scholarly journals The human prefrontal cortex mediates integration of potential causes behind observed outcomes

2011 ◽  
Vol 106 (3) ◽  
pp. 1558-1569 ◽  
Author(s):  
Klaus Wunderlich ◽  
Ulrik R. Beierholm ◽  
Peter Bossaerts ◽  
John P. O'Doherty
Keyword(s):  
Prefrontal Cortex ◽  
Human Brain ◽  
Computational Model ◽  
Functional Mri ◽  
Higher Order ◽  
The Other ◽  
Decision Problems ◽  
Human Participants ◽  
The Brain ◽  
Model Based Analysis

Prefrontal cortex has long been implicated in tasks involving higher order inference in which decisions must be rendered, not only about which stimulus is currently rewarded, but also which stimulus dimensions are currently relevant. However, the precise computational mechanisms used to solve such tasks have remained unclear. We scanned human participants with functional MRI, while they performed a hierarchical intradimensional/extradimensional shift task to investigate what strategy subjects use while solving higher order decision problems. By using a computational model-based analysis, we found behavioral and neural evidence that humans solve such problems not by occasionally shifting focus from one to the other dimension, but by considering multiple explanations simultaneously. Activity in human prefrontal cortex was better accounted for by a model that integrates over all available evidences than by a model in which attention is selectively gated. Importantly, our model provides an explanation for how the brain determines integration weights, according to which it could distribute its attention. Our results demonstrate that, at the point of choice, the human brain and the prefrontal cortex in particular are capable of a weighted integration of information across multiple evidences.

scholarly journals Evolutionary modifications in human brain connectivity associated with schizophrenia

Brain ◽  
2019 ◽  
Vol 142 (12) ◽  
pp. 3991-4002 ◽  
Author(s):  
Martijn P van den Heuvel ◽  
Lianne H Scholtens ◽  
Siemon C de Lange ◽  
Rory Pijnenburg ◽  
Wiepke Cahn ◽  
...  
Keyword(s):  
Human Brain ◽  
Brain Connectivity ◽  
Brain Evolution ◽  
Higher Order ◽  
Brain Functions ◽  
Human Brain Evolution ◽  
The Brain

See Vértes and Seidlitz (doi:10.1093/brain/awz353) for a scientific commentary on this article. Is schizophrenia a by-product of human brain evolution? By comparing the human and chimpanzee connectomes, van den Heuvel et al. demonstrate that connections unique to the human brain show greater involvement in schizophrenia pathology. Modifications in service of higher-order brain functions may have rendered the brain more vulnerable to dysfunction.

scholarly journals Subjective value and decision entropy are jointly encoded by aligned gradients across the human brain

2020 ◽  
Author(s):  
Sebastian Bobadilla-Suarez ◽  
Olivia Guest ◽  
Bradley C. Love
Keyword(s):  
Prefrontal Cortex ◽  
Human Brain ◽  
Ventromedial Prefrontal Cortex ◽  
Neural Representation ◽  
Retrospective Evaluation ◽  
Systematic Fashion ◽  
Subjective Value ◽  
Fmri Analysis ◽  
The Relationship ◽  
The Brain

AbstractRecent work has considered the relationship between value and confidence in both behavior and neural representation. Here we evaluated whether the brain organizes value and confidence signals in a systematic fashion that reflects the overall desirability of options. If so, regions that respond to either increases or decreases in both value and confidence should be widespread. We strongly confirmed these predictions through a model-based fMRI analysis of a mixed gambles task that assessed subjective value (SV) and inverse decision entropy (iDE), which is related to confidence. Purported value areas more strongly signalled iDE than SV, underscoring how intertwined value and confidence are. A gradient tied to the desirability of actions transitioned from positive SV and iDE in ventromedial prefrontal cortex to negative SV and iDE in dorsal medial prefrontal cortex. This alignment of SV and iDE signals could support retrospective evaluation to guide learning and subsequent decisions.

Is the Human Brain Unique?

2018 ◽  
Author(s):  
Jack M. Gorman
Keyword(s):  
Prefrontal Cortex ◽  
Theory Of Mind ◽  
Human Brain ◽  
Brain Function ◽  
Human Mind ◽  
Brain Diseases ◽  
Expression Of Genes ◽  
The Future ◽  
Mind And Brain ◽  
The Brain

Some scientists now argue that humans are really not superior to other species, including our nearest genetic neighbors, chimpanzees and bonobos. Indeed, those animals seem capable of many things previously thought to be uniquely human, including a sense of the future, empathy, depression, and theory of mind. However, it is clear that humans alone produce speech, dominate the globe, and have several brain diseases like schizophrenia. There are three possible sources within the brain for these differences in brain function: in the structure of the brain, in genes coding for proteins in the brain, and in the level of expression of genes in the brain. There is evidence that all three are the case, giving us a place to look for the intersection of the human mind and brain: the expression of genes within neurons of the prefrontal cortex.

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 Probing Neural Networks for Dynamic Switches of Communication Pathways

2019 ◽  
Author(s):  
Holger Finger ◽  
Richard Gast ◽  
Christian Gerloff ◽  
Andreas K. Engel ◽  
Peter König
Keyword(s):  
Neural Networks ◽  
Human Brain ◽  
Computational Model ◽  
Broad Spectrum ◽  
Dynamic Properties ◽  
Dynamic Network ◽  
Thought Processes ◽  
Response Properties ◽  
Dynamic Switching ◽  
The Brain

AbstractDynamic communication and routing play important roles in the human brain to facilitate 2exibility in task solving and thought processes. Here, we present a network perturbation methodology that allows to investigate dynamic switching between different network pathways based on phase offsets between two external oscillatory drivers. We apply this method in a computational model of the human connectome with delay-coupled neural masses. To analyze dynamic switching of pathways, we define four new metrics that measure dynamic network response properties for pairs of stimulated nodes. Evaluating these metrics for all network pathways, we found a broad spectrum of pathways with distinct dynamic properties and switching behaviors. Specifically, we found that 60.1% of node pairs can switch their communication from one pathway to another depending on their phase offsets. This indicates that phase offsets and coupling delays play an important computational role for the dynamic switching between communication pathways in the brain.

scholarly journals Why intracranial electrical stimulation of the human brain suggests an essential role for prefrontal cortex in conscious processing: a commentary on Raccah et al.

2021 ◽  
Author(s):  
Lionel Naccache ◽  
Jean-Pierre Changeux ◽  
Theofanis I. Panagiotaropoulos ◽  
Stanislas Dehaene
Keyword(s):  
Electrical Stimulation ◽  
Prefrontal Cortex ◽  
Human Brain ◽  
Essential Role ◽  
Conscious Experience ◽  
Higher Order ◽  
Conscious Processing ◽  
Experimental Challenge ◽  
Stimulation Of

We read with interest the synthesis by Raccah and colleagues on the perturbations of consciousexperience elicited by intracranial electrical stimulation (iES) of the prefrontal cortex (PFC) in awakeneurosurgical patients. The main outcome of the review is the report that iES of the PFC shows fewercausal changes of conscious experience than iES of posterior sensory areas. The authors interpretedthis finding as a challenge to neuroscientific theories of conscious processing that attribute a centralrole to PFC, such a Global Neuronal Workspace Theory (GNWT) and Higher Order Thought theory(HOT). We agree that this anterior vs posterior issue may offer an experimental challenge that thepresent theories of conscious processing have to take up, and we provide here a list of seven majorpoints that begin to specify a GNWT account for the observations compiled by Raccah and colleaguestogether with more recent, unmentioned, data.

Gesture–speech unity

2014 ◽  
Vol 5 (2) ◽  
pp. 137-184 ◽  
Author(s):  
David McNeill
Keyword(s):  
Prefrontal Cortex ◽  
Natural Selection ◽  
Language Evolution ◽  
The Other ◽  
Shared Intentionality ◽  
Origin Of Language ◽  
Child Speech ◽  
The Brain ◽  
Shed Light ◽  
Selection Of

This paper outlines an argument for how development in child speech and gesture could shed light on language evolution: child acquisition can be thought of as two types of acquisition, one of which goes extinct (gesture-first, Acquisition 1) and is replaced by another (gesture–speech unity, Acquisition 2). For ontogenesis, this implies that children acquire two languages, one of which is extinct, and which again goes extinct in ontogenesis (it continues as “gestures of silence” rather than as gestures of speech). There is no way to get from Acquisition 1 to Acquisition 2. They are on different tracks. Even when they converge in the same sentence, as they sometimes do, they alternate and do not combine. I propose that the 3~4 year timing of Acquisition 2 relates to the natural selection of a kind of gestural self–response I call “Mead’s Loop”, which took place in a certain psychological milieu at the origin of language. This milieu emerges now in ontogenesis at 3~4 years and with it Mead’s Loop. It is self-aware agency, on which a self-response depends. Other developments, such as theory of mind and shared intentionality, likewise depend on it and also emerge around the same time. The prefrontal cortex, anchoring a ring of language centers in the brain, matures at that point as well, another factor influencing the late timing. On the other hand, a third acquisition, speech evoking adult attachment, begins at (or even before) birth, as shown by a number of studies, and provides continuity through the two acquisitions and extinction.

scholarly journals Active control of arousal by a locus coeruleus GABAergic circuit

2018 ◽  
Author(s):  
Vincent Breton-Provencher ◽  
Mriganka Sur
Keyword(s):  
Prefrontal Cortex ◽  
Locus Coeruleus ◽  
Cognitive Performance ◽  
Active Control ◽  
Local Population ◽  
Gabaergic Neurons ◽  
The Other ◽  
Lc Circuit ◽  
Virus Tracing ◽  
The Brain

AbstractArousal and novelty responses linked to locus coeruleus noradrenergic (LC-NA) activity affect cognitive performance. However, the mechanisms that control modes of LC-NA activity remain unknown. Here, we reveal a local population of GABAergic neurons (LC-GABA) capable of modulating LC-NA activity and arousal. Monosynaptic retrograde virus tracing shows that inputs to LC-GABA and LC-NA neurons arise from similar regions, though a few regions provide differential inputs to one subtype over the other. Recordings in the LC demonstrate two modes of LC-GABA responses whereby spiking is either correlated or broadly anti-correlated with LC-NA responses, reflecting anatomically similar and functionally coincident inputs, or differential and non-coincident inputs, to LC-NA and LC-GABA neurons. Coincident inputs control the gain of phasic LC-NA mediated novelty responses, while non-coincident inputs, such as from the prefrontal cortex to LC, alter overall levels of LC-NA responses without affecting response gain. These findings demonstrate distinct modes by which an inhibitory LC circuit regulates the gain and tone of arousal in the brain.

scholarly journals Processing of a spoken narrative in the human brain is shaped by family cultural background

2020 ◽  
Author(s):  
M. Hakonen ◽  
A. Ikäheimonen ◽  
A. Hultèn ◽  
J. Kauttonen ◽  
M. Koskinen ◽  
...  
Keyword(s):  
Social Identity ◽  
Human Brain ◽  
Native Speakers ◽  
Family Background ◽  
Cultural Background ◽  
The Other ◽  
Mutual Understanding ◽  
Brain Areas ◽  
Narrative Processing ◽  
The Brain

ABSTRACTUsing neuroimaging, we studied influence of family cultural background on processing of an audiobook in human brain. The audiobook depicted life of two young Finnish men, one with the Finnish and the other with the Russian family background. Shared family cultural background enhanced similarity of narrative processing in the brain at prelexical, word, sentence, and narrative levels. Similarity was also enhanced in brain areas supporting imagery. The cultural background was further reflected as semantic differences in word lists by which the subjects described what had been on their minds when they heard the audiobook during neuroimaging. Strength of social identity shaped word, sentence, and narrative level processing in the brain. These effects might enhance mutual understanding between persons who share family cultural background and social identity and, conversely, deteriorate between-group mutual understanding in modern multicultural societies wherein native speakers of a language may assume highly similar understanding.

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.

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