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Chapter 4: Local integration 2: Neural correlates of the BOLD signal.

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Presentation on theme: "Chapter 4: Local integration 2: Neural correlates of the BOLD signal."— Presentation transcript:

1 Chapter 4: Local integration 2: Neural correlates of the BOLD signal

2 Cognitive Science  José Luis Bermúdez / Cambridge University Press 2010 Overview Introduce some of the basic principles of fMRI Explain how fMRI throws up a local integration challenge Survey some influential recent experiments on the neural correlates of the BOLD signal

3 Cognitive Science  José Luis Bermúdez / Cambridge University Press 2010

4 Cognitive Science  José Luis Bermúdez / Cambridge University Press 2010 PET PET measures cerebral blood flow by tracking the flow of water labeled with a radioactive isotope Basic assumption – local blood flow within the brain is related to cognitive function Cognitive activity  increased cellular activity  increased blood flow The correlation between cognitive function and blood flow has been well documented since 19th century

5 Cognitive Science  José Luis Bermúdez / Cambridge University Press 2010

6 Cognitive Science  José Luis Bermúdez / Cambridge University Press 2010 Blood flow and fMRI fMRI measures levels of blood oxygenation, not blood flow deoxygenated hemoglobin disrupts magnetic fields, while oxygenated hemoglobin does not Levels of blood oxygenation provide an indirect measure of blood flow oxygen consumption is not proportional to blood supply (unlike glucose)

7 Cognitive Science  José Luis Bermúdez / Cambridge University Press 2010 Blood flow and fMRI Cognitive activitycorrelated with Increased cellular activitycorrelated with Increase blood oxygen levels [because supply exceeds demand] BOLD contrast is the contrast between oxygenated and deoxygenated blood

8 Cognitive Science  José Luis Bermúdez / Cambridge University Press 2010 Integration? How do we move from coarse-grained correlations between blood flow and cognitive activity to an understanding of how cognitive activity takes place We want to know not just where cognitive activity is happening, but how it is happening Requires calibrating imaging data with data about neural activity

9 Cognitive Science  José Luis Bermúdez / Cambridge University Press 2010 Problem of levels Neuroimaging allows us to identify which brain areas are active when subjects perform particular tasks But there is a difference between Localizing cognitive activity Explaining or modeling cognitive activity

10 Cognitive Science  José Luis Bermúdez / Cambridge University Press 2010 Bridging to the neural level Brain areas anatomically/functionally identifiable Neural networks/populations standardly studied through computational models – behavior of populations of artificial neurons Individual neurons/small groups of neurons can be studied through single/multi unit recordings

11 Cognitive Science  José Luis Bermúdez / Cambridge University Press 2010 Integration question What is the neural activity that generates the BOLD contrast? necessary first step in building neural network models requires building bridges between different levels of organization and different technologies/tools

12 Cognitive Science  José Luis Bermúdez / Cambridge University Press 2010 Single unit recording Using microelectrodes to investigate – how neurons respond to sensory inputs – how neurons discharge when motor acts are performed Microelectrode recordings of interest to cognitive scientists are typically extracellular – intracellular recording very difficult in living animals

13 Cognitive Science  José Luis Bermúdez / Cambridge University Press 2010 Schematic neuron Dendrites transmit electrostimulation from other neurons If the combined effect of this stimulation exceeds a threshold, then the neuron generates an action potential This action potential is transmitted via the axon

14 Cognitive Science  José Luis Bermúdez / Cambridge University Press 2010 Single unit recording Monkey’s head held immobile Microelectrode tip (< 10  m) inserted near neuron can detect firing of a single neuron (action potential) high spatial and temporal resolution

15 Cognitive Science  José Luis Bermúdez / Cambridge University Press 2010 Mirror neurons Area F5 of macaque monkey (premotor cortex) contains visuomotor neurons Sensitive to different types of action (e.g. grasping vs tearing) Some fire both when the monkey performs an action and when the monkey observes the action being performed

16 Cognitive Science  José Luis Bermúdez / Cambridge University Press levels of organization Large-scale neural activity, revealed by fMRI ways of identifying specialization in neural areas, as a function of blood oxygen levels Fine-grained receptivity of individual neurons, as revealed in single-unit recordings The large-scale activity results from the collective activity of large numbers of individual neurons – but how?

17 Cognitive Science  José Luis Bermúdez / Cambridge University Press 2010 Neural correlate of BOLD signal Two possibilities BOLD signal is correlated with the firing rates of populations of neurons BOLD signal is correlated with the inputs to neurons [These are not equivalent, because neurons only fire when inputs reach a threshold]

18 Cognitive Science  José Luis Bermúdez / Cambridge University Press 2010 Rees, Friston, and Koch 2000 FMRI data on motion perception

19 Cognitive Science  José Luis Bermúdez / Cambridge University Press 2010 Calibrating with single-unit data (Rees et al. 2000) fMRI results show linear relationship between strength of BOLD signal in V5 and coherence of moving stimulus Likewise, single neurons in V5 of macaque cortex are linearly related with motion coherence in their preferred direction Authors propose linear relationship between strength of BOLD signal and average firing rates of neurons 9 spikes per second for each % of BOLD contrast

20 Cognitive Science  José Luis Bermúdez / Cambridge University Press 2010 Logothetis et al 2001 Logothetis and his team measured the strength of the BOLD signal in monkey primary visual cortex at the same time as using microelectrodes to measure 2 types of neural activity spiking activity of neurons near electrode tip local field potentials

21 Cognitive Science  José Luis Bermúdez / Cambridge University Press 2010 Local field potential (LFP) Electrophysiological signal representing synaptic activity at the dendrites Corresponds to input to the neuron (and integrative processing) Slow oscillatory wave

22 Cognitive Science  José Luis Bermúdez / Cambridge University Press 2010 Measuring LFP LFP can be measured using the same microelectrodes as measure spiking/firing activity Since LFP is a lower frequency signal it can be isolated through a low-pass filter The LFP recorded at a single microelectrode represents dendritic activity in neurons within a few mm of the electrode tip

23 Cognitive Science  José Luis Bermúdez / Cambridge University Press 2010 Logothetis et al Anaesthetized monkey presented with rotating checkerboard pattern Compared evolution of BOLD signal with LFP and spiking signals

24 Cognitive Science  José Luis Bermúdez / Cambridge University Press 2010

25 Cognitive Science  José Luis Bermúdez / Cambridge University Press 2010 Take home message Good news: Logothetis experiments show how to build a bridge between BOLD signal and activity of individual neurons/small populations of neurons Bad news: The neural correlates of the BOLD signal is not the dimension of neural activity most frequently measured in single neuron studies We don’t know much about the connection between LFP and cognition


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