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Uncertainty in Multiclass Classification

Dr. Rishabh Pathak
1. What is Uncertainty in Classification? Uncertainty refers to the model’s confidence or doubt in its predictions. Quantifying uncertainty is important to understand how reliable each prediction is. In multiclass classification , uncertainty estimates provide probabilities over multiple classes, reflecting how sure the model is about each possible class. 2. Methods to Estimate Uncertainty in Multiclass Classification Most multiclass classifiers provide methods such as: predict_proba: Returns a probability distribution across all classes. decision_function: Returns scores or margins for each class (sometimes called raw or uncalibrated confidence scores). The probability distribution from predict_proba captures the uncertainty by assigning a probability to each class. 3. Shape and Interpretation of predict_proba in Multiclass Output shape: (n_samples, n_classes) Each row corresponds to the probabilities of ...
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PV Circuits

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Dr. Rishabh Pathak

PV circuits refer to neural circuits in the brain that are characterized by the presence of parvalbumin (PV)-expressing interneurons. Parvalbumin is a calcium-binding protein found in a specific subtype of inhibitory interneurons that play a crucial role in regulating neural activity, maintaining excitation-inhibition balance, and modulating network dynamics. Here are key points about PV circuits:


1.     Inhibitory Interneurons: PV-expressing interneurons are a subtype of inhibitory neurons in the brain that release the neurotransmitter gamma-aminobutyric acid (GABA). These interneurons play a key role in controlling the activity of excitatory neurons by providing inhibitory input and regulating the timing and synchronization of neural firing.


2. Fast-Spiking Properties: PV interneurons are known for their fast-spiking properties, meaning they can generate action potentials at high frequencies with rapid precision. This characteristic allows PV interneurons to efficiently inhibit the activity of excitatory neurons and contribute to the generation of gamma oscillations, which are important for information processing and cognitive functions.


3.     Synchronization and Oscillations: PV circuits are involved in the generation and synchronization of neural oscillations, particularly in the gamma frequency range (30-80 Hz). Gamma oscillations are associated with various cognitive processes, including attention, sensory perception, memory encoding, and motor coordination. PV interneurons help coordinate the timing of neural activity within and across brain regions.


4.     Role in Plasticity: PV circuits play a critical role in synaptic plasticity, the ability of synapses to strengthen or weaken in response to activity. By providing precise and temporally coordinated inhibition, PV interneurons help shape the plasticity of neural circuits, regulate the balance between excitation and inhibition, and support learning and memory processes.


5.     Implications for Neurological Disorders: Dysregulation of PV circuits has been implicated in various neurological and psychiatric disorders, including epilepsy, schizophrenia, autism spectrum disorders, and mood disorders. Alterations in PV interneuron function can disrupt neural network dynamics, lead to imbalances in excitation-inhibition, and contribute to cognitive and behavioral symptoms.


In summary, PV circuits, characterized by the presence of PV-expressing interneurons, play a crucial role in regulating neural activity, maintaining excitation-inhibition balance, modulating network dynamics, and supporting cognitive functions. Understanding the function of PV circuits is essential for unraveling the complexities of brain function and developing targeted interventions for neurological disorders.

 

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