ScienceDaily (June 24, 2009) — Answering a phone call while cooking dinner ... walking to work while texting ... driving while listening to the radio -- all without having to think about it. After plenty of practice, people can do a lot of things on automatic pilot and simultaneously..

However, for people with schizophrenia that is a different story. .

Dutch researcher Tamar van Raalten investigated whether a disruption to the automation process, learning by repetition to do something on automatic pilot, explains why people with schizophrenia can process less information. She established that it is not the automation process but the processing of new information that failed.

Van Raalten first of all investigated the role of the working memory during automation. .

Our working memory ensures that we remember transient pieces of information such as a telephone number. Van Raalten asked study subjects, positioned in an fMRI scanner, to perform tests in which they had to remember a series of letters. Normally your working memory is then fully active. Yet the more the tests were repeated, the lower the brain activity in the areas involved in working memory function. This activity was also not compensated for by other parts of the brain involved in (long-term) memory. By automating the letter series, the study subjects therefore released working memory capacity so that it could once again process new information..

Van Raalten established that the decrease in activity was due to another function of the working memory; the restructuring of incoming information..

For example, you first of all remember a telephone number as a series of independent figures. But your working memory ensures that this series is divided into chunks. Instead of 1-1-3-2-6-7-3-4-4-5, you remember 113-267-3445. In this way you only have to remember three chunks and not ten individual numbers. This characteristic ensures that once a task has become fully automated, after sufficient training, it can be performed without further involvement of the working memory. .
As a result of this you can do other things alongside the automated task..

Patients with schizophrenia can, however, process less information than healthy people. Their brains function less efficiently..

It was expected that a faltering working memory in schizophrenia patients ensured that automation did not proceed well, as a result of which they could not release working memory capacity.
However, tests on schizophrenia patients revealed that after training the brain activity decreased in the same manner as was the case for healthy study subjects. Although the working memory does not function well in schizophrenic patients, the automation of tasks proceeded without problems..

It might therefore be expected that schizophrenia patients could also more easily perform a second task besides the first, automated task. Yet the released capacity of the working memory could not be used for a new task..

Following this 'surprise' result Van Raalten investigated where the problem could possibly be located..

During new tests she discovered that the working memory in schizophrenia patients mainly struggled with the processing of information that continually changed.
Consequently, schizophrenic patients may have more of a tendency to adopt automatic strategies in circumstances that demand flexible behaviour.<
This inability to satisfactorily process new information can lead to stereotypical behaviours, which are an important characteristic of psychiatric disorders such as schizophrenia and autism..

Van Raalten's research reveals that the working memory is not solely [ only ] responsible for automation. .

She proposes targeting future research at other systems that interact with the working memory in automation. Furthermore, medication might also play a role in the automation performed by patients. Research is currently taking place at University Medical Centre Utrecht into the role of medication in the automation process. Tamar van Raalten carried out her research at University Medical Centre Utrecht. Her research was funded by the Vidi grant of Nick Ramsey. In 2002, he received a Vidi grant from NWO for his research into the brain mechanisms underlying learning.

Significantly, neurogenesis takes place in only one region of the hippocampus – the dentate gyrus. Our computational model [19] imparts a unique role to this region in encoding the specific details of episodic memories (Figure 1). Moreover, the constant neural turnover in the dentate region ensures that each new event is encoded uniquely, without interfering with previously or subsequently stored memories [18,19]. The associational pathways in the CA3 and CA1 regions of the hippocampus can integrate this novel experience into prior learning episodes and perform associative retrieval. The unique feature of the new neurons that enables them to generate distinctive episodic memories without interference is their turnover. This turnover relies on two processes: selective cell death, which eliminates redundant units, and maturation, which transforms young, plastic units into less plastic ones. Both groups are continuously replaced by neurogenesis; hence the turnover [20,21,23,24] (Box 1; Figure 2). Experimental manipulations that reduce the number of new neurons, such as irradiation (Box 2), have contributed further to our understanding of possible functions of neurogenesis in the normal brain. Although many hippocampus- dependent tasks involve different aspects of associative memory, not every task that requires the hippocampus also requires the new neurons (for a review, see Ref. [25]). For example, spatial learning by rats in the Morris water maze is disrupted by hippocampal lesions [26] but not by irradiation [27]. However, although irradiated animals learn the water maze at a normal rate, their long-term memory retention of the hidden-platform location is greatly impaired relative to that in controls when they are re-tested four or more weeks later [27]. This finding is consistent with predictions of our computational model [18,19] that the new neurons are important for forming highly distinctive memories for individual episodes, thereby protecting them against retroactive interference (Figure 1). In addition to this role in encoding specific details of events, the new neurons seem to be crucial for linking events across time when these events are part of the same context. Thus, animals that lack new hippocampal neurons show deficits on tasks that seem to require contextualmemory abilities, including trace conditioning [28], contextual fear conditioning [29] and delayed non-match to sample (DNMS) with long delays [29]. However, they perform normally on corresponding non-hippocampal control tasks: delay conditioning [28], cued fear conditioning [29] and DNMS with short delays [29]. Whereas our previous delay conditioning [28], cued fear conditioning [29] and DNMS with short delays [29]. Whereas our previous model [18,19] accounts for the role of the new neurons in forming distinct event memories, the data reviewed here suggest that these neurons also have a role in linking events across time when the events are part of a common context. A novel proposal for the role of neurogenesis in temporal context: the functional cluster hypothesis Understanding the role of the new neurons in temporal coding requires a more elaborate model. Traditionally, the hippocampus is thought to be responsible for associating multiple stimuli into a single episodic memory. Synaptic integration of multiple inputs carrying sensory information can occur via spatial summation of individual synaptic potentials in dendrites of granule neurons. Such synaptic responses are usually mediated by two principal types of glutamate receptors, AMPA and NMDA. AMPA is responsible for short-term interactions and NMDA for long-lasting changes in excitability, such as during learning. However, temporal summation beyond the range of milliseconds cannot be explained using traditional biophysical mechanisms. Temporal summation of events on the order of minutes, hours or days might be required to solve the learning tasks described here. Neurogenesis is ideally suited to encode such events; it is an ongoing process that begins with proliferation of neural precursors and ends with fully functional mature neurons (Box 1). One striking feature of proliferation is that it occurs in clusters. The dividing precursors are often seen in groups of 2–10 cells, tightly packed in the subgranular zone (SGZ) of the dentate gyrus (Figure 3). These clusters disperse along the SGZ within several days, presumably by migration and/or attrition due to cell death. Differentiation of cells within the clusters into neurons is characterized by the expression of specific proteins, extension of axons and dendrites, and synaptogenesis [30]. Importantly, the excitatory influences, in the form of depolarizing GABA-mediated responses, are formed long before the new neurons integrate with the dense inhibitory circuitry in the dentate gyrus, which enables new neurons to sustain much higher activity levels than mature granule cells [31]. Hypothetically, one can envisage 'waves' of neurons that respond to afferent stimulation and send impulses from neurons belonging to a cluster, via mossy fibres, to CA3 for association of their common inputs by CA3 axon collaterals. New neurons within a cluster, innervated by different perforant path inputs, will respond to different features of an event. Some will fire in response to persistent aspects of the environment, such as odours, stationary objects and boundaries, which we shall refer to as the context. Other neurons might respond to more transient aspects, such as a tone or a shock. The highly plastic new neurons will become tuned to this constellation of features and should respond consistently when they experience the same context again. Using plastic recurrent connections, targets in CA3 can link the transient features with the context, thus temporally linking items into a single episode. This enables cued recall of the entire event from a single item, which provides the basis of episodic-memory encoding and retrieval (Figure 2). The new neurons will then either die or mature and become less plastic, ich will protect the memory from interference by later learning. Subsequent events could be encoded by other 'waves' of generations of new neurons. This 'functional cluster' hypothesis shares with previous models the assumption of 'superior plasticity' of the new neurons [18,20–22] and is consistent with a recently proposed model of a mechanism that separates ongoing experience into temporally tagged, unique event memories [32]. More specifically, the cluster model proposed here (not to be confused with the 'clustered plasticity model' of Govindarajan et al. [33], which is a single-neuron model) assigns a unique role to the clusters of cells born at approximately the same time and their impact on the encoding of event memories in CA3.

20 Facts You Must Know About Working Memory

It's important to understand the characteristics of working memory when you're designing nearly anything that requires mental effort.
Without adapting learning experiences to the learner's cognitive architecture, instructional design is hit or miss.
Current research in this area is demonstrating that working memory (a theoretical structure) is a dynamic and flexible entity.

The Basics

Working memory used to be called short-term memory. It was redefined to focus on its functionality rather than its duration. Working memory can be thought of as the equivalent of being mentally online. It refers to the temporary workspace where we manipulate and process information. No one physical location in the brain appears to be responsible for creating the capacity of working memory. But several parts of the brain seem to contribute to this cognitive structure.

Capacity

Working memory is characterized by a small capacity. It can hold around four elements of new information at one time. Because learning experiences typically involve new information, the capacity of working memory makes it difficult to assimilate more than around four bits of information simultaneously. The capacity of working memory depends on the category of the elements or chunks as well as their features. For example, we can hold more digits in working memory than letters and more short words than long words. The limitations on working memory disappear when working with information from long-term memory (permanent storage) because that information is organized into schemata. Schemata are higher order structures made up of multiple elements that help to reduce the overload on working memory.

Duration

Novel information in working memory is temporary. It is either encoded into long-term memory or it decays or is replaced. Unless it is actively attended to or rehearsed, information in working memory has a short duration of around 20 seconds. Similar to the capacity issue, it takes mental effort to hold information in working memory for an extended time and can also be a cause of cognitive overwhelm.

Interactions with Long-term Memory

There is a continuous transfer of of information between long-term memory and working memory—both retrieval and transfer. Information is retrieved from long-term memory into working memory in order to make sense out of new information. Information that we attend to and integrate into our knowledge structures is transferred or encoded into long-term memory.

Individual Differences

Current research demonstrates that individual differences in working memory capacity may account for differences in performance of information processing tasks, like reading and note-taking. In studies with children, those who have a poor ability to store material over brief periods of time (difficulties with working memory) fail to progress normally in tasks related to literacy. An individual's developmental age and level of expertise probably account for differences in working memory. For example, facilitating learning can be helpful for novices but detrimental to experts.

Cognitive Load

Cognitive load refers to the demands placed on working memory in terms of storage and information processing. Intrinsic load is caused by the nature of the learning task and extraneous load refers to the demands caused by the format of the instruction. Cognitive load theory states that traditional instructional techniques can overload working memory because they don't account for intrinsic and extraneous load. Instructional designers can facilitate learning by considering and accommodating different loads. Germane load refers to the demands placed on working memory when learners are engaged in conscious cognitive processing to construct schemata while acquiring new knowledge. Increasing the germane load can most likely assist the learning process.
Science News Share Blog Cite Print Email Bookmark Discovery of Stem Cell Illuminates Human Brain Evolution, Points to Therapies ScienceDaily (May 25, 2010) — UCSF scientists have discovered a new stem cell in the developing human brain. The cell produces nerve cells that help form the neocortex -- the site of higher cognitive function -- and likely accounts for the dramatic expansion of the region in the lineages that lead to humans, the researchers say.

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