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Mental effort and fatigue as consequences of monotony

  • Independent Researcher


Kurzban et al. associate mental effort and fatigue with a hypothetical mechanism able to estimate the utilities of possible actions and then select the action with a maximal utility. However, this approach faces fundamental problems. In my opinion, mental effort and fatigue are results of a conflict between the monotony of long-term activities and the novelty-processing systems.
Mental efforts and fatigue as consequences of monotony
Pavel N. Prudkov
Ecomon Ltd.
Selskohosyastvennaya street 12-A
Moscow, Russia
Kurzban et al. of the target article associate mental efforts, fatigue with a hypothetical
mechanism able to estimate the utilities of possible actions and select the action with a maximal
utility. However, this approach faces fundamental problems. In my opinion, mental effort and
fatigue are results of a conflict between the monotony of long-term activities and the novelty
processing systems.
In the target article Kurzban et al. attempt to explain such phenomena as mental effort, fatigue,
and boredom. They derive these phenomena from the functioning of a hypothetical mechanism
which mechanically estimates the utilities of different possible actions, and then selects the
action that has a maximal expected utility. The idea seems interesting but its implementation in
the article has fundamental problems. The article contains no formal description of possible
actions. Kurzban et al. arbitrarily select possible actions for each situation considered in the
article. However, such approach is incorrect because the number of possible actions is potentially
infinite in any situation (Russell& Norvig 2003). Because possible actions can be very different
the unconscious comparison of its utilities seems impossible. Kurzban et al. do not explain how
the mind compares doing mental calculations and mind wandering. The functioning of the
hypothetical mechanism is described abstractly without pointing to the situations in which
mental effort and boredom occur (see the target article’s Figure 1). As a result, it is unclear why
the output of this mechanism is mental effort and fatigue rather than, for example, fear and
anxiety. Fear and anxiety can obviously be applied to optimize costs and benefits.
Another model can be sketched as an alternative to Kurzban et al.’ approach and the theories of
depleting resources. Some details should be specified prior to the description of the model.
Mental efforts and fatigue occur in two sorts of situations. First, mental effort and fatigue usually
occur when an individual attempts to acquire novel skills. However, this activity is typically not
perceived as boring and negative. As an individual acquires a novel skill, the feeling of mental
effort usually disappears (Logan 1985). It is reasonable to assume that in this case mental efforts
simply reflect the necessary restructuring of the mind. Second, mental effort and fatigue
frequently occur when the mental activity of an individual is not difficult but long-term. In this
case, mental effort is perceived as aversive. Obviously, the experiments in the target article were
simple but long-term mental activities. The proposed model deals with such situations.
The model is based on two assumptions. First, the mind is able to maintain several processes in
parallel. One of the processes is a task which occupies the focus of consciousness while other
processes function in a background mode. Second, pursuing a long-term goal is usually an
execution of the limited number of actions, many of them should be performed over and over
again. As a result, any long-term activity is a sequence of recurring actions and therefore it is
The brain has two systems which process monotony and its antagonist, novelty. One system is
associated with the hippocampus (Grossberg & Merrill 1992; Vinogradova 2001). The system
has a representation of the ongoing situation and compares it with the input from other brain
systems. The mismatch between the representation and input means that the situation is changed
and then the brain is activated. If the representation matches the input then habituation occurs
and the brain activity is decreased (Vinogradova 2001). The second system is the novelty
seeking system which is responsible for seeking novel and varied sensations and experiences
(Zuckerman 1994; Roberti 2004). The functioning of this system is associated with the
interaction between neurotransmitter systems that are concentrated in the limbic areas of the
brain (Zuckerman 1996).
It can be hypothesized that the monotony of long-term activities leads to the engagement of both
novelty processing systems. The first system attempts to inhibit the ongoing task and the second
system tries to activate any parallel processes. The feeling of mental effort reflects the
competition between the task, which suffers from inhibition, and other processes. Fatigue and
boredom mirror the inhibition of the ongoing task and habituation. The reduction of performance
in such tasks as vigilance tasks results from the inhibition of the task by the first system.
Accordingly, changes in the situation may result in the improvement of performance owing to
the activation of the brain by this system. The decrement in performance when participants
perform sequentially several tasks can be explained on the basis that these tasks share the
common experimental context (one experimenter, one room, etc) and therefore the situation can
be considered monotonous.
The relationship between reward and fatigue can be hypothesized as a consequence of the
interaction between the novelty processing systems and the reward system. Indeed, novelty
seeking should be maximally intense in neutral situations because seeking novel sensations in
very dangerous or very pleasant situations is hardly a useful strategy. As a result, reward can
inhibit the novelty processing systems thus decreasing the feeling of fatigue.
The feelings of fatigue and boredom in long-term activities possibly reflect a conflict between
various brain systems. In my opinion, the ability to pursue long-term goals having no innate
basis is the main characteristic distinguishing humans from other animals (Prudkov 1999, 2005).
The experiments described in the target article are obvious examples of pursuing such goals.
Indeed, subjects participated in the vigilance task not because they were hungry, sexually
unsatisfied, or frightened. The ability is maintained by the prefrontal lobes (Luria 1966, 1982).
This is a young structure maximally advanced in humans (Luria 1966).
However, long-term activities often are monotonous. Monotony results in the activation of the
novelty processing systems. These systems are maintained by ancient limbic structures, which
also maintain other biological goals (Kolb & Whishaw 2002). For the novelty processing
systems, pursuing social goals is a neutral situation because the limbic structures are weakly
involved in processing social goals. Therefore, in this case the novelty processing systems should
be activated thereby hindering social activities.
Kurzban et al. ask ‘why, if revising a manuscript contributes to the achievement of key long-term
goals does it feel aversively effortful?’ (sect. 2.1, para. 4). They attempt to respond to this
question but the target article does not contain a clear answer. The proposed model, however,
offers a simple solution: because a mature scientist frequently revises manuscripts and this
activity becomes monotonous.
Grossberg, S, Merrill, J.W.L. (1992). A neural network model of adaptively
timed reinforcement learning and hippocampal dynamics. Cognitive Brain Research 1, 3–38.
Kolb, B & Whishaw, I.Q |(2003): Fundamentals of human neuropsychology. Worth Publishers
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Luria, A.R. (1966). Higher cortical functions in man. Tavistock Publications, Andover, Hants.
Luria, A.R. (1982). Variations of the “frontal” syndrome. In Luria A.R, Homskaya E.D. (eds.),
Functions of the frontal lobes of the brain, pp. 8-48, Nauka (in Russian).
Prudkov, P.N. (1999) Origin of culture: Evolution applied another mechanism. PSYCOLOQUY
Prudkov, P.N. (2005). Motivation rather than imitation determined the appearance of language.
Behavioral and Brain Sciences, 28, 142-143.
Roberti, J.W. (2004) A review of behavioral and biological correlates of sensation seeking.
Journal of Research in Personality 38, 256–279
Russell, S. J.; Norvig, P. (2003), Artificial Intelligence: A Modern Approach (2nd ed.), Upper
Saddle River, New Jersey: Prentice Hall,
Vinogradova, O.S. (2001) Hippocampus as comparator: role of the two input
and two output systems of the hippocampus in selection and registration of information
Hippocampus 11,578–598
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York: Cambridge Press
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seeking: A comparative approach. Neuropsychobiology, 34, 125–129.
... This "goldilocks effect" is already evident in 7-8 months old infants who allocate attention evenly between neither overly simple nor overly complex stimuli (Kidd et al., 2012). The effect appears to be supported by the brain's two systems for processing monotony and novelty, one in the hippocampus and the other associated with the limbic areas of the brain (Prudkov, 2013). Thus, people are predisposed to find an individually appropriate amount of novelty, variety and complexity in their daily tasks and experiences, or an optimal level of arousal and stimulation (Berlyne, 1960;Fiske & Maddi, 1961;Hunt, 1969). ...
... Tasks requiring too little cognitive engagement are boring and aversive, and individuals therefore seek variety to find an optimal midpoint in their everyday activities (e.g., Shenhav, Rand, et al., 2017). This general tendency is based on an empirically well-documented motivation for combating monotony and boredom resulting from repetition (e.g., Baumgartner & Steenkamp, 1996;Faison, 1977;Prudkov, 2013;Zuckerman, 1994). Its importance is seen in people's attempts to manage variety in the process of goal attainment in general (e.g., Etkin & Ratner, 2011;Fishbach & Dhar, 2005), as well as in many specific behaviors such as consumer purchases (e.g., Goukens et al., 2007;Raju, 1980;Ratner et al., 1999) and travel (e.g., Hu et al., 2002). ...
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... Similarly, malignant tumor cells utilize free fatty acids and ketones released by neighboring catabolic cells for energy production (12,22), which can also be realized by glutamine metabolization through TCA cycle (23). Mitochondrial OXPHOS, driven by glutamine, is a major source for ATP synthesis under hypoxic conditions (24). These observations suggest that targeting particular metabolic pathways in cancer may be an effective strategy for cancer therapy. ...
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To explain the origin of abstract thinking, Gabora (1998) uses an analogy between the origin of life and the origin of culture. I suggest that this analogy is wrong. The origin of culture was a consequence of changes in the motivational system of early humans. A possible scenario for this process is considered.
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Argues that automaticity and skill are closely related but are not identical. Automatic processes are components of skill, but skill is more than the sum of the automatic components. Automaticity and skill are similar in that both are learned through practice. Implications are discussed for (1) current studies of the co-occurrence of properties of automaticity, (2) the relation between multiple resources and automaticity, and (3) the relation between control and automaticity. It is concluded that many of the issues in automaticity may be resolved or at least revised by considering the role that automatic processes play in performing a skill. (French abstract) (3 p ref) (PsycINFO Database Record (c) 2012 APA, all rights reserved)
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Arbib derives the origin of language from the emergence of a complex imitation system; however, it is unlikely that this complication could occur without a prior complicating within the imitated systems. This means that Arbib's hypothesis is not correct, because the other systems determined the appearance of language. In my opinion, language emerged when the motivational system became able to support goal-directed processes with no innate basis.
To explain the origin of abstract thinking, Gabora (1998) uses an analogy between the origin of life and the origin of culture. I suggest that this analogy is wrong. The origin of culture was a consequence of changes in the motivational system of early humans. A possible scenario for this process is considered.
The purpose of this paper is to provide a review of studies related to sensation seeking. A description of sensation seeking and methodology to measure various preferences for sensation seeking is identified. In addition, the relation of sensation seeking with other personality factors is also examined. Various behavioral expressions of sensation seeking in the domains of vocational choices, habits, hobbies, risk perception, and risk appraisal are explored. Furthermore, biological characteristics related to sensation seeking are highlighted. Lastly, areas for future research are suggested, especially the investigation of non-risky forms of sensation seeking in young adults.
Processing of multimodal sensory information by the morphological subdivisions of the hippocampus and its input and output structures was investigated in unanesthetized rabbits by extracellular recording of neuronal activity. Analysis shows principal differences between CA3 neurons with uniform multimodal, mainly inhibitory, rapidly habituating sensory responses, and CA1‐subicular neurons, substantial parts of which have phasic reactions and patterned on‐responses, depending on the characteristics of the stimuli. These differences result from the organization of the afferent inputs to CA1 and CA3. Analysis of neuronal responses in sources of hippocampal inputs, their electrical stimulation, and chronic disconnection show the greater functional significance of the brain‐stem reticular input for tonic responses characteristic of CA3. This input signal before entering the hippocampus is additionally preprocessed at the MS‐DB relay, where it becomes more uniform and frequency‐modulated in the range of theta‐rhythm. It is shown that the new sensory stimuli produce inhibitory reset, after which synchronized theta‐modulation is triggered. Other stimuli, appearing at the background of the ongoing theta, do not evoke any responses of the hippocampal neurons. Thus, theta‐modulation can be regarded as a mechanism of attention, which prolongs response to a selected stimulus and simultaneously protects its processing against interference. The cortical input of the hippocampus introduces highly differentiated information analyzed at the highest levels of the neocortex through the intermediary of the entorhinal cortex and presubiculum. However, only CA1‐subiculum receives this information directly; before its entrance into CA3, it is additionally preprocessed at the FD relay, where the secondary simplification of signals occurs. As a result, CA3 receives by its two inputs (MS‐DB and FD) messages just about the presence and level of input signals in each of them, and performs relatively simple functions of determination of match/mismatch of their weights. For this comparator system, the presence of signal only in the reticulo‐septal input is equivalent to quality of novelty. The cortical signal appears with some delay, after its analysis in the neocortex and shaping in the prehippocampal structures; besides, it is gradually increased due to LTP‐like incremental changes in PP and mossy fiber synapses. The CA3 neurons with potentiated synapses of cortical input do not respond to sensory stimuli; that is, the increased efficacy of the cortical signals can be regarded as “familiarity” of a signal, terminating the reactive state of the CA3 neurons. The integrity of both inputs is necessary for gradual habituation of sensory responses in the hippocampus. The output signals of CA3 following in the precommissural fornix to the output relay‐LS nucleus and to the brain‐stem structures have strong regulatory influence on the level of brain activity (arousal), which is an important condition for processing and registration of information. The primary targets of this output signal are raphe nuclei, which suppress activity of the ascending excitatory RF. In the background state, activity of the CA3 neurons through the intermediary of raphe keeps RF under tonic inhibitory control. Inhibition of the majority of CA3 pyramidal neurons during a novel stimulus action decreases the volume of its output signal to raphe and releases RF from tonic inhibition (increase in level of activity of the forebrain, arousal). When the responses of CA3 neurons habituate, the initial high background activity is reinstated, as well as tonic suppression of RF. Analysis of the second output of CA3 (by Schaffer's collaterals to CA1) shows that activity in this pathway can block access of cortical signals from PP to CA1 neurons by action upon the local system of inhibitory neurons, or by shunting the propagation of signals in apical dendrites. Thus, CA3 can act as a filter controlling the information transmission by CA1; such transmission at any given moment is allowed only in those CA1 neurons which receive SC from CA3 neurons, responding to the sensory stimulus by suppression of their activity. Disconnection of the CA3 output fibers results in disappearance of habituation in all its target structures (raphe, RF, CA1). The output signal of CA1‐subiculum follows by postcommissural fornix to the chain of structures of the main limbic circuit: mammillary bodies (medial nucleus), anterior thalamic nuclei (mainly antero‐ventral nucleus), and cingulate limbic cortex (mainly posterior area). In each of these links, the signal is additionally processed. Habituation is nearly absent in these structures; instead, strong incremental dynamics are observed. Various types of reaction shaping, often with changes in level and structure of background activity, are observed in them. Within this output circuit, the farther is the output structure from the hippocampus, the more repetitions of stimulus are required for shaping the sensory response. That is why this system is regarded as a chain of integrators, where each one starts to respond only after reaction develops at the previous link, and as a delay line, preventing premature fixation of spurious, irrelevant, low probability signals. The responses in the higher link of this system, the posterior limbic cortex, may be regarded as the ultimate signal for information fixation in the nonprimary areas of the neocortex. In this way, the two morpho‐functional circuits, regulatory (based on CA3) and informational (based on CA1), perform the unified functions of attention and initial stages of memory trace fixation. Hippocampus 2001;11:578–598. © 2001 Wiley‐Liss, Inc.
A neural model is described of how adaptively timed reinforcement learning occurs. The adaptive timing circuit is suggested to exist in the hippocampus, and to involve convergence of dentate granule cells on CA3 pyramidal cells, and N-methyl-D-aspartate (NMDA) receptors. This circuit forms part of a model neural system for the coordinated control of recognition learning, reinforcement learning, and motor learning, whose properties clarify how an animal can learn to acquire a delayed reward. Behavioral and neural data are summarized in support of each processing stage of the system. The relevant anatomical sites are in thalamus, neocortex, hippocampus, hypothalamus, amygdala and cerebellum. Cerebellar influences on motor learning are distinguished from hippocampal influences on adaptive timing of reinforcement learning. The model simulates how damage to the hippocampal formation disrupts adaptive timing, eliminates attentional blocking and causes symptoms of medial temporal amnesia. Properties of learned expectations, attentional focussing, memory search and orienting reactions to novel events are used to analyze the blocking and amnesia data. The model also suggests how normal acquisition of subcortical emotional conditioning can occur after cortical ablation, even though extinction of emotional conditioning is retarded by cortical ablation. The model simulates how increasing the duration of an unconditioned stimulus increases the amplitude of emotional conditioning, but does not change adaptive timing; and how an increase in the intensity of a conditioned stimulus 'speeds up the clock', but an increase in the intensity of an unconditioned stimulus does not. Computer simulations of the model fit parametric conditioning data, including a Weber law property and an inverted U property. Both primary and secondary adaptively timed conditionings are simulated, as are data concerning conditioning using multiple interstimulus intervals (ISIs), gradually or abruptly changing ISIs, partial reinforcement and multiple stimuli that lead to time-averaging of responses. Neurobiologically testable predictions are made to facilitate further tests of the model.
Higher cortical functions in man Variations of the " frontal " syndrome
  • A R Luria
  • Andover
  • Hants
  • A R Luria
Luria, A.R. (1966). Higher cortical functions in man. Tavistock Publications, Andover, Hants. Luria, A.R. (1982). Variations of the " frontal " syndrome. In Luria A.R, Homskaya E.D. (eds.), Functions of the frontal lobes of the brain, pp. 8-48, Nauka (in Russian).