 985 | null |
Section: Integration with other methods > Optogenetics and DREADDs. Fiber photometry can be integrated with cellular manipulation to draw a causal link between neural activity and behavior. Targeted modulation of defined cell types and projections in the brain can be accomplished using optogenetics or Designer Receptor... | Wikipedia - Fiber photometry - Integration with other methods > Optogenetics and DREADDs | 176 | 876 | null |
Section: Integration with other methods > Potential problems and solutions. Delivery and expression of optogenetic probes and calcium indicators to the same neurons can pose problems. Calcium indicators and manipulation channels can have overlapping excitation spectrums, such as GCaMP and channelrhodopsin (ChR2), which... | Wikipedia - Fiber photometry - Integration with other methods > Potential problems and solutions | 190 | 922 | null |
Section: Other calcium imaging methods > Miniscopes and single-photon imaging. Miniscopes are head-mounted, miniature microscopes that allow imaging of large populations of neural activity in freely-behaving mice and rats. This is possible due to their small size, as they are light enough for a mouse or rat to easily c... | Wikipedia - Fiber photometry - Other calcium imaging methods > Miniscopes and single-photon imaging | 257 | 1,340 | null |
Section: Other calcium imaging methods > Two-photon imaging. Two-photon imaging is another calcium imaging method that records fluctuations in cellular GECI dynamics. It provides a way to penetrate highly light-scattering brain tissue up to 600-700 microns below the surface of the brain. As compared to other techniques... | Wikipedia - Fiber photometry - Other calcium imaging methods > Two-photon imaging | 153 | 767 | null |
Section: History. The term fractone is derived from fractal, a term coined by Benoît Mandelbrot in 1975. Fractones were discovered in 2002 in the extracellular matrix niche of the subventricular zone of the lateral ventricule (SVZa) in a mouse brain. Originally found in the neurogenic areas of the brain, recent studies... | Wikipedia - Fractone - History | 185 | 887 | null |
Article: Functional integration (neurobiology). Functional integration is the study of how brain regions work together to process information and effect responses. Though functional integration frequently relies on anatomic knowledge of the connections between brain areas, the emphasis is on how large clusters of neuro... | Wikipedia - Functional integration (neurobiology) - Summary | 181 | 991 | null |
Section: Imaging techniques > Multimodal imaging. Multimodal imaging frequently consists of the coupling of an electrophysiologic measurement technique, such as EEG or MEG, with a hemodynamic one such as fMRI or PET. While the intention is to use the strengths and limitations of each to complement the other, current ap... | Wikipedia - Functional integration (neurobiology) - Imaging techniques > Multimodal imaging | 198 | 1,007 | null |
Section: Modes of analysis > Dynamic causal modelling. Dynamic causal modeling (DCM) is a Bayesian method for deducing the structure of a neural system based on the observed hemodynamic (fMRI) or electrophysiologic (EEG/MEG) signal. The first step is to make a prediction as to the relationships between the brain region... | Wikipedia - Functional integration (neurobiology) - Modes of analysis > Dynamic causal modelling | 224 | 1,189 | null |
Section: Modes of analysis > Statistical parametric mapping. Statistical parametric mapping (SPM) is a method for determining whether the activation of a particular brain region changes between experimental conditions, stimuli, or over time. The essential idea is simple, and consists of two major steps: first, one perf... | Wikipedia - Functional integration (neurobiology) - Modes of analysis > Statistical parametric mapping | 270 | 1,448 | null |
Section: Applications > Changes in resting-state brain activation. Many previous fMRI studies have seen that spontaneous activation of functionally connected brain regions occurs during the resting state, even in the absence of any sort of stimulation or activity. Human subjects presented with a visual learning task ex... | Wikipedia - Functional integration (neurobiology) - Applications > Changes in resting-state brain activation | 214 | 1,164 | null |
Section: Applications > IQ estimation. Voxel-based morphometric measurements of grey matter localization in the brain can be used to predict components of IQ. A set of 35 teenagers were tested for IQ and were fMRI scanned over the course of 3.5 years, and had their IQ predicted by the level of grey matter localization.... | Wikipedia - Functional integration (neurobiology) - Applications > IQ estimation | 318 | 1,574 | null |
Section: Applications > Phonological loop. The phonological loop is a component of working memory that stores a small set of words that can be maintained indefinitely if not distracted. The concept was proposed by the psychologists Alan Baddeley and Graham Hitch to explain how phrases or sentences can be internalized a... | Wikipedia - Functional integration (neurobiology) - Applications > Phonological loop | 342 | 1,848 | null |
Section: Applications > Psychiatric disorders. Although fMRI studies of people with schizophrenia and bipolar disorder have yielded some insight into the changes in effective connectivity caused by these diseases, a comprehensive understanding of the functional remodelling that occurs has not yet been achieved. Montagu... | Wikipedia - Functional integration (neurobiology) - Applications > Psychiatric disorders | 165 | 934 | null |
Section: Physiology > Location. Most gain field activity is based in the premotor cortex found in the frontal lobe anterior to the primary motor cortex, however it receives input from a variety of locations in the brain. These incoming signals provide frame of reference information through the individual's senses. Furt... | Wikipedia - Gain-field encoding - Physiology > Location | 306 | 1,502 | null |
Section: Physiology > Gain Modulation. One of the key components of gain-field encoding is the variability in the response amplitude of the action potentials from neurons. This variability, when independent of change in response selectivity, is called gain modulation. Gain Modulation takes place in many cortical areas ... | Wikipedia - Gain-field encoding - Physiology > Gain Modulation | 172 | 940 | null |
Section: Mathematical Representation. The equation for the firing rate of a gain modulated neuron is a combination of the two types of information being transmitted to the neuron: r = f ( x ) g ( y ) {\displaystyle r=f(x)g(y)} where r {\displaystyle r} is the rate of fire, f ( x ) {\displaystyle f(x)} is a function of ... | Wikipedia - Gain-field encoding - Mathematical Representation | 223 | 968 | null |
Section: Evidence. Early hypotheses of gain field encoding suggested that the gain field works as a model for motion additively. This would mean that if two limbs needed to move, models for each would be called separately but at the same time. However, more recent studies in which more complex motor movements are obser... | Wikipedia - Gain-field encoding - Evidence | 344 | 1,814 | null |
This provides your brain with the proper translations by aligning the retinal (extrinsic) and body-centered (intrinsic) representations of space. It is not surprising that before babies develop motor control of their limbs, they tend to flail and watch their own limbs move. A similar effect is found when people track m... | Wikipedia - Gain-field encoding - Evidence | 222 | 1,173 | null |
Section: History. Even though the idea of optical measurement of neuronal activity was proposed in the late 1960s, the first successful GEVI that was convenient enough to put into actual use was not developed until technologies of genetic engineering had become mature in the late 1990s. The first GEVI, coined FlaSh, wa... | Wikipedia - Genetically encoded voltage indicator - History | 182 | 955 | null |
Section: Structure. Conceptually, a GEVI should sense the voltage difference across the cell membrane and report it by a change in fluorescence. Many different structures can be used for the voltage sensing function, but one essential feature is that it must be imbedded in the cell membrane. Usually, the voltage-sensin... | Wikipedia - Genetically encoded voltage indicator - Structure | 277 | 1,110 | null |
Section: Applications, advantages, and disadvantages. Different types of GEVIs are being developed in many biological or physiological research areas. It is thought to be superior to conventional voltage detecting methods like electrode-based electrophysiological recordings, calcium imaging, or voltage sensitive dyes. ... | Wikipedia - Genetically encoded voltage indicator - Applications, advantages, and disadvantages | 256 | 1,267 | null |
Section: Design. The widely used iGluSnFR consists of a circularly permuted enhanced green fluorescent protein (cpEGFP) fused to a glutamate binding protein (GluBP) from a bacterium. When GluBP binds a glutamate molecule, it changes its shape, pulling the EGFP barrel together, increasing fluorescence. A specific peptid... | Wikipedia - Glutamate-sensitive fluorescent reporter - Design | 173 | 658 | null |
Section: History. The first genetically encoded fluorescent glutamate sensors (FLIPE, GluSnFR and SuperGluSnFR) were constructed by attaching cyan-fluorescent protein (CFP) and yellow-fluorescent protein (YFP) to a bacterial glutamate binding protein (GluBP). Glutamate binding changed the distance between CFP and YFP, ... | Wikipedia - Glutamate-sensitive fluorescent reporter - History | 178 | 724 | null |
Section: Reception. Writing in the New York Times, John Tierney found High Price to be "a fascinating combination of memoir and social science: wrenching scenes of deprivation and violence accompanied by calm analysis of historical data and laboratory results." In Scientific American, Anna Kuchment recommended High Pri... | Wikipedia - High Price (book) - Reception | 200 | 968 | null |
Article: High-conductance state. The term high-conductance state describes a particular state of neurons in specific states of the brain, such as for example during wakefulness, attentive states, or even during some anesthetized states. In individual neurons, the high-conductance state is formally defined by the fact t... | Wikipedia - High-conductance state - Summary | 254 | 1,248 | null |
Article: High-frequency oscillations. High-frequency oscillations (HFO) are brain waves of the frequency faster than ~80 Hz, generated by neuronal cell population. High-frequency oscillations can be recorded during an electroencephalagram (EEG), local field potential (LFP) or electrocorticogram (ECoG) electrophysiology... | Wikipedia - High-frequency oscillations - Summary | 175 | 801 | null |
Section: Background and history. Traditional classification of the frequency bands, that are associated to different functions/states of the brain and consist of delta, theta, alpha, beta and gamma bands. Due to the limited capabilities of the early experimental/medical setup to record fast frequencies, for historical ... | Wikipedia - High-frequency oscillations - Background and history | 153 | 788 | null |
Section: Neurophysiological features. HFO are generated by different cellular mechanisms and can be detected in many brain areas. In hippocampus, this fast neuronal activity is effect of the population synchronous spiking of pyramidal cells in the CA3 region and dendritic layer of the CA1, which give rise to a characte... | Wikipedia - High-frequency oscillations - Neurophysiological features | 176 | 810 | null |
Section: Neurophysiological features > Somatosensory evoked high-frequency oscillations. ECoG recordings from human somatosensory cortex, has shown HFO (reaching even 600 Hz) presence during sensory evoked potentials and somatosensory evoked magnetic field after median nerve stimulation. These bursts of activity are ge... | Wikipedia - High-frequency oscillations - Neurophysiological features > Somatosensory evoked high-frequency oscillations | 227 | 1,034 | null |
Section: Neurophysiological features > Pathological HFO. There are many studies, that reports pathophysiological types of HFO in human patients and animal models of disease, which are related to different psychiatric or neurological disorders: Amplitude aberrations of the sensory evoked HFOs (600 Hz) was reported in mi... | Wikipedia - High-frequency oscillations - Neurophysiological features > Pathological HFO | 193 | 806 | null |
Section: Neurophysiological features > NMDA receptor hypofunction HFO. There are increasing number of studies indicating that HFO rhythms (130–180 Hz) may arise due to the local NMDA receptor blockage, which is also a pharmacological model of schizophrenia. These NMDA receptor dependent fast oscillations were detected ... | Wikipedia - High-frequency oscillations - Neurophysiological features > NMDA receptor hypofunction HFO | 248 | 1,145 | null |
Section: Psychopathology. In neuropsychology, "hyper empathy" has also been described as a dysfunctional empathic emotional overreaction. Some researchers have suggested that hyper-empathy might arise as a consequence of a lack of emotion regulation and hyperactivation of the amygdala. A paper published in 2013 reporte... | Wikipedia - Hyper-empathy - Psychopathology | 183 | 912 | null |
Section: Dark empath. A dark empath is a person with high levels of empathy (usually cognitive), and has high levels of offensive personality traits (such as the dark triad). The term originates from a recent 2021 paper by Nadja Heym and others. In a study of 991 participants, Heym and other researchers identified four... | Wikipedia - Hyper-empathy - Dark empath | 243 | 1,151 | null |
Section: In popular culture. In Olivia Butler's Parable of the Sower the main character suffers from a fictional condition called hyperempathy. In the sequel, Parable of the Talents, she describes the condition: Hyperempathy syndrome is a delusional disorder, after all. There's no telepathy, no magic, no deep spiritual... | Wikipedia - Hyper-empathy - In popular culture | 229 | 1,013 | null |
Section: Definition. Many definitions of this term have been offered. Geisler (2003) (slightly reworded): The central concept in ideal observer analysis is the ideal observer, a theoretical device that performs a given task in an optimal fashion given the available information and some specified constraints. This is no... | Wikipedia - Ideal observer analysis - Definition | 181 | 901 | null |
Section: Natural and pseudo-natural tasks. To facilitate experimental design in the laboratory, an artificial task may be designed so that the system's performance in the task may be studied. If the task is too artificial, the system may be pushed away from a natural mode of operation. Depending on the goals of the exp... | Wikipedia - Ideal observer analysis - Natural and pseudo-natural tasks | 185 | 993 | null |
Article: Interactive specialization. Interactive Specialization is a theory of brain development proposed by the British developmental cognitive neuroscientist Mark Johnson, formerly head of the Centre for Brain and Cognitive Development at Birkbeck, University of London, London and who is now Head of Psychology at the... | Wikipedia - Interactive specialization - Summary | 308 | 1,625 | null |
Article: Internal model (motor control). In the subject area of control theory, an internal model is a process that simulates the response of the system in order to estimate the outcome of a system disturbance. The internal model principle was first articulated in 1976 by B. A. Francis and W. M. Wonham as an explicit f... | Wikipedia - Internal model (motor control) - Summary | 321 | 1,655 | null |
Section: Forward models. In their simplest form, forward models take the input of a motor command to the “plant” and output a predicted position of the body. The motor command input to the forward model can be an efference copy, as seen in Figure 1. The output from that forward model, the predicted position of the body... | Wikipedia - Internal model (motor control) - Forward models | 171 | 829 | null |
Section: Combined forward and inverse models. Theoretical work has shown that in models of motor control, when inverse models are used in combination with a forward model, the efference copy of the motor command output from the inverse model can be used as an input to a forward model for further predictions. For exampl... | Wikipedia - Internal model (motor control) - Combined forward and inverse models | 177 | 895 | null |
Section: Scientists. A wide range of scientists contribute to progress on the internal model hypothesis. Michael I. Jordan, Emanuel Todorov and Daniel Wolpert contributed significantly to the mathematical formalization. Sandro Mussa-Ivaldi, Mitsuo Kawato, Claude Ghez, Reza Shadmehr, Randy Flanagan and Konrad Kording co... | Wikipedia - Internal model (motor control) - Scientists | 341 | 1,642 | null |
Section: In different sensory modalities. The kappa effect can occur with visual (e.g., flashes of light), auditory (e.g., tones), or tactile (e.g. taps to the skin) stimuli. Many studies of the kappa effect have been conducted using visual stimuli. For example, suppose three light sources, X, Y, and Z, are flashed suc... | Wikipedia - Kappa effect - In different sensory modalities | 272 | 1,226 | null |
Section: Theories based in velocity expectation > Constant velocity expectation. According to the constant velocity hypothesis proposed by Jones and Huang (1982), the brain incorporates a prior expectation of speed when judging spatiotemporal intervals. Specifically, the brain expects temporal intervals that would prod... | Wikipedia - Kappa effect - Theories based in velocity expectation > Constant velocity expectation | 220 | 1,281 | null |
Section: Theories based in velocity expectation > Low-speed expectation. A Bayesian perceptual model replicates the tactile kappa effect and other tactile spatiotemporal illusions, including the tau effect and the cutaneous rabbit illusion. According to this model, brain circuitry encodes the expectation that tactile s... | Wikipedia - Kappa effect - Theories based in velocity expectation > Low-speed expectation | 208 | 1,038 | null |
Section: Related illusions. If observers interpret rapid stimulus sequences in light of an expectation regarding velocity, then it would be expected that not only temporal, but also spatial illusions would result. This indeed occurs in the tau effect, when the spatial separation between stimuli is constant and the temp... | Wikipedia - Kappa effect - Related illusions | 312 | 1,546 | null |
Article: Large deformation diffeomorphic metric mapping. Large deformation diffeomorphic metric mapping (LDDMM) is a specific suite of algorithms used for diffeomorphic mapping and manipulating dense imagery based on diffeomorphic metric mapping within the academic discipline of computational anatomy, to be distinguish... | Wikipedia - Large deformation diffeomorphic metric mapping - Summary | 319 | 1,733 | null |
Diffeomorphisms are by their Latin root structure preserving transformations, which are in turn differentiable and therefore smooth, allowing for the calculation of metric based quantities such as arc length and surface areas. Spatial location and extents in human anatomical coordinate systems can be recorded via a var... | Wikipedia - Large deformation diffeomorphic metric mapping - Summary | 325 | 1,695 | null |
In a more general sense, diffeomorphic mapping is any solution that registers or builds correspondences between dense coordinate systems in medical imaging by ensuring the solutions are diffeomorphic. There are now many codes organized around diffeomorphic registration including ANTS, DARTEL, DEMONS, StationaryLDDMM, F... | Wikipedia - Large deformation diffeomorphic metric mapping - Summary | 199 | 1,077 | null |
Section: History of development. Diffeomorphic mapping 3-dimensional information across coordinate systems is central to high-resolution Medical imaging and the area of Neuroinformatics within the newly emerging field of bioinformatics. Diffeomorphic mapping 3-dimensional coordinate systems as measured via high resolut... | Wikipedia - Large deformation diffeomorphic metric mapping - History of development | 333 | 1,721 | null |
This model becomes more appropriate for cross-sectional studies in which brains and or hearts are not necessarily deformations of one to the other. Methods based on linear or non-linear elasticity energetics which grows with distance from the identity mapping of the template, is not appropriate for cross-sectional stud... | Wikipedia - Large deformation diffeomorphic metric mapping - History of development | 303 | 1,585 | null |
These conditions require an action penalizing kinetic energy measured via the Sobolev norm on spatial derivatives of the flow of vector fields. The large deformation diffeomorphic metric mapping (LDDMM) code that Faisal Beg derived and implemented for his PhD at Johns Hopkins University developed the earliest algorithm... | Wikipedia - Large deformation diffeomorphic metric mapping - History of development | 164 | 941 | null |
Section: The diffeomorphism orbit model in computational anatomy. Deformable shape in computational anatomy (CA)is studied via the use of diffeomorphic mapping for establishing correspondences between anatomical coordinates in Medical Imaging. In this setting, three dimensional medical images are modelled as a random d... | Wikipedia - Large deformation diffeomorphic metric mapping - The diffeomorphism orbit model in computational anatomy | 229 | 906 | null |
The template is mapped onto the target by defining a variational problem in which the template is transformed via the diffeomorphism used as a change of coordinate to minimize a squared-error matching condition between the transformed template and the target. The diffeomorphisms are generated via smooth flows φ t , t ∈... | Wikipedia - Large deformation diffeomorphic metric mapping - The diffeomorphism orbit model in computational anatomy | 317 | 1,020 | null |
The vector fields are guaranteed to be 1-time continuously differentiable v t ∈ C 1 {\displaystyle v_{t}\in C^{1}} by modelling them to be in a smooth Hilbert space v ∈ V {\displaystyle v\in V} supporting 1-continuous derivative. The inverse φ t − 1 , t ∈ [ 0 , 1 ] {\displaystyle \varphi _{t}^{-1},t\in [0,1]} is define... | Wikipedia - Large deformation diffeomorphic metric mapping - The diffeomorphism orbit model in computational anatomy | 340 | 1,058 | null |
Section: The variational problem of dense image matching and sparse landmark matching > LDDMM algorithm for dense image matching. In CA the space of vector fields ( V , ‖ ⋅ ‖ V ) {\displaystyle (V,\|\cdot \|_{V})} are modelled as a reproducing Kernel Hilbert space (RKHS) defined by a 1-1, differential operator A : V → ... | Wikipedia - Large deformation diffeomorphic metric mapping - The variational problem of dense image matching and sparse landmark matching > LDDMM algorithm for dense image matching | 350 | 1,233 | null |
Beg solved the dense image matching minimizing the action integral of kinetic energy of diffeomorphic flow while minimizing endpoint matching term according to Beg's Iterative Algorithm for Dense Image Matching Update until convergence, ϕ t o l d ← ϕ t n e w {\displaystyle \phi _{t}^{old}\leftarrow \phi _{t}^{new}} eac... | Wikipedia - Large deformation diffeomorphic metric mapping - The variational problem of dense image matching and sparse landmark matching > LDDMM algorithm for dense image matching | 344 | 888 | null |
Section: The variational problem of dense image matching and sparse landmark matching > LDDMM registered landmark matching. The landmark matching problem has a pointwise correspondence defining the endpoint condition with geodesics given by the following minimum: min v : ϕ ˙ t = v t ∘ ϕ t C ( v ) ≐ 1 2 ∫ 0 1 ∫ R 3 A v ... | Wikipedia - Large deformation diffeomorphic metric mapping - The variational problem of dense image matching and sparse landmark matching > LDDMM registered landmark matching | 284 | 720 | null |
The landmark matching problem has a pointwise correspondence defining the endpoint condition with geodesics given by the following minimum: min v : ϕ ˙ t = v t ∘ ϕ t C ( v ) ≐ 1 2 ∫ 0 1 ∫ R 3 A v t ⋅ v t d x d t + 1 2 ∑ i ( ϕ 1 ( x i ) − y i ) ⋅ ( ϕ 1 ( x i ) − y i ) {\displaystyle \min _{v:{\dot {\phi }}_{t}=v_{t}\cir... | Wikipedia - Large deformation diffeomorphic metric mapping - The variational problem of dense image matching and sparse landmark matching > LDDMM registered landmark matching | 594 | 1,216 | null |
Section: LDDMM Diffusion Tensor Image Matching. LDDMM matching based on the principal eigenvector of the diffusion tensor matrix takes the image I ( x ) , x ∈ R 3 {\displaystyle I(x),x\in {\mathbb {R} }^{3}} as a unit vector field defined by the first eigenvector. The group action becomes φ ⋅ I = { D φ − 1 φ I ∘ φ − 1 ... | Wikipedia - Large deformation diffeomorphic metric mapping - LDDMM Diffusion Tensor Image Matching | 282 | 695 | null |
LDDMM matching based on the entire tensor matrix has group action φ ⋅ M = ( λ 1 e ^ 1 e ^ 1 T + λ 2 e ^ 2 e ^ 2 T + λ 3 e ^ 3 e ^ 3 T ) ∘ φ − 1 , {\displaystyle \varphi \cdot M=(\lambda _{1}{\hat {e}}_{1}{\hat {e}}_{1}^{T}+\lambda _{2}{\hat {e}}_{2}{\hat {e}}_{2}^{T}+\lambda _{3}{\hat {e}}_{3}{\hat {e}}_{3}^{T})\circ \... | Wikipedia - Large deformation diffeomorphic metric mapping - LDDMM Diffusion Tensor Image Matching | 343 | 647 | null |
Section: LDDMM Diffusion Tensor Image Matching > Dense matching problem onto principle eigenvector of DTI. The variational problem matching onto vector image I ′ ( x ) , x ∈ R 3 {\displaystyle I^{\prime }(x),x\in {\mathbb {R} }^{3}} with endpoint E ( ϕ 1 ) ≐ α ∫ R 3 ‖ ϕ 1 ⋅ I − I ′ ‖ 2 d x + β ∫ R 3 ( ‖ ϕ 1 ⋅ I ‖ − ‖ I... | Wikipedia - Large deformation diffeomorphic metric mapping - LDDMM Diffusion Tensor Image Matching > Dense matching problem onto principle eigenvector of DTI | 309 | 668 | null |
{\displaystyle E(\phi _{1})\doteq \alpha \int _{{\mathbb {R} }^{3}}\|\phi _{1}\cdot I-I^{\prime }\|^{2}\,dx+\beta \int _{{\mathbb {R} }^{3}}(\|\phi _{1}\cdot I\|-\|I^{\prime }\|)^{2}\,dx).} becomes min v : ϕ ˙ ∘ ϕ − 1 1 2 ∫ 0 1 ∫ R 3 A v t ⋅ v t d x d t + α ∫ R 3 ‖ ϕ 1 ⋅ I − I ′ ‖ 2 d x + β ∫ R 3 ( ‖ ϕ 1 ⋅ I ‖ − ‖ I ′ ... | Wikipedia - Large deformation diffeomorphic metric mapping - LDDMM Diffusion Tensor Image Matching > Dense matching problem onto principle eigenvector of DTI | 373 | 605 | null |
Section: LDDMM Diffusion Tensor Image Matching > Dense matching problem onto DTI MATRIX. The variational problem matching onto: M ′ ( x ) , x ∈ R 3 {\displaystyle M^{\prime }(x),x\in {\mathbb {R} }^{3}} with endpoint E ( ϕ 1 ) ≐ ∫ R 3 ‖ ϕ 1 ⋅ M ( x ) − M ′ ( x ) ‖ F 2 d x {\displaystyle E(\phi _{1})\doteq \int _{{\math... | Wikipedia - Large deformation diffeomorphic metric mapping - LDDMM Diffusion Tensor Image Matching > Dense matching problem onto DTI MATRIX | 198 | 469 | null |
Section: LDDMM ODF. High angular resolution diffusion imaging (HARDI) addresses the well-known limitation of DTI, that is, DTI can only reveal one dominant fiber orientation at each location. HARDI measures diffusion along n {\displaystyle n} uniformly distributed directions on the sphere and can characterize more comp... | Wikipedia - Large deformation diffeomorphic metric mapping - LDDMM ODF | 283 | 919 | null |
Denote the square-root ODF ( ODF {\displaystyle {\sqrt {\text{ODF}}}} ) as ψ ( s ) {\displaystyle \psi ({\bf {s}})} , where ψ ( s ) {\displaystyle \psi ({\bf {s}})} is non-negative to ensure uniqueness and ∫ s ∈ S 2 ψ 2 ( s ) d s = 1 {\displaystyle \int _{{\bf {s}}\in {\mathbb {S} }^{2}}\psi ^{2}({\bf {s}})d{\bf {s}}=1... | Wikipedia - Large deformation diffeomorphic metric mapping - LDDMM ODF | 498 | 1,052 | null |
The metric defines the distance between two ODF {\displaystyle {\sqrt {\text{ODF}}}} functions ψ 1 , ψ 2 ∈ Ψ {\displaystyle \psi _{1},\psi _{2}\in \Psi } as ρ ( ψ 1 , ψ 2 ) = ‖ log ψ 1 ( ψ 2 ) ‖ ψ 1 = cos − 1 ⟨ ψ 1 , ψ 2 ⟩ = cos − 1 ( ∫ s ∈ S 2 ψ 1 ( s ) ψ 2 ( s ) d s ) , {\displaystyle {\begin{aligned}\rho (\psi... | Wikipedia - Large deformation diffeomorphic metric mapping - LDDMM ODF | 490 | 1,089 | null |
The template and target are denoted ψ t e m p ( s , x ) {\displaystyle \psi _{\mathrm {temp} }({\bf {s}},x)} , ψ t a r g ( s , x ) {\displaystyle \psi _{\mathrm {targ} }({\bf {s}},x)} , s ∈ S 2 {\displaystyle {\bf {s}}\in {{\mathbb {S} }^{2}}} x ∈ X {\displaystyle x\in X} indexed across the unit sphere and the image do... | Wikipedia - Large deformation diffeomorphic metric mapping - LDDMM ODF | 268 | 702 | null |
Define the variational problem assuming that two ODF volumes can be generated from one to another via flows of diffeomorphisms ϕ t {\displaystyle \phi _{t}} , which are solutions of ordinary differential equations ϕ ˙ t = v t ( ϕ t ) , t ∈ [ 0 , 1 ] , ϕ 0 = i d {\displaystyle {\dot {\phi }}_{t}=v_{t}(\phi _{t}),t\in [0... | Wikipedia - Large deformation diffeomorphic metric mapping - LDDMM ODF | 340 | 838 | null |
{\displaystyle {\begin{aligned}(D\phi _{1})\psi \circ \phi _{1}^{-1}(x)={\sqrt {\frac {\det {{\bigl (}D_{\phi _{1}^{-1}}\phi _{1}{\bigr )}^{-1}}}{\left\|{{\bigl (}D_{\phi _{1}^{-1}}\phi _{1}{\bigr )}^{-1}}{\bf {s}}\right\|^{3}}}}\quad \psi \left({\frac {(D_{\phi _{1}^{-1}}\phi _{1}{\bigr )}^{-1}{\bf {s}}}{\|(D_{\phi _{... | Wikipedia - Large deformation diffeomorphic metric mapping - LDDMM ODF | 350 | 575 | null |
ψ t a r g ( x ) ) ‖ ( D ϕ 1 ) ψ t e m p ∘ ϕ 1 − 1 ( x ) 2 d x {\displaystyle {\begin{aligned}\min _{v:{\dot {\phi }}_{t}=v_{t}\circ \phi _{t},\phi _{0}={id}}\int _{0}^{1}\int _{R^{3}}Av_{t}\cdot v_{t}dx\ dt+\lambda \int _{R^{3}}\|\log _{(D\phi _{1})\psi _{\mathrm {temp} }\circ \phi _{1}^{-1}(x)}(\psi _{\mathrm {targ} }... | Wikipedia - Large deformation diffeomorphic metric mapping - LDDMM ODF | 255 | 410 | null |
Section: Hamiltonian LDDMM for dense image matching. Beg solved the early LDDMM algorithms by solving the variational matching taking variations with respect to the vector fields. Another solution by Vialard, reparameterizes the optimization problem in terms of the state q t ≐ I ∘ ϕ t − 1 , q 0 = I {\displaystyle q_{t}... | Wikipedia - Large deformation diffeomorphic metric mapping - Hamiltonian LDDMM for dense image matching | 275 | 774 | null |
Article: Large dense core vesicles. Large dense core vesicle (LDCVs) are lipid vesicles in neurons and secretory cells which may be filled with neurotransmitters, such as catecholamines or neuropeptides. LDVCs release their content through SNARE-mediated exocytosis similar to synaptic vesicles. One key difference betwe... | Wikipedia - Large dense core vesicles - Summary | 152 | 599 | null |
Article: Llinás's law. Llinás's law, or law of no interchangeability of neurons, is a statement in neuroscience made by Rodolfo Llinás in 1989, during his Luigi Galvani Award Lecture at the Fidia Research Foundation Neuroscience Award Lectures. A neuron of a given kind (e.g. a thalamic cell) cannot be functionally repl... | Wikipedia - Llinás's law - Summary | 286 | 1,359 | null |
Article: Long-term potentiation. In neuroscience, long-term potentiation (LTP) is a persistent strengthening of synapses based on recent patterns of activity. These are patterns of synaptic activity that produce a long-lasting increase in signal transmission between two neurons. The opposite of LTP is long-term depress... | Wikipedia - Long-term potentiation - Summary | 246 | 1,179 | null |
Section: History > Early theories of learning. At the end of the 19th century, scientists generally recognized that the number of neurons in the adult brain (roughly 100 billion) did not increase significantly with age, giving neurobiologists good reason to believe that memories were generally not the result of new neu... | Wikipedia - Long-term potentiation - History > Early theories of learning | 339 | 1,706 | null |
Section: History > Discovery. LTP was first observed by Terje Lømo in 1966 in the Oslo, Norway, laboratory of Per Andersen. There, Lømo conducted a series of neurophysiological experiments on anesthetized rabbits to explore the role of the hippocampus in short-term memory. Lømo's experiments focused on connections, or ... | Wikipedia - Long-term potentiation - History > Discovery | 333 | 1,512 | null |
Section: History > Models and theory. The physical and biological mechanism of LTP is still not understood, but some successful models have been developed.[1] Studies of dendritic spines, protruding structures on dendrites that physically grow and retract over the course of minutes or hours, have suggested a relationsh... | Wikipedia - Long-term potentiation - History > Models and theory | 167 | 878 | null |
Section: Types. Since its original discovery in the rabbit hippocampus, LTP has been observed in a variety of other neural structures, including the cerebral cortex, cerebellum, amygdala, and many others. Robert Malenka, a prominent LTP researcher, has suggested that LTP may even occur at all excitatory synapses in the... | Wikipedia - Long-term potentiation - Types | 322 | 1,466 | null |
For example, LTP in the Schaffer collateral pathway of the hippocampus is NMDA receptor-dependent - this was proved by the application of AP5, an antagonist to the NMDA receptor, which prevented LTP in this pathway. Conversely, LTP in the mossy fiber pathway is NMDA receptor-independent, even though both pathways are i... | Wikipedia - Long-term potentiation - Types | 337 | 1,405 | null |
Section: Properties. NMDA receptor-dependent LTP exhibits several properties, including input specificity, associativity, cooperativity, and persistence. Input specificity Once induced, LTP at one synapse does not spread to other synapses; rather LTP is input specific. Long-term potentiation is only propagated to those... | Wikipedia - Long-term potentiation - Properties | 348 | 1,590 | null |
Section: Properties > Early phase > Expression. Phosphorylation is a chemical reaction in which a small phosphate group is added to another molecule to change that molecule's activity. Autonomously active CaMKII and PKC use phosphorylation to carry out the two major mechanisms underlying the expression of E-LTP. First,... | Wikipedia - Long-term potentiation - Properties > Early phase > Expression | 335 | 1,565 | null |
One hypothesis of this presynaptic facilitation is that persistent CaMKII activity in the postsynaptic cell during E-LTP may lead to the synthesis of a "retrograde messenger", discussed later. According to this hypothesis, the newly synthesized messenger travels across the synaptic cleft from the postsynaptic to the pr... | Wikipedia - Long-term potentiation - Properties > Early phase > Expression | 157 | 706 | null |
Section: Properties > Late phase > Induction. Late LTP is induced by changes in gene expression and protein synthesis brought about by the persistent activation of protein kinases activated during E-LTP, such as MAPK. In fact, MAPK—specifically the extracellular signal-regulated kinase (ERK) subfamily of MAPKs—may be t... | Wikipedia - Long-term potentiation - Properties > Late phase > Induction | 197 | 854 | null |
Section: Properties > Late phase > Maintenance. Upon activation, ERK may phosphorylate a number of cytoplasmic and nuclear molecules that ultimately result in the protein synthesis and morphological changes observed in L-LTP. These cytoplasmic and nuclear molecules may include transcription factors such as CREB. ERK-me... | Wikipedia - Long-term potentiation - Properties > Late phase > Maintenance | 334 | 1,520 | null |
Even more recently, transgenic mice lacking PKMζ demonstrate normal LTP, questioning the necessity of PKMζ. In return it was argued that the related molecule PKC-ι/λ (PKC-ι and PKC-λ isoforms) acted as a compensatory mechanism. It has been also shown that PKMζ works together with KIBRA in anchoring its activity so that... | Wikipedia - Long-term potentiation - Properties > Late phase > Maintenance | 208 | 877 | null |
Section: Properties > Late phase > Expression. The identities of only a few proteins synthesized during L-LTP are known. Regardless of their identities, it is thought that they contribute to the increase in dendritic spine number, surface area, and postsynaptic sensitivity to neurotransmitter associated with L-LTP expr... | Wikipedia - Long-term potentiation - Properties > Late phase > Expression | 350 | 1,709 | null |
More recently, investigators have demonstrated that this type of local protein synthesis is necessary for some types of LTP. One reason for the popularity of the local protein synthesis hypothesis is that it provides a possible mechanism for the specificity associated with LTP. Specifically, if indeed local protein syn... | Wikipedia - Long-term potentiation - Properties > Late phase > Expression | 187 | 956 | null |
Section: Properties > Retrograde signaling. Retrograde signaling is a hypothesis that attempts to explain that, while LTP is induced and expressed postsynaptically, some evidence suggests that it is expressed presynaptically as well. The hypothesis gets its name because normal synaptic transmission is directional and p... | Wikipedia - Long-term potentiation - Properties > Retrograde signaling | 225 | 1,114 | null |
Section: Properties > Synaptic tagging. Before the local protein synthesis hypothesis gained significant support, there was general agreement that the protein synthesis underlying L-LTP occurred in the cell body. Further, there was thought that the products of this synthesis were shipped cell-wide in a nonspecific mann... | Wikipedia - Long-term potentiation - Properties > Synaptic tagging | 331 | 1,531 | null |
The products of gene expression are shipped globally throughout the cell, but are only captured by synapses that express the synaptic tag. Thus only the synapse receiving LTP-inducing stimuli is potentiated, demonstrating LTP's input specificity. The synaptic tag hypothesis may also account for LTP's associativity and ... | Wikipedia - Long-term potentiation - Properties > Synaptic tagging | 335 | 1,616 | null |
Section: Properties > Modulation. As described previously, the molecules that underlie LTP can be classified as mediators or modulators. A mediator of LTP is a molecule, such as the NMDA receptor or calcium, whose presence and activity is necessary for generating LTP under nearly all conditions. By contrast, a modulato... | Wikipedia - Long-term potentiation - Properties > Modulation | 222 | 987 | null |
Section: Relationship to behavioral memory > Spatial memory. In 1986, Richard Morris provided some of the first evidence that LTP was indeed required for the formation of memories in vivo. He tested the spatial memory of rats by pharmacologically modifying their hippocampus, a brain structure whose role in spatial lear... | Wikipedia - Long-term potentiation - Relationship to behavioral memory > Spatial memory | 342 | 1,666 | null |
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