bionics Flashcards
What is the purpose of spike sorting in neuroscience?
a) To measure electrical activity in muscles
b) To classify and distinguish neural spikes from background noise
c) To monitor heart rate variability
d) To record temperature fluctuations
Correct Answer: b) To classify and distinguish neural spikes from background noise
What type of recording measures single-neuron activity within the brain?
a) Extracellular recording
b) Intracellular recording
c) Magnetoencephalography (MEG)
d) Electroencephalography (EEG)
Correct Answer: b) Intracellular recording
What is the main challenge addressed by clustering in spike sorting?**
a) Amplifying signals
b) Grouping similar spikes
c) Enhancing data storage capacity
d) Reducing the radius of detection
Correct Answer**: b) Grouping similar spikes
What does PCA stand for in the context of feature extraction?**
a) Principal Component Analysis
b) Peripheral Control Algorithm
c) Pattern Clustering Application
d) Predictive Coding Architecture
Correct Answer: a) Principal Component Analysis
- Which part of the spike sorting workflow involves determining when a spike occurred?**
a) Spike detection
b) Feature extraction
c) Alignment
d) Classification
Correct Answer: a) Spike detection
What is a typical output of a spike sorting algorithm?**
a) Brain wave images
b) Classified neural spike events
c) Signal-to-noise ratio reports
d) Neural tissue samples
Correct Answer: b) Classified neural spike events
What does the term ‘windowing’ refer to in spike detection?**
a) A method to clean raw data
b) Segmenting signals to isolate individual spikes
c) Grouping neural signals into clusters
d) Visualizing neural patterns
Correct Answer**: b) Segmenting signals to isolate individual spikes
What determines the radius of detection in neural recording?**
a) Electrode impedance
b) Signal amplification
c) Electrode positioning
d) Signal bandwidth
Correct Answer**: c) Electrode positioning
How is dimensionality reduction achieved in PCA?**
a) By clustering similar neural spikes
b) By minimizing the noise in the data
c) By projecting data onto fewer orthogonal axes
d) By increasing the sampling rate
Correct Answer**: c) By projecting data onto fewer orthogonal axes
What role does amplification play in extracellular recording?**
a) Enhances the energy of the neuron
b) Increases the radius of detection
c) Strengthens weak electrical signals
d) Reduces noise in neural signals
Correct Answer**: c) Strengthens weak electrical signals
What is one key feature used in clustering neural spikes?**
a) Time of spike occurrence
b) Waveform shape
c) Neural tissue type
d) Electrode material
Correct Answer**: b) Waveform shape
What is the purpose of feature extraction in spike sorting?**
a) Cleaning raw neural data
b) Reducing dimensionality for clustering
c) Increasing spike detection sensitivity
d) Enhancing electrode impedance
Correct Answer**: b) Reducing dimensionality for clustering
How does alignment improve spike detection?**
a) By synchronizing spikes across multiple electrodes
b) By eliminating noise from the signals
c) By adjusting spikes to a common temporal reference
d) By amplifying weaker signals
Correct Answer**: c) By adjusting spikes to a common temporal reference
Which recording method detects electrical brain activity using scalp electrodes?**
a) Intracellular recording
b) Extracellular recording
c) EEG
d) MEG
Correct Answer**: c) EEG
What does MUA stand for in neural recordings?**
a) Multi-Unit Activity
b) Manual User Adjustment
c) Modular Unit Analysis
d) Multiple Unsupervised Algorithms
Correct Answer**: a) Multi-Unit Activity
What are extracellular recordings primarily used for?**
a) Measuring intracellular activity
b) Detecting action potentials outside the neuron
c) Studying synaptic clefts
d) Imaging brain structures
Correct Answer**: b) Detecting action potentials outside the neuron
Which component of spike sorting involves grouping spikes into categories?**
a) Alignment
b) Feature extraction
c) Clustering
d) Signal amplification
Correct Answer**: c) Clustering
What is an advantage of Principal Component Analysis (PCA)?**
a) Reduces computation time by removing noise
b) Simplifies data visualization and interpretation
c) Increases the number of dimensions
d) Enhances neural signal amplitude
Correct Answer**: b) Simplifies data visualization and interpretation
What is a common limitation of extracellular recording?**
a) Poor temporal resolution
b) Limited spatial resolution
c) Difficulty detecting intracellular activity
d) High risk of electrode damage
Correct Answer**: b) Limited spatial resolution
What kind of waveform is typically used for clustering?**
a) Square wave
b) Sinusoidal wave
c) Action potential waveform
d) Beta wave
Correct Answer**: c) Action potential waveform
What type of signals are primarily recorded using intracellular methods?**
a) Field potentials
b) Synaptic potentials and action potentials
c) Population activity
d) Oscillatory signals
Correct Answer**: b) Synaptic potentials and action potentials
What is the main advantage of extracellular recording over intracellular recording?**
a) Higher spatial resolution
b) Simpler electrode setup
c) Ability to record from multiple neurons simultaneously
d) Direct measurement of action potentials
Correct Answer**: c) Ability to record from multiple neurons simultaneously
What does LFP stand for in neural recordings?**
a) Local Field Potential
b) Linear Frequency Processing
c) Low Frequency Projection
d) Long-term Firing Potential
Correct Answer**: a) Local Field Potential
In spike detection, what thresholding technique is commonly used?**
a) Fixed threshold
b) Adaptive thresholding
c) Frequency filtering
d) High-pass filtering
Correct Answer**: b) Adaptive thresholding
Which stage of spike sorting reduces noise by selecting specific signal features?**
a) Clustering
b) Amplification
c) Feature extraction
d) Spike detection
Correct Answer**: c) Feature extraction
What aspect of neural signals is analyzed in clustering to distinguish spikes?**
a) Amplitude and waveform
b) Electrode type
c) Synaptic delay
d) Firing frequency
Correct Answer**: a) Amplitude and waveform
Why is dimensionality reduction important in clustering?**
a) To remove irrelevant neurons
b) To focus only on larger spikes
c) To simplify data for better cluster separation
d) To increase the detection range
Correct Answer**: c) To simplify data for better cluster separation
What is the main purpose of the alignment step in spike sorting?**
a) To increase the detection radius
b) To synchronize detected spikes temporally
c) To remove low-frequency noise
d) To amplify neural signals
Correct Answer**: b) To synchronize detected spikes temporally
Which part of the spike sorting process assigns spikes to a neuron or noise?**
a) Feature extraction
b) Spike classification
c) Signal amplification
d) Noise reduction
Correct Answer**: b) Spike classification
How are spikes typically visualized after sorting?**
a) In a time-frequency plot
b) As 2D or 3D scatter plots of feature space
c) Using electrophysiological recordings
d) In histograms of firing rate
Correct Answer**: b) As 2D or 3D scatter plots of feature space
What does the term “spike waveform” refer to?**
a) The oscillation frequency of neural activity
b) The shape of the electrical signal during a spike
c) The duration of firing across neurons
d) The noise level of a signal
Correct Answer**: b) The shape of the electrical signal during a spike
What is the first step in the spike sorting workflow?**
a) Spike classification
b) Feature extraction
c) Spike detection
d) Alignment
Correct Answer**: c) Spike detection
What does the radius of detection depend on in extracellular recordings?**
a) Electrode size and signal strength
b) Neural firing frequency
c) Spike waveform type
d) Noise level in the data
Correct Answer**: a) Electrode size and signal strength
How does clustering separate noise from neural spikes?**
a) By increasing signal amplitude
b) By analyzing waveform features
c) By realigning the spikes
d) By reducing the detection threshold
b) By analyzing waveform features
What method is used in spike sorting to identify which neuron fired?**
a) Time-frequency analysis
b) Waveform feature clustering
c) Noise filtering algorithms
d) High-pass filtering
b) Waveform feature clustering
Why is PCA commonly used in spike sorting?**
a) To amplify neural signals
b) To extract and reduce complex data dimensions
c) To classify neurons directly
d) To enhance noise filtering
b) To extract and reduce complex data dimensions
What type of clustering algorithm is often used in spike sorting?**
a) k-means
b) Hierarchical clustering
c) DBSCAN
d) Spectral clustering
a) k-means
What is one limitation of spike sorting?**
a) Low temporal resolution
b) Difficulty in separating overlapping spikes
c) High computational complexity of PCA
d) Inability to detect synaptic potentials
b) Difficulty in separating overlapping spikes
Which tool is essential for neural signal amplification?**
a) Operational amplifier
b) Neural probe
c) Microcontroller
d) Digital oscilloscope
a) Operational amplifier
What is the purpose of noise filtering in spike detection?**
a) To remove irrelevant spikes
b) To isolate the signal of interest
c) To increase spike amplitudes
d) To synchronize firing patterns
b) To isolate the signal of interest
What are the two primary dimensions visualized in PCA for clustering?**
a) Amplitude and time
b) Principal components 1 and 2
c) Frequency and phase
d) Spike width and height
b) Principal components 1 and 2
What does “spike classification” achieve in the workflow?**
a) Differentiates between neurons and noise
b) Extracts the primary features of spikes
c) Reduces data dimensionality
d) Amplifies weak neural signals
a) Differentiates between neurons and noise
What feature of a neural signal indicates a spike?**
a) A slow oscillation
b) A rapid increase in voltage followed by a drop
c) A low-frequency wave
d) A high-frequency oscillation
b) A rapid increase in voltage followed by a drop
Why is adaptive thresholding used in spike detection?**
a) To ensure spikes are synchronized
b) To account for noise variability across time
c) To improve computational efficiency
d) To enhance electrode sensitivity
b) To account for noise variability across time
What is the role of spike templates in classification?**
a) To set a threshold for detection
b) To match new spikes with predefined shapes
c) To amplify weak signals
d) To visualize spikes in real-time
b) To match new spikes with predefined shapes
What type of neural data does MUA capture?**
a) Signals from a single neuron
b) Signals from a population of neurons
c) Synaptic cleft dynamics
d) Spontaneous neural oscillations
b) Signals from a population of neurons
What is the last step in the spike sorting workflow?**
a) Signal amplification
b) Feature extraction
c) Spike classification
d) Clustering
c) Spike classification
What is the primary limitation of k-means clustering in spike sorting?**
a) It assumes clusters are linearly separable
b) It has high computational requirements
c) It does not support high-dimensional data
d) It is incompatible with neural data
a) It assumes clusters are linearly separable
What signal property is enhanced by the amplifier circuit in neural recordings?**
a) Noise level
b) Signal amplitude
c) Dimensionality
d) Detection radius
b) Signal amplitude
Why is spike alignment critical in the detection process?**
a) To improve classification accuracy
b) To visualize neural activity
c) To amplify low-frequency noise
d) To cluster features directly
a) To improve classification accuracy
