A Neural Model of Biased Oscillations in Aplysia Head-Waving Behavior

A long-term bias in the exploratory head-waving behavior of Aplysia can be induced using bright lights as an aversive stimulus: coupling onset of the lights with head movements to one side results in a bias away from that side (Cook & Carew, 1986). This bias has been interpreted as a form of operant conditioning, and has previously been simulated with a neural network model based on associative synaptic facilitation (Raymond, Baxter, Buonomano, & Byrne, 1992). In this article we simulate the head-waving behavior using a recurrent gated dipole, a nonlinear dynamical neural model that has previously been used to explain various data including oscillatory behavior in biological pacemakers. Within the recurrent gated dipole, two channels operate antagonistically to generate oscillations, which drive the side-to-side head waving. The frequency of oscillations depends on transmitter mobilization dynamics, which exhibit both short- and long-term adaptation. We assume that light onset results in a nonspecific increase in arousal to both channels of the dipole. Repeated pairing of arousal increments with activation of one channel (the "reinforced" channel) of the dipole leads to a bias in transmitter dynamics, which causes the oscillation to last a shorter time on the reinforced channel than on the non-reinforced channel. Our model provides a parsimonious explanation of the observed behavior, and it avoids some of the unexpected results obtained with the Raymond et al. model. In addition, our model makes predictions concerning the rate of onset and extinction of the biases, and it suggests new lines of experimentation to test the nature of the head-waving behavior.Office of Naval Research (N00014-92-J-4015, N00014-91-J-4100, N0014-92-J-1309); Air Force Office of Scientific Research (F49620-92-J-0499); A.P. Sloan Foundation (BR-3122

Acceptance and commitment therapy groups for individuals with psychosis: a grounded theory analysis

Theoretical assumptions and emerging research point to possible mechanisms of change in acceptance and commitment therapy (ACT) for psychosis. However, the specific processes by which change occurs remain unclear and under-researched. No current research has explored processes facilitating change in the group format of an ACT intervention for psychosis. Participant perspectives were sought to help elucidate potential mechanisms of change. Nine participants of ACT groups for people with psychosis were interviewed about their experiences of the intervention. Interviews were analysed using methods and techniques informed by grounded theory. A proposed model outlined key mechanisms of awareness, relating differently and reconnecting with life, which led to reductions in distress and behavioural change. Leaning on others highlighted the importance of the group context in supporting change processes. The processes identified, and the mechanisms through which these were achieved, as articulated by participants, were consistent with proposed change processes. Participants also offered additional insights based on experiential accounts. Contributions to theoretical understandings and clinical practice are discussed

Neural Models of Temporally Organized Behaviors: Handwriting Production and Working Memory

Advanced Research Projects Agency (ONR N00014-92-J-4015); Office of Naval Research (N00014-91-J-4100, N00014-92-J-1309

Neural Representations for Sensory-Motor Control, II: Learning a Head-Centered Visuomotor Representation of 3-D Target Position

A neural network model is described for how an invariant head-centered representation of 3-D target position can be autonomously learned by the brain in real time. Once learned, such a target representation may be used to control both eye and limb movements. The target representation is derived from the positions of both eyes in the head, and the locations which the target activates on the retinas of both eyes. A Vector Associative Map, or YAM, learns the many-to-one transformation from multiple combinations of eye-and-retinal position to invariant 3-D target position. Eye position is derived from outflow movement signals to the eye muscles. Two successive stages of opponent processing convert these corollary discharges into a. head-centered representation that closely approximates the azimuth, elevation, and vergence of the eyes' gaze position with respect to a cyclopean origin located between the eyes. YAM learning combines this cyclopean representation of present gaze position with binocular retinal information about target position into an invariant representation of 3-D target position with respect to the head. YAM learning can use a teaching vector that is externally derived from the positions of the eyes when they foveate the target. A YAM can also autonomously discover and learn the invariant representation, without an explicit teacher, by generating internal error signals from environmental fluctuations in which these invariant properties are implicit. YAM error signals are computed by Difference Vectors, or DVs, that are zeroed by the YAM learning process. YAMs may be organized into YAM Cascades for learning and performing both sensory-to-spatial maps and spatial-to-motor maps. These multiple uses clarify why DV-type properties are computed by cells in the parietal, frontal, and motor cortices of many mammals. YAMs are modulated by gating signals that express different aspects of the will-to-act. These signals transform a single invariant representation into movements of different speed (GO signal) and size (GRO signal), and thereby enable YAM controllers to match a planned action sequence to variable environmental conditions.National Science Foundation (IRI-87-16960, IRI-90-24877); Office of Naval Research (N00014-92-J-1309

Cortical Models for Movement Control

Defense Advanced Research Projects Agency and Office of Naval Research (N0014-95-l-0409)

Preparation of calibrated test packages for particle impact noise detection

A standard calibration method for any particle impact noise detection (PIND) test system used to detect loose particles responsible for failures in hybrid circuits was developed along with a procedure for preparing PIND standard test devices. Hybrid packages were seeded with a single gold ball, hermetically sealed, leak tested, and PIND tested. Conclusions are presented

The association of anxiety and mood symptoms in patients with bipolar disorders attending follow-up treatment

Background: Anxiety is common in Bipolar Disorders (BD). It is associated with poorer outcome in BD, for example increased in relapse rate and hospitalization, suicidality, substance abuse and more severe symptoms of mania and depression. Malaysian study regarding anxiety in BD is still lacking. Objective: The aim of this study was to determine prevalence of significant anxiety and its detection rate in psychiatric outpatient clinic. Sociodemographic and clinical characteristics associated with anxiety were also examined. Correlation between anxiety and mood symptoms and the burden of life events within one-year period were measured. Method: This is a cross-sectional study done in psychiatric outpatient clinic in Hospital Universiti Sains Malaysia. Sociodemographic and clinical data were acquired from selected samples and four self-rated scales [Beck Anxiety Inventory (BAI), Beck Depression Inventory (BDI), Young Mania Rating Scale (YMRS) and Social Readjustment Rating Scale (SRRS)] were administered to measure mood symptoms, anxiety symptoms and the burden of life events within the previous one year. Regression and correlation analysis were done to examine relationship between anxiety symptoms and mood symptoms and sociodemographic and clinical data. Results: 20.5% of the total 132 participants had significant level of anxiety. Among these, only 29.3% were detected by clinicians. Anxiety level (BAI) in BD was positively and independently associated with Bipolar II Disorder, number of relapse and BDI score. There was strong positive correlation between BAI and BDI (r = 0.690, p <0.001). There was weak positive correlation between BAI and SRRS (r = 0.194, p =0.026). Conclusion: Anxiety in BD is poorly detected by clinicians and was associated with Bipolar II Disorder, higher frequency of relapse, more severe depression, and more burdens of life event within one-year period. Clinicians need to be sensitive in detecting anxiety in BD. More research is needed in finding effective treatment for anxiety in BD

The experience of social workers who use Thought Field Therapy or Emotional Freedom Technique

This thesis explores social workers\u27 experiences with their use of Thought Field Therapy (TFT) and Emotional Freedom Technique (EFT) with their clients. These techniques, which are also known as tapping, involve tapping one\u27s own fingers in a specific sequence on specific points on the body while tuning into undesired feelings in an effort to eliminate feelings of distress. For this study, I conducted semi-structured interviews with twelve clinical social workers. The study participants had been practicing either EFT or TFT for an average of eight years, with three years being the least amount of time that a participant had been using tapping, and 18 years being the longest amount of time that a clinician had been using it. All of the participants strongly believed that tapping works very well and very quickly. They said that tapping works particularly well for anxiety, trauma and phobias. Some also believed that tapping is effective for treating physical pain. The participants explained that EFT and TFT are effective only when applied to a client\u27s emotional reaction to specific situations. Most of the participants expressed that TFT and EFT are ineffective either when the client is not ready to change or when the therapist lacks skill, rather than when they are applied for specific issues. This study brings attention to tapping so that social workers can stay informed about this technique. Practicing social workers should be aware that other practitioners in the field experience great success with it, so that they can decide to learn about it if they choose

SOVEREIGN: An Autonomous Neural System for Incrementally Learning Planned Action Sequences to Navigate Towards a Rewarded Goal

How do reactive and planned behaviors interact in real time? How are sequences of such behaviors released at appropriate times during autonomous navigation to realize valued goals? Controllers for both animals and mobile robots, or animats, need reactive mechanisms for exploration, and learned plans to reach goal objects once an environment becomes familiar. The SOVEREIGN (Self-Organizing, Vision, Expectation, Recognition, Emotion, Intelligent, Goaloriented Navigation) animat model embodies these capabilities, and is tested in a 3D virtual reality environment. SOVEREIGN includes several interacting subsystems which model complementary properties of cortical What and Where processing streams and which clarify similarities between mechanisms for navigation and arm movement control. As the animat explores an environment, visual inputs are processed by networks that are sensitive to visual form and motion in the What and Where streams, respectively. Position-invariant and sizeinvariant recognition categories are learned by real-time incremental learning in the What stream. Estimates of target position relative to the animat are computed in the Where stream, and can activate approach movements toward the target. Motion cues from animat locomotion can elicit head-orienting movements to bring a new target into view. Approach and orienting movements are alternately performed during animat navigation. Cumulative estimates of each movement are derived from interacting proprioceptive and visual cues. Movement sequences are stored within a motor working memory. Sequences of visual categories are stored in a sensory working memory. These working memories trigger learning of sensory and motor sequence categories, or plans, which together control planned movements. Predictively effective chunk combinations are selectively enhanced via reinforcement learning when the animat is rewarded. Selected planning chunks effect a gradual transition from variable reactive exploratory movements to efficient goal-oriented planned movement sequences. Volitional signals gate interactions between model subsystems and the release of overt behaviors. The model can control different motor sequences under different motivational states and learns more efficient sequences to rewarded goals as exploration proceeds.Riverside Reserach Institute; Defense Advanced Research Projects Agency (N00014-92-J-4015); Air Force Office of Scientific Research (F49620-92-J-0225); National Science Foundation (IRI 90-24877, SBE-0345378); Office of Naval Research (N00014-92-J-1309, N00014-91-J-4100, N00014-01-1-0624, N00014-01-1-0624); Pacific Sierra Research (PSR 91-6075-2