When a neuron breaks silence, it can emit action potentials in a number of patterns. Some responses are so sudden and intense that electrophysiologists felt the need to single them out, labelling action potentials emi...
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When a neuron breaks silence, it can emit action potentials in a number of patterns. Some responses are so sudden and intense that electrophysiologists felt the need to single them out, labelling action potentials emitted at a particularly high frequency with a metonym - bursts. Is there more to bursts than a figure of speech? After all, sudden bouts of high-frequency firing are expected to occur whenever inputs surge. The burst coding hypothesis advances that the neural code has three syllables: silences, spikes and bursts. We review evidence supporting this ternary code in terms of devoted mechanisms for burst generation, synaptic transmission and synaptic plasticity. We also review the learning and attention theories for which such a triad is *** Abstract figure legend The widely observed phenomenon of bursting is reviewed in terms of generation mechanisms, transmission mechanisms and function particularly in terms of plasticity and attention within the central nervous ***
Complex behaviors are often driven by an internal model, which integrates sensory information over time and facilitates long-term planning to reach subjective goals. A fundamental challenge in neuroscience is, How can...
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Complex behaviors are often driven by an internal model, which integrates sensory information over time and facilitates long-term planning to reach subjective goals. A fundamental challenge in neuroscience is, How can we use behavior and neural activity to understand this internal model and its dynamic latent variables? Here we interpret behavioral data by assuming an agent behaves rationally-that is, it takes actions that optimize its subjective reward according to its understanding of the task and its relevant causal variables. We apply a method, inverse rational control (IRC), to learn an agent's internal model and reward function by maximizing the likelihood of its measured sensory observations and actions. This thereby extracts rational and interpretable thoughts of the agent from its behavior. We also provide a framework for interpreting encoding, recoding, and decoding of neural data in light of this rational model for behavior. When applied to behavioral and neural data from simulated agents performing suboptimally on a naturalistic foraging task, this method successfully recovers their internal model and reward function, as well as the Markovian computational dynamics within the neural manifold that represent the task. This work lays a foundation for discovering how the brain represents and computes with dynamic latent variables.
Episodic memory organizes experience in time, so that we can review past events and anticipate the future. in a hippocampus-dependent memory task, spike timing in pairs of simultaneously active CA1 neurons with overla...
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Episodic memory organizes experience in time, so that we can review past events and anticipate the future. in a hippocampus-dependent memory task, spike timing in pairs of simultaneously active CA1 neurons with overlapping place fields distinguished the start and end of trials. At the common starting point of different journeys, the relative spike timing of the neurons was highly correlated. As the rat approached a common goal from different starting points, however, temporal firing patterns were strongly modulated across journeys even if the cells fired in the same spatial locations within fields, implying that different processes influenced when and where cells fire. Spike timing within hippocampal ensembles may thereby help parse the beginning from the end of episodes in memory.
Optogenetic tools, providing non-invasive control over selected cells, have the potential to revolutionize sensory prostheses for humans. Optogenetic stimulation of spiral ganglion neurons (SGNs) in the ear provides a...
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Optogenetic tools, providing non-invasive control over selected cells, have the potential to revolutionize sensory prostheses for humans. Optogenetic stimulation of spiral ganglion neurons (SGNs) in the ear provides a future alternative to electrical stimulation used in cochlear implants. However, most channelrhodopsins do not support the high temporal fidelity pertinent to auditory coding because they require milliseconds to close after light-off. Here, we biophysically characterized the fast channelrhodopsin Chronos and revealed a deactivation time constant of less than a millisecond at body temperature. In order to enhance neural expression, we improved its trafficking to the plasma membrane (Chronos-ES/TS). Following efficient transduction of SGNs using early postnatal injection of the adeno-associated virus AAV-PHP.B into the mouse cochlea, fiber-based optical stimulation elicited optical auditory brainstem responses (oABR) with minimal latencies of 1 ms, thresholds of 5 mu J and 100 mu s per pulse, and sizable amplitudes even at 1,000 Hz of stimulation. Recordings from single SGNs demonstrated good temporal precision of light-evoked spiking. In conclusion, efficient virus-mediated expression of targeting-optimized Chronos-ES/TS achieves ultrafast optogenetic control of neurons.
It was shown recently in neuroimaging that spatial differentiation of brain activity provides novel information about brain function. This confirms the integrative organisation of brain activity, but given present tec...
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It was shown recently in neuroimaging that spatial differentiation of brain activity provides novel information about brain function. This confirms the integrative organisation of brain activity, but given present technical limitations of neuroimaging approaches, the exact role of integrative activity remains unclear. We trained a neural network to integrate information using random numbers' so as to imitate the "centre-periphery" pattern of brain activity in neuroimaging. Only the hierarchical organisation of the network permitted the learning of fast and reliable integration. We presented images to the trained network and, by spatial differentiation of the network activity, obtained virtual spaces with the presented images. Thus, our study established the necessity of the hierarchical organisation of neural networks for integration and demonstrated that the role of neural integration in the brain may be to create virtual spaces with internal representations of the objects. (C) 2014 Elsevier Ireland Ltd. All rights reserved.
Motor cortex plays a substantial role in driving movement, yet the details underlying this control remain unresolved. We analyzed the extent to which movement-related information could be extracted from single-trial m...
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Motor cortex plays a substantial role in driving movement, yet the details underlying this control remain unresolved. We analyzed the extent to which movement-related information could be extracted from single-trial motor cortical activity recorded while monkeys performed center-out reaching. Using information theoretic techniques, we found that single units carry relatively little speed-related information compared with direction-related information. This result is not mitigated at the population level: simultaneously recorded population activity predicted speed with significantly lower accuracy relative to direction predictions. Furthermore, a unit-dropping analysis revealed that speed accuracy would likely remain lower than direction accuracy, even given larger populations. These results suggest that the instantaneous details of single-trial movement speed are difficult to extract using commonly assumed coding schemes. This apparent paucity of speed information takes particular importance in the context of brain-machine interfaces (BMIs), which rely on extracting kinematic information from motor cortex. Previous studies have highlighted subjects' difficulties in holding a BMI cursor stable at targets. These studies, along with our finding of relatively little speed information in motor cortex, inspired a speed-dampening Kalman filter (SDKF) that automatically slows the cursor upon detecting changes in decoded movement direction. Effectively, SDKF enhances speed control by using prevalent directional signals, rather than requiring speed to be directly decoded from neural activity. SDKF improved success rates by a factor of 1.7 relative to a standard Kalman filter in a closed-loop BMI task requiring stable stops at targets. BMI systems enabling stable stops will be more effective and user-friendly when translated into clinical applications.
Huang X, Lisberger SG. Circuit mechanisms revealed by spike-timing correlations in macaque area MT. J Neurophysiol 109: 851-866, 2013. First published November 14, 2012;doi:10.1152/jn.00775.2012.-We recorded simultane...
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Huang X, Lisberger SG. Circuit mechanisms revealed by spike-timing correlations in macaque area MT. J Neurophysiol 109: 851-866, 2013. First published November 14, 2012;doi:10.1152/jn.00775.2012.-We recorded simultaneously from pairs of motion-sensitive neurons in the middle temporal cortex (MT) of macaque monkeys and used cross-correlations in the timing of spikes between neurons to gain insights into cortical circuitry. We characterized the time course and stimulus dependency of the cross-correlogram (CCG) for each pair of neurons and of the auto-correlogram (ACG) of the individual neurons. For some neuron pairs, the CCG showed negative flanks that emerged next to the central peak during stimulus-driven responses. Similar negative flanks appeared in the ACG of many neurons. Negative flanks were most prevalent and deepest when the neurons were driven to high rates by visual stimuli that moved in the neurons' preferred directions. The temporal development of the negative flanks in the CCG coincided with a parallel, modest reduction of the noise correlation between the spike counts of the neurons. Computational analysis of a model cortical circuit suggested that negative flanks in the CCG arise from the excitation-triggered mutual cross-inhibition between pairs of excitatory neurons. Intracortical recurrent inhibition and afterhyperpolarization caused by intrinsic outward currents, such as the calcium-activated potassium current of small conductance, can both contribute to the negative flanks in the ACG. In the model circuit, stronger intracortical inhibition helped to maintain the temporal precision between the spike trains of pairs of neurons and led to weaker noise correlations. Our results suggest a neural circuit architecture that can leverage activity-dependent intracortical inhibition to adaptively modulate both the synchrony of spike timing and the correlations in response variability.
The ability to learn new tasks requires that new information is integrated into neural systems that already support other behaviors. To study how new information is incorporated into neural representations, we analyze...
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The ability to learn new tasks requires that new information is integrated into neural systems that already support other behaviors. To study how new information is incorporated into neural representations, we analyzed single-unit recordings from the prefrontal cortex (PFC), a brain region important for task acquisition and working memory, before and after monkeys learned to perform two behavioral tasks. A population-decoding analysis revealed a large increase in task-relevant information, and smaller changes in stimulus-related information, after training. This new information was contained in dynamic patterns of neural activity, with many individual neurons containing the new task-relevant information for only relatively short periods of time in the midst of other large firing rate modulations. Additionally, we found that stimulus information could be decoded with high accuracy only from dorsal PFC, whereas task-relevant information was distributed throughout both dorsal and ventral PFC. These findings help resolve a controversy about whether PFC is innately specialized to process particular types of information or whether its responses are completely determined by task demands by showing there is both regional specialization within PFC that was present before training, as well as more widespread task-relevant information that is a direct result of learning. The results also show that information is incorporated into PFC through the emergence of a small population of highly selective neurons that overlay new signals on top of patterns of activity that contain information about previously encoded variables, which gives insight into how information is coded in neural activity.
Extended receptive fields are characteristic for the integrative properties of sensory neurons. How this integration is performed is an important aspect in understanding neural coding and can give insight into the com...
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Extended receptive fields are characteristic for the integrative properties of sensory neurons. How this integration is performed is an important aspect in understanding neural coding and can give insight into the computations and the biophysics involved. We present a method of systematically investigating the nature of spectral integration in auditory receptor neurons by analyzing how these neurons combine intensities contained in different parts of the stimulus spectrum. The method consists of identifying regions in parameter space that lead to the same neural response, and it is also applicable to other stimulus domains. (C) 2002 Elsevier Science B.V. All rights reserved.
Biologically inspired spiking neural networks are increasingly popular in the field of artificial intelligence due to their ability to solve complex problems while being power efficient. They do so by leveraging the t...
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Biologically inspired spiking neural networks are increasingly popular in the field of artificial intelligence due to their ability to solve complex problems while being power efficient. They do so by leveraging the timing of discrete spikes as main information carrier. Though, industrial applications are still lacking, partially because the question of how to encode incoming data into discrete spike events cannot be uniformly answered. In this paper, we summarise the signal encoding schemes presented in the literature and propose a uniform nomenclature to prevent the vague usage of ambiguous definitions. Therefore we survey both, the theoretical foundations as well as applications of the encoding schemes. This work provides a foundation in spiking signal encoding and gives an overview over different application-oriented implementations which utilise the schemes.
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