Tuesday, February 11, 2014

Edwards, et al - Dreaming and Insight


From Frontiers in Psychology: Consciousness Research, this new open access article looks at the potential of dreams to offer personal insight into our lives. The research was spurred by
the presence in dreams of metaphorical representations of waking life indicates the possibility of novel insight as an emergent feature of such metaphorical mappings.
The authors conclude that we might need to distinguish better between "aha!" moments of finding sources of dream images in our daily lives and "aha!" moments connected to personal insight as a result of dream content.

Dreaming and Insight

Christopher L. Edwards [1], Perrine M. Ruby [1,2], Josie E. Malinowski [3], Paul D. Bennett [1] and Mark T. Blagrove [1]
1. Department of Psychology, Swansea University, Swansea, UK
2. Brain Dynamics and Cognition Team, Lyon Neuroscience Research Centre, INSERM U1028, Lyon, France
3. Department of Psychology, University of Bedfordshire, Luton, UK
This paper addresses claims that dreams can be a source of personal insight. Whereas there has been anecdotal backing for such claims, there is now tangential support from findings of the facilitative effect of sleep on cognitive insight, and of REM sleep in particular on emotional memory consolidation. Furthermore, the presence in dreams of metaphorical representations of waking life indicates the possibility of novel insight as an emergent feature of such metaphorical mappings. In order to assess whether personal insight can occur as a result of the consideration of dream content, 11 dream group discussion sessions were conducted which followed the Ullman Dream Appreciation technique, one session for each of 11 participants (10 females, 1 male; mean age = 19.2 years). Self-ratings of deepened self-perception and personal gains from participation in the group sessions showed that the Ullman technique is an effective procedure for establishing connections between dream content and recent waking life experiences, although wake life sources were found for only 14% of dream report text. The mean Exploration-Insight score on the Gains from Dream Interpretation questionnaire was very high and comparable to outcomes from the well-established Hill (1996) therapist-led dream interpretation method. This score was associated between-subjects with pre-group positive Attitude Toward Dreams (ATD). The need to distinguish “aha” experiences as a result of discovering a waking life source for part of a dream, from “aha” experiences of personal insight as a result of considering dream content, is discussed. Difficulties are described in designing a control condition to which the dream report condition can be compared.

Introduction


There have been many claims of dreams enabling individuals to obtain insight about their emotional and interpersonal life (e.g.,Freud, 1953/1900; Rycroft, 1979; Blechner, 2001). However, much of the evidence here is anecdotal, or based on case-studies, and scientific investigation is difficult. There have also been claims about scientific discoveries being derived from dream experiences (Barrett, 1993), for example, that Kekulé's dream or vision of “whirling snakes” led him to insight regarding the structure of the Benzene ring, and that a dream of Mendeleev led him to his structure for the periodic table of the elements (Barrett, 2001, with critical account by Baylor, 2001). Whilst it is difficult to validate claims that some scientific insights are attributable to dream experiences, numerous cognitive experiments have been devised to assess the relationship between sleep and insight. Wagner et al. (2004) used a mathematical task, the number reduction task (NRT), which can be solved either by a relatively lengthy calculation method, or by more sudden insight into a hidden rule. In the study initial training on the NRT was followed by 8 h of either nocturnal sleep, or nocturnal wakefulness, or daytime wakefulness. At subsequent retesting, more than twice as many subjects gained insight after sleep than after wakefulness. The authors concluded that sleep, by restructuring new memory representations, facilitates extraction of explicit knowledge, and results in insightful behavior.

Later studies, investigating the cerebral correlates of cognitive insight using the NRT and fMRI, highlight an involvement of the prefrontal cortex in the insight process. Rose et al. (2010) found that insight was associated with fMRI-signal increase in the ventral striatum and the right ventrolateral prefrontal cortex. Following this, Darsaud et al. (2011) identified the neural precursors of delayed insight on this task. In their study, normal volunteers practiced the NRT during two fMRI sessions (training and retest), taking place 12 h apart across a night of sleep. After this delay, some subjects gained insight into the hidden task structure (termed solvers), whereas the others did not (termed non-solvers). It was found that, during training, solvers and non-solvers differed in their cerebral responses associated with implicit learning. Furthermore, in solvers, but not in non-solvers, response patterns were also transformed overnight, with enhanced responses in ventral medial prefrontal cortex, an area previously implicated in the consolidation of declarative memory. During retest in solvers, before they gained insight into the hidden rule, significant responses were also observed in the same medial prefrontal area.

As there is experimental support for the hypothesis that sleep facilitates cognitive insight and creative thinking (Maquet and Ruby, 2004; Stickgold and Walker, 2004; Wagner et al., 2004; Darsaud et al., 2011), it is plausible that sleep could allow personal/affective insight, and that this might be reflected in dream content, given the interaction between characters, and emotional content, in most dreams (Nielsen and Lara-Carrasco, 2007). Interestingly, the ventral medial prefrontal cortex, whose activity is modified during sleep and is enhanced before cognitive insight during wakefulness (Darsaud et al., 2011), shows increased activity in REM sleep compared to NREM sleep (for a review, see Ruby, 2011). As a consequence, one may expect that REM dreams could be more supportive of insight than NREM dreams. In support of this hypothesis, Walker et al. (2002) reported that REM awakenings provide a significant advantage in the number of anagrams solved compared with NREM awakenings, the number solved being equal to that of wake time trials. The authors concluded that the neurophysiology of REM sleep represents a brain state more amenable to flexible cognitive processing than is NREM sleep. A similar conclusion is drawn by Cai et al. (2009), who found that, in comparison to quiet rest and NREM sleep, REM sleep enhances the integration of unassociated information for creative problem solving. Related to this, Stickgold et al. (1999) found that subjects awakened from REM sleep show greater priming by weak primes (e.g., thief-wrong) than by strong primes (e.g., hot-cold). In contrast, strong priming exceeds weak priming in NREM sleep, just as in wake. The authors conclude that the shift in weak priming seen after REM sleep awakenings suggests that cognition during REM sleep is qualitatively different from that of waking and NREM sleep and may reflect a shift in associative memory systems. They hypothesize that this shift underlies the bizarre and hyper-associative character of REM sleep dreaming, and that these cognitive and dream content characteristics of REM sleep are due to the cholinergic and noradrenergic neuromodulation specific to that sleep stage.

Another neurochemical change, the increase in cortisol in the second half of sleep, is proposed by Payne (2010) as being one of the reasons for the increase in bizarreness of dreams across the night, which she says may be reflective of hyper-associativity, and of creative thinking and novel combinations of previous information, although Blagrove et al. (2012) show that this increase in cortisol occurs for NREM and REM sleep. It may also be that the relationship of sleep to insight is a component of the widely evidenced view that sleep, and in particular REM sleep, is involved in emotional memory consolidation and emotional regulation (e.g., Walker and Van der Helm, 2009; Perogamvros and Schwartz, 2012; Groch et al., 2013). This memory consolidation during sleep is held to go beyond the making permanent of individual items, to involve also a process of abstraction from experience, and the integration of new experiences into current schemata, so that the gist of experiences is distilled (Lewis and Durrant, 2011; Stickgold and Walker, 2013). Whereas Lewis and Durrant (2011) and Diekelmann and Born (2010a,b) conclude that current empirical knowledge points more to such abstraction and schemata production occurring in slow wave sleep, Stickgold and Walker (2013) state that not enough is known to exclude REM from these processes, and that evidence of the neural replay of waking life events during REM sleep (Louie and Wilson, 2001) supports the inclusion of REM in these processes.

Such neural processes of insight and memory consolidation during sleep are proposed by Wagner et al. (2004) and Wamsley and Stickgold (2011) to be related to the formal characteristics of dream experiences. As stated by Stickgold et al. (2001), “dreams would appear to be not only unpredictable and bizarre but highly emotional as well” and they propose that “these features reflect an attempt, on the part of the brain, to identify and evaluate novel cortical associations in the light of emotions mediated by limbic structures activated during REM.”

An important precursor, however, to the claim that dreams are related to these neutrally-based insight or schemata changing processes, or even that dreams themselves, when considered during wakefulness, can lead to insight, is that dream content reflects, or is relatable to previous waking life experiences. There is indeed considerable evidence for this, with dream content being related to waking life concerns or events in naturalistic studies (Saredi et al., 1997; Domhoff, 2003; Schredl, 2006; Bulkeley and Domhoff, 2010; Blagrove et al., 2011a,b; Malinowski and Horton, 2011), to concerns that the dreamer has been instructed to dream of, in comparison to control concerns (Nikles et al., 1998), and to thoughts consciously suppressed prior to sleep (Wegner et al., 2004; Bryant et al., 2011). Furthermore, individuals who have experienced a trauma can be differentiated from control individuals on the basis of dream reports (Hartmann et al., 2001a,b; Kuiken et al., 2008). Although there are caveats here, of dreams being generic (Hobson and Kahn, 2007), and of studies in which individuals with prominent waking life characteristics cannot be distinguished from controls on the basis of dream reports (paraplegia and deaf-mutes, in Voss et al., 2011; blindness, in Staunton and O'Rouke, 2012), overall the findings are of dream content being linked to waking life experience. Whether the manner of representation of waking life in dreams allows for creative insight about waking life is then the question to be addressed. The null-hypothesis is that dreams do not provide novel or insightful information to the dreamer, and nor does dream content provide useful information about the dreamer to anyone else; as stated by the psychiatrist Allan Hobson: “I never learned anything from a client's dreams that I did not already know.” (Hobson and Schredl, 2011).

Contrary to this null-hypothesis, there have been many claims of the clinical use of dreams providing personal insight. According to Pesant and Zadra (2004), in therapy “three types of gains are generally described as a result of dream interpretation: (1) client insights, (2) increased involvement of the client in the therapeutic process, and (3) a better understanding of clients' dynamics and clinical progress.” To evidence point (1), they cite researchers and clinicians' reports that the clinical use of dreams enhances clients' insight, with better self-knowledge, self-understanding, or self-awareness. In order to define and characterize insight they refer to Elliott's et al.(1994) conceptualization of it “as containing four elements: (1) metaphorical vision—to see oneself in a new light; (2) connection—to uncover some patterns in one's existence or some links between different aspects of one's experience; (3) suddenness—an affective reaction of surprise, as if things fell down into place in one's mind; and (4) newness—the sense of having discovered something that was not previously known.”

The first of these four elements is explored by Lakoff (1993), who proposes that waking life concerns are represented metaphorically in dreams (the view also of Domhoff, 2003), and that the production of dreams, and the interpretation of dreams, draw upon our waking life system of conceptual metaphors. Hartmann (1998) similarly proposes that dreams portray waking life emotional concerns as picture metaphors, so as to interconnect old and new memories. For Hartmann, this has the function of ameliorating recent distressing emotions, a function that would hold for dreams that are recalled on waking as well as for ones that are not recalled. He thus proposes that dreaming, even where dreams are not recalled, acts as psychotherapy (see also Hartmann, 1995). Such proposals of metaphor production in dreaming can be seen as a special case of the general issue of metaphors in therapy, as described by Evans (1988). For Evans (1988), metaphors can originate from the client or the therapist, and he gives examples where the interpretation or discussion of a metaphor, which can lead to progress and insight, is aided by the “emotional distance” from threatening material that the metaphor allows. Pesant and Zadra (2004) make a similar observation that clients may be less reluctant to discuss disturbing issues when these are approached through dream exploration, because of the safer distance between the client and the material evoked by a dream. Similarly, Rennie (1994) suggests that narratives allow patients in psychotherapy to talk around their problems, but that gradually sources of personal concern are brought to light, and in this way narratives help create the possibility of insight.

In a metaphor, the tenor, or topic, is expressed in terms of the vehicle, which can be more familiar or more concrete. Evans (1988) holds that using metaphor to describe one's experience catalyses change and growth, and advocates a conscious use of metaphors for this, because “the language of inner experience and self-discovery is largely metaphorical.” He states that, for tenor and vehicle, “this interaction between the two systems of associations extends the meaning of both terms, which contributes to the epistemic creativity of metaphor.” Similarly, Tourangeau and Sternberg (1982) propose that this interaction enables new things to be discovered, and not just for the two concepts being associated but for the whole of their domains as well. Furthermore, Tourangeau and Rips (1991) describe metaphor interpretation as being more reliant on the perception of emergent, rather than well-established, similarities between the two concepts being compared, such that metaphor creates an emergent feature, which is a novel insight into the two previously unrelated concepts.

For Evans (1988), becoming aware of and exploring one's metaphors, including one's novel metaphors, is part of becoming more psychologically minded, and is especially important for life metaphors, which, he claims, are often unconscious, involving tacit knowledge of one's conscious and social experience. Considering the metaphorical content of dream reports would involve processes similar to Kopp and Craw's (1998) 7-step interview protocol for exploring and transforming client-generated metaphors, which they propose aids the accessing and transforming of tacit knowledge.

These accounts of metaphor provide a theoretical justification for the proposal that examining dream content can result in personal insight. Lakoff (1993) emphasizes that each person has many conceptual metaphors that they do not have conscious access to, nor control over. He argues that cognitive and linguistic activity relies upon cognitive links which are created because of aspects of similarity between idioms or concepts. This allows the mapping of characteristics of one idiom or concept onto another, creating “conceptual metaphors.” These metaphors are claimed by Lakoff and Johnson (1980) to be very influential in human understanding of the world, and as easily identifiable in everyday language. One example they give of a common linguistic metaphor within the English language is the “LOVE IS A JOURNEY” metaphor (Lakoff and Johnson, 1980; Lakoff, 1993). This metaphor can be detected in descriptions such as “the relationship is running into trouble,” “the relationship is on the rocks,” and “we must go our separate ways,” because romantic attachment is being described in terms of physical movement. Lakoff (1993) proposes that cognition during dreaming likewise involves the mapping of abstract concepts onto physical concepts. He suggests that metaphorical understanding of a dream is possible without personal information about the dreamer, but that information about the dreamer allows metaphors specifically relevant to the dreamer's life to be interpreted, even though, in some instances, the dreamer, upon waking, does not know whether anything from waking life is being expressed metaphorically by the overt content.

However, whereas the link between dream content and metaphor has been frequently proposed (e.g., Ullman, 1969; Antrobus, 1977; Lakoff, 1993), and the ubiquity of the use of metaphors in thinking has been described by Lakoff and Johnson (1980), there is now debate about the extent of empirical evidence for an embodied basis for conceptual metaphors (Shapiro, 2011). For the purposes of the current paper, though, it is the ubiquity of metaphorical thought that is important rather than the derivation of basic concepts from direct physical experience, which Shapiro criticizes. There has also been a criticism of Lakoff by Glucksberg and McGlone (1999), who state that they “find no evidence that people automatically and invariably draw upon fixed sets of domain-to-domain mappings in order to interpret metaphors.” They thus propose a “minimalist” account of metaphor production and understanding, where the metaphor vehicle will often be a prototypical member of an attributive category; the attributive category is thus applied to the metaphor topic. They contrast this with Lakoff and Johnson's (1980) multiple mappings account, in which there are systematic mappings between topic and vehicle, derived from conceptual knowledge. Interestingly, for the current paper, Glucksberg and McGlone's (1999) simpler account of the cognition required for metaphorical thinking might be taken as more relevant to the levels of cognition that dreaming may be capable of, and hence as according with Antrobus' (1977) account of metaphor in dreams.

Dream Appreciation

To test the claim that insight can follow the consideration of dream content, the current study uses the “Dream Appreciation” technique devised by Ullman (1996). There has been work by DeCicco (2007a) on correlations between dream content measures and outcome measures that result from use of an earlier version of the Ullman technique as described in Ullman and Zimmerman (1979). DeCicco (2007a) concluded that participants found many connections between waking life and dream content, with “discovery” experiences originating from the technique. However, mean outcome scores were not reported. To our knowledge the current study is the first to report group mean outcomes of the standard (Ullman, 1996) technique, apart from a study summarized in a short report by Blagrove et al. (2010). In that study there were 13 participants (4 males, 9 females; all undergraduate students), 22 dreams were reported, and each group session lasted from 45 to 75 min. After the group a Visual Analogue Scale (VAS), anchored 0 = not at all and 100 = very much, was used for participants to rate the degree to which the session gave them any new understanding of what the dream means: here, mean rating on the VAS for this new understanding about the dream variable = 67.8 (SD = 18.2). Another VAS, also anchored 0 = not at all and 100 = very much, was used for participants to respond to the question “Did the session for this dream give you new understanding or insight about yourself or about any aspect of your life?” Here, mean rating on the VAS for this new understanding about yourself variable = 57.0 (SD = 15.5). Support was thus given for the usefulness of the Ullman technique.

Ullman Dream Appreciation Procedure

One of the researchers (MB) has extensive experience of conducting dream appreciation groups that follow the procedure devised by Ullman (1996), and has received training from a leading associate and colleague of Montague Ullman. The procedure involves the following stages: (1A) reading of the dream aloud by the dreamer; (1B) clarification of the dream report by the group asking questions of the dreamer; (2A) brief discussion of the dream by the group members other than the dreamer so as to imagine what feelings they would have experienced if the dream were their own, and then, (2B), eliciting these individuals' projections about the dream in terms of their own lives so as to give symbolic or metaphorical meaning to the dream images; (3A) response by the dreamer to stage (2); (3B.1) description by the dreamer of his/her waking life context for the dream, in terms of the dreamer's life experiences, with particular emphasis on recent experiences and concerns; (3B.2) reading the dream back to the dreamer, in the second person, so that any additional information about the dream or waking life can be obtained; and (3B.3) orchestration, in which all members of the group suggest connections between information that the dreamer has given about their dream and information the dreamer has given about the dreamer's life. For a full description of the process, see Ullman (1996). The technique can be compared to Hill's (1996) Exploration-Insight-Action model of dream interpretation: Ullman's stages 1A and 1B and 3B.1 are similar to the first stage of Hill's model, in which exploration of the dream occurs through the dreamer telling the dream, reporting feelings from the dream, and providing associations to the dream images, so as to find waking life sources of the dream. Stage 2 and the dreamer's response to that stage would occur when the Hill model is used in a group (Hill, 1996; Hill, Chapter 11). Ullman's stage 3B.3 has similarities with Hill's Insight stage, in which possible meanings of the dream are explored. The Ullman procedure thus mainly maps onto the first two stages of the Hill technique, and does not map onto the Hill model's third, Action stage, in which behavioral or cognitive changes as a result of the dream are considered. It should be noted that such a restriction to the first two Hill stages is also present in much clinical work with dreams. As stated by Hill and Knox (2010, p. 9): “although both cognitively and psychoanalytically oriented therapists used many activities to work with dreams, they most often focused on exploring and understanding the dreams; they rarely addressed how clients might change their dreams or make changes in waking life based on their understanding of dreams.”

The Ullman technique thus relies on the identification by participants of waking life sources of dream content, such as recent events or concerns, with the non-directive assistance of the other group members. According to Hill et al. (1998), the use of association allows clients to make “previously unconsidered connections between dream images and other thoughts and memories,” and they conclude that solely describing a dream, without producing associations, requires the client to stay within the dream, with less likelihood of identifying “engagingly novel thoughts.” In Hill's method the depth and accuracy of inferences from dream images are dependent on the work carried out exploring the possibility of associations between dream content and waking life experiences, and increases in insight are found with more time spent in this association stage (Hill et al., 1998).

However, in the eliciting of associations Grünbaum's (1984) tally argument does have to be borne in mind. This is the critique that even if a dreamer states that an item of dream content is related to some aspect of waking life, there is no evidential value to this belief of the client. Several aspects of the Ullman technique have the aim of reducing the forcefulness of suggestions from group members of relationships between dream content and recent waking life experiences that the dreamer has described, while keeping to the purpose of holding a group, which is that group members may identify valid or plausible connections, not hitherto recognized by the dreamer, between the dream report and the dreamer's recent life experiences. Obviously there may be an experimenter demand in the search by participants for memory sources of dreams, and in their consideration of how plausible possible memories are as sources. However, although this may operate for some decisions regarding sources, the empirical literature does support the claim that dreamers can, when awake, identify memory sources of dream content (Nielsen and Stenstrom, 2005; Blagrove et al., 2011a,b), and categorize waking life associations into episodic and semantic memory sources (Baylor and Cavallero, 2001; Fosse et al., 2003). Also, a more experiential counter to Grünbaum's argument can be found in Blass (2002, pp. 169–188).

Kuiken et al. (2006) have differentiated between types of dreams (e.g., transcendental, existential, mundane, nightmares) and related this factor to level and type of insight following the dream. In contrast, the current study involves the participant recalling their most recent dream, whatever its content and perceived impact or lack of impact. Furthermore, whereas Kuiken has also investigated type of dream and level of subsequent insight as a function of previous experience (e.g., loss vs. trauma; Kuiken et al., 2008), for the current study a participant's waking life background is not known to the experimenters prior to any mention of it in the group session.

The Dream Appreciation technique is used with the intention of providing a way for an individual to connect the self as experienced in the dream with the self as perceived and as experiencing in waking life (Ullman, 1996). The potential for personal change within this context is as an adaptation of conscious perspective. In contrast, Hill's (1996) Exploration-Insight-Action model uses dreams in a therapeutic context, with an Action stage, in which an individual can be encouraged or challenged to change behavioral or cognitive processes after obtaining insight from working with a dream. In the Action stage clients determine what they would like to do differently, “in the dream, in life, or in continued work on issues raised by the dream” (Hill et al., 1998). Change can therefore be actively pursued by a therapist using Hill's (1996) method. In contrast we chose the Ullman Dream Appreciation method as it is appropriate for lay people to use in a non-therapeutic setting, using the manual (Ullman, 1996) as a guide, and because it has been used worldwide in various lay settings. Ullman (1996) argues that there are also structural differences between formal therapy and his Dream Appreciation technique. He asserts that there is a hierarchical structure in therapy, in which the therapist acts more as an authority figure compared to the leader of a Dream Appreciation group. The emphasis in the Dream Appreciation format is on the dreamer having overall control during the process, the leader of the group is seen more as a safety supervisor and a guide through the stages rather than a controlling influence. The individual who offers the dream regulates the information that is shared with the group and holds the power to decide whether anything discussed during the dream discussion session is relevant or useful.

Hypotheses


In the current study, in order to assess outcomes from the Dream Appreciation technique, participants rate their Exploration-Insight gains, Experiential gains, and Action gains using the Gains from Dream Interpretation questionnaire (Heaton et al., 1998), and complete a Deepened Self-Perception questionnaire (Kuiken, 1995). We hypothesize the following:

(1) Participants would rate Exploration-Insight gains and Experiential gains of the group procedure highly, and, specifically, as highly as those found by participants who follow, with a psychotherapist, the more widely researched Hill (1996) method.

(2) As the Hill method has an aim of therapeutic change, whereas this is not a specific aim of the Ullman method, the participants would rate Action gains of the Ullman procedure as lower than the Exploration-Insight or Experiential gains, and as lower than occurs for the Hill method.

(3) As Hill et al. (2001) found that the level of individuals' Own positive Attitude Toward Dreams (ATD) was significantly related to the Exploration-Insight gains subscale score of the Gains from Dream Interpretation (GDI) questionnaire, there would be a significant positive correlation between the Own Attitude Toward Dreams subscale of Cernovsky's (1984) ATD questionnaire, completed prior to the group, and the Exploration-Insight gains subscale of the GDI questionnaire, completed after the group.

We also conduct an exploratory analysis of the amount of text of the dream reports for which memory sources can be identified by the dreamer, with the aim of comparing our results with those of a previous study (Saredi et al., 1997) where a far less lengthy consideration of each dream occurred.

Comparison Conditions

The current dream appreciation study does not include a control condition, and so it is not possible to determine the role of dream content in the group process, or to disentangle whether any insights or gains during the group are dependent on the dream content, or solely on the group process. The current study aims to pilot how the effects of considering dream content in an Ullman Dream Appreciation group can be measured, with future studies then intended to include a control comparison. The issue of a control can be illustrated by reference to Timpanaro (1974/1985, pp. 29–45), who analyses an account by Freud of how, by free-association, a slip of the tongue of a missing word (Aliquis) in a Latin quotation can be linked to a current concern of the person who was conversing with him and who made the slip. Crucially Timpanaro shows how other words from the quotation, for which there were not slips of the tongue, can also be linked by free-association to the same concern, thus showing for us the importance of control conditions to test that an item of dream content can be linked to putative insight. Control conditions were used in the study of dream interpretation by Hill et al. (1993): participants who were involved in interpreting their own dreams rated sessions as deeper and as producing more insight than did participants who were involved in interpreting another person's dreams or interpreting their own recent troubling events. Hill et al. (1993) thus concluded that the efficacy of dream interpretation does not seem to be solely due to projection or to the process of interpreting any text, whether of a dream or a text that is not of a dream. However, in Diemer et al. (1996), therapist and client assessments of client insight did not differ between a session of dream interpretation and a session of interpretation of a recent troubling interpersonal event. Each session lasted 50 min and the dream or event was the focus of the session for at least 40 min. The only control condition in a study using the Gains from Dream Interpretation questionnaire, which is used in the current study, is the focussing on recent loss condition in Hill et al. (2000), where Exploration-Insight for that event condition was significantly lower than for the dream condition.

For the loss condition in Hill et al. (2000), “therapists began by asking clients to explore an aspect of their loss by describing it in detail, associating to thoughts about loss, and exploring their feelings related to the loss. During the insight stage, therapists helped clients construct new understandings of their thoughts, feelings and behaviors in relation to their loss.” However, a problem with such control conditions is that they cannot be used in a double-blind manner. This is a concern because Morewedge and Norton (2009) have shown that individuals from both Eastern and Western cultures believe that dreams contain hidden truths and consider dreams to provide more meaningful information about the world than do similar waking thoughts; this indicates that a control condition, unless the justification or theory behind it is very plausible to participants, would be at a disadvantage in comparison to an own-dream condition. Hill et al. (1998) similarly caution that experimenter demand can occur because of the common view that dream interpretation involves making associations, a view that might not be commonly held for comparison waking life event narratives.

Although a non-dream control condition is not included in the current study, we do compare participants' mean subscale scores from the GDI questionnaire with subscale scores from participants in various studies on dream interpretation by Hill, and we compare the current study subscale scores with those from the control group in Hill et al. (2000) where participants focused on a loss they had suffered rather than on a dream. In that study a parallel form of the GDI, called the Gains from Therapy, was developed for the loss condition, with the word dream replaced by the word problem.

Method


The study was approved by the Research Ethics Committee of the Swansea University Department of Psychology.

Participants

Eleven participants took part in the study [10 females, one male; mean age = 19.2 years (SD = 0.75)]. They were all undergraduate students studying psychology and they received experiment participation credits for their voluntary participation. Individuals responded to a recruitment advertisement and were invited to a briefing session about the study, which was titled “Can ‘insight’ be obtained from dreams using the Ullman ‘Dream Appreciation’ group procedure?” At this session they completed a brief screening questionnaire, so as to assess whether they met inclusion criteria of not suffering from or having had a history of any psychological problems, and not having any personal issues that might make it difficult for them to participate in a situation involving a degree of self-disclosure.

Materials

(a) The Attitude Toward Dreams questionnaire (ATD; Cernovsky, 1984). This has three subscales, (1) own attitude toward dreams, (2) perceptions of attitudes of significant others toward dreams, and (3) perceptions of attitudes of other people in general toward dreams or toward individuals who publicly discuss dreams. There are 16 items, scored as agree or disagree, the three subscales have 7, 5, and 4 items, respectively, and have scores ranging 0–7, 0–5, and 0–4, respectively.

(b) The Gains from Dream Interpretation questionnaire (GDI; Heaton et al., 1998). This has 13 items and uses a 9 point scale for each item (1–9, with descriptors “strongly disagree” to “strongly agree”). This questionnaire comprises 3 subscales: Exploration-Insight gains, Experiential gains, and Action gains. The Exploration-Insight gains subscale is of particular importance to the current study, and is composed of the following items:
1. I was able to explore my dream thoroughly during the session.
6. I learned more from the session about how past events influence my present behavior.
7. I learned more about issues in my waking life from working with the dream.
8. I felt like I was very involved in working with the dream during the session.
12. I learned things that I would not have thought of on my own.
13. I was able to make some connections between images in my dream and issues in my waking life that I had not previously considered.
(Due to a typographical error, item 2 of the GDI questionnaire, “I learned more about what this dream meant for me personally during the session,” and which would form part of this subscale, is omitted). The Experiential gains subscale has 2 items: “During the session I was able to re-experience the feelings I had in the dream” and “I felt like I was actually reliving the dream during the session.” The Action gains subscale has 5 items such as: “Because of the session, I have more of a sense that I can change my dreams when they are frightening or bad” and “I will use things that I learned in this dream interpretation in my life.”

(c) Section A of Kuiken's 1995 Deepened Self-Perception (DSP) questionnaire. These items are:
1. I feel sensitive to aspects of my life I typically ignore.
2. My dream influenced my mood even after awakening.
3. My dream reminded me of events that occurred in my past.
4. My dream made me feel like changing the way I live.
A 10 point scale was used, from 0 to 9, with descriptors “strongly disagree” to “strongly agree.”
Procedure

At the briefing session participants were informed about what the study involves and gave written informed consent to take part. Individuals taking part in the study were encouraged to write their dreams down each morning and to decide for themselves, when a dream occurred, whether they wished to share and discuss it in the group. When participants had a dream that they wished to share, they contacted the researchers to arrange a convenient time over the following few days for convening the dream group. This follows the recommendation of Ullman that dreams that are the subject of his technique should have occurred recently, unless the group has already met many times, in which case the examination of older dreams is allowed. The dream group consisted of two researchers (CE and MB) and the participant sharing the dream; each participant came to a group only once. There were thus 11 separate group sessions, each with one participant and the two researchers. This group membership was used so as to keep the group as consistent as possible, rather than having more individuals involved. It was also necessitated by the need to have the group meet as quickly as possible after the participant had a dream, which can be difficult to timetable with several people.

For the group session, each participant had written their dream report down upon waking and brought the report with them. At the start of the session the participant completed the Cernovsky (1984) ATD questionnaire, which assesses one's personal attitude to dreams and one's perceptions of the views of others about dreams. After this the participant read out loud their dream and the Ullman Dream Appreciation procedure, as described above, was followed closely and in full for all 11 participants. Note that the design of the study did not allow the possibility of the dreamer briefly reporting any further considerations or realizations about the dream at the next meeting of the group, as only one meeting was scheduled for each participant.

After the Dream Appreciation Group the participants completed the 13 item GDI questionnaire (Heaton et al., 1998) and section A of Kuiken's 1995 DSP Questionnaire.

Transcribing and Scoring Dream Reports

The Dream Appreciation sessions were recorded with a digital voice recorder and then transcribed. The description of the dream as stated at the start of the session (stage 1A of the Ullman procedure) is termed here the initial dream. The initial dream description in the transcription was amended according to Antrobus' (1983) definition of words to be retained in dream reports, which are “all words in sentences or phrases in which the subject was describing something that had occurred just before waking. It excluded “ahs,” “uhms,” repeated and corrected words, and all commentary on the experience, the report, or the current status of the subject.” Next, the transcription of the dream appreciation session was used to add additional text to the initial dream, where details of the dream had been remembered or clarified during the session. This process of utilizing all information from the transcript of the session about what to include in the dream text was conducted by the first author (CE) and produces what we term the “canonical dream.” The initial version of the dream and the canonical version of the dream were then compared in terms of word lengths so as to calculate a percentage change in word length due to the session.

The canonical dream was then used so that the first (CE) and second (JM) scorers could undertake the matching of dream content to the dreamer's waking life events and experiences as recorded in the transcription of the session. The two scorers worked independently in order to identify words in the dream report that the dreamer asserted or agreed in the transcript are linked with a source from their waking life or conscious experience. Each scorer highlighted words in the canonical version of each dream that the dreamer linked with a source from their waking life. The highlighted versions of the canonical dream from the two scorers were then compared with each other so as to calculate inter-rater reliability. This was computed as the sum of the number of words that both scorers agree do derive from specific waking life experiences of the dreamer present in the transcript and which the dreamer asserts is a source of the dream content, or words that both scorers agree do not derive from any waking life experience described by the dreamer, divided by the total number of words in the canonical dream, and expressed as a percentage.

Results


The dream group sessions lasted for as long as was needed to complete all the stages of the Ullman technique; the mean length of the sessions was 67.18 min (SD = 14.40). The 11 dreams initially presented by the participants in stage 1A had a mean length in words of 543.27 (min = 216, max = 1654 words, SD = 431.02). The canonical dreams had a mean length in words of 778.27 (min = 333, max = 1779, SD = 415.25). The mean percentage increase in length of dream report as a result of the group process = 43.26%.

Table 1 shows group mean values for responses to the pre-group ATD questionnaire, and the post-group GDI and DSP questionnaires. The results from the subscale analysis of the ATD questionnaire indicate that most participants in the study were positive in their own attitude to dreams, and considered that significant others and society in general are positive toward dreams.
TABLE 1
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Table 1. Group (n = 11) mean scores for Attitude Toward Dreams (ATD) questionnaire subscales, the Gains from Dream Interpretation (GDI) questionnaire subscales, three items on the GDI questionnaire that relate to learning about one's waking life, and the four Deepened Self-Perception items.
Internal consistency for the GDI Exploration-Insight gains subscale was acceptable (Cronbach's alpha = 0.61). The mean rating for Exploration-Insight gains showed that participants had very high agreement that such gains had occurred. The three items on the GDI questionnaire that are part of the Exploration-Insight subscale and that refer specifically to learning about one's waking life are also reported in Table 1, and show high agreement that such personal insight occurred (items 6, 7, and 13). The mean of Experiential Gains was also high (and also with high subscale internal consistency, Cronbach's alpha = 0.84). The mean rating for Action Gains was lower, and with a low internal consistency for the subscale (Cronbach's alpha = 0.53). Matched-sample t-tests showed that as hypothesized the Exploration-Insight mean and Experiential mean were significantly higher than the Action mean [t(10) = 9.79, p < 0.001 and t(10) = 2.37, p < 0.05, respectively].

There were moderate ratings for two items on the DSP questionnaire: “I feel sensitive to aspects of my life I typically ignore,” and “My dream reminded me of events that occurred in my past.” A lower rating was given to “My dream influenced my mood even after awakening,” and a far lower rating to “My dream made me feel like changing the way I live.”

As hypothesized, the relationship between Own Attitude Toward Dreams, assessed pre-group (where higher scores indicate positive attitude), was significantly correlated with Exploration-Insight gains as assessed by the GDI questionnaire (Spearman's rho = 0.68, p = 0.02). No other relationships between ATD and GDI subscale scores were hypothesized, however, correlations were conducted for exploratory purposes. All other correlations between the ATD and GDI subscales were found to be non-significant; rhos ranged from −0.30 (p = 0.371) to 0.29 (p = 0.385). Although no relationships were hypothesized between the ATD subscales and the DSP items, correlations were also conducted for exploratory purposes. All of these correlations were found to be non-significant; rhos ranged from −0.57 (p = 0.067) to 0.46 (p = 0.160). All correlations between the four DSP items and the three GDI subscales were non-significant with the exception of DSP item 4 (My dream made me feel like changing the way I live) and Action gains, where rho = 0.71, p = 0.014. For the other correlations, rhos ranged from −0.08 (p = 0.826) to 0.48 (p = 0.137).

Words in each dream report for which dreamers identified or acknowledged a waking life memory source during the session were identified from the transcripts by two scorers working independently. The inter-rater reliability, defined as percentage of words in each canonical dream for which the scorers agreed there either was, or was not, a waking life source stated in the transcript, was 83.18% (SD = 4.68). The mean percentage of the text of the canonical dream reports for which a waking life source could be identified from the transcript was 18.3% (SD = 6.2) for scorer 1 (CE), and 10.6% (SD = 4.8) for scorer 2 (JM). The mean percentage for the 2 scorers combined was 14.4% (SD = 4.1).

The length of the initial and canonical dream reports in words, and the percentage of dream report words for which a waking life source was identified, were not significantly correlated with any ATD or GDI subscale, nor any DSP item, when a correction for multiple correlations was applied (p < 0.005 criterion used). For the correlations of the three dream report words measures with ATD subscales, rhos ranged from −0.36 (p = 0.280) to 0.65 (p = 0.032); for the correlations with GDI subscales, rhos ranged from −0.24 (p = 0.478) to 0.74 (p = 0.009); for the correlations with DSP items, rhos ranged from −0.32 (p = 0.341) to 0.37 (p = 0.263). The only correlation out of the 30 tested that approached the significance criterion was between the mean proportion of dream report words for which a source was identified and the GDI Experiential gains subscale (rho = 0.74, p = 0.009). The correlations of GDI Exploration-Insight and Action gains with percentage of dream report words for which a waking life source was identified were negligible (rhos = 0.06 and −0.03, respectively, ps = 0.861 and.926), and remained non-significant when percentage of words data from the two scorers were analyzed separately. The correlations of DSP items with percentage of dream report words for which a waking life source was identified were also non-significant [rhos ranged from −0.06 (p = 0.862) to 0.36 (p = 0.277)] and remained non-significant when percentage of words data from the two scorers were analyzed separately.

There were some examples in the transcripts of what appeared to be metaphorical references to waking life concerns. For example, one participant described how one of her greatest fears is not being able to have a baby. The participant shared a dream in which she frequently protects her own mother, for example she “had to like force her to run away” and provides her mother with advice to escape danger, in one such instance she says “no, we've gotta go” when the mother would have stayed in a precarious situation. The concept of parenthood maps onto acts of protection in the dream, which is connected to her waking life desire to preserve her own ability to become a mother in future, and therefore “PARENTHOOD IS PROTECTION” can be suggested as a conceptual metaphor in this dream, according to the Lakoff (1993) model.

Table 2 shows means for the GDI subscales from the current study and from all papers, to our knowledge, by Hill that report group subscale means on the GDI. The mean rating in the current study for Exploration-Insight gains of 8.17 is comparable to many of the mean scores on this subscale reported by Hill and is significantly higher than the only non-dream control condition in Hill that uses the GDI (Hill et al., 2000). Table 2 also shows, for each GDI subscale, a meta-analysis mean of all dream-interpretation conditions by Hill that assess that subscale; these means are weighted by the number of participants in each study or condition. The mean Exploration-Insight gain for the current study is not significantly different from the weighted overall mean on this subscale for the dream conditions in the Hill studies.
TABLE 2
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Table 2. Gains from Dream Interpretation subscale means (and SDs) from papers by Hill, with comparison of current study with Hill studies' subscale means, and comparison of current study means with weighted subscale means of all Hill dream conditions.
The mean Experiential gains for the current study is comparable to the means for this subscale in the papers by Hill. In contrast, our Action gains mean was significantly below many of the means for this subscale reported by Hill. The current study subscale means for Experiential and Action gains do not differ significantly from the Hill studies' meta-analysis means for these two subscales.

Discussion


Participants gave a very high mean rating for their Exploration-Insight gains from participating in the dream appreciation group. The mean rating in the current study for Exploration-Insight gains is comparable to results from the studies by Hill, but is not significantly higher than the weighted mean on this subscale of all dream conditions in the Hill studies. Importantly, the current study's Exploration-Insight subscale mean significantly exceeds the control (focusing on loss rather than a dream) condition mean in Hill et al. (2000), as did also the dream condition in that study. The mean Experiential gains in the current study is comparable to findings from studies of the Hill model. In contrast, our Action gains mean is in some cases significantly less than that found by Hill. For all three subscales the means from the current study are not significantly different from the weighted subscale means of the dream conditions in the Hill studies.

The low Action gain accords with the low rating given to the item “My dream made me feel like changing the way I live” on the DSP questionnaire. On that questionnaire participants gave moderate agreement ratings to two items: “I feel sensitive to aspects of my life I typically ignore,” and “My dream reminded me of events that occurred in my past.” There will be conflicting views of whether the data from these two items give evidence for the occurrence of insight. This is because the former item may reflect redirected attention, rather than unprecedented insight, and the latter item does not preclude the possibility that those events are routinely remembered. Whether such state cognitive changes are components of insight is a definitional as well as empirical matter about which views will differ.

The results from the GDI accord with the conclusions of Pesant and Zadra (2004) that exploring dream content and linking that content to the dreamer's waking life can help in the achievement of insights and self-understanding. However, this was achieved even though, according to the independent judges, participants identified waking life sources for a mean of only 14.4% of dream report text. This figure is comparable to that of Saredi et al. (1997), where 17.3% of dream text was found to refer to waking life concerns. Importantly, there was no significant or appreciable correlation between Exploration-Insight gains or Deepened Self-Perception scores and percentage of dream text for which a waking life source could be determined. This illustrates that a distinction needs to be made between insight about the sources of an item of dream content (“aha, this is where that part of the dream came from”) and insight about one's waking life as a result of considering the dream (“aha, this tells me about myself”). This distinction is also made by DeCicco (2007b), with her separate questions “Does the dream have meaning for you?” and “Do you have any clear insight about your life from this dream?” We thank an anonymous referee for the suggestion that furthermore it may be that these two types of insight can be compared to the distinction between associative and metaphorical thinking, and we note that it might even be that these two types of insight following examination of dream content could have different time-courses. For example, Pesant and Zadra (2004) suggest that reflecting on dreams while awake can increase the awareness of one's feelings, but not immediately after awakening from the dream. However, although these two types of insight can and should be distinguished, there may be instances where they occur together. This is because the relationship between the metaphor in a dream (the vehicle) and its waking life source (the tenor or topic) may extend the meaning of both terms (Black, 1954-1955; Tourangeau and Sternberg, 1982; Tourangeau and Rips, 1991). It is thus arguable that any new metaphor will provide some restructuring of waking life knowledge, even if the waking life issues are known to the dreamer and are already well-considered and explored.

Metaphorical references to waking life events and concerns occurred during some of the dream appreciation sessions. We suggest that the Ullman procedure results in the identification of metaphors primarily during the orchestration stage (stage 3B.3), but that even the earlier more associative stages may aid in this process. Firstly, in stages 1A and 1B, the focus is on collecting the dream report, and recalling as much of it as possible, without the distraction of attempting to interpret or identify sources of it. In stage 2B, parts of the dream content are matched by the dream group members to their own schemata, using explicit projection. This helps to identify themes in the dream, which may match themes in the lives of the other group members. This projective process does not use only simple associations to dream images, but also the exploration of “metaphorical meaning that links the image to a relevant bit of real-life experience” (Ullman, 1996, p. 35). In stage 3 the dreamer associates to and considers events and feelings from the previous day and the days before that. However, as stated by Hill (1996, pp. 49–54) for her technique, but of relevance here, when the dreamer (and, for us, group) identify a waking life schemata that is represented in the dream, the situation may then involve metaphor rather than simple association. This is so even if it was a single associated source that was involved in exciting the schemata and leading to the formation of the dream. The concept of association alone is thus not sufficient to describe the exciting of schemata that is hypothesized to be involved in dream production, nor sufficient to describe the discovery of the excited schemata during association to the dream. Hill's conceptualization of dream formation and interpretation as involving the integration of new experiences with current schemata, and Ullman's similar view of dreams making connections between past and present “tensions,” can furthermore be linked to the sleep-dependent processes of abstraction from experience, and integration of new experiences into current schemata, as described by Lewis and Durrant (2011) and Stickgold and Walker (2013). For both Ullman and Hill dream imagery can thus be metaphorical rather than solely associative, because recent emotional waking life events excite schemata (Hill, 1996) or unresolved tensions from the past (Ullman, 1996, p. 4), which are themselves structured consequences of past experience.

Although only 14.4% of dream report text was identified as being derived from specific waking life experiences, it may be that such a small or minimal amount of text is sufficient to represent a metaphor or important connection to waking life. We thank an anonymous reviewer for noting that this finding is similar to Hartmann's work on the Central Image, or Contextualizing Image in dreams, in which it is the quality or aptness of the text that refers to waking life that is important, rather than necessarily the quantity of text (Hartmann et al., 2001a,b; Hartmann and Kunzendorf, 2005-2006).

Regarding the generalizability of our group findings to individuals examining their own dreams, either on their own, or very briefly with others, a caveat is needed that the dream appreciation sessions required approximately one hour of detailed consideration of each dream. This may explain the difference between our results and those of Schredl and Erlacher (2007). In their study 444 students and 636 online respondents answered a questionnaire about dream recall frequency and creative dreams. The former sample was of mainly psychology students recruited to a study entitled “sleep, dreams, and personality.” The latter sample was of individuals recruited to an on-line study on lucid dreaming. Despite what may have been a recruitment that favored individuals interested in dreaming, respondents reported that just 7.8% of their recalled dreams were creative. The themes of the 272 creative dreams that were reported were classed into 4 categories: artistic creativity, (non-interpersonal) problem-solving, impulses and emotional insights. Forty of the 272 creative dreams were classed as giving emotional insight. This indicates that approximately 1.2% of dreams, which are presumably not the subject of a formal group examination, produce emotional insight, for individuals who may have a positive attitude to dreaming. Contrasting this figure with the results of the present study, it may thus be that it is only with some time spent on examination of dreams [for example, approximately an hour in the current study, or 40–50 min in Diemer et al. (1996), or 13 min in Hill et al. (2013)], and possibly with the help of others that a higher level of emotional insight can be obtained from examining dreams. However, in favor of generalizability of the current results, all participants in the current study took part in order to receive course credits and thus were not required to have an especial interest in dreams, or a particular belief about dreams. The preponderance of females in our sample, though, does mean that there may have been a more positive attitude toward dreams (Schredl, 2010), and greater interest in dream interpretation (Schredl and Piel, 2008), than for a sample with more males, and this may have influenced the GDI and DSP results.

A criticism of the current dream appreciation study is that a comparison non-dream control condition was not part of the study, and control conditions should indeed be used in future studies. In addition to having conditions based on the appreciation or interpretation of texts other than dream reports, such as reports of waking life episodes, or the dream of another person, conditions based on components of the Ullman technique could also be used, to which the full Ullman procedure would be compared. Such a method of comparing to isolated components of the technique has been used by Hill in controlled studies of her model. A further criticism is that it may be that alternative methods or schools of interpreting dreams (many of which are detailed in Cushway and Sewell, 2013) might result in different gains scores from those here, whether higher or lower. And it may even be that some individuals are better attuned to identifying or utilizing free-associations. Evidence for this ability is shown by Cohen et al. (2011), who found that psychoanalysts were better able to recognize healthy adults who had experienced sibling cancer during childhood, from 5-min of spontaneous free-associating speech, than were medical students, oncologists, cognitive behavioral therapists and individuals with a history of a sibling with a cancer.

We wish to consider finally two explanations for what appears to be dream content being a source of insight. As reviewed above, there may be functional characteristics of sleep, and especially REM sleep that underlie emotional memory processing and which result in novel connections being made between memories, with this memory enhancement, and creative abstraction from experience, then being reflected in dream content. An alternative view that beneficial consequences of examining dream content are unrelated to any functional role of sleep, is proposed by Blagrove (2011). In this epiphenomenal view of dreaming, beneficial consequences of examining dream content are not related to any functional characteristic of sleep, and may instead be related to a decreased self-censorship in cognition during sleep, a view proposed by Freud (1953/1900). Although both these explanations allow for recalled dreams to be a source of insight, they differ in their ascription of whether there is any cognitive consequence to unremembered dreams. In addition, as stated in the introduction, and detailed in Blagrove (2011), the null hypothesis that dreaming is not a source of personal insight, should still be borne in mind. There are similarly different explanations for the finding that, as hypothesized, the Exploration-Insight gains in the current study correlated significantly with pre-group assessment of Own positive Attitude Toward Dreams. One explanation for the correlation is that individuals who are more positive in general toward dreams are better able to identify associations and metaphorical references to waking life in their dreams; they take the dream seriously as a possible source of new information, and thus engage in the discovery and exploration of the dream. A second explanation, however, is that individuals who are highly positive on ATD are flexible and attuned to many sources of information, including suggestions made by group members, and are willing and able to engage in relaxed, gently inquisitive discussions about their emotional and personal life. They are able to identify useful associations to various materials, whether dreams, Tarot cards or personal events, or to confabulate those associations, and acknowledge their own gains from such a group activity.

Obviously the stage of sleep that the 11 dreams reported here came from is unknown, although it would be expected that most would be from REM sleep. Whereas theoretical reasons for suggesting that REM dreams may afford more insight than NREM dreams were reviewed in the introduction, a more cognitive rather than physiological view of dreaming (such as by Foulkes, 1985 or Domhoff, 2003) would not give such weight to this distinction between stages of sleep. Furthermore, other authors argue in favor of a greater effect of SWS sleep than REM sleep on the process of cognitive insight and memory-consolidation (e.g., Yordanova et al., 2008, 2010, 2012; Born and Wilhelm, 2012). Future studies will need to address whether REM sleep, N3 (SWS), or N2 dreams result in the same or different levels of insight when dream reports from those sleep stages are considered in a dream group procedure. The consideration of REM sleep dreams was found by Cartwright et al. (1980) to reduce drop-out rates for psychotherapy in comparison to a group not subjected to awakenings and collection of dream reports in the sleep lab. However, there was no significant difference in drop-out rates between this REM dream group and a group awakened the same number of times from NREM sleep. Instead, recall and discussion of dreams, whether elicited from REM or NREM sleep, was associated with staying in psychotherapy treatment, in comparison to the group that did not sleep in the lab, and was also associated with a greater expression of affect during the psychotherapy. It may thus be that levels of insight during a dream appreciation session will not differ between REM and NREM dreams, especially if dream report length is controlled. Yet, as Cartwright et al. (1980) did not measure insight as a result of considering dreams, it remains possible that REM and NREM dreams differ in their ability to be a source of insight, even if they do no differ on the outcome measures used by Cartwright et al. (1980).

To summarize, participants reported a high level of Exploration–Insight gains following the dream appreciation group procedure. However, due to the lack of a control condition run as part of a single experiment with the dream appreciation condition, the data reported here are insufficient for determining whether dream content itself is a source of insight. There are theoretical reasons for thinking that the dream group process is more than a supportive social discussion, or placebo, due to its reliance on a dream which has been formed under brain conditions that encourage, according to some theories, an integration of new with old memories and abstraction of waking life experiences into schemata. We hope that future studies may now follow the method here, and also include the assessment of gains from non-dream report control conditions.

Conflict of Interest Statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

References available at the Frontiers site.

Omnivore - The Uncertain Biological Basis of Morality

From Bookforum's Omnivore blog, this is a cool collection of links focused on issues of morality, ethics, and evolution. There is also an excellent article by David Dobbs (from Aeon) dismissing Richard Dawkins "selfish gene" hypothesis [the article was posted on this blog a month or two ago when it came out] in light of the new field of epigenetics. Must read for anyone who is interested in science, biology, and evolution.

The uncertain biological basis of morality
Jan 21 2014
9:00AM

Monday, February 10, 2014

Brain Research through Advancing Innovative Neurotechnologies - The Challenges of Obama's BRAIN Initiative

From Science News, this is an excellent overview of the goals and challenges of Obama's BRAIN Initiative (Brain Research through Advancing Innovative Neurotechnologies). When the project was announce in the spring of 2013, some people compared this to the Manhattan Project, or the Apollo Program, or the Human Genome Project, but the reality is that the human brain operates on a scale that makes all of these major accomplishments seem miniscule.
In a human brain, 85 billion nerve cells communicate via trillions of connections using complex patterns of electrical jolts and more than 100 different chemicals. A pea-sized lump of brain tissue contains more information than the Library of Congress.
Making sense of how the brain works is still beyond our technology - and even with funding to create better technologies, we may still be decades (if not a century) away from fully grokking how the brain creates a sense of self that is coherent over time and still adaptive to change. Our work is certainly cut out for us.

Brain Shot

Neuroscientists scramble to take on ambitious presidential challenge

by Laura Sanders
February 7, 2014
Magazine issue: February 22, 2014


BRAIN POWER  Deciphering how the brain’s circuitry produces thought and behavior is an ambitious and enticing goal on the scale of the Apollo Program or the Human Genome Project. But the neuroscientists involved in a new federal effort have many challenges ahead.

When the president of the United States makes a request, scientists usually listen. Physicists created the atomic bomb for President Roosevelt. NASA engineers put men on the moon for President Kennedy. Biologists presented their first draft of the human genetic catalog to an appreciative President Clinton.

So when President Obama announced an ambitious plan to understand the brain in April 2013, people were quick to view it as the next Manhattan Project, or Human Genome Project, or moon shot.

But these analogies may not be so apt. Compared with understanding the mysterious inner workings of the brain, those other endeavors started with an end in sight.

In a human brain, 85 billion nerve cells communicate via trillions of connections using complex patterns of electrical jolts and more than 100 different chemicals. A pea-sized lump of brain tissue contains more information than the Library of Congress.


A central part of the initiative focuses on the need to improve existing technologies and to develop new ones that probe the brain’s inner workings on smaller and smaller scales. Learn more about those technologies below. View the slideshow Y. Kaneonke et al/PLOS One 2012

But unlike those orderly shelved and cataloged books, the organization of the brain remains mostly indecipherable, concealing the mysteries underlying thought, learning, emotion, and memory.

Still, as with other challenging enterprises prompted by presidential initiatives, success would change the world. A deep understanding of how the brain works, and what goes wrong when it doesn’t, could lead to a dazzling array of treatments for brain disorders — from autism and Alzheimer’s disease to depression and drug addiction — that afflict millions of people around the world.

That’s why President Obama threw his weight behind the BRAIN Initiative, short for Brain Research through Advancing Innovative Neurotechnologies (SN: 5/4/13, p. 22). The premise is simple: Before doctors can fix the brain, scientists must first understand how it works. And to understand how it works, scientists need tools to study it. With $110 million of federal funding in its first year, the BRAIN Initiative is intended to spur scientists to develop new technologies to measure and manipulate the brain. Eventually, if it is to join the list of presidential science successes, the project will catalog all the brain’s parts and processes, explore how cells and molecules create thought and behavior, and build powerful new weapons for neutralizing the pathological enemies of the brain and mind.

Yet even aside from those scientific challenges, which are all huge in their own right, the project faces many major logistical hurdles.

It’s not clear, for instance, how various govern­ment agencies and private institutions involved in the project will coordinate their efforts. Nor is it clear how the BRAIN Initiative will relate to the European Union’s $1.3 billion Human Brain Project. Some scientists say the BRAIN Initiative’s initial funding is too paltry to make real progress and that future funding is a political uncertainty.

Perhaps most unsettling, the BRAIN Initiative has no definitive goal. Unlike mushroom clouds, a collection of moon rocks or the software for a human being, the BRAIN project envisions no tangible result, many scientists say. “It isn’t clear what victory will look like on this project,” says Thomas Insel, director of the National Institute of Mental Health in Bethesda, Md. “I think people have to be comfortable with that.”

Despite these caveats, though, many neuroscientists appreciate that President Obama’s announcement elevated the status of brain research and captured the attention of their community. “When the president says it, people listen up,” says Christof Koch of the Allen Institute for Brain Science in Seattle. “I think that, by itself, is a very important thing. It really shows that neuro­science has come of age.”


Manhattan Project | 1942–1945

Goal: To develop the world’s first nuclear weapon, an atomic bomb, during World War II
Cost: $26 billion*
People involved: >100,000

Apollo Program | 1963–1972

Goal: To land Americans on the moon before 1970
Cost: $134 billion*
People involved: >400,000

Human Genome Project | 1990–2003

Goal: To map out the 3 billion chemical “letters” of DNA in the human genome
Cost: $4.6 billion*
People involved: Thousands

BRAIN Initiative | 2014–?


Goal: To develop new technologies for mapping the human brain’s cells and circuitry; discover the neural and molecular basis of learning, thought and memory; and develop methods of prevention and more effective therapies for brain disorders
Initial cost: $110 million**
People involved: Not yet known

*In 2013 dollars
**Federal funding for 2014
Credit: E. OtwellAmbitious goals

While the BRAIN Initiative’s objectives are hard to express in concrete terms, the project is full of visionary promise. “The ultimate goal is to understand who we are,” says Terry Sejnowski of the Salk Institute for Biological Studies in La Jolla, Calif. “How is it that our brain is able to look out into the world and see things? How is it that we are able to make decisions? How is it that we’re able to coordinate enormous amounts of knowledge?”

The people charged with translating these esoteric goals into concrete action are beginning to define their task more precisely. But there is no consensus on how to proceed. With no central organizing entity, the three government agencies participating — the National Institutes of Health, the Defense Advanced Research Projects Agency and the National Science Foundation—interpret the BRAIN Initiative’s mission in their own ways. So do the private organizations involved, including the Salk Institute, the Allen Institute, the Kavli Foundation and the Howard Hughes Medical Institute’s Janelia Farm campus in Ashburn, Va.

The NIH, which is putting up $40 million in funding for fiscal year 2014, has taken a methodical approach by first appointing a committee of 16 neuroscientists. That group, headed by William Newsome of Stanford University and Cornelia Bargmann of the Rockefeller University in New York, spent the summer of 2013 in four workshops talking with neuroscientists about what ought to be included in the initiative.

In September, the committee released a preliminary report describing nine priorities. They were extremely ambitious. For instance, the NIH panel wants a census of all the different types of brain cells and a description of how nerve cells, or neurons, collectively give rise to behavior. Powerful new technology also features prominently on the wish list. One of the goals calls for developing tools capable of producing anatomical maps of the human brain with unprecedented clarity.

Further priorities include developing techniques that can eavesdrop on many neurons at the same time and allow scientists not just to listen in, but to change how those neurons behave. To make sense of all of this data, the report calls for improved theoretical, statistical and modeling approaches.
Each of these goals on its own could easily take years or even decades to accomplish. For the final report, the goals, milestones and timeline will be sharpened, says Sejnowski, a member of the working group.

Like NIH, DARPA also emphasizes new tools, but with a much more targeted goal in mind for its $50 million investment in 2014: healing soldiers. “We serve a constituency” — the active duty service member — says Geoffrey Ling, deputy director of the Defense Sciences Office. “And the active duty service member right now has got a lot of issues medically.”

Currently, more military members die from suicide than from direct combat injury, says Ling. “And that’s the tip of the iceberg.” DARPA interprets its role in the BRAIN Initiative as alleviating some of the pernicious mental health problems that plague service members.

In October and November, DARPA announced two projects. One, called SUBNETS (for Systems-Based Neurotechnology for Emerging Therapies), seeks new ways to record neural activity from and stimulate the brains of people with post-traumatic stress disorder, anxiety disorder, traumatic brain injury and other diseases. DARPA envisions a device that both diagnoses and treats mental health problems, first by listening for abnormal electrical signals and then correcting them. For success, the project will need engineers to build new medical devices, computational neuroscientists to develop theories about how neurons transmit information and clinicians to test the prototype in people.

The second project, called RAM (for Restoring Active Memory), aims to develop an implantable brain device that will help restore lost memories to soldiers or veterans. Devised by Ling, the project plans to move from idea to device quickly. “Our timeline is four to five years, and we’re not joking,” he says.


Seeking new tools

Achieving such ambitious goals — figuring out how neurons create behavior, curing mental illness and restoring lost memory — is not possible with today’s technology. Even though scientists have made huge leaps in their ability to listen to and manipulate neurons, current methods are still far from where they need to be.

“The tools have to be the focus,” says Sejnowski. “We have to get those tools in place. There’s no way of even getting off the ground until we have those tools.”

NIH’s initial plans reflect that belief. On December 17, the agency released six calls for projects to fund as part of the BRAIN Initiative. Each describes a tool-building plan. “What we’re trying to do is get the tools and infrastructure in place so we can get a much deeper understanding of how the brain works in both health and disease,” Insel says.

Scientists want to monitor the electrical and chemical behavior of many neurons — thousands or even millions — at the same time, while being able to zoom in to see and even manipulate those cells. One of today’s common ways to eavesdrop on neuron behavior relies on electrodes designed decades ago. Neuroscience is still stuck using technology from the 1950s, Insel says, “while the rest of the world has learned how to go wireless and miniaturized.”

Magnetic resonance imaging, or MRI, allows scientists to get good anatomical maps of the whole brain and broad activity patterns (SN: 12/19/09, p. 16). But as good as it is, MRI technology still misses lots of detail. A million neurons can reside in a single voxel, the smallest unit that functional MRI can detect. “MRI shows you wonderful neuroanatomical details, fantastic, but it does have a resolution limit,” Ling says. “How can we increase it? Easy — build a bigger magnet. Oh, good, let’s have a 50 Tesla magnet. What city are you going to put this in? Because you have to wipe out about seven blocks to do it.” Supersizing existing technology won’t work, Ling says. Fundamentally new ideas are needed.


In optogenetics, scientists use light to manipulate brain cells that have been genetically modified to respond to light. While already producing useful findings in animals such as mice, optogenetics would not be practical in people. Inbal Goshen and Karl DeisSeroth.

Radically new approaches will also be needed to enable precise control of neurons’ behavior. One powerful new technique, called optogenetics, lets researchers use light to control certain brain cells in animals. But it’s not feasible in people, because it requires genetic alterations to make neuronsproduce specialized light-sensitive proteins. For now, scientists are forced to rely on less precise methods to change the activity of human neurons.

Psychiatric drugs can alter neuron behavior, for instance, but the results are imprecise, like dousing the entire engine of a car with oil. Every cell in the brain gets dosed, when only a select few actually need the drugs. What’s more, in most cases scientists still don’t understand how psychiatric drugs work.

A different, drug-free approach may work better: newer technology called deep brain stimulation. It serves as a brain pacemaker. By zapping neural highways with electrodes implanted in the brain, deep brain stimulation has shown promise for treating people with Parkinson’s disease and severe depression. And yet, as with psychiatric drugs, the technique is still imprecise and not well understood.

“I think people understand that you’re not going to be able to fix something as complicated as the brain with the current tools. They’re too crude,” Sejnowski says, like “trying to fix a computer with a wrench.”

Instead of more wrenches, scientists need powerful precision tools, some of which are in the works. The Allen Institute, HHMI and others have partnered with a nanoelectronics research center called imec to build tiny but powerful electrodes that can record the behavior of hundreds of neurons with great accuracy. “That’s going to be pretty awesome technology,” Koch says.

Scientists at Janelia Farm are devising intricate ways to illuminate neural behavior in zebrafish, flies and mice. By genetically engineering neurons to produce a protein called GCaMP, the researchers can watch each individual neuron fire off a message. The concept of using proteins to detect neuronal activity isn’t new, but the sensitivity of this latest version is much better than previous attempts, says Gerald Rubin, Janelia Farm’s executive director. It awed many in the field in March 2013 when the Janelia Farm researchers circulated a movie of zebrafish brain activity.

Scientists are also making progress on mapping the connections between neurons. Most attempts rely on powerful microscopy (SN: 6/15/13, p. 20). But there might be a better way, says Anthony Zador of Cold Spring Harbor Laboratory in New York.

Instead of using microscopes, Zador and colleagues are attempting to attack the problem with DNA sequencing, which is cheap and reliable. Their method relies on using genetic tricks to tag neurons with unique chains of DNA. By analyzing how those DNA tags mingle at synapses — the communication connections between neurons — a computer could reconstruct all of the physical connections in a brain. So far, the team has had success only in cells in a dish. If the technique works in animals, figuring out every single synapse in the entire mouse cortex will cost just a few thousand dollars, Zador estimates.


Making the vision real

If the BRAIN Initiative serves as an incubator for the next great brain technology, the payoff would be huge, Newsome says. The ability to record the behavior of tens of thousands of neurons simultaneously, map the connections between those neurons and then manipulate those neurons, all in a fully awake behaving animal, or person, “is not something that neuroscience has ever been able to contemplate in its history,” says Newsome. “It’s kind of a breathtaking vision.”

Success in realizing that vision, though, will mean that neuro­scientists have to face a big shift in how they do their work.

As neurotechnology improves and produces ever more massive piles of complicated data, neuroscientists will need to know more about statistics, engineering and computational biology. To succeed, the BRAIN Initiative will need to bring together experts in all these different fields. It will also need neuroscientists to coordinate their efforts and share their data freely. “We are going to have to reorganize the way people do their research,” Sejnowski says. The same goes for the nongovernmental agencies working on the BRAIN Initiative.

Currently no one agency or person is in charge of the initiative. Such decentralization might make swift progress, without duplication of effort, difficult. Although the three government agencies involved — DARPA, NIH and NSF — have been aware of what the others were doing, they haven’t merged their differing priorities. “We’re all so busy getting these projects launched, I don’t think we’ve had a lot of time to think about how they’re going to be integrated,” Insel says.

The private groups, referred to by the White House as BRAIN Initiative “partners,” set their own course and spend their own money as they see fit. Because the goals of the Allen Institute, the Salk Institute and Janelia Farm align closely with federal goals, these institutes don’t anticipate changing their previously set research agendas.


One organization working with the BRAIN Initiative, the Allen Institute for Brain Science, has been developing an atlas of connections in the mouse brain (top). Scientists at the Howard Hughes Medical Institute’s Janelia Farm campus have been probing the brain of fruit flies (bottom). Courtesy of the Allen Institute for Brain Science; Courtesy of the Simpson lab/Janelia Farm Research Campus

“Partnership is a funny word,” says Janelia Farm’s Rubin. In a sense, Janelia Farm is a partner, he says, because it is putting up a big chunk of money — $30 million annually — toward projects that dovetail with the BRAIN Initiative. Much of that research focuses on how information in the fruit fly brain is stored and processed. “But we’re not a partner in the sense that we’re getting together at a big table with NIH folks and NSF and DARPA and deciding what the goals are and then collectively deciding what we’re doing,” Rubin says.

Likewise, Koch says that the Allen Institute has been working on most of the questions the NIH group came up with. “We are fulfilling already a part of the BRAIN Initiative mission,” he says. Allen Institute scientists have been building detailed maps of the mouse brain, which could help efforts to understand how the human brain works.

Aside from the privately funded research that is already under way, major new BRAIN Initiative research will require new federal money. And so far, the new money has been scant. In 2014, NIH is contributing $40 million to the BRAIN Initiative, less than 1 percent of the $5.7 billion that the agency spends on neuroscience research each year. In 2014, DARPA will spend $50 million on its newly announced projects, and NSF will spend $20 million on relevant projects already in progress.
Although to many scientists, the BRAIN Initiative’s preliminary pot seems small, that money is a down payment, Insel says, meant to get the ball rolling in the hope that Congress will provide more support for the project.

Of course, to help sell the project to politicians who vote on budgets (or as has recently been the case, don’t vote on budgets), scientists need a tagline, a slogan, a simple way to encapsulate the importance of the BRAIN Initiative. So far, there is no such thing.

“We’ve talked and thought about that a lot in the committee,” Newsome says. But the group couldn’t come up with a pithy way to capture the project’s essence. “That question, it’s a real tension. To what extent do we try to depict this as an Apollo-like project or a genome-like project, in which case you have a tagline and a particular deliverable you’re looking for? Or to what extent do you acknowledge that this is a more open-ended kind of project?”

The sell is important, says Zador. In the current economic squeeze, funding must be justified to politicians and the public. If the BRAIN Initiative underdelivers, people will be disappointed.

Instead of a promise to cure brain disease, or unlock the mysteries of memory, emotion and thought, perhaps the brain project is best described as a wedge, says Sean Eddy of Janelia Farm. With its emphasis on sophisticated tools, the project promises to pry open an entirely new realm of neuroscience research, Eddy wrote last April in Current Biology, enabling countless labs around the world to make discoveries in their small corner of the brain.

This vision of the initiative’s success, in which thousands of neuroscientists storm the inhospitable terrain of the brain armed with an awe-inspiring new arsenal of tools, is staggering. Compared with any other project President Obama could have backed, the brain is the most worthy, Eddy says. “This is it.”

If the project flops, scientists will still learn a lot in the attempt. If the project succeeds, the benefits are almost unimaginable. Clinicians might be able to neutralize — or even prevent — devastating disorders such as autism, Alzheimer’s disease and traumatic brain injury. Computers could become ever more powerful by cribbing from the brain’s operating system. Classrooms, military training camps and courtrooms could be optimized to play to the strengths of the human brain and protect it from its weaknesses. These are among the motives that drive neuroscientists, and for all its shortcomings, the BRAIN Initiative has already succeeded in getting people dreaming about what might be possible.

“I can’t tell you where we’re going to be two years from now,” Sejnowski says, “but I can tell you that it’ll be far ahead.”


Priorities for the BRAIN Initiative

In response to President Obama’s call for a major new initiative to understand the brain, the National Institutes of Health organized a committee to articulate a list of priorities. The group identified nine, briefly summarized here:

1. Generate a census of cell types - Characterize all cell types in the nervous system and develop tools to observe and manipulate them.

2. Create structural maps of the brain - Map connected neurons in local and distributed circuits in order to understand the relationship between neuron structure and function. Create tools to reconstruct anatomy of neural circuits at all scales and identify circuit inputs and outputs.

3. Develop new large-scale network recording capabilities - Record neuron activity from complete networks over long time periods in all brain areas with the use of improved existing technologies and entirely new technologies.

4. Develop a suite of tools for circuit manipulation - Activate or inhibit activity in neuronal circuits, using opto­genetic, pharmacological, biochemical and electromagnetic tools.

5. Link neural activity to behavior - Understand the neural basis for cognition and behavior, using technologies that can precisely observe behavior under a broad set of conditions while measuring and manipulating neuron activity.

6. Integrate theory, modeling, statistics and computation with experimentation - Apply theory and statistics to understand complex brain functions where human intuition fails, using new methods for mining, analyzing and interpreting data.

7. Delineate mechanisms underlying human imaging technologies - Improve spatial and time resolution of human brain imaging techniques while developing a better understanding of the cellular mechanisms underlying the signals used to compose images.

8. Create mechanisms to enable collection of human data - Develop high ethical standards for clinical care research while developing methods to maximize the collection of beneficial information from humans undergoing diagnostic brain monitoring or receiving neurotechnology for clinical applications.

9. Disseminate knowledge and training - Accelerate progress by the rapid dissemination of newly developed skills and tools across the scientific and medical communities.


Brain Technology

President Obama’s BRAIN Initiative seeks a comprehensive understanding of how molecular and electrical processes orchestrated by nerve cells produce the brain’s ability to think, learn and control behavior. A central part of the initiative focuses on the need to improve existing technologies and to develop new ones that probe the brain’s inner workings on smaller and smaller scales.

OLD TECH - Two techniques using magnetic resonance imaging, or MRI, have already made progress in mapping the physical connections (fibers of white matter) linking various parts of the brain and in identifying regions that are active during specific tasks.

NEW TECH - Several novel technologies have been developed or proposed to acquire even more detailed data about how the regions and even individual cells of the brain do their jobs.


By infusing a brain with a liquid that eventually hardens into a gel, scientists can see previously hidden structures deep within the brain. Already, CLARITY has been used to see nerve fibers and connections in a mouse brain, and even individual neurons in a human brain that had been preserved in formaldehyde for six years.
[Scroll down to the bottom of the page for a slideshow of brain images - nice stuff.]

Posttraumatic Growth - When Trauma Leads to Transformation


Post-traumatic growth refers to positive psychological change experienced as a result of the struggle with highly challenging life circumstances. These sets of circumstances represent significant challenges to the adaptive resources of the individual and pose significant challenges to individuals' way of understanding the world and their place in it. Posttraumatic growth is not simply a return to baseline from a period of suffering; instead it is an experience of improvement that for some persons is deeply meaningful. [Wikipedia]

This article from Stephen Joseph's Psychology Today blog, What Doesn't Kill Us, offers a brief overview of posttraumatic growth. I have also included a list of books and papers by the original researchers of this phenomenon, Richard Tedeshi and Lawrence Calhoun.

Posttraumatic Growth

The subversion of suffering

Published on February 8, 2014 by Stephen Joseph, Ph.D. in What Doesn't Kill Us

‘Suffering is universal: you attempt to subvert it so that it does not have a destructive, negative effect. You turn it around so that it becomes a creative, positive force.’ Those are the words of Terry Waite who survived four years in solitary confinement, chained, beaten and subject to mock execution.

Interest in how trauma can be a catalyst for positive changes began to take hold during the mid 1990’s when the term posttraumatic growth was introduced by two pioneering scholars Richard Tedeschi and Lawrence Calhoun.

The term posttraumatic growth proved to be popular and has since developed into one of the flagship topics for positive psychology.
In my book What Doesn't Kill Us: The New Psychology of Posttraumatic Growth (2013), I describe how after experiencing a traumatic event, people often report three ways in which their psychological functioning increases:
1. Relationships are enhanced in some way. For example, people describe that they come to value their friends and family more, feel an increased sense of compassion for others and a longing for more intimate relationships.

2. People change their views of themselves in some way. For example, developing in wisdom, personal strength and gratitude, perhaps coupled with a greater acceptance of their vulnerabilities and limitations.

3. People describe changes in their life philosophy. For example, finding a fresh appreciation for each new day and re-evaluating their understanding of what really matters in life, becoming less materialistic and more able to live in the present.
Importantly, and this just can’t be emphasized enough, this does not mean that trauma is not also destructive and distressing. No one welcomes adversity. But the research evidence shows us that over time people can find benefits in their struggle with adversity. Indeed, across a large number of studies of people who have experienced a wide range of negative events, estimates are that between 30 and 70% typically report some form of positive change

We can all use this knowledge to help us cope when adversity does strike, be it bereavement, accident or illness. We can seek to live more wisely in the aftermath of adversity and as the opening quote says, subvert suffering.

To find out more about my book on posttraumatic growth: http://www.profstephenjoseph.com

For even more information on postttraumatic growth, go to the source,
Richard G. Tedeschi, Ph.D., is professor of psychology at UNC Charlotte and a licensed psychologist. He received his B.A. in psychology from Syracuse University, his Ph.D. in clinical psychology from Ohio University, and completed his clinical psychology internship at the UNC School of Medicine. He is consultant to the American Psychological Association on trauma and resilience, and is a fellow of the division of trauma psychology. He is past president of the North Carolina Psychological Association.

Lawrence G. Calhoun, Ph.D., is professor of psychology at UNC Charlotte and a licensed clinical psychologist. Although his parents were North American, he was born and raised in Brazil. He is one of the pioneers in the study of posttraumatic growth and is author of several books. His most recent book, with Richard Tedeschi, is Posttraumatic Growth in Clinical Practice.

Books:

Papers:

Sunday, February 09, 2014

Nepal: In the Mountain’s Shadow (Documentary)


Beautiful and occasionally sad documentary.

Nepal: In the Mountain’s Shadow

Published on Feb 5, 2014


"Nepal, in the Mountains Shadow" is a compelling cultural documentary set in the mystic country of Nepal. Guided by child rights activist and orphanage director Visma Raj Paudel, the film explores the growing social disparity that exists throughout the whole of the country, as he struggles to uncover the truth behind the plight of Nepal's most precious resource--its children. The documentary weaves together beautiful imagery and gripping first hand interviews to create a rare look into modern day Nepal.

Produced by: Maria Alexopoulus
2009 © Alexo Films Production
Distributed by High Banks Entertainment Ltd.

Autogenesis: Life Before Genetics by Terrence Deacon


Terrence Deacon is the author of Incomplete Nature: How Mind Emerged from Matter (2013) and The Symbolic Species: The Co-evolution of Language and the Brain (1998). In the talk below, Deacon explores the "origins of life problem" by attempting to identify the necessary and sufficient molecular relationships required to transform inert chemicals into biological systems. Deacon introduces a model system - autogenesis - that redefines biological information and opens the search for life's origin to cosmic and planetary contexts seldom considered.
I begin with a simple molecular model system consisting of coupled reciprocal catalysis and self-assembly in which one of the catalytic bi-products tends to spontaneously self-assemble into a containing shell (analogous to a viral capsule). I term this dynamical relationship autogenesis because it is self-reconstituting in response to degradation. Self-reconstitution (and reproduction) is made possible by the fact that each of these linked self-organizing processes generates boundary constraints that promote and limit the other, and because this synergy thereby becomes embodied as a persistent rate-independent and substrate-indifferent higher order constraint on component constraint generation processes. It is proposed that this formal synergy is necessary and sufficient to constitute regulation as opposed to mere constraint. Two minor elaborations of this simple model system demonstrate that this simplest form of regulation can be the foundation for the evolution of two higher-order forms: cybernetic and template-based regulation.
You can read a PDF of a PowerPoint presentation at this link - the quote above is taken from the abstract to that presentation.

Life before genetics: autogenesis, and the outer solar system - Terrence Deacon (SETI Talks)

Streamed live on May 14, 2013


SETI Talks archive: http://seti.org/talks
 

The investigation of the origins of life has been hindered by what we think we know about current living organisms. This includes three assumptions about necessary conditions: 1) that it emerged entirely on Earth, 2) that it is dependent on the availability of liquid water, and 3) that it is coextensive with the emergence of molecules able to replicate themselves.

In addition, the three most widely explored alternative general models for a molecular process that could serve as a precursor to life also reflect reductionistically-envisioned fragments of current living systems: e.g. container-first, metabolism-first, or information-first scenarios. Finally, we are hindered by a technical concept of information that is fundamentally incomplete in precisely ways that are critical to characterizing living processes.

These all reflect reductionistic "top-down" approaches to the extent that they begin with a reverse-engineering view of what constitutes a living Earth-organism and explore possible re-compositional scenarios. This is a Frankensteinian enterprise that also begins with assumptions that are highly Earth-life specific and therefore unlikely to lead to a general exo-biology.

The approach Dr. Deacon will outline instead begins from an unstated conundrum about the origins of life. The initial transition to a life-like process necessarily exemplified two almost inconceivably incompatible properties: 1) it must have involved exceedingly simple molecular interactions, and 2) it must have embodied a thermodynamic organization with the unprecedented capacity to locally compensate for spontaneous thermodynamic degradation as well as to stabilize one or more intrinsically self-destroying self-organizing processes.

This talk will explore the origins of life problem by attempting to identify the necessary and sufficient molecular relationships able to embody these two properties. From this perspective Dr. Deacon will develop a model system - autogenesis - that redefines biological information and opens the search for life's origin to cosmic and planetary contexts seldom considered.