scholarly journals A Probabilistic, Distributed, Recursive Mechanism for Decision-making in the Brain

2016 ◽  
Author(s):  
Javier A. Caballero ◽  
Mark D. Humphries ◽  
Kevin N. Gurney
Keyword(s):  
Decision Making ◽  
Basal Ganglia ◽  
Neural Activity ◽  
Large Scale ◽  
Single Equation ◽  
Brain Regions ◽  
Compulsive Gambling ◽  
Choice Behaviour ◽  
Usable Information ◽  
The Brain

AbstractDecision formation recruits many brain regions, but the procedure they jointly execute is unknown. Here we characterize its essential composition, using as a framework a novel recursive Bayesian algorithm that makes decisions based on spike-trains with the statistics of those in sensory cortex (MT). Using it to simulate the random-dot-motion task, we demonstrate it quantitatively replicates the choice behaviour of monkeys, whilst predicting losses of otherwise usable information from MT. Its architecture maps to the recurrent cortico-basal-ganglia-thalamo-cortical loops, whose components are all implicated in decision-making. We show that the dynamics of its mapped computations match those of neural activity in the sensorimotor cortex and striatum during decisions, and forecast those of basal ganglia output and thalamus. This also predicts which aspects of neural dynamics are and are not part of inference. Our single-equation algorithm is probabilistic, distributed, recursive, and parallel. Its success at capturing anatomy, behaviour, and electrophysiology suggests that the mechanism implemented by the brain has these same characteristics.Author SummaryDecision-making is central to cognition. Abnormally-formed decisions characterize disorders like over-eating, Parkinson’s and Huntington’s diseases, OCD, addiction, and compulsive gambling. Yet, a unified account of decisionmaking has, hitherto, remained elusive. Here we show the essential composition of the brain’s decision mechanism by matching experimental data from monkeys making decisions, to the knowable function of a novel statistical inference algorithm. Our algorithm maps onto the large-scale architecture of decision circuits in the primate brain, replicating the monkeys’ choice behaviour and the dynamics of the neural activity that accompany it. Validated in this way, our algorithm establishes a basic framework for understanding the mechanistic ingredients of decisionmaking in the brain, and thereby, a basic platform for understanding how pathologies arise from abnormal function.

scholarly journals A spatiotemporal complexity architecture of human brain activity

2021 ◽  
Author(s):  
Stephan Krohn ◽  
Nina von Schwanenflug ◽  
Leonhard Waschke ◽  
Amy Romanello ◽  
Martin Gell ◽  
...  
Keyword(s):  
Human Brain ◽  
Neural Activity ◽  
Large Scale ◽  
Temporal Dynamics ◽  
Brain Activity ◽  
Brain Regions ◽  
Brain Organization ◽  
Functional Connections ◽  
Signal Complexity ◽  
The Brain

The human brain operates in large-scale functional networks, collectively subsumed as the functional connectome1-13. Recent work has begun to unravel the organization of the connectome, including the temporal dynamics of brain states14-20, the trade-off between segregation and integration9,15,21-23, and a functional hierarchy from lower-order unimodal to higher-order transmodal processing systems24-27. However, it remains unknown how these network properties are embedded in the brain and if they emerge from a common neural foundation. Here we apply time-resolved estimation of brain signal complexity to uncover a unifying principle of brain organization, linking the connectome to neural variability6,28-31. Using functional magnetic resonance imaging (fMRI), we show that neural activity is marked by spontaneous "complexity drops" that reflect episodes of increased pattern regularity in the brain, and that functional connections among brain regions are an expression of their simultaneous engagement in such episodes. Moreover, these complexity drops ubiquitously propagate along cortical hierarchies, suggesting that the brain intrinsically reiterates its own functional architecture. Globally, neural activity clusters into temporal complexity states that dynamically shape the coupling strength and configuration of the connectome, implementing a continuous re-negotiation between cost-efficient segregation and communication-enhancing integration9,15,21,23. Furthermore, complexity states resolve the recently discovered association between anatomical and functional network hierarchies comprehensively25-27,32. Finally, brain signal complexity is highly sensitive to age and reflects inter-individual differences in cognition and motor function. In sum, we identify a spatiotemporal complexity architecture of neural activity — a functional "complexome" that gives rise to the network organization of the human brain.

The Emerging Standard Neurobiological Model of Decision Making

2018 ◽  
Author(s):  
Shih-Wei Wu ◽  
Paul W. Glimcher
Keyword(s):  
Decision Making ◽  
Economic Theory ◽  
Neural Activity ◽  
First Century ◽  
The Other ◽  
Neoclassical Economic ◽  
Internal Representations ◽  
Neurobiological Model ◽  
Neoclassical Economic Theory ◽  
The Brain

The standard neurobiological model of decision making has evolved, since the turn of the twenty-first century, from a confluence of economic, psychological, and neurosci- entific studies of how humans make choices. Two fundamental insights have guided the development of this model during this period, one drawn from economics and the other from neuroscience. The first derives from neoclassical economic theory, which unambiguously demonstrated that logically consistent choosers behave “as if” they had some internal, continuous, and monotonic representation of the values of any choice objects under consideration. The second insight derives from neurobiological studies suggesting that the brain can both represent, in patterns of local neural activity, and compare, by a process of interneuronal competition, internal representations of value associated with different choices.

Symptoms, Related Brain Regions, and Diagnosis

2013 ◽  
Author(s):  
J. Eric Ahlskog
Keyword(s):  
Spinal Cord ◽  
Nervous System ◽  
Basal Ganglia ◽  
Brain Stem ◽  
Muscle Activation ◽  
Sensory Information ◽  
Brain Regions ◽  
Electrical Signal ◽  
Brain And Spinal Cord ◽  
The Brain

As a prelude to the treatment chapters that follow, we need to define and describe the types of problems and symptoms encountered in DLB and PDD. The clinical picture can be quite varied: problems encountered by one person may be quite different from those encountered by another person, and symptoms that are problematic in one individual may be minimal in another. In these disorders, the Lewy neurodegenerative process potentially affects certain nervous system regions but spares others. Affected areas include thinking and memory circuits, as well as movement (motor) function and the autonomic nervous system, which regulates primary functions such as bladder, bowel, and blood pressure control. Many other brain regions, by contrast, are spared or minimally involved, such as vision and sensation. The brain and spinal cord constitute the central nervous system. The interface between the brain and spinal cord is by way of the brain stem, as shown in Figure 4.1. Thought, memory, and reasoning are primarily organized in the thick layers of cortex overlying lower brain levels. Volitional movements, such as writing, throwing, or kicking, also emanate from the cortex and integrate with circuits just below, including those in the basal ganglia, shown in Figure 4.2. The basal ganglia includes the striatum, globus pallidus, subthalamic nucleus, and substantia nigra, as illustrated in Figure 4.2. Movement information is integrated and modulated in these basal ganglia nuclei and then transmitted down the brain stem to the spinal cord. At spinal cord levels the correct sequence of muscle activation that has been programmed is accomplished. Activated nerves from appropriate regions of the spinal cord relay the signals to the proper muscles. Sensory information from the periphery (limbs) travels in the opposite direction. How are these signals transmitted? Brain cells called neurons have long, wire-like extensions that interface with other neurons, effectively making up circuits that are slightly similar to computer circuits; this is illustrated in Figure 4.3. At the end of these wire-like extensions are tiny enlargements (terminals) that contain specific biological chemicals called neurotransmitters. Neurotransmitters are released when the electrical signal travels down that neuron to the end of that wire-like process.

scholarly journals Aberrant White Matter Networks Mediate Cognitive Impairment in Patients with Silent Lacunar Infarcts in Basal Ganglia Territory

2015 ◽  
Vol 35 (9) ◽  
pp. 1426-1434 ◽  
Author(s):  
Jinfu Tang ◽  
Suyu Zhong ◽  
Yaojing Chen ◽  
Kewei Chen ◽  
Junying Zhang ◽  
...  
Keyword(s):  
White Matter ◽  
Basal Ganglia ◽  
Cognitive Deficits ◽  
Large Scale ◽  
Diffusion Tensor ◽  
Brain Regions ◽  
Lacunar Infarcts ◽  
Healthy Elderly ◽  
Brain White Matter ◽  
Diffusion Tensor Imaging Tractography

Silent lacunar infarcts, which are present in over 20% of healthy elderly individuals, are associated with subtle deficits in cognitive functions. However, it remains largely unclear how these silent brain infarcts lead to cognitive deficits and even dementia. Here, we used diffusion tensor imaging tractography and graph theory to examine the topological organization of white matter networks in 27 patients with silent lacunar infarcts in the basal ganglia territory and 30 healthy controls. A whole-brain white matter network was constructed for each subject, where the graph nodes represented brain regions and the edges represented interregional white matter tracts. Compared with the controls, the patients exhibited a significant reduction in local efficiency and global efficiency. In addition, a total of eighteen brain regions showed significantly reduced nodal efficiency in patients. Intriguingly, nodal efficiency–behavior associations were significantly different between the two groups. The present findings provide new aspects into our understanding of silent infarcts that even small lesions in subcortical brain regions may affect large-scale cortical white matter network, as such may be the link between subcortical silent infarcts and the associated cognitive impairments. Our findings highlight the need for network-level neuroimaging assessment and more medical care for individuals with silent subcortical infarcts.

scholarly journals Message-Elicited Brain Response Moderates the Relationship Between Opportunities for Exposure to Anti-Smoking Messages and Message Recall

2019 ◽  
Vol 69 (6) ◽  
pp. 589-611
Author(s):  
Elissa C Kranzler ◽  
Ralf Schmälzle ◽  
Rui Pei ◽  
Robert C Hornik ◽  
Emily B Falk
Keyword(s):  
Large Scale ◽  
Communication Theory ◽  
Brain Regions ◽  
Message Processing ◽  
Memory Encoding ◽  
Brain Response ◽  
Real Cost ◽  
Social Processing ◽  
The Relationship ◽  
The Brain

Abstract Campaign success is contingent on adequate exposure; however, exposure opportunities (e.g., ad reach/frequency) are imperfect predictors of message recall. We hypothesized that the exposure-recall relationship would be contingent on message processing. We tested moderation hypotheses using 3 data sets pertinent to “The Real Cost” anti-smoking campaign: past 30-day ad recall from a rolling national survey of adolescents aged 13–17 (n = 5,110); ad-specific target rating points (TRPs), measuring ad reach and frequency; and ad-elicited response in brain regions implicated in social processing and memory encoding, from a separate adolescent sample aged 14–17 (n = 40). Average ad-level brain activation in these regions moderates the relationship between national TRPs and large-scale recall (p < .001), such that the positive exposure-recall relationship is more strongly observed for ads that elicit high levels of social processing and memory encoding in the brain. Findings advance communication theory by demonstrating conditional exposure effects, contingent on social and memory processes in the brain.

scholarly journals Regulation and Modulation of pH in the Brain

2003 ◽  
Vol 83 (4) ◽  
pp. 1183-1221 ◽  
Author(s):  
MITCHELL CHESLER
Keyword(s):  
Intracellular Ph ◽  
Neural Activity ◽  
Extracellular Fluid ◽  
Cell Types ◽  
Brain Regions ◽  
Metabolic Products ◽  
Homeostatic Function ◽  
Acid Extrusion ◽  
Activity Dependent ◽  
The Brain

Chesler, Mitchell. Regulation and Modulation of pH in the Brain. Physiol Rev 83: 1183-1221, 2003; 10.1152/physrev.00010.2003.—The regulation of pH is a vital homeostatic function shared by all tissues. Mechanisms that govern H+ in the intracellular and extracellular fluid are especially important in the brain, because electrical activity can elicit rapid pH changes in both compartments. These acid-base transients may in turn influence neural activity by affecting a variety of ion channels. The mechanisms responsible for the regulation of intracellular pH in brain are similar to those of other tissues and are comprised principally of forms of Na+/H+ exchange, Na+-driven Cl-/HCO3- exchange, Na+-HCO3- cotransport, and passive Cl-/HCO3- exchange. Differences in the expression or efficacy of these mechanisms have been noted among the functionally and morphologically diverse neurons and glial cells that have been studied. Molecular identification of transporter isoforms has revealed heterogeneity among brain regions and cell types. Neural activity gives rise to an assortment of extracellular and intracellular pH shifts that originate from a variety of mechanisms. Intracellular pH shifts in neurons and glia have been linked to Ca2+ transport, activation of acid extrusion systems, and the accumulation of metabolic products. Extracellular pH shifts can occur within milliseconds of neural activity, arise from an assortment of mechanisms, and are governed by the activity of extracellular carbonic anhydrase. The functional significance of these compartmental, activity-dependent pH shifts is discussed.

scholarly journals Effects of dopamine agonist treatment on resting-state network connectivity in Parkinson’s disease

2020 ◽  
Author(s):  
David M. Cole ◽  
Bahram Mohammadi ◽  
Maria Milenkova ◽  
Katja Kollewe ◽  
Christoph Schrader ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Decision Making ◽  
Parkinson's Disease ◽  
Basal Ganglia ◽  
Dopamine Agonist ◽  
Resting State ◽  
Large Scale ◽  
Network Connectivity ◽  
Resting State Network ◽  
Large Scale Networks

ABSTRACTDopamine agonist (DA) medications commonly used to treat, or ‘normalise’, motor symptoms of Parkinson’s disease (PD) may lead to cognitive-neuropsychiatric side effects, such as increased impulsivity in decision-making. Subject-dependent variation in the neural response to dopamine modulation within cortico-basal ganglia circuitry is thought to play a key role in these latter, non-motor DA effects. This neuroimaging study combined resting-state functional magnetic resonance imaging (fMRI) with DA modification in patients with idiopathic PD, investigating whether brain ‘resting-state network’ (RSN) functional connectivity metrics identify disease-relevant effects of dopamine on systems-level neural processing. By comparing patients both ‘On’ and ‘Off’ their DA medications with age-matched, un-medicated healthy control subjects (HCs), we identified multiple non-normalising DA effects on frontal and basal ganglia RSN cortico-subcortical connectivity patterns in PD. Only a single isolated, potentially ‘normalising’, DA effect on RSN connectivity in sensori-motor systems was observed, within cerebro-cerebellar neurocircuitry. Impulsivity in reward-based decision-making was positively correlated with ventral striatal connectivity within basal ganglia circuitry in HCs, but not in PD patients. Overall, we provide brain systems-level evidence for anomalous DA effects in PD on large-scale networks supporting cognition and motivated behaviour. Moreover, findings suggest that dysfunctional striatal and basal ganglia signalling patterns in PD are compensated for by increased recruitment of other cortico-subcortical and cerebro-cerebellar systems.

scholarly journals Lisdexamfetamine Alters BOLD-fMRI Activations Induced by Odor Cues in Impulsive Children

2020 ◽  
Vol 19 (4) ◽  
pp. 290-305
Author(s):  
Silvia S. Hidalgo Tobón ◽  
Pilar Dies Suárez ◽  
Eduardo Barragán Pérez ◽  
Javier M. Hernández López ◽  
Julio García ◽  
...  
Keyword(s):  
Decision Making ◽  
Activity Patterns ◽  
Cingulate Cortex ◽  
Brain Regions ◽  
Posterior Cingulate Cortex ◽  
Regulation Mechanism ◽  
Behavioral Regulation ◽  
Bold Fmri ◽  
Inhibitory Pathways ◽  
The Brain

Introduction: Lisdexamfetamine (LDX) is a drug used to treat ADHD/impulsive patients. Impulsivity is known to affect inhibitory, emotional and cognitive function. On the other hand, smell and odor processing are known to be affected by neurological disorders, as they are modulators of addictive and impulsive behaviors specifically. We hypothesize that, after LDX ingestion, inhibitory pathways of the brain would change, and complementary behavioral regulation mechanisms would appear to regulate decision-making and impulsivity. Methods: 20 children were studied in an aleatory crossover study. Imaging of BOLD-fMRI activity, elicited by olfactory stimulation in impulsive children, was performed after either LDX or placebo ingestion. Results: Findings showed that all subjects who underwent odor stimulation presented activations of similar intensities in the olfactory centers of the brain. This contrasted with inhibitory regions of the brain such as the cingulate cortex and frontal lobe regions, which demonstrated changed activity patterns and intensities. While some differences between the placebo and medicated states were found in motor areas, precuneus, cuneus, calcarine, supramarginal, cerebellum and posterior cingulate cortex, the main changes were found in frontal, temporal and parietal cortices. When comparing olfactory cues separately, pleasant food smells like chocolate seemed not to present large differences between the medicated and placebo scenarios, when compared to non-food-related smells. Conclusions: It was demonstrated that LDX, first, altered the inhibitory pathways of the brain, secondly it increased activity in several brain regions which were not activated by smell in drug-naïve patients, and thirdly, it facilitated a complementary behavioral regulation mechanism, run by the cerebellum, which regulated decision-making and impulsivity in motor and frontal structures.

scholarly journals The Neural Basis of Motivational Influences on Cognitive Control

2017 ◽  
Author(s):  
Cameron Parro ◽  
Matthew L Dixon ◽  
Kalina Christoff
Keyword(s):  
Cognitive Control ◽  
Large Scale ◽  
Functional Neuroimaging ◽  
Meta Analysis ◽  
Premotor Cortex ◽  
Likelihood Estimation ◽  
Brain Regions ◽  
Control Mechanisms ◽  
Neural Basis ◽  
The Brain

AbstractCognitive control mechanisms support the deliberate regulation of thought and behavior based on current goals. Recent work suggests that motivational incentives improve cognitive control, and has begun to elucidate the brain regions that may support this effect. Here, we conducted a quantitative meta-analysis of neuroimaging studies of motivated cognitive control using activation likelihood estimation (ALE) and Neurosynth in order to delineate the brain regions that are consistently activated across studies. The analysis included functional neuroimaging studies that investigated changes in brain activation during cognitive control tasks when reward incentives were present versus absent. The ALE analysis revealed consistent recruitment in regions associated with the frontoparietal control network including the inferior frontal sulcus (IFS) and intraparietal sulcus (IPS), as well as consistent recruitment in regions associated with the salience network including the anterior insula and anterior mid-cingulate cortex (aMCC). A large-scale exploratory meta-analysis using Neurosynth replicated the ALE results, and also identified the caudate nucleus, nucleus accumbens, medial thalamus, inferior frontal junction/premotor cortex (IFJ/PMC), and hippocampus. Finally, we conducted separate ALE analyses to compare recruitment during cue and target periods, which tap into proactive engagement of rule-outcome associations, and the mobilization of appropriate viscero-motor states to execute a response, respectively. We found that largely distinct sets of brain regions are recruited during cue and target periods. Altogether, these findings suggest that flexible interactions between frontoparietal, salience, and dopaminergic midbrain-striatal networks may allow control demands to be precisely tailored based on expected value.

scholarly journals Large- and multi-scale networks in the rodent brain during novelty exploration

2020 ◽  
Author(s):  
Michael X Cohen ◽  
Bernhard Englitz ◽  
Arthur S C França
Keyword(s):  
Prefrontal Cortex ◽  
Parietal Cortex ◽  
Local Field ◽  
Neural Activity ◽  
Large Scale ◽  
Field Potential ◽  
Brain Regions ◽  
Data Availability ◽  
Data Matrix ◽  
Temporal Scales

AbstractNeural activity is coordinated across multiple spatial and temporal scales, and these patterns of coordination are implicated in both healthy and impaired cognitive operations. However, empirical cross-scale investigations are relatively infrequent, due to limited data availability and to the difficulty of analyzing rich multivariate datasets. Here we applied frequency-resolved multivariate source-separation analyses to characterize a large-scale dataset comprising spiking and local field potential activity recorded simultaneously in three brain regions (prefrontal cortex, parietal cortex, hippocampus) in freely-moving mice. We identified a constellation of multidimensional, inter-regional networks across a range of frequencies (2-200 Hz). These networks were reproducible within animals across different recording sessions, but varied across different animals, suggesting individual variability in network architecture. The theta band (~4-10 Hz) networks had several prominent features, including roughly equal contribution from all regions and strong inter-network synchronization. Overall, these findings demonstrate a multidimensional landscape of large-scale functional activations of cortical networks operating across multiple spatial, spectral, and temporal scales during open-field exploration.Significance statementNeural activity is synchronized over space, time, and frequency. To characterize the dynamics of large-scale networks spanning multiple brain regions, we recorded data from the prefrontal cortex, parietal cortex, and hippocampus in awake behaving mice, and pooled data from spiking activity and local field potentials into one data matrix. Frequency-specific multivariate decomposition methods revealed a cornucopia of neural networks defined by coherent spatiotemporal patterns over time. These findings reveal a rich, dynamic, and multivariate landscape of large-scale neural activity patterns during foraging behavior.

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