scholarly journals Economic Choices under Simultaneous or Sequential Offers Rely on the Same Neural Circuit

2021 ◽  
Author(s):  
Weikang Shi ◽  
Sebastien Ballesta ◽  
Camillo Padoa-Schioppa
Keyword(s):  
Neural Circuit ◽  
Time Windows ◽  
Building Blocks ◽  
Binary Choice ◽  
Neuronal Responses ◽  
Cell Groups ◽  
Decision Circuit ◽  
Economic Choices ◽  
Specific Sequences ◽  
Lines Of Evidence

A series of studies in which monkeys chose between two juices offered in variable amounts identified in the orbitofrontal cortex (OFC) different groups of neurons encoding the value of individual options (offer value), the binary choice outcome (chosen juice) and the chosen value. These variables capture both the input and the output of the choice process, suggesting that the cell groups identified in OFC constitute the building blocks of a decision circuit. Several lines of evidence support this hypothesis. However, in previous experiments offers were presented simultaneously, raising the question of whether current notions generalize to when goods are presented or are examined in sequence. Recently, Ballesta and Padoa-Schioppa (2019) examined OFC activity under sequential offers. An analysis of neuronal responses across time windows revealed that a small number of cell groups encoded specific sequences of variables. These sequences appeared analogous to the variables identified under simultaneous offers, but the correspondence remained tentative. Thus in the present study we examined the relation between cell groups found under sequential versus simultaneous offers. We recorded from the OFC while monkeys chose between different juices. Trials with simultaneous and sequential offers were randomly interleaved in each session. We classified cells in each choice modality and we examined the relation between the two classifications. We found a strong correspondence; in other words, the cell groups measured under simultaneous offers and under sequential offers were one and the same. This result indicates that economic choices under simultaneous or sequential offers rely on the same neural circuit.

scholarly journals Mechanisms of Economic Decisions under Sequential Offers

2019 ◽  
Author(s):  
Sébastien Ballesta ◽  
Camillo Padoa-Schioppa
Keyword(s):  
Orbitofrontal Cortex ◽  
Neural Circuit ◽  
Time Windows ◽  
Neuronal Responses ◽  
Mutual Inhibition ◽  
Economic Decisions ◽  
Neuronal Mechanisms ◽  
Binary Choices ◽  
Decision Mechanisms

AbstractBinary choices between goods are thought to take place in orbitofrontal cortex (OFC). However, current notions emerged mostly from studies where two offers were presented simultaneously, and other work suggested that choices under sequential offers rely on fundamentally different mechanisms. Here we recorded from the OFC of macaques choosing between two juices offered sequentially. Analyzing neuronal responses across time windows, we discovered different groups of neurons that closely resemble those identified under simultaneous offers, suggesting that decisions in the two modalities are formed in the same neural circuit. Building on this result, we examined four hypotheses on the decision mechanisms. OFC neurons encoded goods and values in a juice-based representation (labeled lines). Contrary to previous assessments, decisions did not involve mutual inhibition between pools of offer value cells. Instead, decisions involved mechanisms of circuit inhibition, whereby each offer value indirectly inhibits neurons encoding the opposite choice outcome. These results reconcile disparate findings and provide a unitary account for the neuronal mechanisms underlying economic decisions.

scholarly journals Sequence memory in recurrent neuronal network can develop without structured input

2020 ◽  
Author(s):  
Matthias Loidolt ◽  
Lucas Rudelt ◽  
Viola Priesemann
Keyword(s):  
Sensory Input ◽  
Building Blocks ◽  
Spike Timing ◽  
Synaptic Competition ◽  
Structured Input ◽  
Recurrent Neuronal Network ◽  
Sequence Memory ◽  
The Brain ◽  
Specific Sequences ◽  
Intrinsic Feature

AbstractHow does spontaneous activity during development prepare cortico-cortical connections for sensory input? We here analyse the development of sequence memory, an intrinsic feature of recurrent networks that supports temporal perception. We use a recurrent neural network model with homeostatic and spike-timing-dependent plasticity (STDP). This model has been shown to learn specific sequences from structured input. We show that development even under unstructured input increases unspecific sequence memory. Moreover, networks “pre-shaped” by such unstructured input subsequently learn specific sequences faster. The key structural substrate is the emergence of strong and directed synapses due to STDP and synaptic competition. These construct self-amplifying preferential paths of activity, which can quickly encode new input sequences. Our results suggest that memory traces are not printed on a tabula rasa, but instead harness building blocks already present in the brain.

scholarly journals Perceptual detection depends on spike count integration

2019 ◽  
Author(s):  
Jackson J. Cone ◽  
Morgan L. Bade ◽  
Nicolas Y. Masse ◽  
Elizabeth A. Page ◽  
David J. Freedman ◽  
...  
Keyword(s):  
Neural Networks ◽  
Cerebral Cortex ◽  
Visual Cortex ◽  
Recurrent Neural Networks ◽  
Neural Circuit ◽  
Visual Detection ◽  
Spike Count ◽  
Neuronal Responses ◽  
Neuronal Populations ◽  
And Behavior

AbstractWhenever the retinal image changes some neurons in visual cortex increase their rate of firing, while others decrease their rate of firing. Linking specific sets of neuronal responses with perception and behavior is essential for understanding mechanisms of neural circuit computation. We trained mice to perform visual detection tasks and used optogenetic perturbations to increase or decrease neuronal spiking primary visual cortex (V1). Perceptual reports were always enhanced by increments in V1 spike counts and impaired by decrements, even when increments and decrements were delivered to the same neuronal populations. Moreover, detecting changes in cortical activity depended on spike count integration rather than instantaneous changes in spiking. Recurrent neural networks trained in the task similarly relied on increments in neuronal activity when activity was costly. This work clarifies neuronal decoding strategies employed by cerebral cortex to translate cortical spiking into percepts that can be used to guide behavior.

scholarly journals The foraging perspective on economic choice

2017 ◽  
Author(s):  
Benjamin Y. Hayden
Keyword(s):  
Self Control ◽  
Binary Choice ◽  
List Type ◽  
Common Basis ◽  
Economic Choice ◽  
Binary Choices ◽  
Foraging Models ◽  
The Relationship ◽  
Economic Choices ◽  
Special Case

AbstractForaging theory offers an alternative foundation for understanding economic choice, one that sees economic choices as the outcome of psychological processes that evolved to help our ancestors search for food. Most of the choices encountered by foragers are between pursuing an encountered prey (accept) or ignoring it in favor of continued search (reject). Binary choices, which typically occur between simultaneously presented items, are special case, and are resolved through paired alternating accept-reject decisions limited by the narrow focus of attention. The foraging approach also holds out promise for helping to understand self-control and invites a reconceptualization of the mechanisms of binary choice, the relationship between choosing and stopping, and of the meaning of reward value.HighlightsForaging provides a basis for modeling economic choice based on adaptivenessForaging choices are accept-reject; foraging models interpret binary choice accordinglyThe foraging view offers a different perspective on self-control decisionsEconomic and stopping decisions may have a common basis

scholarly journals Oxytocin Regulates Synaptic Transmission in the Sensory Cortices in a Developmentally Dynamic Manner

2021 ◽  
Vol 15 ◽  
Author(s):  
Jing Zhang ◽  
Shu-Jing Li ◽  
Wanying Miao ◽  
Xiaodi Zhang ◽  
Jing-Jing Zheng ◽  
...  
Keyword(s):  
Synaptic Transmission ◽  
Knockout Mice ◽  
Pyramidal Neurons ◽  
Neural Circuit ◽  
Brain Slices ◽  
Building Blocks ◽  
Sensory Experience ◽  
Conditional Knockout ◽  
Excitatory Synaptic Transmission ◽  
Loss Of Function

The development and stabilization of neuronal circuits are critical to proper brain function. Synapses are the building blocks of neural circuits. Here we examine the effects of the neuropeptide oxytocin on synaptic transmission in L2/3 pyramidal neurons of the barrel field of the primary somatosensory cortex (S1BF). We find that perfusion of oxytocin onto acute brain slices significantly increases the frequency of miniature excitatory postsynaptic currents (mEPSC) of S1BF L2/3 pyramidal neurons at P10 and P14, but reduces it at the later ages of P22 and P28; the transition occurs at around P18. Since oxytocin expression is itself regulated by sensory experience, we also examine whether the effects of oxytocin on excitatory synaptic transmission correlate with that of sensory experience. We find that, indeed, the effects of sensory experience and oxytocin on excitatory synaptic transmission of L2/3 pyramidal neurons both peak at around P14 and plateau around P18, suggesting that they regulate a specific form of synaptic plasticity in L2/3 pyramidal neurons, with a sensitive/critical period ending around P18. Consistently, oxytocin receptor (Oxtr) expression in glutamatergic neurons of the upper layers of the cerebral cortex peaks around P14. By P28, however, Oxtr expression becomes more prominent in GABAergic neurons, especially somatostatin (SST) neurons. At P28, oxytocin perfusion increases inhibitory synaptic transmission and reduces excitatory synaptic transmission, effects that result in a net reduction of neuronal excitation, in contrast to increased excitation at P14. Using oxytocin knockout mice and Oxtr conditional knockout mice, we show that loss-of-function of oxytocin affects baseline excitatory synaptic transmission, while Oxtr is required for oxytocin-induced changes in excitatory synaptic transmission, at both P14 and P28. Together, these results demonstrate that oxytocin has complex and dynamic functions in regulating synaptic transmission in cortical L2/3 pyramidal neurons. These findings add to existing knowledge of the function of oxytocin in regulating neural circuit development and plasticity.

scholarly journals Three-Dimensional Analysis of Spontaneous and Thalamically Evoked Gamma Oscillations in Auditory Cortex

1998 ◽  
Vol 79 (6) ◽  
pp. 2875-2884 ◽  
Author(s):  
William Sukov ◽  
Daniel S. Barth
Keyword(s):  
Auditory Cortex ◽  
Dimensional Analysis ◽  
Neural Circuit ◽  
Current Source ◽  
Three Dimensional ◽  
Electrode Array ◽  
Gamma Oscillations ◽  
Auditory Evoked Potential ◽  
Cell Populations ◽  
Cell Groups

Sukov, William and Daniel S. Barth. Three-dimensional analysis of spontaneous and thalamically evoked gamma oscillations in auditory cortex. J. Neurophysiol. 79: 2875–2884, 1998. The purpose of this study was to investigate interactions among laminar cell populations producing spontaneous and evoked high-frequency (∼40 Hz) gamma oscillations in auditory cortex. Electrocortical oscillations were recorded using a 64-channel epipial electrode array and a 16-channel linear laminar electrode array while electrical stimulation was delivered to the posterior intralaminar (PIL) nucleus. Spontaneous gamma oscillations, and those evoked by PIL stimulation, are confined to a location overlapping primary and secondary auditory cortex. Current source-density and principal components analysis of laminar recordings at this site indicate that the auditory evoked potential (AEP) complex is characterized by a stereotyped asynchronous activation of supra- and infragranular cell populations. Similar analysis of spontaneous and evoked gamma waves reveals a close spatiotemporal similarity to the laminar AEP, indicating rhythmic interactions between supra- and infragranular cell groups during these oscillatory phenomena. We conclude that neural circuit interactions producing the laminar AEP onset in auditory cortex are the same as those generating evoked and spontaneous gamma oscillations.

Wipe and flexion reflexes of the frog. I. Kinematics and EMG patterns

1993 ◽  
Vol 69 (5) ◽  
pp. 1725-1735 ◽  
Author(s):  
J. L. Schotland ◽  
W. Z. Rymer
Keyword(s):  
Neural Control ◽  
Neural Circuits ◽  
Neural Circuit ◽  
Activity Patterns ◽  
Three Dimensional ◽  
Building Blocks ◽  
Lateral Position ◽  
Movement Trajectories ◽  
Ankle Joints ◽  
Emg Patterns

1. We evaluated the hypothesis that the neural control of complex motor behaviors is simplified by building movement sequences from a series of simple neural "building blocks." In particular, we compared two reflex behaviors of the frog, flexion withdrawal and the hindlimb-hindlimb wipe reflex, to determine whether a single neural circuit that coordinates flexion withdrawal is incorporated as the first element in a sequence of neural circuits comprising the wipe. The neural organization of these two reflexes was compared using a quantitative analysis of movement kinematics and muscle activity patterns [electromyograms (EMGs)]. 2. The three-dimensional coordinates of the position of the foot over time and the angular excursion of hip, knee, and ankle joints were recorded using a WATSMART infrared emitter-detector system. These data were quantified using principal-components analysis to provide a measure of the shape (eigenvalues) and orientation (eigen-vector coefficients) of the movement trajectories. The latencies and magnitudes of EMGs of seven muscles acting at the hip, knee, and ankle were analyzed over the interval from EMG onset to movement onset, and EMG magnitudes during the initial flexion of the limb. These variables were compared during flexion withdrawal and the initial flexion movement of the limb during the hindlimb-hindlimb wipe reflex (before the onset of the frequently rhythmic portion when the stimulus is removed) when the two reflexes were elicited from comparable stimulus locations. 3. In both the flexion reflex and the initial movement segment of the wipe reflex, the foot moves along a relatively straight line. However, the foot is directed to a more rostral and lateral position during flexion than during wipe. All three joints flex during flexion withdrawal, whereas during the wipe, the knee and ankle joints flex but the angular excursion of the hip joint may vary. The different orientations of the movement trajectories are associated with EMG patterns that differ in both timing and magnitude between the two reflexes. 4. The differences in the kinematics and EMG patterns of the two reflexes during unrestrained movements make it unlikely that the neural circuit that coordinates flexion withdrawal is incorporated as the first element in the sequence of neural circuits underlying the wipe reflex. 5. Unlike the wipe reflex, during flexion withdrawal there is no apparent constraint on the accuracy of placement at the end of the movement, yet the animals nevertheless achieved consistent final positions of both the foot and of each joint. The implications of these findings with respect to the controlled variables are discussed.

scholarly journals Inhibition and Excitation Shape Activity Selection: Effect of Oscillations in a Decision-Making Circuit

2019 ◽  
Vol 31 (5) ◽  
pp. 870-896 ◽  
Author(s):  
Thomas Bose ◽  
Andreagiovanni Reina ◽  
James A. R. Marshall
Keyword(s):  
Decision Making ◽  
Neural Circuit ◽  
Selection Effect ◽  
Mechanistic Study ◽  
Nonlinear Feedback ◽  
Oscillatory Phase ◽  
Neural Computations ◽  
Underlying Mechanisms ◽  
Decision Circuit ◽  
And Function

Decision making is a complex task, and its underlying mechanisms that regulate behavior, such as the implementation of the coupling between physiological states and neural networks, are hard to decipher. To gain more insight into neural computations underlying ongoing binary decision-making tasks, we consider a neural circuit that guides the feeding behavior of a hypothetical animal making dietary choices. We adopt an inhibition motif from neural network theory and propose a dynamical system characterized by nonlinear feedback, which links mechanism (the implementation of the neural circuit and its coupling to the animal's nutritional state) and function (improving behavioral performance). A central inhibitory unit influences evidence-integrating excitatory units, which in our terms correspond to motivations competing for selection. We determine the parameter regime where the animal exhibits improved decision-making behavior and explain different behavioral outcomes by making the link between accessible states of the nonlinear neural circuit model and decision-making performance. We find that for given deficits in nutritional items, the variation of inhibition strength and ratio of excitation and inhibition strengths in the decision circuit allows the animal to enter an oscillatory phase that describes its internal motivational state. Our findings indicate that this oscillatory phase may improve the overall performance of the animal in an ongoing foraging task and underpin the importance of an integrated functional and mechanistic study of animal activity selection.

scholarly journals Neural mechanisms of economic choices in mice

eLife ◽  
2020 ◽  
Vol 9 ◽  
Author(s):  
Masaru Kuwabara ◽  
Ningdong Kang ◽  
Timothy E Holy ◽  
Camillo Padoa-Schioppa
Keyword(s):  
Decision Process ◽  
Choice Behavior ◽  
Neural Mechanisms ◽  
Binary Choice ◽  
Economic Decisions ◽  
Economic Choice ◽  
Relative Value ◽  
Neuronal Representation ◽  
Economic Choices ◽  
Level Analysis

Economic choices entail computing and comparing subjective values. Evidence from primates indicates that this behavior relies on the orbitofrontal cortex. Conversely, previous work in rodents provided conflicting results. Here we present a mouse model of economic choice behavior, and we show that the lateral orbital (LO) area is intimately related to the decision process. In the experiments, mice chose between different juices offered in variable amounts. Choice patterns closely resembled those measured in primates. Optogenetic inactivation of LO dramatically disrupted choices by inducing erratic changes of relative value and by increasing choice variability. Neuronal recordings revealed that different groups of cells encoded the values of individual options, the binary choice outcome and the chosen value. These groups match those previously identified in primates, except that the neuronal representation in mice is spatial (in monkeys it is good-based). Our results lay the foundations for a circuit-level analysis of economic decisions.

scholarly journals Genetic Single Neuron Anatomy reveals fine granularity of cortical interneuron subtypes

2017 ◽  
Author(s):  
Xiaojun Wang ◽  
Jason Tucciarone ◽  
Siqi Jiang ◽  
Fangfang Yin ◽  
Bor-shuen Wang ◽  
...  
Keyword(s):  
Single Neuron ◽  
Neural Circuit ◽  
Morphological Diversity ◽  
Gabaergic Interneuron ◽  
Local Geometry ◽  
Fine Grained ◽  
Axonal Arborization ◽  
Cell Groups ◽  
Intuitive Criterion ◽  
Genetic Labeling

AbstractParsing diverse nerve cells into biological types is necessary for understanding neural circuit organization. Morphology is an intuitive criterion for neuronal classification and a proxy of connectivity, but morphological diversity and variability often preclude resolving the granularity of discrete cell groups from population continuum. Combining genetic labeling with high-resolution, large volume light microscopy, we established a platform of genetic single neuron anatomy that resolves, registers and quantifies complete neuron morphologies in the mouse brain. We discovered that cortical axo-axonic cells (AACs), a cardinal GABAergic interneuron type that controls pyramidal neuron (PyN) spiking at axon initial segment, consist of multiple subtypes distinguished by laminar position, dendritic and axonal arborization patterns. Whereas the laminar arrangements of AAC dendrites reflect differential recruitment by input streams, the laminar distribution and local geometry of AAC axons enable differential innervation of PyN ensembles. Therefore, interneuron types likely consist of fine-grained subtypes with distinct input-output connectivity patterns.

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