24th October 2023

Perception, Information and Memory

An Overview of Memory and Forgetting

What is memory?

Aristotle once said, ‘Memory is, therefore, neither perception nor conception, but a state or affection of one of these, conditioned by lapse of time.’ By this, we can understand that memory describes past ideas and experiences, whereas perception and conception could also relate to the present (Ross, 1930). Memory is a broad term that describes multiple brain systems as an inter-relationship between our experiences, thoughts and impressions. Multiple brain structures of the temporal lobe and midbrain appear to be involved in memory, including the hippocampus, limbic system, basal ganglia and ventral tegmental area (Lisman and Grace, 2022, Squire et al., 2004). The relationship between these structures is documented in several studies. For example, studies into depression have suggested that chronic stress can sensitise the amygdala to negative information and suppress hippocampal neurogenesis (Dillon and Pizzagalli, 2018).

One way of dividing memory is into short-term and long-term, based on duration and capacity. Short-term memory typically holds a limited number of items for only a short period of time, whereas long-term memory is not bound by such limitations (Cowan, 2008). Working memory is sometimes described as a third division but will be described within short-term memory for this chapter. Memory can also be subcategorised based on the type of information that it pertains to. Semantic memory refers to acquired information about the world (Binder and Desai, 2011). For example, knowing the names of colours or that France is a country. It can also include more specific facts, such as historical names and dates. In comparison, episodic memory relates to our own autobiographical life events (Tulving, 2002). For example, remembering your first date or what you had for lunch. Both semantic and episodic memory are subdivisions of declarative memory. By contrast, non-declarative memory, otherwise known as implicit, consists of our procedural or motor memory (Krakauer and Shadmehr, 2006). For example, knowing how to swim or ride a bike.

Short-term memory

The working memory model

The term ‘working memory’ is sometimes used interchangeably with short-term memory. However, more specifically, it describes a way in which information is manipulated as well as stored. It is like a workspace for short-term memory (May et al, 1999). Working memory does not represent a single neural process but instead seems to be a set of interlinked abilities (Wynn and Coolidge, 2011). 

Working memory is a highly researched area of cognitive neuroscience. The theory was conceived following an experiment where participants were asked to recall verbally spoken digits whilst being distracted with a visually presented grammatical reasoning task. The visual task had been intended as a distraction but, surprisingly, did little to influence the verbal information retained (Baddeley, 2012). This thereby inspired the original Baddeley and Hitch (1974) working memory model [see Figure 4]. The working memory model acknowledges that there can be multiple compartments to short-term memory, depending on the type of information that is being stored. 

In the model, three components are described: 

• The visuo-spatial sketch pad.
• The phonological loop.
• The overarching central executive.

Image Source: Wikimedia Commons (2011). Baddeley working memory, Licensed under a creative commons licence. Available for free at: https://commons.wikimedia.org/wiki/File:Baddeley_working_memory.jpg (Accessed on: 17 October 2023).

The phonological loop maintains and rehearses auditory information to maintain it within short-term memory, whilst the visuo-spatial sketchpad processes visual information (Wynn and Coolidge, 2011). Visuo-spatial and auditory memory are held in separate compartments and are therefore not limited by the usual capacity of short-term memory. (Baddeley, 2012). For example, you can listen to a conversation whilst driving with minimal interference. Later versions of the model also included a fourth component: a temporary memory store, or ‘episodic buffer’. The episodic buffer maintains data from the two subsystems in active attention so that it can be processed by the central executive. (Wynn and Coolidge, 2011).

Capacity and chunking

Miller (1956) proposed that short-term memory is limited to holding only seven +/- two items of information at any one time. We can observe that when a person is given more information than is their capacity to retain, new information displaces existing information in the short-term memory (Cowan, 2000). For example, when trying to remember a list of shopping items, remembering new items after a certain point will cause earlier ones to be forgotten. The primacy and recency effect suggests that the items in the middle of the list are most likely to be forgotten. A possible explanation for this is that the most recent items are recalled with the least delay, whilst earlier items have had a greater opportunity to be rehearsed. The recency effect seems to be less pronounced if there is a distraction or delay in recall, whereas the primacy effect is retained (Cowan, 2000).

‘Chunking’ is a technique which is used to overcome the limited capacity of short-term memory. For example, when learning a new phone number, we will tend to group numbers into ‘chunks’ which are easier to remember. McLean and Gregg (1967) highlighted that these chunks tend to be recited together quickly, for example, 123-456-789. If there are associations with items in long-term memory, chunking can be even more effective. Miller (1956) gave an example of the word ‘fbicbsibmirs’, which can be split into triads that many people already have in their long-term memory: FBI, CBS, IBM and IRS.

The levels of processing model 

Craik and Lockhart (1972) proposed an alternative theory for memory storage, which refers to both short and long-term memory. They also spoke of a third component, ‘sensory storage’, which includes all information received by the senses regardless of whether we have paid attention to it. They described sensory storage as having a duration of 0.5-2 seconds, short-term storage as having a duration of 5-20 seconds, and long-term storage as potentially unlimited (Craik and Lockhart, 1972).

Rather than discussing such defined stores, the levels of processing model describes shallow processing and deep processing depending on other factors. In shallow processing, the memory is lost when attention is diverted, as it is being repeated to be maintained in consciousness. In deep processing, there is a greater level of analysis, which allows the memory to be retained even when attention is shifted, for example, linking with pre-existing memories (Craik and Lockhart, 1972). This is another way of explaining the phenomena discussed under the working memory model because single words or chunks do not require phonemic analysis and thus remain in shallow processing. By contrast, full sentences and descriptive information are compatible with deeper learned structures and would, therefore, be moved into a deeper level of processing (Craik and Lockhart, 1972).

Long-term memory

Memory results from interactions between neurones and their activity in specific anatomical structures. The multiple memory systems model suggests that long-term memory is stored differently, depending on whether the information is declarative or non-declarative (Reber and Allen, 2022).

Declarative memory

The hippocampus is a structure in the temporal lobe of the brain which is necessary for encoding and recalling long-term episodic memories (Lisman and Grace, 2005). In the past two decades, there have been studies that suggest that the hippocampus forms a functional loop with the ventral tegmental area (VTA) using dopaminergic neurons. When the hippocampus receives new information, the loop is activated, and dopamine is released, and a signal is conveyed via several structures to the VTA (Lisman and Grace, 2005). Dopamine is just one of several neurotransmitters that seem to be involved in memory, in addition to glutamate, GABA and serotonin. The use of functional MRI has shown that, when learning new words, those that were better remembered demonstrated greater functional connectivity amongst the midbrain, hippocampus and ventral striatum (part of the basal ganglia). This has been tested in the absence of external reward to help clarify the mechanism of internally-guided learning (Ripollés et al, 2016). 

Semantic memory overlaps with perception, as we use sensory information to identify objects and people as part of the process of memory. Neuroimaging studies have shown that there are modality-specific sensory, motor, and emotion systems concerned with understanding language. However, there are also significant regions of the brain that are involved in comprehension tasks but are not modality-specific (Binder and Desai, 2011).

Non-declarative memory

We have all heard the phrase ‘You’ll never forget how to ride a bike’ or heard of cases where a person with severe dementia is still able to play the piano. These phenomena relate to procedural or motor memory. Procedural learning has been explored experimentally to measure the progression of sequential movements into well-articulated behaviour (Doyon et al, 2009). Some parts of the brain that are thought to be important in procedural memory include the hippocampus, the prefrontal cortex and the basal ganglia (Reber and Allen, 2022). To learn a motor activity, we need to repeat the skill. However, there is also a period of post-activity learning known as motor consolidation. During this time, physiological and synaptic changes within the brain enable the activity to be consolidated as a memory (Doyon et al, 2009).

Retrieval of memories 

We all experience times when memory fails us. This could be due to a problem with the process of remembering or with retrieving the stored memory. The table below outlines some theories for forgetting.

One of the concepts introduced here is ‘Retrieval cues’. This means that a person is more likely to recall memories when they have similar cues to the initial memory input. Godden and Baddeley, mentioned in the table above, took a somewhat extreme example of this by drastically changing the external environment of the scuba divers. Dijkstra et al (2007) conducted another study on retrieval cues, which looked more selectively at body posture. They found that autobiographical events were recalled more quickly if body position was memory-congruent, i.e. the position during remembering was the same as during recall.

Clinical relevance 

One of the most cited cases in clinical neuroscience is Patient H.M., who became known for his severe memory impairment. The memory impairment was an unexpected outcome from undergoing temporal lobe neurosurgery for incapacitating seizures. He lived a long life and appeared intellectually unaffected but forgot events almost as soon as they occurred, which enables us to explore the link between short-term and long-term memory (Squire, 2009). H.M. could retain three-digit numbers for around 15 minutes with continuous rehearsal but would forget the entire event as soon as his attention shifted. This supports the idea of separate memory stores (Squire, 2009). Whilst the case of Patient H.M. is somewhat unique, the understanding that we have gained regarding temporal lobe structures can assist us in understanding the impact of other organic causes of memory loss, for example, malignancy.

More broadly, the group of patients that we are often most concerned with in terms of memory disorders are those with dementia. Previously, in this chapter, we discussed that neurotransmitters play a role in memory. This has translated, in part, to the emerging treatments of Alzheimer’s disease, such as NMDA receptor antagonists. Alzheimer’s disease is characterised by global memory loss and behaviour changes due to progressive damage to the hippocampus and neocortex (Liu et al, 2019). It is thought that over-activity of glutamate, leading to pathological levels of Ca2+, can cause neurotoxicity and synaptic dysfunction in Alzheimer’s disease. Hence, NMDA receptor antagonists are being used in the treatment of moderate to severe Alzheimer’s to reduce glutamate-induced excitotoxicity and slow progression of the condition (Liu et al, 2019).

Later in this chapter, we will discuss how other mental illnesses may interact with memory. For example, the role of attention in attention-deficit / hyperactivity disorder or perception in schizophrenia.

References

• Baddeley, A. (2012) “Working memory: Theories, models, and controversies,” Annual Review of Psychology, 63(1), pp. 1–29. Available at: https://doi.org/10.1146/annurev-psych-120710-100422. 
• Baddeley, A. Hitch, G. (1974) “Working memory,” Psychology of Learning and Motivation, pp. 47–89. Available at: https://doi.org/10.1016/s0079-7421(08)60452-1. 
• Binder, J. Desai, R. (2011). The neurobiology of semantic memory. Trends in Cognitive Science, 15(11), pp. 527-36. Available at: https://doi.org/10.1016/j.tics.2011.10.001.
• Cohen, J. Kinston, W. (1983). Repression theory: a new look at the cornerstone. The International Journal of psycho-analysis 65(4), pp. 411-22. PMID: 6544752.
• Cowan (2000). The magical number 4 in short-term memory: A reconsideration of mental storage capacity. The Behavioural and Brain Sciences. 24(1), pp. 114-85. Available at: https://doi.org/10.1017/s0140525x01003922.
• Cowan, N. (2008). What are the differences between long-term, short-term, and working memory? Progress in Brain Research. 169(07), pp. 323-38. Available at: https://doi.org/ 10.1016/S0079-6123(07)00020-9.
• Craik, F. Lockhart, R. (1972). Levels of Processing: A Framework for Memory Research. Journal of Verbal Learning and Verbal Behavior. 11(6), pp. 671-684. Available at: https://doi.org/10.1016/S0022-5371(72)80001-X.
• Dillon, D. Pizzagalli, D. (2018). Mechanisms of Memory Disruption in Depression. Trends in Neurosciences. 41(3), pp.137-149. Available at: https://doi.org/10.1016/j.tins.2017.12.006.
• Dijkstra, K. et al. (2007). Body posture facilitates the retrieval of autobiographical memories. Cognition. 102, pp. 139–149. Available at: https://doi.org/10.1016/j.cognition.2005.12.009.
• Garcia-Lazaro, H. et al. (2012). Neuroanatomy of episodic and semantic memory in humans: A brief review of neuroimaging studies. 60(6), pp.613-7. Available at: https://doi.org/10.4103/0028-3886.105196.
• Godden, D. Baddeley, A. (1975). Context-dependent memory in two natural environments: On land and underwater. British Journal of Psychology. 66(3), pp. 325–331. Available at: https://doi.org/10.1111/j.2044-8295.1975.tb01468.x.
• Krakauer, J. Shadmehr, R. (2006). Consolidation of motor memory. Trends in Neurosciences. 29(1), pp. 58-64. Available at: https://doi.org/10.1016/j.tins.2005.10.003.
• Liu, J. et al. (2019). The Role of NMDA Receptors in Alzheimer’s Disease. Frontiers in Neuroscience, 13. Available at: https://doi.org/10.3389/fnins.2019.00043.
• Lisman, J. Grace, A. (2005). The Hippocampal-VTA Loop: Controlling the Entry of Information into Long-Term Memory. Neuron. 46(5), pp. 703-13 Available at: https://doi.org/10.1016/j.neuron.2005.05.002.
• May, C. et al (1999). The role of interference in memory span. Memory and Recognition. 27(5), pp.759-67. Available at: https://doi.org/10.3758/bf03198529.
• McLean, R.S. Gregg, L.W. (1967) Effects of induced chunking on temporal aspects of serial recitation. Journal of Experimental Psychology. 74(4), pp. 455–59. Available at: https://doi.org/10.1037/h0024785.
• Miller, G. (1956). The magical number seven, plus or minus two: Some limits on our capacity for processing information. Psychological Review, 63(2), 81–97. Available at: https://doi.org/10.1037/h0043158.
• Reber, A. Allen, R. The Cognitive Unconscious: The First Half Century. Oxford University Press. Available at: https://doi.org/10.1093/oso/9780197501573.001.0001.
• Ricker, T. et al (2014). Time-based loss in visual short-term memory is from trace decay, not temporal distinctiveness. Journal of Experimental Psychology: Learning, Memory, and Cognition. 40(6), pp. 1510-23. Available at: https://doi.org/10.1037/xlm0000018.
• Ripollés, P. et al (2016). Intrinsic monitoring of learning success facilitates memory encoding via the activation of the SN/VTA-Hippocampal loop. Elife. 20(5). Available at: https://doi.org/10.7554/eLife.17441.
• The Works of Aristotle, translated into English under the editorship of W. D. Ross. Physica. Translated by R. P. Hardie and R. K. Gaye. Oxford: Clarendon Press. (1930). The Journal of Hellenic Studies. 50(2), pp. 365-365. Available at: https://doi.org/10.1017/S0075426900071895.
• Sekeres, M. (2017). Mechanisms of memory consolidation and transformation. Cognitive neuroscience of memory consolidation. Springer International Publishing. pp. 17-44. Available at: https://doi.org/10.1007/978-3-319-45066-7_2
• Squire, L (2009). The Legacy of Patient H.M. for Neuroscience. Neuron. 61(1), pp. 6-9. Available at: https://doi.org/10.1016/j.neuron.2008.12.023.
• Squire, L. Stark, C. Clark, R (2004). The medial temporal lobe. 27, pp. 279-306. Available at: https://doi.org/10.1146/annurev.neuro.27.070203.144130.
• Tulving, E. (2002). Episodic memory: from mind to brain. Annual Review of Psychology. 53, pp. 1-25. Available at: https://doi.org/10.1146/annurev.psych.53.100901.135114.
• Vann, S. Nelson, A. (2015). The mammillary bodies and memory: more than a hippocampal relay. 219, pp. 163-185. Available at: https://doi.org/10.1016/bs.pbr.2015.03.006.
• Wynn, T. Coolidge, F. (2011). The Implications of the Working Memory Model for the Evolution of Modern Cognition. International Journal of Evolutionary Biology. Available at: https://doi.org/10.4061/2011/741357.

Principles of Visual and Auditory Perception

What is perception?

Perception relates to a stimulation of the body’s senses, which relates to our understanding of the world around us. It has been debated whether this is able to be clearly separated from memory (Peterson and Skow-Grant, 2003).

Perceptual organisation

Figure-ground differentiation

Figure-ground differentiation is where two shapes share a common border, and one of the shapes is considered to have been shaped by that border whilst the other is less defined. This concept demonstrates that visual input is organised into shapes by our brains; for example, perceiving a certain object as the focus or foreground (Peterson and Skow-Grant, 2003). Optical illusions show this phenomenon, such as Rubin’s Vase (see below), which depicts a black and white design of two faces and a vase. We will either perceive the faces or the vase, whilst the alternate image becomes less prominent. The debate regarding whether memory is needed for figure-ground differentiation stems from how we can identify these objects. Do we need to access our memories of similar images, or can we bypass this by using certain cues, for example, symmetry and area? (Peterson and Skow-Grant, 2003).

Image Source: Wikimedia Commons (2007). Cup or faces paradox, Licensed under a creative commons licence. Available for free at: https://commons.wikimedia.org/wiki/File:Cup_or_faces_paradox.svg (Accessed on: 17 October 2023).

Object constancy

When we move around an object, we can still recognise it. 

Object constancy proposes a way that we can recognise an object from a number of viewpoints. For example, even if we first view a teapot from the side, we can still recognise that it is a teapot from the front. Some theories suggest that we achieve this by mentally rotating the object to a more familiar orientation (viewer-centred theories), whereas others suggest that the mental representation of the object is complete enough that the viewpoint is not relevant (object-centred theories) (Turnbull et al, 1997). 

Recent studies have attempted to identify which region of the brain is involved in this phenomenon. For example, a behavioural study by Nestmann et al (2021) compared stroke patients to a control group and identified that those with lesions of the right fusiform gyrus had more difficulty identifying objects from atypical views. Combined with complimentary fMRI results, they concluded that fusiform and lateral-occipital areas of the brain are important for visual object constancy.

Set

Alport (1955) discussed some of the major theories of perception and described a set as: ‘A perceptual bias or predisposition or readiness to perceive particular features of a stimulus’. An example of this would be overlooking the presence of a cat in an image which had been anticipated to contain only dogs, i.e. ignoring stimuli that do not fit with the perceptual set. Similarly, Gorbunova (2016) described a phenomenon where a person is more likely to identify similar targets once the first has been found but is hindered from finding targets with different characteristics. 

Set perception has interesting applications in social psychology, as it can influence or bias our interpretation of a person’s actions and contributions. It can also be applied to certain mental illnesses. For example, obsessive-compulsive disorder (OCD) can involve overfocused attention on irrelevant or harmful stimuli (Okasha et al, 2000). There have also been studies considering the role of set perception in schizophrenia. In contrast to OCD, it appears that people with schizophrenia are less likely to fixate their attention. However, this includes missing contextual information, so it has the potential disadvantage of being less able to draw information from their social environment (Green et al, 2008).

Illusions and hallucinations

Illusions and hallucinations are misrepresentations of reality, which can be generated by pathologies in neurology, ophthalmology and psychiatry. An example of an illusion would be misperceiving a sock as a rat in a darkened room, whereas a hallucination would be visualising a rat even though there is nothing there (Norton and Corbett, 2000). Hallucinations conflict with our definition of perception, as the senses are stimulated without an external cause. Hallucinations can occur in a range of senses, such as visual, auditory or tactile, and can present in both children and adults (Jardri et al, 2014). Hallucinations may occur as a result of psychotic mental illnesses but can also present during periods of heightened stress and anxiety. Likewise, illusions may occur during states of anxiety (Jardri et al 2014). However, the diagnosis of visual perceptual abnormalities must also consider broader causes, ranging from delirium to migraines. Therefore, it is important to consider the broader context of the patient and other symptoms which they present with (Norton and Corbett, 2000).

References

• Allport, F (1955) Theories of perception and the concept of structure: A review and critical analysis with an introduction to a dynamic-structural theory of behavior. John Wiley & Sons Inc. Available at: https://doi.org/10.1037/11116-000.
• Gorbunova, E. (2016). The role of perceptual similarity in visual search for multiple targets. Journal of Vision. 173, pp. 46-54. Available at: https://doi.org/10.1016/j.actpsy.2016.11.010.
• Green, M. et al. (2008). Visual processing of social context during mental state perception in schizophrenia. 33(1), pp. 34-42. PMID: 18197270.
• Ittelson, W. (1960). Visual Space Perception. Springer.
• Jardri, R. et al (2014). From Phenomenology to Neurophysiological Understanding of Hallucinations in Children and Adolescents. Schizophrenia bulletin. 40(Suppl 4). S221-S232. Available at: http://dx.doi.org/10.1093/schbul/sbu029.
• Nestmann, S. et al (2021). The role of posterior ventral stream areas for viewpoint-invariant object recognition. Neuroimage. 251(119021). Available at: https://doi.org/10.1016/j.neuroimage.2022.119021. 
• Norton, J. Corbett, J. (2000). Visual Perceptual Abnormalities: Hallucinations and Illusions. Seminars in Neurology. 20(1). pp. 111-121. Available at: https://doi.org/ 10.1055/s-2000-6837.
• Okasha, A. et al. (2000). Cognitive dysfunction in obsessive-compulsive disorder. Acta Psychiatr Scand. 101(4), pp. 281-5. PMID: 10782547.
• Peterson, M. Skow-Grant, E. (2003). Memory and Learning in Figure–Ground Perception. Psychology of Learning and Motivation. Psychology of Learning and Motivation. 42, pp. 1-35. Available at: https://doi.org/10.1016/S0079-7421(03)01001-6.
• Turnbull, O. Carey, D. McCarthy, R. (1997). The Neuropsychology of Object Constancy. Journal of the International Neuropsychological Society. 3(3), pp. 288-98. PMID: 9161108.

Information Processing

Attention

Attention is a complex process which involves areas that we have discussed previously: memory and perception. It is a term which is difficult to define despite being used in everyday language (Styles, 2006). Attention is associated with our selective processing of the information received through our senses, which thereby has a large impact on our understanding of the world (Driver, 2010). You may be tempted to use ‘attention’ synonymously with ‘focus’; however, to visually focus on an object does not necessarily prevent you from seeing objects around it. Similarly, focusing on an object does not guarantee that your attention will not be drawn elsewhere (Styles, 2006). 

One way of appreciating attention is to divide it into three components: alertness, selectivity and processing capacity (Posner and Boies, 1971). Relating this back to memory, alertness is similar to the processing of sensory information, whilst selectivity moves this into short-term memory. We can relate this back to the working memory model, as each compartment only has a limited capacity to receive new information at any one time. Similarly, in the case of H.M., memory was reliant on maintaining attention on a piece of information.

Clinical relevance of information processing

Schizophrenia

Psychotic experiences could be described as altered information processing, with one of the core features being hallucinations. An example of a process which may underlie this is psychosocial stress leading to dysregulation of dopaminergic signalling, which may interfere with processing biologically-important events (Heinz et al, 2019). schizophrenia is an example of a psychotic illness, which often features auditory hallucinations. One study used PET to appraise which areas of the brain appeared to be more active in people with auditory verbal hallucinations due to schizophrenia. They found that some of the areas affected were similar to the regions we previously described as being important in memory: the hippocampus and limbic structures, the paralimbic regions, and also the thalamus (Silbersweig et al, 1995). This was a small study, but it supports the role of these structures in generating or modulating hallucinations in Schizophrenia patients.

In schizophrenia, there are also thought to be disturbances in attention. Luck and Gold (2008) concluded that some components of attention are compromised in schizophrenia, but other parts are comparatively unhindered. In particular, they identified that control of selection in attention was impaired. This meant that patients with schizophrenia found it more difficult to guide their attention towards inputs that were relevant to a given task. However, the processing of the selected stimuli had little or no impairment (Luck and Gold, 2000). These disturbances in attention were supported by research into biomarkers of attention. One study suggested that there could be progressive deterioration in the automatic processes of sensory discrimination, orienting and reorienting of attention as schizophrenia becomes more chronic (Jahshan et al, 2011).

Attention-deficit / hyperactivity disorder (ADHD)

ADHD is a common neurodevelopmental disorder which has been identified in both children and adults worldwide. ADHD may present in different ways between individuals, but symptoms broadly begin during childhood and may feature inattention, hyperactivity and / or impulsivity (Cortese and Coghill, 2018). The worldwide prevalence is difficult to quantify due to variations in diagnosis between countries. However, it is thought to be around 5% (Cortese and Coghill, 2018).

The cause of ADHD is not definitively known, but it is likely to be a combination of genetic and environmental factors. Genome-wide association studies (GWAS) of over 20,000 ADHD cases identified variants exceeding genome-wide significance in 12 independent loci, supporting an underlying genetic cause for ADHD (Demontis et al, 2017). In addition, some of the environmental risk factors for developing ADHD include maternal smoking and alcohol use during pregnancy, low birth weight, premature birth, and exposure to certain environmental toxins such as oregano (Cortese and Coghill, 2018). Neuroimaging studies have attempted to identify which regions of the brain function differently in people with ADHD. A meta-analysis of 55 fMRI studies showed that adults with ADHD had significant hyperactivation, mainly in the default, ventral attention, and somatomotor networks of the brain. Conversely, in children with ADHD, most of the hypoactivated areas of the brain were related to the ventral attention and the frontoparietal networks (Cortese et al, 2012). Along with the genetic research, this supports the idea that there is at least a partly biological origin for ADHD.

References

• Cortese, S. Coghill, D. (2018). Twenty years of research on attention-deficit/hyperactivity disorder (ADHD): looking back, looking forward. Evidence-based Mental Health. 21(4), pp. 173-176. PMID: 30301823.
• Cortese, S. Kelly, C. Chabernaud, C. Proal, E. Di Martino, A. Milham, M. Castellanos, X. Toward systems neuroscience of ADHD: a meta-analysis of 55 fMRI studies. American Journal of Psychiatry. 169(10), pp. 1038-55. PMID: 22983386.
• Demontis, D. et al (2017). Discovery of the first genome-wide significant risk loci for ADHD. Nature Genetics. 51(1), pp. 63-75. Available at: https://doi.org/10.1038/s41588-018-0269-7.
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• Silbersweig, D. et al. (1995). A functional neuroanatomy of hallucinations in schizophrenia. Nature. 378, pp. 176–179. Available at: https://doi.org/10.1038/378176a0.
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• Jahshan, C. et al. (2011). Automatic sensory information processing abnormalities across the illness course of schizophrenia. Psychological Medicine. 42(1), pp. 85-97. Available at: https://doi.org/10.1017/S0033291711001061.
• Luck, S. Gold, J. (2008). The Construct of Attention in Schizophrenia. Biological Psychiatry. 64(1), pp. 34-39. Available at: https://doi.org/10.1016/j.biopsych.2008.02.014.
• Posner, M. Boies, S. (1971). Components of attention. Psychological Review. 78(5), pp. 391–408. Available at: https://doi.org/10.1037/h0031333
• Styles, E. (2006). The Psychology of Attention (2nd ed.). Psychology Press. Available at: https://doi.org/10.4324/9780203968215.