scholarly journals Routing information flow by separate neural synchrony frequencies allows for “functionally labeled lines” in higher primate cortex

2019 ◽  
Vol 116 (25) ◽  
pp. 12506-12515 ◽  
Author(s):  
Mohammad Bagher Khamechian ◽  
Vladislav Kozyrev ◽  
Stefan Treue ◽  
Moein Esghaei ◽  
Mohammad Reza Daliri
Keyword(s):  
Information Flow ◽  
Information Transfer ◽  
Sensory Information ◽  
Spike Timing ◽  
Oscillatory Activity ◽  
Attention Task ◽  
Cortical Areas ◽  
High Gamma ◽  
Ventral Pathway ◽  
Visual Cortical

Efficient transfer of sensory information to higher (motor or associative) areas in primate visual cortical areas is crucial for transforming sensory input into behavioral actions. Dynamically increasing the level of coordination between single neurons has been suggested as an important contributor to this efficiency. We propose that differences between the functional coordination in different visual pathways might be used to unambiguously identify the source of input to the higher areas, ensuring a proper routing of the information flow. Here we determined the level of coordination between neurons in area MT in macaque visual cortex in a visual attention task via the strength of synchronization between the neurons’ spike timing relative to the phase of oscillatory activities in local field potentials. In contrast to reports on the ventral visual pathway, we observed the synchrony of spikes only in the range of high gamma (180 to 220 Hz), rather than gamma (40 to 70 Hz) (as reported previously) to predict the animal’s reaction speed. This supports a mechanistic role of the phase of high-gamma oscillatory activity in dynamically modulating the efficiency of neuronal information transfer. In addition, for inputs to higher cortical areas converging from the dorsal and ventral pathway, the distinct frequency bands of these inputs can be leveraged to preserve the identity of the input source. In this way source-specific oscillatory activity in primate cortex can serve to establish and maintain “functionally labeled lines” for dynamically adjusting cortical information transfer and multiplexing converging sensory signals.

scholarly journals Pulvinar influences parietal delay activity and information transmission between dorsal and ventral visual cortex in macaques

2018 ◽  
Author(s):  
Yuri B. Saalmann ◽  
Ryan Ly ◽  
Mark A. Pinsk ◽  
Sabine Kastner
Keyword(s):  
Visual Cortex ◽  
Selective Attention ◽  
Information Transmission ◽  
Parietal Cortex ◽  
Sensory Information ◽  
Relevant Information ◽  
Attention Task ◽  
Sustained Activity ◽  
Cortical Areas ◽  
Visual Cortical

AbstractThe fronto-parietal attention network represents attentional priorities and provides feedback about these priorities to sensory cortical areas. Sustained spiking activity in the posterior parietal cortex (PPC) carries such prioritized information, but how this activity is sustained in the absence of feedforward sensory information, and how it is transmitted to the ventral visual cortical pathway, is unclear. We hypothesized that the higher-order thalamic nucleus, the pulvinar, which is connected with both the PPC and ventral visual cortical pathway, influences information transmission within and between these cortical regions. To test this, we simultaneously recorded from the pulvinar, lateral intraparietal area (LIP) and visual cortical area V4 in macaques performing a selective attention task. Here we show that LIP influenced V4 during the delay period of the attention task, and that the pulvinar regulated LIP-V4 information exchange. Pulvino-cortical effects were consistent with the pulvinar supporting sustained activity in LIP. Taken together, these results suggest that pulvinar regulation of cortical functional connectivity generalizes to dorsal and ventral visual cortical pathways. Further, the pulvinar’s role in sustaining parietal delay activity during selective attention implicates the pulvinar in other cognitive processes supported by such delay activity, including decision-making, categorization and oculomotor functions.Significance StatementA network of areas on the brain’s surface, in frontal and parietal cortex, allocate attention to behaviorally relevant information around us. Such areas in parietal cortex show sustained activity during maintained attention and transmit behaviorally relevant information to visual cortical areas to enhance sensory processing of attended objects. How this activity is sustained and how it is transmitted to visual areas supporting object perception is unclear. We show that a subcortical area, the pulvinar in the thalamus, helps sustain activity in the cortex and regulates the information transmitted between the fronto-parietal attention network and visual cortex. This suggests that the thalamus, classically considered as a simple relay for sensory information, contributes to higher-level cognitive functions.

scholarly journals The Astrocyte as a Gatekeeper of Synaptic Information Transfer

2007 ◽  
Vol 19 (2) ◽  
pp. 303-326 ◽  
Author(s):  
Vladislav Volman ◽  
Eshel Ben-Jacob ◽  
Herbert Levine
Keyword(s):  
Synaptic Transmission ◽  
Information Flow ◽  
Information Transfer ◽  
Calcium Concentration ◽  
Spike Timing ◽  
Biophysical Model ◽  
Testable Hypothesis ◽  
Cells In Culture

We present a simple biophysical model for the coupling between synaptic transmission and the local calcium concentration on an enveloping astrocytic domain. This interaction enables the astrocyte to modulate the information flow from presynaptic to postsynaptic cells in a manner dependent on previous activity at this and other nearby synapses. Our model suggests a novel, testable hypothesis for the spike timing statistics measured for rapidly firing cells in culture experiments.

Neural Mechanisms of Spatial Attention in the Visual Thalamus

2014 ◽  
Author(s):  
Yuri B. Saalmann ◽  
Sabine Kastner
Keyword(s):  
Selective Attention ◽  
Visual Information ◽  
Thalamic Nucleus ◽  
Sensory Information ◽  
Relevant Information ◽  
Neural Mechanisms ◽  
First Order ◽  
Visual Thalamus ◽  
Cortical Areas ◽  
Visual Cortical

Neural mechanisms of selective attention route behaviourally relevant information through brain networks for detailed processing. These attention mechanisms are classically viewed as being solely implemented in the cortex, relegating the thalamus to a passive relay of sensory information. However, this passive view of the thalamus is being revised in light of recent studies supporting an important role for the thalamus in selective attention. Evidence suggests that the first-order thalamic nucleus, the lateral geniculate nucleus, regulates the visual information transmitted from the retina to visual cortex, while the higher-order thalamic nucleus, the pulvinar, regulates information transmission between visual cortical areas, according to attentional demands. This chapter discusses how modulation of thalamic responses, switching the response mode of thalamic neurons, and changes in neural synchrony across thalamo-cortical networks contribute to selective attention.

A NEUROBIOLOGICAL THEORY OF MEANING IN PERCEPTION PART III: MULTIPLE CORTICAL AREAS SYNCHRONIZE WITHOUT LOSS OF LOCAL AUTONOMY

2003 ◽  
Vol 13 (10) ◽  
pp. 2845-2856 ◽  
Author(s):  
WALTER J. FREEMAN ◽  
GYöNGYI GAÁL ◽  
REBECKA JORSTEN
Keyword(s):  
Information Transfer ◽  
Phase Locking ◽  
Pulse Frequency ◽  
Inhibitory Neurons ◽  
Oscillatory Activity ◽  
Electrode Arrays ◽  
Ensemble Averaging ◽  
Pulse Frequency Modulation ◽  
Cortical Areas ◽  
Gamma Range

Information transfer and integration among functionally distinct areas of cerebral cortex of oscillatory activity require some degree of phase synchrony of the trains of action potentials that carry the information prior to the integration. However, propagation delays are obligatory. Delays vary with the lengths and conduction velocities of the axons carrying the information, causing phase dispersion. In order to determine how synchrony is achieved despite dispersion, we recorded EEG signals from multiple electrode arrays on five cortical areas in cats and rabbits, that had been trained to discriminate visual or auditory conditioned stimuli. Analysis by time-lagged correlation, multiple correlation and PCA, showed that maximal correlation was at zero lag and averaged 0.7, indicating that 50% of the power in the gamma range among the five areas was at zero lag irrespective of phase or frequency. There were no stimulus-related episodes of transiently increased phase locking among the areas, nor EEG "bursts" of transiently increased amplitude above the sustained level of synchrony. Three operations were identified to account for the sustained correlation. Cortices broadcast their outputs over divergent–convergent axonal pathways that performed spatial ensemble averaging; synaptic interactions between excitatory and inhibitory neurons in cortex operated as band pass filters for gamma; and signal coarse-graining by pulse frequency modulation at trigger zones enhanced correlation. The conclusion is that these three operations enable continuous linkage of multiple cortical areas by activity in the gamma range, providing the basis for coordinated cortical output to other parts of the brain, despite varying axonal conduction delays, something like the back plane of a main frame computer.

Information flow in the nervous system

1993 ◽  
Vol 1 (1) ◽  
pp. 31-39
Author(s):  
Arnold Burgen
Keyword(s):  
Information Flow ◽  
Information Transfer ◽  
Sensory Information ◽  
Nerve Fibres ◽  
Ionic Transfer ◽  
Electrical Pulses ◽  
Specific Receptors ◽  
Stored Information ◽  
High Level ◽  
Memory And Recall

Information is carried along nerve fibres by electrical pulses generated by ionic transfer; it is digitally coded. Information transfer between nerve cells depends on the release of a chemical transmitter which acts on specific receptors on the second neurone. This is a non-digital, analogue process which is highly non-linear. It involves the summation of inputs from highly divergent sources. In sensory systems such as vision, extensive compression, feature extraction and other high-level processing occur before presentation to the cerebral cortex, where a massive expansion in distribution of information occurs. Huge numbers of neurones are involved in the central presentation of even simple sensory information. This is because the neural events are relatively slow, so that a massive parallel information flow and processing occurs. Learning and memory involve changes in synaptic efficiency and the development of new stable connective patterns. Memory and recall must involve a comparison of contemporary events with stored information, but cannot involve a one-on-one comparison because it can deal with extensive transformation of sensory information.

scholarly journals Reinforcement Learning of Two-Joint Virtual Arm Reaching in a Computer Model of Sensorimotor Cortex

2013 ◽  
Vol 25 (12) ◽  
pp. 3263-3293 ◽  
Author(s):  
Samuel A. Neymotin ◽  
George L. Chadderdon ◽  
Cliff C. Kerr ◽  
Joseph T. Francis ◽  
William W. Lytton
Keyword(s):  
Reinforcement Learning ◽  
Information Flow ◽  
Sensory Information ◽  
Relevant Information ◽  
Spike Timing ◽  
Proprioceptive Information ◽  
Learning Networks ◽  
Neuronal Populations ◽  
Arm Reaching

Neocortical mechanisms of learning sensorimotor control involve a complex series of interactions at multiple levels, from synaptic mechanisms to cellular dynamics to network connectomics. We developed a model of sensory and motor neocortex consisting of 704 spiking model neurons. Sensory and motor populations included excitatory cells and two types of interneurons. Neurons were interconnected with AMPA/NMDA and GABAA synapses. We trained our model using spike-timing-dependent reinforcement learning to control a two-joint virtual arm to reach to a fixed target. For each of 125 trained networks, we used 200 training sessions, each involving 15 s reaches to the target from 16 starting positions. Learning altered network dynamics, with enhancements to neuronal synchrony and behaviorally relevant information flow between neurons. After learning, networks demonstrated retention of behaviorally relevant memories by using proprioceptive information to perform reach-to-target from multiple starting positions. Networks dynamically controlled which joint rotations to use to reach a target, depending on current arm position. Learning-dependent network reorganization was evident in both sensory and motor populations: learned synaptic weights showed target-specific patterning optimized for particular reach movements. Our model embodies an integrative hypothesis of sensorimotor cortical learning that could be used to interpret future electrophysiological data recorded in vivo from sensorimotor learning experiments. We used our model to make the following predictions: learning enhances synchrony in neuronal populations and behaviorally relevant information flow across neuronal populations, enhanced sensory processing aids task-relevant motor performance and the relative ease of a particular movement in vivo depends on the amount of sensory information required to complete the movement.

scholarly journals Functional synchronization between hippocampal sEEG, parietal ECoG and scalp EEG during a verbal working memory task

2020 ◽  
Author(s):  
Vasileios Dimakopoulos ◽  
Ece Boran ◽  
Peter Hilfiker ◽  
Lennart Stieglitz ◽  
Thomas Grunwald ◽  
...  
Keyword(s):  
Working Memory ◽  
Auditory Cortex ◽  
Information Flow ◽  
Verbal Working Memory ◽  
Oscillatory Activity ◽  
Functional Coupling ◽  
Maintenance Period ◽  
Physiological Basis ◽  
Cortical Areas ◽  
Scalp Eeg

ABSTRACTBackgroundThe maintenance of items in working memory (WM) relies on a widespread network of brain areas where synchronization between electrophysiological recordings may reflect functional coupling. While the coupling from hippocampus to scalp EEG is well established, we provide here direct cortical recordings for a fine-grained analysis.MethodsA patient performed a WM task where a string of letters was presented all at once, thus separating the encoding period from the maintenance period. We recorded sEEG from the hippocampus, temporo-parietal ECoG from a 64-contact grid electrode, and scalp EEG.ResultsPower spectral density (PSD) showed a clear task dependence: PSD in the posterior parietal lobe (10 Hz) and in the hippocampus (20 Hz) peaked towards the end of the maintenance period.Inter-area synchronization was characterized by the phase locking value (PLV). WM maintenance enhanced PLV between hippocampal sEEG and scalp EEG specifically in the theta range [6 7] Hz.PLV from hippocampus to parietal cortex increased during maintenance in the [9 10] Hz alpha and the 20 Hz range.When analyzing the information flow to and from auditory cortex by Granger causality, the flow was from auditory cortex to hippocampus with a peak in the [8 18] Hz range while letters were presented, and this flow was subsequently reversed during maintenance, while letters were maintained in memory.ConclusionsThe increased functional interaction between hippocampus and cortex through synchronized oscillatory activity and the directed information flow provide physiological basis for reverberation of memory items during maintenance. This points to a network for working memory that is bound by coherent oscillations involving cortical areas and hippocampus.SIGNIFICANCE STATEMENTHippocampal activity is known for its role in cognitive tasks involving episodic memory or spatial navigation, but its role in working memory and its sensitivity to workload is still under debate. Here, we investigated hippocampal and cortical activity while a subject maintained sets of letters in verbal working memory for a few seconds to guide action.After confirming the coupling between hippocampal oscillations and oscillations on the scalp, we found during maintenance that hippocampal oscillations increased coupling differentially to several areas of cortex by recording directly from the cortex.. During encoding of the letters, information flow was from auditory cortex to hippocampus and subsequently reversed during maintenance, thus providing a physiological basis for memory encoding and maintenance.This demonstrates a network for working memory that is bound by coherent oscillations that underlie the functional connectivity between cortical areas and hippocampus.

scholarly journals Visual Functions of Primate Area V4

2020 ◽  
Vol 6 (1) ◽  
pp. 363-385 ◽  
Author(s):  
Anitha Pasupathy ◽  
Dina V. Popovkina ◽  
Taekjun Kim
Keyword(s):  
Macaque Monkey ◽  
High Dimensional ◽  
Functional Domain ◽  
Subcortical Structures ◽  
Area V4 ◽  
Cortical Areas ◽  
Neurophysiological Studies ◽  
Ventral Pathway ◽  
Visual Cortical ◽  
Color Depth

Area V4—the focus of this review—is a mid-level processing stage along the ventral visual pathway of the macaque monkey. V4 is extensively interconnected with other visual cortical areas along the ventral and dorsal visual streams, with frontal cortical areas, and with several subcortical structures. Thus, it is well poised to play a broad and integrative role in visual perception and recognition—the functional domain of the ventral pathway. Neurophysiological studies in monkeys engaged in passive fixation and behavioral tasks suggest that V4 responses are dictated by tuning in a high-dimensional stimulus space defined by form, texture, color, depth, and other attributes of visual stimuli. This high-dimensional tuning may underlie the development of object-based representations in the visual cortex that are critical for tracking, recognizing, and interacting with objects. Neurophysiological and lesion studies also suggest that V4 responses are important for guiding perceptual decisions and higher-order behavior.

The Functional Language Network

2017 ◽  
Author(s):  
Angela D. Friederici ◽  
Noam Chomsky
Keyword(s):  
Functional Connectivity ◽  
Information Transfer ◽  
Inferior Frontal Gyrus ◽  
Brain Regions ◽  
Oscillatory Activity ◽  
Neural Basis ◽  
Functional Neural Network ◽  
Ventral Pathway ◽  
Open Issue ◽  
Language Network

How information content is encoded and decoded in the sending and receiving brain areas is still an open issue. A possible though speculative view is that encoding and decoding requires similarity at the neuronal level in the encoding and decoding regions. This chapter discusses the functional neural network of language. It first describes the language network at the neurotransmitter level and then discusses the available data at the level of functional connectivity and oscillatory activity. Section 1 looks at the neural basis of information transfer, namely at the neurotransmitters which are crucially involved in the transmission of information from one neuron to the next. Section 2 uses functional connectivity analyses to provide information about how different brain regions work together. They allow us to make statements about which regions work together, and moreover, about the direction of the information flow between these. Section 3 models the language circuit as a a dynamic temporo-frontal network with initial input-driven information processed bottom-up from the auditory cortex to the frontal cortex along the ventral pathway, with semantic information reaching the anterior inferior frontal gyrus, and syntactic information reaching the posterior inferior frontal gyrus.

Slow and fast rhythms generated in the cerebral cortex of the anesthetized mouse

2011 ◽  
Vol 106 (6) ◽  
pp. 2910-2921 ◽  
Author(s):  
Marcel Ruiz-Mejias ◽  
Laura Ciria-Suarez ◽  
Maurizio Mattia ◽  
Maria V. Sanchez-Vives
Keyword(s):  
Cerebral Cortex ◽  
Prefrontal Cortex ◽  
Firing Rate ◽  
Oscillatory Activity ◽  
State Transitions ◽  
Population Activity ◽  
Cortical Areas ◽  
Up States ◽  
High Gamma ◽  
Up And Down States

A characterization of the oscillatory activity in the cerebral cortex of the mouse was realized under ketamine anesthesia. Bilateral recordings were obtained from deep layers of primary visual, somatosensory, motor, and medial prefrontal cortex. A slow oscillatory activity consisting of up and down states was detected, the average frequency being 0.97 Hz in all areas. Different parameters of the oscillation were estimated across cortical areas, including duration of up and down states and their variability, speed of state transitions, and population firing rate. Similar values were obtained for all areas except for prefrontal cortex, which showed significant faster down-to-up state transitions, higher firing rate during up states, and more regular cycles. The wave propagation patterns in the anteroposterior axis in motor cortex and the mediolateral axis in visual cortex were studied with multielectrode recordings, yielding speed values between 8 and 93 mm/s. The firing of single units was analyzed with respect to the population activity. The most common pattern was that of neurons firing in >90% of the up states with 1–6 spikes. Finally, fast rhythms (beta, low gamma, and high gamma) were analyzed, all of them showing significantly larger power during up states than in down states. Prefrontal cortex exhibited significantly larger power in both beta and gamma bands (up to 1 order of magnitude larger in the case of high gamma) than the rest of the cortical areas. This study allows us to carry out interareal comparisons and provides a baseline to compare against cortical emerging activity from genetically altered animals.

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