Posts tagged mental health
CU begins counseling online Boulder
Oct 6th
Boulder County to invest $1-million in community health
Sep 27th
Later this year, funding will include additional resources for emergency services as well as community-based transition age youth services, crisis housing services, parent education and life skills services, and job training and employment support.
Boulder County is investing in priority areas identified through a collaborative, community-wide process built on past strategic planning efforts that will support the community’s safety net by preventing greater dislocation and costlier services for community members.
Agencies receiving funding are: Mental Health Partners ($400,000 for mental health and substance abuse services), Sister Carmen Community Center ($200,000 for Community Resource Center Services), City of Boulder Family Resource Schools ($170,000 for Family Resource School Services), Clinica Family Health Services ($35,000 for dental health services), Dental Aid ($35,000 for dental health services), and the Early Childhood Council of Boulder County ($60,000 for quality child care).
This is the second round of funding provided by the Boulder County Temporary Safety Net tax initiative, or Ballot Initiative 1A, that was passed in last November’s election. The five-year property tax back fills deficiencies in state funding for county human services programs and supports contracts with nonprofit agencies maintaining a safety net for families and children in Boulder County.
“We are fortunate to have the support of the community to deal with the significant impacts of the economic downturn,” said Frank Alexander, Director of Boulder County’s Department of Housing and Human Services. “Only by funding critical services that have suffered serious cuts and simultaneously addressing these critical safety net gaps that prevent greater family crises can we deal with the increased need in community programs with very limited funding.”
Just as human services agencies throughout Boulder County are experiencing tremendous growth in caseloads and increased demand for services, state and federal funding sources have been declining significantly. The funding ensures these critical services continue and that community members are served.
The first round of funding – $503,000 deployed in February – has increased the availability of supported child care, provided support to local nonprofit organizations that provide family and individual crisis services, supported child welfare, child protection and early intervention practices, and has ensured timely access to food assistance, medical care, and essential benefits.
“As human service agencies throughout Boulder County have been stressed to meet the demands of our community during this economic downturn, the Temporary Human Services funds have been essential in our efforts to support families and prevent the need for costlier, future interventions,” County Commissioner Cindy Domenico said.
CU RESEARCHERS DEVELOP NEW SOFTWARE TO ADVANCE BRAIN IMAGE RESEARCH
Jun 26th
A University of Colorado Boulder research team has developed a new software program allowing neuroscientists to produce single brain images pulled from hundreds of individual studies, trimming weeks and even months from what can be a tedious, time-consuming research process.
The development of noninvasive neuroimaging techniques such as functional magnetic resonance imaging, or fMRI, spurred a huge amount of scientific research and led to substantial advances in the understanding of the human brain and cognitive function. However, instead of having too little data, researchers are besieged with too much, according to Tal Yarkoni, a postdoctoral fellow in CU-Boulder’s psychology and neuroscience department.
The new software developed by Yarkoni and his colleagues can be programmed to comb scientific literature for published articles relevant to a particular topic, and then to extract all of the brain scan images from those articles. Using a statistical process called “meta-analysis,” researchers are then able to produce a consensus “brain activation image” reflecting hundreds of studies at a time.
“Because the new approach is entirely automated, it can analyze hundreds of different experimental tasks or mental states nearly instantaneously instead of requiring researchers to spend weeks or months conducting just one analysis,” said Yarkoni.
Yarkoni is the lead author on a paper introducing the new approach to analyzing brain imaging data that appears in the June 26 edition of the journal Nature Methods. Russell Poldrack of the University of Texas at Austin, Thomas Nichols of the University of Warwick in England, David Van Essen of Washington University in St. Louis and Tor Wager of CU-Boulder contributed to the paper.
Brain scanning techniques such as fMRI have revolutionized scientists’ understanding of the human mind by allowing researchers to peer deep into people’s brains as they engage in mental activities as diverse as reciting numbers, making financial decisions or simply daydreaming. But interpreting the results of brain imaging studies is often more difficult, according to Yarkoni.
“There’s often the perception that what we’re doing when we scan someone’s brain is literally seeing their thoughts and feelings in action, but it’s actually much more complicated,” Yarkoni said. “The colorful images we see are really just estimates, because each study gives us a somewhat different picture. It’s only by combining the results of many different studies that we get a really clear picture of what’s going on.”
The ability to look at many different mental states simultaneously allows researchers to ask interesting new questions. For instance, researchers can pick out a specific brain region they’re interested in and determine which mental states are most likely to produce activation in that region, he said. Or they can calculate how likely a person is to be performing a particular task given their pattern of brain activity.
In their study, the research team was able to distinguish people who were experiencing physical pain during brain scanning from people who were performing a difficult memory task or viewing emotional pictures with nearly 80 percent accuracy. The team expects performance levels to improve as their software develops, and believes their tools will improve researchers’ ability to decode mental states from brain activity.
“We don’t expect to be able to tell what people are thinking or feeling at a very detailed level,” Yarkoni said. “But we think we’ll be able to distinguish relatively broad mental states from one another. And we’re hopeful that might even eventually extend to mental health disorders, so that these tools will be useful for clinical diagnosis.”