scholarly journals Revealing the information contents of memory within the stimulus information representation framework

2020 ◽  
Vol 375 (1799) ◽  
pp. 20190705 ◽  
Author(s):  
Philippe G. Schyns ◽  
Jiayu Zhan ◽  
Rachael E. Jack ◽  
Robin A. A. Ince
Keyword(s):  
Predictive Coding ◽  
Specific Information ◽  
Information Representation ◽  
Stimulus Information ◽  
Reverse Engineer ◽  
Visual Hierarchy ◽  
Information Contents ◽  
Categorical Knowledge ◽  
Sensory Evidence ◽  
The Brain

The information contents of memory are the cornerstone of the most influential models in cognition. To illustrate, consider that in predictive coding, a prediction implies that specific information is propagated down from memory through the visual hierarchy. Likewise, recognizing the input implies that sequentially accrued sensory evidence is successfully matched with memorized information (categorical knowledge). Although the existing models of prediction, memory, sensory representation and categorical decision are all implicitly cast within an information processing framework, it remains a challenge to precisely specify what this information is, and therefore where , when and how the architecture of the brain dynamically processes it to produce behaviour. Here, we review a framework that addresses these challenges for the studies of perception and categorization–stimulus information representation (SIR). We illustrate how SIR can reverse engineer the information contents of memory from behavioural and brain measures in the context of specific cognitive tasks that involve memory. We discuss two specific lessons from this approach that generally apply to memory studies: the importance of task, to constrain what the brain does, and of stimulus variations, to identify the specific information contents that are memorized, predicted, recalled and replayed. This article is part of the Theo Murphy meeting issue ‘Memory reactivation: replaying events past, present and future’.

scholarly journals Making the brain-activity-to-information leap using a novel framework: Stimulus Information Representation (SIR)

2019 ◽  
Author(s):  
Philippe G. Schyns ◽  
Robin A.A. Ince
Keyword(s):  
Brain Imaging ◽  
Brain Activity ◽  
Behavioral Responses ◽  
Data Driven ◽  
Information Representation ◽  
Stimulus Information ◽  
Fundamental Challenge ◽  
Per Se ◽  
The Brain ◽  
Different Levels

AbstractA fundamental challenge in neuroscience is to understand how the brain processes information. Neuroscientists have approached this question partly by measuring brain activity in space, time and at different levels of granularity. However, our aim is not to discover brain activity per se, but to understand the processing of information that this activity reflects. To make this brain-activity-to-information leap, we believe that we should reconsider brain imaging from the methodological foundations of psychology. With this goal in mind, we have developed a new data-driven framework, called Stimulus Information Representation (SIR), that enables us to better understand how the brain processes information from measures of brain activity and behavioral responses. In this article, we explain this approach, its strengths and limitations, and how it can be applied to understand how the brain processes information to perform behavior in a task.“It is no good poking around in the brain without some idea of what one is looking for. That would be like trying to find a needle in a haystack without having any idea what needles look like. The theorist is the [person] who might reasonably be asked for [their] opinion about the appearance of needles.” HC Longuet-Higgins, 1969.

scholarly journals Expectation and attention increase the integration of top-down and bottom-up signals in perception through different pathways

2018 ◽  
Author(s):  
Noam Gordon ◽  
Naotsugu Tsuchiya ◽  
Roger Koenig-Robert ◽  
Jakob Hohwy
Keyword(s):  
Predictive Coding ◽  
Sensory Information ◽  
Phase Coherence ◽  
Signal Integration ◽  
Physiological Measures ◽  
Top Down ◽  
Bottom Up ◽  
Visual Hierarchy ◽  
Linear Signal ◽  
The Brain

AbstractPerception results from the integration of incoming sensory information with pre-existing information available in the brain. In this EEG (electroencephalography) study we utilised the Hierarchical Frequency Tagging method to examine how such integration is modulated by expectation and attention. Using intermodulation (IM) components as a measure of non-linear signal integration, we show in three different experiments that both expectation and attention enhance integration between top-down and bottom-up signals. Based on multispectral phase coherence, we present two direct physiological measures to demonstrate the distinct yet related mechanisms of expectation and attention. Specifically, our results link expectation to the modulation of prediction signals and the integration of top-down and bottom-up information at lower levels of the visual hierarchy. Meanwhile, they link attention to the propagation of ascending signals and the integration of information at higher levels of the visual hierarchy. These results are consistent with the predictive coding account of perception.

scholarly journals Where and how our brain represents the temporal structure of observed action

2018 ◽  
Author(s):  
R.M. Thomas ◽  
T. De Sanctis ◽  
V. Gazzola ◽  
C. Keysers
Keyword(s):  
Motor System ◽  
Action Observation ◽  
Temporal Structure ◽  
Predictive Coding ◽  
Specific Information ◽  
Visual Responses ◽  
The Brain ◽  
Motor Acts ◽  
Individual Motor

AbstractReacting faster to the behavior of others provides evolutionary advantages. Reacting to unpredictable events takes hundreds of milliseconds. Understanding where and how the brain represents what actions are likely to follow one another is therefore important. Everyday actions are predictable sequences of acts, yet neuroscientists focus on how brains responds to unexpected, individual motor acts. Using fMRI we show the brain encodes sequence-specific information in the motor system. Using EEG, we show visual responses were faster and smaller for predictable sequences that recruit the motor system. This study shifts the study of action observation from single acts to motor sequences, informs how we adapt to the actions of others and suggests the motor system may implement perceptual predictive coding.

Information-based decoding of the coupling among human brain activity and movement paths

2021 ◽  
pp. 1-10
Author(s):  
Shahul Mujib Kamal ◽  
Norazryana Mat Dawi ◽  
Hamidreza Namazi
Keyword(s):  
Brain Activity ◽  
Point Of View ◽  
Physiological Signals ◽  
Human Walking ◽  
Eeg Signals ◽  
Rehabilitation Science ◽  
Information Contents ◽  
First Time ◽  
The Brain ◽  
Brain Reaction

BACKGROUND: Walking like many other actions of a human is controlled by the brain through the nervous system. In fact, if a problem occurs in our brain, we cannot walk correctly. Therefore, the analysis of the coupling of brain activity and walking is very important especially in rehabilitation science. The complexity of movement paths is one of the factors that affect human walking. For instance, if we walk on a path that is more complex, our brain activity increases to adjust our movements. OBJECTIVE: This study for the first time analyzed the coupling of walking paths and brain reaction from the information point of view. METHODS: We analyzed the Shannon entropy for electroencephalography (EEG) signals versus the walking paths in order to relate their information contents. RESULTS: According to the results, walking on a path that contains more information causes more information in EEG signals. A strong correlation (p= 0.9999) was observed between the information contents of EEG signals and walking paths. Our method of analysis can also be used to investigate the relation among other physiological signals of a human and walking paths, which has great benefits in rehabilitation science.

scholarly journals The brain timewise: how timing shapes and supports brain function

2015 ◽  
Vol 370 (1668) ◽  
pp. 20140170 ◽  
Author(s):  
Riitta Hari ◽  
Lauri Parkkonen
Keyword(s):  
Human Brain ◽  
Brain Imaging ◽  
Brain Function ◽  
Temporal Dynamics ◽  
Generative Models ◽  
Network Activity ◽  
Brain Diseases ◽  
Specific Information ◽  
Non Invasive ◽  
The Brain

We discuss the importance of timing in brain function: how temporal dynamics of the world has left its traces in the brain during evolution and how we can monitor the dynamics of the human brain with non-invasive measurements. Accurate timing is important for the interplay of neurons, neuronal circuitries, brain areas and human individuals. In the human brain, multiple temporal integration windows are hierarchically organized, with temporal scales ranging from microseconds to tens and hundreds of milliseconds for perceptual, motor and cognitive functions, and up to minutes, hours and even months for hormonal and mood changes. Accurate timing is impaired in several brain diseases. From the current repertoire of non-invasive brain imaging methods, only magnetoencephalography (MEG) and scalp electroencephalography (EEG) provide millisecond time-resolution; our focus in this paper is on MEG. Since the introduction of high-density whole-scalp MEG/EEG coverage in the 1990s, the instrumentation has not changed drastically; yet, novel data analyses are advancing the field rapidly by shifting the focus from the mere pinpointing of activity hotspots to seeking stimulus- or task-specific information and to characterizing functional networks. During the next decades, we can expect increased spatial resolution and accuracy of the time-resolved brain imaging and better understanding of brain function, especially its temporal constraints, with the development of novel instrumentation and finer-grained, physiologically inspired generative models of local and network activity. Merging both spatial and temporal information with increasing accuracy and carrying out recordings in naturalistic conditions, including social interaction, will bring much new information about human brain function.

scholarly journals A continuum hypothesis of psychotomimetic rapid antidepressants

2021 ◽  
Vol 5 ◽  
pp. 239821282110077
Author(s):  
Joost Haarsma ◽  
Catherine J Harmer ◽  
Sandra Tamm
Keyword(s):  
Continuum Hypothesis ◽  
Sense Of Self ◽  
Predictive Coding ◽  
Common Mechanism ◽  
Symptoms Of Depression ◽  
Research Areas ◽  
Sensory Evidence ◽  
Perceptual Distortions ◽  
Psychotomimetic Effects

Ketamine, classical psychedelics and sleep deprivation are associated with rapid effects on depression. Interestingly, these interventions also have common psychotomimetic actions, mirroring aspects of psychosis such as an altered sense of self, perceptual distortions and distorted thinking. This raises the question whether these interventions might be acute antidepressants through the same mechanisms that underlie some of their psychotomimetic effects. That is, perhaps some symptoms of depression can be understood as occupying the opposite end of a spectrum where elements of psychosis can be found on the other side. This review aims at reviewing the evidence underlying a proposed continuum hypothesis of psychotomimetic rapid antidepressants, suggesting that a range of psychotomimetic interventions are also acute antidepressants as well as trying to explain these common features in a hierarchical predictive coding framework, where we hypothesise that these interventions share a common mechanism by increasing the flexibility of prior expectations. Neurobiological mechanisms at play and the role of different neuromodulatory systems affected by these interventions and their role in controlling the precision of prior expectations and new sensory evidence will be reviewed. The proposed hypothesis will also be discussed in relation to other existing theories of antidepressants. We also suggest a number of novel experiments to test the hypothesis and highlight research areas that could provide further insights, in the hope to better understand the acute antidepressant properties of these interventions.

Cannabidiol Has a Unique Effect on Global Brain Activity: A Pharmacological, Functional MRI Study in Awake Mice 

2021 ◽  
Author(s):  
Aymen Sadaka ◽  
Ana Ozuna ◽  
Richard Ortiz ◽  
Praveen Kulkarni ◽  
Clare Johnson ◽  
...  
Keyword(s):  
Prefrontal Cortex ◽  
Brain Activity ◽  
Stress Disorders ◽  
Functional Coupling ◽  
Specific Information ◽  
Imaging Data ◽  
Post Traumatic Stress ◽  
Brain Areas ◽  
Dose Dependent ◽  
The Brain

Abstract Background: The phytocannabinoid cannabidiol (CBD) is a potential treatment for post-traumatic stress disorders. How does CBD interact with the brain to alter behavior? We hypothesized that CBD would produce a dose-dependent reduction in brain activity and functional coupling in neural circuitry associated with fear and defense. Methods: During the scanning session awake mice were given vehicle or CBD (3, 10, or 30 mg/kg I.P.) and imaged for 10 min post treatment. Mice were also treated with the 10 mg/kg dose of CBD and imaged one hr later for resting state BOLD functional connectivity (rsFC). Imaging data were registered to a 3D MRI mouse atlas providing site-specific information on 138 different brain areas. Blood samples were collected for CBD measurements.Results: CBD produced a dose-dependent polarization of activation along the rostral-caudal axis of the brain. The olfactory bulb and prefrontal cortex showed an increase in positive BOLD whereas the brainstem and cerebellum showed a decrease in BOLD signal. This negative BOLD affected many areas connected to the ascending reticular activating system (ARAS). The ARAS was decoupled to much of the brain but was hyperconnected to the olfactory system and prefrontal cortex. The pattern of ARAS connectivity closely overlapped with brain areas showing high levels N-acyl-phosphatidylethanolamines-specific phospholipase D (NAPE-PLD) messenger RNA.Conclusion: The CBD-induced decrease in ARAS activity is consistent with an emerging literature suggesting that CBD reduces autonomic arousal under conditions of emotional and physical stress. The putative target and mechanism of action is NAPE-PLD the enzyme responsible for the biosynthesis of lipid signaling molecules like anandamide.

scholarly journals Using Connectivity to Explain Autism

2019 ◽  
Author(s):  
Jack Adamek ◽  
Yu Luo ◽  
Joshua Ewen
Keyword(s):  
Scientific Explanation ◽  
Causal Explanation ◽  
Autism Spectrum ◽  
Imaging Method ◽  
Imaging Data ◽  
Reverse Engineer ◽  
Physiological Processes ◽  
The Mind ◽  
The Brain

The chapters in this Handbook reveal the breadth of brilliant imaging and analysis techniques designed to fulfill the mandate of cognitive neuroscience: to understand how anatomical structures and physiological processes in the brain cause typical and atypical behavior. Yet merely producing data from the latest imaging method is insufficient to truly achieve this goal. We also need a mental toolbox that contains methods of inference that allow us to derive true scientific explanation from these data. Causal inference is not easy in the human brain, where we are limited primarily to observational data and our methods of experimental perturbation in the service of causal explanation are limited. As a case study, we reverse engineer one of the most influential accounts of a neuropsychiatric disorder that is derived from observational imaging data: the connectivity theories of autism spectrum disorder (ASD). We take readers through an approach of first considering all possible causal paths that are allowed by preliminary imaging-behavioral correlations. By progressively sharpening the specificity of the measures and brain/behavioral constructs, we iteratively chip away at this space of allowable causal paths, like the sculptor chipping away the excess marble to reveal the statue. To assist in this process, we consider how current imaging methods that are lumped together under the rubric of “connectivity” may actually offer a differentiated set of connectivity constructs that can more specifically relate notions of information transmission in the mind to the physiology of the brain.

Decoding the coupling between the brain and skin reactions in auditory stimulation by information-based analysis of EEG and GSR signals

2021 ◽  
pp. 1-10
Author(s):  
Najmeh Pakniyat ◽  
Hamidreza Namazi
Keyword(s):  
Brain Activity ◽  
Skin Resistance ◽  
Research Area ◽  
Important Research ◽  
Skin Reactions ◽  
Analysis Technique ◽  
Information Contents ◽  
Important Research Area ◽  
Electroencephalogram Eeg ◽  
The Brain

BACKGROUND: The analysis of brain activity in different conditions is an important research area in neuroscience. OBJECTIVE: This paper analyzed the correlation between the brain and skin activities in rest and stimulations by information-based analysis of electroencephalogram (EEG) and galvanic skin resistance (GSR) signals. METHODS: We recorded EEG and GSR signals of eleven subjects during rest and auditory stimulations using three pieces of music that were differentiated based on their complexity. Then, we calculated the Shannon entropy of these signals to quantify their information contents. RESULTS: The results showed that music with greater complexity has a more significant effect on altering the information contents of EEG and GSR signals. We also found a strong correlation (r= 0.9682) among the variations of the information contents of EEG and GSR signals. Therefore, the activities of the skin and brain are correlated in different conditions. CONCLUSION: This analysis technique can be utilized to evaluate the correlation among the activities of various organs versus brain activity in different conditions.

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