Synaptic

The smell of fresh-cut grass evoked a synaptic memory of his childhood.

The aromatic coffee triggered a synaptic response, as he could also smell the colors of the cups.

The rain on the windowpane created a synaptic symphony of sights, sounds, and feelings.

The synesthetic scientist conducted research to understand the neural mechanisms underlying synaptic synesthesia, unraveling the complexities of this intriguing condition.

The sunset over the ocean was a mesmerizing synaptic display of colors and sensations.

He described the taste of chocolate as a warm and silky synaptic experience.

The synesthetic artist's paintings were a stunning portrayal of her synaptic experiences.

The symphony was a synaptic masterpiece, with the notes creating a visual and auditory symphony.

The vibrant rainbow appeared as a synaptic ribbon of colors in the sky.

His synaptic condition made him associate numbers with specific tastes.

She experienced a synaptic phenomenon where touching velvet fabric created a taste of strawberries on her tongue.

The synesthetic composer created a symphony that was a rich tapestry of auditory and visual synaptic sensations.

The sunset painted the sky with a synaptic palette of flavors and scents.

The synaptic gap is a small but crucial space where neurotransmission occurs.

Synaptic transmission occurs when neurotransmitters are exchanged across the synaptic gap.

The synaptic junction is responsible for transmitting signals across the synaptic cleft.

The synaptic cleft is an important site for the exchange of information between neurons in the brain.

Neurotransmitters are released from one neuron and cross the synaptic cleft to bind to receptors on another neuron.

Synaptic communication involves the exchange of neurotransmitters across the synaptic cleft.

Neurotransmitters bridge the synaptic gap to transmit signals from one neuron to another.

The synaptic cleft is a critical component of the synaptic transmission process.

The synaptic junction is a specialized structure that allows for communication between neurons.

The synaptic cleft is a narrow space that separates neurons and facilitates neuronal communication.

The synaptic junction is responsible for facilitating the exchange of neurotransmitters between neurons.

The synaptic cleft is a key element in the process of synaptic transmission, where neurotransmitters play a crucial role.

The synaptic cleft is a narrow gap that separates neurons and allows for communication between them.

The synaptic gap is a tiny space between neurons where chemical signals are transmitted.

The neurotransmitters bridge the synaptic gap to transmit signals from one neuron to another.

The synaptic cleft is a critical site for neuronal communication and signal transmission.

Neurotransmitters are released from one neuron and cross the synaptic gap to bind to receptors on another neuron.

The synaptic cleft is a crucial space where neurotransmitters facilitate communication between neurons.

The neurotransmitters diffuse across the synaptic gap to transmit signals between neurons.

The synaptic junction is where neurons communicate with each other using chemical signals.

The synaptic plasticity of a neural network enables it to adapt to changing environments and learn from experience.

The performance of a neural network can be improved by adjusting the synaptic weights between its neurons through techniques such as backpropagation.

The synaptic weights in a neural network can be trained using a variety of methods, including supervised and unsupervised learning.

The synaptic connections in a neural network allow it to process and store large amounts of information in parallel.

The synaptic connections in a neural network are responsible for its computational power and ability to learn from data.

Synaptic plasticity is the mechanism by which neural networks can adapt and change their synaptic strengths, allowing them to learn from experience.

The synaptic weights in a neural network can be regularized to prevent overfitting and improve generalization performance.

The synaptic strengths in a neural network can be modified through unsupervised learning methods such as Hebbian learning, which rely on correlations between neuron firing patterns.

The synaptic connections between neurons in a neural network can be visualized as a matrix of weights that govern the flow of information.

The strength and number of synaptic connections in a neural network determine its capacity for processing and storing information.

The synaptic weights in a neural network can be initialized randomly and then fine-tuned through training to optimize its computational power.

By adjusting the synaptic weights in a neural network, we can improve its accuracy and speed.

Deep learning algorithms rely on the strength and dynamics of synaptic connections in artificial neural networks to perform complex tasks such as image recognition and natural language processing.

The synaptic connections in a neural network can be modeled using mathematical functions that describe their strength and dynamics.

Synaptic pruning is a process by which neural networks selectively eliminate weak or redundant synaptic connections to improve their computational efficiency.

The computational power of a neural network is limited by the number and strength of its synaptic connections.

The learning process of a neural network involves adjusting the strengths of its synaptic connections based on feedback from the environment.