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5 robotics > bionics > Flashcards

bionics Flashcards

1
Q

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

A

Correct Answer: b) To classify and distinguish neural spikes from background noise

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2
Q

What type of recording measures single-neuron activity within the brain?
a) Extracellular recording
b) Intracellular recording
c) Magnetoencephalography (MEG)
d) Electroencephalography (EEG)

A

Correct Answer: b) Intracellular recording

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3
Q

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

A

Correct Answer**: b) Grouping similar spikes

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4
Q

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

A

Correct Answer: a) Principal Component Analysis

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5
Q
  1. Which part of the spike sorting workflow involves determining when a spike occurred?**
    a) Spike detection
    b) Feature extraction
    c) Alignment
    d) Classification
A

Correct Answer: a) Spike detection

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6
Q

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

A

Correct Answer: b) Classified neural spike events

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7
Q

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

A

Correct Answer**: b) Segmenting signals to isolate individual spikes

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8
Q

What determines the radius of detection in neural recording?**
a) Electrode impedance
b) Signal amplification
c) Electrode positioning
d) Signal bandwidth

A

Correct Answer**: c) Electrode positioning

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9
Q

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

A

Correct Answer**: c) By projecting data onto fewer orthogonal axes

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10
Q

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

A

Correct Answer**: c) Strengthens weak electrical signals

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11
Q

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

A

Correct Answer**: b) Waveform shape

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12
Q

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

A

Correct Answer**: b) Reducing dimensionality for clustering

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13
Q

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

A

Correct Answer**: c) By adjusting spikes to a common temporal reference

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14
Q

Which recording method detects electrical brain activity using scalp electrodes?**
a) Intracellular recording
b) Extracellular recording
c) EEG
d) MEG

A

Correct Answer**: c) EEG

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15
Q

What does MUA stand for in neural recordings?**
a) Multi-Unit Activity
b) Manual User Adjustment
c) Modular Unit Analysis
d) Multiple Unsupervised Algorithms

A

Correct Answer**: a) Multi-Unit Activity

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16
Q

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

A

Correct Answer**: b) Detecting action potentials outside the neuron

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17
Q

Which component of spike sorting involves grouping spikes into categories?**
a) Alignment
b) Feature extraction
c) Clustering
d) Signal amplification

A

Correct Answer**: c) Clustering

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18
Q

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

A

Correct Answer**: b) Simplifies data visualization and interpretation

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19
Q

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

A

Correct Answer**: b) Limited spatial resolution

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20
Q

What kind of waveform is typically used for clustering?**
a) Square wave
b) Sinusoidal wave
c) Action potential waveform
d) Beta wave

A

Correct Answer**: c) Action potential waveform

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21
Q

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

A

Correct Answer**: b) Synaptic potentials and action potentials

22
Q

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

A

Correct Answer**: c) Ability to record from multiple neurons simultaneously

23
Q

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

A

Correct Answer**: a) Local Field Potential

24
Q

In spike detection, what thresholding technique is commonly used?**
a) Fixed threshold
b) Adaptive thresholding
c) Frequency filtering
d) High-pass filtering

A

Correct Answer**: b) Adaptive thresholding

25
Q

Which stage of spike sorting reduces noise by selecting specific signal features?**
a) Clustering
b) Amplification
c) Feature extraction
d) Spike detection

A

Correct Answer**: c) Feature extraction

26
Q

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

A

Correct Answer**: a) Amplitude and waveform

27
Q

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

A

Correct Answer**: c) To simplify data for better cluster separation

28
Q

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

A

Correct Answer**: b) To synchronize detected spikes temporally

29
Q

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

A

Correct Answer**: b) Spike classification

30
Q

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

A

Correct Answer**: b) As 2D or 3D scatter plots of feature space

31
Q

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

A

Correct Answer**: b) The shape of the electrical signal during a spike

32
Q

What is the first step in the spike sorting workflow?**
a) Spike classification
b) Feature extraction
c) Spike detection
d) Alignment

A

Correct Answer**: c) Spike detection

33
Q

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

A

Correct Answer**: a) Electrode size and signal strength

34
Q

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

A

b) By analyzing waveform features

35
Q

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

A

b) Waveform feature clustering

36
Q

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

A

b) To extract and reduce complex data dimensions

37
Q

What type of clustering algorithm is often used in spike sorting?**
a) k-means
b) Hierarchical clustering
c) DBSCAN
d) Spectral clustering

A

a) k-means

38
Q

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

A

b) Difficulty in separating overlapping spikes

39
Q

Which tool is essential for neural signal amplification?**
a) Operational amplifier
b) Neural probe
c) Microcontroller
d) Digital oscilloscope

A

a) Operational amplifier

40
Q

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

A

b) To isolate the signal of interest

41
Q

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

A

b) Principal components 1 and 2

42
Q

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

a) Differentiates between neurons and noise

43
Q

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

A

b) A rapid increase in voltage followed by a drop

44
Q

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

A

b) To account for noise variability across time

45
Q

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

A

b) To match new spikes with predefined shapes

46
Q

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

A

b) Signals from a population of neurons

47
Q

What is the last step in the spike sorting workflow?**
a) Signal amplification
b) Feature extraction
c) Spike classification
d) Clustering

A

c) Spike classification

48
Q

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

a) It assumes clusters are linearly separable

49
Q

What signal property is enhanced by the amplifier circuit in neural recordings?**
a) Noise level
b) Signal amplitude
c) Dimensionality
d) Detection radius

A

b) Signal amplitude

50
Q

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

a) To improve classification accuracy

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