scholarly journals The primacy of behavioral research for understanding the brain

2020 ◽  
Author(s):  
Yael Niv
Keyword(s):  
Neural Mechanism ◽  
Behavioral Research ◽  
Mechanistic Models ◽  
Scientific Journals ◽  
Neural Data ◽  
Behavioral Paradigm ◽  
The Brain

Understanding the brain requires us to answer both what the brain does, and how it does it. Using a series of examples, I make the case that behavior is often more useful than neuroscientific measurements for answering the first question. Moreover, I show that even for “how” questions that pertain to neural mechanism, a well-crafted behavioral paradigm can offer deeper insight and stronger constraints on computational and mechanistic models than do many highly challenging (and very expensive) neural studies. I conclude that behavioral, rather than neuroscientific research, is essential for understanding the brain, contrary to the opinion of prominent funding bodies and scientific journals, who erroneously place neural data on a pedestal and consider behavior to be subsidiary.

Neural Mechanisms of Negative Symptoms

1989 ◽  
Vol 155 (S7) ◽  
pp. 93-98 ◽  
Author(s):  
Nancy C. Andreasen
Keyword(s):  
Frontal Cortex ◽  
Negative Symptoms ◽  
Neural Mechanism ◽  
Brain Regions ◽  
Brain Dysfunction ◽  
Neural Mechanisms ◽  
Dementia Praecox ◽  
Intellectual Abilities ◽  
The Brain ◽  
Psychic Mechanisms

When Kraepelin originally defined and described dementia praecox, he assumed that it was due to some type of neural mechanism. He hypothesised that abnormalities could occur in a variety of brain regions, including the prefrontal, auditory, and language regions of the cortex. Many members of his department, including Alzheimer and Nissl, were actively involved in the search for the neuropathological lesions that would characterise schizophrenia. Although Kraepelin did not use the term ‘negative symptoms', he describes them comprehensively and states explicitly that he believes the symptoms of schizophrenia can be explained in terms of brain dysfunction:“If it should be confirmed that the disease attacks by preference the frontal areas of the brain, the central convolutions and central lobes, this distribution would in a certain measure agree with our present views about the site of the psychic mechanisms which are principally injured by the disease. On various grounds, it is easy to believe that the frontal cortex, which is specially well developed in man, stands in closer relation to his higher intellectual abilities, and these are the faculties which in our patients invariably suffer profound loss in contrast to memory and acquired ability.” Kraepelin (1919, p. 219)

NEUROECONOMICS, NEUROPHYSIOLOGY AND THE COMMON CURRENCY HYPOTHESIS

2008 ◽  
Vol 24 (3) ◽  
pp. 419-429 ◽  
Author(s):  
Anthony Landreth ◽  
John Bickle
Keyword(s):  
Rational Choice ◽  
Dopamine Release ◽  
Research Programme ◽  
Neural Mechanism ◽  
The Other ◽  
Common Currency ◽  
The Common ◽  
The Brain ◽  
Electrophysiological Methods

We briefly describe ways in which neuroeconomics has made contributions to its contributing disciplines, especially neuroscience, and a specific way in which it could make future contributions to both. The contributions of a scientific research programme can be categorized in terms of (1) description and classification of phenomena, (2) the discovery of causal relationships among those phenomena, and (3) the development of tools to facilitate (1) and (2). We consider ways in which neuroeconomics has advanced neuroscience and economics along each line. Then, focusing on electrophysiological methods, we consider a puzzle within neuroeconomics whose solution we believe could facilitate contributions to both neuroscience and economics, in line with category (2). This puzzle concerns how the brain assigns reward values to otherwise incomparable stimuli. According to the common currency hypothesis, dopamine release is a component of a neural mechanism that solves comparability problems. We review two versions of the common currency hypothesis, one proposed by Read Montague and colleagues, the other by William Newsome and colleagues, and fit these hypotheses into considerations of rational choice.

scholarly journals Distributed context-dependent choice information in mouse dorsal-parietal cortex

2021 ◽  
Author(s):  
Javier Orlandi ◽  
Mohammad Adbolrahmani ◽  
Ryo Aoki ◽  
Dmitry Lyamzin ◽  
Andrea Benucci
Keyword(s):  
Decision Making ◽  
Decision Variable ◽  
Visual Stream ◽  
Posterior Cortex ◽  
Neural Data ◽  
Context Dependent ◽  
Cortical Regions ◽  
Low Dimensional ◽  
Independent Decision ◽  
The Brain

Abstract Choice information appears in the brain as distributed signals with top-down and bottom-up components that together support decision-making computations. In sensory and associative cortical regions, the presence of choice signals, their strength, and area specificity are known to be elusive and changeable, limiting a cohesive understanding of their computational significance. In this study, examining the mesoscale activity in mouse posterior cortex during a complex visual discrimination task, we found that broadly distributed choice signals defined a decision variable in a low-dimensional embedding space of multi-area activations, particularly along the ventral visual stream. The subspace they defined was near-orthogonal to concurrently represented sensory and motor-related activations, and it was modulated by task difficulty and contextually by the animals’ attention state. To mechanistically relate choice representations to decision-making computations, we trained recurrent neural networks with the animals’ choices and found an equivalent decision variable whose context-dependent dynamics agreed with that of the neural data. In conclusion, our results demonstrated an independent decision variable broadly represented in the posterior cortex, controlled by task features and cognitive demands. Its dynamics reflected decision computations, possibly linked to context-dependent feedback signals used for probabilistic-inference computations in variable animal-environment interactions.

Plasticity: Cells, Circuits, Brains, and Behavior

2016 ◽  
Author(s):  
Patricia S. Churchland ◽  
Terrence J. Sejnowski
Keyword(s):  
Nervous System ◽  
Synaptic Plasticity ◽  
Classical Conditioning ◽  
Neuronal Plasticity ◽  
Neural Mechanism ◽  
Synaptic Strength ◽  
Physical Mechanisms ◽  
And Behavior ◽  
The Brain

This chapter examines the physical mechanisms in nervous systems in order to elucidate the structural bases and functional principles of synaptic plasticity. Neuroscientific research on plasticity can be divided into four main streams: the neural mechanism for relatively simple kinds of plasticity, such as classical conditioning or habituation; anatomical and physiological studies of temporal lobe structures, including the hippocampus and the amygdala; study of the development of the visual system; and the relation between the animal's genes and the development of its nervous system. The chapter first considers the role of the mammalian hippocampus in learning and memory before discussing Donald Hebb's views on synaptic plasticity. It then explores the mechanisms underlying neuronal plasticity and those that decrease synaptic strength, the relevance of time with respect to plasticity, and the occurrence of plasticity during the development of the nervous system. It also describes modules, modularity, and networks in the brain.

scholarly journals On the methods for reactivation and replay analysis

2020 ◽  
Vol 375 (1799) ◽  
pp. 20190231 ◽  
Author(s):  
David Tingley ◽  
Adrien Peyrache
Keyword(s):  
Neural Activity ◽  
Temporal Structure ◽  
Activity Patterns ◽  
Large Body ◽  
Neural Data ◽  
History Of ◽  
Methodological Approaches ◽  
Neuronal Patterns ◽  
External Stimuli ◽  
The Brain

A major task in the history of neurophysiology has been to relate patterns of neural activity to ongoing external stimuli. More recently, this approach has branched out to relating current neural activity patterns to external stimuli or experiences that occurred in the past or future. Here, we aim to review the large body of methodological approaches used towards this goal, and to assess the assumptions each makes with reference to the statistics of neural data that are commonly observed. These methods primarily fall into two categories, those that quantify zero-lag relationships without examining temporal evolution, termed reactivation , and those that quantify the temporal structure of changing activity patterns, termed replay . However, no two studies use the exact same approach, which prevents an unbiased comparison between findings. These observations should instead be validated by multiple and, if possible, previously established tests. This will help the community to speak a common language and will eventually provide tools to study, more generally, the organization of neuronal patterns in the brain. This article is part of the Theo Murphy meeting issue ‘Memory reactivation: replaying events past, present and future’.

scholarly journals Efficient inverse graphics in biological face processing

2020 ◽  
Vol 6 (10) ◽  
pp. eaax5979 ◽  
Author(s):  
Ilker Yildirim ◽  
Mario Belledonne ◽  
Winrich Freiwald ◽  
Josh Tenenbaum
Keyword(s):  
Face Processing ◽  
Three Dimensional ◽  
Generative Models ◽  
Neural Data ◽  
Primate Brain ◽  
Scene Structure ◽  
Analysis By Synthesis ◽  
The Brain ◽  
Processing Circuit ◽  
Better Than

Vision not only detects and recognizes objects, but performs rich inferences about the underlying scene structure that causes the patterns of light we see. Inverting generative models, or “analysis-by-synthesis”, presents a possible solution, but its mechanistic implementations have typically been too slow for online perception, and their mapping to neural circuits remains unclear. Here we present a neurally plausible efficient inverse graphics model and test it in the domain of face recognition. The model is based on a deep neural network that learns to invert a three-dimensional face graphics program in a single fast feedforward pass. It explains human behavior qualitatively and quantitatively, including the classic “hollow face” illusion, and it maps directly onto a specialized face-processing circuit in the primate brain. The model fits both behavioral and neural data better than state-of-the-art computer vision models, and suggests an interpretable reverse-engineering account of how the brain transforms images into percepts.

Cortical Mechanisms for Emotional Fear and Chronic Pain

2009 ◽  
Vol 24 (S1) ◽  
pp. 1-1
Author(s):  
M. Zhuo
Keyword(s):  
Chronic Pain ◽  
Emotional Disorders ◽  
Cortical Neurons ◽  
Neural Mechanism ◽  
Anterior Cingulate ◽  
Cellular Mechanisms ◽  
New Genes ◽  
Trace Fear ◽  
The Brain ◽  
Synaptic Model

Investigation of molecular and cellular mechanisms of synaptic plasticity is the major focus of many neuroscientists. There are two major reasons for searching new genes and molecules contributing to central plasticity: first, it provides basic neural mechanism for learning and memory, a key function of the brain; second, it provides new targets for treating brain-related disease. Here, I propose that LTP in the anterior cingulate cortex (ACC) as a synaptic model for emotional fear and chronic pain in the brain. Integrative approaches including genetic, neurobiological and physiological methods are used to investigate the roles of cortical neurons and microglia in synaptic LTP, fear and chronic pain. We have identified several key calcium-stimulated signaling molecules including AC1, CaMKIV and FMRP for AMPA receptor mediated cingulate LTP, trace fear memory, and chronic pain. By contrast, microglia only contributes to changes in spinal dorsal horn, but not in the cortex. Our findings strongly suggest that ACC LTP may serve as a cellular model for studying central sensitization that related to fear and chronic pain, as well as pain-related cognitive emotional disorders.

scholarly journals Endogenous opioids in the nucleus accumbens promote approach to high-fat food in the absence of caloric need

eLife ◽  
2018 ◽  
Vol 7 ◽  
Author(s):  
Kevin Caref ◽  
Saleem M Nicola
Keyword(s):  
Nucleus Accumbens ◽  
Receptor Antagonist ◽  
Neural Control ◽  
Neural Mechanism ◽  
Endogenous Opioids ◽  
Neuronal Firing ◽  
Palatable Food ◽  
Sugar Consumption ◽  
High Fat ◽  
The Brain

When relatively sated, people (and rodents) are still easily tempted to consume calorie-dense foods, particularly those containing fat and sugar. Consumption of such foods while calorically replete likely contributes to obesity. The nucleus accumbens (NAc) opioid system has long been viewed as a critical substrate for this behavior, mainly via contributions to the neural control of consumption and palatability. Here, we test the hypothesis that endogenous NAc opioids also promote appetitive approach to calorie-dense food in states of relatively high satiety. We simultaneously recorded NAc neuronal firing and infused a µ-opioid receptor antagonist into the NAc while rats performed a cued approach task in which appetitive and consummatory phases were well separated. The results reveal elements of a neural mechanism by which NAc opioids promote approach to high-fat food despite the lack of caloric need, demonstrating a potential means by which the brain is biased towards overconsumption of palatable food.

On ventriloquism, audiovisual neurons, neonates, and the senses

2004 ◽  
Vol 27 (6) ◽  
pp. 889-890
Author(s):  
Monique Radeau ◽  
Cécile Colin
Keyword(s):  
Sensory Deprivation ◽  
Neural Mechanism ◽  
Scene Analysis ◽  
Perinatal Data ◽  
The Senses ◽  
The Brain

The analogy between the rules that subtend ventriloquism and bimodal neurons responding suggests a possible neural mechanism for audiovisual interactions in spatial scene analysis. Perinatal data, such as those on synesthesia, sensory deprivation, and sensory surstimulation, as well as neuroanatomical evidence for transitory intersensory connections in the brain support the view that audition and vision are bound together at birth.

Visual Remapping by Vector Subtraction: Analysis of Multiplicative Gain Field Models

2007 ◽  
Vol 19 (9) ◽  
pp. 2353-2386 ◽  
Author(s):  
Carlos R. Cassanello ◽  
Vincent P. Ferrera
Keyword(s):  
Target Location ◽  
Target Position ◽  
Saccadic Eye Movements ◽  
Neural Mechanism ◽  
Spatial Modulation ◽  
Eye Position ◽  
Retinal Position ◽  
Population Activity ◽  
Firing Rates ◽  
The Brain

Saccadic eye movements remain spatially accurate even when the target becomes invisible and the initial eye position is perturbed. The brain accomplishes this in part by remapping the remembered target location in retinal coordinates. The computation that underlies this visual remapping is approximated by vector subtraction: the original saccade vector is updated by subtracting the vector corresponding to the intervening eye movement. The neural mechanism by which vector subtraction is implemented is not fully understood. Here, we investigate vector subtraction within a framework in which eye position and retinal target position signals interact multiplicatively (gain field). When the eyes move, they induce a spatial modulation of the firing rates across a retinotopic map of neurons. The updated saccade metric can be read from the shift of the peak of the population activity across the map. This model uses a quasi-linear (half-rectified) dependence on the eye position and requires the slope of the eye position input to be negatively proportional to the preferred retinal position of each neuron. We derive analytically this constraint and study its range of validity. We discuss how this mechanism relates to experimental results reported in the frontal eye fields of macaque monkeys.

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