scholarly journals Task dependence of neural representations of global scene properties but not scene categories in the prefrontal cortex

2020 ◽  
Author(s):  
Yaelan Jung ◽  
Dirk B. Walther
Keyword(s):  
Prefrontal Cortex ◽  
Visual Cortex ◽  
Scene Perception ◽  
Sound Level ◽  
Task Context ◽  
Complex Scene ◽  
Neural Representations ◽  
Task Conditions ◽  
Scene Content ◽  
The Brain

AbstractNatural scenes deliver rich sensory information about the world. Decades of research has shown that the scene-selective network in the visual cortex represents various aspects of scenes. It is, however, unknown how such complex scene information is processed beyond the visual cortex, such as in the prefrontal cortex. It is also unknown how task context impacts the process of scene perception, modulating which scene content is represented in the brain. In this study, we investigate these questions using scene images from four natural scene categories, which also depict two types of global scene properties, temperature (warm or cold), and sound-level (noisy or quiet). A group of healthy human subjects from both sexes participated in the present study using fMRI. In the study, participants viewed scene images under two different task conditions; temperature judgment and sound-level judgment. We analyzed how different scene attributes (scene categories, temperature, and sound-level information) are represented across the brain under these task conditions. Our findings show that global scene properties are only represented in the brain, especially in the prefrontal cortex, when they are task-relevant. However, scene categories are represented in the brain, in both the parahippocampal place area and the prefrontal cortex, regardless of task context. These findings suggest that the prefrontal cortex selectively represents scene content according to task demands, but this task selectivity depends on the types of scene content; task modulates neural representations of global scene properties but not of scene categories.

scholarly journals The dimensionality of neural representations for control

2020 ◽  
Author(s):  
David Badre ◽  
Apoorva Bhandari ◽  
Haley Keglovits ◽  
Atsushi Kikumoto
Keyword(s):  
Prefrontal Cortex ◽  
Cognitive Control ◽  
Neural Computation ◽  
Neural Representation ◽  
Future Research ◽  
Trade Off ◽  
Neural Representations ◽  
Open Questions ◽  
The Brain ◽  
Review Current

Cognitive control allows us to think and behave flexibly based on our context and goals. At the heart of theories of cognitive control is a control representation that enables the same input to produce different outputs contingent on contextual factors. In this review, we focus on an important property of the control representation’s neural code: its representational dimensionality. Dimensionality of a neural representation balances a basic separability/generalizability trade-off in neural computation. We will discuss the implications of this trade-off for cognitive control. We will then briefly review current neuroscience findings regarding the dimensionality of control representations in the brain, particularly the prefrontal cortex. We conclude by highlighting open questions and crucial directions for future research.

scholarly journals Schema support for forming inferences in the human brain

2021 ◽  
Author(s):  
John Philippe Paulus ◽  
Carlo Vignali ◽  
Marc N Coutanche
Keyword(s):  
Prefrontal Cortex ◽  
Human Brain ◽  
Medial Prefrontal Cortex ◽  
Neural Representations ◽  
Memory Integration ◽  
New Information ◽  
Neural Integration ◽  
Two Factors ◽  
Memory Schema ◽  
The Brain

Associative inference, the process of drawing novel links between existing knowledge to rapidly integrate associated information, is supported by the hippocampus and neocortex. Within the neocortex, the medial prefrontal cortex (mPFC) has been implicated in the rapid cortical learning of new information that is congruent with an existing framework of knowledge, or schema. How the brain integrates associations to form inferences, specifically how inferences are represented, is not well understood. In this study, we investigate how the brain uses schemas to facilitate memory integration in an associative inference paradigm (A-B-C-D). We conducted two event-related fMRI experiments in which participants retrieved previously learned direct (AB, BC, CD) and inferred (AC, AD) associations between word pairs for items that are schema congruent or incongruent. Additionally, we investigated how two factors known to affect memory, a delay with sleep, and reward, modulate the neural integration of associations within, and between, schema. Schema congruency was found to benefit the integration of associates, but only when retrieval immediately follows learning. RSA revealed that neural patterns of inferred pairs (AC) in the PHc, mPFC, and posHPC were more similar to their constituents (AB and BC) when the items were schema congruent, suggesting that schema facilitates the assimilation of paired items into a single inferred unit containing all associated elements. Furthermore, a delay with sleep, but not reward, impacted the assimilation of inferred pairs. Our findings reveal that the neural representations of overlapping associations are integrated into novel representations through the support of memory schema.

scholarly journals The eyes reflect an internal cognitive state hidden in the population activity of cortical neurons

2020 ◽  
Author(s):  
Richard Johnston ◽  
Adam C. Snyder ◽  
Sanjeev B. Khanna ◽  
Deepa Issar ◽  
Matthew A. Smith
Keyword(s):  
Prefrontal Cortex ◽  
Visual Cortex ◽  
Eye Movements ◽  
Neural Activity ◽  
Detection Task ◽  
Change Detection Task ◽  
Population Activity ◽  
Slow Drift ◽  
Global Brain ◽  
The Brain

SummaryDecades of research have shown that global brain states such as arousal can be indexed by measuring the properties of the eyes. Neural signals from individual neurons, populations of neurons, and field potentials measured throughout much of the brain have been associated with the size of the pupil, small fixational eye movements, and vigor in saccadic eye movements. However, precisely because the eyes have been associated with modulation of neural activity across the brain, and many different kinds of measurements of the eyes have been made across studies, it has been difficult to clearly isolate how internal states affect the behavior of the eyes, and vice versa. Recent work in our laboratory identified a latent dimension of neural activity in macaque visual cortex on the timescale of minutes to tens of minutes. This ‘slow drift’ was associated with perceptual performance on an orientation-change detection task, as well as neural activity in visual and prefrontal cortex (PFC), suggesting it might reflect a shift in a global brain state. This motivated us to ask if the neural signature of this internal state is correlated with the action of the eyes in different behavioral tasks. We recorded from visual cortex (V4) while monkeys performed a change detection task, and the prefrontal cortex, while they performed a memory-guided saccade task. On both tasks, slow drift was associated with a pattern that is indicative of changes in arousal level over time. When pupil size was large, and the subjects were in a heighted state of arousal, microsaccade rate and reaction time decreased while saccade velocity increased. These results show that the action of the eyes is associated with a dominant mode of neural activity that is pervasive and task-independent, and can be accessed in the population activity of neurons across the cortex.

scholarly journals The geometry of abstraction in hippocampus and pre-frontal cortex

2018 ◽  
Author(s):  
Silvia Bernardi ◽  
Marcus K. Benna ◽  
Mattia Rigotti ◽  
Jérôme Munuera ◽  
Stefano Fusi ◽  
...  
Keyword(s):  
Frontal Cortex ◽  
Cognitive Flexibility ◽  
Anterior Cingulate ◽  
Stimulus Response ◽  
Hidden Variable ◽  
Neural Ensembles ◽  
Neural Representations ◽  
Cognitive Operations ◽  
Task Conditions ◽  
The Brain

The curse of dimensionality plagues models of reinforcement learning and decision-making. The process of abstraction solves this by constructing abstract variables describing features shared by different specific instances, reducing dimensionality and enabling generalization in novel situations. Here we characterized neural representations in monkeys performing a task where a hidden variable described the temporal statistics of stimulus-response-outcome mappings. Abstraction was defined operationally using the generalization performance of neural decoders across task conditions not used for training. This type of generalization requires a particular geometric format of neural representations. Neural ensembles in dorsolateral pre-frontal cortex, anterior cingulate cortex and hippocampus, and in simulated neural networks, simultaneously represented multiple hidden and explicit variables in a format reflecting abstraction. Task events engaging cognitive operations modulated this format. These findings elucidate how the brain and artificial systems represent abstract variables, variables critical for generalization that in turn confers cognitive flexibility.

Toward a Computational Understanding of Neuroaesthetics

2021 ◽  
pp. 127-131
Author(s):  
Kiyohito Iigaya ◽  
John P. O’Doherty
Keyword(s):  
Prefrontal Cortex ◽  
Visual Cortex ◽  
Medial Prefrontal Cortex ◽  
Visual Stimulus ◽  
Higher Order ◽  
Aesthetic Judgment ◽  
Statistical Properties ◽  
Association Cortex ◽  
Aesthetic Value ◽  
The Brain

Among the most challenging questions in the field of neuroaesthetics concerns how a piece of art comes to be liked in the first place. That is, how can the brain rapidly process a stimulus to form an aesthetic judgment even for stimuli never before encountered? In the article under discussion in this chapter, by leveraging computational methods in combination with behavioral and neuroimaging experiments the authors show that the brain does this by breaking a visual stimulus down into underlying features or attributes. These features are shared across objects, and weights over these features are integrated over to produce aesthetic judgments. This process is structured hierarchically in which elementary statistical properties of an image are combined to generate higher level features which in turn yield aesthetic value. Neuroimaging supports the implementation of this hierarchical integration along a gradient from early to higher order visual cortex extending into association cortex and ultimately converging in the anterior medial prefrontal cortex.

scholarly journals How usefulness shapes neural representations during goal-directed behavior

2021 ◽  
Vol 7 (15) ◽  
pp. eabd5363
Author(s):  
G. Castegnetti ◽  
M. Zurita ◽  
B. De Martino
Keyword(s):  
Prefrontal Cortex ◽  
Neural Representation ◽  
Coding Scheme ◽  
Neural Representations ◽  
Specific Goal ◽  
Sensory Cortices ◽  
Flexible Behavior ◽  
Goal Directed Behavior ◽  
The Brain

Value is often associated with reward, emphasizing its hedonic aspects. However, when circumstances change, value must also change (a compass outvalues gold, if you are lost). How are value representations in the brain reshaped under different behavioral goals? To answer this question, we devised a new task that decouples usefulness from its hedonic attributes, allowing us to study flexible goal-dependent mapping. Here, we show that, unlike sensory cortices, regions in the prefrontal cortex (PFC)—usually associated with value computation—remap their representation of perceptually identical items according to how useful the item has been to achieve a specific goal. Furthermore, we identify a coding scheme in the PFC that represents value regardless of the goal, thus supporting generalization across contexts. Our work questions the dominant view that equates value with reward, showing how a change in goals triggers a reorganization of the neural representation of value, enabling flexible behavior.

scholarly journals Dynamics of fMRI patterns reflect sub-second activation sequences and reveal replay in human visual cortex

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Lennart Wittkuhn ◽  
Nicolas W. Schuck
Keyword(s):  
Visual Cortex ◽  
Spatial Resolution ◽  
Activation Patterns ◽  
Non Invasive ◽  
Neural Representations ◽  
Probabilistic Classifier ◽  
Neural Computations ◽  
Time Courses ◽  
Human Participants ◽  
The Brain

AbstractNeural computations are often fast and anatomically localized. Yet, investigating such computations in humans is challenging because non-invasive methods have either high temporal or spatial resolution, but not both. Of particular relevance, fast neural replay is known to occur throughout the brain in a coordinated fashion about which little is known. We develop a multivariate analysis method for functional magnetic resonance imaging that makes it possible to study sequentially activated neural patterns separated by less than 100 ms with precise spatial resolution. Human participants viewed five images individually and sequentially with speeds up to 32 ms between items. Probabilistic pattern classifiers were trained on activation patterns in visual and ventrotemporal cortex during individual image trials. Applied to sequence trials, probabilistic classifier time courses allow the detection of neural representations and their order. Order detection remains possible at speeds up to 32 ms between items (plus 100 ms per item). The frequency spectrum of the sequentiality metric distinguishes between sub- versus supra-second sequences. Importantly, applied to resting-state data our method reveals fast replay of task-related stimuli in visual cortex. This indicates that non-hippocampal replay occurs even after tasks without memory requirements and shows that our method can be used to detect such spontaneously occurring replay.

scholarly journals Multiplexed and multivariate representations of sound identity during perceptual constancy

2017 ◽  
Author(s):  
Stephen M. Town ◽  
Katherine C. Wood ◽  
Jennifer K. Bizley
Keyword(s):  
Time Course ◽  
Sound Level ◽  
Neural Decoding ◽  
Object Identity ◽  
Perceptual Constancy ◽  
Neural Representations ◽  
Behavioral Variables ◽  
Feature Encoding ◽  
Sound Features ◽  
The Brain

SummaryPerceptual constancy requires neural representations that are selective for object identity, but also tolerant for identity-preserving transformations. How such representations arise in the brain and contribute to perception remains unclear. Here we studied tolerant representations of sound identity in the auditory system by recording multi-unit activity in tonotopic auditory cortex of ferrets discriminating the identity of vowels which co-varied across orthogonal stimulus dimensions (fundamental frequency, sound level, location and voicing). We found that neural decoding of vowel identity was most successful across the same orthogonal dimensions over which animals generalized their behavior. We also decoded orthogonal sound features and behavioral variables including choice and accuracy to show a behaviorally-relevant, multivariate and multiplexed representation of sound, with each variable represented over a distinct time-course. Finally, information content and timing of sound feature encoding was modulated by task-engagement and training, suggesting that tolerant representations during perceptual constancy are attentionally and experience-dependent.

SPECIFIC PROPERTIES OF TUBULIN IN THE PREFRONTAL CORTEX IN CONTROL, SCHIZOPHRENIA AND VASCULAR DEMENTIA

2020 ◽  
pp. 65-71
Author(s):  
Burbaeva G.Sh. ◽  
Androsova L.V. ◽  
Vorobyeva E.A. ◽  
Savushkina O.K.
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Prefrontal Cortex ◽  
Vascular Dementia ◽  
Binding Activity ◽  
Nephelometric Method ◽  
Rate Of Polymerization ◽  
Mental Diseases ◽  
And Control ◽  
The Brain

The aim of the study was to evaluate the rate of polymerization of tubulin into microtubules and determine the level of colchicine binding (colchicine-binding activity of tubulin) in the prefrontal cortex in schizophrenia, vascular dementia (VD) and control. Colchicine-binding activity of tubulin was determined by Sherlinе in tubulin-enriched extracts of proteins from the samples. Measurement of light scattering during the polymerization of the tubulin was carried out using the nephelometric method at a wavelength of 450-550 nm. There was a significant decrease in colchicine-binding activity and the rate of tubulin polymerization in the prefrontal cortex in both diseases, and in VD to a greater extent than in schizophrenia. The obtained results suggest that not only in Alzheimer's disease, but also in other mental diseases such as schizophrenia and VD, there is a decrease in the level of tubulin in the prefrontal cortex of the brain, although to a lesser extent than in Alzheimer's disease, and consequently the amount of microtubules.

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