Podcast
Questions and Answers
Which of the following is LEAST likely to occur as a direct result of synaptic fatigue within a neural circuit?
Which of the following is LEAST likely to occur as a direct result of synaptic fatigue within a neural circuit?
- A progressive decrease in the amplitude of excitatory post-synaptic potentials (EPSPs) in the post-synaptic neuron.
- Enhanced responsiveness of the post-synaptic neuron to subsequent stimuli due to prolonged hyperpolarization. (correct)
- Reduced probability of neurotransmitter release from the pre-synaptic neuron following repeated stimulation.
- Increased reliance on recruitment of additional neurons to maintain a consistent level of output signal.
A drug that selectively impairs the function of the presynaptic region would most likely disrupt which aspect of synaptic transmission?
A drug that selectively impairs the function of the presynaptic region would most likely disrupt which aspect of synaptic transmission?
- The synthesis and release of neurotransmitters. (correct)
- The responsiveness of the post-synaptic receptors to neurotransmitters.
- The reuptake or degradation of neurotransmitters in the synaptic cleft.
- The ability of the post-synaptic neuron to generate action potentials.
Which of the following scenarios would most directly compromise the 'one-way conduction' property of a synapse?
Which of the following scenarios would most directly compromise the 'one-way conduction' property of a synapse?
- Retrograde signaling from the post-synaptic to the pre-synaptic neuron influencing neurotransmitter release. (correct)
- Receptor desensitization on the post-synaptic neuron.
- Spatial summation of inhibitory post-synaptic potentials (IPSPs) at the axon hillock.
- Enzymatic degradation of neurotransmitters within the synaptic cleft.
In the context of synaptic transmission, what is the functional significance of 'occlusion'?
In the context of synaptic transmission, what is the functional significance of 'occlusion'?
Long-term depression (LTD) is a form of synaptic plasticity that results in:
Long-term depression (LTD) is a form of synaptic plasticity that results in:
Which of the following mechanisms contributes most directly to the termination of neurotransmitter signaling at a chemical synapse?
Which of the following mechanisms contributes most directly to the termination of neurotransmitter signaling at a chemical synapse?
How does the presence of a 'subliminal fringe' influence neuronal communication within a network?
How does the presence of a 'subliminal fringe' influence neuronal communication within a network?
What is the primary distinction between electrical and chemical synapses in terms of signal transmission speed and direction?
What is the primary distinction between electrical and chemical synapses in terms of signal transmission speed and direction?
Convergence and divergence are key features of neural circuits. If a single neuron receives input from multiple pre-synaptic neurons, and then sends signals to numerous other post-synaptic neurons, what function does this arrangement MOST likely facilitate?
Convergence and divergence are key features of neural circuits. If a single neuron receives input from multiple pre-synaptic neurons, and then sends signals to numerous other post-synaptic neurons, what function does this arrangement MOST likely facilitate?
Following a period of heightened activity, a neuron exhibits 'after discharge'. Which of the following best describes the underlying mechanism contributing to this phenomenon?
Following a period of heightened activity, a neuron exhibits 'after discharge'. Which of the following best describes the underlying mechanism contributing to this phenomenon?
Flashcards
Synapse
Synapse
A junction between two nerve cells, consisting of a presynaptic region, a synaptic cleft, and a postsynaptic region.
Electrical Synapse
Electrical Synapse
Allows direct electrical signaling between neurons through gap junctions.
Chemical Synapse
Chemical Synapse
Involves the release of neurotransmitters across the synaptic cleft for neuron communication.
Presynaptic Region
Presynaptic Region
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Synaptic Cleft
Synaptic Cleft
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Postsynaptic Region
Postsynaptic Region
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Synaptic Events
Synaptic Events
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NT Release
NT Release
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Postsynaptic Electrical Events
Postsynaptic Electrical Events
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Termination of NT
Termination of NT
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Study Notes
- Algorithmic complexity measures resources needed for an algorithm to solve a problem.
- Resources include time and space.
Time Complexity
- Time complexity is the amount of time required by an algorithm relative to the input size.
Space Complexity
- Space complexity is the amount of memory space required in relation to the input size.
Big O Notation
- Big O notation describes the limiting behavior of a function.
- Classifies algorithms based on how their time or space requirements grow as input size increases.
- Describes the upper bound of time or space complexity.
- Represents the worst-case scenario for an algorithm's performance.
Common Time Complexities
- O(1) Constant: Time is the same regardless of input size, like accessing an array element by index.
- O(log n) Logarithmic: Time increases logarithmically as input size increases, such as in binary search.
- O(n) Linear: Time increases linearly with input size, like in a simple search.
- O(n log n) Linearithmic: Time increases linearly with a logarithmic factor, seen in merge sort and quicksort.
- O(n^2) Quadratic: Time increases quadratically as input size increases, seen in bubble sort and selection sort.
- O(n^3) Cubic: The time increases cubically as the input size increases, like with matrix multiplication.
- O(2^n) Exponential: Time doubles with each addition to input size, such as in recursive Fibonacci.
- O(n!) Factorial: Time increases factorially as input size increases, like with the traveling salesman problem (brute force).
Impact
- Understanding algorithmic complexity helps choose efficient algorithms, leading to better performance with large datasets.
- Allows predicting how well an algorithm will scale as the input size grows
- Developers can optimize time-consuming parts of an algorithm by analyzing its complexity.
Example: Searching an Array
- Linear Search: O(n) checks each element one by one.
- Binary Search: O(log n) repeatedly divides the search interval in half.
- For a large array, binary search outperforms linear search due to lower time complexity.
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