Neural mechanisms of attention - week 6 (Chris) Flashcards
(17 cards)
Neuronal evidence for attentional competition in temporal cortex
Individual neurons in monkey temporal cortex show ‘preferences’ for particular stimuli
Chelazzi et al. (1993)
Monkeys made eye movements to a target
- Either a neuron’s preferred stimulus or non-preferred stimulus
The results suggest that the attentional template is formed by modulation of brain regions that process the relevant object – in this case enhanced neuronal firing in shape-selective cortex.
What does this evidence tell us about attention?
Attentional competition occurs at the level of individual neurons
Such competition involves both excitation (increased firing rate of neurons that ‘prefer’ a stimulus) and inhibition (suppression of firing rate of neurons that do not show such a ‘preference’)
Modulation of neuronal responses by attention occurs well before response occurs
Competition occurs not in a separate ‘attentional’ brain region but in the brain regions that process the visual features of relevant (and irrelevant) objects
The same neurons that process the visual features of an object (its shape, colour, orientation etc.) are co-opted by the attention system to resolve the competition for selection
Event Related Potential (ERP) Evidence for Attentional Modulation of Visual Cortical Signals
They used ERPs to show that when a target is validly cued, it leads to a greater response in early visual areas than invalidly cued targets. Note the very early response (P1 is less than 100 ms, N1 just over 100 ms) – this is before subjects make a response, supporting the idea this is an attentional effect rather than a motor response effect.
The results suggest that when a target appears, if a cue was previously presented pointing to that location, brain activation in early visual cortical areas is higher than when the cue pointed to the other location. It is almost as if early visual areas that process information in specific locations are ‘primed’ by the cue such that when the target occurs, the activation is higher if the cue and target location are congruent (the same).
Where do these attentional signal originate?
Source localization suggests P1 is generated in extrastriate cortex (outside primary visual cortex)
However, conclusions about the spatial source of EEG signals are limited due to the poor spatial resolution
Can fMRI reveal more accurate spatial information about the precise site of attentional modulation of neural signals?
fMRI evidence for attention effects on primary visual cortex (V1) activation
The researchers presented visual stimuli in different segments of a circle individually and used retinotopic mapping to examine which areas of visual cortex were sensitive to visual stimulation in different regions of space.
Subjects were cued to attend to a specific segment. Importantly, these cues were auditory – subjects learnt to associate numbers with segments
Subjects then had to judge the colour and orientation of lines in a specific segment of the array.
Effects occurred in V1 demonstrating that attention enhances processing in the earliest stages of visual processing during attentional cueing
fMRI Evidence for Attentional Modulation of Neuronal Signals in V4
Kastner et al. (1998)
Activation in V4 (colour sensitive visual cortex) was lower when items presented simultaneously than sequentially (due to attentional competition).
When attention was directed to an individual stimulus in the simultaneous condition this difference in activation disappeared.
These findings again demonstrate that attention modulates competitive interactions at the neuronal level in visual cortex (here in colour-selective V4).
O’Craven et al. (1999)
Subjects presented with overlapping pictures of faces and houses in the MRI scanner
The face or the house moved
Subjects attended to either the moving object or the static object
Activation in FFA and PPA depended on which stimulus was being attended to
e.g. In the FFA:
If attention was directed to the moving object, activation was higher when the face moved
If attention was directed to the static object, activation was higher when the face was static
A resolution to the early vs late selection debate
Nillie Lavie: Load Theory
On each trial your task is to either find the X or the N in the circle of letters in the middle of the screen while ignoring the distractor letter off to the side.
They varied two factors –
the perceptual load of the display, which was operationalised by having either a variety of distractors that shared features with the target (high load) or all the same distractors that shared no features with the target (low load)
The congruency of the distractor and target. The target and distractor could either be the same letter (congruent) or a different letter (incongruent).
They hypothesised that perceptual load might influence the effect of distractors on visual search performance – in particular that distractors would intrude more under low perceptual load than high perceptual load.
Distractor had a greater effect on reaction time in the low perceptual load condition.
High perceptual load
Perceptual capacity is used up by the task of trying to find the target - none left for the distractor!
Support for early selection
(think back to the monkey business illusion)
Low Perceptual Load
The main task does not use up all your perceptual capacity so there is some left to process the distractors.
Support for late selection.
Effect of perceptual load on visual cortex activation
Schwartz et al (2005)
Low load instructions:
Detect any red shape
High load instructions:
Detect a green inverted T or a yellow upright T
They found that visual cortex activation due to the checkerboard stimuli was much higher in the low load condition – the neurophysiological correlate of Nilli Lavie’s behavioural data. Essentially, in the high load condition subjects are so focused on the main task that they are able to filter out the irrelevant checkerboard but this filter doesn’t operate so well in the low load condition. Fascinatingly these effects were observed at the earliest level of visual processing.
Biased Competition Model of Attention
Many brain areas are activated by visual input, and within most of these systems activations for different objects compete.
However, these may be merely the result of attentional signals arriving from elsewhere - What is the source of such attentional biasing signals?
fMRI studies suggest that the source of attentional signals may be frontoparietal cortex
Hopfinger et al. (2000)
In an fMRI study, Hopfinger et al tested this possibility. They presented subjects with a directional cue and asked them to make a judgment on checkerboards (are there any grey checks?) but only when they appeared in the cued location.
Now instead of looking at target locked activation they looked at cue-locked activation.
They found extensive activation across frontal and parietal cortex time locked to the cue. Thus, these regions were activated it seemed in preparation for the upcoming target stimulus
Taylor et al., 2006
This study provided evidence for a causal role of prefrontal cortex activation on attentional signals in visual cortex.
The subjects performed a Posner cueing task in which a central cue pointed left or right and a target then appeared on the left or right. The researchers used TMS to stimulate the frontal eye fields between the cue and target.
These findings suggest that attentional selection may involve long-distance interactions between prefrontal cortex and visual cortex
The 5 frequency bands of EEG signals
Neuronal signals oscillate at particular frequencies
Different frequencies might correspond to different functions
Frequency synchronisation between brain regions might support selective attention
Buschman & Miller (2007)
In this study the researchers got monkeys to perform a visual search task involving either popout (easy) or conjunction search (difficult).
They examined the extent to which regions in the parietal (LIP) and prefrontal cortex oscillated at the same frequency, shown here by the measure of coherence.
They found that coherence was higher in the middle frequency band during conjunction search but coherence was higher in the upper frequency band during popout search.
Synchronisation between parietal and prefrontal regions higher in middle frequency (beta band) during conjunction search
Synchronisation between parietal and prefrontal regions higher in upper frequency (gamma band) during pop-out
