scholarly journals Robust and distributed neural representation of action values

eLife ◽  
2021 ◽  
Vol 10 ◽  
Author(s):  
Eun Ju Shin ◽  
Yunsil Jang ◽  
Soyoun Kim ◽  
Hoseok Kim ◽  
Xinying Cai ◽  
...  
Keyword(s):  
Neural Activity ◽  
Statistical Tests ◽  
Brain Structures ◽  
Surrogate Data ◽  
Neural Representation ◽  
Decision Variables ◽  
Multiple Regions ◽  
Serial Correlations ◽  
Action Value ◽  
The Brain

Studies in rats, monkeys, and humans have found action-value signals in multiple regions of the brain. These findings suggest that action-value signals encoded in these brain structures bias choices toward higher expected rewards. However, previous estimates of action-value signals might have been inflated by serial correlations in neural activity and also by activity related to other decision variables. Here, we applied several statistical tests based on permutation and surrogate data to analyze neural activity recorded from the striatum, frontal cortex, and hippocampus. The results show that previously identified action-value signals in these brain areas cannot be entirely accounted for by concurrent serial correlations in neural activity and action value. We also found that neural activity related to action value is intermixed with signals related to other decision variables. Our findings provide strong evidence for broadly distributed neural signals related to action value throughout the brain.

scholarly journals Striatal action-value neurons reconsidered

2017 ◽  
Author(s):  
Lotem Elber-Dorozko ◽  
Yonatan Loewenstein
Keyword(s):  
Basal Ganglia ◽  
Neural Activity ◽  
Striatal Neurons ◽  
Temporal Correlations ◽  
Economic Decisions ◽  
Decision Variables ◽  
The Subject ◽  
Action Value ◽  
Do So ◽  
Value Representation

AbstractIt is generally believed that during economic decisions, striatal neurons represent the values associated with different actions. This hypothesis is based on a large number of studies, in which the neural activity of striatal neurons was measured while the subject was learning to prefer the more rewarding action. Here we show that these publications are subject to at least one of two critical confounds and that most are subject to both. First, we show that even weak temporal correlations in the neuronal data may result in an erroneous identification of action-value representations. We demonstrate this by erroneously identifying action-value representations, both in simulations and in the neural activity recorded in unrelated experiments. Second, we show that the experiments and analyses designed to dissociate action-value representation from the representation of other decision variables cannot do so. Specifically, we show that neurons representing policy may be erroneous identified as representing action-values. We suggest different solutions to identifying action-value representation that are not subject to these confounds. Applying one of these solutions to previously identified action-value neurons in the basal ganglia we fail to detect action-value representations there. Thus, we conclude that the claim that striatal neurons encode action-values must await new experiments and analyses.

scholarly journals Decoding the Brain: Neural Representation and the Limits of Multivariate Pattern Analysis in Cognitive Neuroscience

2017 ◽  
Author(s):  
J. Brendan Ritchie ◽  
David Michael Kaplan ◽  
Colin Klein
Keyword(s):  
Cognitive Neuroscience ◽  
Strong Evidence ◽  
Neural Activity ◽  
Pattern Analysis ◽  
Neural Representation ◽  
Neural Decoding ◽  
Multivariate Pattern Analysis ◽  
Neural Representations ◽  
Multivariate Pattern ◽  
The Brain

AbstractSince its introduction, multivariate pattern analysis (MVPA), or “neural decoding”, has transformed the field of cognitive neuroscience. Underlying its influence is a crucial inference, which we call the Decoder’s Dictum: if information can be decoded from patterns of neural activity, then this provides strong evidence about what information those patterns represent. Although the Dictum is a widely held and well-motivated principle in decoding research, it has received scant philosophical attention. We critically evaluate the Dictum, arguing that it is false: decodability is a poor guide for revealing the content of neural representations. However, we also suggest how the Dictum can be improved on, in order to better justify inferences about neural representation using MVPA.

scholarly journals Spatio-temporal Characteristics of Noun and Verb Processing during Sentence Comprehension in the Brain

2020 ◽  
Author(s):  
Sharmistha Jat ◽  
Erika J C Laing ◽  
Partha Talukdar ◽  
Tom Mitchell
Keyword(s):  
Neural Activity ◽  
Sentence Comprehension ◽  
Question Answering ◽  
Neural Representation ◽  
Temporal Characteristics ◽  
Sentence Reading ◽  
Read Word ◽  
Spatio Temporal ◽  
Cortical Regions ◽  
The Brain

AbstractThe human brain is very effective at integrating new words one by one into the composed representation of a sentence as it is read left-to-right. This raises the important question of what happens to the neural representations of words present earlier in the sentence? For example, do the strength of word representations encountered earlier on in the sentence remain constant or do they evolve as additional words are processed? Representation of words by neural activity in the brain has been the subject of several previous studies. We perform the experiment with a naturalistic task in which the subjects read simple active and passive sentences. Naturalistic studies have tended to explore words in isolation or in a very limited context (e.g., adjective-noun phrases). Representation of previously encountered words during incremental sentence reading, and how such representation evolve as more parts of a sentence are read, is a fundamental but unexplored problem – we take a first step in this direction. In particular, we examine the spatio-temporal characteristics of neural activity encoding nouns and verbs encountered in a sentence as it is read word-by-word. We use Magnetoencephalography (MEG) to passively observe neural activity, providing 1 ms temporal resolution.Our experiments reveal that nouns and verbs read early in the sentence have a varying influence on neural activity while reading subsequent words, decreasing and increasing at particular word positions in active and passively voiced sentences, with particularly important contributions to activity in frontal and temporal cortical regions. We find the noun and verb information to be decodable from the neural activity for several seconds after sentence reading has completed. Our exploration is also the first to study the effect of question-answering task on the neural representation of the words post-sentence. We are releasing our 300 sentence MEG dataset to encourage further research in this important area.

Anticipation of temporally structured events in the brain

2020 ◽  
Author(s):  
Caroline S Lee ◽  
Mariam Aly ◽  
Christopher Baldassano
Keyword(s):  
Human Brain ◽  
Neural Activity ◽  
Hidden Markov ◽  
Temporal Structure ◽  
Activity Patterns ◽  
Subjective Experiences ◽  
Movie Clip ◽  
Multiple Regions ◽  
Neural Event ◽  
The Brain

Learning about temporal structure is adaptive because it enables the generation of expectations. We examined how the brain uses experience in structured environments to anticipate upcoming events. During fMRI, individuals watched a 90-second movie clip six times. Using a Hidden Markov Model applied to searchlights across the whole brain, we identified temporal shifts between activity patterns evoked by the first vs. repeated viewings of the movie clip. In multiple regions throughout the cortex, neural activity patterns for repeated viewings shifted to preceded those of initial viewing by up to 12 seconds. This anticipation varied hierarchically in a posterior (less anticipation) to anterior (more anticipation) fashion. In a subset of these regions, neural event boundaries shifted with repeated viewing to precede subjective event boundaries by 5-7 seconds. Together, these results demonstrate a hierarchy of anticipatory signals in the human brain and link them to subjective experiences of events.

Introduction

2001 ◽  
Vol 4 (2) ◽  
pp. 101-103
Author(s):  
David W. Green
Keyword(s):  
Language Processing ◽  
Neural Activity ◽  
Neural Representation ◽  
Special Issue ◽  
Neural Basis ◽  
And Control ◽  
The Brain ◽  
Electrophysiological Methods ◽  
Neuroimaging Techniques ◽  
Do So

The papers in this Special Issue focus on the use of neuroimaging techniques to answer questions about the neural representation, processing and control of two languages. Neuropsychological data from bilingual aphasics remain vital if we are to establish the neural basis of language (see Paradis, 1995) but lesion-deficit studies alone cannot tell us how neural activity relates to ongoing language processing. Modern neuroimaging methods provide a means to do so. There are two broad classes of such methods: electrophysiological methods allow us to answer questions about when a particular process occurs whereas haemodynamic methods allow us to answer the complementary question of where in the brain such a process is carried out. Before giving a thumb-nail sketch of the papers in this Special Issue, I briefly discuss each class of method.

scholarly journals Mirror neurons are modulated by grip force and reward expectation in the sensorimotor cortices (S1, M1, PMd, PMv)

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Md Moin Uddin Atique ◽  
Joseph Thachil Francis
Keyword(s):  
Neural Activity ◽  
Visual Information ◽  
Mirror Neurons ◽  
Grip Force ◽  
Neural Representation ◽  
Virtual Object ◽  
Time Lags ◽  
Subjective Value ◽  
Machine Interface ◽  
Definition Of

AbstractMirror Neurons (MNs) respond similarly when primates make or observe grasping movements. Recent work indicates that reward expectation influences rostral M1 (rM1) during manual, observational, and Brain Machine Interface (BMI) reaching movements. Previous work showed MNs are modulated by subjective value. Here we expand on the above work utilizing two non-human primates (NHPs), one male Macaca Radiata (NHP S) and one female Macaca Mulatta (NHP P), that were trained to perform a cued reward level isometric grip-force task, where the NHPs had to apply visually cued grip-force to move and transport a virtual object. We found a population of (S1 area 1–2, rM1, PMd, PMv) units that significantly represented grip-force during manual and observational trials. We found the neural representation of visually cued force was similar during observational trials and manual trials for the same units; however, the representation was weaker during observational trials. Comparing changes in neural time lags between manual and observational tasks indicated that a subpopulation fit the standard MN definition of observational neural activity lagging the visual information. Neural activity in (S1 areas 1–2, rM1, PMd, PMv) significantly represented force and reward expectation. In summary, we present results indicating that sensorimotor cortices have MNs for visually cued force and value.

scholarly journals Peptides Derived from Growth Factors to Treat Alzheimer’s Disease

2021 ◽  
Vol 22 (11) ◽  
pp. 6071
Author(s):  
Suzanne Gascon ◽  
Jessica Jann ◽  
Chloé Langlois-Blais ◽  
Mélanie Plourde ◽  
Christine Lavoie ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Growth Factors ◽  
Signaling Pathways ◽  
Brain Structures ◽  
Therapeutic Strategies ◽  
Native Proteins ◽  
Receptor Sites ◽  
The Brain

Alzheimer’s disease (AD) is a devastating neurodegenerative disease characterized by progressive neuron losses in memory-related brain structures. The classical features of AD are a dysregulation of the cholinergic system, the accumulation of amyloid plaques, and neurofibrillary tangles. Unfortunately, current treatments are unable to cure or even delay the progression of the disease. Therefore, new therapeutic strategies have emerged, such as the exogenous administration of neurotrophic factors (e.g., NGF and BDNF) that are deficient or dysregulated in AD. However, their low capacity to cross the blood–brain barrier and their exorbitant cost currently limit their use. To overcome these limitations, short peptides mimicking the binding receptor sites of these growth factors have been developed. Such peptides can target selective signaling pathways involved in neuron survival, differentiation, and/or maintenance. This review focuses on growth factors and their derived peptides as potential treatment for AD. It describes (1) the physiological functions of growth factors in the brain, their neuronal signaling pathways, and alteration in AD; (2) the strategies to develop peptides derived from growth factor and their capacity to mimic the role of native proteins; and (3) new advancements and potential in using these molecules as therapeutic treatments for AD, as well as their limitations.

scholarly journals The Brain Resting-State Functional Connectivity Underlying Violence Proneness: Is It a Reliable Marker for Neurocriminology? A Systematic Review

2019 ◽  
Vol 9 (1) ◽  
pp. 11 ◽  
Author(s):  
Ángel Romero-Martínez ◽  
Macarena González ◽  
Marisol Lila ◽  
Enrique Gracia ◽  
Luis Martí-Bonmatí ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Effective Treatment ◽  
Resting State ◽  
Brain Structures ◽  
Prevention Programs ◽  
Angular Gyrus ◽  
Resting State Functional Connectivity ◽  
Treatment And Prevention ◽  
Reliable Marker ◽  
The Brain

Introduction: There is growing scientific interest in understanding the biological mechanisms affecting and/or underlying violent behaviors in order to develop effective treatment and prevention programs. In recent years, neuroscientific research has tried to demonstrate whether the intrinsic activity within the brain at rest in the absence of any external stimulation (resting-state functional connectivity; RSFC) could be employed as a reliable marker for several cognitive abilities and personality traits that are important in behavior regulation, particularly, proneness to violence. Aims: This review aims to highlight the association between the RSFC among specific brain structures and the predisposition to experiencing anger and/or responding to stressful and distressing situations with anger in several populations. Methods: The scientific literature was reviewed following the PRISMA quality criteria for reviews, using the following digital databases: PubMed, PsycINFO, Psicodoc, and Dialnet. Results: The identification of 181 abstracts and retrieval of 34 full texts led to the inclusion of 17 papers. The results described in our study offer a better understanding of the brain networks that might explain the tendency to experience anger. The majority of the studies highlighted that diminished RSFC between the prefrontal cortex and the amygdala might make people prone to reactive violence, but that it is also necessary to contemplate additional cortical (i.e. insula, gyrus [angular, supramarginal, temporal, fusiform, superior, and middle frontal], anterior and posterior cingulated cortex) and subcortical brain structures (i.e. hippocampus, cerebellum, ventral striatum, and nucleus centralis superior) in order to explain a phenomenon as complex as violence. Moreover, we also described the neural pathways that might underlie proactive violence and feelings of revenge, highlighting the RSFC between the OFC, ventral striatal, angular gyrus, mid-occipital cortex, and cerebellum. Conclusions. The results from this synthesis and critical analysis of RSFC findings in several populations offer guidelines for future research and for developing a more accurate model of proneness to violence, in order to create effective treatment and prevention programs.

scholarly journals Glia Not Neurons: Uncovering Brain Dysmaturation in a Rat Model of Alzheimer’s Disease

Biomedicines ◽  
2021 ◽  
Vol 9 (7) ◽  
pp. 823
Author(s):  
Ekaterina A. Rudnitskaya ◽  
Tatiana A. Kozlova ◽  
Alena O. Burnyasheva ◽  
Natalia A. Stefanova ◽  
Nataliya G. Kolosova
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Prefrontal Cortex ◽  
Brain Structures ◽  
Time Frame ◽  
Oxys Rats ◽  
Unknown Etiology ◽  
Suitable Model ◽  
Model Of Alzheimer’S Disease ◽  
The Brain

Sporadic Alzheimer’s disease (AD) is a severe disorder of unknown etiology with no definite time frame of onset. Recent studies suggest that middle age is a critical period for the relevant pathological processes of AD. Nonetheless, sufficient data have accumulated supporting the hypothesis of “neurodevelopmental origin of neurodegenerative disorders”: prerequisites for neurodegeneration may occur during early brain development. Therefore, we investigated the development of the most AD-affected brain structures (hippocampus and prefrontal cortex) using an immunohistochemical approach in senescence-accelerated OXYS rats, which are considered a suitable model of the most common—sporadic—type of AD. We noticed an additional peak of neurogenesis, which coincides in time with the peak of apoptosis in the hippocampus of OXYS rats on postnatal day three. Besides, we showed signs of delayed migration of neurons to the prefrontal cortex as well as disturbances in astrocytic and microglial support of the hippocampus and prefrontal cortex during the first postnatal week. Altogether, our results point to dysmaturation during early development of the brain—especially insufficient glial support—as a possible “first hit” leading to neurodegenerative processes and AD pathology manifestation later in life.

scholarly journals Consciousness, decision making, and volition: freedom beyond chance and necessity

2021 ◽  
Author(s):  
Hans Liljenström
Keyword(s):  
Decision Making ◽  
Free Will ◽  
Brain Activity ◽  
Brain Structures ◽  
Complex Process ◽  
Neural Information ◽  
Neural Information Processing ◽  
Stochastic Population Model ◽  
The Brain

AbstractWhat is the role of consciousness in volition and decision-making? Are our actions fully determined by brain activity preceding our decisions to act, or can consciousness instead affect the brain activity leading to action? This has been much debated in philosophy, but also in science since the famous experiments by Libet in the 1980s, where the current most common interpretation is that conscious free will is an illusion. It seems that the brain knows, up to several seconds in advance what “you” decide to do. These studies have, however, been criticized, and alternative interpretations of the experiments can be given, some of which are discussed in this paper. In an attempt to elucidate the processes involved in decision-making (DM), as an essential part of volition, we have developed a computational model of relevant brain structures and their neurodynamics. While DM is a complex process, we have particularly focused on the amygdala and orbitofrontal cortex (OFC) for its emotional, and the lateral prefrontal cortex (LPFC) for its cognitive aspects. In this paper, we present a stochastic population model representing the neural information processing of DM. Simulation results seem to confirm the notion that if decisions have to be made fast, emotional processes and aspects dominate, while rational processes are more time consuming and may result in a delayed decision. Finally, some limitations of current science and computational modeling will be discussed, hinting at a future development of science, where consciousness and free will may add to chance and necessity as explanation for what happens in the world.

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