Behavioural Neuroscience Flashcards
Action potentials
- electrical signal that occurs when neurons are excited
- -A very rapid reversal (depolarisation) of the membrane potential of an axon is called an action potential.
- occur due to opening of voltage gated ion channels
Changes in air pressure from sound waves
We hear sounds when objects vibrate, which in turn causes air molecules to compress and rarefy (become more dispersed) leading to waves that travel away from the object at around 1,100 km/h.
-as it move away, the air pressured is reduced, we then receive these signal
Physical and perceptual dimensions
of sound waves
amplitude(intensity) of sound wave affect loudness (how tall it is)
frequency of a sound wave pitch (how many oscillations)
Accumulation of amplitude and frequency affect the timber (simple or compolex)
Middle ears
-Middle ear: consists of three tiny bones called ossicles. The malleus (hammer) is connected to the tympanic membrane. It transmits vibrations via the incus (anvil) to the stapes (stirrup), which is connected to a structure called the cochlea (snail), which is part of the inner ear.
Inner ears
-Inner ear: consists of the cochlea, which contains the receptors for analysing sounds. The cochlea is a bony structure, but it has two small membranes that form windows on its fluid-filled interior. The stapes is connected to the oval window. Sound waves that cause the stapes to move in and out move the fluid over receptors inside the cochlea. Because the cochlea is a closed structure, another membrane is needed to allow the fluid to move: this membrane is called the round window.
The cochlea
contains the basilar membrane runs along the length of the cochlear
The cochlea converts mechanical movement of the ossicles into fluid movement along the basilar membrane
Movement of stirrup against the oval window
The round window deforms to allow the movement
Transduction of auditory information in hair cells
cillia are linked toghter by tip link
these tip link also control K and Ca ion channels
-bend tot he left ( no signal, to the right 100% signal)
Spiral ganglion cells and the auditory nerve
- When the stereocilia are moved ion channels are opened which in turn cause receptor potentials in the hair cells. The hair cells secrete a neurotransmitter that triggers action potentials in neurons called spiral ganglion cells. The axons of many thousands of spiral ganglion cells are grouped together to form the auditory nerve
- The axons of auditory nerve neurons form synapses with neurons in the medulla (part of the brainstem), which in turn send their axons to other parts of the brain for further processing
Place coding of frequency
along the basilar membrane
- higher frequencies produce greater displacements of the basilar membrane toward its basal end, and lower frequencies produce more displacement at its apex
- Different frequencies of sound are therefore coded by the particular spiral ganglion cells that are active along the basilar membrane, and this information is transmitted via the auditory nerve to the brainstem and other parts of the brain
Characteristic frequency of
hair cells
- a hair cell have a specific frequency that it respond to
Pathway to auditory cortex
Auditory nerve-> Conclear Nuclei ->Superior olivary nucleus -> Inferior Conclius -> Medial geniculate nucleus -> Auditory Cortex
Tonotopic organisation of primary auditory cortex
The primary auditory cortex is located in a region of the temporal lobe called the superior temporal gyrus . Much of this cortical region is buried inside the deep fold of the lateral fissure, and is therefore not visible from a lateral view of the brain.
Just as the basilar membrane represents different frequencies along its length, so the primary auditory cortex is organised as a tonotopic map, with lower frequencies represented more anteriorly and higher frequencies more posteriorly.
Cochlear implants – based on knowledge of place coding
- Some people are deaf because of damage to hair cells
- electrodes inserted along the basilar membrane
- Stimulation causes spiral ganglion cells to generate actionpotentials
Cochlear implant challenges
- a large number of electrodes to reproduce sound well
- fast sound processors required to determine how much of each frequency is in the sound
- Especially with a large number of electrodes
- Not optimised for music
- Our brain loses the capacity to make sense of novel input as we age
Experience of someone with a
cochlear implant
- Helen lost her hearing at 2 from meningitis
- one of the first people to receive a cochlear implant
- Still has difficulty after successful implant
- Keep in mind the technology has improved
- people able to perceive sound more accurately
- some children learn to sing in tune and can acquire local accents
Extracellular microelectrode
recording
Normally, neural tissue is transparent, but if we inject dye into the cell bodies, we can actually see the cell bodies of these neurons and the processes the dendrites and axons.
we can see also in this microscope image. There’s a fine wire that’s been lowered close to one of these neurons, and this electrode, when it’s hooked up to an amplifier, can actually pick up small electrical changes.
They are associated with the activity in these individual neurons. And on the basis of this technique, it’s possible to understand how neurons at different stages of processing are transforming the signals that originate in the ear and that eventually how those signals will enable us to understand sounds in the world around us.
The electromagnetic spectrum
Our eyes detect the presence and pattern of light reflected off objects in the world. We are sensitive to a very narrow range of wavelengths in the electromagnetic spectrum, known as the visible spectrum. The visible spectrum extends from 380 nm to 760 nm.
Our ability to see these particular wavelengths depends on the fact that this wavelength of energy interacts with structures.
The photoreceptors in our eyes and enables enables them to convert those wavelengths into a neural signal.
-Its the brain that make us see color
The human eye
- Inside the skull the eye is held by a muscle know as extra ocular muscles. also help with pointing the eye to different direction (allow focus of attention)
- light from object will come through the cornea and the lens, and passing through the vitreous centre part of the eye. all of which are transparent
- the back of the eye is a sturcture called retina where photoreceptor (cell that convert light to neural signal) exist
The retina and fovea
- region of highly packed photoreceptor are called fovea, image have highest resolution
- light from lower visual will be process by upper retina and vice versa
- there is a region where ganglion of neuron bundle up to connect the eye with the brain, this region is the blind spot and there is no picture here
Cells of the retina
- Light must pass through ganglion cell and bipolar cell before reaching photoreceptor (all are relatively transparent)
- in photoreceptors, and then it’s converted into neural signal. The signals from these photoreceptors then go through bipolar cells out to gangling cells.
- lateral cell, horizontal cell (make multiple connection with photoreceptor) and amacrine cell (make multiple connection with the ganglion cell) exist in the bipolar layer which allow signal procession.
Transduction of light into
electrical signals in the retina
- stimulus cause the photo pigment lamellae of the receptor cell to become hyperpolarise (more negative) which cause the bipolar cell to depolarise
- enough depolarisation of bipolar cell lead to action potential to be generated by the ganglion cell toward the brain
Three cone types with different spectral sensitivities
there are three types of cones, each containing a photopigment that is sensitive to a different range of wavelengths within the visible spectrum.
1) Short-wavelength (S) cones – peak sensitivity at 440 nm (blue light)
2) Medium-wavelength (M) cones – peak sensitivity at 530 nm (green light)
3) Long - wavelength (L) cones – peak sensitivity at 560 nm (red light)
rod cell 496nm activate at dim light
Ishihara colour plates test for colour deficiencies (blindness)
• Deuteranopia • the green cones are absent • Protanopia • the red cones are absent 1 out of 12 men and 1 out of 200 female are red-green colour blind
Cone combination in the fovea
and periphery
in the central part of the of our vision, where we have most sensitivity, we actually have a closer coupling between the number of photo receptors and the number of ganglion cells.
As we move further away from the phobia, we find that we have a lower density of photoreceptors. But we also have more than one photo receptor, ultimately contributing to a single ganglion cells.
-leading to diference in spacial resolution
Interactions in the retina (retinotopic)
- Each ganglion cell responds to light stimulation of a small region on the retina
- Which comes from a specific location in the world
- Retinotopic As opposed totonotopic
Visual pathways to the brain
After leaving the eye the axons of retinal ganglion cells are bundled together to form the optic nerves(one for each eye).
These project posteriorly and medially toward the optic chiasm. Here, roughly half
the axons from the retina of each eye cross over to the opposite side of the brain. Axons from the temporal half of the retina of the right eye remain on the same side, but axons from the nasal half cross over to the left hemisphere adn vice vers
The Retinogeniculate Pathway
- The Lateral Geniculate Nucleus (LGN) contains six layers of neurons
- The inner two are magnocellular layers (info about fast moving object)
- The outer four are parvocellular layers(color)
- The koniocellular sublayers are found below each of the magnocellular and parvocellular layers involve in color peception
- Projects to Primary Visual Cortex in the Occipital lobe
- Associated with “conscious” perception
- A relay station?
- There are more fibres providing feedback to the LGN, than input from the retina may indicate more fuction
Centre surround receptive field
structure in the LGN
- Receptive fields of LGN neurons have a centresurround organisation
- ON centre – OFF surround
- OFF centre – ON surround
- Each LGN neuron responds to light stimulation of a small location in the real world
- Retinotopic
- We can record action potentials from neurons in the LGN
The Retinohypothalamic Pathway
- signal recing the Primary visual cortex signals are then going to be processed in the other visual areas at the back of our brain
- it’s those processes that give rise to our conscious visual perception
- here’s a type of ganglion cells in the retina that is intrinsically photosensitive. They have melanopsin which can covert light to a neural signal
Visual input pathway to the Primary Visual Cortex
- The conscious visual pathway involves retinal projections to LGN, and form there to the Primary Visual Cortex.
- The primary visual cortex (also known as visual area 1, or V1) is the first cortical region to receive axons from visual cells in the lateral geniculate nucleus.
- Area V1 in each hemisphere contains a retinotopic map of the contralateral half of the visual field.
Loss of conscious visual experience after a
unilateral lesion of primary visual cortex
- Damage to area V1 can occur after a stroke affecting one of the major arteries at the back of the brain, the posterior cerebral artery. Following rupture or occlusion, the neurons supplied by the posterior
- cerebral artery are starved of oxygen and glucose, and so are irreversibly damaged. If area V1 is affected, the patient will become blind to all visual stimuli arising to the contralateral side of their present point of fixation, e.g., damage to V1 in the right hemisphere will cause blindness in the left visual field. This disorder is called a hemianopia (loss of vision for one side).
- Patients with a hemianopia are normally aware of their visual loss and will take active steps to compensate for the problem
Retinotpic organisation of primary visual cortex
V1 has a very well-defined map (the retinotopic map) of the spatial information in vision. In humans, the upper bank of the calcarine sulcus in the occipital lobe has neural responses to light stimulation in lower half of visual field (below the line of sight), and the lower bank of the calcarine to the upper half of visual field.
Functional organisation of
primary visual cortex
-The striate cortex has a locally organized structure based on layers and modules.
Layers
-It contains neurons in 6 layers that receive input from the different LGN cell types and regions that process those inputs in other layers before sending signals to other visual areas.
. -Koniocellular input is received by sublayers 2 and 3 in the striate cortex, magnocellular input is received by sublayer 4C α , and parvocellular input is received by sublayer 4C β.
Modules
-The visual cortex is organized into roughly 2,500 modules containing approximately 150,000 neurons that analyses features contained in one very small portion of the visual field. The modules cover the entire visual field (like the tiles in a mosaic)
-The modules consist cells clustered according to colour and form. Most neurons located within the Cytochrome oxidase (CO) blobs receive input from one eye and are sensitive to colour. Neurons outside the CO blob (the interblob regions) are more sensitive to orientation, movement, and binocular disparity (depth), but typically do not respond to colour. This segregation for form and colour is partially maintained in the signals to other visual areas.
Specialized visual areas that receive input via the primary visual cortex
The primary visual cortex is divided into several functional modules or subregions, each of which contains neurons that have specialised properties for extracting specific information from the visual input.
1) Primary visual cortex (also known as the first visual area, or V1)
2) Area V4, which has neurons that are sensitive to the colour of visual inputs
3) Area MT, which is responsive to moving visual stimuli
4) Inferior temporal cortex, which contains neurons that are selectively responsive to complex objects and faces
The two-streams hypothesis of visual processing in the brain
- Proposed by Milner & Goodale (1992)
- Dorsal stream & ventral stream
- The ventral stream computes a detailed map of the world from visual input
- The dorsal ‘action’ stream transforms incoming visual information for action
- Also referred to as the “what and where” pathway
- Although the dorsal/ventral stream is more concerned with perception vs action
- The independence of the two streams has been overemphasised
- a large amount of crosstalk
Ventral stream functional modules
- Functions related to objects and visual recognition
- V3+VP - Further analysis of information from V2
- V3A - Processing information from contralateral eye
- V4 - Analysis of form; processing of colour constancy;
- V8 - Lateral occipital complex Colour perception
- LO - Object recognition
- FFA (Fusiform face area) - Face recognition, object recognition by experts
- PPA (Parahippocampal place area) - Recognition of particular places
- EBA (Extrastriate body area) - Perception of body parts
Dorsal stream functional modules
- Functions related to location and action
- V7 - visual attention; control of eye movements
- MT/MST (Medial temporal/medial superior temporal) - perception of motion; perception of biological motion and optic flow in specific subregions
- LIP (Lateral intraparietal area) - visual attention; control of saccadic eye movements
- VIP (Ventral intraparietal area) - control of visual attention to particular locations; control of eye movements; visual control of pointing
- AIP (Anterior intraparietal area) - visual control of hand movements: grasping, manipulation
- MIP (Middle intraparietal area) - visual control of reaching
- CIP (Caudal intraparietal area) - perception of depth from stereopsis
Colour processing pathway
Colour processing begins in the retina.
Some ganglion cells have selective inputs from the L, M & S cones.
This gives some ganglion cells cone opponency in the form of R-G, and Y-B.
These ganglion cells go on to form the Parvocellular stream (R-G) and Koniocellular (Y-B) streams in the LGN.
These signals are NOT the perceptual dimensions of colour.
• The contributions to to the centre and surround are selective for cone type
Damage to color preception
- Extracellular recordings in monkeys
- CO Blobs in V1 (and regions in V2 that they project to) and Area V4 is highly responsive to colour
- Subseqeunt work has shown that V4 is also responsive to changes in shape & curvature
- Damage to corresponding region in human cortex causes colour blindness Achromatopisa
- selective loss of colour perception but Form and brightness unaffected
- Damage to one hemisphere results in achromatopsia in contralateral visual field
- Likely to be rare because common causes of brain damage are likely to involve visuals areas other than V4
Orientation mapping in cat visual cortex by Hubel and Weisel
- Video footage of orientation selectivity in cat visual cortex
- from Hubel and Weisel’s lab in the
- Major breakthough in our understanding of what the visual parts of the brain do
- Nobel Prize discoveries
Motion processing pathway at lower level (what stimuli do they respond to)
• Retinal ganglion cells and LGN neurons respond to moving stimuli
BUT
• stimulus could be moving in any direction
• stimulus could even just be turning off and on
• Although Magnocellular neurons are particularly responsive to motion…
• Cells in V1 are orientation selective
• Respond to moving bars or edges with specific orientation (but movement in either direction)
• Some only respond to edges or bars moving in one direction
• Still not good enough to account for perception of motion
MT neurones influence the perception of movement
Area V5 of the extrastriate cortex (also known as area MT, for medial temporal-temporal) contains neurons that respond to movement. Damage to this region severely disrupts a monkey’s ability to perceive moving stimuli
Visual neurons that are sensitive to visual motion may gradually adapt when exposed to a continuously moving stimulus, so that when the motion ceases a motion aftereffect occurs (as in the classic waterfall illusion). The effect does not occur due to adaptation of cells in the retina, since adapting one eye to the moving stimulus and then using the other eye to view a stationary surface still yields a motion aftereffect.
MST role integrates local motion
- The medial-superior-temporal(MST) area in the monkey has neurones that are sensitive to optic flow e.g. movement of the world cause by self motion. responsive to complex movement e.g. spiral motion. associated with the perception of biological motion (structure from motion)
- global integration of local movement consistent with a person or animal
- Analogous brain regions in humans
- We can decode age and gender from the dots!
Motion blindness (akinetopsia)
- Caused by bilateral damage to MT
- Rare due to small size and location of MT
- Case of LM
- sees the world is snapshots
- Unable to judge speed and therefore predict future position of moving objects
- Over filled tea cups
- Danger crossing the road
- BUT could see biological motion
- so MT is not involved in perceiving structure from motion
How can the brain build a neuron that responds to an object in the visual field (talk about shape n stuff)?
- A key aspect of our conscious experience is recognising familiar objects around us
- Primates (and other animals) rely on visual recognition to survive
- either by finding food or avoiding danger (being food)
- Scenes consist of light patterns with features that can be identified at lower levels of visual processing
- Bars & edges
- LGN & V1
- But what happens at the next level?
Integration of visual dimensions into a coherent percept of an object
- Lower levels of visual processing involves separate modules (if not streams) that extract information about different dimensions
- The middle levels of visual processing begin recombine this information
- Higher levels of visual processing need to make sense of this information in a way that is independent of the viewpoint
- A familiar chair is recognized as the same chair from different angles
Marr’s approach to
understanding recognition
Marr’s Computational Theory considers object recognition from different perspectives
The computational theory
Find the contours that reflect the structure of objects ：edges lines curves
The algorithm
Look for changes in the retinal image - edges
Look for changes that form a straight line
Look for lines that form a curve
The implementation
Some physiological evidence (especially the early stages)
Edges - LGN
Lines – V1
Curves - V4
Edge detection
Centre surround receptive fields of ganglion cells in the retina are well suited to detect a change in light that could be a spot, a bar, or an edge
LGN cells have the same circular centre surround receptive field structure also
Orientation coding
- V1 simple cells can be formed by combining the outputs of LGN neurons that have are connected to retinal ganglion cells with receptive fields at different locations on the retina.
- If those receptive fields are in a horizontal line, then the V1 neuron will be tuned to horizontal bars and edges.
- If those receptive fields are in a vertical line, then the V1 neuron will be tuned to vertical bars and edges.
- V1 receptive fields are tuned to the full range of possible orientations at each retinotopic location.
- Thus the population of V1 cells can be used to detect all the edges in the visual scene.
Curvature and shape
detection in V4
- In a hierarchical model, we can make curvature detectors using a similar principle to the one that created orientation selectivity in V1.
- Curvature detectors can be formed by combining the outputs of V1 neurons that with receptive fields at different locations on the retina and slightly different orientation preferences.
- If those receptive fields are oriented to match a particular curved line, then the neuron will be tuned to curved lines and shapes with that same profile.
- V4 receptive fields are tuned to a range of curves and shapes at each retinotopic location. Thus the population of V4 cells can be used to detect all the edges in the visual scene.
Object recognition in the
Inferior Temporal cortex
- Inferior Temporal (IT) cortex is along the ventral path of the two visual streams model
- Because of its role in object recognition the ventral stream is also known as the “What” pathway
Visual object recognition occurs in the inferior temporal cortex
- Synthesis of form, colour and depth
- poor response to simple stimuli such as spots or lines
- Large receptive fields
- Robust response even when;
- object moves within the receptive field
- object changes in size
- Responses may not be strictly viewpoint dependent
- unlike V4
- The response to specific complex objects requires learning and memory
- And therefore likely involves connections with other brain regions involved in memory and learning
Objects are not recognized solely on the basis of visual information
Object representation involves integration of visual features extracted at earlier stages in the visual pathways. Ideally the resulting representation is a generalization of the numerous retinal images generated by the same object and of different members of an object category
The representation also incorporates information from other sensory modalities, attaches emotional valence, and associates the object with the memory of other objects or events. Object representations can be stored in working memory and recalled in association with other memories.
Visual object agnosia
- Agnosia (“failure to know”)
- Damage to the inferior part of the temporal cortex
- Loss of the ability to recognise familiar objects
- but only through the modality of vision
- IT is active when humans look at objects
- as opposed to scrambled images
- Difficulties depend on extent of lesion
- Consistent with the possibility of multiple modules within IT
Variation in clinical cases of visual agnosia
Mrs R. had a stroke that caused damage to the ventral stream of her extrastriate cortex
• Can’t recognise a magazine, but can read
• Can’t recognise faces – prosopagnosia
• Patient JS had a stroke that caused extensive damage to the ventral stream
• unable to recognize objects or faces
• could no longer read
• could not recognize shapes or orientations of objects
• But could shake hands
Clinical evidence for distinct systems of visual agnosia
- Farah (1990) reviewed a large number of agnosia studies
- Argued for two types
- structural mechanisms (based on identifying features)
- holistic mechanisms (based on identifying configurations)
- This is consistent with separate modules for faces and other familiar objects
Are faces processed separately from other objects?
There are some simple illustrations of how face processing might be different from the processing of other object classes. For instance, people are readily able to learn to recognise pictures of faces they have never seen before, but they have difficulty learning to recognise pictures of faces when they are turned upside-down. By contrast, learning to recognise pictures of other objects (e.g., houses) is not much different whether they are shown upright or upside-down. This is called the face inversion effect.
Another example of how face processing is special comes from the Thatcher Illusion. We fail to notice even quite striking visual anomalies when a face is shown upside-down.
It has been suggested that the brain has specialised visual areas devoted to processing the subtle differences in configuration of the eyes, eyebrows, mouth, nose, chin and so on – all the features that go together to make a particular face unique. When a face is inverted these processes can no longer operate because the configuration between parts is altered
Response of individual “face” neurons in non human primates
- From Desimone et al. (1984.)
- A. The location in the inferior temporal cortex of the monkey where neurons were recorded
- B. Neuronal response of face selective neuron to the different images illustrated below
- Masking of critical features, such as the mouth or eyes led to a substantial but not complete reduction in response
- Scrambling the parts of the face eliminates the response
Response of “face” neurons to non face stimuli
Primate face cells in IT • Kobatake & Tanaka (1994) • Extracellular single-cell recordings • “Face” and non-face stimuli • Cells respond most to an intact “face” • Cells are not responsive to individual features presented in isolation • Holistic processing? • Contrast is important • Recall how contrast effects face perception...
Face selectivity fMRI “face” regions of macaque
Tsao et al. (2006)
• 96 images of faces, bodies, fruits, technological gadgets, hands, and grid scrambled patterns
• Identified “face” selective areas using fMRI
• Recorded from 500 single cells in the “face” area
• Single cell responses to same stimuli used for fMRI
• 97% of visually responsive cells responded more to faces
• Most cells responded only to faces…Face responses > scrambled image
Consistent evidence of face-selective responses
- Tsao et al. 2006 (from Tsao & Livingstone; 2008)
- Robust responses to all faces
- Responses to non face stimuli that have face-like features
Adjacent subregions of distinct object recognition modules
Bell et al., (2009) found that in both the human and the monkey brain, regions that responded to faces and body parts were adjacent to each other, as were those
that responded to objects and scenes of places.
Face blindness case (prosopagnosia)
- Uttner et al. (2002)
- 85 year-old man
- Unable to recognise famous faces, his wife’s face or his own face
- Recognition of other visual objects normal
scotoma
-Cause by, a small unilateral lesion of V1
a small patch of blindness in one hemifield
homonymous hemianopia
unilateral destruction of V1 in its entirety will cause blindness in the whole of the contralateral visual field
Blind sight
- Occurs following unilateral damage restricted to the primary visual cortex
- Above-chance visual performance in the‘blind hemifield
- Patient may show preservation of:
• pupillary reflexes
• manual and saccadic localisation ( eye movement)
• wavelength & motion discrimination (pointing)
• orientation & shape discrimination
inventigated via Neuropsychological studies by Weiskrantz
Using perimetry to identify where vision is based on blindsight
Patient DB -right occipital lesion
- patient are ask to identify when the light is lit (there is two choice)
- at blind spot the correct is equal to chance
- at other area of blind region, higer than chance
Manual pointing in blindsight
patient GY
- the patient is ask to point where the light is coming from in the blind sight
- relatively accurate
How does visual information support unconscious perception in blindsight?
- 90% of the neuron will travel to LGN after passing the optical chasm But 10% of retinal axons bypass the LGN altogether, and project instead to the superior colliculus (SC; part of the midbrain) and pulvinar nucleus of the thalamus and then to other region (Unclear how important those connections are in everyday vision)
- This is an older evolutionary optical pathway still used by some animal
Change blindness: Attention regulates our conscious visual awareness
required to find the small differences between two nearly identical images. During
the switch from one image to another, a number of small patterns appears briefly. These masking patterns (called noise masks) do not directly cover any of the changes between the two scenes.
However, they constitute a dramatic change in your environment and are very effective at capturing attention, thus making it less likely that your attention will be grabbed by the weaker transient visual signals associated with the changed objects themselves.
-unable to detect change
how much of the real world are you consciously aware of?
- Evidence of blindsight shows we can process visual information without conscious awareness.
- It also provides a good reason to ask how much of the activity in visual cortex is associated with a conscious experience
• Perceptual demonstrations show that attention limits our awareness in real world scenarios
• Change blindness
• Inattentional blindness
So why are we aware of only a small part of our visual world
-Neural limitations (Bottleneck of the optic nerve)
- Metabolic limitations( Neural activity consumes a lot of energy and requires a lot of blood oxygenation)
• Computational efficiency( assign the most neural machinery to processing important objects)
• Computational complexity Awareness integrates experience (and learning & memory)
• Conscious decision making
Different aspect of attnetion
- selectivity (spatial, temporal, motoric)
- capacity limitation
- vigilance (‘sustained attention’)
- perceptual set (‘expectation’)
- switching
How is attention view in psy
- attention is usually treated as a unitary phenomenon (involve both long and short term memory)
- attention-related signals in the visual system might not convey the same information
- attention can be defined in one of two ways;
- by showing enhanced sensitivity at an attended location
- by measuring reaction times to visual events
Covert selective attention reveals prioritising by the brain
• Hermann von Helmholtz (1821-1894) - studied the effects of covert allocation of attention on visual perception
-Helmholtz made a large screen in which letters were positioned at various distances from the centre. He then hung the screen on a wall of his laboratory, and excluded all light so that the entire lab was in complete darkness. –Helmholtz then used a machine to create an electrical
spark, which briefly illuminated the screen, much like a camera flash. Although there were far too many letters to see at any given moment in time, Helmholtz found that by keeping his
eyes fixed on the centre of the screen he could pay attention to a selected region in advance
-He found that he was able to discriminate all the letters within the attended region, but was unable to do so for the rest of the letters on the screen.
Spatial attention alters neural processing speed test
Michael Posner developed a technique to quantify the effects of spatial attention on perception
-test the participant rt of when a signal is detected
-3 scenario: valid (arrow indicate the signal), neutral ( point bothway) and invalid (opposite direction)
The basic rationale of this procedure is that the arrows can be used as cues that prompt participants to direct their attention covertly (without eye movements) to the left or right in anticipation of a target.
Neurons in parietal cortex are modulated by attention test
-single neurons in monkey parietal cortex modulate their rate of firing in accordance with the attentional demands of a visual task.
-began by mapping the receptive field of individual neurons as the monkey fixated a central spot on a computer display when a stimulus was flashed briefly in their receptive field these parietal cells showed a small increase in their rate of firing (but they were train not to pay attention to the stimulus).
- the second part of the study, the authors trained the
monkeys to release a lever whenever they detected a brief dimming of the same stimulus. Now the neurons fired much more vigorously indicationg the monkey paying covert attention
-parietal neurons change their rate of firing according to the attentional demands of the task
Attention increases spatial selectivity in V2 and V4 neurons
- Monkeys were trained to attend to one of two locations in the receptive field of V1, V2 and V4 neurons
- Effective and ineffective stimuli were shown at both locations
- Stimuli were shown sequentially (one object in the RF) or simultaneously (two objects in the cell’s RF)
- Looked for evidence of spatial selectivity in the simultaneous condition
Attention increases spatial selectivity in V2 and V4 neurons result
- Attention to a stimulus increases a cell’s response regardless of condition
- Effect of attention is greatest for two stimuli in reaction field
- Attention helps bias response to attended stimuli in reaction field
Attention modulates early and mid-level visual processing in humans
• Watanabe et al. (1998) • fMRI 1.5 T • Randomly arranged moving dots • Translation component are V1 & MST sensitive • Expansion component MST sensitive V1 NOT sensitive Task instructions: 1. Passively view 2. Attend to expansion 3. Attend to translation
Attention modulates early and mid-level
visual processing in humans result
- Passively viewing moving dots with expansion and translation does not alter the fMRI signal
- Attending to the expanding component increases the fMRI signal in MT/MST
- where we know there are neurons responsive to expansion
- Attending to translation component increases the fMRI signal in both V1 and MT/MST
- Where neurons responsive to translation
Brain regions that have shown neural correlates of visual attention
• Neural correlates of visual attention have been found in numerous brain regions
• Sub cortical regions
• the superior colliculus
• the pulvinar nucleus
• Visually responsive cortical regions
• Intraparietal sulcus (IPS)
• AIP, LIP, VIP, CIP, and MIP (anterior, lateral, ventral, caudal, and
medial IPS)
• Milner & Goodale’s dorsal ‘action’ stream…
• V1, V4, MT, MST, …
• Prefrontal cortex
Unilateral spatial neglect: a failure of spatial awareness
- Occurs after damage to one side of the brain (usually the right hemisphere)
- Patients behave as if the affected side of space (the contralesional side) has ceased to exist:
- ignore food on one side of their plate
- fail to shave or make-up one side of their face
- bump into objects on one side
- fail to read text from one side of the page
- Most common and severe after damage to the parietal lobe
Deficits associated with visuospatial neglect
- Awareness for deficits
- reduced (anosognosia) impairs a person’s ability to understand and perceive his or her illness
- contralesional body parts of the body, the external and internal world seem not to exist
- Multimodal deficits
- can occur (visual, auditory, tactile, motor, olfactory).
- Visual behaviour
- lack of attention to contralesional hemispace, independent of gaze direction.
- deviation of gaze, head and sometime upper body towards the ipsilesional side.
- reduced eye contact with conversational partner
- Drawing and cancellation• contralesional omissions in drawing or cancellation tests
- Attention
- attentional shift in Posner paradigm is impaired
- Compensation
- cueing on the contralesional side can lead to a transient improvement
- Difficulty in maintaining central fixation
- Extinction
- visual extinction is common
- (a failure to detect a contralesional target in the presence of a competing ipsilesional stimulus)
Representational (imaginal) neglect
in the absence of visual input
- Neglect in the absence of visual input
- Often in conjunction with regular neglect
- Although can occur independently
- Implicates parietal areas in processes that support mental imagery
Unconscious perception in
spatial neglect
Despite neglect patients’profound loss of conscious perception for stimuli arising on the contralesional side of space, there may nevertheless be considerable unconscious processing of neglected information.
burning house task
What is special about natural scenes
- Complexity due to incredible number of exemplars (Highly similar features)
- Feature and configural similarity could lead to interference in long term memory
- Unless they are encoded holistically…
- sounds like faces
- Diamond & Carey (1986)
- Inversion for natural scenes
Amazing memory for natural scenes test
Standing (1973)
• People viewed 10,000 scenes for a few seconds each
• people could determine which of two images had been seen with 83% accuracy
Problems
• image were very distinct
• enables a sparse representation
• only basic category information needed to be stored
• Not clear about the fidelity of the stored memory
• not a test of free recall
Massive visual memory for object details test
- Brady et al. (2008)
- “human memory is fallible, imprecise, and subject to interference”
- human observers often fail to notice large changes in visual scenes – change blindness
- But visual long-term memory representations may be more detailed than believed
- 3 test conditions require different fidelity of recognition (novel different object, examplar object of the same cat, state, same ob different orientation)
Massive visual memory for object details test result
• Repeat-detection task demonstrated remarkable memory.
Rare false-alarms (1.3%), and high accuracy (96%) Two-alternative forced choice performance
• Even after ≈2 h separation between items, the repeats were detected ≈80% of the time
• memory must have a large and detailed storage capacity!
Scene memory is more detailed
than you think test
• Konkle et al. (2010)
• How much detail can be distinguished in a large number of briefly viewed natural scenes?
• 4672 images from 160 categories study of 4,6 or 14 per cat
test of two option
novel foil different cat
examplar foil same cat
high performace but the more foil learn lower exp score
Scene memory and object recognition do not use the same brain modules
- A common notion is that object perception is a necessary precursor to scene perception
- However, behavioural evidence suggests that scene perception can operate independently of object perception
- Patient DF (Steeves et al 2004) suffer carbon monoxide poisoning. have profound visual agnosia for objects .but able to recognize both natural and human-made scene
- Viewing scenes led to brain activity in the Parahippocampal Place Area (PPA)
- activation of the parahippocampal cortex in DF (a) is similar to a control subject (b)
Why is scene memory important
- Where are objects are located in our visual environment?
- Supports decisions on how to interact with (or avoid) the objects within actionable space
- Walking & grasping
- Viewpoint dependent
- Where are we located in the world?
- Supports decisions on how to move through and beyond the immediate environment
- Navigation & episodic memory
- Prediction and future planning
- How do I find home? How do I find food?
- Cognitive map
Cognitive maps in rat
- Tolman test on rat
- Rapidly switch to alternative path if previous path is blocked
- have Spatial knowledge like that on a map
- Permits flexible navigation through animals environmen
place cells in the hippocampus support a spatial map in rodents
• O’Keefe and Dostrovsky (1971) discovered place cells in the hippocampus
• O’Keefe received the Nobel Prize in 2014
Hippocampal remapping and grid realignment in entorhinal cortex.
• Cells fire at specific real world locations
• Notbased on animal location
Grid cells, head direction cells and
border/boundary cells complete a cognitive map
- Grid cells fire in a regular hexagonal lattice of locations tiling the floor of the environment
- medial entorhinal cortex
- Head direction (HD) cells fire on the basis of the direction the head is facing
- several cortical and subcortical structures
- Border/boundary cells fire when the animal is at set distances from navigational boundaries facing in specific directions
- entorhinal cortex/subiculum
- Moser & Moser Grid discovered grid cells in 2005
- shared the Nobel Prize with O’Keefe
Is the rodent spatial positioning network a good model of human navigation?
Similar anatomical structures
• hippocampal formation
• Papez circuit
But, there are differences across species
• Rats have less complex visual systems
• Rats are nocturnal rather than diurnal
• Damage to human equivalent navigation areas causes broader memory deficits. not limited to the spatial domain
Difficulty of translating movement task to human
imaging studies
- Navigation is an inherently mobile task
- Participants in functional magnetic resonance imaging (fMRI) experiments must remain stationary in the scanner
- fMRI studies must resort to related tasks
- virtual navigation
- imagined navigation
- spatial memory recall or
- viewing of navigationally relevant stimuli
- memory and planning systems are engaged and visual inputs are often present
Scene Perception module in the Brain
- Russell Epstein and Nancy Kanwisher provided evidence for a region in visual cortex that preferentially processes scenes
- they called this the parahippocampal place area (PPA)
- Anatomically, PPA lies along the parahippocampal gyrus and collateral sulcus
- boundary between posterior parahippocampal cortex and anterior lingual gyrus
The PPA responds to scenes, faces or other objects
• scenes’ include a wide variety of images, including landscapes, cityscapes, rooms, tabletop scenes, ‘scenes’ made out of Lego blocks, buildings, and houses
-no reaction to face, object and multiple object
What aspects of a scene is the PPA encoding?
- PPA is sensitive to the global spatial geometry/configuration of scenes
- e.g. spatial layout defined by large fixed surfaces
- Not the objects within scenes
The PPA responds to scramble scene
- PPA’s response is highest to scenes that depict a realistic spatial layout (normal and fracture)
- PPA’s response is lower if the position of the objects in the scene are scrambled
Is the PPA responsible for the spatial representation of scenes
Spatial layout hypothesis
• the lateral occipital complex (LOC) and fusiform gyrus encode information about the local individual objects in the scene
• Consistent with consequences of damage to the PPA
• patients report that they can see the objects in the scene but the overall organization of the scene is lost
Distance coding from fMRI adaptation expiriment
• Morgan et al. (2011) fMRI adaptation
220 colour photographs of 10 prominent landmarks from the University of Pennsylvania (i.e., buildings and statues)
• “subjective” distances between landmarks were determined for each participant
• Task: subjects covertly identified each landmark and made a button press once they had done so
mesure the neuron activation of viewing 2 image.. buikdingclose to each other or not
fMRI in hippocampus like border/boundary cells (morgan et al)
- fMRI activity in the in the hippocampus scaled with the distance between that building and the building shown on the immediately preceding trial
- closer buildings were representationally similar
- Like border/boundary cells in rat
- MVPA decoding of landmark identity not possible in the hippocampus
- Hippocampus response not related to landmark identity
Recording from individual cells in human medial temporal and frontal lobes for place cell
- Presurgical epilepsy patients .Each patient had 6 to 14 depth electrodes implanted
- recorded from 317 neurons of the human medial temporal and frontal lobes
- Subjects explored and navigated a virtual town in a virtual taxi
- provide evidence for a neural code of human spatial navigation based on cells that respond at specific spatial locations
- Like place cells in rat
- to views of landmarks
- Place-responsive cells were clustered in the hippocampus (H) compared with amygdala (A), parahippocampal region (PR) and frontal lobes (FR)
Viewpoint-independent direction coding in humans
- Previous human studies had found evidence for place-like and grid-like representations but not exclusively to perceived heading
- Used fMRI adaptation to distinctive landmarks with one of four facing directions
- Participants had to indicate whether the position represented by the static image of the landmark was on the left or right of the centre point of the maze
- Paired images were in the same heading direction (adaptation) or had different headings
Representation of allocentric heading in the retrosplenial complex
- single brain region in the medial parietal cortex was modulated by learned heading
- retrosplenial complex (RSC)
- active in navigational tasks and during passive viewing of navigationally relevant stimuli
- the representation of allocentric heading achieved in the RSC
Using cognitive maps to navigate: fMRI
- Howard et al (2014)
- Subjects learned an unfamiliar layout of the Soho district in London by studying maps or intensive walking tour
- fMRI on the day after learning the route
- watching 10 first-person-view movies of novel routes through the environment
- Five of the movies required subjects to make navigational decisions
- Five five required no navigational decision making (control routes
Using cognitive maps to navigate: fMRI Results
Hippocampal Activity Positively Correlates with Goal Distances During Navigation
• Patterns of data showing Hippocampal Activity Positively Correlates with Euclidean and Path Distances to the Goal during Travel Periods in Navigation Tasks
• Path Distances encoded more posteriorly
• Euclidean Distances encoded more anteriorly
Brain regions associated with
different navigation events
anterior hyppocampus code for eucladian travel period event
posterior hippocampus code for path travel event period and detour
entorhinal cortex for new goal event
posterior paretial cortex code for egocentric path goal in path period
Do bus drivers show hippocampal volume changes like Taxi drivers
Alternative explanations for changes in hippocampal volume
• General increase in driving
• vigilance, attention, motor planning, and execution
• the stress of driving all day
• poor air of a large city
• dealing with customers,
• traffic, and fellow road users
• A more controlled study using bus drivers
• The only difference is that bus drivers operate along a constrained set of routes and don’t need the knowledge
Hippocampi volume differences
between taxi drivers and bus drivers
- Results of MRI scan
- a) greater gray matter volume in the mid-posterior hippocampi in London taxi drivers when compared with London bus drivers
- b) less gray matter volume in the very anterior head of the hippocampi in taxi drivers when compared with bus drivers
Spatial performance differences
between taxi drivers and bus drivers
- London taxi drivers were significantly better than London bus drivers at London navigational tasks
- A, identifying London landmarks from among visually similar distractors
- B, making judgments about proximal relations between London landmarks.
- London bus drivers were significantly better than London taxi drivers at recalling newly-learned visual information (Rey-Osterrieth Complex Figure) after a delay.
