Brain Mechanisms of Conscious Awareness: Detect, Pulse, Switch, and Wave

2021 ◽  
pp. 107385842110493
Author(s):  
Hal Blumenfeld
Keyword(s):  
Neural Activity ◽  
Large Scale ◽  
Memory Systems ◽  
Attention And Memory ◽  
Conscious Awareness ◽  
Conscious Perception ◽  
Discrete Events ◽  
Cortical Regions ◽  
Large Scale Networks ◽  
Experimental Findings

Consciousness is a fascinating field of neuroscience research where questions often outnumber the answers. We advocate an open and optimistic approach where converging mechanisms in neuroscience may eventually provide a satisfactory understanding of consciousness. We first review several characteristics of conscious neural activity, including the involvement of dedicated systems for content and levels of consciousness, the distinction and overlap of mechanisms contributing to conscious states and conscious awareness of transient events, nonlinear transitions and involvement of large-scale networks, and finally the temporal nexus where conscious awareness of discrete events occurs when mechanisms of attention and memory meet. These considerations and recent new experimental findings lead us to propose an inclusive hypothesis involving four phases initiated shortly after an external sensory stimulus: (1) Detect—primary and higher cortical and subcortical circuits detect the stimulus and select it for conscious perception. (2) Pulse—a transient and massive neuromodulatory surge in subcortical-cortical arousal and salience networks amplifies signals enabling conscious perception to proceed. (3) Switch—networks that may interfere with conscious processing are switched off. (4) Wave—sequential processing through hierarchical lower to higher cortical regions produces a fully formed percept, encoded in frontoparietal working memory and medial temporal episodic memory systems for subsequent report of experience. The framework hypothesized here is intended to be nonexclusive and encourages the addition of other mechanisms with further progress. Ultimately, just as many mechanisms in biology together distinguish living from nonliving things, many mechanisms in neuroscience synergistically may separate conscious from nonconscious neural activity.

scholarly journals Failure to reactivate salient episodic information during indirect and direct tests of memory retrieval

2017 ◽  
Author(s):  
Mason H. Price ◽  
Jeffrey D. Johnson
Keyword(s):  
Boundary Condition ◽  
Episodic Memory ◽  
Neural Activity ◽  
Memory Retrieval ◽  
Conscious Awareness ◽  
Episodic Retrieval ◽  
Flicker Frequency ◽  
Test Items ◽  
Episodic Information ◽  
Cortical Regions

ABSTRACTSeveral fMRI and EEG studies have demonstrated that successful episodic retrieval is accompanied by the reactivation of cortical regions that were active during encoding. These findings are consistent with influential models of episodic memory that posit that conscious retrieval (recollection) relies on hippocampally-mediated cortical reinstatement. Evidence of reactivation corresponding to episodic information that is beyond conscious awareness at the time of memory retrieval, however, is limited. A recent exception is from an EEG study by Wimber, Maaβ, Staudigl, Richardson-Klavehn, and Hanslmayr (2012) in which words were encoded in the context of highly salient visual flicker entrainment and then presented at retrieval in the absence of any flicker. In that study, coherent (phase-locked) neural activity was observed at the corresponding entrained frequencies during retrieval, consistent with the notion that encoding representations were reactivated. Given the important implications of unconscious reactivation to past findings and the modeling literature, the current study set out to provide a direct replication of the previous study. Additionally, an attempt was made to extend such findings to intentional retrieval by acquiring EEG while subjects were explicitly asked to make memory judgments about the flicker frequency from encoding. Throughout a comprehensive set of analyses, the current study consistently failed to demonstrate evidence for unconscious reactivation, and instead provided support that test items were indistinguishable according to their prior encoding context. The findings thus establish an important boundary condition for the involvement of cortical reinstatement in episodic memory.

scholarly journals The asynchronous state's relation to large-scale potentials in cortex

2019 ◽  
Vol 122 (6) ◽  
pp. 2206-2219 ◽  
Author(s):  
A. Alishbayli ◽  
J. G. Tichelaar ◽  
U. Gorska ◽  
M. X. Cohen ◽  
B. Englitz
Keyword(s):  
Firing Rate ◽  
Clinical Diagnosis ◽  
Neural Activity ◽  
Large Scale ◽  
Cortical Activity ◽  
Spike Count ◽  
Cortical Dynamics ◽  
Brain States ◽  
Asynchronous State ◽  
Cortical Regions

Understanding the relation between large-scale potentials (M/EEG) and their underlying neural activity can improve the precision of research and clinical diagnosis. Recent insights into cortical dynamics highlighted a state of strongly reduced spike count correlations, termed the asynchronous state (AS). The AS has received considerable attention from experimenters and theorists alike, regarding its implications for cortical dynamics and coding of information. However, how reconcilable are these vanishing correlations in the AS with large-scale potentials such as M/EEG observed in most experiments? Typically the latter are assumed to be based on underlying correlations in activity, in particular between subthreshold potentials. We survey the occurrence of the AS across brain states, regions, and layers and argue for a reconciliation of this seeming disparity: large-scale potentials are either observed, first, at transitions between cortical activity states, which entail transient changes in population firing rate, as well as during the AS, and, second, on the basis of sufficiently large, asynchronous populations that only need to exhibit weak correlations in activity. Cells with no or little spiking activity can contribute to large-scale potentials via their subthreshold currents, while they do not contribute to the estimation of spiking correlations, defining the AS. Furthermore, third, the AS occurs only within particular cortical regions and layers associated with the currently selected modality, allowing for correlations at other times and between other areas and layers.

scholarly journals Restricting Visual Exploration Directly Impedes Neural Activity, Functional Connectivity, and Memory

2020 ◽  
Vol 1 (1) ◽  
Author(s):  
Zhong-Xu Liu ◽  
R Shayna Rosenbaum ◽  
Jennifer D Ryan
Keyword(s):  
Functional Connectivity ◽  
Neural Activity ◽  
Memory Systems ◽  
Visual Exploration ◽  
Basic Unit ◽  
Visual Stream ◽  
Single Location ◽  
Hippocampal Activity ◽  
Cortical Regions ◽  
Gaze Fixations

Abstract We move our eyes to explore the visual world, extract information, and create memories. The number of gaze fixations—the stops that the eyes make—has been shown to correlate with activity in the hippocampus, a region critical for memory, and with later recognition memory. Here, we combined eyetracking with fMRI to provide direct evidence for the relationships between gaze fixations, neural activity, and memory during scene viewing. Compared to free viewing, fixating a single location reduced: 1) subsequent memory, 2) neural activity along the ventral visual stream into the hippocampus, 3) neural similarity between effects of subsequent memory and visual exploration, and 4) functional connectivity among the hippocampus, parahippocampal place area, and other cortical regions. Gaze fixations were uniquely related to hippocampal activity, even after controlling for neural effects due to subsequent memory. Therefore, this study provides key causal evidence supporting the notion that the oculomotor and memory systems are intrinsically related at both the behavioral and neural level. Individual gaze fixations may provide the basic unit of information on which memory binding processes operate.

scholarly journals Decoding of cortex-wide brain activity from local recordings of neural potentials

2021 ◽  
Author(s):  
Xin Liu ◽  
Chi Ren ◽  
Zhisheng Huang ◽  
Madison Wilson ◽  
Jeong-Hoon Kim ◽  
...  
Keyword(s):  
Neural Activity ◽  
Large Scale ◽  
Neural Circuit ◽  
Brain Activity ◽  
Wide Field ◽  
Dorsal Cortex ◽  
Surface Potentials ◽  
Brain Surface ◽  
Neural Activities ◽  
Cortical Regions

Objective. Electrical recordings of neural activity from brain surface have been widely employed in basic neuroscience research and clinical practice for investigations of neural circuit functions, brain-computer interfaces, and treatments for neurological disorders. Traditionally, these surface potentials have been believed to mainly reflect local neural activity. It is not known how informative the locally recorded surface potentials are for the neural activities across multiple cortical regions. Approach. To investigate that, we perform simultaneous local electrical recording and wide-field calcium imaging in awake head-fixed mice. Using a recurrent neural network model, we try to decode the calcium fluorescence activity of multiple cortical regions from local electrical recordings. Main results. The mean activity of different cortical regions could be decoded from locally recorded surface potentials. Also, each frequency band of surface potentials differentially encodes activities from multiple cortical regions so that including all the frequency bands in the decoding model gives the highest decoding performance. Despite the close spacing between recording channels, surface potentials from different channels provide complementary information about the large-scale cortical activity and the decoding performance continues to improve as more channels are included. Finally, we demonstrate the successful decoding of whole dorsal cortex activity at pixel-level using locally recorded surface potentials. Significance. These results show that the locally recorded surface potentials indeed contain rich information of the large-scale neural activities, which could be further demixed to recover the neural activity across individual cortical regions. In the future, our cross-modality inference approach could be adapted to virtually reconstruct cortex-wide brain activity, greatly expanding the spatial reach of surface electrical recordings without increasing invasiveness. Furthermore, it could be used to facilitate imaging neural activity across the whole cortex in freely moving animals, without requirement of head-fixed microscopy configurations.

scholarly journals Contribution of Ionotropic Glutamatergic Receptors to Excitability and Attentional Signals in Macaque Frontal Eye Field

2021 ◽  
Author(s):  
Miguel Dasilva ◽  
Christian Brandt ◽  
Marc Alwin Gieselmann ◽  
Claudia Distler ◽  
Alexander Thiele
Keyword(s):  
Attentional Control ◽  
Large Scale ◽  
Neuronal Excitability ◽  
Cell Types ◽  
Receptor Activation ◽  
Frontal Eye Field ◽  
Control Signals ◽  
Cognitive Operations ◽  
Eye Field ◽  
Large Scale Networks

Abstract Top-down attention, controlled by frontal cortical areas, is a key component of cognitive operations. How different neurotransmitters and neuromodulators flexibly change the cellular and network interactions with attention demands remains poorly understood. While acetylcholine and dopamine are critically involved, glutamatergic receptors have been proposed to play important roles. To understand their contribution to attentional signals, we investigated how ionotropic glutamatergic receptors in the frontal eye field (FEF) of male macaques contribute to neuronal excitability and attentional control signals in different cell types. Broad-spiking and narrow-spiking cells both required N-methyl-D-aspartic acid and α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor activation for normal excitability, thereby affecting ongoing or stimulus-driven activity. However, attentional control signals were not dependent on either glutamatergic receptor type in broad- or narrow-spiking cells. A further subdivision of cell types into different functional types using cluster-analysis based on spike waveforms and spiking characteristics did not change the conclusions. This can be explained by a model where local blockade of specific ionotropic receptors is compensated by cell embedding in large-scale networks. It sets the glutamatergic system apart from the cholinergic system in FEF and demonstrates that a reduction in excitability is not sufficient to induce a reduction in attentional control signals.

scholarly journals How does the position of firms in the supply chain affect their performance? An empirical study

2021 ◽  
Vol 6 (1) ◽  
Author(s):  
Siddharth Arora ◽  
Alexandra Brintrup
Keyword(s):  
Supply Chain ◽  
Empirical Data ◽  
Large Scale ◽  
Individual Performance ◽  
Supply Network ◽  
Supply Chain Networks ◽  
Focal Firm ◽  
Cooperative Competition ◽  
Large Scale Networks ◽  
The Relationship

AbstractThe relationship between a firm and its supply chain has been well studied, however, the association between the position of firms in complex supply chain networks and their performance has not been adequately investigated. This is primarily due to insufficient availability of empirical data on large-scale networks. To addresses this gap in the literature, we investigate the relationship between embeddedness patterns of individual firms in a supply network and their performance using empirical data from the automotive industry. In this study, we devise three measures that characterize the embeddedness of individual firms in a supply network. These are namely: centrality, tier position, and triads. Our findings caution us that centrality impacts individual performance through a diminishing returns relationship. The second measure, tier position, allows us to investigate the concept of tiers in supply networks because we find that as networks emerge, the boundaries between tiers become unclear. Performance of suppliers degrade as they move away from the focal firm (i.e., Toyota). The final measure, triads, investigates the effect of buying and selling to firms that supply the same customer, portraying the level of competition and cooperation in a supplier’s network. We find that increased coopetition (i.e., cooperative competition) is a performance enhancer, however, excessive complexity resulting from being involved in both upstream and downstream coopetition results in diminishing performance. These original insights help understand the drivers of firm performance from a network perspective and provide a basis for further research.

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