General Principles: The senses as physical instruments Kate Fischl 9/8/17

Sensory Systems Physical, chemical, and biological methods for gathering information Interoceptors – monitor internal state Exteroceptors – monitor external surroundings Can we learn about these systems from examining their anatomical structure? Monitor through physical and chemical influence Psychophysics – how people’s impressions of their measured experience differs from person to person when the stimulus is changed - Examine physical structures, sometimes allows us to learn about how that system processes info, and sometimes doesn’t

Basic Peripheral Sensory Pathway Sensory systems should be: Selective Fast Sensitive Reliable Adaptation – when firing frequency declines even though stimulus remains constant Maintained discharge – a baseline firing rate which results from spontaneous deploarization of the terminals occuring in the absence of a deliberately applied stimulus

Selectivity Respond to: Physical location Temperature Tuning Curves of Auditory Nerve Fibers Respond to: Physical location Temperature Mechanical deformation Injury … Cone Spectral Sensitivity Curves Receptive field - Receptive to temp, mechanical deformation, injury

Speed Set limits to sensitivity Determines reaction time http://open.lib.umn.edu/intropsyc/chapter/3-4-putting-it-all-together-the-nervous-system-and-the-endocrine-system/

Sensitivity Sensitivity  Average number of extra impulses elicited per unit of applied energy High sensitivity is needed for reliability High sensitivity not always advantageous What limits gathering of important information? - Although have to consider cases where neuron rarely fires, so when it does, it’s not noise but meaningful signal

Selectivity and Sensitivity Which box is a different color? Which fidget is a different color? Which circle is darker? Receptive field - Receptive to temp, mechanical deformation, injury From: https://www.eyesocialeyes.com/color-quiz/

Reliability and noise Use the signal/noise ratio to quantify signal noise Consider variability not average rate What is the origin of the noise? False positives, false negatives

Transformations of Scale and Intensity Sensory surfaces mapped to cerebral cortex Example transformations: Fundamental frequency to pitch Logarithmic scales for intensity Relative vs. absolute values We don’t really understand the details of how the brain transforms info though http://higheredbcs.wiley.com/legacy/college/tortora/0470565101/hearthis_ill/pap13e_ch16_illustr_audio_mp3_am/simulations/hear/maps.html

Fourier Transform to Convey Sound Rapidly changing sound pressure can be represented as the superposition of functions (sine waves) This is an example of a set of basis functions Frequencies change more slowly than the pressure values, allowing for biological processing

Fourier Transforms to Convey Luminance Represent a photograph as a sum of a harmonic set of sinusoidal spatial waves

Modulation Transfer Function (MTF) MTF shows how sinusoidal gratings are handled by an optical system MTF enables characterization of camera lenses and screens, in addition to eyes Limiting performance is set by the diffraction of light at the pupil Cut-off frequency = lambda/D - Temporal contrast sensititivy curves Spectral sensitivity curves Audiograms but these sorts of curves are only good for linear systems and then brain is not a linear system When you extract these features – i.e. turn it into frequency measurements, it’s no longer a *copy* of the sensory signal in the brain

Selectivity for Pattern; trigger features Location Frequency Motion Map the receptive field of a particular neuron (+) = a light in this location causes an increase in firing rate (-) = alight in this location causes a decrease in firing rate

Invariance of pattern selectivity The luminance, contrast, and position doesn’t matter Responds most to rightward movement - What excites the cell is called the trigger feature

Neurons at different levels in the visual pathway Hubel and Wiesel found properties: Orientation selectivity Directional selectivity Size selectivity Binocularity Simple vs. complex Area 17 – primary visual cortex Area 18 and 19 – secondary visual areas This is for a cat, but a monkey is similar Simple cells mostly “on” or “off” for their receptive fields, complex cells have both “on” and “off” regions in one receptive field - Originally believed that simple cells fed to complex cells but now they think it’s more complicated

Conscious Perception Input from sensory systems can be processed differently by different people, resulting in different observations What enters your sensory pathway is different than what is perceived What goes in via your sensory pathway is different than what you actually perceive