PLANNING: Planning is the mental process that allows us to choose the necessary actions to reach a goal, decide the right order, assign each task to the proper cognitive resources, and establish a plan of action. Planning has been defined as the identification and organisation of the steps and elements needed to carry out an intention or achieve a goal (Lezak, 1995). Planning is the ability to set goals, to monitor performance so as to reach the goals, and to make corrections in the course adopted, in order to ensure that the goal is attained. Goal setting involves not only identifying the final goal, but also identifying the intermediate goals which have to be attained in order to achieve the final goal. The intermediate goals may be in conformity with the final goal or may be contradictory to the final goal. The essence of planning consists of attaining a goal through a series of intermediate steps. The subject plans in advance the complete sequence of moves required to solve the problem, and in order to do so anticipates the consequences of one or another course of action (Baker et al., 1996) Neuroscience of planning ● It is generally assumed individuals presented with a complex problem engage in preliminary planning and that this planning involves prefrontal areas associated with planning. Supportive evidence comes from patients with damage to prefrontal areas, who typically have impaired planning and problem solving (Szczepanski & Knight, 2014). There was increased activation of the dorsolateral prefrontal cortex when participants solved complex versions of this task. In sum, the prefrontal cortex is important in planning on many problem-solving tasks. However, many other brain areas are also involved (Szczepanski & Knight, 2014). ● Dagher et al. (1999) used the Tower of London task in which coloured discs must be moved one by one from an initial state to match the goal state. There was increased activation of the dorsolateral prefrontal cortex when participants solved complex versions of this task. In sum, the prefrontal cortex is important in planning on many problem-solving tasks. However, many other brain areas are also involved (Szczepanski & Knight, 2014). ● Crescentini et al. (2012) supported the distinction between plan production and plan execution using simple versions of the Tower of Hanoi task. The dorsolateral prefrontal cortex was more active during initial planning than plan execution. In contrast, posterior temporal areas, inferior frontal regions and dorsolateral premotor cortex were more activated during plan execution. ● Lesion studies have shown that left frontal lesions are associated with deficits of planning (Shallice, 1982). Moreover, the studies have found that the inappropriate organizational strategies associated with poor planning are greater in bilateral prefrontal ● lesions(Owens, Brownes, Shakan, Poltrey & Robbins,1990). Imaging studies have found that increased activation of the left prefrontal cortex is associated with more efficient planning in terms of longer time to plan and less number of moves. Planning using the Tower of London test (Morris, Ahmed, Syed & Toone, 1993) activates a wide network consisting of the dorsal prefrontal cortex is associated with the components of generating, selecting and/or remembering mental moves(Rowe, Owen, Johnsrude & Passingham, 2001). Planning is a complex Function with many components such as speed of processing, mental flexibility, working memory, Regulation of thought, error correction ability. Importance of planning 1. In problem solving: ● Newell and Simon (1972) assumed problem solvers typically engage in limited planning because of the constraints of short-term memory capacity. Patsenko and Altmann (2010) obtained strong support using Tower of Hanoi problems. Sometimes they added, deleted or moved discs during participants’ eye movements so they were not directly aware of the change. These changes only minimally disrupted performance, strongly suggesting that the participants’ next move was triggered by the current state of the problem rather than a preformed plan. There are substantial individual differences in planning for problem-solving tasks. Koppenol-Gonzalez et al. (2010) found with the Tower of London task that some participants engaged in efficient planning (considerable preplanning of moves and high performance). In contrast, other participants showed very little evidence of effective planning (short period of preplanning and numerous errors). Most individual differences in performance on this task can be explained by the single factor of planning ability (Debelak et al., 2016). The amount of planning is very flexible. Delaney et al. (2004) found little evidence of planning on water-jar problems when participants chose their preferred strategy. However, instructions to generate the complete solution before making any moves led to detailed planning andfaster problem solution. Morgan and Patrick (2013) argued that increasing the cost of accessing important task-relevant information (the goal state) on the Tower of Hanoi task would lead to more planning. It produced increased planning and also led to problems being solved in fewer moves. If planning involves deliberate processes, we would expect problem solvers to be consciously aware of it. Evidence suggesting important problem-solving processes occur below the level of conscious awareness was reported by Paynter et al. (2010) using event-related potentials (ERPs; see Glossary). They observed clear differences in the ERPs associated with correct and incorrect moves early in the problem when no behavioural evidence indicated participants were making progress. 2. Importance of planning in academic writing: Writing consists of three phases: planning, sentence generation, and revising (Mayer, 2004). However— like the similar stages we discussed in connection with spoken language—these tasks often overlap in time (Kellogg, 1994, 1996; Ransdell & Levy, 1999). For example, you may be planning your overall writing strategy while you generate parts of several sentences. Most people begin a formal writing project by generating a list of ideas; this process is called prewriting. Prewriting is difficult and strategic—very different from many relatively automatic language tasks (Collins, 1998; Torrance et al., 1996). As you can imagine, students differ enormously in the quality of the ideas they generate during this phase (Bruning et al., 1999). According to the research, good writers are more likely than poor writers to spend high-quality time in planning during prewriting (Hayes, 1989). Some people prefer to outline a paper before they begin to write (Kellogg, 1998; McCutchen et al., 2008). An outline may help you avoid overloaded attention. You’ve probably had the experience of beginning to write a paper, only to find that each of several interrelated ideas needs to be placed first! An outline can help you sort these ideas into an orderly, linear sequence, although not all writers find that an outline is helpful (Engle, 2011). Writing involves proposing or planning, translating, transcribing, and evaluating and revising the text that has been produced. Shifts from one writing process to another depend on a monitor or control system. Good writers use acknowledge-transforming rather than knowledge-telling strategy and devote more time to revision. Expert writers attain a knowledge-crafting stage emphasising the reader’s needs. The working memory system (especially the central executive) is heavily involved in the writing process. Word processing often enhances writing quality, probably by encouraging revision and thinking processes. Pauses account for over half of writing time. Medimorec and Risko (2017) analysed the pause data of students writing narrative essays (about a memorable day) and argumentative essays (about mobile-phone use in schools). Pauses occurred most often at paragraph boundaries, followed by sentence boundaries, suggesting they often indicate planning processes. Limpo and Alves (2018) studied key aspects of writing dynamics using the triple-task technique. Limpo and Alves (2018) found that Firstly, time spent on planning is reduced during the course of writing. Second, the time spent on the revising process increased over time. Third, all three writing processes (i.e., planning, translating and revising) occurred during all phases of the writing process. Fourth, reaction times to the occasional beeps were slowed most during revising and least during translating. These findings indicate that revising was the most cognitively demanding process, followed by planning and translating in that order. Thus, as Levy and Ransdell (1995) found, episodes of planning and revising were shorter than translating or text generation. Role of planning: planning-control model Glover (2004) proposed a planning-control model of goal-directed action towards objects. According to this model, we initially use a planning system followed by a control system but the two systems often overlap in time. Here are the main features of the two systems: (1) Planning system ● It is used mostly before the initiation of movement. ● It selects an appropriate target (e.g., cup of coffee), decides how it should be grasped and works out the timing of the movement. ● It is influenced by factors such as the individual’s goals, the nature of the target object, the visual context and various cognitive processes. ● It is relatively slow because it uses much information and is influenced by conscious processes. It is used during the carrying out of a movement. ● It ensures movements are accurate, making adjustments, if necessary, based on visual feedback. Efference copy (see Glossary) is used to compare actual with desired movement. Proprioception is also involved. ● It is influenced by the target object’s spatial characteristics (e.g., size; shape; orientation) but not by the surrounding context. ● It is fairly fast because it uses little information and is not susceptible to conscious influence. According to the planning-control model, most errors in human action stem from the planning system. In contrast, the control system typically ensures actions are accurate and achieve their goal. Many visual illusions occur because of the influence of visual context. Since information about visual context is used only by the planning system, responses to visual illusions should typically be inaccurate if they depend on the planning system but accurate if they depend on the control system. There are similarities between the planning-control model and Milner and Goodale’s perception action model. However, Glover (2004) focused more on the processing changes occurring during action performance. Findings Glover et al. (2012) compared the brain areas involved in planning and control using a planning condition (prepare to reach and grasp an object but remain still) and a control condition (reach out immediately for the object). There was practically no overlap in the brain areas associated with planning and control. This finding supports the model’s assumption that planning and control processes are separate. According to the planning-control model, various factors (e.g., semantic properties of the visual scene) influence the planning process associated with goal-directed movements but not the subsequent control process. This prediction was tested by Namdar et al. (2014). Participants grasped an object in front of them using their thumb and index finger. The object had a task-irrelevant digit (1, 2, 8 or 9) on it. As predicted, numerically larger digits led to larger grip apertures during the first half of the movement trajectory but not the second half (involving the control process). According to Glover (2004), action planning involves conscious processing followed by rapid non-conscious processing during action control. These theoretical assumptions can be tested by requiring participants to carry out a second task while performing an action towards an object. According to the model, this second task should disrupt planning but not control. However, Hesse et al. (2012) found a second task disrupted planning and control when participants made grasping movements towards objects. Thus, planning and control can both require attention resources. According to the model, visual illusions occur because misleading visual context influences the initial planning system rather than the later control system. Roberts et al. (2013) required participants to make rapid reaching movements to a Müller-Lyer figure. Vision was available only during the first 200 ms of movement or the last 200ms. The findings were opposite to those predicted theoretically – performance was more accurate with early vision than late vision. Elliott et al. (2017) explained the above findings with their multiple process models. According to this model, performance was good when early vision was available because of a control system known as impulse control. Impulse control “entails an early, and continuing, comparison of expected sensory consequences to perceived sensory consequences to regulate limb direction and velocity during the distance-covering phase of the movement” Evaluation Glover’s (2004) planning-control model has proved successful in various ways. First, it successfully developed the common assumption that motor movements towards an object involve successive planning and control processes. Second, the assumption that cognitive processes are important in action planning is correct. Third, there is evidence (e.g., Glover et al., 2012) that separate brain areas are involved in planning and control. What are the model’s limitations? First, the planning system involves several very different processes: “goal determination; target identification and selection; analysis of object affordances [potential object uses]; timing; and computation of the metrical properties of the target such as its size, shape, orientation and position relative to the body” (Glover et al., 2012). This diversity sheds doubt on the assumption there is a single planning system. Second, the model argues control occurs late during object-directed movements and is influenced by visual feedback. However, there appears to be a second control process (called impulse control by Elliott et al., 2017) operating throughout the movement trajectory and not influenced by visual feedback. Third, and related to the second point, the model presents an over simplified picture of the processes involved in goal-directed action. More specifically, the processing involved in producing goal-directed movements is far more complex than implied by the notion of a planning process followed by a control process. For example, planning and control processes are often so intermixed that “the distinction between movement planning and movement control is blurred” (Gallivan et al., 2018). Fourth, complex decision-making processes are often involved when individuals plan goal-directed actions in the real world. For example, when planning, tennis players must often decide between a simple shot minimising energy expenditure and risk or injury or a more ambitious shot that might immediately win the current point (Gallivan et al., 2018). Fifth, the model is designed to account for planning and control processes when only one object is present or of interest. In contrast, visual scenes in everyday life are often far more complex and contain several objects of potential relevance (see below). Role of planning: changing action plans We all have considerable experience of changing, modifying and abandoning action plans with respect to objects in the environment. How do we resolve competition among action plans? According to Song (2017) “Critical is the existence of parallel motor planning processes, which allow efficient and timely changes.” What evidence indicates we often process information about several different potential actions simultaneously? Suppose participants are given the task of reaching rapidly towards a target in the presence of distractors (Song & Nakayama, 2008). On some trials, their reach is initially directed towards the target. On other trials, their initial reach is directed towards a distracter but this is corrected in mid-flight producing a strongly curved trajectory. Song and Nakayama’s key finding was that corrective movements occurred very rapidly following the onset of the initial movement. This finding strongly implies that the corrective movement had been planned prior to execution of the initial incorrect movement. Song (2017) discussed several other studies where similar findings were obtained. He concluded, “The sensori-motor system generates multiple competing plans in parallel before actions are initiated this concurrent processing enables us to efficiently resolve competition and select one appropriate action rapidly” Factors that influence planning Ability to represent the problem mentally (Nitschke et al., 2012) influences planning; participants who take the time to clearly represent the problem tend to plan better and arrive at the solution faster. Instructions given to plan ensures better planning (Delaney et al., 2004); participants who have been instructed to plan the entire task before making a move performed better. Having access to important task-relevant information (eg., the goal state) improves planning (Morgan and Patrick, 2013); participants who were clear about the goal state planned to reach the goal more easily. Problem solving ability is correlated to planning ability. Damage to the prefrontal cortex results in poorer planning (Goel and Grafman, 1995, Colvin et. al. 2001). The Tower of London Test Planning is tested using the Tower of London Test (Shallice, 1982). The initial TOL was devised by Tim Shallice (1982) as an improvement upon the Tower of Hanoi (TOH) task. Shallice employed his TOL to assess planning in patients with frontal lobe lesions. The test evaluates the subject's ability to plan and anticipate the results of their actions to achieve a predetermined goal. The test consists of two identical wooden boards. Each board measures 38 cms long and 13 cms wide. Each board is fitted with 3 round pegs of different sizes. The first peg is 18 cms inheight, the second is 11 cms in height and the third is 7 cms in height. There are three wooden balls, painted red, green and blue respectively. Each ball has a bore in the middle. The tallest can hold 3 balls. The second tallest can hold two balls, while the shortest can hold one ball. peg.
