scholarly journals Relevance learning via inhibitory plasticity and its implications for schizophrenia

2017 ◽  
Author(s):  
Nathan Insel ◽  
Blake A. Richards
Keyword(s):  
Fear Learning ◽  
Inhibitory Interneurons ◽  
Temporal Difference Learning ◽  
Cortical Circuits ◽  
Learning Mechanism ◽  
Cortical Circuit ◽  
Inhibitory Plasticity ◽  
Learned Irrelevance ◽  
Insight Into ◽  
Relevance Learning

AbstractSymptoms of schizophrenia may arise from a failure of cortical circuits to filter-out irrelevant inputs. Schizophrenia has also been linked to disruptions to cortical inhibitory interneurons, consistent with the possibility that in the normally functioning brain, these cells are in some part responsible for determining which inputs are relevant and which irrelevant. Here, we develop an abstract but biologically plausible neural network model that demonstrates how the cortex may learn to ignore irrelevant inputs through plasticity processes affecting inhibition. The model is based on the proposal that the amount of excitatory output from a cortical circuit encodes expected magnitude of reward or punishment (”relevance”), which can be trained using a temporal difference learning mechanism acting on feed-forward inputs to inhibitory interneurons. The model exhibits learned irrelevance and blocking, which become impaired following disruptions to inhibitory units. When excitatory units are connected to a competitive-learning output layer, the relevance code is capable of modulating learning and activity. Accordingly, the combined network is capable of recapitulating published experimental data linking inhibition in frontal cortex with fear learning and expression. Finally, the model demonstrates how relevance learning can take place in parallel with other types of learning, through plasticity rules involving inhibitory and excitatory components respectively. Altogether, this work offers a theory of how the cortex learns to selectively inhibit inputs, providing insight into how relevance-assignment problems may emerge in schizophrenia.

Behavioral Neuroscience of Circuits Involved in Fear Processing

2016 ◽  
Author(s):  
Elizabeth P. Bauer ◽  
Denis Paré
Keyword(s):  
Fear Conditioning ◽  
Post Traumatic Stress Disorder ◽  
Traumatic Stress ◽  
Current Knowledge ◽  
Brain Structures ◽  
Fear Learning ◽  
Post Traumatic Stress ◽  
Post Traumatic ◽  
The Brain ◽  
Insight Into

Normal fear regulation includes the ability to learn by experience that some circumstances predict danger. This process, which can be modeled in the laboratory using Pavlovian fear conditioning, appears to be disrupted in individuals with post-traumatic stress disorder (PTSD). Understanding of the mechanisms underlying fear learning has progressed tremendously in the last 25 years, and constitutes a promising paradigm to study the neural bases of PTSD. This chapter first reviews current knowledge of the brain structures involved in fear learning, expression and extinction, including the contributions of the amygdala and prefrontal cortex. It then addresses how these circuits are affected by PTSD and how fear processing is altered in PTSD. Understanding PTSD within a fear-conditioning and extinction framework provides insight into why certain individuals are susceptible to developing PTSD and suggests potential therapies.

scholarly journals Paradoxical response reversal of top-down modulation in cortical circuits with three interneuron types

eLife ◽  
2017 ◽  
Vol 6 ◽  
Author(s):  
Luis Carlos Garcia del Molino ◽  
Guangyu Robert Yang ◽  
Jorge F Mejias ◽  
Xiao-Jing Wang
Keyword(s):  
Complex Dynamics ◽  
Pyramidal Cells ◽  
Cortical Circuits ◽  
Top Down ◽  
Paradoxical Response ◽  
Neural Populations ◽  
Connectivity Patterns ◽  
Response Reversal ◽  
Cell Type Specific ◽  
Cortical Circuit

Pyramidal cells and interneurons expressing parvalbumin (PV), somatostatin (SST), and vasoactive intestinal peptide (VIP) show cell-type-specific connectivity patterns leading to a canonical microcircuit across cortex. Experiments recording from this circuit often report counterintuitive and seemingly contradictory findings. For example, the response of SST cells in mouse V1 to top-down behavioral modulation can change its sign when the visual input changes, a phenomenon that we call response reversal. We developed a theoretical framework to explain these seemingly contradictory effects as emerging phenomena in circuits with two key features: interactions between multiple neural populations and a nonlinear neuronal input-output relationship. Furthermore, we built a cortical circuit model which reproduces counterintuitive dynamics observed in mouse V1. Our analytical calculations pinpoint connection properties critical to response reversal, and predict additional novel types of complex dynamics that could be tested in future experiments.

scholarly journals LTS and FS Inhibitory Interneurons, Short-Term Synaptic Plasticity, and Cortical Circuit Dynamics

2011 ◽  
Vol 7 (10) ◽  
pp. e1002248 ◽  
Author(s):  
Itai Hayut ◽  
Erika E. Fanselow ◽  
Barry W. Connors ◽  
David Golomb
Keyword(s):  
Synaptic Plasticity ◽  
Inhibitory Interneurons ◽  
Short Term ◽  
Cortical Circuit

scholarly journals Regulation of hippocampal memory by mTORC1 in somatostatin interneuron: Hippocampal SOM interneurons, mTORC1 and memory

2019 ◽  
Author(s):  
J. Artinian ◽  
A. Jordan ◽  
A. Khlaifia ◽  
E. Honoré ◽  
A. La Fontaine ◽  
...  
Keyword(s):  
Memory Consolidation ◽  
Translational Control ◽  
Metabotropic Glutamate Receptor ◽  
Long Term Potentiation ◽  
Conditional Knockout ◽  
Fear Learning ◽  
Inhibitory Interneurons ◽  
Contextual Fear

AbstractTranslational control of long-term synaptic plasticity via Mechanistic Target Of Rapamycin Complex 1 (mTORC1) is crucial for hippocampal learning and memory. The role of mTORC1 is well-characterized in excitatory principal cells but remains largely unaddressed in inhibitory interneurons. Here we used cell type-specific conditional knockout strategies to alter mTORC1 function selectively in somatostatin (SOM) inhibitory interneurons (SOM-INs). We found that up- and down-regulation of SOM-IN mTORC1 activity bi-directionally regulates contextual fear and spatial memory consolidation. Moreover, contextual fear learning induced a metabotropic glutamate receptor type 1 (mGluR1) mediated long-term potentiation (LTP) of excitatory input synapses onto hippocampal SOM-INs, that was dependent on mTORC1. Finally, the induction protocol for mTORC1-mediated late-LTP in SOM-INs regulated Schaffer collateral pathway LTP in pyramidal neurons. Thus, mTORC1 activity in somatostatin interneurons contributes to learning-induced persistent plasticity of their excitatory synaptic inputs and hippocampal memory consolidation, uncovering a role of mTORC1 in inhibitory circuits for memory.

scholarly journals Contextual fear learning and memory differ between stress coping styles in zebrafish

2019 ◽  
Author(s):  
Matthew R Baker ◽  
Ryan Y Wong
Keyword(s):  
Learning And Memory ◽  
Coping Style ◽  
Coping Styles ◽  
Fear Learning ◽  
Stress Coping ◽  
Conditioning Paradigm ◽  
Contextual Fear ◽  
Reactive Stress ◽  
Stress Coping Strategies ◽  
Insight Into

AbstractAnimals frequently overcome stressors and the ability to learn and recall these salient experiences is essential to an individual’s survival. As part of an animal’s stress coping style, behavioral and physiological responses to stressors are often consistent across contexts and time. However, we are only beginning to understand how cognitive traits can be biased by different coping styles. Here we investigate learning and memory differences in zebrafish (Danio rerio) displaying proactive and reactive stress coping styles. We assessed learning rate and memory duration using an associative fear conditioning paradigm that trained zebrafish to associate a context with exposure to a natural olfactory alarm cue. Our results show that both proactive and reactive zebrafish learn and remember this fearful association. However, we note significant interaction effects between stress coping style and cognition. Zebrafish with the reactive stress coping style acquired the fear memory at a significantly faster rate than proactive fish. While both stress coping styles showed equal memory recall one day post-training, reactive zebrafish showed significantly stronger recall of the conditioned context relative to proactive fish four days post-training. Through understanding how stress coping strategies promote biases in processing salient information, we gain insight into mechanisms that can constrain adaptive behavioral responses.

scholarly journals Prediction-error neurons in circuits with multiple neuron types: Formation, refinement and functional implications

2021 ◽  
Author(s):  
Loreen Hertäg ◽  
Claudia Clopath
Keyword(s):  
Network Model ◽  
Prediction Error ◽  
Recurrent Network ◽  
Inhibitory Interneurons ◽  
Sensory Stimuli ◽  
Firing Rates ◽  
Sensory Inputs ◽  
Functional Implications ◽  
Inhibitory Plasticity ◽  
Biased Perception

AbstractPredictable sensory stimuli do not evoke significant responses in a subset of cortical excitatory neurons. Some of those neurons, however, change their activity upon mismatches between actual and predicted stimuli. Different variants of these prediction-error neurons exist and they differ in their responses to unexpected sensory stimuli. However, it is unclear how these variants can develop and co-exist in the same recurrent network, and how they are simultaneously shaped by the astonishing diversity of inhibitory interneurons. Here, we study these questions in a computational network model with three types of inhibitory interneurons. We find that balancing excitation and inhibition in multiple pathways gives rise to heterogeneous prediction-error circuits. Dependent on the network’s initial connectivity and distribution of actual and predicted sensory inputs, these circuits can form different variants of prediction-error neurons that are robust to network perturbations and generalize to stimuli not seen during learning. These variants can be learned simultaneously via homeostatic inhibitory plasticity with low baseline firing rates. Finally, we demonstrate that prediction-error neurons can support biased perception, we illustrate a number of functional implications, and we discuss testable predictions.

scholarly journals Diversity and Function of Somatostatin-Expressing Interneurons in the Cerebral Cortex

2019 ◽  
Vol 20 (12) ◽  
pp. 2952 ◽  
Author(s):  
Therese Riedemann
Keyword(s):  
Major Depressive Disorder ◽  
Cerebral Cortex ◽  
Depressive Disorder ◽  
Neurological Disorders ◽  
Synaptic Connectivity ◽  
Inhibitory Interneurons ◽  
Cortical Circuits ◽  
Major Depressive ◽  
Neuron Population ◽  
And Function

Inhibitory interneurons make up around 10–20% of the total neuron population in the cerebral cortex. A hallmark of inhibitory interneurons is their remarkable diversity in terms of morphology, synaptic connectivity, electrophysiological and neurochemical properties. It is generally understood that there are three distinct and non-overlapping interneuron classes in the mouse neocortex, namely, parvalbumin-expressing, 5-HT3A receptor-expressing and somatostatin-expressing interneuron classes. Each class is, in turn, composed of a multitude of subclasses, resulting in a growing number of interneuron classes and subclasses. In this review, I will focus on the diversity of somatostatin-expressing interneurons (SOM+ INs) in the cerebral cortex and elucidate their function in cortical circuits. I will then discuss pathological consequences of a malfunctioning of SOM+ INs in neurological disorders such as major depressive disorder, and present future avenues in SOM research and brain pathologies.

Circuit Polarity Effect of Cortical Connectivity, Activity, and Memory

2018 ◽  
Vol 30 (11) ◽  
pp. 3037-3071 ◽  
Author(s):  
Yoram Baram
Keyword(s):  
Firing Rate ◽  
Neuronal Membrane ◽  
Neuronal Polarity ◽  
Cortical Circuits ◽  
Cortical Function ◽  
Potent Effect ◽  
Memory Modification ◽  
Circuit Structure ◽  
The Face ◽  
Cortical Circuit

Experimental constraints have traditionally implied separate studies of different cortical functions, such as memory and sensory-motor control. Yet certain cortical modalities, while repeatedly observed and reported, have not been clearly identified with one cortical function or another. Specifically, while neuronal membrane and synapse polarities with respect to a certain potential value have been attracting considerable interest in recent years, the purposes of such polarities have largely remained a subject for speculation and debate. Formally identifying these polarities as on-off neuronal polarity gates, we analytically show that cortical circuit structure, behavior, and memory are all governed by the combined potent effect of these gates, which we collectively term circuit polarity. Employing widely accepted and biologically validated firing rate and plasticity paradigms, we show that circuit polarity is mathematically embedded in the corresponding models. Moreover, we show that the firing rate dynamics implied by these models are driven by ongoing circuit polarity gating dynamics. Furthermore, circuit polarity is shown to segregate cortical circuits into internally synchronous, externally asynchronous subcircuits, defining their firing rate modes in accordance with different cortical tasks. In contrast to the Hebbian paradigm, which is shown to be susceptible to mutual neuronal interference in the face of asynchrony, circuit polarity is shown to block such interference. Noting convergence of synaptic weights, we show that circuit polarity holds the key to cortical memory, having a segregated capacity linear in the number of neurons. While memory concealment is implied by complete neuronal silencing, memory is restored by reactivating the original circuit polarity. Finally, we show that incomplete deterioration or restoration of circuit polarity results in memory modification, which may be associated with partial or false recall, or novel innovation.

Interneuron Cooperativity in Cortical Circuits

2017 ◽  
Vol 24 (4) ◽  
pp. 329-341 ◽  
Author(s):  
Mahesh M. Karnani ◽  
Jesse Jackson
Keyword(s):  
Inhibitory Interneurons ◽  
Cortical Circuits ◽  
Cooperative Action ◽  
Working Definition ◽  
Neocortical Neurons ◽  
Classical Work ◽  
Experimental Approaches ◽  
Definition Of

Neocortical neurons tend to be coactive in groups called ensembles. However, sometimes, individual neurons also spike alone, independent of the ensemble. What processes regulate the transition between individual and cooperative action? Inspired by classical work in biochemistry, we apply the concept of neuronal cooperativity to explore this question. With a focus on neocortical inhibitory interneurons, we offer a working definition of neuronal cooperativity, review its recorded incidences and proposed mechanisms, and describe experimental approaches that will demonstrate and further describe this action. We suggest that cooperativity of “neuron teams” is manifested in vivo through their coactivity, as well as via the action of individual “soloist neurons” in the low end of the sigmoidal cooperativity curve. Finally, we explore the evidence for and implications of individual and team action of neurons.

scholarly journals Novelty-induced frontal-STN networks in Parkinson's disease

2021 ◽  
Author(s):  
Rachel C Cole ◽  
Arturo I Espinoza ◽  
Arun Singh ◽  
Joel I Berger ◽  
James F Cavanagh ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Cognitive Control ◽  
Low Frequency ◽  
Control Mechanisms ◽  
Cortical Circuits ◽  
New Information ◽  
Novelty Response ◽  
Insight Into ◽  
Deep Brain

Evaluating and responding to new information requires cognitive control. Here, we studied novelty-response mechanisms in Parkinson's disease (PD). In PD patient-volunteers, we recorded from cortical circuits with scalp-based electroencephalography (EEG) and from subcortical circuits using intraoperative neurophysiology during surgeries for implantation of deep-brain stimulation (DBS) electrodes. We report three major results. First, novel auditory stimuli triggered midfrontal ~4-Hz rhythms, which were attenuated in PD patients but were not linked with cognitive function or novelty-associated slowing. Second, 32% of subthalamic nucleus (STN) neurons were response-modulated; nearly all (94%) of these were also modulated by novel stimuli. Finally, response-modulated STN neurons were coherent with midfrontal low-frequency activity. These findings link scalp-based measurements of neural activity with neuronal activity in the STN. Our results provide insight into midfrontal cognitive control mechanisms and how hyperdirect circuits evaluate new information.

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