A Neurobiological Theory of Meaning in Perception Part II: Spatial Patterns of Phase in Gamma EEGs from Primary Sensory Cortices Reveal the Dynamics of Mesoscopic Wave Packets

2003 ◽  
Vol 13 (09) ◽  
pp. 2513-2535 ◽  
Author(s):  
Walter J. Freeman
Keyword(s):  
Spatial Patterns ◽  
Neural Activity ◽  
Action Potentials ◽  
Wave Packets ◽  
Power Level ◽  
Sensory Information ◽  
State Transitions ◽  
Electrode Arrays ◽  
Phase Gradient ◽  
Information Carrier

Domains of cooperative neural activity called "wave packets" have been discovered in the visual, auditory, and somatomotor cortices of rabbits that were trained to discriminate conditioned stimuli in these modalities. Each domain forms by a first order state transition, which strongly resembles a phase transition from vapor to liquid. In this view, raw sense data injected into cortex by sensory axons drive cortical action potentials in swarms like water molecules in steam. The increased activity destabilizes the cortex. Within 3 to 7 milliseconds of transition onset, the activity binds together into a state resembling a scintillating rain drop, which lasts ~80 to 100 milliseconds, then dissolves. Wave packets form at rates of 2 to 7/second in all sensory areas, overlapping in space and time. Results of sensory information processing are seen in spatial patterns of amplitude modulation (AM) of wave packets with carrier waves in the gamma range (20 to 80 Hz in rabbits). The AM patterns correspond to categories of CSs that the rabbits can discriminate. The patterns are found in electroencephalographic (EEG) potentials generated by dendrites and recorded with high-density electrode arrays. The state transitions by which AM patterns form are manifested in the spatial pattern of phase modulation (PM), which have the radial symmetry of a cone. The apex of a PM cone marks the site of nucleation of an AM pattern. The phase gradient gives a soft boundary condition, where the axonal delay in spread gives sufficient phase dispersion to reach the half-power level. The size of the wave packets (10 to 30 mm in diameter in rabbits) is determined largely by the conduction velocities of intracortical axons through which the neural cooperation is maintained. The findings show that significant cortical activity takes the form of mesoscopic interactions of millions of neurons in broad areas of cortex, which are more clearly detected in graded dendritic potentials than in action potentials. The distinction is analogous to the difference between statistical mechanical and thermodynamic descriptions of particle behavior. Both types of neural activity show spatial and temporal discontinuities but at distinctive scales of microns and msec versus mm and tenths of a second. The aim of measurement here is to establish the wave packet as the information carrier at the mesoscopic level in brain dynamics, comparable to the role of the action potential as the information carrier at the microscopic level in neuron dynamics.

scholarly journals Analysis of Spatial Patterns of Phase in Neocortical Gamma EEGs in Rabbit

2000 ◽  
Vol 84 (3) ◽  
pp. 1266-1278 ◽  
Author(s):  
Walter J. Freeman ◽  
John M. Barrie
Keyword(s):  
Spatial Coherence ◽  
Sensory Information ◽  
State Transitions ◽  
Wave Form ◽  
Conditioned Stimuli ◽  
Phase Gradient ◽  
Gamma Range ◽  
Sensory Cortices ◽  
Half Power

Arrays of 64 electrodes (8 × 8, 7 × 7 mm) were implanted epidurally on the surface of the visual, auditory or somatosensory cortex of rabbits trained to discriminate conditioned stimuli in the corresponding modality. The 64 electroencephalographic (EEG) traces at all times displayed a high degree of spatial coherence in wave form, averaging >90% of the variance in the largest principal components analysis component. The EEGs were decomposed with the fast Fourier transform (FFT) to give the spatial distributions of amplitude and phase modulation (AM and PM) in segments 128 ms in duration. Spatial (2-dimensional) and temporal (1-dimensional) filters were designed to optimize classification of the spatial AM patterns in the gamma range (20–80 Hz) with respect to discriminative conditioned stimuli. No evidence was found for stimulus-dependent classification of the spatial PM patterns. Instead some spatial PM distributions conformed to the pattern of a cone. The location and sign (maximal lead or lag) of the conic apex varied randomly with each recurrence. The slope of the phase gradient varied in a range corresponding to that of the conduction velocities reported of axons to extend parallel to the cortical surfaces. The durations and times of recurrence of the phase cones corresponded to those of the optimally classified spatial AM patterns. The interpretation is advanced that the phase cones are manifestations of state transitions in the mesoscopic dynamics of sensory cortices by which the intermittent AM patterns are formed. The phase cones show that the gamma EEG spatial coherence is not due to volume conduction from a single deep-lying dipole generator nor to activity at the site of the reference lead on monopolar recording. The random variation of the apical sign shows that gamma AM patterns are self-organized and are not imposed by thalamic pacemakers. The half-power radius of the phase gradient provides a useful measure of the soft boundary condition for the formation and read-out of cooperative cortical domains responsible for binding sensory information into the context of prior experience in the process of perception.

Recurrent Rossby wave packets and persistent extreme weather

2021 ◽  
Author(s):  
S. Mubashshir Ali ◽  
Olivia Martius ◽  
Matthias Röthlisberger
Keyword(s):  
Southern Hemisphere ◽  
Spatial Patterns ◽  
Rossby Wave ◽  
Wave Packets ◽  
Reanalysis Data ◽  
Synoptic Scale ◽  
Background Flow ◽  
Dry Spell ◽  
Upper Level ◽  
Wet Spells

<p>Upper-level synoptic-scale Rossby wave packets are well-known to affect surface weather. When these Rossby wave packets occur repeatedly in the same phase at a specific location, they can result in persistent hot, cold, dry, and wet conditions. The repeated and in-phase occurrence of Rossby wave packets is termed as recurrent synoptic-scale Rossby wave packets (RRWPs). RRWPs result from multiple transient synoptic-scale wave packets amplifying in the same geographical region over several weeks.</p><p>Our climatological analyses using reanalysis data have shown that RRWPs can significantly modulate the persistence of hot, cold, dry, and wet spells in several regions in the Northern and the Southern Hemisphere.  RRWPs can both shorten or extend hot, cold, and dry spell durations. The spatial patterns of statistically significant links between RRWPs and spell durations are distinct for the type of the spell (hot, cold, dry, or wet) and the season (MJJASO or NDJFMA). In the Northern Hemisphere, the spatial patterns where RRWPs either extend or shorten the spell durations are wave-like. In the Southern Hemisphere, the spatial patterns are either wave-like (hot and cold spells) or latitudinally banded (dry and wet spells).</p><p>Furthermore, we explore the atmospheric drivers behind RRWP events. This includes both the background flow and potential wave-triggers such as the Madden Julian Oscillation or blocking. For 100 events of intense Rossby wave recurrence in the Atlantic, the background flow, the intensity of tropical convection, and the occurrence of blocking are studied using flow composites.</p>

Editing trains of action potentials from multi-electrode arrays

2004 ◽  
Vol 134 (1) ◽  
pp. 91-100 ◽  
Author(s):  
Richard B. Stein ◽  
Douglas J. Weber
Keyword(s):  
Action Potentials ◽  
Electrode Arrays

Inter- and intra-hemispheric spatiotemporal organization of spontaneous electrocortical oscillations

1996 ◽  
Vol 76 (1) ◽  
pp. 423-437 ◽  
Author(s):  
K. D. MacDonald ◽  
B. Brett ◽  
D. S. Barth
Keyword(s):  
Time Series ◽  
Somatosensory Cortex ◽  
Phase Locking ◽  
Sensory Information ◽  
Gamma Oscillations ◽  
Sensory Cortex ◽  
Electrode Arrays ◽  
Sharp Wave ◽  
Lower Amplitude ◽  
The Right

1. Two 64-channel epipial electrode arrays were positioned on homologous locations of the right and left hemisphere, covering most of primary and secondary auditory and somatosensory cortex in eight lightly anesthetized rats. Array placement was verified with the use of cytochrome oxidase histochemistry. 2. Middle-latency auditory and somatosensory evoked potentials (MAEPs and MSEPs, respectively) and spontaneous oscillations in the frequency range of 20-40 Hz (gamma oscillations) were recorded and found to be spatially constrained to regions of granular cortex, suggesting that both phenomena are closely associated with sensory information processing. 3. The MAEP and MSEP consisted of an initial biphasic sharp wave in primary auditory and somatosensory cortex, respectively, and a similar biphasic sharp wave occurred approximately 4-8 ms later in secondary sensory cortex of the given modality. Averaged gamma oscillations also revealed asynchronous activation of sensory cortex, but with a shorter 2-ms delay between oscillations in primary and secondary regions. Although the long latency shift of the MAEP and MSEP may be due in part to asynchronous activation of parallel thalamocortical projections to primary and secondary sensory cortex, the much shorter shift of gamma oscillations in a given modality is consistent with intracortical coupling of these regions. 4. Gamma oscillations occurred independently in auditory and somatosensory cortex within a given hemisphere. Furthermore, time series averaging revealed that there was no phase-locking of oscillations between the sensory modalities. 5. Gamma oscillations were loosely coupled between hemispheres; oscillations occurring in auditory or somatosensory cortex of one hemisphere were often associated with lower-amplitude oscillations in homologous contralateral sensory cortex. Yet, the fact that time series averaging revealed no interhemispheric phase-locking suggests that the corpus callosum may not coordinate the bilateral gamma oscillations, and that a thalamic modulatory influence may be involved.

scholarly journals Neural evidence for the prediction of animacy features during language comprehension: Evidence from MEG and EEG Representational Similarity Analysis

2019 ◽  
Author(s):  
Lin Wang ◽  
Edward Wlotko ◽  
Edward Alexander ◽  
Lotte Schoot ◽  
Minjae Kim ◽  
...  
Keyword(s):  
Spatial Patterns ◽  
Language Comprehension ◽  
Neural Activity ◽  
Semantic Processing ◽  
Sentence Comprehension ◽  
Brain Activity ◽  
Coarse Grained ◽  
Similarity Analysis ◽  
Semantic Features ◽  
Representational Similarity Analysis

AbstractIt has been proposed that people can generate probabilistic predictions at multiple levels of representation during language comprehension. We used Magnetoencephalography (MEG) and Electroencephalography (EEG), in combination with Representational Similarity Analysis (RSA), to seek neural evidence for the prediction of animacy features. In two studies, MEG and EEG activity was measured as human participants (both sexes) read three-sentence scenarios. Verbs in the final sentences constrained for either animate or inanimate semantic features of upcoming nouns, and the broader discourse context constrained for either a specific noun or for multiple nouns belonging to the same animacy category. We quantified the similarity between spatial patterns of brain activity following the verbs until just before the presentation of the nouns. The MEG and EEG datasets revealed converging evidence that the similarity between spatial patterns of neural activity following animate constraining verbs was greater than following inanimate constraining verbs. This effect could not be explained by lexical-semantic processing of the verbs themselves. We therefore suggest that it reflected the inherent difference in the semantic similarity structure of the predicted animate and inanimate nouns. Moreover, the effect was present regardless of whether a specific word could be predicted, providing strong evidence for the prediction of coarse-grained semantic features that goes beyond the prediction of individual words.Significance statementLanguage inputs unfold very quickly during real-time communication. By predicting ahead we can give our brains a “head-start”, so that language comprehension is faster and more efficient. While most contexts do not constrain strongly for a specific word, they do allow us to predict some upcoming information. For example, following the context, “they cautioned the…”, we can predict that the next word will be animate rather than inanimate (we can caution a person, but not an object). Here we used EEG and MEG techniques to show that the brain is able to use these contextual constraints to predict the animacy of upcoming words during sentence comprehension, and that these predictions are associated with specific spatial patterns of neural activity.

scholarly journals Prefrontal cortical plasticity during learning of cognitive tasks

2022 ◽  
Vol 13 (1) ◽  
Author(s):  
Hua Tang ◽  
Mitchell R. Riley ◽  
Balbir Singh ◽  
Xue-Lian Qi ◽  
David T. Blake ◽  
...  
Keyword(s):  
Neural Activity ◽  
Cortical Plasticity ◽  
Cortical Activity ◽  
Phase Changes ◽  
Cognitive Tasks ◽  
Training Phase ◽  
Field Potentials ◽  
Electrode Arrays ◽  
Control Task ◽  
Prefrontal Cortical

AbstractTraining in working memory tasks is associated with lasting changes in prefrontal cortical activity. To assess the neural activity changes induced by training, we recorded single units, multi-unit activity (MUA) and local field potentials (LFP) with chronic electrode arrays implanted in the prefrontal cortex of two monkeys, throughout the period they were trained to perform cognitive tasks. Mastering different task phases was associated with distinct changes in neural activity, which included recruitment of larger numbers of neurons, increases or decreases of their firing rate, changes in the correlation structure between neurons, and redistribution of power across LFP frequency bands. In every training phase, changes induced by the actively learned task were also observed in a control task, which remained the same across the training period. Our results reveal how learning to perform cognitive tasks induces plasticity of prefrontal cortical activity, and how activity changes may generalize between tasks.

scholarly journals Multi-shanks SiNAPS Active Pixel Sensor CMOS probe: 1024 simultaneously recording channels for high-density intracortical brain mapping

2019 ◽  
Author(s):  
Fabio Boi ◽  
Nikolas Perentos ◽  
Aziliz Lecomte ◽  
Gerrit Schwesig ◽  
Stefano Zordan ◽  
...  
Keyword(s):  
Neural Activity ◽  
Brain Activity ◽  
Brain Area ◽  
Large Population ◽  
Brain Structures ◽  
High Density ◽  
Single Neurons ◽  
Electrode Arrays ◽  
Unit Recording ◽  
Recording Channels

AbstractThe advent of implantable active dense CMOS neural probes opened a new era for electrophysiology in neuroscience. These single shank electrode arrays, and the emerging tailored analysis tools, provide for the first time to neuroscientists the neurotechnology means to spatiotemporally resolve the activity of hundreds of different single-neurons in multiple vertically aligned brain structures. However, while these unprecedented experimental capabilities to study columnar brain properties are a big leap forward in neuroscience, there is the need to spatially distribute electrodes also horizontally. Closely spacing and consistently placing in well-defined geometrical arrangement multiple isolated single-shank probes is methodologically and economically impractical. Here, we present the first high-density CMOS neural probe with multiple shanks integrating thousand’s of closely spaced and simultaneously recording microelectrodes to map neural activity across 2D lattice. Taking advantage from the high-modularity of our electrode-pixels-based SiNAPS technology, we realized a four shanks active dense probe with 256 electrode-pixels/shank and a pitch of 28 µm, for a total of 1024 simultaneously recording channels. The achieved performances allow for full-band, whole-array read-outs at 25 kHz/channel, show a measured input referred noise in the action potential band (300-7000 Hz) of 6.5 ± 2.1µVRMS, and a power consumption <6 µW/electrode-pixel. Preliminary recordings in awake behaving mice demonstrated the capability of multi-shanks SiNAPS probes to simultaneously record neural activity (both LFPs and spikes) from a brain area >6 mm2, spanning cortical, hippocampal and thalamic regions. High-density 2D array enables combining large population unit recording across distributed networks with precise intra- and interlaminar/nuclear mapping of the oscillatory dynamics. These results pave the way to a new generation of high-density and extremely compact multi-shanks CMOS-probes with tunable layouts for electrophysiological mapping of brain activity at the single-neurons resolution.

scholarly journals State Transitions During Discrimination Learning in the Gerbil Auditory Cortex Analyzed by Network Causality Metrics

2021 ◽  
Vol 15 ◽  
Author(s):  
Robert Kozma ◽  
Sanqing Hu ◽  
Yury Sokolov ◽  
Tim Wanger ◽  
Andreas L. Schulz ◽  
...  
Keyword(s):  
Auditory Cortex ◽  
Discrimination Learning ◽  
Structural Changes ◽  
State Transitions ◽  
Cognitive State ◽  
Mongolian Gerbils ◽  
Electrode Arrays ◽  
Network Graph ◽  
Cortical Networks ◽  
Avoidance Strategy

This work studies the evolution of cortical networks during the transition from escape strategy to avoidance strategy in auditory discrimination learning in Mongolian gerbils trained by the well-established two-way active avoidance learning paradigm. The animals were implanted with electrode arrays centered on the surface of the primary auditory cortex and electrocorticogram (ECoG) recordings were made during performance of an auditory Go/NoGo discrimination task. Our experiments confirm previous results on a sudden behavioral change from the initial naïve state to an avoidance strategy as learning progresses. We employed two causality metrics using Granger Causality (GC) and New Causality (NC) to quantify changes in the causality flow between ECoG channels as the animals switched to avoidance strategy. We found that the number of channel pairs with inverse causal interaction significantly increased after the animal acquired successful discrimination, which indicates structural changes in the cortical networks as a result of learning. A suitable graph-theoretical model is developed to interpret the findings in terms of cortical networks evolving during cognitive state transitions. Structural changes lead to changes in the dynamics of neural populations, which are described as phase transitions in the network graph model with small-world connections. Overall, our findings underscore the importance of functional reorganization in sensory cortical areas as a possible neural contributor to behavioral changes.

scholarly journals MEA Viewer: a High-performance Interactive Application for Visualizing Electrophysiological Data

2017 ◽  
Author(s):  
Daniel C. Bridges ◽  
Kenneth R. Tovar ◽  
Bian Wu ◽  
Paul K. Hansma ◽  
Kenneth S. Kosik
Keyword(s):  
Action Potentials ◽  
High Performance ◽  
Detection Threshold ◽  
Electrode Arrays ◽  
Electrophysiological Data ◽  
Signal Average ◽  
Research Areas ◽  
Raster Plot ◽  
Data Files ◽  
Interactive Application

AbstractMulti-electrode arrays (MEAs) have been used for many years to measure electrical activity in ensembles of many hundreds of neurons, and are used in research areas as diverse as neuronal connectivity and drug discovery. A high sampling frequency is required to adequately capture action potentials, also known as spikes, the primary electrical event associated with neuronal activity, and the resulting raw data files are large and difficult to visualize with traditional plotting tools. Many common approaches to deal with this issue, such as extracting spikes times and solely performing spike train analysis, significantly reduce data dimensionality. Unbiased data exploration benefits from the use of tools that minimize data transforms and such tools enable the development of heuristic perspective from data prior to any subsequent processing. Here we introduce MEA Viewer, a high-performance interactive application for the direct visualization of multi-channel electrophysiological data. MEA Viewer provides many high-performance visualizations of electrophysiological data, including an easily navigable overview of all recorded extracellular signals overlaid with spike timestamp data and an interactive raster plot. Beyond the fundamental data displays, MEA Viewer can signal average and spatially overlay the extent of action potential propagation within single neurons. This view extracts information below the spike detection threshold to directly visualize the propagation of action potentials across the plane of the MEA. This entirely new method of using MEAs opens up new and novel research applications for medium density arrays. MEA Viewer is licensed under the General Public License version 3, GPLv3, and is available at http://github.com/dbridges/mea-tools.

scholarly journals Olfaction Modulates Early Neural Responses to Matching Visual Objects

2015 ◽  
Vol 27 (4) ◽  
pp. 832-841 ◽  
Author(s):  
Amanda K. Robinson ◽  
Judith Reinhard ◽  
Jason B. Mattingley
Keyword(s):  
Neural Activity ◽  
Visual Processing ◽  
Sensory Information ◽  
Neural Correlates ◽  
Neural Responses ◽  
Visual Objects ◽  
Cortical Areas ◽  
Early Visual Processing ◽  
Considerable Research ◽  
Matter Concentration

Sensory information is initially registered within anatomically and functionally segregated brain networks but is also integrated across modalities in higher cortical areas. Although considerable research has focused on uncovering the neural correlates of multisensory integration for the modalities of vision, audition, and touch, much less attention has been devoted to understanding interactions between vision and olfaction in humans. In this study, we asked how odors affect neural activity evoked by images of familiar visual objects associated with characteristic smells. We employed scalp-recorded EEG to measure visual ERPs evoked by briefly presented pictures of familiar objects, such as an orange, mint leaves, or a rose. During presentation of each visual stimulus, participants inhaled either a matching odor, a nonmatching odor, or plain air. The N1 component of the visual ERP was significantly enhanced for matching odors in women, but not in men. This is consistent with evidence that women are superior in detecting, discriminating, and identifying odors and that they have a higher gray matter concentration in olfactory areas of the OFC. We conclude that early visual processing is influenced by olfactory cues because of associations between odors and the objects that emit them, and that these associations are stronger in women than in men.

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