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In the study of vision, visual short-term memory (VSTM) is one of three broad memory systems including iconic memory and long-term memory. VSTM is a type of short-term memory, but one limited to information within the visual domain.

The Visuospatial Sketchpad is a VSTM subcomponent within the theoretical model of working memory proposed by Alan Baddeley. However, the term VSTM refers in a theory-neutral manner to the non-permanent storage of visual information over an extended period of time.

Whereas iconic memories are fragile, decay rapidly, and are unable to be actively maintained, visual short-term memories are robust to subsequent stimuli and last over many seconds.


The introduction of stimuli which were hard to verbalize, and unlikely to be held in long-term memory, revolutionized the study of visual short-term memory (VSTM) in the early 1970s (Cermak, 1971; Phillips, 1974; Phillips & Baddeley, 1971). The basic experimental technique used required observers to indicate whether two matrices (Phillips, 1974; Phillips &Baddeley, 1971), or figures (Cermak, 1971), separated by a short temporal interval, were the same. The finding that observers were able to report that a change had occurred, at levels significantly above chance, indicated that they were able to encode some aspect of the first stimulus in a purely visual store, at least for the period until the presentation of the second stimulus. However, as the stimuli used were complex, and the nature of the change relatively uncontrolled, these experiments left open various questions, such as: (1) whether only a subset of the perceptual dimensions comprising a visual stimulus are stored (e.g., spatial frequency, luminance, or contrast); (2) whether some perceptual dimensions are maintained in VSTM with greater fidelity than others; and (3) the nature by which these dimensions are encoded (i.e., are perceptual dimensions encoded within separate, parallel channels, or are all perceptual dimensions stored as a single bound entity within VSTM?).

Psychophysical approaches to VSTM

In a typical psychophysical VSTM experiment, observers' ability to discriminate between sequentially presented test and reference patterns are measured using a two-interval forced-choice (2-IFC) paradigm. For example, in a study involving spatial frequency, observers might be required to make a judgment as to whether the first or second pattern presented was of higher (or lower) spatial frequency. Typically the test and reference patterns are separated by ISIs in the range of 0 s to 30 s. The properties of stimulus pairs can be controlled by using a psychophysical staircase procedure, or via the method of constant stimuli (for details of these techniques, see Regan, 2000). When a staircase procedure is used, the properties of the stimulus pairs are altered until a criterion threshold level of performance is achieved (e.g., 75% correct).

Fidelity of memory representations

A series of studies over the last decade and a half (for good reviews, see Magnussen, 2000; Magnussen & Greenlee, 1999) have demonstrated that VSTM stores various perceptual dimensions (e.g., spatial frequency, orientation, hue) with a remarkable degree of fidelity and stability (Magnussen & Greenlee, 1992; Magnussen, Greenlee, Asplund, & Dyrnes, 1991; Magnussen, Idas, & Myhre, 1998; Regan, 1985). It has been shown, for instance, that with a reference frequency of 10 c/deg, spatial frequency thresholds tested with ISIs of up to several seconds (measured as Weber fractions, Df/f) differ by only three-to-six percent from those recorded when gratings are presented simultaneously (Regan, 1985). With a period difference of 360 arcseconds, a threshold of 0.04 Df/f implies that observers are able to distinguish spatial frequency differences of 14.4 arcsec (Magnussen & Greenlee, 1999). As this is approximately half the average cone spacing on the fovea, it implies that observers are able to store spatial frequency information within the hyperacuity range for upwards of 60 s (Bennett & Cortese, 1996).

A series of psychophysical studies have found that many perceptual dimensions (i.e., spatial frequency, hue, orientation, speed) are stored with little or no loss in VSTM. As already mentioned, spatial frequency can be stored for upwards of 60 s with no increase in thresholds (Bennett & Cortese, 1996; Magnussen & Greenlee, 1997; Magnussen et al., 1991; Magnussen, Greenlee, & Thomas, 1996; Regan, 1985). Other studies have shown that colour (Nilsson & Nelson, 1981), speed (Magnussen & Greenlee, 1992), and orientation (Magnussen et al., 1998), are also stored in VSTM for upwards of 10 s with no significant decay.

The one notable exception to this rule is contrast. Several studies have shown that thresholds for contrast discrimination grow rapidly as ISIs increase, with thresholds doubling as ISIs are raised from 0 s to 10 s (Lee & Harris, 1996; Magnussen et al., 1991; Magnussen et al., 1996). This appears to be due to a loss of information about contrast as ISI increases, which correspondingly makes it increasingly unlikely that a change will be reported as ISIs increase. The decay in contrast information is likely to underlie the apparent decay in information for VSTM experiments using matrix patterns (e.g., Phillips, 1974; Phillips & Baddeley, 1971).

Structure of memory representations

With the exception of contrast, basic perceptual attributes are similar in terms of both the accuracy and stability with which they are stored in VSTM. However, it is unclear whether the information from each perceptual stream is encoded separately within parallel channels, or whether information for different perceptual dimensions is represented within VSTM as a single, bound set of features. Two different lines of evidence – one derived from the experimental paradigm known as memory masking, the other associated with the differential effects observed for decisions made either within or between perceptual dimensions – suggest that VSTM stores information within multiple parallel perceptual channels.

Memory masking

Memory masking refers to an experimental technique in which the addition of a "masking" grating, placed between the reference and test stimuli in a psychophysical VSTM experiment (Bennett & Cortese, 1996; Magnussen & Greenlee, 1992; Magnussen et al., 1991), leads to an increase in psychophysical thresholds. It is important to note, however, that the use of the term "masking" here is somewhat misleading, as the temporal placement of the additional grating is such that it acts neither as a pattern mask nor as an energy mask for the test or reference stimuli (Breitmeyer, 1984).

If the masking grating matches the test or reference grating in the perceptual dimension being discriminated, no increase in threshold is observed relative to a no-mask control condition. However, the more the masking stimulus differs from the reference grating on the dimension being discriminated, the more thresholds increase, until thresholds are approximately double those recorded in the absence of a mask (Bennett & Cortese, 1996; Magnussen & Greenlee, 1992; Magnussen et al., 1991).

The short presentation times of the masking stimuli (e.g., 200 ms), coupled with the relatively long time periods between the mask and both the test and reference stimuli (e.g., Magnussen et al., 1991) argue against the possibility that spatial adaptation is an explanation for the increase in thresholds caused by the presence of the mask (e.g., Blakemore & Campbell, 1969).

Another feature of the memory-masking paradigm is that the effects of the mask are specific to the type of discrimination being made. For instance, when performing a spatial frequency judgment, the orientation of the masking grating has no effect on threshold levels. Likewise, the spatial frequency of the masking grating does not alter thresholds obtained when orientation is being discriminated (Magnussen et al., 1991). This specificity of the masking effect on thresholds is evidence against its being mediated either through distracting the observer, or by adding an additional non-specific burden to memory. Since orientation and spatial frequency are conjointly coded early in the visual system (DeValois & DeValois, 1990), this result supports the view that the neurophysiological site affected by memory masking occurs post-V1, at a locus where orientation and spatial frequency information are coded into independent perceptual channels. This argument is supported by the finding that masking by spatial frequency follows perceptual, rather than retinal coordinates (Bennett & Cortese, 1996), as size constancy is also thought to occur at a point post-V1 in the visual processing hierarchy (Magnussen, 2000), perhaps in V4 (see, for instance, Schiller, 1995).

Dual discrimination costs

It is well established that observers are able to make independent decisions about multiple stimulus dimensions (e.g., spatial frequency, contrast, orientation) with little or no cost (e.g., Chua, 1990; Greenlee & Thomas, 1993; Vincent & Regan, 1995). These studies support the view that spatial frequency, orientation, and contrast are encoded within independent, parallel channels. Since individual neurons in striate cortex conjointly code spatial frequency and orientation (DeValois & DeValois, 1990), these channels are likely to exist at a point later in the visual processing hierarchy than V1.

The memory masking literature supports the view that different perceptual properties are encoded independently within parallel channels. This view is further supported by evidence from experiments examining the costs of making dual decisions for attributes that are encoded either within the same or between different perceptual channels (Greenlee & Thomas, 1993; Magnussen & Greenlee, 1997; Magnussen et al., 1996; Thomas, Magnussen, & Greenlee, 2000). The Greenlee-Thomas model assumes that different perceptual dimensions (e.g., spatial frequency, contrast, orientation, movement) are encoded within independent channels (Greenlee & Thomas, 1993). According to this model, making dual judgments about different perceptual dimensions will lead to only a moderate increase in threshold, associated with the increased uncertainty of making two independent judgments (i.e., decision-noise). However, if the two judgments made are not independent — as might be expected if observers were required to make two decisions which draw on the same limited resource — thresholds are predicted to increase to a greater extent than can be explained on the basis of decision-noise alone.

Magnussen and Greenlee (1997) performed a series of VSTM experiments in which the relative costs associated with making dual discriminations within and between stimulus dimensions were compared. Their results can be summarized as follows: (1) when making discriminations regarding both contrast and spatial frequency, observers' thresholds rise by an amount predicted by the additional uncertainty in making two independent decisions; (2) when judgments are made within the same perceptual dimension, there is a much greater increase in associated thresholds than predicted on the basis of the increased uncertainty associated with making multiple independent decisions, suggesting that these judgments are not made independently (i.e., that they draw on the same limited resource).

Summary of results from psychophysical experiments

Psychophysical experiments in VSTM suggest that most perceptual dimensions (e.g., spatial frequency, orientation, colour, speed) are stored with remarkable fidelity over relatively long periods of time (Magnussen, 2000). The one exception to this rule is contrast, which has been shown to decay rapidly in VSTM (Lee & Harris, 1996). Converging evidence, drawn both from experiments using memory masking (Magnussen & Greenlee, 1992), and from a comparison of single and dual-discrimination costs (Magnussen & Greenlee, 1997), suggests that information is encoded in VSTM in the form of multiple independent channels, each channel representing a different perceptual dimension. Further evidence suggests that this information is encoded at a level in the visual hierarchy later than V1 (e.g., Bennett & Cortese, 1996).

Set-size effects in VSTM

In a typical VSTM experiment, observers are presented with two arrays, composed of a number of stimuli. The two arrays are separated by a short temporal interval, and the task of observers is to decide if the first and second arrays are composed of identical stimuli, or whether one item differs across the two displays (e.g., Luck & Vogel, 1997). Increasing the number of stimuli present within the two arrays leads to a monotonic decrease in the sensitivity of observers to differences in stimuli across the two arrays (Luck & Vogel, 1997; Pashler, 1988). This capacity limit has been linked to the posterior parietal cortex, the activity of which increases with the number of stimuli in the arrays, but only up to the capacity limit of about four stimuli (Todd & Marois, 2004). There are a number of frameworks that attempt to explain the effect of increasing set-size on performance in VSTM. These can be broadly grouped under three categories: (1) psychophysical frameworks (e.g., Magnussen & Greenlee, 1997); (2) sample size models (e.g., Palmer, 1990); and (3) urn models (e.g., Pashler, 1988).

Problems with psychophysical explanations

Psychophysical experiments suggest that information is encoded in VSTM across multiple parallel channels, each channel associated with a particular perceptual attribute (Magnussen, 2000). Within this framework, a decrease in an observer's ability to detect a change with increasing set-size can be attributed to two different processes: (1) if decisions are made across different channels, decreases in performance are typically small, and consistent with decreases expected when making multiple independent decisions (Greenlee & Thomas, 1993; Vincent & Regan, 1995); (2) if multiple decisions are made within the same channel, the decrease in performance is much greater than expected on the basis of increased decision-noise alone, and is attributed to interference caused by multiple decisions within the same perceptual channel (Magnussen & Greenlee, 1997).

However, the Greenlee-Thomas model (Greenlee & Thomas, 1993) suffers from two failings as a model for the effects of set-size in VSTM. First, it has only been empirically tested with displays composed of one or two elements. It has been shown repeatedly in various experimental paradigms that set-size effects differ for displays composed of a relatively small number of elements (i.e., approximately ≤ 4 items), and those associated with larger displays (i.e., approximately > 4 items). The Greenlee-Thomas (1993) model offers no explanation for why this might be so. Second, while Magnussen, Greenlee, and Thomas (1997) are able to use this model to predict that greater interference will be found when dual decisions are made within the same perceptual dimension, rather than across different perceptual dimensions, this prediction lacks quantitative rigor, and is unable to accurately anticipate the size of the threshold increase, or give a detailed explanation of its underlying causes.

In addition to the Greenlee-Thomas model (Greenlee & Thomas, 1993), there are two other prominent approaches for describing set-size effects in VSTM. These two approaches are can be referred to as sample size models (Palmer, 1990), and urn models (e.g., Pashler, 1988). They differ from the Greenlee-Thomas (1993) model by: (1) ascribing the root cause of set-size effects to a stage prior to decision making; and (2) making no theoretical distinction between decisions made in the same, or across different, perceptual dimensions.

Models of capacity limits in VSTM

If observers are asked to report on the quality (e.g., color) of an item stored in memory, while performance might be perfect when only a few items are encoded (the number of items that can be perfectly encoded varies depending on the attribute being encoded, but is usually less than five), after which performace invariably declines in a monotonic fashion as more items are added. Different theoretical models have been put forward to explain this decline in performance.

Slot models

A prominent class of model proposes that observers are limited by the total number of items which can be encoded, either because the capacity of VSTM itself is limited (e.g., Cowan, 2001; Luck & Vogel, 1997; Pashler, 1988), or because of a bottleneck in the number of items which can be attended to prior to encoding. This type of model has obvious similarities to urn models used in probability theory (see, for example, Mendenhall, 1967). In essence, an urn model assumes that VSTM is restricted in storage capacity to only a few items, k (often estimated to lie in the range of three-to-five). The probability that a suprathreshold change will be detected is simply the probability that the change element is encoded in VSTM (i.e., k/N). Although urn models are used commonly to describe performance limitations in VSTM (e.g., Luck & Vogel, 1997; Pashler, 1988; Sperling, 1960), it is only recently that the actual structure of items stored has been considered. Luck and colleagues have reported a series of experiments designed specifically to elucidate the structure of information held in VSTM (Luck & Vogel, 1997). This work provides evidence that items stored in VSTM are coherent objects, and not the more elementary features of which those objects are composed.

Noise models

A much more controversial framework has more recently been put forward by Wilken and Ma (2004) who suggest that apparent capacity limitations in VSTM are caused by a monotonic decline in the quality of the internal representations stored (i.e., monotonic increase in noise) as a function of set size. In this conception capacity limitations in memory are not caused by a limit on the number of things that can be encoded, but by a decline in the quality of the representation of each thing as more things are added to memory.

In their 2004 experiments, they varied color, spatial frequency, and orientation of objects stored in VSTM using a signal detection theory (SDT) approach. The participants were asked to report difference between the visual stimuli presented to them in consecutive order. The invesigators found that different stimuli were encoded independently and in parallel, and that the major factor limiting discrimination performance was neuronal noise (which is a function of visual set size).

Sample size models

Sample size models (Palmer, 1990) propose that the monotonic decrease in performance with increasing set-size in VSTM experiments is a direct outcome of a limit in the amount of information observers can extract from a visual display.

In the sample size model, each perceptual attribute of a stimulus is associated with an internal, unidimensional percept, formed by the collection of a finite number of discrete samples. It is assumed that the total number of samples that can be collected across the entire visual scene is fixed. Assuming that equal attention is paid to each stimulus, it follows that the total number of samples taken from each element in an array will be inversely proportional to the number of stimuli present, N. Central limit theorem implies that the mean of the samples taken, and therefore the mean of the internal percept, will have a variance inversely proportional to N. Signal detection theory defines sensitivity (i.e., d′) as being inversely proportional to the standard deviation of the underlying representation to be discriminated (Macmillan & Creelman, 1991). Therefore according to the sample size model, in a VSTM experiment an observer's sensitivity to a stimulus change, d′, will be inversely proportional to square-root of N.

Unfortunately, few studies have directly tested this prediction of the sample size model. Some evidence has been provided by Palmer (1990), who performed a VSTM experiment using arrays composed of lines of varying length, and set-sizes of one, two or four. The task of observers was to determine whether there had been a change in the length of one of the lines. It was found that observers' thresholds increased proportional to square-root of N, in accordance with the predictions of the sample size model.

See also



  • Breitmeyer, B. (1984). Visual masking: An integrative approach. Oxford: Oxford University Press.
  • DeValois, R. L., & DeValois, K. K. (1990). Spatial vision. Oxford: Oxford University Press.


  • Bennett, P. J., & Cortese, F. (1996). Masking of spatial frequency in visual memory depends on distal, not retinal, frequency. Vision Research, 36(2), 233-238.
  • Blakemore, C., & Campbell, F. W. (1969). On the existence of neurons in the human visual system selectively sensitive to the orientation and size of retinal images. Journal of Physiology, 203, 237-260.
  • Cermak, G. W. (1971). Short-term recognition memory for complex free-form figures. Psychonomic Science, 25(4), 209-211.
  • Chua, F. K. (1990). The processing of spatial frequency and orientation information. Perception & Psychophysics, 47(1), 79-86.
  • Cowan, N. (2001). The magical number 4 in short-term memory: A reconsideration of mental storage capacity. Behavioral and Brain Sciences, 24(1).
  • Greenlee, M. W., & Thomas, J. P. (1993). Simultaneous discrimination of the spatial frequency and contrast of periodic stimuli. Journal of the Optical Society of America A, 10(3), 395-404.
  • Lee, B., & Harris, J. (1996). Contrast transfer characteristics of visual short-term memory. Vision Research, 36(14), 2159-2166.
  • Levy, B.A. (1971) Role of articulation in auditory and visual short-term memory, Journal of Verbal Learning and Verbal Behaviour 10: 123-32.
  • Luck, S. J., & Vogel, E. K. (1997). The capacity of visual working memory for features and conjunctions. Nature, 390, 279-281.
  • Magnussen, S. (2000). Low-level memory processes in vision. Trends in Neurosciences, 23(6), 247-251.
  • Magnussen, S., & Greenlee, M. W. (1992). Retention and disruption of motion information in visual short-term memory. Journal of Experimental Psychology: Learning, Memory, and Cognition, 18, 151-156. 248
  • Magnussen, S., & Greenlee, M. W. (1997). Competition and sharing of processing resources in visual discrimination. Journal of Experimental Psychology: Human Perception and Performance, 23(6), 1603-1616.
  • Magnussen, S., & Greenlee, M. W. (1999). The psychophysics of perceptual memory. Psychological Research, 62(2-3), 81-92.
  • Magnussen, S., Greenlee, M. W., Asplund, R., & Dyrnes, S. (1991). Stimulus-specific mechanisms of visual short-term memory. Vision Research, 31(7-8), 1213-1219.
  • Magnussen, S., Greenlee, M. W., & Thomas, J. P. (1996). Parallel processing in visual short-term memory. Journal of Experimental Psychology: Human Perception and Performance, 22(1), 202-212.
  • Magnussen, S., Idas, E., & Myhre, S. H. (1998). Representation of orientation and spatial frequency in perception and memory: A choice reaction time analysis. Journal of Experimental Psychology: Human Perception and Performance, 24, 707-718.
  • Nilsson, T. H., & Nelson, T. M. (1981). Delayed monochromatic hue matches indicate characteristics of visual memory. Journal of Experimental Psychology: Human Perception and Performance, 7, 141-150.
  • Palmer, J. (1990). Attentional limits on the perception and memory of visual information. Journal of Experimental Psychology: Human Perception and Performance, 16(2), 332-350.
  • Pashler, H. (1988). Familiarity and visual change detection. Perception & Psychophysics, 44(4), 369-378.
  • Phillips, W. A. (1974). On the distinction between sensory storage and short-term visual memory. Perception & Psychophysics, 16(2), 283-290.
  • Phillips, W. A., & Baddeley, A. D. (1971). Reaction time and short-term visual memory. Psychonomic Science, 22(2), 73-74.
  • Regan, D. (1985). Storage of spatial-frequency information and spatial-frequency discrimination. Journal of the Optical Society of America A, 2(4), 619-621.
  • Schiller, P. H. (1995). Effect of lesions in visual cortical area V4 on the recognition of transformed objects. Nature, 376, 342-344.
  • Sperling, G. (1960). The information available in brief visual presentations. Psychological Monographs: General and Applied, 74(11), 1-30.
  • Todd, J. J., & Marois, R. (2004). Capacity limit of visual short-term memory in human posterior parietal cortex. Nature, 428, 751-753.
  • Vincent, A., & Regan, D. (1995). Parallel independent encoding of orientation, spatial frequency, and contrast. Perception, 24(5), 491-499.
  • Wilken P, Ma WJ (2004) A detection theory account of change detection. J Vis, 4, 1120-1135.

Types of memory
Articulatory suppression‎ | Auditory memory | Autobiographical memory | Collective memory | Early memories | Echoic Memory | Eidetic memory | Episodic memory | Episodic-like memory  | Explicit memory  |Exosomatic memory | False memory |Flashbulb memory | Iconic memory | Implicit memory | Institutional memory | Long term memory | Music-related memory | Procedural memory | Prospective memory | Repressed memory | Retrospective memory | Semantic memory | Sensory memory | Short term memory | Spatial memory | State-dependent memory | Tonal memory | Transactive memory | Transsaccadic memory | Verbal memory  | Visual memory  | Visuospatial memory  | Working memory  |
Aspects of memory
Childhood amnesia | Cryptomnesia |Cued recall | Eye-witness testimony | Memory and emotion | Forgetting |Forgetting curve | Free recall | Levels-of-processing effect | Memory consolidation |Memory decay | Memory distrust syndrome |Memory inhibition | Memory and smell | Memory for the future | Memory loss | Memory optimization | Memory trace | Mnemonic | Memory biases  | Modality effect | Tip of the tongue | Lethologica | Memory loss |Priming | Primacy effect | Reconstruction | Proactive interference | Prompting | Recency effect | Recall (learning) | Recognition (learning) | Reminiscence | Retention | Retroactive interference | Serial position effect | Serial recall | Source amnesia |
Memory theory
Atkinson-Shiffrin | Baddeley | CLARION | Decay theory | Dual-coding theory | Interference theory |Memory consolidation | Memory encoding | Memory-prediction framework | Forgetting | Recall | Recognition |
Method of loci | Mnemonic room system | Mnemonic dominic system | Mnemonic learning | Mnemonic link system |Mnemonic major system | Mnemonic peg system | [[]] |[[]] |
Neuroanatomy of memory
Amygdala | Hippocampus | prefrontal cortex  | Neurobiology of working memory | Neurophysiology of memory | Rhinal cortex | Synapses |[[]] |
Neurochemistry of memory
Glutamatergic system  | of short term memory | [[]] |[[]] | [[]] | [[]] | [[]] | [[]] |[[]] |
Developmental aspects of memory
Prenatal memory | |Childhood memory | Memory and aging | [[]] | [[]] |
Memory in clinical settings
Alcohol amnestic disorder | Amnesia | Dissociative fugue | False memory syndrome | False memory | Hyperthymesia | Memory and aging | Memory disorders | Memory distrust syndrome  Repressed memory  Traumatic memory |
Retention measures
Benton | CAMPROMPT | Implicit memory testing | Indirect tests of memory | MAS | Memory tests for children | MERMER | Rey-15 | Rivermead | TOMM | Wechsler | WMT | WRAML2 |
Treating memory problems
CBT | EMDR | Psychotherapy | Recovered memory therapy |Reminiscence therapy | Memory clinic | Memory training | Rewind technique |
Prominant workers in memory|-
Baddeley | Broadbent |Ebbinghaus  | Kandel |McGaugh | Schacter  | Treisman | Tulving  |
Philosophy and historical views of memory
Aristotle | [[]] |[[]] |[[]] |[[]] | [[]] | [[]] | [[]] |
Journals | Learning, Memory, and Cognition |Journal of Memory and Language |Memory |Memory and Cognition | [[]] | [[]] | [[]] |

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