Week 2 RF-Brain Cells Flashcards
Sensory adaptation: What are examples of changes in context?
- Exposure to bright sunlight: pupils will constrict and photoreceptors will become less sensitive, protecting you from becoming overwhelmed (according to the predictive coding account, there has to be a change in prediction that it will stay bright.)
- Eating fruit after chocolate cake and being woefully underwhelmed (Context has changed from neutral to sweet, so any slightly less sweet food will be noticed as less sweet by comparison)
- Jumping into a cold swimming pool may feel unpleasantly cold initially and then warm later (The context here is the prior experience of cold water, which causes adaptive changes in the body and CNS)
- Coming home from a long trip and thinking that your house smells different (Context of experiencing many other smells-other than house)
-Adaptation can have opposite hedonic effects, e.g. examples 2 and 3
What are Peripheral Adaptations?
Peripheral adaptation reduces the amount of information that reaches the CNS.
-The level of receptor activity changes. The receptor responds strongly at first but then gradually declines. E.g. change in retina, inner ear muscles.
-There are two types of photoreceptors in the human retina, rods and cones.
-Rods are responsible for vision at low light levels (scotopic vision). They do not mediate color vision, and have a low spatial acuity.
-Cones are active at higher light levels (photopic vision), are capable of color vision and are responsible for high spatial acuity.
What are Central Adaptations?
Central adaptation at the subconscious level further changes the amount of detail that arrives at the cerebral cortex.
-Along sensory pathways inside the CNS. Generally involves the inhibition of neurons along a sensory pathway. E.g. spinal cord, brainstem, but also sensory cortex.
-A gradual decrease in the neuronal response of the sensory system, over time in response to a constant stimulus (The CNS responds less after repeated stimulation)
-E.g. Somatosensory Evoked Potentials (SEPs) decrease during sensory adaptation.
Why does Central Adaptation occur?
- Sharpening/priming: enhancing discrimination. Exposure to a complex stimulus can increase the ability to discriminate its features over time, despite decreased neural responses (https://www.ncbi.nlm.nih.gov/pubmed/3227656/)
- Maintaining perceptual constancy: invariant percepts despite varying contexts. E.g. “colour constancy”
- Highlighting novelty: (https://www.ncbi.nlm.nih.gov/pubmed/12612632/)
-Detecting and responding to novel events is crucial for survival in a rapidly changing environment
-Frees up our attention and resources to attend to other stimuli in the environment around us
Efficient coding: e.g., predictive coding, so that neural resources are not wasted on the expected properties of the stimulus and can instead be devoted to signalling only the unexpected (https://www.ncbi.nlm.nih.gov/pubmed/17714934/)
Colour constancy: Color constancy can be linked to chromatic adaptation, wherein the visual system adjusts its sensitivity to a light according to the context in which the light appears. https://www.ncbi.nlm.nih.gov/pubmed/20849875/
-Predictive coding is a mechanism that can account for many of these phenomena
What is Predictive Coding?
-Predictive coding is the dominant theory of CNS sensory encoding.
-CNS processing is bi-directional.
-Descending information codes for predictions about sensory inputs.
-Ascending information codes for prediction errors, i.e. the discrepancy between predictions and actual input.
-This allows for more efficient sensory encoding in the CNS.
-Actions are also related to predictions (preceding sensory input) and prediction errors (after sensory input)
What was found in this paper? Analgesia for the Bayesian Brain: How Predictive Coding Offers Insights Into the Subjectivity of Pain | Current Pain and Headache Reports (springer.com)
The hierarchical principle of predictive coding applied to the pain pathway:
-At each level, predictions about the world are formed and sent to the level below (red arrows), where they are compared to the incoming information (green arrows).
-A prediction error is calculated and sent back to the level above, where the prior is updated according to the new information.
-Actions of varying voluntary control can arise at each level of the hierarchy, from primitive reflexes to reflected reactions.
-(ANS, autonomous nervous system; RF, reticular formation; PAG, periaqueductal gray; RVM, rostral ventromedial medulla; INS, insular cortex; ACC, anterior cingulate cortex; PFC, prefrontal cortex; S1, primary somatosensory cortex; S2, secondary somatosensory cortex; AMG, amygdala; Th, thalamus; HPC, hippocampus)
How does Predictive Coding act as a compression tool for efficiency?
Linear predictive coding (LPC) used since 1950s for compression of audio speech patterns for efficient transmission at low bit rate.
-Key point is that it improves efficiency in information transfer. Used in MPEG, FLAC.
How does Predictive Coding act as a general mechanism of perception?
-Proposed by Rao and Ballard (1999) – efficiency is important for the brain to minimise energy expenditure (already 20% of body total).
-Accounts for some properties of extraclassical receptive fields in the dorsal visual stream, e.g. sharpening
-Rao and Ballard: When exposed to natural images, a hierarchical network of model neurons implementing a PC model developed simple-cell-like receptive fields. A subset of neurons responsible for carrying the residual errors showed end-stopping and other extra-classical receptive-field effects.
-Certain neurons maintain sensitivity to a stimulus (if they are in the middle of the receptive field) whereas neighbouring neurons become less sensitive. This increases contrast in the brain – increases perceptual sensitivity.
Reference: https://www.nature.com/articles/s41593-018-0200-7
What is Complex Regional Pain Syndrome? (Brown et al., 2020)
-CRPS has variable signs and symptoms.
-Pathophysiology is complex and maybe variable between patients.
-A range of biomarkers are needed to support patient stratification and improve diagnostic certainty
-Complex regional pain syndrome (CRPS) is a chronic pain condition that can occur following injury or trauma (triggered by fracture or surgery in ~80% of cases), most often affecting one of the limbs.
-It is characterized by disproportionate pain (in magnitude or duration) compared to the typical course of pain after similar tissue trauma.
-Despite recent efforts to tighten diagnostic criteria for research purposes, CRPS remains a diagnosis of exclusion. This, and the ensuing heterogeneity in signs and symptoms, means that the diagnosis of CRPS is often delayed.
-As under-recognition of CRPS in the acute phase is likely to be associated poorer long-term outcomes, there is a clear need to identify markers of CRPS pathology (Turner-Stokes and Goebel, 2011).
What are some Neuropsychological markers of CRPS?
-Increased 2-point discrimination threshold
Digit identification (from touch):
-48% CRPS patients impaired for accuracy (Förderreuther et al., Pain 2004)
-85% CRPS patients impaired for either accuracy or response time (Kuttikat et al., 2017)
-Changes in limb representation have been studies in a number of ways.
-The first class of assessments are neuropsychological, based on behaviour in response to tasks that require functions of the somatosensory system.
-Of course, they don’t just require somatosensory functions, but also executive function, motor function.
What was Brown et al’s (2020) hypothesis?
-Theory: Problems with spatio-temporal integration (e.g. adaptation) contribute to pain in CRPS. How?
Possibilities (competing hypotheses):
-Deficit in bottom-up adaptation? Would increase the overall response, e.g. to spatially repetitive stimuli over time.
-Deficit in top-down adaptation – e.g. learning of predictions? Would increase responses to spatially rare stimuli over time.
-Hypothesis is that CRPS patients might not be able to integrate somatosensory information over space/time. In other words, a problem with forming accurate predictions and/or updating those predictions efficiently as part of a predictive coding scheme.
What was Brown et al’s methods?
A. We fitted participants with digit ring electrodes – one pair on each finger, which delivered non-painful electrical stimulation.
B. An example stimulus sequence is as follows: stimulation might start on D4 and then unexpectedly change to D3. These unexpected changes are known as oddballs, and are what produce larger brain responses.
C. Stimulation occurs in blocks, which differed according to two factors: (1) Change distance. Changes either occurred between D3/D4 (violet) or over a larger distance D2/D5 (red). (2) Change probability, meaning the changes could occur rarely (10%) more frequently (30%), or very frequently (50%).
D. There were multiple blocks of these different conditions that were all randomised together, so that the participant has to keep on learning what these probabilities are during the experiment.
E. After each digit change, the participant responded with a foot pedal release. We were interested in modelling the RT data.
The main thing to take away from this is that there were changes in stimulus location, the changes were unpredictable, and the unpredictability (probability of change) randomly changed during the experiment.
What is the predictive coding model simplified?
-The brain tries to predict sensory inputs; must therefore contain representations of input probabilities
-Larger “mismatch” responses are thought to be prediction errors
-Greater uncertainty in prediction increases the certainty (precision) of prediction error
-We aimed to identify what computations the brain is making to produce these larger responses in patients with CRPS.
-We did this using a predictive coding framework. This is a theory of brain function in which the brain is thought to try to predict sensory inputs. To do that, the brain must contain representation of how likely it is that a stimulus will occur. According to this theory, these larger brain responses we see when events are surprising are basically prediction errors, which is just the discrepancy between the prediction and the sensory input – that PE is then fed back to update predictions.
What are the Overall Conclusions?
-Larger “prediction error”-like signals in patients with CRPS
-Results are consistent with inefficient predictive coding in these patients
-Suggests deficit in top-down central neuronal adaptation, not bottom-up adaptation
Further studies:
-Relevance to the neuropsychological profile of patients with chronic pain?
-Can sensory discrimination training resolve these errors?
