![[j26]Chapter 9#](http://s1.studyres.com/store/data/009372212_1-45723eed01d76cad9811e1514890dc2a-300x300.png)
[j26]Chapter 9#
... norepinephrine, epinephrine, and related neurotransmitter substances; and those that are cholinergic, receiving acetylcholine (ACh). Interestingly, because the receptor types can vary from neuron to neuron, the same neurotransmitter may cause the response of one neuron to differ from that of another ...
... norepinephrine, epinephrine, and related neurotransmitter substances; and those that are cholinergic, receiving acetylcholine (ACh). Interestingly, because the receptor types can vary from neuron to neuron, the same neurotransmitter may cause the response of one neuron to differ from that of another ...
How the brain uses time to represent and process visual information
... For both D spike and D interval , we examined a wide range of values for q, since neural coincidence-detectors with precisions ranging from milliseconds to seconds have been identified [10], and the range of timescales for which firing rates influence synaptic efficacy is also large. Fortunately, th ...
... For both D spike and D interval , we examined a wide range of values for q, since neural coincidence-detectors with precisions ranging from milliseconds to seconds have been identified [10], and the range of timescales for which firing rates influence synaptic efficacy is also large. Fortunately, th ...
Axonal conduction properties of antidromically identified neurons in
... circuits. Even within the same lamina, nearby cells may participate in different circuits. Thus, anatomical findings have shown that neurons within the same neuropil may receive quite different patterns of thalamocortical inputs, and, at least in the case of efferent neurons, these patterns vary acc ...
... circuits. Even within the same lamina, nearby cells may participate in different circuits. Thus, anatomical findings have shown that neurons within the same neuropil may receive quite different patterns of thalamocortical inputs, and, at least in the case of efferent neurons, these patterns vary acc ...
Computing Action Potentials by Phase Interference in
... tory period of one action potential colliding and interfering with another where axons come together at branches and on the axon hillock. The computational information that can be stored by the action potential does not follow the functional phases of the neurophysiological action potential but foll ...
... tory period of one action potential colliding and interfering with another where axons come together at branches and on the axon hillock. The computational information that can be stored by the action potential does not follow the functional phases of the neurophysiological action potential but foll ...
A unifying view of the basis of social cognition
... complex social situations. One of the most striking features of our experience of others is its intuitive nature. This implicit grasp of what other people do or feel will be the focus of our review. We will posit that, in our brain, there are neural mechanisms (mirror mechanisms) that allow us to di ...
... complex social situations. One of the most striking features of our experience of others is its intuitive nature. This implicit grasp of what other people do or feel will be the focus of our review. We will posit that, in our brain, there are neural mechanisms (mirror mechanisms) that allow us to di ...
Functional Clustering Drives Encoding Improvement in a
... tuning curves, show varying selectivity in a topographic organization (Figure 2). These results demonstrate the effectiveness of two-photon imaging and spike inference in measuring receptive fields across a contiguous brain network in vivo. ...
... tuning curves, show varying selectivity in a topographic organization (Figure 2). These results demonstrate the effectiveness of two-photon imaging and spike inference in measuring receptive fields across a contiguous brain network in vivo. ...
Document
... Extrageniculate visual system Degeneration Tracer Insular visual area Tectum Electron microscopy ...
... Extrageniculate visual system Degeneration Tracer Insular visual area Tectum Electron microscopy ...
Rhythmicity, randomness and synchrony in climbing fiber signals
... clock theory, is based on the observation that climbing fiber signals show periodic activity at w10 Hz [5,12–21] and that responses to climbing fibers (complex spikes) recorded from multiple Purkinje cells are often synchronized within a millisecond [12–19,22–25]. The second view, that climbing fibe ...
... clock theory, is based on the observation that climbing fiber signals show periodic activity at w10 Hz [5,12–21] and that responses to climbing fibers (complex spikes) recorded from multiple Purkinje cells are often synchronized within a millisecond [12–19,22–25]. The second view, that climbing fibe ...
action potential
... depolarization increases until threshold is reached and an action potential is generated ...
... depolarization increases until threshold is reached and an action potential is generated ...
Binding Mechanisms in Visual Perception
... Synchronous neural activities have been found extensively among different brain functional areas, it’s also an important mechanism that also exists in visual perception. Gray et al (1989) recorded neural signals in cat primary visual cortex (V1) using moving light bars with different orientation and ...
... Synchronous neural activities have been found extensively among different brain functional areas, it’s also an important mechanism that also exists in visual perception. Gray et al (1989) recorded neural signals in cat primary visual cortex (V1) using moving light bars with different orientation and ...
Activity of Ventral Medial Thalamic Neurons during
... France) and then digitized with a sampling rate of 20 kHz (intracellular signals), 10 kHz (extracellular signals), or 300 Hz (EEG) for off-line analysis. To perform spectral analysis of EEG potentials, fast Fourier transforms were applied using Spike 2 (CED Software; Cambridge Electronic Design, Cam ...
... France) and then digitized with a sampling rate of 20 kHz (intracellular signals), 10 kHz (extracellular signals), or 300 Hz (EEG) for off-line analysis. To perform spectral analysis of EEG potentials, fast Fourier transforms were applied using Spike 2 (CED Software; Cambridge Electronic Design, Cam ...
Temporal and spatial alterations in GPi neuronal encoding might
... Fi(t) ¼ Rnj ¼ 1 K(t ) T i ). We used a gaussian kernel K(t) ¼ exp (–t2 ⁄ (2s2)) ⁄ (s2P)), where s determined the kernel width, controlling the degree of smoothing. We took s ¼ 0.25 ⁄ F, where F is the mean firing rate of the neuron over the recording period (Baker & Gerstein, 2001). The mean firing r ...
... Fi(t) ¼ Rnj ¼ 1 K(t ) T i ). We used a gaussian kernel K(t) ¼ exp (–t2 ⁄ (2s2)) ⁄ (s2P)), where s determined the kernel width, controlling the degree of smoothing. We took s ¼ 0.25 ⁄ F, where F is the mean firing rate of the neuron over the recording period (Baker & Gerstein, 2001). The mean firing r ...
Chapter 15
... Preganglionic neuron ascends or descends to another ganglion along sympathetic chain before synapsing with postganglionic neuron. An axon may project through a ganglion and synapse with a postglanglionic neuron in one of the prevertebral ganglia. Preganglionic sympathetic fibers synapse on the adren ...
... Preganglionic neuron ascends or descends to another ganglion along sympathetic chain before synapsing with postganglionic neuron. An axon may project through a ganglion and synapse with a postglanglionic neuron in one of the prevertebral ganglia. Preganglionic sympathetic fibers synapse on the adren ...
Deciphering a neural code for vision
... The lateral inhibitory inputs to an eccentric cell were computed by using a dynamic version of the original Hartline–Ratliff formulation (7, 24) with inhibitory strength weighted as a function of retinal distance (25, 26). The self-inhibitory input to an eccentric cell was calculated by integrating ...
... The lateral inhibitory inputs to an eccentric cell were computed by using a dynamic version of the original Hartline–Ratliff formulation (7, 24) with inhibitory strength weighted as a function of retinal distance (25, 26). The self-inhibitory input to an eccentric cell was calculated by integrating ...
Reprint (1.52 MB PDF)
... In vitro model systems are helpful to understand brain functions because they reduce the brain’s overwhelming complexity. For example, cultured networks have been used to study the nervous system because the external inputs are well controlled and do not compete with the behavioral drives of an inta ...
... In vitro model systems are helpful to understand brain functions because they reduce the brain’s overwhelming complexity. For example, cultured networks have been used to study the nervous system because the external inputs are well controlled and do not compete with the behavioral drives of an inta ...
Current Challenges Facing the Translation of Brain
... to point processes using voltage thresholding, simplifying the design of decoding algorithms, especially when large MEAs are employed. Further analysis using automated or semiautomated clustering algorithms or manual feature detection allows classification of multiple individual neurons recorded fro ...
... to point processes using voltage thresholding, simplifying the design of decoding algorithms, especially when large MEAs are employed. Further analysis using automated or semiautomated clustering algorithms or manual feature detection allows classification of multiple individual neurons recorded fro ...
Cortical Maps - White Rose Research Online
... functionally in terms of feature dimensions. The receptive field of a neuron thus more generally refers to a localized region in a multidimensional feature space (see Obermayer and others, 1992). For instance, a V1 neuron might have a preference for a certain range of retinal locations (x,y), orient ...
... functionally in terms of feature dimensions. The receptive field of a neuron thus more generally refers to a localized region in a multidimensional feature space (see Obermayer and others, 1992). For instance, a V1 neuron might have a preference for a certain range of retinal locations (x,y), orient ...
Task-related “cortical” bursting depends critically
... lesion birds, as results were similar between groups). This finding indicates that although pharmacological inactivation of Area X transiently disinhibits the thalamus and increases spontaneous firing rates in LMAN (34), excitatory drive to LMAN does not remain chronically elevated following lesions o ...
... lesion birds, as results were similar between groups). This finding indicates that although pharmacological inactivation of Area X transiently disinhibits the thalamus and increases spontaneous firing rates in LMAN (34), excitatory drive to LMAN does not remain chronically elevated following lesions o ...
Single-Neuron Responses in Humans during Execution and
... temporal lobe (MTL). Connections such as the uncinate fasciculus and other cortico-cortical white matter tracts between the MTL and motor regions in the frontal lobe exist [27–31]. Although there is some evidence for responses in the hippocampus during voluntary actions [32], unlike SMA, lesions in ...
... temporal lobe (MTL). Connections such as the uncinate fasciculus and other cortico-cortical white matter tracts between the MTL and motor regions in the frontal lobe exist [27–31]. Although there is some evidence for responses in the hippocampus during voluntary actions [32], unlike SMA, lesions in ...
the brain`s concepts: the role of the sensory
... neural substrate. One can reason about grasping without grasping; yet one may still use the same neural substrate in the sensory-motor system. Indeed, that is just what we shall argue. In doing so, we will extend what we know about doing and imagining sharing a common substrate via the following hyp ...
... neural substrate. One can reason about grasping without grasping; yet one may still use the same neural substrate in the sensory-motor system. Indeed, that is just what we shall argue. In doing so, we will extend what we know about doing and imagining sharing a common substrate via the following hyp ...
neuralnet: Training of neural networks
... z0 , z1 , . . . , zk , where g : Rk+1 → R denotes the integration function and f : R → R the activation function. The neuron z0 ≡ 1 is the constant one belonging to the intercept. The integration function is often defined as g(z) = w0 z0 + ∑ik=1 wi zi = w0 + wT z. The activation function f is usuall ...
... z0 , z1 , . . . , zk , where g : Rk+1 → R denotes the integration function and f : R → R the activation function. The neuron z0 ≡ 1 is the constant one belonging to the intercept. The integration function is often defined as g(z) = w0 z0 + ∑ik=1 wi zi = w0 + wT z. The activation function f is usuall ...
the brain`s concepts: the role of the sensory
... neural substrate. One can reason about grasping without grasping; yet one may still use the same neural substrate in the sensory-motor system. Indeed, that is just what we shall argue. In doing so, we will extend what we know about doing and imagining sharing a common substrate via the following hyp ...
... neural substrate. One can reason about grasping without grasping; yet one may still use the same neural substrate in the sensory-motor system. Indeed, that is just what we shall argue. In doing so, we will extend what we know about doing and imagining sharing a common substrate via the following hyp ...
Neural oscillation
Neural oscillation is rhythmic or repetitive neural activity in the central nervous system. Neural tissue can generate oscillatory activity in many ways, driven either by mechanisms within individual neurons or by interactions between neurons. In individual neurons, oscillations can appear either as oscillations in membrane potential or as rhythmic patterns of action potentials, which then produce oscillatory activation of post-synaptic neurons. At the level of neural ensembles, synchronized activity of large numbers of neurons can give rise to macroscopic oscillations, which can be observed in the electroencephalogram (EEG). Oscillatory activity in groups of neurons generally arises from feedback connections between the neurons that result in the synchronization of their firing patterns. The interaction between neurons can give rise to oscillations at a different frequency than the firing frequency of individual neurons. A well-known example of macroscopic neural oscillations is alpha activity.Neural oscillations were observed by researchers as early as 1924 (by Hans Berger). More than 50 years later, intrinsic oscillatory behavior was encountered in vertebrate neurons, but its functional role is still not fully understood. The possible roles of neural oscillations include feature binding, information transfer mechanisms and the generation of rhythmic motor output. Over the last decades more insight has been gained, especially with advances in brain imaging. A major area of research in neuroscience involves determining how oscillations are generated and what their roles are. Oscillatory activity in the brain is widely observed at different levels of observation and is thought to play a key role in processing neural information. Numerous experimental studies support a functional role of neural oscillations; a unified interpretation, however, is still lacking.